METHOD FOR DIAGNOSIS AND/OR PROGNOSIS OF LIVER DISEASE PROGRESSION AND RISK OF HEPATOCELLULAR CARCINOMA AND DISCOVERY OF THERAPEUTIC COMPOUNDS AND TARGETS TO TREAT LIVER DISEASE AND CANCER

Abstract
The present invention relates to diagnosis and/or prognosis of liver disease progression and risk of hepatocellular carcinoma and the discovery of therapeutic compounds and targets to treat liver disease and cancer.
Description
FIELD OF THE INVENTION

The present invention relates to diagnosis and/or prognosis of liver disease progression and risk of hepatocellular carcinoma and the discovery of therapeutic compounds and targets to treat liver disease and cancer.


BACKGROUND OF THE INVENTION

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver with rising incidence[1]. HCC usually arises in advanced liver disease of viral and metabolic origin. Chronic hepatitis C (CHC) is a major cause of HCC. The HCC risk still remains elevated post-cure especially in patients with advanced fibrosis [2]. Non-alcoholic steatohepatitis (NASH) patients are also at high risk of developing HCC. Given the change in lifestyle with increasing obesity and diabetes, NASH will replace viral hepatitis as major cause for HCC [3]. Liver fibrosis is the key risk factor of HCC and HCC almost arises in advanced liver fibrosis [4]. There are no approved therapeutic strategies to treat liver fibrosis and prevent liver disease progression to HCC [4]. Due to the high HCC mortality and unsatisfactory treatment options, the development of strategies to treat liver fibrosis and prevent liver disease progression to HCC is a key unmet medical need[4].


Epigenetic regulation is a major determinant of gene expression. Alteration of the epigenetic program plays a key role for pathogenesis of human disease and cancer[5]. Several studies have investigated the role of epigenetics in HCC, however the role of epigenome modifications for liver disease progression and hepatocarcinogenesis is only recently emerging. The inventors and others have recently demonstrated that CHC results in genome-wide epigenetic modifications, which are associated with HCC risk and persist post cure with DAA[6, 7].


The reversibility of epigenetic changes offers a therapeutic perspective to counteract the associated transcriptional changes and their functional consequences for disease biology. Small molecule inhibitors targeting chromatin modifiers or readers are currently explored as therapeutic approaches with a particular focus on cancer[8, 9].


Thus, there is a pressing need of new therapy to treat liver disease and prevent liver disease progression and the development of hepatocellular carcinoma. To identify patients at risk for liver disease progression and HCC, it is important to identify epigenetic and transcriptional changes associated with HCC in CHC and NASH patient and assess their impact as biomarker for surveillance and treatment approaches. The identification of pathways associated with liver disease progression and hepatocarcinogenesis provides opportunities to treat advanced liver disease and prevent HCC.


SUMMARY OF THE INVENTION

The present invention features, at least in part, a method of diagnosis and/or prognosis of liver disease progression and risk of hepatocellular carcinoma in a subject comprising detection of an epigenetic or transcriptomic change in subjects with liver disease, the method comprising comparing the level of expression of a marker or a plurality of markers in a subject sample; and the level of expression of the marker or plurality of markers in a control sample, wherein the marker or plurality of markers are selected from the group consisting of the markers listed in table S3 and a significant difference between the level of expression of the marker or plurality of markers in the subject sample and the control sample is an indication that the subject is at risk for progression of liver disease and developing a hepatocellular carcinoma. In one embodiment, the subject is at risk for progression of liver disease, death and developing a hepatocellular carcinoma and the liver disease is a non-alcoholic or alcoholic steatohepatitis or chronic hepatitis A, B, C, D, E-related liver disease or liver fibrosis. In another embodiment, the liver disease is a non-alcoholic or alcoholic steatohepatitis or chronic hepatitis B or C-related liver disease or liver fibrosis. In another embodiment, the subject is a direct-acting antivirals-cured patient or a patient cured of viral infection by any treatment.


In one embodiment the marker or plurality of markers have increased expression relative to a control. In another embodiment the marker or plurality of markers have decreased expression relative to a control. In another embodiment, at least one marker has increased expression and at least one marker has decreased expression relative to a control. The marker can be detected in liver tissue, the serum or plasma or urine or any other body part.


In one embodiment, the subject has undergone tumor resection and in another embodiment the subject sample is obtained from non-tumorous liver tissue or tissue surrounding a resected tumor. In another embodiment, the patient has undergone liver biopsy of fine needle aspiration or obtained a blood test. In yet another embodiment the subject sample is selected from the group consisting of fresh tissue, fresh frozen tissue, fixed embedded tissue or subject-derived spheroids. In still another embodiment, the subject-derived spheroids were generated from fresh liver tissue and cultured in spheroid culture medium. In another embodiment, the subject sample is serum or plasma or urine.


The present invention also features a method of diagnosis and/or prognosis of liver disease progression, survival or risk hepatocellular carcinoma in a subject comprising detecting a biomarker selected from the list of 1693 genes displayed in Table S3.


The present invention also features a method of diagnosis and/or prognosis of liver disease progression, survival or risk hepatocellular carcinoma in a subject comprising detecting a biomarker selected from GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, TMED3, GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR, HPX, RARRES2, ACADSB, CFHR5, DCXR, and GALK1 genes.


The present invention further features a method of assessing the efficacy of a liver disease and hepatocellular carcinoma prevention and treatment approach in a subject with liver disease, the method comprising comparing the level of expression of a marker or a plurality of markers in a subject sample; and the level of expression of the marker or plurality of markers in a second subject sample following the treatment with the therapy, wherein the marker or plurality of markers are selected from the group consisting of the markers listed in Table S3, and a significant difference between the level of expression of the marker or plurality of markers indicates the efficacy of the liver disease or hepatocellular carcinoma prevention therapy.


The present invention further features a method of identifying an agent or compound for use in treatment of viral and metabolic liver disease and chemoprevention or treatment of metabolic and viral hepatocellular carcinoma, said method comprising the steps of providing a sample, contacting the sample with a candidate compound; and detecting an increase or decrease in expression of a marker or a plurality of markers selected from the group consisting of the markers in Table S3, relative to a control, wherein an agent or compound that increases or decreases the expression of said marker or plurality of markers relative to the control is an agent or compound for use in treatment of liver disease or chemoprevention or treatment of metabolic and viral hepatocellular carcinoma. In one embodiment the sample is a subject-derived HCC or adjacent liver tissues or a cancer cell line. In another embodiment the liver cancer cell line is selected from the group consisting of the Huh6, Huh7, Huh7.5.1, Hep3B.1-7, HepG2, SkHep1, C3A, PLC/PRF/5 and SNU-398 cell lines or optionally a combination with another cell line such as LX2 cells, THP1 cells or another cell line or primary cells such as human Kupffer cells or human myofibroblasts or liver sinusoidal endothelial cells.


The sample to be assessed can be any sample that contains a gene expression product. Suitable sources of gene expression products, i.e., samples, can include cells, lysed cells, cellular material for determining gene expression, or material containing gene expression products. Examples of such samples are blood, plasma, lymph, urine, tissue, mucus, sputum, saliva or other cell samples. Methods of obtaining such samples are known in the art. In one embodiment, the sample is derived from an individual who has been clinically diagnosed as having or at risk of developing a hepatic disorder (e.g., liver disease due to any origin/etiology or hepatocellular carcinoma and/or liver fibrosis and cirrhosis). As used herein “obtaining” means acquiring a sample, either by directly procuring a sample from a subject or a sample (tissue biopsy, serum, plasma, primary cell, cultured cells), or by receiving the sample from one or more people who procured the sample from the subject or sample.


Furthermore, the present invention features a screening method for identifying an agent for prevention and treatment of liver disease and hepatocellular carcinoma said method comprising steps of (i) generating different cellular models for liver disease and hepatocellular carcinoma development using the exposure of hepatocyte-like or hepatoma cells to different liver disease injury or hepatocarcinogenic agent, said cellular models exhibiting a Prognostic Epigenetic Signature (PES) poor prognosis—HCC high-risk gene signature, (ii) selection of a candidate compound, (iii) determining the effect of the candidate compound on the PES poor prognosis-high-risk gene signature, (iv) identifying the candidate compound as an agent useful for the treatment and prevention of liver disease and HCC if the candidate compound transforms the PES high-risk gene/poor prognosis signature of the liver cells to a PES HCC low-risk/good prognosis signature in a cellular model system modeling liver injury by hepatocarcinogenic agents. In a first specific embodiment the high-risk gene signature is the poor prognosis/HCC high-risk 1693-gene signature presented in Table S3 or the 25 gene subset thereof presented in Table S4, and wherein the candidate compound is identified as an agent useful for the prevention and treatment of liver disease and HCC if the candidate compound suppresses the expression of the 10 HCC high-risk/poor prognosis genes, or of a subset thereof and/or induces the expression of the 15 HCC low-risk genes/good prognosis genes, or of a subset thereof. In a second specific embodiment the exposure of hepatocyte-like or hepatoma cells to different hepatocarcinogenic agents comprises exposure to the free fatty acids modeling metabolic liver disease such as non-alcoholic liver disease (NASH) and NASH associated fibrosis. In a specific embodiment, the hepatocyte-like cells are co cultured with non-parenchymal liver cells. In a third embodiment, the compound is pre-selected by in vitro, in silico or cell culture drug screening.


The present invention features, in another part, a compound transforming a PES HCC high-risk gene/poor prognosis signature of the liver cells to a PES HCC low-risk/good prognosis signature in a cellular model for liver disease progression and HCC risk for use in the treatment or prevention of liver disease and hepatocellular carcinoma. In a specific embodiment, the PES signature is the 25-gene signature presented in Table S4, and wherein the candidate compound is identified as an agent useful in the treatment or prevention of liver disease and hepatocellular carcinoma if the candidate compound suppresses the expression of the high-risk/poor prognosis genes, or of a subset thereof and/or induces the expression of the low-risk/good prognosis genes, or of a subset thereof. In another specific embodiment the chromatin modifier, regulator or reader-targeting compound is selected from the group consisting of BRD4 inhibitors, BRPF1B inhibitors, G9a/GLP inhibitors, PCAF/GCN5 inhibitors, LSD1 inhibitors, SPIN1 inhibitors, CREBBP/EP300 inhibitors, SMYD2 inhibitors, PRDM9 inhibitors, SMARCA2/4 inhibitors, EZH2 inhibitors, BAZ2A/2B inhibitors, SUV420H1/H2 inhibitors, CECR2/BPTF inhibitors, L3MBTL3 inhibitors, ATAD2A/B inhibitors and PRMT4/6 inhibitors.


The present invention features, in another part, a chromatin modifier, regulator or reader inhibitor or compound targeting epigenetic gene expression regulation for use in the treatment or prevention of liver disease and hepatocellular carcinoma in a subject in need thereof. In a specific embodiment, the subject has a liver disease, comprising chronic hepatitis due to viral infection or metabolic causes such as non-alcoholic steatohepatitis or alcoholic liver disease.


DETAILED DESCRIPTION OF THE INVENTION
Definitions

As used herein, each of the following terms has the meaning associated with it in this section.


The articles “a” and “an” are used herein to refer to one or to more than one (i.e., to at least one) of the grammatical object of the article. By way of example, “an element” means one element or more than one element.


The term “liver disease” and/or a related phrase refers to conditions related to the liver, such as alcoholic cirrhosis, alpha-1 antitypsin deficiency, autoimmune cirrhosis, cryptogenic cirrhosis, fulminant hepatitis, hepatitis A, B, C, D and E, and non-alcoholic and alcoholic steatohepatitis, biliary tract disorders, cystic fibrosis, primary biliary cirrhosis, sclerosing cholangitis, biliary obstruction, and cancer (e.g., hepatic carcinoma). Other well-known disease can be found in the prior art, e.g., Wiesner, R. H, Current Indications, Contra Indications and Timing for Liver Transplantation (1996), in Transplantation of the Liver, Saunders (publ.); Busuttil, R. W. and Klintmalm, G. B. (eds.) Chapter 6; Klein, A. W., (1998) Partial Hypertension: The Role of Liver Transplantation, Musby (publ.) in Current Surgical Therapy β.sup.th Ed. Cameron, J. (ed) for more specific disclosure relating to relevant hepatic disorders.


The terms “tumor” or “cancer” refer to the presence of cells possessing characteristics typical of cancer-causing cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological features. Cancer cells are often in the form of a tumor, but such cells may exist alone within an animal, or may be a non-tumorigenic cancer cell, such as a leukemia cell.


The term “hepatocellular cancer” as used herein, is meant to include primary malignancies of the liver.


The terms “hepatocellular carcinoma” and “HCC” are used herein interchangeably. They refer to the most common type of liver cancer, also called malignant hepatoma. HCC can be secondary to infection with hepatitis C virus (HCV), or secondary to hepatitis B virus (HBV) or hepatitis D virus infection, alcoholic liver disease, non-alcoholic fatty liver disease, hereditary hemochromatosis, alpha 1-antitrypsin deficiency, autoimmune hepatitis, some porphyrias, Wilson's disease, aflatoxin exposure, type 2 diabetes, obesity or other etiologies.


As used herein, a “marker” or “biomarker” is a gene or protein which may be altered, wherein said alteration is associated with a disorder of the liver or a subset thereof. The alteration may be in amount, structure, and/or activity in a tissue or cell having a or modelling a hepatic disorder, as compared to its amount, structure, and/or activity, in a normal or healthy tissue or cell (e.g., a control), and is associated with a disease state, such as cancer and/or cirrhosis. For example, a marker of the invention which is associated with liver disease progression or cancer may have altered copy number, expression level, protein level, protein activity, or methylation status, in a cancer/liver tissue or cancer/liver cell as compared to a normal, healthy tissue or cell. Furthermore, a “marker” includes a molecule whose structure is altered, e.g., mutated (contains an allelic variant), e.g., differs from the wild type sequence at the nucleotide or amino acid level, e.g., by substitution, deletion, or addition, when present in a tissue or cell associated with a disease state, such as cancer. Markers identified herein include diagnostic and therapeutic markers. A single marker may be a diagnostic marker, a therapeutic marker, or both a diagnostic and therapeutic marker.


As used herein, the term “therapeutic marker” includes markers, e.g., markers set forth in the Tables, Figures, or Sequence Listing described herein, which are believed to be involved in the development (including maintenance, progression, angiogenesis, and/or metastasis) of hepatic diseases.


The amount of a marker, e.g., expression or copy number of a marker, or protein level of a marker, in a subject or sample is “significantly” higher or lower than that of a control, if the amount of the marker is greater or less, respectively, than the normal level by an amount greater than the standard error of the assay employed to assess amount, and preferably at least twice, and more preferably three, four, five, ten or more times that amount. Alternately, the amount of the marker in the subject or sample can be considered “significantly” higher or lower than that of a control if the amount is at least about two, and preferably at least about three, four, or five times, higher or lower, respectively, than the normal amount of the marker.


An “overexpression” or “increased expression” of a marker refers to an expression level or copy number in a test sample that is greater than the standard error of the assay employed to assess expression or copy number, and is preferably at least twice, and more preferably three, four, five or ten or more times the expression level or copy number of the marker in a control sample (e.g., sample from a healthy subject not afflicted with cancer), or preferably, the average expression level or copy number of the marker in several control samples.


An “underexpression” or “decreased expression” of a marker refers to an expression level or copy number in a test sample that is lower than the standard error of the assay employed to assess expression or copy number, but is preferably at least twice, and more preferably three, four, five or ten or more times less than the expression level or copy number of the marker in a control sample (e.g., sample from a healthy subject not afflicted with cancer) or, preferably, than the average expression level or copy number of the marker in several control samples.


As used herein, the term “chemoprevention” is the use of drugs or other natural or synthetic agents, which may be biologic or chemical, to try to reduce the risk of, prevent, suppress, reverse, or delay the development, or recurrence of, premalignant lesions and/or cancer more specifically a hepatocellular cancer. It also includes the treatment of a condition such as advanced liver disease or liver fibrosis, predisposing the patient at risk to develop HCC.


A “marker nucleic acid” is a nucleic acid (e.g., DNA, mRNA, cDNA, microRNA) encoded by or corresponding to a marker of the invention. For example, such marker nucleic acid molecules include DNA (e.g., cDNA) comprising the entire or a partial sequence of any of the nucleic acid sequences encoding markers set forth in the Tables, Figures, or Sequence Listing described herein or the complement or hybridizing fragment of such a sequence. The marker nucleic acid molecules also include RNA comprising the entire or a partial sequence of any of the nucleic acid sequences encoding markers set forth in the Tables, Figures, or Sequence Listing or the complement of such a sequence, wherein all thymidine residues are replaced with uridine residues.


As used herein, the terms “cells” refers to cells in various forms, including but not limited to cells retained in tissues, cell clusters, and individually isolated cells. The term “isolated”, when used herein to characterize cells, means cells which, by virtue of their origin or manipulation, are separated from at least some of the components with which they are naturally associated or with which they are associated when initially obtained or prepared. In the context of the invention, liver cancer cells are used to prepare the cellular model system of HCC development and progression. The term “liver cancer cells” refers to cells that have been isolated from a liver tumor or liver cancer sample (e.g., a biopsy sample) or to cells from a liver tumor-derived cell line or from a liver cancer-derived cell line.


As used herein, the term “non-parenchymal cell” refers to any cell that is not a parenchymal cell. In the liver, non-parenchymal cells produce key paracrine factors that influence growth, metabolism, and transport functions in hepatocytes. Nonparenchymal liver cells include Kupffer cells, stellate cells, liver resident macrophages, liver myofibroblasts, fibroblasts, sinusoidal endothelial cells, immune cells (T, B, NK cells and the like), intrahepatic lymphocytes, and biliary cells as well as cell lines modelling non-parenchymal liver cells.


As used herein, the term “gene” refers to a polynucleotide that encodes a discrete macromolecular product, be it a RNA or a protein, and may include regulatory sequences preceding (5′ non-coding sequences) and following (3′ non-coding sequences) the coding sequence. As more than one polynucleotide may encode a discrete product, the term “gene” also includes alleles and polymorphisms of a gene that encode the same product, or a functionally associated (including gain, loss or modulation of function) analog thereof.


The term “gene expression” refers to the process by which RNA and proteins are made from the instructions encoded in genes. Gene expression includes transcription and/or translation of nucleic acid material. The terms “gene expression pattern” and “gene expression profile” are used herein interchangeably. They refer to the expression (i.e., to the level or amount or copy number) of an individual gene or of a set of genes. A gene expression pattern may include information regarding the presence of target transcripts in a sample, and the relative or absolute abundance levels of target transcripts.


As used herein, the term “subject” refers to a human or another mammal (e.g., primate, dog, cat, goat, horse, pig, mouse, rat, rabbit, and the like), that can develop hepatocellular carcinoma, but may or may not be suffering from the disease. Non-human subjects may be transgenic or otherwise modified animals. In many embodiments of the present invention, the subject is a human being. In such embodiments, the subject is often referred to as an “individual” or a “patient” The term “individual” does not denote a particular age, and thus encompasses newborns, children, teenagers, and adults. The term “patient” more specifically refers to an individual suffering from a disease. In the practice of the present invention, a patient will generally be diagnosed with a liver disease.


The term “candidate compound” refers to any naturally occurring or non-naturally occurring molecule, such as a biological macromolecule (e.g., nucleic acid, polypeptide or protein), organic or inorganic molecule, or an extract made from biological materials such as bacteria, plants, fungi, or animal (particularly mammalian, including human) cells or tissues to be tested for an activity of interest. More specifically these candidate compounds are chromatin modifier or chromatin reader inhibitor. In the screening methods of the invention, candidate compounds are evaluated for their ability to modulate the expression of genes of a Prognostic Epigenetic Signature (PES).


The term “small molecule”, as used herein, refers to any natural or synthetic organic or inorganic compound or factor with a low molecular weight. Preferred small molecules have molecular weights of more than 50 Daltons and less than 2,500 Daltons. More preferably, small molecules have molecular weights of less than 600-700 Daltons. Even more preferably, small molecules have molecular weights of less than 350 Daltons.


A “pharmaceutical composition” is defined herein as comprising an effective amount of an agent that has been identified by a method of screening of the invention to be useful in the treatment or prevention of cirrhosis/HCC, and at least one pharmaceutically acceptable carrier or excipient.


As used herein, the term “effective amount” refers to any amount of a compound, agent, or composition that is sufficient to fulfil its intended purpose(s), e.g., a desired biological or medicinal response in a cell, tissue, system or subject. For example, in certain embodiments of the present invention, the purpose(s) may be: to prevent the onset of hepatocellular carcinoma, to slow down, alleviate or stop the progression, aggravation or deterioration of the symptoms of liver disease or hepatocellular carcinoma; to bring about amelioration of the symptoms of the disease, or to prevent and cure the disease or hepatocellular carcinoma.


The term “pharmaceutically acceptable carrier or excipient” refers to a carrier medium which does not interfere with the effectiveness of the biological activity of the active ingredient(s) and which is not significantly toxic to the host at the concentration at which it is administered. The term includes solvents, dispersion, media, coatings, antibacterial and antifungal agents, isotonic agents, and adsorption delaying agents, and the like. The use of such media and agents for pharmaceutically active substances is well known in the art (see for example “Remington's Pharmaceutical Sciences”, E. W. Martin, 18th Ed., 1990, Mack Publishing Co.: Easton, PA, which is incorporated herein by reference in its entirety).


The terms “approximately” and “about”, as used in reference to a number, generally include numbers that fall within a range of 10% in either direction of the number (greater than or less than the number) unless otherwise stated or otherwise evident from the context (except where such number would exceed 100% of a possible value).


In eukaryotic cells, DNA is packaged along with histone proteins in a nucleoprotein complex referred to as chromatin. The minimal repeating units of chromatin are the nucleosomes, which enable the folding of chromatin into fibers and higher order structures. Gene regulation on the chromatin level (“epigenetics”) is achieved by nature through dynamic chemical modifications of both DNA and histones and associated proteins or molecules, mediated by specialized “chromatin writer” and “chromatin eraser” or “chromatin regulator” enzymes, collectively referred to as “chromatin modifiers”, “chromatin reader” or “chromatin regulators”.


As used herein, the term “chromatin reader inhibitor” or “chromatin modifier inhibitor” or “chromatin regulator” refers to a chemical compound which modulate the Chromatin reader, modifier or regulator enzyme or associated proteins/molecules by inhibition or enhancement of its function.


The term “Prognostic Gene Signature”, as used herein, refers to molecular biomarkers, gene expression or any other means for identification or prediction of liver disease as fibrosis, cirrhosis progression and/or HCC development that comprises a 1693-gene signature referred as the “Extended Prognostic Epigenetic Signature” (Extended PES or PES Extended), and a subset composed of a 25-gene stromal liver signature predictive of liver disease as HCC development, cirrhosis progression and liver-specific and overall death previously developed by the present inventors. Table S3 provides the identity of the 1693 genes of the signature (PES Extended) and Table S4, which is presented in the Examples section below, provides the identity of the 25 genes of the signature (PES).


As used herein, the term “high-risk genes” refers to genes of the signature whose overexpression correlates with high risk of future liver disease and fibrosis progression, HCC development, and poorer liver-specific and overall survival, and the term “low-risk genes” refers to genes whose overexpression correlates with absence or low risk of future HCC development or liver disease progression and good survival.


The term “liver cells exhibiting a poor prognosis status or HCC high-risk gene signature”, as used herein to characterize liver cells of a cellular model for liver disease as fibrosis, cirrhosis or HCC development and progression according to the invention, refers to cells in which the high-risk genes, or a subset thereof, are overexpressed, and in which the low-risk genes, or a subset thereof, are underexpressed. In contrast, the term “liver cells exhibiting a good prognosis status or HCC low-risk gene signature”, as used herein to characterize liver cells (for example hepatocyte-like cells obtained by differentiation according to the invention), refers to cells in which the poor prognosis or HCC high-risk genes of Table S3, or a subset thereof as disclosed in Table S4, are underexpressed or unchanged and in which the PES good prognosis or HCC low-risk genes of Table S4, or a subset thereof, are overexpressed or unchanged.


The present invention pertains to the field of predictive medicine in which diagnostic assays, prognostic assays, pharmacogenomics, and monitoring clinical trials are used for prognostic (predictive) purposes to thereby treat an individual prophylactically. Accordingly, one aspect of the present invention relates to diagnostic assays for determining the amount, structure, and/or activity of polypeptides or nucleic acids corresponding to one or more markers of the invention, in order to determine whether an individual, eventually with liver disease, is at risk of developing a liver cancer. Such assays can be used for prognostic or predictive purposes to thereby prophylactically treat an individual prior to the onset of a cancer.


Yet another aspect of the invention pertains to monitoring the influence of agents (e. g., drugs or other compounds), administered either to prevent a liver cancer, on the amount, structure, and/or activity of a marker of the invention in clinical trials.


Methods of evaluating the copy number of a particular marker or chromosomal region are well known to those of skill in the art. The presence or absence of chromosomal gain or loss can be evaluated simply by a determination of copy number of the regions or markers identified herein.


Methods for evaluating copy number of encoding nucleic acid in a sample include, but are not limited to, hybridization-based assays. For example, one method for evaluating the copy number of encoding nucleic acid in a sample involves a Southern Blot. In a Southern Blot, the genomic DNA (typically fragmented and separated on an electrophoretic gel) is hybridized to a probe specific for the target region. Comparison of the intensity of the hybridization signal from the probe for the target region with control probe signal from analysis of normal genomic DNA (e.g., a non-amplified portion of the same or related cell, tissue, organ, etc.) provides an estimate of the relative copy number of the target nucleic acid. Alternatively, a Northern blot may be utilized for evaluating the copy number of encoding nucleic acid in a sample. In a Northern blot, mRNA is hybridized to a probe specific for the target region. Comparison of the intensity of the hybridization signal from the probe for the target region with control probe signal from analysis of normal mRNA (e.g., a non-amplified portion of the same or related cell, tissue, organ, etc.) provides an estimate of the relative copy number of the target nucleic acid.


In still another embodiment, amplification-based assays can be used to measure copy number. In such amplification-based assays, the nucleic acid sequences act as a template in an amplification reaction (e.g., Polymerase Chain Reaction (PCR). In a quantitative amplification, the amount of amplification product will be proportional to the amount of template in the original sample. Comparison to appropriate controls, e.g. healthy tissue, provides a measure of the copy number.


In a particular embodiment, the level of mRNA corresponding to the marker can be determined both by in situ and by in vitro formats in a biological sample using methods known in the art. The term “biological sample” is intended to include tissues, cells, biological fluids and isolates thereof, isolated from a subject, as well as tissues, cells and fluids present within a subject. Many expression detection methods use isolated RNA. For in vitro methods, any RNA isolation technique that does not select against the isolation of mRNA can be utilized for the purification of RNA from cells (see, e.g., Ausubel et al, ed., Current Protocols in Molecular Biology, John Wiley & Sons, New York 1987-1999). Additionally, large numbers of tissue samples can readily be processed using techniques well known to those of skill in the art, such as, for example, the single-step RNA isolation process of Chomczynski (1989, U.S. Pat. No. 4,843,155).


In another embodiment mRNA expression is measured using a nCounter Nanostring assay.


The activity or level of a marker protein can also be detected and/or quantified by detecting or quantifying the expressed polypeptide. The polypeptide can be detected and quantified by any of a number of means well known to those of skill in the art. These may include analytic biochemical methods such as electrophoresis, capillary electrophoresis, high performance liquid chromatography (HPLC), thin layer chromatography (TLC), hyperdiffusion chromatography, and the like, or various immunological methods such as fluid or gel precipitin reactions, immunodiffusion (single or double), immunoelectrophoresis, radioimmunoassay (RIA), enzyme-linked immunosorbent assays (ELISAs), immunofluorescent assays, Western blotting, and the like. A skilled artisan can readily adapt known protein/antibody detection methods for use in determining whether cells express a marker of the present invention.


Marker and Plurality of Markers


The marker for use in the methods, kits and use according to the invention is preferably a gene selected from the group consisting of the genes listed in Table S3.


The marker may be a HCC high-risk gene (also called poor prognosis gene) or a HCC low-risk gene (also called good prognosis gene).


The HCC high-risk gene is preferably selected from the group consisting of GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, and TMED3.


A HCC low-risk gene is preferably selected from the group consisting of GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR, HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1.


The marker is preferably a HCC high-risk gene as defined above or a HCC low-risk gene.


When a plurality of markers is used, the markers of said plurality of markers are as defined above.


The plurality of markers as defined above may comprise at least 10 genes, preferably at least 15 genes, more preferably at least 20 genes, still more preferably at least 25 genes and/or at most 180 genes, preferably at most 150 genes, more preferably at most 100 genes, still more preferably at most 50 genes.


The plurality of markers as defined above preferably comprises at least one gene, preferably at least 4 genes, more preferably at least 8 genes, selected from the group consisting GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, TMED3, GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR, HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1.


In another preferred embodiment, the plurality of markers as defined above comprises GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, TMED3, GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR, HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1 genes. This combination of PES genes advantageously allows a similar or improved capability to identify patients with higher HCC risk compared to the full signature of 1693 genes.


Assessing the Level of Expression of a Marker


The level of expression of a marker as defined above or of the markers of the plurality of markers as defined above may be assessed by any method well known by the skilled person.


The level of expression of a given marker can for example be assessed by quantifying the expressed protein encoded by said marker or by determining the copy number or level of mRNA translated from the marker.


Quantifying an expressed protein or determining the copy number or level of an mRNA may be assessed by any method well known by the skilled person, for example as defined above.


Kit


The present invention also relates to a kit for the diagnosis and/or prognosis of liver disease progression, survival and/or risk of hepatocellular carcinoma, wherein said kit comprises means for assessing the level of expression of a marker as defined above or of a plurality of markers as defined above.


The kit as defined above preferably comprises means for assessing the level of expression of at least 10 markers, preferably at least 15 markers, more preferably at least 20 markers, still more preferably at least 25 markers as defined above and/or at most 180 markers, preferably at most 150 markers, more preferably at most 100 markers, still more preferably at most 50 markers.


An embodiment of the kit as defined above comprises means for assessing the level of expression of the following markers: GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, TMED3, GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR, HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1.


The means for assessing the level of expression of a marker or a plurality of markers are well known by the skilled person.


Method of Diagnosis and/or Prognosis of Liver Disease Progression, Survival and/or Risk of Hepatocellular Carcinoma


The present invention thus relates to a method of diagnosis and/or prognosis of liver disease progression, survival and/or risk of hepatocellular carcinoma in a subject comprising detecting an epigenetic or transcriptomic change in subject with liver disease.


Detecting an epigenetic or transcriptomic change is particularly carried out by determining the level of expression of a marker or a plurality of markers in a subject sample and comparing the obtained level of expression with those obtained in a control sample.


The method as defined above thus particularly comprises comparing:

    • a) the level of expression of a marker or a plurality of markers in a subject sample; and
    • b) the level of expression of the marker or plurality of markers in a control sample,


      wherein the marker or plurality of markers are selected from the group consisting of the genes listed in table S3 and a significant difference between the level of expression of the marker or at least one marker of the plurality of markers in the subject sample and the control sample is an indication that the subject is at risk for progression of liver disease, low survival and/or developing a hepatocellular carcinoma.


For example, the subject is at risk or increased risk for progression of liver disease, low survival and/or developing a hepatocellular carcinoma when at least one gene of the PES Extended high-risk gene is overexpressed and/or when at least one gene of the PES Extended low-risk gene is underexpressed in the subject sample in comparison to the control sample.


On the contrary, the subject is not at risk or has decreased risk for progression of liver disease, low survival and/or developing a hepatocellular carcinoma when at least one gene of the PES Extended high-risk gene is underexpressed and/or when at least one gene of the PES Extended low-risk gene is overexpressed in the subject sample in comparison to the control sample.


On the contrary, the subject is not at risk or has a decreased risk for progression of liver disease, low survival and/or developing a hepatocellular carcinoma when at least one gene of the PES Extended high-risk gene and/or of the PES Extended low-risk gene expression is similar in the subject sample and the control sample. In this case, HCC low-risk are usually not overexpressed compared to controls but at more similar levels than in a subject at risk for progression of liver disease, low survival and/or developing a hepatocellular carcinoma.


The marker or the plurality of markers are particularly as defined above.


The liver disease is particularly as defined above.


The liver disease is preferably a non-alcoholic or alcoholic steatohepatitis, chronic hepatitis A, B, C, D or E related liver disease or of any other etiology.


The subject may have undergone tumor resection.


The subject may have undergone a liver biopsy, fine needle aspiration or a blood or urine test.


The subject may be a patient without treatment or cured by direct-acting antivirals (DAA) and/or interferon-alfa based treatment or a patient cured of or with controlled viral infection, in particular by any treatment.


The subject sample may be selected from the group consisting of a tissue, patient-derived spheroids, serum, plasma or urine.


The tissue as defined above may be a fresh tissue, fresh frozen tissue or fixed embedded tissue.


The tissue as defined above may be a non-tumorous liver tissue or a tissue surrounding a resected tumor.


Patient-derived spheroids may be generated by culturing fresh liver tissue in a spheroid culture medium.


Any spheroid culture medium well known by the skilled person may be used.


The control sample is preferably a sample from a patient without significant liver disease. The patient has particularly no liver disease and is not at risk of developing a liver disease.


The control sample is a sample of the same nature as the subject sample.


The control sample can also be of a patient with liver disease without risk of disease progression or cancer (e.g., early stage liver disease).


For example, both the control sample and subject sample are a tissue, spheroids, serum, plasma or urine.


Alternatively, the level of expression of the marker or of a marker of the plurality of markers in a control sample corresponds to an average of the level of expression of said marker obtained from several healthy subjects or corresponds to a reference value.


The reference value may be determined in function of an average of the level of expression of said marker obtained from several healthy subjects.


The marker or at least one marker of the plurality of markers may have increased expression in the subject sample relative to the control sample.


The marker or at least one marker of the plurality of markers may have decreased expression in the subject sample relative to the control sample.


Alternatively, at least one marker has increased expression in the subject sample relative to the control sample and at least one marker has decreased expression in the subject sample relative to the control sample.


The plurality of markers as defined above preferably comprises at least 10 genes, preferably at least 15 genes, more preferably 20 genes, still more preferably at least 25 genes.


The plurality of markers as defined above preferably comprises at most 180 genes, preferably at most 150 genes, more preferably at most 100 genes, still more preferably at most 50 genes.


The plurality of markers preferably comprises GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, TMED3, GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR, HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1.


A significant difference between the level of expression of at least one marker, preferably at least two markers, at least four markers, at least eight markers, at least ten markers or at least twelve markers selected from the group consisting of GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, TMED3, GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR, HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1 in the subject sample and the control sample is an indication that the subject is at risk for progression of liver disease, at risk of developing a hepatocellular carcinoma and/or at risk of poor survival.


In Vitro Use of a Marker or a Plurality of Markers for the Diagnosis and/or Prognosis of Liver Disease Progression, Survival and/or Risk Hepatocellular Carcinoma


The present invention also relates to the in vitro use of a marker or a plurality of markers as defined above or of a kit as defined above, for the diagnosis and/or prognosis of liver disease progression, survival and/or risk hepatocellular carcinoma in a subject.


Said marker is preferably a gene selected from the list of 1693 genes displayed in Table S3.


The marker or the plurality of markers are particularly as defined above.


The present invention particularly relates to the in vitro use of a plurality of markers as defined above or a kit as defined above, for the diagnosis and/or prognosis of liver disease progression, survival and/or risk hepatocellular carcinoma in a subject, wherein the plurality of markers comprises at least 10 genes, preferably at least 15 genes, more preferably 20 genes, still more preferably at least 25 genes, for example selected from the 1693 genes listed in Table S3.


The plurality of markers as defined above preferably comprises at most 180 genes, preferably at most 150 genes, more preferably at most 100 genes, still more preferably at most 50 genes.


The plurality of markers preferably comprises GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, TMED3, GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR, HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1.


An overexpression of at least one marker, preferably at least two markers, at least four markers, at least eight markers, selected from the group consisting of GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, and TMED3 and/or an underexpression of at least one marker, preferably at least two markers, at least four markers, at least eight markers, at least ten markers or at least twelve markers, selected from the group consisting of GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1 in a subject sample is associated with a risk for progression of liver disease, a risk of developing a hepatocellular carcinoma and/or at risk of poor survival.


Method of Assessing the Efficacy of a Therapy for Liver Disease and/or Hepatocellular Carcinoma Prevention or Treatment


The present invention also relates to a method of assessing the efficacy or prediction the efficacy of a therapy for liver disease and/or hepatocellular carcinoma prevention or treatment in a subject with liver disease, the method comprising comparing:

    • a) the level of expression of a marker or a plurality of markers in a subject sample, preferably before treatment with the therapy or at a time t1 during treatment with the therapy; and
    • b) the level of expression of the marker or plurality of markers in a second subject sample, preferably following the treatment with the therapy or at time t2 later than t1,


      wherein the marker or plurality of markers are selected from the group consisting of the genes listed in tables S3 and a significant difference between the level of expression of the marker or plurality of markers indicates the efficacy of the therapy, in particular the efficacy of the prevention and treatment of liver disease and hepatocellular carcinoma.


The subject is preferably a subject at risk of progression of liver disease, death and/or developing a hepatocellular carcinoma.


By “a subject at risk of death”, it is herein meant a subject with poor survival.


The subject may have been diagnosed of at risk for progression of liver disease, poor survival and/or developing a hepatocellular carcinoma by the method of diagnosis and/or prognosis of liver disease progression, survival and/or risk of hepatocellular carcinoma as defined above.


The liver disease is preferably a non-alcoholic or alcoholic steatohepatitis, chronic hepatitis A, B, C, D or E-related liver disease or liver fibrosis.


A decreased expression of at least one marker, preferably at least two markers, at least four markers, at least eight markers, selected from the group consisting of GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, and TMED3, and/or an increased expression of at least one marker, preferably at least two markers, at least four markers, at least eight markers, at least ten markers or at least twelve markers, selected from the group consisting of GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1 between the level obtained in step a) and the level obtained in step b) particularly indicates the efficacy of the therapy, in particular of the prevention and treatment of liver disease and hepatocellular carcinoma.


An increased expression or similar expression of at least one marker, preferably at least two markers, at least four markers, at least eight markers, selected from the group consisting of GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, and TMED3, and/or a decreased expression or similar expression of at least one marker, preferably at least two markers, at least four markers, at least eight markers, at least ten markers or at least twelve markers, selected from the group consisting of GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1 between the level obtained in step a) and the level obtained in step b) particularly indicates a lack of efficacy of the therapy, in particular of the prevention and treatment of liver disease and hepatocellular carcinoma.


In case of a lack of efficacy of the therapy, another therapy may be administered to the subject.


The method as defined above may be carried out several time in course of the therapy.


Method of Identifying a Compound Useful for the Prevention or Treatment of Liver Disease and/or Hepatocellular Carcinoma


The present invention also relates to a method of identifying a compound useful for the prevention or treatment of liver disease and/or hepatocellular carcinoma, said method comprising the steps of:

    • a) providing a sample;
    • b) contacting the sample with a candidate compound; and
    • c) detecting an increase or decrease in expression of a marker or a plurality of markers selected from the group consisting of the genes listed in Table S3, relative to a control, and
    • d) identifying the compound as useful for the prevention or treatment of liver disease and/or hepatocellular carcinoma if it increases or decreases the expression of said marker or plurality of markers relative to the control.


The marker or plurality of markers and the liver-disease are particularly as defined above.


The sample may be or comprise a subject-derived HCC or adjacent liver tissue, a cancer cell, a liver cell line, cells or a cell line derived from a subject-derived HCC or adjacent liver tissue plasma, serum or urine or a combination of cells and cell lines.


The control in step c) may be (i) the level of expression sample of the marker or plurality of markers in a sample not contacted with the candidate compound or (ii) a reference value, in particular as defined above.


Method for Preventing or Delaying the Progression of a Liver Disease or for Preventing, Delaying the Onset of or Treating Hepatocellular Carcinoma


The present invention also relates to a method for preventing or delaying the progression of a liver disease or for preventing, delaying the onset of or treating hepatocellular carcinoma in a subject comprising:

    • performing the steps of the method of diagnosis and/or prognosis of liver disease progression and/or risk of hepatocellular carcinoma as defined above, and
    • administering a treatment to the subject diagnosed as at risk for progression of liver disease and/or developing a hepatocellular carcinoma.


The treatment may for example comprises at least one inhibitor of a chromatin reader or modifier, a regulator or reader-targeting or previously identified candidate compounds for treatment of advanced liver disease and HCC prevention (e.g., Nizatidine).


The inhibitor of a chromatin reader or modifier may for example be an inhibitor of p300 histone acetyltransferase (for example C646 or CTK7A), a bromodomain 3 or 4 inhibitor (for example IBET151 or JQ1), an inhibitor of the MLL/WOR5 complex (for example WFR-0103 or MM-102), an inhibitor of HDAC (Histone deacetyltransferases) (for example SAHA, TSA or TMP150).


The inhibitor of a chromatin reader or modifier or regulator or reader-targeting may for example be selected from the group consisting of in a BRPF1B inhibitors, G9a/GLP inhibitors, PCAF/GCN5 inhibitors, LSD1 inhibitors, SPIN1 inhibitors, CREBBP/EP300 inhibitors, SMYD2 inhibitors, PRDM9 inhibitors, SMARCA2/4 inhibitors, EZH2 inhibitors, BAZ2A/2B inhibitors, SUV420H1/H2 inhibitors, CECR2/BPTF inhibitors, L3MBTL3 inhibitors, ATAD2A/B inhibitors or PRMT4/6 inhibitors.


The present invention features, in another part, a chromatin modifier, regulator or reader inhibitor or compound targeting epigenetic gene expression regulation for use in the treatment or prevention of liver disease and hepatocellular carcinoma in a subject in need thereof. In a specific embodiment the subject has a liver disease, comprising chronic hepatitis due to viral infection or metabolic causes such as non-alcoholic steatohepatitis or alcoholic liver disease.


In the method for generating a cellular model identifying an agent for treatment or prevention of liver disease and hepatocellular carcinoma, hepatocyte-like cells, which were obtained by differentiation of liver cancer cells, are submitted to a liver disease causing or hepatocarcinogenic agent. As used herein, the term “submitting cells to a liver disease of hepatocarcinogenic agent” refers to a process in which cells are exposed to (e.g., contacted with and/or incubated with and/or grown in the presence of) a hepatocarcinogenic agent while being cultured. The exposure or contact is performed under conditions and for a time sufficient for the hepatocarcinogenic agent to induce the desired effect (i.e., to induce a stable HCC high-risk gene/poor prognosis signature in the cells). The hepatocarcinogenic agent may be any suitable hepatocarcinogenic agent, and its mechanism of action is not a limiting factor.


In certain embodiments of the invention, submitting hepatocyte-like cells to a hepatocarcinogenic agent may be: submitting said hepatocyte-like cells to persistent HCV infection. Methods for infecting cells (including liver cells) with HCV are known in the art11. The inventors have found that when cells are differentiated with DMSO for a short period of time (about 7-10 days) and then infected with HCV for a short period of time (about 10 days), the PES/HCC risk signature is efficiently induced.


In other embodiments of the invention, submitting hepatocyte-like cells to a hepatocarcinogenic agent may be: submitting said hepatocyte-like cells to persistent HBV infection. As already mentioned above, to prepare a cellular model for HCC development and progression by HBV infection, the starting cells must be HBV susceptible cells (i.e., must be cells that are intrinsically susceptible to HBV infection or cells that have been genetically engineered to overexpress NTCP). Methods for infecting cells (including liver cells) with HBV are known in the art54, 55.


In yet other embodiments of the invention, submitting hepatocyte-like cells to a hepatocarcinogenic agent may be: submitting said hepatocyte-like cells to ethanol exposure. Ethanol may be used at any suitable concentration and the exposure may be performed for any suitable time.


In yet other embodiments of the invention, submitting hepatocyte-like cells to a hepatocarcinogenic agent may be: submitting said hepatocyte-like cells to free fatty acid exposure. Free fatty acid may be used at any suitable concentration and the exposure may be performed for any suitable time. For example, the cells may be exposed to about 400 μM, about 600 μM, about 800 μM, about 1000 μM or more of oleic acid and/or about 200 μM, about 400 μM or about 600 μM or more of palmitic acid, for at least 1 day less than 5 days, preferably 3 days. Any other saturated fatty acid can be used in the method. Preferably, fresh medium containing ethanol is replenished every day. The Examples section below provides a method for exposing cells to free fatty acid.


During the step where the hepatocyte-like cells are submitted to a hepatocarcinogenic agent, DMSO may be present in the cell culture medium (e.g., at a concentration of between about 0.1% to about 3% DMSO vol:vol in the cell culture medium).


In certain embodiments, step (1) of a method for generating different cellular models for liver disease and hepatocellular carcinoma development and progression using the exposure of hepatocyte-like cells to different hepatocarcinogenic agent according to the invention is performed while the hepatocyte-like cells are co-cultured with non-parenchymal liver cells. It is known in the art that co-culture of hepatocytes with non-parenchymal liver cells better represent both normal in vivo liver physiology and disease states. The present inventors have found that, in addition to further improve the in vitro liver cell model, the presence of non-parenchymal liver cells enhances the induction of the HCC high-risk gene signature/PES poor prognosis status in a cell- and dose-dependent manner. While hepatocytes alone are sufficient for generating the HCC high-risk gene signature by exposure to a hepatocarcinogenic agent, this can be amplified through cross-talk with non-parenchymal cells.


Non-parenchymal liver cells that can be used in the context of the present invention include, but are not limited to Kupffer cells, stellate cells, liver resident macrophages, sinusoidal endothelial cells, immune cells (T, B, NK cells and the like), intrahepatic lymphocytes, fibroblasts and myofibroblasts and biliary cells as well as cell lines modelling non-parenchymal liver cells. In certain embodiments, the non-parenchymal cells co-cultured with the hepatocyte-like cells are of a single cell type (e.g., hepatic stellate cells). In other embodiments, non-parenchymal cells co-cultured with the hepatocyte-like cells are a mixture of different types of non-parenchymal cells (e.g., hepatic stellate cells and sinusoidal endothelial cells or hepatic stellate cells and Kupffer cells).


Generally, hepatocyte-like cells and non-parenchymal liver cells are co-cultured under conditions where they are in physical contact. As used herein, the term “physical contact” has its general meaning. For example, cells are in physical contact with each other when they are in a conformation or arrangement that allows for intercellular exchange of materials and/or information to take place.


The invention comprises the following items:


Item 1: A method of diagnosis and/or prognosis of liver disease progression, survival and/or risk of hepatocellular carcinoma in a subject comprising detecting an epigenetic or transcriptomic change in subject with liver disease, the method comprising comparing

    • a) the level of expression of a marker or a plurality of markers in a subject sample; and
    • b) the level of expression of the marker or plurality of markers in a control sample,


wherein the marker or plurality of markers are selected from the group consisting of the genes listed in table S3 and a significant difference between the level of expression of the marker or plurality of markers in the subject sample and the control sample is an indication that the subject is at risk for progression of liver disease, at risk of poor survival and/or at risk of developing a hepatocellular carcinoma.


Item 2: The method of item 1, wherein the liver disease is a non-alcoholic or alcoholic liver disease, a liver disease due to viral hepatitis or liver fibrosis.


Item 3: The method of item 2, wherein the liver disease is a non-alcoholic or alcoholic steatohepatitis, chronic hepatitis A, B, C, D or E related liver disease or liver fibrosis.


Item 4: The method according to any one of items 1 to 3, wherein the subject is a patient cured by direct-acting antivirals (DAA) and/or interferon-alfa based treatment or a patient cured of or with controlled viral infection by any treatment.


Item 5: The method according to any one of items 1 to 4, wherein the marker or at least one marker of the plurality of markers have increased expression in the subject sample relative to the control sample.


Item 6: The method according to any one of items 1 to 4, wherein the marker or at least one marker of the plurality of markers have decreased expression in the subject sample relative to the control sample.


Item 7: The method according to any one of items 1 to 4, wherein at least one marker has increased expression in the subject sample relative to the control sample and at least one marker has decreased expression in the subject sample relative to the control sample.


Item 8: The method according to any one of items 1 to 4, wherein at least one gene of the high-risk gene of Table S3 is overexpressed and/or wherein at least one gene of the low-risk gene of Table S3 is underexpressed, in the subject sample in comparison to the control sample.


Item 9: The method according to any one of items 1 to 8, wherein the subject has undergone tumor resection.


Item 10: The method according to any one of items 1 to 9, wherein the subject sample is obtained from a non-tumorous liver tissue or a tissue surrounding a resected tumor.


Item 11: The method according to any one of items 1 to 10, wherein the subject sample is selected from the group consisting of fresh tissue, fresh frozen tissue, fixed embedded tissue, patient-derived spheroids, serum, plasma or urine.


Item 12: The method according to item 11, wherein the patient-derived spheroids were generated by culturing fresh liver tissue in spheroid culture medium.


Item 13: An in vitro use of a marker or a plurality of markers for the diagnosis and/or prognosis of liver disease progression, survival and/or risk hepatocellular carcinoma in a subject, wherein said marker is a gene selected from the genes displayed in Table S3.


Item 14: The method according to any one of items 1 to 12 or the use according to item 13, wherein the marker is or the plurality of markers are a gene selected from the group consisting of GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, TMED3, GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR, HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1.


Item 15: A method of assessing the efficacy of a therapy for liver disease and/or hepatocellular carcinoma prevention or treatment in a subject with liver disease, the method comprising comparing:

    • a) the level of expression of a marker or a plurality of markers in a subject sample; and
    • b) the level of expression of the marker or plurality of markers in a second subject sample following the treatment with the therapy,


wherein the marker or plurality of markers are selected from the group consisting of the genes listed in tables S3 and a significant difference between the level of expression of the marker or plurality of markers indicates the efficacy of the prevention or treatment of liver disease and/or hepatocellular carcinoma.


Item 16: The method of item 15, wherein (i) the subject is at risk for progression of liver disease, death and/or developing a hepatocellular carcinoma and/or (ii) the liver disease is a non-alcoholic or alcoholic steatohepatitis, chronic hepatitis A, B, C, D or E-related liver disease or liver fibrosis.


Item 17: A method of identifying a compound useful for the prevention or treatment of liver disease and/or hepatocellular carcinoma, said method comprising the steps of:

    • a) providing a sample;
    • b) contacting the sample with a candidate compound; and
    • c) detecting an increase or decrease in expression of a marker or a plurality of markers selected from the group consisting of the genes listed in Table S3, relative to a control, and
    • d) identifying the compound as useful for the prevention or treatment of liver disease and/or hepatocellular carcinoma if it increases or decreases the expression of said marker or at least a marker of the plurality of markers relative to the control.


Item 18: The method according to item 17, wherein the genes is the subset of 25-genes presented in Table S4, and wherein the candidate compound is identified as an agent useful for agent for treatment of liver disease or prevention and treatment of hepatocellular carcinoma if the candidate compound suppresses the expression of the 10 HCC high-risk genes, or of a subset thereof and/or induces the expression of the 15 HCC low-risk genes, or of a subset thereof.


Item 19: The method according to item 17, wherein the sample is or comprises a subject-derived HCC or adjacent liver tissue, a cancer cell, a liver cell line, a combination of liver and non-liver cell lines including non-parenchymal cells or a cell line derived from a subject-derived HCC or adjacent liver tissue plasma, serum or urine.


Item 20: The method according to any of items 17 to 19, wherein the candidate compound is a chromatin modifier, regulator or reader inhibitor or compound targeting epigenetic gene regulation.


Item 21: The method according to item 20, wherein the chromatin modifier, regulator or reader inhibitor or compound targeting epigenetic gene regulation is selected from the list the group consisting of BRPF1B inhibitors, G9a/GLP inhibitors, PCAF/GCN5 inhibitors, LSD1 inhibitors, SPIN1 inhibitors, CREBBP/EP300 inhibitors, SMYD2 inhibitors, PRDM9 inhibitors, SMARCA2/4 inhibitors, EZH2 inhibitors, BAZ2A/2B inhibitors, SUV420H1/H2 inhibitors, CECR2/BPTF inhibitors, L3MBTL3 inhibitors, ATAD2A/B inhibitors or PRMT4/6 inhibitor.


Item 22: A method for preventing or delaying the progression of a liver disease, delaying the onset of or treating hepatocellular carcinoma in a subject comprising:

    • performing the steps of the method of diagnosis and/or prognosis of liver disease progression and/or risk of hepatocellular carcinoma according to any one of items 1 to 12 or 14, and
    • administering a preventive treatment to the subject diagnosed as at risk for progression of liver disease and/or at risk of developing a hepatocellular carcinoma.


Item 23: A kit for the diagnosis and/or prognosis of liver disease progression, survival and/or risk of hepatocellular carcinoma, wherein said kit comprises means for assessing the level of expression of GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, TMED3, GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR, HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1.


Item 24: A method for generating a cellular model for liver disease or hepatocellular carcinoma (HCC) development and progression, said method comprising steps of:

    • (a) differentiating liver cancer cell line to obtain hepatocyte-like cells; and
    • (b) submitting said hepatocyte-like cells to one hepatocarcinogenic/fibrosis causing agent such as hepatitis C virus or free fatty acids to obtain liver cells exhibiting a Prognostic Epigentic Signature (PES) high-risk gene signature


Item 25: The method according to item 24, wherein the liver cancer cell line is selected from the group consisting of the Huh6, Huh7, Huh7.5.1, Hep3B.1-7, HepG2, SkHepI, C3A, PLC/PRF/5 and SNU-398 cell lines or optionally a combination with another cell line such as 5 LX2 cells or THP1 cells or another cell line or liver non-parenchymal cells such as Kupffer cells, or myofibroblasts or liver sinusoidal endothelial cells.


Item 26: Use of a cellular model for liver disease progression and HCC risk according to item 24 or item 25 for identifying an agent for the treatment or prevention of liver disease and HCC.


The invention will be further illustrated by the following figures and examples. However, these examples and figures should not be interpreted in any way as limiting the scope of the present invention.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1. NASH and CHC patients with advanced liver disease share similar epigenetic and transcriptional changes associated with HCC. (A) RNA-Seq (left panel) and ChIP-Seq (right panel) mapping of NASH- and CHC-induced transcriptomic and H3K27ac modifications from patient-derived liver biopsies and resections. Left panel: Unsupervised clustering of significant 4,790 differentially expressed genes in livers from NASH (n=3) and CHC (n=6) compared to control patients (n=3 and 5, respectively). Right panel: Differential signals in H3K27ac ChIP-Seq peaks for corresponding genes in livers from NASH (n=7) and CHC (n=6) compared to control patients (n=6). (B) Significant H3K27ac modifications correlate (Spearman's rank correlation coefficients and p-values) with gene expression changes in both NASH (top panel) and CHC (bottom panel) patients. Prognostic association of gene expression was determined using Cox score for time to overall death in a cohort of patients as described in the material and methods. (C) HALLMARK pathways significantly enriched for H3K27ac modifications in NASH (n=7) and CHC (n=6) compared to control (n=6) patient samples. (D) Significant H3K27ac changes of the 1,693 genes with corresponding transcriptomic changes in NASH and CHC patients derived from B. (E) Venn diagram showing the overlap of significant epigenetically modified genes (shown in D) with corresponding expression changes in NASH and CHC patients with advanced liver disease derived from the ChIP-Seq and RNA-Seq experiments shown in B.



FIG. 2. Advanced fibrosis and risk for HCC development and PES expression in patients with advanced liver disease. (A) The probabilities of future hepatocarcinogenesis and overall survival according to the presence of the epigenetic dysregulation related to the PES. The dysregulation was significantly associated with future HCC development and mortality in patients with HCV-related early-stage cirrhosis. (B) The prevalence of the presence of the epigenetic dysregulation in patients with NASH. The dysregulation was more frequently observed in patients with advanced fibrosis, one of the well-known HCC risk, compared to those with mild fibrosis. (C) The probabilities of future hepatocarcinogenesis and overall survival according to the presence of dysregulation of a gene subset termed the “prognostic epigenetic signature” (PES). (D) The prevalence of the presence of the epigenetic dysregulation in patients with NASH. The PES, including 25 genes, showed better or similar capability to identify patients with higher HCC risk compared to the full signature. The PES was defined as commonly prognostic genes in both HCV and NASH (FDR<0.25).



FIG. 3 (related to FIG. 1A). Sequencing tag density of H3K27ac enrichment in the NFcB2 gene in liver tissue of control, NASH, CHC and DAA-cured patients with HCC. H3K27ac ChIPmentation-based ChIP-Seq was performed on non-infected (Control 1-6; green), on NASH (NASH 1-7; brown), on CHC (CHC 1-6; red) and on DAA/HCC cured (DAA/HCC 1-6; orange) patient livers shown in FIG. 1A. Blue boxes indicate called H3K27ac-enriched loci. Integrative Genomics Viewer (IGV) was used to illustrate reads on the NFκB2 gene.



FIG. 4 (related to FIG. 2). NASH, CHC and DAA/HCC cured patients with advanced liver disease share epigenetic and transcriptional changes associated with HCC risk. (A) RNA-Seq (left panel) and ChIP-Seq (right panel) mapping of transcriptomic and H3K27ac modifications among NASH-, CHC- and DAA/HCC cured patient-derived liver biopsies and resections. Left panel: Unsupervised clustering of significant 5,786 differentially expressed genes in livers from NASH (n=3), CHC (n=6) and DAA/HCC cured (n=3) patients compared to control patients (n=3, 5 and 3 respectively). Right panel: Differential signals in H3K27ac ChIP-Seq peaks for corresponding genes in livers from NASH (n=7), CHC (n=6) and DAA/HCC cured (n=6) compared to control patients (n=6). (B) Significant H3K27ac modifications correlate (Spearman's rank correlation coefficients and p-values) with gene expression changes in DAA/HCC cured patients. Prognostic association of hepatic gene expression was determined as described for FIG. 1B. (C) Venn diagram showing the overlap of significant epigenetically modified genes with corresponding expression changes in NASH, CHC and DAA/HCC cured patients derived from the ChIP-Seq and RNA-Seq experiments shown in panel A. (D) H3K27ac changes of the 1,256 genes with significant transcriptomic changes in NASH, CHC and DAA/HCC cured patients.



FIG. 5. Development of a diagnostic assays for detection of the PES in patient liver tissues using an FDA-approved nCounter probe and development of a noninvasive blood-based immune-assay to detect secreted PES proteins. (A) A custom-made PES hybridization array, designed and applied by the inventors and using the FDA-approved Nanostring nCounter hybridization technology, enables robust detection of the PES in liver tissues of patients with advanced fibrosis (F3-F4) vs. patients with early fibrosis (F0-F1). Gene set enrichment analysis of gene expression revealed a significant (FDR<0.05) induction of PES genes associated with high cancer risk (PES_high risk genes) and suppression of PES genes associated with a protective effect (PES_low risk genes). NES=normalized enrichment score in the assays. (B) Secreted PES-based proteins can be detected by immuno-assays in blood as shown for catalase (CAT). The PES component catalase (CAT) is associated with low cancer risk is strongly and significantly (adjusted P<0.05) impaired in the blood plasma of mice with metabolic liver disease (FRG-NOD mice fed with choline-deficient high fat diet) compared to mice fed with normal diet. Catalase protein abundance was measured with a scioDiscover antibody microarray (Sciomics, Germany).



FIG. 6. Modelling of PES expression and associated epigenetic modifications in cell-based models for viral and metabolic liver disease. (A) Schematic representation of the experimental setup of the model systems for liver disease model systems. H3K27ac marks were profiled by ChIP-Seq following free fatty acid (FFA) treatment (top panel: day 3) or persistent HCV infection (bottom panel: day 10). (B) H3K27ac data of the 1693 genes with significant transcriptomic changes in patients with NASH and chronic hepatitis C (CHC) derived from FIG. 1B, and corresponding changes in FFA-treated or HCV-infected cells derived from the ChIP-Seq experiment shown in panels A and B, and corresponding transcriptional changes in cell culture. (C) GSEA enrichments of 1693-gene signature and 25-gene signature (PES) gene sets in data shown for cell culture on panel B and D. The global status corresponds to the difference between low risk- and high risk-gene expression. (D) H3K27ac and transcriptomic changes for the subset of 25 (PES) genes which are included in 1693-gene signature as shown on panel B. (E) Gene Set Enrichment Analysis (GSEA) pathway analysis of genes associated with H3K27ac modifications in FFA-treated or HCV-infected compared with Mock or non-infected cells from the ChIP-Seq experiment shown in panels A and B.



FIG. 7. Discovery of compounds for prevention and treatment of liver disease using a cell-based assay modeling the clinical PES. (A) Schematic set-up of the drug discovery model using HCV infection as described in FIG. 7 and Materials and Methods. (B-C) Reversal of the poor prognosis/HCC high risk genes to good prognosis/HCC low risk expression by JQ1 (B) and Nizatidine (C) but not by other compounds. Differentiated Huh7.5.1 cells infected with HCV and expressing the PES poor prognosis status were subjected to treatment with compounds indicated and PES was expression was analyzed as described in Methods. The global status corresponds to the difference between low risk- and high risk-gene expression.



FIG. 8. Reversal of the PES poor prognosis status in vivo by a bromodomain-4 inhibitor translates into improvement of liver disease and cancer prevention (A) Schematic representation of in vivo the proof-of-concept study using a mouse model of DEN and choline-deficient, L-amino acid-defined, high-fat diet (CDAHFD)-induced hepatocarcinogenesis. (B) Transcriptomic changes of genes with significant H3K27ac modifications from livers from patients with NASH and chronic hepatitis C (CHC) as explained in FIG. 1D (overlapping genes) and corresponding changes in vehicle or JQ1-treated DEN/CDAHFD mice. (C) Venn diagram showing epigenetically and transcriptionally altered genes in CHC/NASH patients and in DEN/CDAHFD mice, that were corrected by JQ1 treatment. Genes that harbor epigenetic and transcriptomic changes were identified in CHC/NASH patients and in DEN/CDAHFD mice. Among the changed genes, the inventors analyzed whether JQ1 could revert back their H3K27ac levels and their transcript expression levels. (H) GSEA enrichments of 1693-gene signature and 25-gene signature (PES) gene sets in data shown for JQ1-treated DEN/CDAHFD mice. (D) Improvement of liver disease and prevention of HCC. The global status corresponds to the difference between low risk- and high risk-gene expression. GSEA enrichments of 1693-gene signature and 25-gene signature (PES) gene sets in data shown for JQ1-treatment on panel B. The global status corresponds to the difference between low risk- and high risk-gene expression. (E) JQ1 significantly reduces tumor burden in vivo. While body weights are stable, liver weights as well as the numbers of tumors are significantly (*p<0.05; ***p<0.001; ****p<0.0001, unpaired t-test) reduced in JQ1-treated (n=8) compared with untreated (n=8) mice. Results are expressed as means±SEM. (F) Representative macroscopic photographs of livers (×1.5 magnified), H&E and Sirius red staining of liver sections from vehicle and JQ1-treated mice. Tumor nodules are indicated by an arrowhead and are delimited by dashed lines. (G) JQ1 efficiently reduces liver fibrosis. Fibrosis stage was evaluated through quantitative digital analysis of whole-scanned liver sections (collagen proportional area (CPA)) in JQ1-treated (n=3) compared with JQ1-untreated (n=3) mice. Results are expressed as means±SD.





BRIEF DESCRIPTION OF THE TABLES

Table S1. Clinical data of patients included in epigenetic analyses using ChIP-seq (related to FIG. 1). Fibrosis was staged according to Kleiner score[51] for NASH and METAVIR score[52] for all the other etiologies. METAVIR score was used for histological grading of the activity of HCV infection[53]. ASV=asunaprevir, CHC=chronic hepatitis C, DCV=daclatasvir, HCC=hepatocellular carcinoma, HCV=hepatitis C virus, LDV=ledipasvir, N/A=not applicable, NASH=non-alcoholic steatohepatitis, RBV=ribavirin, SOF=sofosbuvir.


Table S3 (related to FIG. 1D). List of the 1693 genes of the prognostic epigenetic signature. Epigenetic (H3K27ac) log 2FCs of 1,693 common genes in NASH and CHC patients with similar significant epigenetic modifications and corresponding transcriptional changes.


Table S4 (related to FIG. 2C). List of the 25 genes of the prognostic epigenetic signature (PES). List of the 25 genes (high and low-risk genes) with the highest prediction of HCC risk predicted from the 1,693 commonly changed genes on CHC and NASH patients (FDR<0.25) shown in FIG. 2C. The dysregulation was determined by the nearest template prediction [16].


Examples
Material and Methods

Human subjects. The inventors analyzed adjacent non-tumorous liver tissue from: 6 control patients without known liver disease and without HCC, 3 patients without known liver disease (F0) and HCC (“spontaneous” HCC), 3 CHC patients without HCC (F3-F4), 3 CHC patients with HCC (F3-F4), 6 DAA-cured CHC patients with HCC (F3-F4), 3 NASH and HCC (F1), 3 NASH and HCC (F4), and 4 NASH without HCC (F4) from patients undergoing surgical liver resection (see Table S1). The protocols were approved by the Ethics Committee of the Strasbourg University Hospitals (DC-2016-2616), Mount Sinai Hospital, New York (HS13-00159), Basel University Hospital (EKNZ 2014-362) and Hiroshima University Hospitals (E-1049-1). Some subjects have been described [6].


ChIPmentation based ChIP-Seq and RNA next-generation sequencing (NGS). ChIPmentation-based ChIP-Seq was performed as described[6, 11]. RNA-Seq was performed as described[6]. Mouse RNA-Seq data was processed as described for patient's data but was instead mapped to the mouse genome mm10 and annotated using the Gencode vM15 gene annotation. Processing of ChIPmentation data was described[6], and data was partially derived from BioProject PRJNA506130. Since late stage fibrosis patients have the highest HCC risk, patient tissues from late stage fibrosis (F3 and F4) samples were included for all H3K27ac analyses as well as from the external CHC RNA-Seq dataset (GSE84346)[12]. Transcriptomic data for NASH patients was derived from external expression dataset (GSE115193)[13] and data for DAA-cured patients was published in BioProject PRJNA506130[6]. The RNA-Seq data from HCV-infected liver cells was published in (GSE126831)[14].


Cell-based models. Huh7.5.1 and human stellate LX2 cells were cultured in Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% heat-decomplemented fetal bovine serum FBS, gentamycin (0.05 mg/mL) and non-essential amino acids (complete DMEM) at 37° C. with 5% CO2. For proliferation arrest and differentiation (Huh7.5.1thf cells), Huh7.5.1 cells were cultured in complete DMEM supplemented 1% DMSO [5]. All cell lines were certified mycoplasma-free. To analyze the PES induction Huh7.5.1thf cells were infected with HCV Jc1 (genotype 2a/2a) [6] for a total of 10 days. Cells were then treated with Captopril (1 μM), Nizatidine (10 μM), Pioglitazone (1 μM), JQ1 (50 nM). For the FFA model, Huh7.5.1dif cells were cocultured with 20% LX-2 cells. Following co-culture for 3 days in DMEM supplemented with 10% heat-decomplemented FBS, gentamycin and 1% DMSO at 37° C. and 5% CO2, cells were incubated with FFA (800 μM oleic acid and 400 μM palmitic acid) for 72 h [7].


Analysis of gene expression of the prognostic epigenetic signature (PES) using nCounter expression or RNASeq analyses. Profiling of the PES was performed using Nanostring nCounter assay or RNASeq as described[15]. Induction or suppression of the PES in gene expression data was determined as previously reported using the Gene Set Enrichment Analysis (GSEA), implemented in GenePattern genomic analysis toolkits[16-18]. False discovery rate (FDR)<0.05 was regarded as statistically significant. Results are presented as heatmaps showing: (top) the classification of the PES global status as poor (orange) or good (green) prognosis; (bottom) the significance of induction (red) or suppression (blue) of PES poor- or good-prognosis genes. Global status corresponds to the difference between low risk- and high risk-gene enrichments. For PES results are presented as heatmaps showing the significance of induction (red) or suppression (blue) of (top) PES high-risk- or (bottom) low-risk genes.


Protein profiling of mouse plasma samples with liver disease using scioDiscover antibody microarrays (Sciomics, Germany). FGR-NOD mice (n=9) were transplanted with human primary hepatocytes as described. 4 mice were fed with normal diet and 5 mice with choline-deficient high fat diet (Research diet, Brogaarden, Denmark) for 20 weeks. At the end of the diet, the mouse livers were harvested and liver lysates were labelled at an adjusted protein concentration for two hours with scioDye 1 and scioDye 2. After two hours the reaction was stopped and the buffer exchanged to PBS. All labelled protein samples were stored at −20° C. until use. Samples were analysed in a dual-colour approach using a reference based design on 9 scioDiscover antibody microarrays (Sciomics, Germany) targeting 1,360 different proteins with 1,830 antibodies. Each antibody is represented on the array in four replicates. The arrays were blocked with scioBlock (Sciomics, Germany) on a Hybstation 4800 (Tecan, Austria) and afterwards the samples were incubated competitively using a dual-colour approach. After incubation for three hours, the slides were thoroughly washed with 1×PBSTT, rinsed with 0.1×PBS as well as with water and subsequently dried with nitrogen. Slide scanning was conducted using a Powerscanner (Tecan, Austria) with identical instrument laser power and adjusted PMT settings. Spot segmentation was performed with GenePix Pro 6.0 (Molecular Devices, Union City, CA, USA). Acquired raw data were analyzed using the linear models for microarray data (LIMMA) package of R-Bioconductor after uploading the median signal intensities.


Pathway enrichment and correlation analyses. Hallmark pathway enrichment and correlation analyses were performed as described [6].


Statistical analyses. Statistical analyses of NGS data are based on DESeq (RNA-Seq) and MACS2/edgeR (ChIP-Seq) as described [6]. The cell culture and tumorspheroids data are presented as the mean±SD except where mean±SEM. is indicated and were analyzed by the unpaired Student's t-test or the two-tailed Mann-Whitney test as indicated after determination of distribution by the Shapiro-Wilk normality test. The p-values are indicated in the figure legends for each figure panel. P<0.05 was considered significant. Statistical analyzes were performed with GraphPad Prism 6 software. For the antibody capture arrays (sciDiscover, Sciomics, Germany), raw data were normalized using a specialized invariant Lowess method. For analysis of the samples a one-factorial linear model was fitted with LIMMA resulting in a two-sided t-test or F-test based on moderated statistics. All presented p-values were adjusted for multiple testing by controlling the false discovery rate according to Benjamini and Hochberg. Differences in protein abundance between different samples or sample groups are presented as log-fold changes (log FC) calculated for the basis 2. Proteins were defined as differential for log FC>0.5 and an adjusted p value<0.05. In a study comparing samples versus control a log FC=1 means that the sample group had on average a 21=2 fold higher signal as the control group. log FC=−1 stands for 2−1=1/2 of the signal in the sample as compared to the control group (normal diet).


HCC risk profiling. Transcriptome profiles of 72 NASH-affected liver tissues were obtained from NCBI Gene Expression Omnibus database (www.ncbi.nlm.nih.gov/geo, accession number GSE49541). Transcriptomic molecular dysregulation was determined using Nearest Template Prediction (NTP) algorithm as previously described [16] and defined based on p<0.05.


Results


Example 1: NASH and CHC patients with advanced liver disease share similar epigenetic and transcriptional changes associated with HCC risk. To characterize epigenetic and transcriptional modifications in the liver driving HCC risk, the inventors analyzed NASH and CHC liver tissues with advanced liver fibrosis (F3/F4) using ChIPmentation-based ChIP-Seq profiling of the H3K27ac epigenetic marks of active promoters and enhancers combined with RNA-Seq (FIGS. 1A and 3). Within each etiology, epigenetically modified genes significantly correlate with transcriptomic changes (FIG. 1B). Pathways analysis revealed that NASH and CHC patients with advanced liver disease (F3 and F4) display increased H3K27ac levels on genes related to TNFα signaling via NF-κB, inflammatory response, epithelial-to-mesenchymal transition (EMT) and IL2-STAT5, and decreased levels of H3K27ac on genes related to xenobiotic, bile acid, and fatty acid metabolism as well as adipogenesis, coagulation, and oxidative phosphorylation (FIG. 1C). The inventors then identified genes with H3K27ac modifications and concomitant alteration of corresponding transcript expression, and then intersected NASH (n=2,721) and CHC (n=4,017) groups to identify a gene set with modulated expression in both etiologies present in the adjacent tissue of HCC. The inventors uncovered a total of 1,693 genes with common epigenetic and transcriptional changes (FIG. 1D-E, Table S3). Within the genes shared by CHC and NASH, the inventors identified overexpressed oncogenes with increased level of H3K27ac and down-regulated tumor suppressor genes (TSG) with decreased level of H3K27ac. Among the overexpressed oncogenes were FGFR1, a member of the fibroblast growth factor receptor (FGFR) family that plays a key role in the development and progression of HCC[22], the cyclin CCND2, reported to drive tumorigenesis and progression of various cancers including HCC, MLLT3, an oncogene associated to leukemia, CDH11, a cadherin reported to be involved in liver fibrosis and in EMT[23] as well as MAML2, a coactivator of the Notch signaling pathway known to mediate liver carcinogenesis[24]. Downregulated TSG included FANCC, encoding a protein associated to the DNA damage response, and TSC2, a negative regulator of the mTOR signaling pathway[25].


Since the analysis included only a limited number of patients and the large majority having already established HCC without detailed longitudinal data available, the inventors studied the association of the observed gene set modulation with HCC risk and overall mortality in a validation cohort of patients with HCV-related early-stage cirrhosis and longitudinal analysis [26]. Patients with dysregulation of the 1,693 commonly changed genes exhibited a significantly shorter survival and a significantly earlier HCC development than those with transcriptionally intact liver (FIG. 2A). Furthermore, the dysregulation was more prevalent in patients with NASH-related advanced fibrosis defined as F3 or F4, whose HCC risk is higher[27], compared to those with mild fibrosis defined as F0 or F1 (p<0.001) (FIG. 2B). The identified gene set could be condensed to an intersected gene set of 25 genes with highest prediction of HCC risk. This gene set was termed “prognostic epigenetic signature” (PES) (FIG. 2C-D and Table S4). Collectively, this validation analysis suggests that the identified gene expression changes are associated with HCC risk in advanced liver disease.


To assess transcriptional changes that were associated with the presence of advanced fibrosis (F3-4), the inventors intersected liver tissues with and without advanced fibrosis. Using this approach, the inventors found that 43% of the epigenetically modified genes appeared to be linked to the presence of advanced fibrosis (742 of 1,693). Interestingly, the inventors found 27 genes with epigenetic modifications in the adjacent tissue of three patients with spontaneous HCC without fibrosis which were not altered in patients with HCC and fibrosis of any stage and not present in patients without liver disease. These findings suggest that epigenetic modifications associated with hepatocarcinogenesis can occur in the absence of fibrosis.


Next, the inventors studied the role of epigenetic changes for the status of the prognostic liver signature (PLS)—a well characterized stromal liver 186-gene expression signature that has been shown to predict survival and HCC risk in patients with advanced liver disease of all major HCC etiologies[19]. In line with previously published results[6], the inventors observed a modulation of expression of genes predicting HCC high risk in both NASH and CHC patients with advanced liver disease (FIG. 2E, left panel). Interestingly, H3K27ac levels on these 186 genes were correlated with their respective transcript expression (FIG. 2E, right panel, and 2F), suggesting an association between disease-induced epigenetic modifications and the PLS gene expression. Interestingly, the poor-prognosis PLS status remained (FIG. 2E) upon HCV cure in patients with advanced fibrosis and HCC.


Finally, the inventors intersected the RNA-Seq and H3K27ac ChIP-Seq data among the three patient groups to uncover genes for which changes in their transcript were significantly correlated with H3K27ac modifications, assuming that these genes are most strongly associated with HCC risk. Seventy six percent (1,286 out of 1,693) of the genes identified in both NASH and CHC patient livers were similarly modulated in livers from DAA-cured patients who developed a HCC (FIG. 4A-D).


Example 2: Development of liver tissue- and blood-based diagnostic assays for prediction of liver disease progression and HCC risk based on PES gene and protein expression. Based on the patient investigations and discovery of the PES the inventors developed a diagnostic assay for its detection in patient tissues and blood. As shown in FIG. 5, an assay was developed allowing to robustly detect the PES in patient tissues using a the FDA-approved hybridization array nCounter (NanoString). For example in this PES-based assay, the poor prognosis status of the PES was significantly (FDR<0.05) induced in liver tissues of patients with advanced liver disease and cirrhosis compared to livers of patients with mild fibrosis reflecting the evident risk of liver disease progression and HCC risk in cirrhotic patients36. Importantly, PES components are also secreted into the blood and can be detected by antibody capture array (sciDicover, Sciomics, Germany). As an example, the inventors a detected significant decreased expression of the corresponding protein Catalase of the PES poor prognosis gene CAT in the blood of mice with diet-induced metabolic-associated liver disease (FIG. 5B). Collectively, these data demonstrate that the PES can be detected in liver tissue using an FRD-approved technology and secreted proteins corresponding to PES genes can be used to develop a minimal invasive diagnostic assay detecting risk for liver disease progression, based PES and its components.


Example 3: Modeling of the patient PES in human liver cell-based systems. The inventors next aimed to model the epigenetic changes observed in patients in cell-based models that partially recapitulates transcriptomic and proteomic changes in patients with chronic liver disease. Dimethyl sulfoxide-differentiated Huh7.5.1 cells (Huh7.5.1 dif cells) infected by HCV showed transcriptomic and proteomic changes found in liver tissue from HCV-infected patients. Next, the inventors established a cell culture system aiming to model transcriptional changes in metabolic liver injury by using a co-culture of Huh7.5.1dif and LX2 stellate cells treated with free fatty acids (FFA). ChIPmentation-based ChIP-Seq profiling of the H3K27ac epigenetic marks and RNA-Seq analyses (FIG. 6A) revealed that both persistent HCV infection and FFA treatment led to similar epigenetic and transcriptomic changes in cell culture that were observed in patients with NASH and CHC (FIG. 6B). In concordance with the results found in patient-derived liver tissues, GSEA analyses revealed perturbation of pathways mediating TNFα signaling activation, E2F targets, G2M checkpoint, and EMT signaling (FIG. 3E). Importantly, the 1693-gene signature and 25-gene signature (PES) gene sets were induced with poor prognosis/high risk status in the above-mentioned cell culture models under treatment with FFA or infections with HCV (FIG. 6B-D). Collectively, these analyses demonstrate that the cell-based models model the clinical PES and partially recapitulates epigenetic and associated transcriptional alterations that are found in patients with liver disease such as CHC and NASH.


Example 4: Discovery of compounds for prevention and treatment of liver disease and cancer using the PES cell-based model. Aiming to establish a PES-based drug discovery platform, the inventors studied whether the cell-based assays described in Example 3 can be applied to identify compounds which modulate the PES gene expression status from HCC high risk/poor prognosis status to HCC low risk/good prognosis status. As shown in FIG. 7A the inventors first induced the PES poor prognosis/HCC high risk status by infecting differentiated Huh7.5.1 cells with recombinant HCV. The inventors then treated the cells with different small molecules and studied the PES (25 gene subset)expression by RNA-Seq or nCounter Nanostring technology as shown in Example 2. Treatment with bromodomain-4 inhibitor JQ1 reverted the 25-gene signature (PES) (FIG. 7B) from a HCC high risk, poor prognosis status to a HCC low risk, good prognosis as shown by PES (25 gene subset) gene expression analyses. Similar results were obtained when Nizatidine, a HRH2 antagonist was used to incubate the cells (FIG. 7C). These data demonstrate that a cell-based model can identify compounds which revert the high HCC risk, poor prognosis status to HCC low risk, good prognosis status of the PES.


Example 5: Reversal of the PES poor prognosis status in vivo translates into improvement of liver disease, inhibition of fibrosis progession and cancer prevention. To investigate (1) whether the PES is modeled in animal models for liver disease and (2) reversal of the PLS poor prognosis status by a compound correlates with improvement of liver disease and cancer prevention, the inventors studied the 1693 gene signature and the 25 gene subset expression in a NASH-fibrosis-HCC mouse model, in which the mice are treated with the BRD inhibitor JQ1 following development of liver disease. In this model a Choline-deficient high-fat-diet (CDHFD) diet combined with DEN, a chemical carcinogen, induces liver fibrosis progressing to HCC. Genetically, DEN-induced tumors resemble human tumors with poor prognosis38 and DEN administration changes the proportion of heterochromatin and euchromatin, suggesting an alteration of epigenetic marks. Mice were treated with JQ1 after 6 weeks of CDAHFD feeding when liver disease developed (FIG. 8A). Transcriptomic profiling of DEN/CDAHFD mouse livers (FIG. 8B-C) unravelled gene expression changes on a large fraction of the 1693 genes of the 1693-gene signature that were similarly modulated in patients with CHC and NASH suggesting that the DEN/CDAHFD mouse model enables the study of epigenetic/transcriptomic changes associated with human liver carcinogenesis. Furthermore, the inventors' analyses revealed that expression of 59% (1007 out of 1693 genes) of H3K27ac-altered genes in patients were reverted by JQ1 treatment in DEN/CDAHFD mice, and 1693-gene signature and 25-gene signature (PES) gene sets were correspondingly (i.e., reversely) enriched after treatment (FIG. 8B-D). Analyses of liver fibrosis and HCC revealed that both the expression of the 1693 gene signature and the 25 gene subset expression and perturbation by JQ1 was associated with improvement of liver disease, fibrosis and HCC prevention. JQ1 treatment significantly reduced liver weights of DEN/CDAHFD mice without altering their body weight (FIG. 8E). Quantification of tumor nodules revealed an overall decrease in their number irrespective of their size and location (FIG. 8E-F). Moreover, JQ1 significantly (p<0.05) reduced liver fibrosis measured by collagen proportionate area (CPA) (FIG. 8G). Collectively, these data show that (i) fibrotic liver disease progressing to HCC is associated with induction of the PES poor prognosis status and (2) reversal of the 1693 gene signature and the 25 gene subset (PES) poor prognosis to good prognosis status by a small molecule targeting bromodomain-4 in vivo translates into improvement of liver disease and HCC prevention.


Discussion

HCC prevention in patients with advanced liver fibrosis is likely the most effective strategy to improve patient survival, because tumor recurrence after surgical treatment is frequent, and therapeutic approaches for advanced disease as well as HCC remain unsatisfactory[46, 47]. Approved therapies for NASH are absent and late-stage clinical trials show only moderate success. In CHC, DAA-cured patients with advanced fibrosis remain at risk for HCC[2].


Here, the inventors have shown that liver injury in major viral and metabolic etiologies of liver diseases and HCC (CHC and NASH) results in similar epigenetic footprints and transcriptional changes associated with liver disease progression and HCC risk (FIG. 1-2). This finding is in line with the clinical and pathological observation that CHC and NASH share many phenotypes such as steatosis, insulin resistance, inflammation and fibrosis [43] and that HCCs of CHC and NASH exhibit similar deregulated pathways and genetic footprints[44, 45]. These observations also indicate that HCV infection may serve as a model for understanding progression of liver disease progression and hepatocarcinogenesis in NASH.


Based on these analyses the inventors identified a set of 1693 commonly changed genes that was associated with significantly shorter survival and a significantly earlier HCC development than those with transcriptionally intact liver suggesting that this gene set (1693-gene signature) enables to predict HCC risk and survival. To assess transcriptional changes that were associated with the presence of advanced fibrosis (F3-4), the inventors intersected liver tissues with and without advanced fibrosis. Using this approach, the inventors found that a large fraction of the epigenetically modified genes appeared to be linked to the presence of advanced fibrosis. Furthermore, the more prevalent dysregulation in patients with NASH-related advanced fibrosis defined as F3 or F4, compared to those with mild fibrosis defined as F0 or F1 (FIG. 1) suggests that this gene set may also associated with fibrosis progression and predict progression of fibrotic liver disease.


The signature of 1693 genes as well as condensed intersected gene set of 25 genes with highest prediction of HCC, termed “prognostic epigenetic signature” (PES) may serve a biomarker to predict liver disease progression, HCC risk and survival in patients. Collectively, the inventors' validation analysis in a second cohort suggests the validity of this approach. The detection of the PES in patient liver tissue by a commercially available and FDA approved technology (nCounter, Nanostring) demonstrates that the PES can be used to detect risk of disease progression of fibrotic liver disease and HCC in clinical material (FIG. 2). The detection of a protein corresponding to a PES gene in the blood of an animal model for liver disease (FIG. 2) opens a perspective to develop a minimal or non-invasive blood-based assay to predict liver disease progression, HCC risk and survival in patients with liver disease.


Furthermore, the inventors' data across models demonstrate that inhibition of disease-induced epigenetic changes robustly inhibits gene expression associated with liver disease progression and HCC risk and markedly and significantly inhibits hepatocarcinogenesis in a state-of-the-art in vivo model for NASH-induced HCC (FIG. 5). Collectively, these data demonstrate that epigenetic modifications are a target for treatment of advanced liver disease and HCC prevention. HCC prevention in patients with advanced liver fibrosis is likely the most effective strategy to improve patient survival, because tumor recurrence after surgical treatment is frequent, and therapeutic approaches for advanced disease remain unsatisfactory. Approved therapies for NASH and fibrosis are absent and late-stage clinical trials show only moderate success. In CHC, DAA-cured patients with advanced fibrosis remain at risk for HCC. Addressing this key unmet medical need, the inventors identify BRD4 as a candidate target and BRD4 inhibitor JQ1 as a candidate compound for treatment of liver fibrosis and HCC prevention.


There is an unmet technical need for experimental systems modeling human disease-specific gene expression to understand liver disease biology and hepatocarcinogenesis and enable drug discovery for treatment of advanced liver disease and HCC. Here we addressed this need by the development of a simple and robust liver cell-based system that models gene expression of patients with fibrotic and carcinogenic liver disease caused by HCV and NASH—two major etiologies of advanced liver disease progressing to HCC. Our findings demonstrate the clinical 1693 gene signature and the 25 gene subset (PES) can be experimentally modeled in a cell-based model (cPES). The cPES model offers opportunities to discover compounds for treatment of chronic liver disease treatment and HCC across the distinct liver cancer etiologies, in a fast-track high-throughput screening format as shown for JQ1 or Nizatidine. The innovation of the cPES model is its read-out of a clinically identified cPES predicting disease progression and HCC risk, which enables drug and target discovery for prevention and treatment of liver disease, fibrosis and HCC. The translatability of the compounds identified by the cPES assay is shown by in vivo validation of bromodomain-4 inhibitor JQ1 in a state-of-the-art mouse model for liver disease and hepatocarcinogenesis where reversal of the PES poor prognosis/HCC high risk status (shown for both the 1693 signature and the 25 subset, FIG. 8) by JQ1 was associated with inhibition of liver disease progression, improvement of liver fibrosis and reduced HCC development.


Tables









TABLE S1







Clinical data of patients included in epigenetic analyses using ChIP-seq (related to FIG. 1).



















Liver

Viral
METAVIR
Fibrosis
Antiviral
Viral load


Group
Gender
Age
disease
Tumor
genotype
grade
stage
treatment
(log10 IU/ml)



















Controls
F
55
Minimal
No
N/A
N/A
F0
N/A
N/A





hepatitis


Controls
M
46
Minimal
No
N/A
N/A
F0
N/A
N/A





hepatitis


Controls
F
40
Lobular
No
N/A
N/A
F0
N/A
N/A





hepatitis


Controls
F
53
Minimal
No
N/A
N/A
F0
N/A
N/A





hepatitis


Controls
M
56
Lobular
No
N/A
N/A
F0
N/A
N/A





hepatitis


Controls
F
58
Minimal
No
N/A
N/A
F0
N/A
N/A





hepatitis


HCC w/o
F
71
No
HCC
N/A
N/A
F0
N/A
N/A


liver


disease


HCC w/o
M
66
No
HCC
N/A
N/A
F0
N/A
N/A


liver


disease


HCC w/o
F
65
No
HCC
N/A
N/A
F0
N/A
N/A


liver


disease


NASH
M
65
NASH
HCC
N/A
N/A
F1
N/A
N/A


NASH
M
84
NASH
HCC
N/A
N/A
F1
N/A
N/A


NASH
M
78
NASH
HCC
N/A
N/A
F1
N/A
N/A


NASH
M
27
NASH
No
N/A
N/A
F4
N/A
N/A


NASH
M
63
NASH
HCC
N/A
N/A
F4
N/A
N/A


NASH
M
73
NASH
HCC
N/A
N/A
F4
N/A
N/A


NASH
M
76
NASH
HCC
N/A
N/A
F4
N/A
N/A


NASH
F
65
NASH
No
N/A
N/A
F4
N/A
N/A


NASH
F
47
NASH
No
N/A
N/A
F4
N/A
N/A


NASH
F
68
NASH
No
N/A
N/A
F4
N/A
N/A


CHC
M
52
CHC
No
1a
A3
F3
Naïve
5.82


CHC
M
54
CHC
HCC
1b
A1
F4
Relapse to
4.64










SOF/DCV/RBV


CHC
M
68
CHC
HCC
2a
A3
F3
Naïve
5.40


CHC
F
48
CHC
No
3a
A3
F4
Naïve
6.06


CHC
M
65
CHC
No
1b
A2
F4
Naïve
6.35


CHC
M
51
CHC
HCC
3a
A2
F4
Relapse to
6.58










SOF/RBV


Cured
M
58
Cured
HCC
1a
A0
F4
SOF/LDV
Undetectable


CHC


CHC


Cured
F
79
Cured
HCC
1b
A2
F4
DCV/ASV
Undetectable


CHC


CHC


Cured
M
63
Cured
HCC
2a
A2
F4
SOF/RBV
Undetectable


CHC


CHC


Cured
M
69
Cured
HCC
1b
A2
F3
DCV/ASV
Undetectable


CHC


CHC


Cured
M
73
Cured
HCC
1b
A2
F3
DCV/ASV
Undetectable


CHC


CHC


Cured
M
75
Cured
HCC
1b
A2
F3
SOF/LDV
Undetectable


CHC


CHC





Fibrosis was staged according to Kleiner score for NASH and METAVIR score for all the other etiologies. METAVIR score was used for histological grading of the activity of HCV infection.


ASV = asunaprevir, CHC = chronic hepatitis C, DCV = daclatasvir, HCC = hepatocellular carcinoma, HCV = hepatitis C virus, LDV = ledipasvir, N/A = not applicable, NASH = non-alcoholic steatohepatitis, RBV = ribavirin, SOF = sofosbuvir.






















TABLE S2








Liver

Viral
METAVIR
Fibrosis
Antiviral
Viral load


Group
Gender
Age
disease
Tumor
genotype
Grade
Stage
treatment
(log10 UI/ml)
























Spheroids
M
72
NASH
HCC
N/A
N/A
F4
N/A
N/A


Spheroids
M
83
No
HCC
N/A
N/A
F1
N/A
N/A


Spheroids
M
72
NASH
HCC
N/A
N/A
F4
N/A
N/A


Spheroids
M
65
Cured
HCC
3
A1
F1
PEG IFN and
Undetectable





CHC




RBV


Spheroids
F
28
NAFLD
HCA
N/A
N/A
F0
N/A
N/A
















TABLE S3







1693 gene-signature also referred as PES Extended. Epigenetic


(H3K27ac) log2FCs of 1693 common genes in NASH and CHC


patients with similar significant epigenetic modifications


and corresponding transcriptional changes. Negative


changes indicate good prognosis genes while positive


changes indicate poor prognosis genes











Gene
NASH
HCV















DPPA4
−0.99149595
−1.50988763



RP11-423H2.1
−0.94754738
−1.48155106



ABCC6P2
−1.24512898
−1.44208662



KCNN2
−0.76184643
−1.39228038



CLRN1-AS1
−0.96441909
−1.3557784



RP11-403I13.5
−0.85779975
−1.26410861



GYG2
−0.69968025
−1.26305098



RP11-205M3.3
−0.66576087
−1.19639311



AC114730.3
−0.95312175
−1.15783489



U91319.1
−0.59765221
−1.15552389



HSD17B3
−0.93519793
−1.15249858



CES5A
−0.58376485
−1.15154589



PZP
−0.69107133
−1.14231349



ASXL3
−0.43301035
−1.13917046



RP3-475N16.1
−1.13779469
−0.98193217



AGXT
−1.12923854
−0.75283994



KCNK17
−0.90529918
−1.124968



HORMAD2
−1.09406334
−1.11939868



CAPN3
−0.85622675
−1.11518713



RP11-164J13.1
−0.85622679
−1.11518708



GNMT
−1.1093108
−1.01696047



NEU4
−0.9270435
−1.10879394



SLC6A13
−0.90009565
−1.09119231



RP11-626H12.1
−0.84179363
−1.07827663



GCK
−1.06523593
−0.86809113



KANK4
−0.74251028
−1.0564263



PPP1R1A
−0.7017774
−1.03625106



LPA
−0.49306007
−1.0169621



CNDP1
−0.63792646
−0.9987607



ATAD3C
−0.99811532
−0.83210312



CYP1A2
−0.98668091
−0.81786809



AOC1
−0.53624729
−0.98432856



MAD1L1
−0.97826581
−0.87221391



CHRNA4
−0.81746823
−0.96924072



RP11-261N11.8
−0.81746808
−0.96924071



ESPNL
−0.94309271
−0.70166788



TMTC1
−0.4180584
−0.94205862



CTNNA3
−0.42221582
−0.94007736



GSTA2
−0.93792451
−0.88896097



RP11-168L7.1
−0.48701285
−0.93286311



ACSM2B
−0.91701906
−0.89974648



MROH7
−0.89045029
−0.91423505



SLC2A4RG
−0.9095737
−0.59876869



LIME1
−0.90957369
−0.59876869



NAT2
−0.48889312
−0.90882634



MME
−0.78982822
−0.90698252



APOC3
−0.89246412
−0.45008406



APOA1
−0.89246411
−0.45008404



GCGR
−0.89023552
−0.62501281



ACADS
−0.78259387
−0.88482951



IGFALS
−0.88450169
−0.6259388



CPNE6
−0.87891263
−0.80760341



CYP2E1
−0.73994513
−0.87852408



RP4-601P9.2
−0.77082548
−0.87729331



THOP1
−0.86939272
−0.74055984



GCDH
−0.86451674
−0.61958447



FAM151A
−0.83402025
−0.85612392



LINC00844
−0.64764145
−0.84587488



AOX1
−0.43160766
−0.84293406



TBX3
−0.63799608
−0.84108221



TRIM55
−0.41269109
−0.84011324



SLC22A25
−0.61387539
−0.83916424



RBP4
−0.83168116
−0.72002451



RP11-6B4.1
−0.48612421
−0.82930402



PRODH2
−0.82671595
−0.78277324



PCOLCE2
−0.67769587
−0.8229104



CXXC4
−0.49948404
−0.82209373



ORM2
−0.48125488
−0.82026193



TRPC5
−0.43558564
−0.81958049



GPR88
−0.81941466
−0.61700657



CNPY3
−0.81711475
−0.71387346



PPP1R32
−0.81701208
−0.54806826



FITM1
−0.6639242
−0.81316963



C1orf226
−0.72632656
−0.81225523



PDLIM1P4
−0.44372511
−0.81068592



RGN
−0.8093521
−0.64054053



C3P1
−0.67831697
−0.80805497



ETNK2
−0.80482527
−0.67150957



CES1P1
−0.79369268
−0.80408941



NAGS
−0.80097203
−0.71944772



ZGPAT
−0.79965053
−0.51234221



FADS6
−0.73288221
−0.79342869



HAO2-IT1
−0.59955733
−0.79336794



KBTBD11
−0.40521894
−0.79100922



MAGI2-AS3
−0.35584842
−0.78285799



SLC7A9
−0.78097086
−0.76962553



GFRA1
−0.55440634
−0.78061658



CTD-2529021.2
−0.53112617
−0.78012415



SNTG1
−0.55097541
−0.77969493



RP11-113122.1
−0.7130455
−0.77938329



MEX3A
−0.522985
−0.77832605



TYK2
−0.65803804
−0.7777852



MOGAT2
−0.71494902
−0.77733915



Y_RNA
−0.57640779
−0.77705699



SMO
−0.69834739
−0.77436359



RP11-475O6.1
−0.49405245
−0.77418792



RP11-115J16.1
−0.55973102
−0.77241533



RP11-417L19.2
−0.77042498
−0.62416275



ALDH1L1-AS2
−0.63925942
−0.77040614



AR
−0.59966299
−0.76993595



WFIKKN1
−0.76945835
−0.60842709



FAM35BP
−0.72495655
−0.76611146



RP11-38L15.8
−0.72495294
−0.76610895



CYP2D6
−0.76392889
−0.54764712



ADH4
−0.62470979
−0.762872



SERPINC1
−0.64231174
−0.75788513



GPER1
−0.73874659
−0.7562845



FAM99B
−0.75424502
−0.63999416



TSC2
−0.75369796
−0.6199147



RP11-122K13.7
−0.75356381
−0.54125037



PRAP1
−0.75356381
−0.54125041



FUOM
−0.75356381
−0.54125046



CHAD
−0.74741586
−0.49513365



APOC2
−0.7450738
−0.54355247



SLCO1B3
−0.58591714
−0.7442032



ALDH1L1
−0.59999491
−0.74407132



FMO3
−0.49424232
−0.74299001



TM6SF2
−0.73970533
−0.62457193



CAMSAP3
−0.7391082
−0.64069753



RP11-403I13.4
−0.53561344
−0.73909758



RP11-7F17.3
−0.73628466
−0.7269955



RP11-830F9.5
−0.7359723
−0.57756223



RP11-119D9.1
−0.66797538
−0.73584138



ECHDC3
−0.73574499
−0.64695488



GJB1
−0.73271966
−0.71216975



GSTA7P
−0.69554599
−0.72836277



C11orf95
−0.66759182
−0.72831986



MTND4P20
−0.53622291
−0.72807145



LINC01018
−0.72663526
−0.4670925



CTD-2227E11.1
−0.72581509
−0.72646364



HAGH
−0.7241312
−0.56129832



RP11-372E1.4
−0.48838126
−0.72382996



RP11-706C16.7
−0.72151361
−0.67126525



JAKMIP2
−0.59190911
−0.71988615



AP006216.5
−0.71728566
−0.60883583



HPX
−0.53134133
−0.71341157



ALB
−0.61593953
−0.71214067



RP5-881L22.6
−0.71205592
−0.62633386



PLEK2
−0.58279018
−0.71204221



HGFAC
−0.51325387
−0.71165281



ASB13
−0.70086639
−0.71154238



GSTA1
−0.71032899
−0.64856362



DGAT2
−0.70679534
−0.70974109



NAT1
−0.70961995
−0.68535333



RP1-152L7.5
−0.60024854
−0.7088288



PLGLA
−0.52861767
−0.70862097



CBLN4
−0.68430856
−0.70843115



AASS
−0.56644207
−0.70571741



CYP4A11
−0.705453
−0.56334321



MIR5589
−0.53586591
−0.70311148



GALK1
−0.6524941
−0.70208265



RP11-260M19.2
−0.7011436
−0.6485646



AC005077.7
−0.46807058
−0.7006907



EFNA2
−0.49300466
−0.69998303



LYNX1
−0.69971324
−0.67462418



SPSB3
−0.69903937
−0.46642679



KCNMA1
−0.55430532
−0.69530983



C10orf11
−0.29734433
−0.69480888



RP11-659E9.2
−0.66184955
−0.69454529



CECR2
−0.54792984
−0.69282446



ADRA1A
−0.4610272
−0.68963291



APOA5
−0.68897857
−0.46835311



IGF2
−0.68669975
−0.61636773



INS-IGF2
−0.68669973
−0.61636774



AADAT
−0.50497899
−0.68563358



CTD-2587M2.1
−0.68322033
−0.65519024



SLC10A1
−0.68208719
−0.60260581



TMPRSS6
−0.67892758
−0.46227989



CTC-575D19.1
−0.50301008
−0.67783699



SCP2
−0.54729091
−0.67775912



NR1I2
−0.67700905
−0.62030923



ABAT
−0.33331643
−0.67659891



GS1-124K5.11
−0.6751906
−0.64925827



ECHDC2
−0.54473282
−0.67350042



PON3
−0.58047417
−0.6721999



HAO2
−0.58929896
−0.6716787



SLC22A7
−0.66730949
−0.51135093



SLC9A3R2
−0.66600375
−0.49863254



GRHPR
−0.6657719
−0.47558544



SLC25A47
−0.66548534
−0.44343802



CFHR5
−0.39484139
−0.66518336



PLG
−0.52855394
−0.66518177



AZGP1
−0.62395669
−0.66494299



PCSK9
−0.60364697
−0.66493919



NTHL1
−0.66491983
−0.49255849



APOC1
−0.66305233
−0.48365484



APOE
−0.66305233
−0.48365476



AZGP1P1
−0.66194605
−0.54918409



F2
−0.46835274
−0.66110168



DFFB
−0.61016315
−0.66016317



MAT1A
−0.47979927
−0.65852281



EVPLL
−0.54608141
−0.6559937



MFSD3
−0.65447539
−0.44261957



GPT
−0.65447539
−0.44261959



SMLR1
−0.52661369
−0.6541607



PPP1R1C
−0.48262948
−0.65398528



CTD-2517M22.14
−0.65335043
−0.4442219



SULT1A1
−0.65307806
−0.54881671



ST3GAL6
−0.29637856
−0.6524712



SLC25A34
−0.65212305
−0.54308214



MGMT
−0.46699718
−0.65200609



ZNF511
−0.65139548
−0.4622824



TMEM105
−0.55302581
−0.65100671



HSD17B10
−0.65077375
−0.54606299



RP3-339A18.6
−0.65077365
−0.54606314



SERPINF2
−0.61094679
−0.65017548



FBLN7
−0.65001246
−0.38974033



SLC39A5
−0.64976858
−0.55007742



SYAP1
−0.4535541
−0.64927048



RP13-650J16.1
−0.6478358
−0.3982245



DCXR
−0.64783579
−0.39822448



TPCN2
−0.64773178
−0.59461018



PON1
−0.59295438
−0.64760568



FAHD1
−0.64633858
−0.48634266



FOXP2
−0.33860001
−0.64592897



AZGP1P2
−0.64485418
−0.53287999



TRABD2B
−0.47722253
−0.64321508



PROX1-AS1
−0.33832987
−0.64270413



C2orf72
−0.5594156
−0.6418142



GNA11
−0.57685342
−0.64092872



HAAO
−0.6387934
−0.45134397



APOH
−0.43648694
−0.63846139



THAP3
−0.50147004
−0.63719817



SLC38A3
−0.63662377
−0.36577035



AP006285.7
−0.63650096
−0.51105337



RP11-223I10.1
−0.57321173
−0.6353221



MSRB1
−0.4839175
−0.63462722



SEMA4G
−0.63420912
−0.46527582



UGT2B7
−0.34735527
−0.63379328



COL18A1
−0.633764
−0.48613968



TTR
−0.60446147
−0.63364811



GC
−0.29478957
−0.6335266



SLC6A12
−0.6333656
−0.45859746



MT1X
−0.44253318
−0.63240484



HPGD
−0.4128829
−0.63133765



SKP2
−0.35220983
−0.62910207



SULT1E1
−0.40411073
−0.62873206



GOT2
−0.62852963
−0.53663294



PROX1
−0.35402263
−0.62818618



LCAT
−0.62813838
−0.51929613



TP53I13
−0.62703429
−0.37204121



CES3
−0.58736479
−0.626415



KLF15
−0.62635639
−0.45928035



BHMT
−0.62591419
−0.55159714



HSD17B6
−0.52637047
−0.62578294



CYP2C8
−0.45076188
−0.62565461



MASP2
−0.62540411
−0.45429021



FTCD
−0.62522253
−0.38500405



ABCC6P1
−0.62509976
−0.38452141



TDO2
−0.35564566
−0.62458298



SEPP1
−0.39355054
−0.62306905



PSAT1
−0.54753136
−0.62300561



AC016768.1
−0.38420885
−0.62272919



ESRP2
−0.6218496
−0.48248855



REXO1
−0.56277739
−0.62150134



BCKDHB
−0.62123979
−0.4713873



WNK3
−0.62106763
−0.34570911



GYS2
−0.41303876
−0.62103511



SULT1A2
−0.62028062
−0.48991151



TOMM40
−0.61989376
−0.43165585



GRB14
−0.4458305
−0.61988769



ALDH7A1
−0.46238695
−0.61876846



SEC14L4
−0.61755403
−0.41089817



MLXIPL
−0.6175478
−0.54816044



RAC3
−0.61724767
−0.35175161



NUGGC
−0.44890558
−0.61652604



F7
−0.61648164
−0.50799424



RTP3
−0.61626652
−0.54756019



CES1
−0.61619799
−0.41731858



RFNG
−0.61435967
−0.50350499



GPS1
−0.61435961
−0.50350491



PPP1R16A
−0.61345434
−0.41105207



TTBK1
−0.60395821
−0.61324208



KLHDC10
−0.61303155
−0.60010566



MYO15A
−0.61245206
−0.50874414



RP5-834N19.1
−0.51365436
−0.61200935



GAMT
−0.61187939
−0.36664478



IYD
−0.50358548
−0.61132638



MPST
−0.6108748
−0.54581605



RP11-418J17.3
−0.57473442
−0.61052084



CPN2
−0.48459523
−0.6103631



PSMB7
−0.40820418
−0.61021229



PPARA
−0.6100155
−0.52676745



SPP2
−0.56862656
−0.60999811



HFE2
−0.46933974
−0.60889644



DMRTA1
−0.51210504
−0.60876512



SORD
−0.58079901
−0.60821283



FAM99A
−0.608083
−0.52127727



XAB2
−0.60789085
−0.53251592



GPRC5C
−0.60748968
−0.58039232



PKD2
−0.44771588
−0.6074226



ACOT6
−0.60734884
−0.41927042



COX10-AS1
−0.53103449
−0.60731393



ST18
−0.40357472
−0.6066086



NRBP2
−0.6050793
−0.55679106



ABCC11
−0.40158633
−0.60456873



PGRMC1
−0.47252679
−0.60425638



PLIN4
−0.60248646
−0.60349035



FES
−0.42565685
−0.60271729



SLC45A3
−0.38899675
−0.60209738



TMEM176A
−0.46405227
−0.60127865



MBL2
−0.53147691
−0.60088917



SLC16A2
−0.33244141
−0.60064312



ADH1B
−0.43132286
−0.60005989



NOS1AP
−0.40807855
−0.59979899



SLC44A1
−0.36490248
−0.59952296



TDGF1
−0.41829492
−0.59947195



ACSM5
−0.4846508
−0.59940731



DHTKD1
−0.59913906
−0.4510699



ANPEP
−0.39222731
−0.59797437



AP000695.6
−0.59793891
−0.58609996



TMEM110-MUSTN1
−0.48091903
−0.59739318



MIR3646
−0.5959499
−0.52518315



NUDC
−0.59416921
−0.54419999



TMEM176B
−0.45821951
−0.59377894



DGAT1
−0.59367306
−0.38374643



CNTLN
−0.38339951
−0.59294026



ASGR2
−0.57713067
−0.59260218



NLRP14
−0.47829452
−0.59257624



RAVER1
−0.58965445
−0.56794636



PLIN5
−0.43688193
−0.58939783



RAPSN
−0.44810686
−0.58914135



KHK
−0.58850678
−0.47178375



NBPF13P
−0.52308524
−0.58820299



CEACAM22P
−0.58759132
−0.5714708



SLC43A1
−0.58716714
−0.48673092



HNF1A
−0.58703441
−0.43191851



CMYA5
−0.46678244
−0.586006



PQLC1
−0.51128552
−0.58518879



LRRC3
−0.58506819
−0.33908631



LRRC3-AS1
−0.58506818
−0.33908633



CHID1
−0.52113529
−0.58487534



KLKB1
−0.49699917
−0.58477479



CTB-50L17.14
−0.42648991
−0.58312503



HSD17B14
−0.58311868
−0.52414515



MGST1
−0.44586517
−0.58266921



ARID3C
−0.58266304
−0.51941336



CAT
−0.58201229
−0.48705715



RP11-252E2.2
−0.58143053
−0.56129588



SLC22A10
−0.53408945
−0.58121634



ACOX2
−0.5805449
−0.51146067



RP11-696N14.1
−0.44797812
−0.58037082



GLYAT
−0.41431923
−0.57973952



NR2F6
−0.5793919
−0.40638654



RNF128
−0.36331509
−0.57910884



C1orf115
−0.49538995
−0.57895323



SNAPC4
−0.57830369
−0.36224395



SNED1
−0.57740037
−0.40034854



PNPLA3
−0.5771948
−0.50713825



SCG5
−0.50820222
−0.57715739



NIT2
−0.52382134
−0.57681417



TST
−0.57610113
−0.47748132



GGACT
−0.29750282
−0.57565388



GSTZ1
−0.57416671
−0.49594461



MRPL43
−0.57393552
−0.38562571



SLC27A5
−0.57384955
−0.36274605



BCAT2
−0.57362287
−0.4821496



POLE
−0.5734815
−0.36457824



SERPINA4
−0.45149394
−0.57326362



ABCG8
−0.57311013
−0.43992538



TEF
−0.57245391
−0.41824675



LBX2
−0.54741405
−0.571731



LBX2-AS1
−0.54741406
−0.57173079



RP11-523H20.3
−0.54741405
−0.57173062



BPHL
−0.37664424
−0.57086038



PACSIN3
−0.51016493
−0.569775



ASPG
−0.5695377
−0.44994196



SERPINA5
−0.37963361
−0.56949765



CA14
−0.56920372
−0.47864338



GGH
−0.30389191
−0.56847041



AKRID1
−0.46639569
−0.56766263



HNF1A-AS1
−0.56746377
−0.42809642



PKD1
−0.56703768
−0.35638666



C8orf82
−0.56627989
−0.3824422



TTC36
−0.55970467
−0.56589728



CLDN14
−0.51014848
−0.5653727



PROC
−0.46263394
−0.56342543



HNF4A
−0.56170072
−0.52228426



KCTD21-AS1
−0.37965635
−0.56160309



NDUFA6-AS1
−0.56092034
−0.38097628



IVD
−0.56033217
−0.43510994



SLC25A10
−0.55948616
−0.36553108



DNAJC12
−0.40517798
−0.55921823



ITIH4
−0.48430675
−0.55896096



RP5-966M1.6
−0.48430678
−0.5589609



CBS
−0.55818014
−0.49263627



VIL1
−0.55804691
−0.50261453



FTCDNL1
−0.55759976
−0.42851501



TMEM25
−0.53650468
−0.55661602



ALAD
−0.55652649
−0.4414033



POMT2
−0.55575725
−0.47829184



SLC19A1
−0.55514766
−0.39980198



AK4
−0.37776613
−0.55510821



MOGAT1
−0.46931272
−0.55422142



PCYT2
−0.55361709
−0.37385382



RP4-758J18.2
−0.55342691
−0.33293506



CCNL2
−0.5534269
−0.33293503



QDPR
−0.41312051
−0.55337415



GNAO1
−0.40709817
−0.55335288



SAT2
−0.55328098
−0.32899268



NUDT16
−0.49638324
−0.55146716



ABHD15
−0.55087095
−0.2706481



RP3-402G11.26
−0.55049535
−0.42967261



SELO
−0.55049531
−0.42967262



TMEM110
−0.4523131
−0.54941938



AMBP
−0.5332563
−0.54935059



PHGDH
−0.39295342
−0.54867972



ALKBH2
−0.53423372
−0.54812573



XYLB
−0.54782416
−0.46845163



TTC31
−0.54772171
−0.40042391



C1R
−0.36476152
−0.54761051



STEAP3
−0.37738984
−0.54733639



PMM1
−0.54627888
−0.28253201



C16orf13
−0.54570672
−0.32688719



ITIH1
−0.44793049
−0.54564737



SHMT2
−0.54552397
−0.52298954



SH3PXD2A
−0.44187639
−0.54539559



ASL
−0.54456235
−0.52231389



NDUFS7
−0.54417121
−0.29338413



NAPEPLD
−0.42271619
−0.54372659



TCEA3
−0.45619391
−0.54341951



SUGP1
−0.54098686
−0.44638745



VTN
−0.54075469
−0.443821



SHANK3
−0.54064551
−0.39602555



ECHS1
−0.54056713
−0.41448155



MFAP3L
−0.30652926
−0.53937362



MRPL23
−0.53932617
−0.50045197



MIR126
−0.53192407
−0.53928628



AGXT2
−0.32841234
−0.53910873



SLC25A42
−0.53807907
−0.36450899



MARC1
−0.38312721
−0.53739454



ELP3
−0.36883554
−0.53613072



DAB1
−0.32375416
−0.53608108



TMEM37
−0.3196043
−0.53540935



GULOP
−0.53516416
−0.40178378



ASPSCR1
−0.53480527
−0.32653753



GNE
−0.45806797
−0.53442947



SLC25A18
−0.50350814
−0.53424868



SLC46A1
−0.53407199
−0.42455711



SFXN5
−0.496014
−0.53339116



C3
−0.32496828
−0.53334588



ICAM3
−0.5330691
−0.47745957



TTPAL
−0.53285799
−0.4357361



CTNS
−0.53240924
−0.37648291



PRKAG2-AS1
−0.5310375
−0.31160358



ABCG5
−0.5300833
−0.41424045



PROZ
−0.52983523
−0.46086358



SUOX
−0.47224945
−0.52936307



FAM53A
−0.52900374
−0.37347314



SPTBN2
−0.41482506
−0.52846757



CASC10
−0.46069097
−0.52801376



LCN12
−0.52755957
−0.2416872



C8G
−0.52755957
−0.2416872



SIGMAR1
−0.52753124
−0.29635608



MLYCD
−0.52746589
−0.40467836



CPPED1
−0.45585123
−0.52692497



APOF
−0.39252114
−0.52685065



ABCC2
−0.33069775
−0.526547



HPN
−0.52571552
−0.45549562



PKLR
−0.52544006
−0.47379075



RAD54L2
−0.52459046
−0.48270611



RP5-875H18.4
−0.52423609
−0.39216451



CMBL
−0.50367322
−0.52370941



RP11-390F4.2
−0.33177001
−0.52181134



SLC30A10
−0.38143031
−0.52019655



ACADSB
−0.35733082
−0.51715283



ITCH
−0.36434796
−0.51632268



RP11-1151B14.3
−0.39617577
−0.51550649



RP11-661A12.7
−0.51475978
−0.36138695



SLC13A5
−0.44023114
−0.51468042



TMEM220
−0.44426325
−0.51422255



PRKAG2
−0.51333418
−0.37661849



TADA1
−0.51288083
−0.42028579



ASGR1
−0.5127561
−0.48431379



DOLPP1
−0.51267896
−0.41169338



FXYD1
−0.51259674
−0.34985605



PCK2
−0.51153711
−0.38174507



DHRS4
−0.51151351
−0.35312145



PGLYRP2
−0.51129907
−0.43756266



LPAL2
−0.47613199
−0.51093138



AC142528.1
−0.50993273
−0.47855001



AGPAT2
−0.50987929
−0.50145303



PEBP1
−0.50957342
−0.36946543



HIBADH
−0.40473344
−0.50932067



CYP4F3
−0.50927874
−0.48591038



RGS12
−0.41474877
−0.50878816



TNFAIP8L1
−0.50681237
−0.31462028



RP11-407B7.1
−0.36462574
−0.50655877



DCTD
−0.38206799
−0.5062648



MRPS22
−0.42399493
−0.50613564



DBT
−0.35164339
−0.50496922



PAOX
−0.50466519
−0.27578744



PAIP2B
−0.50458813
−0.43717477



MPC1
−0.32317742
−0.50313087



NDRG2
−0.38817639
−0.5029702



PEMT
−0.47849196
−0.50282158



ALDH8A1
−0.30685945
−0.50167267



TSSC1
−0.41604199
−0.50166131



AP001065.15
−0.50121439
−0.43630473



TSPAN9
−0.39052741
−0.5010383



FGFR4
−0.50079069
−0.40955859



ZNF444
−0.49924193
−0.47143732



LINC00094
−0.49907735
−0.34613862



FAM73B
−0.49864561
−0.41579389



TTPA
−0.29893692
−0.49838552



CTD-2545H1.2
−0.49794342
−0.4922324



TFR2
−0.49737757
−0.40044049



FLCN
−0.49727171
−0.39699181



ACAA1
−0.49691562
−0.40187225



FURIN
−0.38736648
−0.49665955



SALL1
−0.32368911
−0.49658827



ZNF696
−0.49657629
−0.3440484



RNF126
−0.49601691
−0.33194009



AC004156.3
−0.49601688
−0.33194018



POLR3H
−0.49517761
−0.31785751



GHR
−0.32229072
−0.49490278



ACP2
−0.49474027
−0.46615352



ZNF497
−0.49442209
−0.39183096



ZBTB48
−0.49401346
−0.2997022



FAM20C
−0.49390927
−0.46207081



NAT8
−0.4935748
−0.42309711



HPD
−0.49355526
−0.42777177



ADI1
−0.49351634
−0.42814468



CTA-292E10.6
−0.2790415
−0.49296135



SNHG8
−0.30963332
−0.49265941



BNIP3
−0.49251914
−0.36536377



ZNF517
−0.4917722
−0.46460047



EHHADH
−0.41997315
−0.49164704



RP11-449P15.2
−0.49137643
−0.43785462



GET4
−0.4913764
−0.43785455



TBC1D2
−0.44369124
−0.49087881



SFXN1
−0.45312962
−0.49081025



FBXW11P1
−0.42475793
−0.49075521



TTC6
−0.2733433
−0.49007905



GALT
−0.48939574
−0.32661027



MRPL20
−0.48889795
−0.29298016



RP11-513G11.3
−0.32566644
−0.48866387



ZBTB45
−0.48783977
−0.30485582



EDC3
−0.44603223
−0.48753583



AC009166.5
−0.32444132
−0.48751622



PCBD1
−0.48719245
−0.39835197



RP11-44M6.3
−0.48716407
−0.36623863



LRRC37A5P
−0.4311686
−0.48715786



OSGIN1
−0.48661609
−0.33313549



DEPDC7
−0.3491709
−0.48657689



TMEM82
−0.48639705
−0.40000723



SLC26A1
−0.48606527
−0.39855654



HSBP1L1
−0.35304183
−0.48601142



THRB
−0.29114288
−0.48535447



ENTPD5
−0.35027874
−0.48523689



PKD1L2
−0.46030085
−0.48456053



BDH1
−0.48419263
−0.33955255



SLC25A20
−0.48393904
−0.34051564



RDH16
−0.48359387
−0.4489049



MYD88
−0.48334123
−0.39550524



MPLKIP
−0.48304731
−0.40127274



FBP1
−0.48272264
−0.35558511



SOWAHB
−0.46464072
−0.48157392



FUBP3
−0.48155248
−0.40610461



CYP27A1
−0.41327242
−0.48118186



IL11RA
−0.4798205
−0.3337762



SLC27A2
−0.44706769
−0.47901059



ZNF385B
−0.33023531
−0.47848627



DEAF1
−0.47796184
−0.36825415



POLR2F
−0.47774132
−0.33296713



MMACHC
−0.47712778
−0.41091257



RP11-344P13.4
−0.39852927
−0.47679292



IDUA
−0.47671009
−0.39321773



HDHD3
−0.44181024
−0.47659129



FABP1
−0.30753758
−0.47627108



SCCPDH
−0.45745009
−0.47546018



EPHX2
−0.47481538
−0.43637706



TTC38
−0.474034
−0.28784079



PCDH1
−0.27460496
−0.47387188



C19orf66
−0.47381786
−0.43815769



CFB
−0.35693341
−0.47336005



MTHFD1
−0.46427643
−0.47210587



CYP8B1
−0.32041968
−0.47112259



TRIM24
−0.40642724
−0.46963243



FKBP8
−0.46922264
−0.43147395



PEX6
−0.46908041
−0.33063488



BTD
−0.38310231
−0.46782556



SLC6A1
−0.46749302
−0.33398139



RANBP1
−0.46739615
−0.34553256



RP11-38G5.4
−0.44114597
−0.4670968



TOLLIP
−0.4670631
−0.37155505



LGI4
−0.46690066
−0.30048316



RP11-209K10.2
−0.35233705
−0.46683615



OPLAH
−0.44651345
−0.46490928



SGK2
−0.39416895
−0.46457315



EI24
−0.46454905
−0.3812715



CYP4F11
−0.4083028
−0.46418502



WDR18
−0.40553702
−0.46347861



TOLLIP-AS1
−0.463264
−0.37064645



USP30
−0.45958095
−0.46283748



ABCG2
−0.45366629
−0.46181431



ACACB
−0.35797062
−0.46176925



AHCY
−0.4064863
−0.46103644



ABCC6
−0.43846415
−0.45989323



GLS2
−0.45963971
−0.27880136



AC019181.2
−0.39783467
−0.45961561



ACVR1C
−0.38045717
−0.45891588



F10
−0.45882069
−0.36950754



ZKSCAN1
−0.39867916
−0.45840621



ADCY1
−0.45809579
−0.37976781



CHMP6
−0.42696208
−0.4575594



RPL7AP6
−0.35534184
−0.4563226



SEC14L2
−0.43225002
−0.45577579



C7orf50
−0.45567089
−0.36783366



FAH
−0.36603446
−0.45532692



CLUH
−0.45525342
−0.26882068



PPP6R2
−0.45511075
−0.25961048



C1S
−0.27588469
−0.45447322



FANCC
−0.28011776
−0.45402927



SLC25A13
−0.45387704
−0.43150595



RAPH1
−0.31973935
−0.45347927



RNF215
−0.45336741
−0.45261625



PAH
−0.36803375
−0.45335418



GCSH
−0.45281308
−0.34995596



LHPP
−0.45207122
−0.33877499



TFDP2
−0.45187246
−0.39525617



KDM8
−0.39823294
−0.45164846



ACSF2
−0.45161505
−0.28630564



RAB26
−0.45154017
−0.29370101



SMOC1
−0.40655165
−0.45031917



AL161668.5
−0.4499014
−0.32396975



TPPP2
−0.44990139
−0.3239697



IPO5
−0.26741723
−0.44948608



ZC3H7B
−0.44913537
−0.3385584



RP4-584D14.7
−0.3750442
−0.44912805



RARRES2
−0.3750443
−0.44912805



POLM
−0.44893481
−0.29853335



RP11-713M15.2
−0.38277897
−0.44866948



GPR146
−0.44865796
−0.38895443



MOCS1
−0.41773577
−0.44792101



SERPIND1
−0.36698026
−0.44786657



TACO1
−0.44688164
−0.37216997



EPHX1
−0.4466512
−0.2775992



SDC2
−0.3101171
−0.44600249



RP11-45M22.4
−0.44589988
−0.30248336



TOP1MT
−0.39726686
−0.44579036



FAAH
−0.44572098
−0.40437451



SLC22A1
−0.35592978
−0.44505431



CTD-2619J13.8
−0.44504645
−0.33025985



PUF60
−0.44404391
−0.29095008



GLYCTK
−0.44377755
−0.35026885



ARFGAP2
−0.44372545
−0.35288168



PXMP2
−0.4433802
−0.24999398



RAB40C
−0.44330146
−0.31355658



PPL
−0.4315543
−0.44327275



ESD
−0.39666646
−0.44284912



IQGAP2
−0.32689737
−0.44264569



DECR2
−0.3407892
−0.44198449



ARMC6
−0.44171579
−0.38459195



POLE2
−0.43139487
−0.44093522



CDO1
−0.44002295
−0.33446279



ITIH3
−0.34223843
−0.43953042



SP5
−0.43825549
−0.42995769



MAL2
−0.32726125
−0.43704003



SMARCA1
−0.29755465
−0.43694811



AP1M1
−0.42285109
−0.43687256



SH2D3A
−0.39439644
−0.43681467



CLSTN3
−0.35954896
−0.43629611



RP11-736K20.6
−0.35310608
−0.43597212



MAOB
−0.35851329
−0.43468652



ACSM3
−0.40360969
−0.43359854



PITPNM2
−0.43183173
−0.40867964



ALDH6A1
−0.43183011
−0.35096677



EPB41L4B
−0.43182827
−0.32919962



SCLY
−0.40008884
−0.43091631



OAF
−0.33562809
−0.43048654



ALDH4A1
−0.28716605
−0.43042383



ARRDC1
−0.43038866
−0.31724026



KCTD21
−0.33341511
−0.43004666



MTSS1
−0.33017069
−0.42971923



RP11-273B20.1
−0.42903237
−0.38342987



RBP5
−0.42903235
−0.38342977



AGL
−0.30940841
−0.42726395



AKT2
−0.42725154
−0.30639023



DHRS1
−0.31698678
−0.42714246



SS18L1
−0.29773655
−0.42702242



LDHD
−0.42515427
−0.42699012



CNGA1
−0.4261871
−0.37338182



CYB5A
−0.30128304
−0.42584528



GPD1
−0.42512576
−0.33581025



CRLS1
−0.38554414
−0.42500853



EEF1D
−0.42455967
−0.27087658



RNF43
−0.33079245
−0.42327577



SND1
−0.41353442
−0.42320194



STARD10
−0.42288169
−0.30011581



UNC119B
−0.2635271
−0.42255029



CYP4F2
−0.36909994
−0.42188912



RAPGEFL1
−0.42174714
−0.38579213



CCS
−0.42145656
−0.35268149



C1RL
−0.28282706
−0.42072201



RABEPK
−0.25830292
−0.42060896



SLC25A1
−0.42051755
−0.29538267



XRCC5
−0.41252298
−0.42007243



RTTN
−0.27426122
−0.42003928



AC091729.9
−0.41998922
−0.30812968



ZFAND2A
−0.41998921
−0.30812963



FAM50B
−0.24568531
−0.41974922



ZCCHC24
−0.3000804
−0.41900341



KIAA1161
−0.41780651
−0.31125164



ORAI3
−0.41675126
−0.2260546



RTKN
−0.37891422
−0.41651837



ARVCF
−0.4158601
−0.33280454



RANBP10
−0.41582233
−0.35862083



GGCX
−0.41520765
−0.4005541



RAI14
−0.28978227
−0.41414754



SEC24B
−0.41410303
−0.40612039



DHRS4-AS1
−0.41357542
−0.28741066



HGD
−0.41354462
−0.39801706



AK2
−0.33886441
−0.41331637



COMT
−0.41291208
−0.40673668



RP11-390F4.3
−0.4128031
−0.37317276



IGSF8
−0.41194622
−0.35958714



CNNM3
−0.40992921
−0.27139126



CDA
−0.36907875
−0.40982203



NIPSNAP1
−0.40921439
−0.27157182



MARC2
−0.29767051
−0.40886411



RMDN2
−0.33596855
−0.40884522



CDHR3
−0.31811406
−0.40828798



CDKN2AIPNL
−0.35830649
−0.40812345



HMGCS2
−0.35195098
−0.40794621



RUNDC3B
−0.40754375
−0.36411206



PAQR9
−0.40581813
−0.34342162



PGM1
−0.29171942
−0.40564516



CLU
−0.33992741
−0.40451622



METTL7B
−0.40440387
−0.36579102



OGFR-AS1
−0.40303212
−0.28290761



OGFR
−0.40303194
−0.28290762



CNP
−0.40300593
−0.27696223



ALDH2
−0.34376265
−0.40235433



SMARCD2
−0.40191315
−0.26016194



SLC47A1
−0.38887493
−0.40078725



MYH14
−0.39185752
−0.40078648



SNTB1
−0.29749725
−0.39967707



ZNF3
−0.39956344
−0.29301597



PHYHD1
−0.36517495
−0.39823507



CSAD
−0.39743692
−0.31170411



ACSL1
−0.38375538
−0.39712276



CLDN15
−0.2855084
−0.39595715



ZER1
−0.39454397
−0.33872364



RP11-384L8.1
−0.39319765
−0.3070985



CMTM8
−0.39319761
−0.30709859



LRP1
−0.29833253
−0.39301776



PKP2
−0.34439876
−0.3926357



SLC25A27
−0.33965267
−0.39108688



CYP39A1
−0.33965247
−0.39108607



RNF220
−0.36030039
−0.39104117



RP5-1033H22.2
−0.30503081
−0.39050236



ECI2
−0.39036176
−0.30879026



SIRT7
−0.38972422
−0.28326125



FZD4
−0.34499709
−0.38933786



SUV39H1
−0.36971855
−0.38888921



TCF7L1
−0.26986858
−0.38839527



CHST13
−0.38814415
−0.32402455



NFIC
−0.38801358
−0.31715258



PC
−0.2713548
−0.38793794



SESN2
−0.3709953
−0.38782191



AFMID
−0.38774641
−0.30584992



NR0B2
−0.36539925
−0.38774243



SLC12A7
−0.38663084
−0.27527243



CAPN5
−0.34570202
−0.38577686



THRB-AS1
−0.34943077
−0.38575153



ABHD6
−0.34257166
−0.38522473



ATXN7L1
−0.26845327
−0.38521028



TALDO1
−0.38502538
−0.30703897



DGCR8
−0.38471087
−0.3773287



ATP5SL
−0.31559414
−0.38440531



ZBTB42
−0.38427243
−0.2922977



AKT1
−0.38427243
−0.29229771



PANX2
−0.38404028
−0.36173835



MTFR1
−0.38367093
−0.24254236



SHMT1
−0.38348468
−0.35373178



GCH1
−0.2959687
−0.38317213



F12
−0.38308371
−0.27951505



MTM1
−0.38247333
−0.29781583



NME4
−0.32377865
−0.38216429



SLCO2B1
−0.38122455
−0.26391129



RASSF7
−0.3811343
−0.293724



RP11-655M14.13
−0.38109626
−0.26735602



TBX10
−0.38109598
−0.26735594



NUDT8
−0.38109581
−0.2673559



PSMA7
−0.38098092
−0.29845841



TRMT2A
−0.38057839
−0.22895339



EEFSEC
−0.34037015
−0.38025914



HLF
−0.32957238
−0.38009922



PEX16
−0.37993452
−0.33492077



PARP10
−0.37981547
−0.21387565



RP11-134G8.7
−0.27602285
−0.37863625



GRTP1
−0.37814196
−0.36530467



HDLBP
−0.37797755
−0.3024235



MAVS
−0.37731114
−0.36557947



EPN1
−0.37682644
−0.27167571



IRF2BP1
−0.37674375
−0.32099143



ASB3
−0.31361875
−0.37647766



TMEM80
−0.37570265
−0.24624656



C16orf70
−0.37492915
−0.31083243



SLC35D1
−0.37436408
−0.27595108



SCAP
−0.37369073
−0.28496227



MDN1
−0.3562244
−0.3736243



ADCK3
−0.29812925
−0.37307645



HSD11B2
−0.3726025
−0.31254558



PHYH
−0.3720753
−0.33485628



MMP15
−0.35668513
−0.37172165



HOGA1
−0.31742346
−0.37107901



RHCE
−0.37080779
−0.30171794



ARL6IP4
−0.37076139
−0.28891513



AQP3
−0.32343107
−0.36985801



LRR1
−0.3287904
−0.36848651



SETD1A
−0.36744264
−0.23242592



TMEM57
−0.3357718
−0.36739329



EPS8L2
−0.36492322
−0.22369652



AP000355.2
−0.36480429
−0.31196501



GPAM
−0.36443184
−0.34811237



FOXA3
−0.36375897
−0.29284569



PIPOX
−0.36276665
−0.28074058



EPHB4
−0.33746387
−0.36213718



TMEM192
−0.27675938
−0.36162899



ANG
−0.25749011
−0.36109385



SMPDL3A
−0.25931705
−0.36022303



NT5DC3
−0.26949837
−0.35751769



WDR81
−0.35673733
−0.25774597



RAP2C
−0.35660216
−0.24521162



RP11-350G8.5
−0.3543378
−0.35485534



EPB41L5
−0.35472404
−0.2812191



CERS2
−0.26745357
−0.35404273



GTF2IRD1
−0.35349659
−0.33576831



PEX19
−0.35337264
−0.34915125



AKAP1
−0.35263918
−0.29265316



SH2D4A
−0.25490705
−0.35212954



NR1H3
−0.35210006
−0.27146195



PDIK1L
−0.35204896
−0.2829924



ANXA9
−0.26745198
−0.35124338



PFKFB1
−0.33473836
−0.35099402



KANK2
−0.35036754
−0.3319646



SHH
−0.32551636
−0.35032606



TMEM101
−0.33732052
−0.34983763



RXRA
−0.34948675
−0.28767448



HPCAL1
−0.28039765
−0.34899215



C1RL-AS1
−0.34870299
−0.3393696



KIF1C
−0.34811672
−0.23372311



IDNK
−0.2652978
−0.34799289



SIVA1
−0.34716386
−0.27226572



ELK1
−0.34650465
−0.30471213



IL6R
−0.34129699
−0.3463338



NEIL1
−0.34551526
−0.32270888



SERPINF1
−0.34534084
−0.33522948



FCGRT
−0.34444097
−0.27204935



AGFG2
−0.34421296
−0.29824866



MUM1
−0.34369254
−0.32853246



ABHD14A
−0.34363545
−0.23778997



CLASRP
−0.34316616
−0.25338292



MLX
−0.34239925
−0.32670861



ACY1
−0.34232231
−0.247427



STARD5
−0.3419298
−0.31524065



FZD5
−0.25822211
−0.3409676



DCAF8
−0.27681872
−0.339734



ZNF408
−0.26236338
−0.33957453



ALG3
−0.3389394
−0.32429392



WIZ
−0.3386708
−0.23583346



BAIAP2L1
−0.26230457
−0.33833424



CTIF
−0.32081451
−0.33504599



MACROD1
−0.33385226
−0.31944701



WWC2-AS2
−0.22097621
−0.3336651



COASY
−0.33200618
−0.31079482



GLTPD2
−0.33175708
−0.27314765



SEPHS2
−0.27031363
−0.3309181



CES2
−0.32990787
−0.24570301



FAM96B
−0.32990787
−0.24570233



SDC1
−0.26936324
−0.32918957



ZBTB39
−0.32865224
−0.32095137



HDAC4
−0.32840301
−0.31694505



SLC23A3
−0.32771937
−0.31415409



XBP1
−0.23846671
−0.32709786



C1orf220
−0.32669137
−0.27036106



AP000253.1
−0.32451248
−0.29401886



SLC35A3
−0.29282936
−0.32197216



PPP1R26
−0.3197786
−0.29937873



PCTP
−0.28365657
−0.3197411



RPS29
−0.27154984
−0.319368



LTB4R2
−0.27227953
−0.31874686



LTB4R
−0.27227964
−0.31874682



KIAA2013
−0.31837726
−0.27583915



SOD1
−0.31814476
−0.30820525



NFYC
−0.31229081
−0.31672619



DDI2
−0.31641086
−0.26843984



PLA2G12B
−0.31627894
−0.27972574



GSDMD
−0.31549845
−0.28092864



C2
−0.31260761
−0.31434771



ENKD1
−0.31330502
−0.30424951



SUN2
−0.31313228
−0.23607547



NUDT7
−0.29642592
−0.31281805



CDON
−0.31268371
−0.26055483



PEX11G
−0.28673975
−0.31256604



UPB1
−0.31139815
−0.27512159



COBL
−0.31078456
−0.27482485



CTNNBIP1
−0.31070486
−0.26971012



FAHD2A
−0.2759954
−0.31009587



RAB40B
−0.27038904
−0.30958601



NAPA
−0.30932566
−0.24080098



ATP11C
−0.30919624
−0.29446512



RBL2
−0.30816824
−0.25066095



TPCN1
−0.2009117
−0.30642959



KLHDC2
−0.25686425
−0.30247648



MCEE
−0.30024145
−0.29215766



SLC37A4
−0.27316758
−0.30000485



VAMP8
−0.29952151
−0.27377672



SLC25A44
−0.29879377
−0.29111812



AKAP8
−0.29806694
−0.27827847



ERMARD
−0.29347634
−0.29781332



NELFB
−0.29745893
−0.24232981



GRINA
−0.29608637
−0.22354455



FAM35A
−0.29523254
−0.26738233



RPL41
−0.29310028
−0.23916321



ZNF490
−0.24853924
−0.29208614



RP4-605O3.4
−0.2906624
−0.23350988



COX14
−0.2906624
−0.2335097



PMF1
−0.22145396
−0.28935479



DNAJC25
−0.2511999
−0.28893162



MTMR4
−0.28516127
−0.28642688



CRTC2
−0.25459398
−0.28468128



MCCC2
−0.28210687
−0.26364444



ZNF787
−0.27950087
−0.21988141



NPRL3
−0.25928478
−0.27888637



RAB11FIP3
−0.25547192
−0.27748997



PLXNB2
−0.2757926
−0.20709931



RP11-1055B8.4
−0.24897767
−0.27466938



TPRN
−0.25973517
−0.27431518



DBI
−0.23974492
−0.26067366



ABCB6
−0.25566735
−0.25991797



COG8
−0.25807848
−0.23033772



SLC27A3
−0.22292407
−0.25561704



RP11-1275H24.1
−0.22375083
−0.25122346



RP11-1275H24.3
−0.22375074
−0.25122324



ZNF689
−0.24985306
−0.24292946



ATXN2
−0.23871843
−0.24756363



OGG1
−0.23787695
−0.24669267



ILK
0.2107524
0.21567035



HIPK1
0.22308137
0.22679421



AFTPH
0.22903256
0.23199635



EZR
0.26048853
0.25396407



ATM
0.25494652
0.26255025



PLEKHA2
0.2728107
0.25542597



DCHS1
0.27428179
0.24121081



C15orf39
0.27940961
0.25906811



GAL3ST4
0.24442711
0.28107799



CASP8
0.28831686
0.28884766



GGPS1
0.27350961
0.2914372



PPARD
0.29422585
0.26209515



PRPF38B
0.28612183
0.29435086



HIVEP2
0.29979044
0.26748027



DENND3
0.26159665
0.30049974



ADD3
0.30430185
0.28750897



RP11-356I2.4
0.27518333
0.30451362



CTC1
0.27179002
0.30572551



CREB1
0.30337455
0.30671961



SSH2
0.30718237
0.28522004



MAP3K1
0.26723477
0.3077578



CACUL1
0.3085782
0.2941355



FGD6
0.3089605
0.23620758



OSTM1
0.29658056
0.31139925



NABP1
0.31071937
0.31259699



SLC43A2
0.28064101
0.31293773



TUBA1C
0.29126926
0.31379851



GNA13
0.31531003
0.26145623



SPAG4
0.31660075
0.31274341



PARP8
0.28475341
0.317782



SYT11
0.32092233
0.32197549



GON4L
0.3209226
0.32197557



RAB34
0.28369033
0.32260509



ARL4A
0.323018
0.3129778



LEPROTL1
0.32585751
0.27928831



YWHAH
0.32625776
0.31678903



HIVEP3
0.29366104
0.32863623



CHMP4A
0.25714653
0.32963386



ARPC5
0.32536411
0.33003866



ANXA11
0.33060593
0.2010745



OGFRL1
0.33488857
0.30733855



KLHL5
0.3353751
0.28553148



IGF1R
0.34046751
0.32825058



COL4A2
0.34215423
0.25903599



PAK1
0.3427117
0.32645573



JUN
0.34682145
0.29406581



MTMR11
0.34716135
0.28582582



LINC00857
0.34786949
0.22936654



PDCD4
0.26620003
0.35243856



ANKRD53
0.31397449
0.3549392



FHL3
0.3431548
0.35544121



CD63
0.3167874
0.35658012



F2R
0.35693987
0.35232893



MAP3K8
0.35769287
0.27357984



SERPINB9
0.31953944
0.3598179



PRDM2
0.28054952
0.35994273



PRKCH
0.36102968
0.27743854



IFFO2
0.36126927
0.34581623



ZNF160
0.35993642
0.36378827



ZNF397
0.31489028
0.36584279



TCP11L2
0.28389699
0.36684095



ACER2
0.36782935
0.30536002



U73166.2
0.36816264
0.32979711



GPRIN3
0.35076587
0.36842184



SERAC1
0.36849956
0.29506972



RNF145
0.36582755
0.36903238



SH3RF3
0.2870755
0.36954186



CTD-2201E18.3
0.36995465
0.33561194



SMURF2
0.30973965
0.37256902



CD47
0.373919
0.36315117



MKL1
0.37531047
0.29102788



MAPRE1
0.35081922
0.37557016



BCL2
0.3620567
0.37762952



ARHGEF2
0.2802985
0.37847804



TSPYL1
0.37911655
0.27570659



RALGDS
0.31588532
0.38045161



USP37
0.38160616
0.34059824



GNA12
0.38340653
0.29021981



RUNX2
0.29206024
0.38402238



IQGAP1
0.3841836
0.37678882



CDC42EP3
0.38492335
0.37741779



CCNG2
0.34678301
0.38542955



PAFAH1B2
0.38586348
0.35567709



DUSP5
0.37846408
0.38624474



RNF24
0.38748492
0.29782783



PLA2G4C
0.38868241
0.37218793



ITGA6
0.28413376
0.3897485



SLC12A2
0.3912081
0.36340859



GYPC
0.30513307
0.39166292



IL2RA
0.39535583
0.32875042



SLC25A12
0.39580534
0.23786379



ZNF304
0.32302879
0.39613419



RAP2B
0.37400913
0.39725167



FAM129B
0.36540402
0.39745065



CAPN2
0.38426856
0.39788697



AAGAB
0.39411787
0.4028782



KIAA1462
0.40346982
0.39022757



SNN
0.29266211
0.40383775



CTB-55O6.12
0.24814694
0.40494538



MDFIC
0.40499853
0.31179508



IGFBP7
0.37855108
0.40553844



PLCD3
0.30730081
0.40569611



NOD2
0.4063656
0.31642647



STK17A
0.3926019
0.40642822



POU6F1
0.38276416
0.40795243



CEP135
0.40805415
0.34136025



ZNF829
0.35517015
0.40811835



AEN
0.38432407
0.40843242



ZNF568
0.33969794
0.40852172



TTC16
0.40948024
0.39201105



IDS
0.37552294
0.40957342



HSPG2
0.3918783
0.41001784



ATP2B4
0.26574319
0.41007285



HELB
0.41035191
0.40435962



FAM49B
0.29091936
0.41106319



AGO2
0.28394163
0.41116859



SYNGAP1
0.28654513
0.41198544



CDC42SE2
0.41240258
0.3792452



LY6G5C
0.38755945
0.41256565



SP110
0.35181251
0.4129386



REL
0.41352048
0.27269062



FAM228B
0.41355544
0.39511166



LUZP1
0.41366119
0.3241621



CD58
0.37465017
0.41459738



TULP3
0.41536548
0.39175604



JAG1
0.41536706
0.27433069



ZNF292
0.41604909
0.30230274



CTTNBP2NL
0.41729261
0.30793738



CCNJ
0.36735682
0.41765825



CCDC28B
0.340358
0.41972829



ZNF512
0.34494758
0.41998657



BBS7
0.38128807
0.42024751



HSPA12A
0.42119491
0.35460429



PRICKLE2
0.4223884
0.2695499



RAVER2
0.42464549
0.39642982



GRIN2D
0.3772624
0.42483366



EGLN3
0.35420715
0.42732412



ZNF614
0.42734074
0.32668887



TIMP2
0.42790695
0.3976555



MXD1
0.42906983
0.33033446



PKDCC
0.36179776
0.42972519



SFMBT2
0.34457148
0.43061116



PLP2
0.43116284
0.37154635



DYRK2
0.34939968
0.43140284



LOXL3
0.33730819
0.43211472



DOK1
0.33730827
0.43211541



TMSB10
0.34648728
0.43295041



EVA1C
0.43400964
0.4169852



SYNJ2
0.43404459
0.37729678



DNAJC10
0.41325387
0.43449638



FZD3
0.43463077
0.36760367



KIRREL
0.4351682
0.41940162



RPS6KA3
0.43588415
0.29224785



ZNF347
0.43610448
0.43305458



HSPBAP1
0.44034637
0.26476308



TP53I3
0.43168036
0.44063386



ANKRD44
0.35421672
0.44114336



STK4
0.30557742
0.44162894



PHACTR2
0.44186311
0.30109068



RP1-111C20.4
0.29870027
0.44232855



HMGN4
0.39458524
0.44312601



ZNF548
0.29203637
0.44325844



ETS1
0.38507175
0.44343685



PDE7A
0.44419666
0.42157149



C1QTNF1
0.44015928
0.44453413



NF1
0.44460792
0.34325888



PMP22
0.44598518
0.4028151



TAGLN2
0.41063153
0.44666745



ANTXR1
0.37101085
0.44800178



NXPE3
0.44813856
0.27467834



UBASH3B
0.35945585
0.44966858



SLC41A1
0.44969093
0.42095754



TMEM217
0.44969829
0.31413917



PPP1R12B
0.45108735
0.26002915



PAG1
0.31164018
0.45144144



LINC00092
0.33776175
0.45248883



ANKRD36C
0.42114693
0.45312528



SLC6A9
0.38816511
0.45316169



QSOX1
0.42971667
0.45443878



HMGCR
0.45463584
0.33868725



PAPOLG
0.45494359
0.42735562



MPP3
0.45501537
0.42775513



AMIGO2
0.37551093
0.45574505



PDE4B
0.45635271
0.33535628



TMEM185B
0.40094285
0.45663537



ALOX5
0.31486994
0.45679653



PRKX
0.45686789
0.45514033



C10orf128
0.38293117
0.45754484



DDHD1
0.45794778
0.37834292



RFX5
0.35284567
0.45828102



PAM
0.45896442
0.41257519



ARMC2
0.45969429
0.25523299



EMP3
0.30966654
0.46017564



PRTFDC1
0.43036982
0.46088073



NFKBIE
0.25910283
0.46144042



KIAA0556
0.34073991
0.46244078



WIPF1
0.34676681
0.46304747



UBE2Q2
0.46342887
0.44039956



DNM3
0.46708241
0.4226569



PACS1
0.37466034
0.46757148



STARD3NL
0.46838676
0.42147856



ABR
0.31153821
0.46976107



MAFK
0.47102533
0.40103476



EML2
0.45565411
0.4724727



HECA
0.32915436
0.47786029



FHOD1
0.40956315
0.47825439



ZNF611
0.39414727
0.47916196



FAM188B
0.47938055
0.35957877



FKBP10
0.45869871
0.47991687



CEP85L
0.48009881
0.3076561



CAV2
0.48010438
0.2827198



PRDM1
0.46971767
0.48160546



TMEM184B
0.48163047
0.47869769



IER5
0.37380049
0.48238365



GPRASP1
0.38849838
0.48242602



ANK1
0.33321029
0.48282041



GAS8
0.43469481
0.48323083



HIST1H4H
0.41684649
0.48488746



PIP4K2A
0.40369193
0.48490063



FAM57A
0.42520587
0.4849433



ARF3
0.40778092
0.4854765



STXBP1
0.48770991
0.46077966



SYTL3
0.23936244
0.48812979



SCLT1
0.48933128
0.42659741



TPM2
0.49037062
0.4880653



ARRDC4
0.34973272
0.49054962



RUNX1
0.4910348
0.39624144



LHFPL2
0.49123161
0.34682454



CUEDC1
0.49161992
0.33336144



SEL1L3
0.41317706
0.49164071



ZC3HAVIL
0.38668801
0.49225992



DACT1
0.49339673
0.45229507



ANK3
0.3784585
0.49503629



BIRC3
0.483975
0.49518394



APH1B
0.49565719
0.46748055



PDE4D
0.4965212
0.36657125



CMTM7
0.33828934
0.49655722



TYROBP
0.30310964
0.496969



GLIPR2
0.30316371
0.4971785



IKZF2
0.49752303
0.27186267



CACNB3
0.44463524
0.49869309



ARHGAP27
0.30243399
0.49974341



MMP25
0.36376234
0.50007319



ABCC4
0.50075499
0.3744854



PPP1R2
0.30381138
0.50101244



PHLDB1
0.39787274
0.5012486



MEF2C
0.50294246
0.35897157



CEP97
0.50332863
0.4070238



ITPKB
0.33312205
0.50451849



METRNL
0.32182726
0.50659894



COL4A1
0.50693035
0.45289629



DBN1
0.46345206
0.50779986



TNFAIP8
0.41689345
0.50951227



CHST15
0.50987762
0.43353198



HID1
0.44648635
0.51027467



FBLIM1
0.51097315
0.44851917



PCSK5
0.51289366
0.40155007



ARRDC2
0.43813799
0.51427321



MFSD7
0.32302576
0.51444871



SMARCD3
0.37790608
0.51456669



MMP14
0.51457997
0.35766629



STK32C
0.29817777
0.51482284



BARD1
0.5157784
0.49116312



ARHGEF19
0.34717626
0.51597494



RP11-344B5.2
0.47688681
0.5160077



GATA2
0.40734865
0.51642578



FAM102B
0.51018536
0.51646631



PHF20
0.35967186
0.51714878



FOS
0.51723482
0.49843324



PLAGL1
0.36332848
0.51831473



ADAMTS10
0.51891303
0.45949198



VCL
0.51963989
0.3093319



NFKB2
0.3763195
0.52061422



ZNF267
0.52210061
0.40389285



ZNF737
0.52232205
0.50969225



ARHGDIB
0.42518457
0.52245756



ZNF85
0.49766617
0.52266336



GEM
0.49369967
0.52275169



SH3YL1
0.52462088
0.39617475



TP53BP1
0.41798994
0.52582135



CHST3
0.52597136
0.39870375



MEF2C-AS1
0.52831047
0.43584248



BTN2A3P
0.45618558
0.52891207



RP11-10K16.1
0.47912049
0.52942448



GALNT7
0.4791205
0.52942741



PPP1R15A
0.51438974
0.52960335



CASP1
0.53004311
0.38226252



FAM131A
0.53052353
0.47029867



CDKN2A
0.53121383
0.49892258



CHST11
0.35013813
0.53121634



NEURL3
0.53200576
0.40525289



SPINT2
0.40865108
0.53216305



RIN1
0.50104036
0.53266083



ANKDD1B
0.53338926
0.36210881



CDKN1A
0.53585024
0.37035565



PAQR8
0.42941828
0.53590815



RASGRP3
0.53609675
0.42685963



PDE3A
0.53625641
0.41263336



PDE5A
0.53732958
0.45986461



DNAJB6
0.43164569
0.5373962



GIPR
0.53501251
0.53901154



NKRF
0.53907752
0.48815413



TNFRSF12A
0.54017298
0.47555485



B3GNT7
0.40492137
0.5431056



SLC1A5
0.41749864
0.54348945



NOTCH3
0.54369334
0.3879665



HCG11
0.35711029
0.54571694



AC092835.2
0.36293675
0.54587032



HDAC7
0.4644996
0.54608113



ARL4C
0.38595878
0.54751588



RPS6KA1
0.2448949
0.54783821



SLC26A2
0.47719781
0.5479984



E2F3
0.54912729
0.4093195



C10orf54
0.27096674
0.55216616



NFKBID
0.35908523
0.55219818



HCST
0.35908535
0.5521982



ENDOD1
0.55248025
0.55221703



IMPDH1
0.40902717
0.55270406



ANXA2R
0.55341079
0.52331638



AC025171.1
0.55341079
0.52331644



PEA15
0.55550754
0.54654346



TRABD2A
0.34077103
0.55605791



FLVCR1
0.5560836
0.33767305



TUBB6
0.55625243
0.49154716



CHORDC1
0.5564496
0.54151163



CAV1
0.55749876
0.30249684



SLC35F2
0.55860647
0.51792416



TNFSF8
0.51293016
0.55941066



PDP1
0.39213174
0.55993107



NRSN2
0.56069089
0.56040862



FAM167A
0.4562808
0.56243388



FMNL3
0.36738023
0.56260499



PHF19
0.30788195
0.56263611



AP3M2
0.31214264
0.56298546



MTHFD1L
0.563114
0.3889355



ITPR3
0.34723006
0.56319202



SYK
0.56337245
0.54784322



ISG20
0.45028012
0.56611837



TRIM31
0.51590358
0.56710758



RARG
0.38131729
0.56736657



TMEM51
0.56747986
0.42353012



RP11-712B9.2
0.51234728
0.5677274



PCBP3
0.45831443
0.56812112



ARHGAP31
0.56256999
0.56887828



INPP4B
0.50195657
0.56989785



PRICKLE1
0.57026461
0.5689147



SWAP70
0.57121006
0.54702142



TMEM173
0.31375224
0.5719445



ALOX5AP
0.47668661
0.57400025



WNT4
0.44679828
0.57537098



C5orf30
0.57591781
0.5074811



MARCH3
0.57605523
0.45001766



PWWP2B
0.30247751
0.57642316



PTPRH
0.5767047
0.53219812



TMEM51-AS1
0.57689266
0.42152941



HNRNPA1L2
0.5668362
0.57929393



DBNDD1
0.55159325
0.57950392



ADAM9
0.5809513
0.27644204



AP1S3
0.58125243
0.4899579



GSTM5
0.53508569
0.58281795



GSN
0.5830383
0.34920528



PLAU
0.36932798
0.58416417



RAB8B
0.5843851
0.43509498



ZNF486
0.51365374
0.58467117



CHD3
0.34974385
0.5848934



RP11-848P1.9
0.57955488
0.58526065



ZNF853
0.4073588
0.58652254



DLG3
0.52896732
0.58685481



FGFR1
0.58780905
0.51033287



STX11
0.58956956
0.55775123



ZSWIM4
0.58973443
0.56286966



CD83
0.43427826
0.59034087



P2RX1
0.39595553
0.59207479



SYCP2
0.50774449
0.59353471



PHLDA3
0.59361913
0.48179321



SLC25A24
0.59527835
0.45030916



FAR1
0.37933675
0.59574564



ITGA3
0.59653283
0.57519978



IL34
0.52681978
0.59673106



PPDPF
0.37317828
0.59688014



COL16A1
0.53911551
0.59846358



FUT4
0.52582932
0.59851705



ZDHHC1
0.59939596
0.49127992



TPM4
0.42021788
0.59985211



MCAM
0.60098824
0.5073176



STAT4
0.60106806
0.5689905



FBLN5
0.41215194
0.60110259



HMGA1
0.4465091
0.60122377



ZSCAN9
0.60170843
0.45016034



LOXL1
0.39225189
0.60176019



ENAH
0.60282452
0.37060372



IFI27L2
0.58017434
0.60293347



KIF3C
0.54475307
0.60434703



EIF5A2
0.58321585
0.60488452



F3
0.6056885
0.49185377



CD96
0.56613089
0.6062371



TRNP1
0.60679965
0.3961341



ITM2C
0.47444143
0.60811754



CLSTN1
0.52612578
0.60983087



MTHFD2
0.49159257
0.6101798



LINC00271
0.6117606
0.36538242



AHI1
0.61176064
0.36538254



PTGER4
0.3781944
0.61257286



SRGN
0.61265101
0.56588221



PARP6
0.40968134
0.61266417



C1orf116
0.6127681
0.48258022



CYS1
0.61404874
0.58710389



ZNF816
0.49012137
0.61509152



ATP9A
0.61548665
0.31186667



CYTIP
0.53009704
0.61590384



C1orf145
0.42581101
0.61601003



COL12A1
0.61787272
0.55428585



SESN3
0.41189014
0.6196084



ALDH1A3
0.62036516
0.54893551



PDLIM4
0.62041818
0.52071777



ABCC1
0.6022527
0.62140983



ARSJ
0.6218029
0.38518403



RELB
0.40104726
0.62198863



MYOF
0.62355697
0.47967252



GSTP1
0.56525828
0.62403088



RHOQ
0.62453525
0.50619135



LRP8
0.44236347
0.62479346



DAGLA
0.59829134
0.62492443



LTBP4
0.35542217
0.62495215



BATF3
0.62535223
0.60967772



TEAD4
0.62582399
0.43564597



TP53I11
0.59236895
0.62614093



COL1A2
0.47829077
0.62628384



RIMKLB
0.62717825
0.45935488



RIPK3
0.49096529
0.6277245



MYO5A
0.40920988
0.62779222



PYGO1
0.45202523
0.62840257



ROBO1
0.62849096
0.55898068



ZNF529
0.55712458
0.62858898



RAB11FIP5
0.62919558
0.36616513



RECK
0.6294769
0.43788935



BEX4
0.5910851
0.63005211



SFXN3
0.58797575
0.63040854



PIWIL4
0.6313442
0.5386261



SPECC1
0.47948072
0.63444676



PAQR5
0.63467314
0.53113008



PLEKHG4
0.38365905
0.63495302



PRR7
0.4790133
0.6349686



NMNAT2
0.63588177
0.63561552



ISYNA1
0.43951788
0.6369664



VIM-AS1
0.51139609
0.63730363



LINC00982
0.60717294
0.63741163



GBGT1
0.41594828
0.63834565



ZNF667-AS1
0.52877945
0.63838193



ZNF667
0.52877916
0.63838209



RAB11FIP1
0.38599858
0.63846934



ODF2L
0.63858194
0.60858386



NCK2
0.51803331
0.63867034



DZIP1L
0.63933721
0.60065084



SLC38A1
0.5888489
0.63944904



AKR1B1
0.56929296
0.64032396



SCRN1
0.64171508
0.56966255



HENMT1
0.41349065
0.64282589



SLC45A4
0.48788347
0.64300174



VIM
0.50548708
0.64433933



ZNF506
0.64461734
0.61013154



SLC4A8
0.42042218
0.6446396



OSBPL7
0.45545053
0.64485672



MLLT3
0.59936912
0.64569286



AC144831.1
0.58979539
0.64742621



RP11-353N14.5
0.53817712
0.64832393



TMEM243
0.49426528
0.64920592



PLD4
0.50270134
0.64991953



SLC7A6
0.41512372
0.65110127



FRAS1
0.65177099
0.53817222



XYLT1
0.42788894
0.65179297



CHIT1
0.39041954
0.6519958



DNAJC6
0.65338665
0.56617878



BICD1
0.65364578
0.56603614



CYR61
0.65428371
0.47510669



ZNF426
0.65441711
0.43673876



OBSCN
0.40311877
0.65513282



CLCF1
0.6554957
0.62940671



S100A11
0.65702966
0.60215854



SLC6A6
0.44054689
0.65770945



CARD16
0.65908174
0.58386911



C7orf31
0.40684957
0.66003683



LCA5
0.6600795
0.43118261



ZFP82
0.62599046
0.66067734



LXN
0.66111868
0.48350004



KIAA0226L
0.50874131
0.66190765



LBH
0.34498832
0.66191651



CD59
0.66292552
0.3725589



RP11-44N21.1
0.50320866
0.66316455



BCL11A
0.56981758
0.66319515



ATP6V1E2
0.66322131
0.52488336



SOD3
0.58411381
0.66330532



ABCA7
0.27373557
0.66455718



VANGL2
0.66497775
0.63181702



MAP2
0.66574025
0.4419067



TUBA1A
0.53760031
0.66603317



FLRT2
0.66632757
0.55087694



IFT57
0.66668838
0.53532668



AC006129.2
0.40575517
0.66707076



RP11-1149O23.3
0.53127556
0.66905934



NFATC4
0.56365233
0.6691852



ADRA2A
0.66896096
0.67013393



KIAA1549
0.67077788
0.3846937



RAP1GAP2
0.67059011
0.67200911



PKM
0.645632
0.67446074



HLA-L
0.53280219
0.67606992



CD44
0.41471387
0.67718683



ORAI2
0.40671418
0.678431



STK39
0.55501553
0.67932671



PTP4A3
0.33653795
0.6798218



RASSF3
0.67482527
0.68118708



IGF2BP2
0.61517048
0.68516452



TRIM59
0.49495112
0.68718385



ARMCX1
0.67367224
0.6926071



PDGFA
0.69274886
0.64020435



MAML2
0.69286813
0.61444161



HOMER1
0.64588532
0.69471367



SLC25A36
0.61822678
0.69515008



MEX3B
0.48825645
0.69525689



KCNAB2
0.28017135
0.69571201



RP11-4O1.2
0.69699882
0.64007133



ZNF14
0.50911358
0.69700309



CSGALNACT1
0.6972112
0.53962567



ZNF43
0.69766043
0.66041851



FAM60A
0.69798662
0.57687346



ZDHHC13
0.59284567
0.70134313



ROR2
0.47953378
0.70146852



LRRC8B
0.70218975
0.43526829



SNPH
0.65861824
0.7030763



LAPTM5
0.35569268
0.70316271



PIK3IP1
0.45872585
0.70367893



SIK1
0.57517578
0.70403294



PDE4A
0.50238721
0.70742546



SLC6A8
0.49251283
0.70985862



LETM2
0.70993884
0.51858834



NLRP1
0.33686951
0.71202987



SLFN11
0.57179801
0.71204882



CDC7
0.71385596
0.46514214



AFAP1
0.63624792
0.71489051



ZC2HC1A
0.62917918
0.71651923



FMNL1
0.3242739
0.71782192



OSBPL3
0.54660585
0.71872488



SLC7A7
0.71925364
0.65642501



NFE2L3
0.57475584
0.71968189



TNFRSF21
0.7196947
0.54695308



CHST10
0.71972882
0.61237824



SELM
0.56812723
0.71975839



RP11-325F22.2
0.50460597
0.72090451



MST1R
0.47181874
0.7209631



STX3
0.72102985
0.48367941



MFSD6
0.52289539
0.72111097



MIR24-2
0.5390643
0.72140079



TNFRSF10A
0.50417259
0.72150615



GABBR1
0.6500145
0.7215756



S100A4
0.36820521
0.72160432



TMED3
0.6722162
0.72252257



LMTK3
0.53581676
0.72422981



CNN2
0.35223128
0.72444483



NFATC1
0.53048737
0.72455305



SGCA
0.72589799
0.7198172



HTR7
0.4759203
0.72789687



ZNF462
0.73006055
0.4488765



EPB41L4A
0.73040779
0.57817447



TC2N
0.5669905
0.73047692



STK17B
0.45729752
0.73168938



FAM43A
0.38031763
0.7321046



ZNF682
0.73258188
0.55241921



CDR2L
0.73259998
0.52105382



ANXA1
0.73264023
0.57869759



DBNDD2
0.73310133
0.73344632



MCTP2
0.73454144
0.71721696



CACNB1
0.47128632
0.7393145



TRPC1
0.74188418
0.59654163



NCR3LG1
0.74276061
0.60495753



GDPD1
0.74610697
0.52045434



ZNF551
0.5517514
0.74765999



EFEMP1
0.68304411
0.74833159



WDR54
0.45749948
0.74856452



BTG2
0.6140358
0.7489323



GPR160
0.69934449
0.75515911



PCYOX1L
0.49390356
0.75582657



ENO2
0.56016537
0.75727464



PTPN13
0.73135756
0.75732687



MAPK10
0.73135737
0.75732839



SRGAP1
0.7586089
0.6047318



RP11-196G18.3
0.65548978
0.75891918



METTL24
0.76034617
0.71722934



LOXL1-AS1
0.47086974
0.76116581



ZNF135
0.61234173
0.76129642



AC006273.5
0.76159241
0.73583054



SLC7A1
0.76343128
0.68634926



KCNN4
0.39542934
0.76376793



NRARP
0.61413335
0.76444255



LRRC7
0.76457592
0.65462437



S100A6
0.71410763
0.76557321



DUSP4
0.76719907
0.56528911



TES
0.64641779
0.76721734



RASSF2
0.42520019
0.76744221



PFKP
0.76863343
0.39487891



IL32
0.42036146
0.7705907



C11orf63
0.76641642
0.77070393



PLEKHN1
0.77090664
0.75277317



SERTAD4
0.61386474
0.77235122



SPHK1
0.77352945
0.59674735



ZNF93
0.7413635
0.77732631



DOCK8
0.71316828
0.77998158



DNAJA4
0.41673965
0.78066734



GUCY1A3
0.78101523
0.43909463



FAT1
0.78161206
0.41320572



SEZ6L2
0.78300846
0.52046814



ENPP2
0.66985804
0.78327047



HAGHL
0.32832646
0.78364508



ZNF430
0.62275886
0.78636638



KIF5C
0.56901499
0.78695083



PMAIP1
0.78805908
0.7697196



MIR155HG
0.63833738
0.78900615



SLC44A3
0.78996891
0.35579282



OSM
0.45717062
0.79018332



GLIS2
0.58553663
0.79081199



HS3ST1
0.79134804
0.56934978



MB21D2
0.79162081
0.61279489



PAPLN
0.60978089
0.79186658



ZNF83
0.74987129
0.79591802



ZNF525
0.6508787
0.79797534



JAK3
0.42769928
0.79907813



CD24P4
0.79989556
0.79379019



GLS
0.76883896
0.80128197



CDS1
0.80415355
0.63792143



PDZK1IP1
0.80419565
0.59092917



SGPP2
0.80642066
0.74843572



EMILIN2
0.56552122
0.80927578



ZNF738
0.71420581
0.8101293



ZNF827
0.61687125
0.81182985



KIAA1324L
0.64072218
0.81313444



CRIM1
0.81351764
0.5727473



ARHGAP22
0.81355971
0.53217941



LGALS3
0.81554883
0.80460839



SLFN12
0.58587157
0.81763725



AC009495.4
0.82025839
0.62715837



GALNT3
0.8202589
0.62715973



LAYN
0.82570013
0.56557893



CDH11
0.78947697
0.82706053



NBEA
0.82816261
0.55764296



SUSD1
0.82864571
0.63820308



IFI16
0.82900121
0.57093752



MICAL1
0.40809112
0.83229



PRDM8
0.4147069
0.83317986



EPHA4
0.8407004
0.51534728



IL20RA
0.84074687
0.63080009



MCOLN3
0.84799599
0.82310983



MOXD1
0.61819037
0.85571757



ZNF610
0.85580077
0.76624814



C2CD4A
0.85807699
0.61331564



PTPN14
0.85928039
0.54240255



CLDN4
0.86385408
0.70732723



ZNF320
0.69940051
0.86434523



SULT1C4
0.8666197
0.55853359



C1orf198
0.86838867
0.75771881



RP11-255H23.2
0.78348346
0.87134821



RP11-54O7.17
0.66060703
0.87492254



HES4
0.66060698
0.87492257



ZNF439
0.7754003
0.87763927



OXCT1
0.69052376
0.88093823



HLA-V
0.65968038
0.88135899



HCG4
0.65968113
0.8813591



NACAD
0.88540406
0.78948956



KLHL29
0.88688097
0.78426889



GRAMD1B
0.88789388
0.87824523



BHLHE41
0.89380159
0.82046044



CXCL1
0.89397774
0.49676709



ETV4
0.89505799
0.77147938



LOXL4
0.83770117
0.89640324



SPINT1
0.9019053
0.81320729



TUBB3
0.77901178
0.90258575



SLFN13
0.71647168
0.90474057



TESC
0.91154566
0.7155896



SSPN
0.91333829
0.80776856



HKDC1
0.80267098
0.91553292



GPRC5B
0.91582436
0.71925544



B3GALT5
0.82298552
0.92241342



LEF1
0.64581157
0.92796029



CCND2
0.51570471
0.93297174



BACE2
0.93873245
0.93421453



LAMA2
0.94512492
0.70426537



ZNF781
0.8958214
0.94739801



WFDC2
0.95117142
0.84255703



LPAR2
0.74984023
0.95256452



ITGA2
0.95418097
0.72896514



COL4A4
0.71663337
0.96095475



COL4A3
0.71663331
0.96095538



TAF4B
0.60146796
0.96199357



ITGAM
0.9681795
0.8187902



ASNS
0.80819223
0.9686812



SOX4
0.97014313
0.64336655



ZNF607
0.96801207
0.97105325



HSPA4L
0.97111408
0.70391323



PRSS22
0.97314734
0.78588991



KRT80
0.97565683
0.77689948



ANXA3
0.98288653
0.65418067



DCDC2
0.98344899
0.84556677



ZNF665
0.98826934
0.98849773



C1orf106
0.98917225
0.92284703



ZNF888
0.90202205
0.99204931



BDKRB2
1.00219891
0.75459275



ZNF66
0.78637292
1.00612414



AC098614.2
0.73989189
1.0094951



ANKRD18A
1.01070424
0.79144155



FAM201A
1.01070424
0.79144103



KLF5
1.01939278
0.61866171



ITGB8
1.02049996
0.95067059



ST8SIA1
0.52806315
1.02256245



ADAMTS9-AS2
1.03801979
0.67690411



ADAMTS9
1.0380198
0.67690424



ZNF793
1.03634612
1.04053639



C3orf52
1.05646192
0.74854065



CXCR4
0.69277409
1.05694656



TGFB2
1.07245542
0.66816217



YBX3
1.07488767
0.60213429



CXCL6
1.07602493
0.82122851



F2RL1
1.07822298
0.62809111



GULP1
1.08334898
0.87106295



ZNF382
0.91514769
1.08943678



EVC
0.70441736
1.09029465



TNFRSF11B
1.09291997
0.80432709



PDX1
1.03806686
1.10210071



MDFI
0.99970847
1.10729961



NPNT
1.11084697
0.90699949



PMEPA1
1.11864875
0.98597334



FAM150B
1.12938884
0.93355004



WNT10A
0.54025736
1.13200548



TTC9
0.91326661
1.1326541



TMEM55A
1.13757001
1.02024542



EVC2
0.79916052
1.13916517



HSPB8
1.02574973
1.15133921



ZNF431
1.05242004
1.1614527



B3GNT3
1.16547116
1.13459562



GABRE
1.16594765
0.83124387



CTD-2008P7.9
1.16713333
0.99437014



TBC1D30
1.18821614
0.75123115



GABRB3
1.08299275
1.19747739



RASEF
1.22724328
1.07280705



VCAN
1.22905187
0.76885504



LRRC1
1.16117843
1.23945445



KRT7
1.29272853
1.01287264



ZNF714
0.99537496
1.30371306



CLIC6
1.32775759
1.0734942



DUSP8
1.11637838
1.33563505



CDH6
1.38128848
1.12788111



EPCAM
1.39394879
1.36241594



SNAP25
1.47530976
1.0638733



ID4
1.24692876
1.52077185



SOX9
1.55632138
1.6100915



DTNA
1.74642847
1.81480646

















TABLE S4







Prognostic epigenetic signature - 25 gene subset. The common


prognostic subset of signature genes in NASH and CHC (related


to FIG. 1). List of the 25 genes with the highest prediction


of HCC risk predicted from the 1693 commonly changed genes


on CHC and NASH patients (FDR < 0.25). The dysregulation


was determined by the nearest template prediction










High risk genes
Low risk genes







GPRIN3
GSTA1



COL1A2
GRB14



SLC7A6
SERPINA5



CHST11
CAT



LBH
SLC25A1



TRPC1
PKLR



IGF2BP2
ADH4



ARRDC2
GLYAT



SELM
TTR



TMED3
HPX




RARRES2




ACADSB




CFHR5




DCXR




GALK1










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Claims
  • 1. A method of diagnosis and/or prognosis of liver disease progression, survival and/or risk of hepatocellular carcinoma in a subject comprising detecting an epigenetic or transcriptomic change in subject with liver disease, the method comprising comparing a) the level of expression of a marker or a plurality of markers in a subject sample; andb) the level of expression of the marker or plurality of markers in a control sample,
  • 2. The method of claim 1, wherein the liver disease is a non-alcoholic or alcoholic liver disease, a liver disease due to viral hepatitis or liver fibrosis.
  • 3. The method of claim 2, wherein the liver disease is a non-alcoholic or alcoholic steatohepatitis, chronic hepatitis A, B, C, D or E related liver disease or liver fibrosis.
  • 4. The method according to claim 1, wherein the subject is a patient cured by direct-acting antivirals (DAA) and/or interferon-alfa based treatment or a patient cured of or with controlled viral infection by any treatment.
  • 5. The method according to claim 1, wherein the marker or at least one marker of the plurality of markers have increased expression in the subject sample relative to the control sample.
  • 6. The method according to claim 1, wherein the marker or at least one marker of the plurality of markers have decreased expression in the subject sample relative to the control sample.
  • 7. The method according to claim 1, wherein at least one marker has increased expression in the subject sample relative to the control sample and at least one marker has decreased expression in the subject sample relative to the control sample.
  • 8. The method according to claim 1, wherein at least one gene of the high-risk gene of Table S3 is overexpressed and/or wherein at least one gene of the low-risk gene of Table S3 is underexpressed, in the subject sample in comparison to the control sample.
  • 9. The method according to claim 1, wherein the subject has undergone tumor resection.
  • 10. The method according to claim 1, wherein the subject sample is obtained from a non-tumorous liver tissue or a tissue surrounding a resected tumor.
  • 11. The method according to claim 1, wherein the subject sample is selected from the group consisting of fresh tissue, fresh frozen tissue, fixed embedded tissue, patient-derived spheroids, serum, plasma or urine.
  • 12. The method according to claim 11, wherein the patient-derived spheroids were generated by culturing fresh liver tissue in spheroid culture medium.
  • 13. (canceled)
  • 14. The method according to claim 1, wherein the marker is or the plurality of markers are a gene selected from the group consisting of GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, TMED3, GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR, HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1.
  • 15. A method of assessing the efficacy of a therapy for liver disease and/or hepatocellular carcinoma prevention or treatment in a subject with liver disease, the method comprising comparing: a) the level of expression of a marker or a plurality of markers in a subject sample; andb) the level of expression of the marker or plurality of markers in a second subject sample following the treatment with the therapy,
  • 16. The method of claim 15, wherein (i) the subject is at risk for progression of liver disease, death and/or developing a hepatocellular carcinoma and/or (ii) the liver disease is a non-alcoholic or alcoholic steatohepatitis, chronic hepatitis A, B, C, D or E-related liver disease or liver fibrosis.
  • 17. A method of identifying a compound useful for the prevention or treatment of liver disease and/or hepatocellular carcinoma, said method comprising the steps of: a) providing a sample;b) contacting the sample with a candidate compound; andc) detecting an increase or decrease in expression of a marker or a plurality of markers selected from the group consisting of the genes listed in Table S3, relative to a control, andd) identifying the compound as useful for the prevention or treatment of liver disease and/or hepatocellular carcinoma if it increases or decreases the expression of said marker or at least a marker of the plurality of markers relative to the control.
  • 18. The method according to claim 17, wherein the genes is the subset of 25-genes presented in Table S4, and wherein the candidate compound is identified as an agent useful for agent for treatment of liver disease or prevention and treatment of hepatocellular carcinoma if the candidate compound suppresses the expression of the 10 HCC high-risk genes, or of a subset thereof and/or induces the expression of the 15 HCC low-risk genes, or of a subset thereof.
  • 19. The method according to claim 17, wherein the sample is or comprises a subject-derived HCC or adjacent liver tissue, a cancer cell, a liver cell line, a combination of liver and non-liver cell lines including non-parenchymal cells or a cell line derived from a subject-derived HCC or adjacent liver tissue plasma, serum or urine.
  • 20. The method according to claim 17, wherein the candidate compound is a chromatin modifier, regulator or reader inhibitor or compound targeting epigenetic gene regulation.
  • 21. The method according to claim 20, wherein the chromatin modifier, regulator or reader inhibitor or compound targeting epigenetic gene regulation is selected from the list the group consisting of BRPF1B inhibitors, G9a/GLP inhibitors, PCAF/GCN5 inhibitors, LSD1 inhibitors, SPIN1 inhibitors, CREBBP/EP300 inhibitors, SMYD2 inhibitors, PRDM9 inhibitors, SMARCA2/4 inhibitors, EZH2 inhibitors, BAZ2A/2B inhibitors, SUV420H1/H2 inhibitors, CECR2/BPTF inhibitors, L3MBTL3 inhibitors, ATAD2A/B inhibitors or PRMT4/6 inhibitor.
  • 22. A method for preventing or delaying the progression of a liver disease, delaying the onset of or treating hepatocellular carcinoma in a subject comprising: performing the steps of the method of diagnosis and/or prognosis of liver disease progression and/or risk of hepatocellular carcinoma according to claim 1 or 14, andadministering a preventive treatment to the subject diagnosed as at risk for progression of liver disease and/or at risk of developing a hepatocellular carcinoma.
  • 23. A kit for the diagnosis and/or prognosis of liver disease progression, survival and/or risk of hepatocellular carcinoma, wherein said kit comprises means for assessing the level of expression of GPRIN3, COL1A2, SLC7A6, CHST11, LBH, TRPC1, IGF2BP2, ARRDC2, SELM, TMED3, GSTA1, GRB14, SERPINA5, CAT, SLC25A1, PKLR, ADH4, GLYAT, TTR, HPX, RARRES2, ACADSB, CFHR5, DCXR and GALK1.
  • 24. A method for generating a cellular model for liver disease or hepatocellular carcinoma (HCC) development and progression, said method comprising steps of: (a) differentiating liver cancer cell line to obtain hepatocyte-like cells; and(b) submitting said hepatocyte-like cells to one hepatocarcinogenic/fibrosis causing agent such as hepatitis C virus or free fatty acids to obtain liver cells exhibiting a Prognostic Epigenetic Signature (PES) high-risk gene signature
  • 25. The method according to claim 24, wherein the liver cancer cell line is selected from the group consisting of the Huh6, Huh7, Huh7.5.1, Hep3B.1-7, HepG2, SkHepI, C3A, PLC/PRF/5 and SNU-398 cell lines or optionally a combination with another cell line such as LX2 cells or THP1 cells or another cell line or liver non-parenchymal cells such as Kupffer cells, or myofibroblasts or liver sinusoidal endothelial cells.
  • 26. A method for identifying an agent for the treatment or prevention of liver disease and HCC, wherein said method comprises the use of a cellular model for liver disease progression and HCC risk according to claim 24.
PCT Information
Filing Document Filing Date Country Kind
PCT/EP2021/055203 3/2/2021 WO
Provisional Applications (1)
Number Date Country
62983965 Mar 2020 US