Patent Application
20230131334
The present disclosure relates to methods of predicting treatment sensitivity or drug resistance, especially for epidermal growth factor receptor (EGFR) inhibitors using leucine proline-enriched proteoglycan 1 (LEPRE1 ) gene expression level before or during a treatment, methods of discovering companion diagnostic biomarkers using efficacies of EGFR inhibitors on the expression of genes, including genes involved with regulation of extracellular matrix environment, or metabolism of collagen, and methods of predicting treatment or drug sensitivity or resistance using the companion diagnostic biomarkers thereof.
With recent innovations in the next-generation sequencing (NGS) technology, gene sequencing information and expression information required to understand complex and various cancers have been rapidly secured. In addition, a catalog of somatic mutations in various cancer types and a comprehensive cancer driver mutation database were established through the formation of an international consortium. Due to these achievements, expectations for the discovery of biomarkers capable of confirming the difference between patients with each allogeneic tumor, as well as the condition of tumors, and personalized cancer treatment using the same are also rapidly increasing. However, biomarkers approved and used in clinical practice are still insufficient. Genomics of drug sensitivity in cancer (GDSC), which is a database including experimental results of drug toxicity information of 1,070 human cancer cells for 265 anticancer compounds, was published through several collaborative consortiums for integrating molecular profiling data of cancer cell lines and drug toxicity data (www.lincsproject.org), and, as a result of carrying out genetic biomarker labeling scan (GBLscan) of the present applicant by using GDSC, the correlation between LEPRE1 and drug sensitivity, which is shown when treated with an EGFR inhibitor, was confirmed.
LEPRE1 (P3H1), also known as Leprecan, is a protein belonging to the collagen prolyl hydroxylase family, has the function of hydroxylating proline of collagen constituting fibrils, and is an enzyme having an essential function for collagen synthesis and structural formation. 28 types of collagen in the human body can be largely classified depending on the function thereof into: fibrillar collagens such as type I, II, III, V, XI, XXIV, and XXVII collagens; and structural network-forming collagens such as type IV and VIII collagens. LEPRE1 plays an important role in constituting the extracellular matrix existing in the space between cells by hydroxylating the 896th proline (Pro896) of type I collagen from among the above collagen types to induce the modification of collagen protein, and it has been reported that mutations in LEPRE1 induce diseases such as osteochondrodysplasia (including osteogenesis imperfecta), kyphosis, and rhizomelia
The hydroxylation of type I collagen by LEPRE1 is also involved in bone cancer and cancer-related bone metastasis, and the expression level of LEPRE1 also increases in solid cancers such as pancreatic cancer, colorectal cancer, breast cancer, and lung cancer, which is closely associated with the progression of cancer. It is also known that LEPRE1 and type I collagen also affect the formation of carcinoma associated fibroblasts, and thus play an important role in cancer progression, and the amount of type I collagen increases in bone cancer, pancreatic cancer, rectal cancer, ovarian cancer, lung cancer, and the like, compared to normal tissues, thus inducing the overexpression of TGF-β, and as a result, the proliferation of cancer cells is promoted and apoptosis is reduced. In addition, it can be seen that the modification process of type I collagen by LEPRE1 plays important roles, such as: a higher growth rate of cancer cells located close to type I collagen than that of cells located not close thereto; increased metastasis-related invasiveness; and an increase in the number of circulating tumor cells, in not only an osteogenic process but also the progression processes, such as onset and metastasis, of cancer.
Epidermal growth factor receptor (EGFR) is an oncogene, and a mutation-induced increase in the expression or activity of the gene shows a high disease association in various carcinomas, including lung cancer, head and neck cancer, and the like. It has been reported that an increase in EGFR in breast cancer induces decreased LEPRE1 expression, and the possibility of the direct binding between EGFR and LEPRE1 has also been suggested. Through the above contents, it can be seen that LEPRE1, which is closely related to the onset and progression of cancer, and type I collagen, which is a target thereof, are also associated with EGFR, which can be a direct basis for the difference in the activity of an EGFR inhibitor according to the expression level of LEPRE1 according to the present disclosure.
One embodiment of the present disclosure provides methods of predicting treatment sensitivity or drug resistance, especially for epidermal growth factor receptor (EGFR) inhibitors determining leucine proline-enriched proteoglycan 1 (LEPRE1) gene expression level before or during a treatment.
Another embodiment of the present disclosure provides methods of predicting treatment or drug sensitivity or drug resistance, especially for epidermal growth factor receptor (EGFR) inhibitors determining expression level genes that are related to regulation of extracellular matrix environment, metabolism of collagen, or mixture of thereof, before or during a treatment.
Yet another embodiment of the present disclosure provides methods of predicting treatment or drug sensitivity or resistance by determining the expression level of companion diagnostic biomarkers involved with regulation of extracellular matrix environment, metabolism of collagen, or mixture of thereof, wherein the drugs have a similar multi-target efficacies as an epidermal growth factor receptor (EGFR) inhibitors.
In one embodiment, the present disclosure provides a method of discovering a gene for determining drug sensitivity comprising:
In another embodiment, the present disclosure provide a companion diagnostic composition for determining the sensitivity to an EGFR inhibitor drug, the companion diagnostic composition comprising an agent for measuring an RNA expression level of a LEPRE1 gene or an agent for specifying a protein expression level of the LEPRE1 gene.
In a further embodiment, the present disclosure provides a method of discovering a gene for determining drug sensitivity, the method comprising:
The present disclosure relates to methods of predicting treatment or drug sensitivity or drug resistance, especially for epidermal growth factor receptor (EGFR) inhibitors using leucine proline-enriched proteoglycan 1 (LEPRE1) gene expression level before or during a treatment, methods of discovering companion diagnostic biomarkers using efficacies of EGFR inhibitors on the expression of genes, including genes involved with regulation of extracellular matrix environment, or metabolism of collagen, and methods of predicting treatment or drug sensitivity or resistance using the companion diagnostic biomarkers thereof.
One embodiment of the present disclosure provides methods of predicting treatment sensitivity or drug resistance, especially for epidermal growth factor receptor (EGFR) inhibitors determining leucine proline-enriched proteoglycan 1 (LEPRE1) gene expression level before or during a treatment.
Another embodiment of the present disclosure provides methods of predicting treatment sensitivity or drug resistance, especially for epidermal growth factor receptor (EGFR) inhibitors determining expression level genes that are related to regulation of extracellular matrix environment, metabolism of collagen, or mixture of thereof, before or during a treatment.
Yet another embodiment of the present disclosure provides methods of predicting treatment sensitivity or resistance of drugs by determining the expression level of companion diagnostic biomarkers involved with regulation of extracellular matrix environment, metabolism of collagen, or mixture of thereof, wherein the drugs have a similar multi-target efficacies as an epidermal growth factor receptor (EGFR) inhibitors.
In the present disclosure, the correlation between LEPRE1, discovered using the unique GBLscan method, and drug sensitivity to an EGFR inhibitor was confirmed, and the present disclosure is to provide LEPRE1 as a biomarker to be used in cancer treatment through EGFR inhibitor treatment.
The common cancer drug responsiveness information and next-generation sequencing information (genomes and transcriptomes), and a biomarker gene LEPRE1 verified through the same, and the present disclosure relates to the prediction and verification of a companion diagnostic biomarker gene and mutant composition that improve cancer drug responsiveness, when a haplotype biomarker composition or gene expression information of a gene expression regulatory region is known, and in particular, to a companion diagnostic biomarker for an EGFR inhibitor.
In the present disclosure, the correlation between LEPRE1, discovered using the unique GBLscan method of the present applicant, and drug sensitivity of an EGFR inhibitor was measured, and the present disclosure provides LEPRE1 as a biomarker to be used in cancer treatment through EGFR inhibitor treatment.
The EGFR inhibitor is selected from Erlotinib (OSI-774) HCI, Gefitinib (ZD1839), Lapatinib (GW-572016) Ditosylate, Afatinib (BIBW2992), Saracatinib (AZD0530), Vandetanib (ZD6474), Neratinib (HKI-272), Canertinib (CI-1033), Lapatinib (GW-572016), AG-490 (Tyrphostin B42), CP-724714, Dacomitinib (PF-00299804), WZ4002, Sapitinib (AZD8931), CUDC-101, AG-1478 (Tyrphostin AG-1478), PD153035 HCI, Pelitinib (EKB-569), AEE788 (NVP-AEE788), AC480 (BMS-599626), AP26113-analog (ALK-IN-1), OSI-420, WZ3146, Allitinib tosylate, Rociletinib (CO-1686), Varlitinib, Icotinib (BPI-2009H), TAK-285, WHI-P154, Daphnetin, PD168393, CNX-2006, Tyrphostin 9, AG-18, O-Demethyl-Gefitinib, AST-1306, ErbB2 inhibitor, BDTX-189, Epertinib hydrochloride, JND3229, BI-4020, Tyrphostin AG-528, AG 556, Canertinib dihydrochloride, Gefitinib-based PROTAC 3, SU5214, RG 13022, TQB3804 (EGFR-IN-7), TAS6417, Pyrotinib (SHR-1258) dimaleate, PD153035, AG 494, AG 555, Theliatinib (HMPL-309), Avitinib (AC0010), Lazertinib, Gefitinib hydrochloride, Cetuximab (anti-EGFR), Lifirafenib (BGB-283), Nazartinib (EGF816), Brigatinib (AP26113), Tucatinib, Zorifertinib (AZD3759), Afatinib (BIBW2992) Dimaleate, Erlotinib (OSI-774), CL-387785 (EKI-785), Poziotinib (HM781-36B), Osimertinib (AZD9291), AZ5104, AV-412 or pharmaceutically acceptable salt thereof.
In one embodiment, the present disclosure provides a method of discovering a gene for predicting and/or determining drug sensitivity comprising:
In an example of embodiment, the gene associated to determining sensitivity to EGFR inhibitor is selected from genes in Table 2, most of which regulate the extracellular matrix environment, similar to LEPRE1, to predict or determine the drug sensitivity such that the sensitivity of the cancer cell line to the EGFR inhibitor by measuring the expression level of the genes:
In another example of the method, the gene associated to sensitivity to EGFR inhibitors is selected from the genes shown in Table 3, most of which regulate the metabolism of collagen, similar to LEPRE1, to predict or determine the drug sensitivity such that the sensitivity of the cancer cell line to the EGFR inhibitor by measuring the expression level of the genes:
In yet another embodiment of the present disclosure provides methods to predict and/or determine sensitivity to the drug having multi-target efficacy as shown in Table 4 or an efficacy profile similar thereto, similar to EGFR inhibitor, preferably Pelitinib, by determining expression level of genes in Table 2, Table 3 or a mixture thereof:
The present disclosure also provide a companion diagnostic composition for determining the sensitivity of an EGFR inhibitor drug, the companion diagnostic composition comprising an agent for measuring an RNA expression level of a LEPRE1 gene or an agent for specifying a protein expression level of the LEPRE1 gene, wherein,
In a further embodiment, the present disclosure provides a method of discovering a gene for determining drug sensitivity, the method comprising:
The present disclosure has experimentally confirmed a biomarker predicted through a system (GBLscan) for predicting the correlation between a cancer drug and the expression information and gene copy number variation of a cell line genome, through collection information-based linear regression modeling of quantitative trait loci and deep machine learning, and is to provide reliability by verifying prediction through a machine learning system. The expression level of the LEPRE1 gene in cancer cells with high EGFR expression shows the example of a verification experiment for determining sensitivity to a tyrosine kinase inhibitor anticancer agent.
The present disclosure also provides a model for verifying a tyrosine kinase inhibitor biomarker, thus enabling other drugs and other genes to be verified in the same manner in the future.
According to the characteristics of the present disclosure for achieving the above-described objects, the present disclosure largely comprises two steps of: predicting the expression information and gene copy number variation of a cell line genome and drug responsiveness; and verifying whether an alteration predicted through a system actually affects drug sensitivity. In the prediction step, GBLscan, which is a program (a machine learning system) developed by the present applicant, was used, and experimental verification was carried out through joint research with the Safety Evaluation Institute, which is a national verification organization.
As described above, according to the present disclosure, from the in-vivo or in-vitro sensitivity results of drugs of which the genetic information is known, it was experimentally verified whether the alteration or copy number variation and a change in the expression level of a resultant predicted by GBLscan, which has the effect of predicting the degree of sensitivity to drugs of which the pharmacological effects are unidentified, actually affect drug responsiveness.
According to exemplary embodiments of the present disclosure, the drug sensitivity in a cancer cell line is determined according to the expression level of a gene, wherein the gene is a LEPRE1 gene, and the drug is an EGFR inhibitor drug, drug sensitivity is determined such that the sensitivity of an EGFR inhibitor drug in the cancer cell line is high according to the overexpression level of the LEPRE1 gene, and the resistance of an EGFR inhibitor drug to the cancer cell line is high according to the under expression level of the LEPRE1 gene, wherein the EGFR inhibitor drug is pelitinib, and the cancer cell line is any at least one selected from THP-1 and KG-1, which are hematological cancer cell lines, and A549, which is a lung cancer cell line, and the expression level of the LEPRE1 gene is determined by detecting at least one alteration from the Table 1.
Accordingly, in the present disclosure, from the in-vivo or in-vitro sensitivity results of drugs of which the genetic information is known, it was experimentally confirmed whether the alteration or copy number variation and a change in the expression level of a resultant predicted by GBLscan, which has the effect of predicting the degree of sensitivity to drugs of which the pharmacological effects are unidentified, actually affect drug responsiveness.
According to exemplary embodiments of the present disclosure, wherein the gene associated to drug sensitivity further comprise at least one gene selected from Table 2 below that regulate the extracellular matrix environment, such as LEPRE1. The sensitivity or resistance to the drug varies according to the expression level of the genes.
According to exemplary embodiments of the present disclosure, wherein the gene associated to drug sensitivity is selected from the genes selected from Table 3 below that regulate the metabolism of collagen, such as LEPRE1, and determining drug sensitivity such that the sensitivity of the EGFR inhibitor drug to the cancer cell line changes according to the expression level of the genes. The sensitivity or resistance to the drug varies according to the expression level of the genes.
Another exemplary embodiments of the present disclosure provides a method to determine a sensitivity or resistance to a drug comprising:
In the present disclosure, examples provides if the expression of the LEPRE1 gene predicted through a drug response prediction system using an artificial intelligence deep learning model based on combined data of cell line alterations and cancer drugs, according to the present disclosure, actually affects cancer drug responsiveness.
Epidermal growth factor receptor is a member of the ErbB receptor family and consists of four closely related receptors (the subfamily of tyrosine kinases: EGFR (ErbB-1); HER2/neu (ErbB-2); Her 3 (ErbB-3); and Her 4 (ErbB-4). In addition, in many cancer types, mutations that affect EGFR expression or activity can cause cancer.
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| Number | Date | Country | Kind |
|---|---|---|---|
| 10-2020-0075057 | Jun 2020 | KR | national |
This application is a continuation-in-part of PCT/KR2021/007706, filed Jun. 18, 2021 which claims the benefit of priority from Korean Patent Application No. 10-2020-0075057, filed Jun. 19, 2020, the contents of each of which are incorporated herein by reference.
| Number | Date | Country | |
|---|---|---|---|
| Parent | PCT/KR2021/007706 | Jun 2021 | WO |
| Child | 18068517 | US |
