Patent Application
20220136065
The present invention relates to a method of determining the status of high-grade serous ovarian carcinoma (HGSOC) in a subject, related methods of detection, treatments, compositions and kits.
High-grade serous ovarian carcinoma (HGSOC) is a type of tumour that arises from the fallopian tube epithelium and the epithelial layer in the abdominopelvic cavity. HGSOCs make up the majority of ovarian cancer cases and have the lowest survival rates. HGSOC is distinct from low-grade serous ovarian carcinoma (LGSOC). LGSOC is less aggressive and is associated with better survival.
Precise and robust stratification of tumors facilitates diagnosis and treatment. It has been achieved in many cancer types. For example, the subtypes of breast cancer, luminal and basal, have been connected to the cell types of origin. This subtyping has promoted the delivery of efficient treatments. However, for high-grade serous ovarian carcinoma (HGSOC), its classification remains a major challenge due to its genomic complexity. Most of the published molecular classifications were based on the global expression matrix (Bell et al., 2011; Tothill et al., 2008). For instance, the TCGA (The Cancer Genome Atlas) study clustered HGSOC tumors into four distinct groups (immunoreactive, differentiated, proliferative and mesenchymal) based on 1,500 high variance genes. However, a recent consensus clustering study pointed out that this discrete classification system is not robust, and a subset of tumors is unclassifiable (Chen et al., 2018).
Recent evidences strongly support the tubal origin hypothesis that HGSOC originates from the fallopian tube epithelium (FTE) by mouse models and genetic evolutional analysis. FTE is a single-cell layer of secretory cells and ciliated cells, whereas knowledge of these cellular subtypes is limited to few well-known markers, such as PAX8 and TUBB4. Although the HGSOC presumably originates from FTE secretory cells, the classification and understanding of secretory cells remains elusive. Moreover, the “peg” basal cells in FTE have been proposed as stem cells; however, other studies reported infiltrated lymphocytes with similar morphology as those peg cells. Limited understanding regarding of FTE has hindered further investigation into HGSOC.
An aim of the invention is to provide improved methods for determining the status or classifying of high-grade serous ovarian carcinoma (HGSOC) in a subject.
According to a first aspect of the invention, there is provided a method of determining the status of high-grade serous ovarian carcinoma (HGSOC) in a subject, the method comprising:
According to another aspect of the invention, there is provided a method of determining the status of high-grade serous ovarian carcinoma (HGSOC) in a subject, the method comprising:
one or more of cell cycle biomarker proteins and/or nucleic acid encoding cell cycle biomarker proteins selected from the group comprising FEN1, NUSAP1, UBE2C, ZWINT, PRC1, ASF1B, MCM4, GINS2, CENPM, MCM2, TK1, MCM6, SMC4, CENPU, and MAD2L1; and
one or more of ciliated cell biomarker proteins and/or nucleic acid encoding ciliated cell biomarker proteins selected from the group comprising TEKT1, TUBA4B, C20orf85, CAPSL, LRRC46, EFCAB1, C6orf118, and CCDC78;
According to another aspect of the invention, there is provided a method of determining the status of high-grade serous ovarian carcinoma (HGSOC) in a subject, the method comprising:
In one embodiment, the method determines the presence and level of the cell types (e.g. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) in the HGSOC by detecting one or more of their representative biomarkers listed herein, for example listed in Table 1 or Table 2, or the combination thereof.
In one embodiment, the fraction of EMT cells in the high-grade serous ovarian carcinoma in the subject is compared to a pre-determined threshold level to indicate if the high-grade serous ovarian carcinoma in the subject is an EMT subclass of high-grade serous ovarian carcinoma.
In one embodiment, the level of the EMT biomarkers/cell types relative to the differentiated, KRT17 Cluster, cell cycle and ciliated biomarkers/cell types is indicative of the fraction of EMT cells, and the fraction of EMT cells above a pre-determined threshold level is indicative of an EMT subclass of high-grade serous ovarian carcinoma in the subject.
In one embodiment, an EMT subclass (also known as an “EMT-high subclass) of HGSOC is indicative of a poorer prognosis for the subject. Additionally or alternatively, an EMT subclass of HGSOC is indicative of an aggressive form of a HGSOC in a subject.
The invention herein advantageously identifies a subclass of patients having EMT- type HGSOC. The hazard of death in EMT tumours as defined by the method of the invention is at least twice that for non-EMT tumours for any given period of time. For example for TCGA data, the hazard risk is determined to be 2.297 (95% Confidence interval=1.291˜4.087). For AOCS data, the hazard risk is determined to be 2.691 (95% Confidence interval=1.556˜4.655).
The hazard risk score from an indication of an EMT subclass of high-grade serous ovarian carcinoma in the subject may be at least 2. In another embodiment, the hazard risk score from an indication of an EMT subclass of high-grade serous ovarian carcinoma in the subject may be at least 2.297. In another embodiment, the hazard risk score from an indication of an EMT subclass of high-grade serous ovarian carcinoma in the subject prognosis may be at least 2.691.
The present invention advantageously identifies cellular subtypes in FTE, which have been thoroughly studied at the transcriptomic level. In particular, the invention profiles the fallopian tube epithelium from patients with HGSOC or endometrium cancer to delineate subtypes in FTE secretory cells and their marker genes. These markers from FTE single cells can then advantageously be used to stratify HSGOCs and identify a tumor subtype with poor overall survival, in particular an EMT subclass of HSGOC with poor overall survival.
According to another aspect of the invention, there is provided a method of detecting a panel of biomarkers in a sample of a subject, the method comprising: providing a sample obtained from a subject and detecting the presence of:
According to another aspect of the invention, there is provided a method of detecting a panel of biomarkers in a sample of a subject, the method comprising: providing a sample obtained from a subject and detecting the presence of:
According to another aspect of the invention, there is provided a method of detecting a panel of biomarkers in a sample of a subject, the method comprising: providing a sample obtained from a subject and detecting the presence of:
According to another aspect of the invention, there is provided a method of detecting a panel of biomarkers in a sample of a subject, the method comprising: providing a sample obtained from a subject and detecting the presence of:
LTBP4, SLC25A25, LAMC2, DHCR24, PLK3, LRG1 and LDLR;
According to another aspect of the invention, there is provided a method of detecting a panel of biomarkers in a sample of a subject, the method comprising: providing a sample obtained from a subject and detecting the presence of:
According to another aspect of the invention, there is provided a method of detecting the complexing of a panel of probes with a panel of biomarkers in a sample of a subject, the method comprising:
According to another aspect of the invention, there is provided a method of detecting the complexing of a panel of probes with a panel of biomarkers in a sample of a subject, the method comprising:
According to another aspect of the invention, there is provided a method of detecting the complexing of a panel of probes with a panel of biomarkers in a sample of a subject, the method comprising:
In one embodiment, detecting the presence of a biomarker may comprise the detecting the presence or absence, or the level of the biomarkers. In one embodiment, detecting the presence of a biomarker may comprise the detecting of a level of the biomarker. In one embodiment, detecting the presence or level of a biomarker may comprise determining the expression values for the biomarkers. The pre-determined threshold level may be a pre-determined threshold expression value.
In one embodiment, detecting the complexing of the panel of probes comprises detecting the level of complexing of the panel of probes.
In one embodiment, the level of expression of the biomarkers is indicative of an EMT subclass of high-grade serous ovarian carcinoma in the subject.
The expression value of the biomarkers may be determined using the counts of transcripts to determine the expression such as TCGA data or relative to a standard quantitative or relative transcript data set, such as AOCS data.
In one embodiment, the expression values of the biomarkers that represent the EMT type are compared to the expression values of other types (i.e. differentiated, KRT17 Cluster, cell cycle and ciliated) so that an estimate of the fraction of cells that represent EMT cells is obtained.
The skilled person will be aware of appropriate statistical methods, mathematical methods or computational algorithms, such as standard deconvolution analysis, to estimate the fraction of cells from the expression values. To estimate the fraction of cells from the expression values the level of expression of the EMT biomarkers to those of other tumour types may be compared.
For example, deconvolution analysis may be provided by using the CIBERSORT method (https://cibersort.stanford.edu/), which is an analytical tool developed by Newman et al. (2015. Nature Methods volume 12, pages 453-457, and which is incorporated herein by reference) to provide an estimation of the abundances of member cell types in a mixed cell population, using gene expression data.
In one embodiment, the level of the EMT biomarkers above a pre-determined threshold expression value of the EMT biomarkers is indicative of an EMT subclass of high-grade serous ovarian carcinoma in the subject. In an embodiment using the counts of transcripts (e.g. using TCGA data) to determine the expression value of the EMT biomarkers the pre-determined threshold level of the fraction of EMT cells may be at least 0.2. In another embodiment using a quantitative or relative method (e.g. using AOCS data) to determine the expression value of the EMT biomarkers the pre-determined threshold level of the fraction of EMT cells may be at least 0.4. In one embodiment, the pre-determined threshold level of the fraction of EMT cells may be at least 0.2. In one embodiment, the pre-determined threshold level of the fraction of EMT cells may be at least 0.4.
The method of the invention may be used, for example, for any one or more of the following: to advise on the prognosis for a subject with HGSOC; to advise on treatment options and/or to monitor effectiveness or response of a subject to a treatment for HGSOC. The presence, or level, of the biomarkers may be used to stratify patients. This stratification may be used to decide the appropriate treatment.
Information regarding the HGSOC status of a subject may be relayed to a third party, such as a doctor, other medical professional, pharmacist or other interested party. This information may be relayed digitally, for example via email, SMS or other digital means.
Biomarker Determination/Detection
In one embodiment, the presence, absence, or level of a biomarker may be determined by any suitable assay. In one embodiment, detecting the presence, absence, or level of a biomarker may comprise the use of a probe, such as an oligonucleotide probe. The detecting the presence or level of a biomarker may comprise the detection or measurement of hybridisation of an oligonucleotide to a target sequence of nucleic acid encoding the biomarker. The detecting the presence or level of a biomarker may comprise the detection of binding of a probe to a biomarker, or nucleic acid encoding the biomarker.
The nucleic acid encoding the biomarker may comprise mRNA transcripts or cDNA copies thereof. Therefore the method may comprise determining the transcript level of the biomarkers. The transcript level may be the transcript numbers or the relative levels. In one embodiment, the method comprises the provision of cDNA copies of RNA transcripts of nucleic acid encoding the biomarkers. cDNA copies of all RNA transcript species in the sample may be provided.
The skilled person will recognise there are a number of methods and technologies available to determine the presence and/or level of a biomarker or nucleic acid encoding a biomarker. For example the detection may comprise Northern blot analysis, nuclease protection assays (NPA), in situ hybridization, or reverse transcription-polymerase chain reaction. The detection may comprise the use of Surface-enhanced Raman Spectroscopy (SERS) to detect probes labelled with Raman- active dyes.
The Probes for Detection
In one embodiment, the probes are oligonucleotide probes. An oligonucleotide probe may comprise or consist of a sequence that is substantially or fully complementary to a nucleic acid sequence of a biomarker, or an mRNA or cDNA copy thereof. Each biomarker may be provided with a corresponding oligonucleotide probe that is capable of hybridisation with the sequence encoding the biomarker, for example under stringent conditions. The oligonucleotide probe may comprise or consist of a sequence that is sufficiently complementary to a nucleic acid sequence of a biomarker, or an mRNA or cDNA copy thereof to enable specific hybridisation.
The skilled person will recognise that the number of transcripts of biomarker sequence in a sample or cell can be measured using a variety of techniques.
The oligonucleotide probes may be sufficient length to provide specific hybridisation to a target sequence (of the biomarker) under stringent conditions. In one embodiment, the oligonucleotide probes are at least 10 nucleotides in length. In one embodiment, the oligonucleotide probes are at least 15 nucleotides in length. In one embodiment, the oligonucleotide probes are between 10 and 200 nucleotides in length. In one embodiment, the oligonucleotide probes are between 10 and 100 nucleotides in length. In one embodiment, the oligonucleotide probes are between 10 and 50 nucleotides in length. In one embodiment, the oligonucleotide probes are between 10 and 30 nucleotides in length. In one embodiment, the oligonucleotide probes are between 15 and 30 nucleotides in length.
The oligonucleotide probes may comprise or consist of DNA or RNA. In another embodiment, oligonucleotide probes may comprise or consist of nucleotide analogues, such as PNA, LNA, or PMO; or combinations thereof. The oligonucleotide probes may comprise or consist of DNA and one or more nucleotide analogues, such as PNA, LNA, or PMO.
In one embodiment the oligonucleotide probes are reporter probes, for example that provide a signal upon hybridisation (directly or indirectly via another molecule). The probe may be labelled, for example with a fluorescent marker or dye, or a radiolabel. Fluorescent dyes may comprise one or more of coumarin, Cy2, Cy3, rhodamine red, texas red, Cy5, Cy5.5 and Cy7, or functional equivalents or derivatives thereof. The label may comprise a Raman-active dye, such as Azo dyes. Examples of Raman-active dyes that may be used are Rhodamine 6G, Cy3, Cy5, or Malachite Green. The probe may be labelled with a fluorescent barcode (e.g. a series of different fluorescent molecules that can be used to identify a probe by determining the sequence or position of the fluorescent molecules in the fluorescent barcode. In another embodiment the label may be a genetic barcode (i.e. a sequence of nucleotides that can be used to label the probe).
In one embodiment, the oligonucleotide probes are immobilised on a substrate. In one embodiment, the oligonucleotide probes comprise a tag for capture/anchoring (or otherwise known as immobilising) on a substrate. The tag on the probe may comprise a biotin-avidin tag, e.g. the probe may be biotinylated. The tag on the probe may comprise a nanoparticle, such as a metal nanoparticle. In another embodiment the tag may be a nucleic acid sequence of the probe, which is capable of hybridising to a complementary sequence of a nucleic acid that is anchored to a substrate.
The detection of the biomarkers may comprise the use of nCounter® Technology (otherwise known as direct multiplexed measurement of gene expression with color-coded probe pairs) (e.g. by Nanostring™) (see Geiss et al. 2008 (Direct multiplexed measurement of gene expression with color-coded probe pairs. Nature Biotechnology volume 26, pages 317-325), which is herein incorporated by reference). In one embodiment, the probe is a capture probe that is capable of hybridizing to a target nucleic acid sequence of the biomarker sequence, or a mRNA or cDNA copy thereof. The capture probe may comprise an anchor tag that is capable of anchoring the capture probe to a substrate. A second probe, known as a reporter probe, may be provided to further hybridise to the target sequence, or mRNA or cDNA copy thereof, together with the capture probe and form a target-probe complex. The reporter probe may comprise a fluorescent barcode for detection and identification of the target-probe complex. The target-probe complexes may be isolated by capture using the tag on the capture probe, and excess probes may be removed, including excess reporter probes and/or excess non-hybridized capture probes. The target-probe complexes may be detected in a device capable of imaging and reading fluorescent barcodes of the target-probe complexes.
In another embodiment, the probes may be PCR primers, such that the biomarker may be detected by PCR amplifying nucleic acid encoding the biomarker. In an embodiment where the probes are primers, a forward and reverse primer may be provided. The skilled person will readily be able to design and provide appropriate primers for a given biomarker nucleic acid encoding sequence. The PCR may be RT-PCR.
The probes may be provided in the form of a microarray.
In one embodiment, polypeptides of the biomarkers are detected/measured. In one embodiment, polypeptides of the biomarkers are detected by antibodies, for example by an Immunohistochemistry (IHC) panel of biomarkers. The antibodies may be monoclonal. The antibodies may be immobilised on a substrate. The antibodies may be conjugated to a label, such as an enzyme (such as peroxidase) or fluorophore.
Sequencing
In one embodiment, detecting the biomarkers may comprise the detection by sequencing nucleic acid encoding the biomarkers, such as mRNA/transcriptome sequencing. The sequencing may comprise single cell RNA transcriptome sequencing. The sequence may comprise single molecule sequencing, such as nanopore sequencing.
Biomarkers for Detection
Table 1 lists a first panel of 52 biomarkers that have been found to enable the sub-classification of HGSOCs in accordance with the invention. Table 2 lists a second panel of 52 biomarkers that have been found to enable the sub-classification of HGSOCs in accordance with the invention. In one embodiment, all 52 biomarkers of Table 1 may be detected/probed. In another embodiment, all 52 biomarkers of Table 2 may be detected/probed. In another embodiment, all biomarkers of Table 1 and 2 may be detected/probed. In one embodiment, at least 50%, 60%, 70% 90%, 95%, or 98% of the 52 biomarkers of Table 1 may be detected/probed. In another embodiment, at least 50%, 60%, 70% 90%, 95%, or 98% of the 52 biomarkers of Table 2 may be detected/probed. In one embodiment, at least one or two biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 1 may be detected. In another embodiment, at least one or two biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 2 may be detected. In another embodiment, at least one or two biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of a combination of Tables 1 and 2 may be detected. In another embodiment, at least 50% of the biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 1 or Table 2 may be detected. In another embodiment, at least 50% of the biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 1 and Table 2 in combination may be detected. In another embodiment, at least 60% or 80% of the biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 1 may be detected. In another embodiment, at least 60% or 80% of the biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 2 may be detected. In another embodiment, at least 60% or 80% of the biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 1 and Table 2 combined may be detected. The skilled person will recognise that reference to the combined biomarkers of Tables 1 and 2 comprises duplicates, which may only be counted once as a single biomarker.
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
cell cycle biomarker proteins and/or nucleic acid encoding cell cycle biomarker proteins of FEN1, NUSAP1, UBE2C, ZWINT, PRC1, ASF1B, MCM4, GINS2, CENPM, MCM2, TK1, MCM6, SMC4, CENPU, and MAD2L1; and ciliated cell biomarker proteins and/or nucleic acid encoding ciliated cell biomarker proteins of TEKT1, FAM92B, SNTN, LRRC46, EFCAB1, CDHR3, C6orf118, CCDC78, TUBA4B, C20orf85 and CAPSL.
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the method comprises detecting the presence or level of:
In one embodiment, the detection does not comprise the detection of immune genes, such as CD8, CD4, CD3 or CD45.
Advantageously, the exclusion of immune genes provides that the classification results are not confounded by the infiltration of lymphocytes.
The Sample
The sample from the subject may be a tissue sample. The tissue sample may comprise or consist of an ovarian cancer biopsy tissue. The ovarian cancer biopsy tissue may be from sites such as the ovary, peritoneum, omentum, or diaphragm. The tissue sample may be a post-operative sample (i.e. a sample taken during surgery on the subject). In another embodiment the sample is a blood or serum sample for the detection of circulating biomarkers.
Providing a sample obtained from a subject may comprises obtaining a tissue sample, such as conducting a biopsy. In another embodiment, the sample may be provided for testing, for example from a third party or from a separate procedure. In one embodiment, the tissue sample is obtained from a biopsy of the tissue. The sample may be a fresh sample (e.g. not frozen or otherwise stored for a period of greater than 1 day), or it may have been frozen, for example for storing the sample, prior to the detection. In another embodiment, the sample may have been preserved or fixed prior to the detection.
The amount of sample may be an amount that provides sufficient biomarker to be measured, for example an amount that provides 1, 2, 3 or more nanograms of RNA.
Some or all of the steps of the method of the invention may be carried out in vitro.
The Subject
The subject may have or is suspected of having ovarian cancer. The subject may have or is suspected of having high-grade serous ovarian cancer.
In one embodiment, the subject is mammalian, such as a human. In one embodiment, the subject is a human adult female.
Other Aspects of the Invention
According to another aspect of the invention, there is provided a composition comprising a panel of probes, wherein the probes are for detecting:
UBE2C, ZWINT, PRC1, ASF1B, MCM4, GINS2, CENPM, MCM2, TK1, MCM6, SMC4, CENPU, and MAD2L1; and
CAPSL.
According to another aspect of the invention, there is provided a composition comprising a panel of probes, wherein the probes are for detecting:
According to another aspect of the invention, there is provided a composition comprising a panel of probes, wherein the probes are for detecting:
According to another aspect of the invention, there is provided a kit for determining the status of high-grade serous ovarian carcinoma (HGSOC) in a subject, the kit comprising a panel of probes, wherein the probes are for detecting:
According to another aspect of the invention, there is provided a kit for determining the status of high-grade serous ovarian carcinoma (HGSOC) in a subject, the kit comprising a panel of probes, wherein the probes are for detecting:
According to another aspect of the invention, there is provided a kit for determining the status of high-grade serous ovarian carcinoma (HGSOC) in a subject, the kit comprising a panel of probes, wherein the probes are for detecting:
In one embodiment of the composition or the kit, a probe may be provided for each of the 52 biomarkers of Table 1 or Table 2, or a combination of Tables 1 and 2. In one embodiment of the composition or the kit, probes may be provided for at least 50%, 60%, 70% 90%, 95%, or 98% of the 52 biomarkers of Table 1. In another embodiment of the composition or the kit, probes may be provided for at least 50%, 60%, 70% 90%, 95%, or 98% of the 52 biomarkers of Table 2. In another embodiment of the composition or the kit, probes may be provided for at least 50%, 60%, 70% 90%, 95%, or 98% of the biomarkers of Table 1 and Table 2 combined. In one embodiment of the composition or the kit, probes may be provided for at least one or two biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 1. In another embodiment of the composition or the kit, probes may be provided for at least one or two biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 2. In another embodiment of the composition or the kit, probes may be provided for at least one or two biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 1 and Table 2 combined. In another embodiment of the composition or the kit, probes may be provided for at least 50% of the biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 1 or Table 2, or Table 1 and Table 2 combined. In another embodiment of the composition or the kit, probes may be provided for at least 60% or 80% of the biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 1. In another embodiment of the composition or the kit, probes may be provided for at least 60% or 80% of the biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 2. In another embodiment of the composition or the kit, probes may be provided for at least 60% or 80% of the biomarkers from each signature group (i.e. differentiated, KRT17 Cluster, EMT, cell cycle, and ciliated) of Table 1 and Table 2 combined.
According to another aspect of the invention, there is provided a method of selecting a patient for treatment with an agent, agent combination, or composition for treatment or prevention of HGSOC, the method comprising determining the status of high-grade serous ovarian carcinoma (HGSOC) in a subject according to the method if the invention herein, wherein the determination of an EMT subclass of HGSOC indicates that the subject should or should not receive the agent, agent combination, or composition.
The subject may be provided with a choice of not receiving treatment (or advised not to receive treatment) with a therapeutic agent, such as Carboplatin, Paclitaxel or
PARP inhibitors, which may be less effective for EMT HGSOC subjects. PARP inhibitors may comprise Olaparib, Rucaparib, Niraparib, or Talazoparib.
The agent, agent combination, or composition may comprise a therapeutically effective amount of the agent, agent combination, or composition. The agent, agent combination, or composition may be a known to treat HGSOC or EMT HGSOC, or reduce symptoms thereof. The agent may comprise a PI3K pathway inhibitor.
In one embodiment, the treatment comprises immunotherapy. Therefore, the agent may comprise an immunotherapeutic agent. The agent may comprise a vaccine arranged to produce an immune response to HGSOC tumour cells, an antibody, such as a monoclonal antibody, or cell, such as a T-cell, arranged to target HGSOC tumour cells (or markers thereof). The immunotherapy/immunotherapeutic agent may be used in combination with other therapeutic agents, such as PI3K pathway inhibitor.
According to another aspect of the invention, there is provided a PI3K pathway inhibitor for use in the treatment of high-grade serous ovarian carcinoma (HGSOC) in a subject, wherein the treatment comprises selecting the patient for treatment based on the determination of an EMT subclass of high-grade serous ovarian carcinoma in the subject.
According to another aspect of the invention, there is provided an immunotherapeutic agent for use in the treatment of high-grade serous ovarian carcinoma (HGSOC) in a subject, wherein the treatment comprises selecting the patient for treatment based on the determination of an EMT subclass of high-grade serous ovarian carcinoma in the subject.
According to another aspect of the invention, there is provided a method of treating a subject with a PI3K pathway inhibitor, wherein the subject is determined to have an EMT subclass of high-grade serous ovarian carcinoma;
According to another aspect of the invention, there is provided a method of treating a subject with immunotherapy targeting an EMT subclass of high-grade serous ovarian carcinoma, wherein the subject is determined to have an EMT subclass of high-grade serous ovarian carcinoma;
The determination of an EMT subclass of high-grade serous ovarian carcinoma in the subject may comprise the method of determining the status of high-grade serous ovarian carcinoma (HGSOC) of a subject in accordance with the invention herein.
According to another aspect of the invention, there is provided a method of treating a subject with a PI3K pathway inhibitor, wherein the subject has, or is suspected of having, HGSOC,
According to another aspect of the invention, there is provided a method of treating a subject with an immunotherapy targeting HGSOC, wherein the subject has, or is suspected of having, HGSOC,
The biomarker assay may be obtained from conducting the method of determining the status of high-grade serous ovarian carcinoma (HGSOC) of a subject in accordance with the invention herein.
The PI3K pathway inhibitor may comprise a PI3K inhibitor or an AKT inhibitor, or a combination thereof.
In one embodiment, the PI3K inhibitor comprises an PI3K inhibitor selected from pilaralisib, ACP-319 (Acerta Pharma BV), ACP-319 (Acerta Pharma BV), BAY-1082439 (Bayer AG), AZD-8154 (AstraZeneca Plc), BPS-001 (Biopep Solutions Inc), PF-4989216 (Pfizer Inc), BR-101801 (Boryung Pharmaceutical Co Ltd), ZSTK-474 (Zenyaku Kogyo Co Ltd), ZSTK-474 (Zenyaku Kogyo Co Ltd), ZSTK-474 (Zenyaku Kogyo Co Ltd), WX-008 (Chia Tai Tianqing Pharmaceutical Group Co Ltd), IBL-202 (Inflection Biosciences Ltd) IBL-202 (Inflection Biosciences Ltd), SRX-3207 (SignalRx Pharmaceuticals Inc), AMXI-9001 (AtlasMedx Inc), X-480 (Xcovery Holding Company LLC), pictilisib, CLR-457 (Novartis AG), AMG-511 (Amgen Inc), AS-605240 (Merck KGaA), CU-903 (Curis Inc), PI-3065 (F. Hoffmann-La Roche Ltd), acalisib, AEZS-129 (Aeterna Zentaris Inc), GSK-1059615 (GlaxoSmithKline Plc), WX-037 (Heidelberg Pharma AG), and AEZS-132 (Aeterna Zentaris Inc); or combinations thereof.
In one embodiment, the AKT inhibitor comprises an AKT inhibitor or AKT inhibitor combination selected from ipatasertib, LY-2503029 (Eli Lily and Co), capivasertib, MK-2206 (Merck & Co Inc), MK-2206 + selumetinib sulfate, uprosertib, TAS-117 (Taiho Pharmaceutical Co Ltd.), ARQ-751 (ArQule Inc); FXY-1 (Krisani Bio Sciences Pvt Ltd), perifosine, RX-0183 (Rexahn Pharmaceuticals Inc), VLI-27 (NovaLead Pharma Pvt Ltd), PX-316 (Seattle Genetics Inc), J-9 (Columbia University), and afuresertib+trametinib; or combinations thereof.
The immunotherapy may comprise the administration or use of a vaccine arranged to produce an immune response to HGSOC tumour cells, an antibody, such as a monoclonal antibody, or cell, such as a T-cell, arranged to target HGSOC tumour cells. An immunotherapeutic agent may be used or administered in combination with another therapeutic agent, such a PI3K pathway inhibitor.
The method of the invention herein may further comprise a second/follow-up determination of the status of high-grade serous ovarian carcinoma (HGSOC) of a subject. Two or more measurements may be provided to measure the progression of a subject's cancer. For example, a subject's status may be measured two or more times at different time points (for example before, during and after treatment) in order to determining if the EMT HGSOC is reduced or eliminated, or if HGSOC has developed into EMT HGSOC.
According to another aspect of the invention, there is provided the use of a panel of biomarkers for determining the fraction of EMT cells present in HGSOC or determining the status of HGSOC, wherein the biomarkers comprise:
According to another aspect of the invention, there is provided the use of a panel of biomarkers for determining the fraction of EMT cells present in HGSOC or determining the status of HGSOC, wherein the biomarkers comprise:
According to another aspect of the invention, there is provided the use of a panel of biomarkers for determining the fraction of EMT cells present in HGSOC or determining the status of HGSOC, wherein the biomarkers comprise:
The use of the biomarkers may comprise the determination of the biomarkers in a sample from a subject, such as a tissue sample.
Definitions
The biomarkers listed herein may include variants of the biomarkers, for example variants having natural mutations/polymorphisms in a population. It is understood that reference to protein or nucleic acid “variants”, it is understood to mean a protein or nucleic acid sequence that has at least 70%, 80%, 90%, 95%, 98%, 99%, 99.9% identity with the sequence of the fore mentioned protein or nucleic acid. The percentage identity may be calculated under standard NCBI blast p/n alignment parameters. “Variants” may also include truncations of a protein or nucleic acid sequence. Variants may include biomarker listed herein comprising the same sequence, but comprising or consisting of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10, or more modifications, such as substitutions, deletions, additions of nucleotides or bases. Variants may also comprise redundant/degenerate codon variations.
The term “encoding”, may mean at least partially encoding or fully encoding a given biomarker/gene. The at least partially encoding may be at least enough sequence to identify the biomarker/gene.
The term “detected” or “detecting” in the context of a biomarker is understood to mean that an attempt is made to detect the biomarker, such that a biomarker in the sample is attempted to be detected even in the event that the biomarker not present in the sample.
By an “agent” we include all chemical entities, for example oligonucleotides, polynucleotide, polypeptides, peptidomimetics and small compounds.
A ‘therapeutically effective amount’, or ‘effective amount’, or ‘therapeutically effective’, as used herein, refers to that amount which provides a therapeutic effect for a given condition and administration regimen. This is a predetermined quantity of active material calculated to produce a desired therapeutic effect in association with the required additive and diluent, i.e. a carrier or administration vehicle. Further, it is intended to mean an amount sufficient to reduce and most preferably prevent, a clinically significant deficit in the activity, function and response of the host. Alternatively, a therapeutically effective amount is sufficient to cause an improvement in a clinically significant condition in a host. As is appreciated by those skilled in the art, the amount of a compound may vary depending on its specific activity. Suitable dosage amounts may contain a predetermined quantity of active composition calculated to produce the desired therapeutic effect in association with the required diluent. In the methods and use for manufacture of compositions of the invention, a therapeutically effective amount of the active component is provided. A therapeutically effective amount can be determined by the ordinary skilled medical or veterinary worker based on patient characteristics, such as age, weight, sex, condition, complications, other diseases, etc., as is well known in the art.
Reference to hybridization of a probe or primer herein is understood to mean the specific complementary binding of one molecule to another under standard stringent conditions.
The skilled person will understand that optional features of one embodiment or aspect of the invention may be applicable, where appropriate, to other embodiments or aspects of the invention.
Embodiments of the invention will now be described in more detail, by way of example only, with reference to the accompanying figures.
Introduction
Limited understanding regarding of FTE has hindered further investigation into HGSOC; therefore, cellular subtypes in FTE need to be thoroughly studied at the transcriptomic level. Herein, we profiled the fallopian tube epithelium from patients with HGSOC or endometrium cancer to delineate subtypes in FTE secretory cells and their marker genes. These markers from FTE single cells were then used to stratify HSGOCs and identified a tumor subtype with poor overall survival.
Results
A Cell census of human fallopian tubes in cancer patients We analyzed 3,877 single cells from the fallopian tubes of six ovarian cancer patients and four endometrial cancer patients using Smart-Seq2 technique (Picelli et al., 2014) (
However, we observed striking effects of the culture conditions on the single cell transcriptomes. Most notably, overnight culturing, induced profound differential expression changes in pathways related to cell cycle (e.g. RGCC, p21 and MCM4), RNA processing (e.g. POLR2B, PRPF3 and METTL3) and stress response (e.g. NR4A1, FOS and EGR1) (
Within the epithelial cells, we identified the two previously established subtypes, secretory and ciliated cells (
In addition to the two established cell types, we discovered a rare intermediate type that was characterized by the expression of the secretory cell marker KRT7 and high expression of ciliated marker CAPS (
Four Novel Secretory Subtypes in FTE
We next attempted to classify secretory cells based on their transcriptomes. To ensure the purity of secretory cells, the cell was only kept for further analysis if it had strong expression of KRT7 and EPCAM and no expression of CCDC17 or PTPRC. In addition, to avoid including contaminating cancer cells, we excluded cells that had detectable copy numbers variants or loss-of-heterogeneity (
Surprisingly, C7 showed high expression of a Regulator of G protein signaling (RGS16) and genes that were enriched in the extracellular matrix (ECM) pathway (false discovery rate [FDR]=1.80E-17), such as TIMP3, SPARC and COL1A (
Cluster C3 had upregulation of genes that are involved in RNA synthesis and transport (e.g. PTBP1, ZNF259 and PRPF38A). It probably represented a transient differentiating cell population. Cluster 4 is characterized by the upregulation of major histocompatibility complex (MHC) Class II genes (e.g. HLA-DQA1, HLA-DPA1 and HLA-DPB1), cytokeratins (KRT17 and KRT23), aldehyde dehydrogenases (e.g. ALDH1A1 and ALDH3B2) and CDKN1A (also called p21) (
C9 cluster (−1.6% of fresh FTESCs) most probably represented cycling cells because the marker genes of this cluster were enriched in three pathways, namely cell cycle (e.g. MCM2-7, MKI67, TK1 and STMN1), DNA repair (e.g. FANCD2, FANCI and MSH2) and chromatin remodeling (e.g. HMGB2 and SMC1A) (
We also confirmed the CD45+EPCAM+ population that was located as basal cells in FTE by IF staining (
Deconvolution Revealed a Poor-Prognostic Tumor Subtype
We hypothesized that FTE cell subtypes might be correlated with HSGOC tumor types. Based on the four novel secretory subclasses and the ciliated cell type, we firstly computed a reference matrix with cell-type derived transcriptomic signature from five major FTE cellular subtypes (Cell cycle, EMT, Differentiated, KRT17 cluster and ciliated) as previously described (
We next tested whether any of the five tumor subtype scores from the deconvolution analysis correlated with survival. The EMT score was significantly associated with poor overall survival and was independent of the effect of ages, stages and residual diseases (p<0.05, by Cox proportional hazard model). The robustness of the association was confirmed by the permutation test (n=500) leaving out 10% samples each time (empirical p-values=0.012 [TCGA] and 0 [AOCS], permutation test).
SPARC, one of the 12 genes that comprise the EMT signature, was previously described in the mesenchymal subtype of HGSOC (Tothill et al., 2008), while some other markers were reported to be related to EMT in ovarian cancer or other cancers, such as SFRP4 (Ford et al., 2013), TIMP3 (Anastassiou et al., 2011), MYH11 (Y.-R. Li and W.-X. Yang, 2016) and EFEMP1 (Yin et al., 2016). Nevertheless, the link between this tumor types and a particular FTE cellular subtype was previously unrevealed. The mesenchymal subtype was previously thought to have an association with poor prognosis, but the reproducibility of the observation was inconsistent probably because of the difficulty in defining this group of tumors. Using the EMT scores from deconvolution, we reached a robust classification with consistently significant correlation with poor survival (p<0.03) in another seven independent datasets, including the AOCS dataset (Tothill et al., 2008) and six additional microarray datasets (N>100) from the CuratedOvarianData database (Ganzfried et al., 2013) (Table 3).
A DE analysis of TCGA miRNA data revealed that the miRNA-200 family (miR-200a, miR-200b, miR-200c, miR-141 and miR-429) was downregulated in EMT-high tumors (FDR<0.01, log-FC<−0.5), which agrees with the previous finding that this miRNA family suppresses EMT process and that its loss can activate EMT in invasive breast cancer cell lines with a mesenchymal phenotype (Gregory et al., 2008). We also found that miRNA-483 and miRNA-214 were significantly upregulated in EMT-high tumors, while miRNA-513c, miRNA-509 and miRNA-514 were downregulated (
ζValidation survival analysis was restricted to eight microarray datasets with over 100 samples.
To exclude the potential paracrine effect of cancer cells on non-cancer FTE cells, we validated the existence of the four secretory subtypes in the FTE cells obtained from benign (non-cancer) donors. We first analyzed 1857 single-cell transcriptomes of fallopian tubes from five patients with benign conditions (
According to the invention herein, a first panel of cell-signature markers was identified, as provided in Table 3 below. After further analysis, where the threshold for selecting the marker genes was adjusted, a second panel of cell-signature markers was identified, as provided in Table 4 below. Whilst both panels prove useful for identifying the cell-signatures, the second panel generated more significant (p<0.05) and reproducible results across multiple datasets.
Comparison between the First Panel and the Second Panel
By comparing the survival analysis results, the second gene panel generated more significant (p<0.05) and reproducible results across multiple datasets.
We investigated if the EMT scores correlate with the immunophenotype of SOC. We computed the proportion of multiple types of leukocytes in the TCGA data by using CIBERSORT. We used both the LM22 and LM6 signatures, which generates two sets of deconvolution results. In the results generated by using LM22, the EMT-high tumors have significantly higher proportion of macrophage M2 (
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| Number | Date | Country | Kind |
|---|---|---|---|
| 1902653.3 | Feb 2019 | GB | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/GB2020/050286 | 2/7/2020 | WO | 00 |
