Epistatic Targets-Based Anti-Breast Cancer Combinatorial Drugs Discovery

Breast cancer is one of the highest incidence and mortality malignant tumors in the world.The main drugs for breast cancer treatment are endocrine therapy drugs,chemotherapeutic drugs and targeted drugs.Targeted drugs can target specific pathogenic factors and reduce side effects,so they are favored by people.Currently,most of the targeted drugs are single-target,which are effective for genetic diseases with single genetic factors,but they are not effective when treating complex diseases such as breast cancer.Moreover,with the time of drug use extending,breast cancer patients may be drug-resistant.Combinatorial drugs can not only target multiple pathogenic factors,but also enhance the effect of chemotherapy and reduce toxicity through working synergistically.In addition,combinatorial drugs can also delay drug resistance,which makes combinatorial drugs become the trend of treating complex diseases at present.However,efficiently screening the combinatorial drugs that have both anti-breast cancer activity and synergistic effect is a challenge.Genes usually exert function based on interaction,so that we assumed that breast cancer is not caused by several major genes but caused by many interacted disease-related genes(epistasis genes).Therefore,we assumed that targeting these genes may synergistically have a greater impact on the disease.In this study,the following three aspects were applied to verify our hypothesis:(1)Combinatorial drugs were screened by targeting cancer-related synergistic lethality genes(similar with epistatic genes).Through statistical analysis of the efficacy of these combinatorial drugs,the result showed that these combinatorial drugs we screened is over 2.1 times than DCDB(Drug Combination Database),which can significantly enrich the anticancer combination.(2)In order to further verify the important value of these interactions of disease-related genes for combinatorial drugs discovery,many epistatic gene pairs potentially associated with breast cancer were identifiied by using epistasis detection software from breast cancer GWAS(Genome-wide association study)dataset.Then we screened combinatorial drugs by targeting these gene pairs and analyzed the clinical activity of these combinatorial drugs.As a result,the anti-breast cancer proportion of combinatorial drugs we screened is over 1.7 times than DCDB,indicating that screening efficiency(6.9%)was improved.Then,in order to strengthen the genetic association between the epistatic genes and breast cancer,and to further improve the screening efficiency of anti breast cancer combinatorial drugs,we screened the epistatic genes,which were simultaneously identified by three kinds of software,and the results showed that the screening efficiency of the anti breast cancer combination was increased by 5 times(above 35.1%).(3)In order to verify the reliability of this our method and avoid missing meaningful gene interaction relationship,we filtered these gene pairs with the gene links in gene co-opening network that was built based on the 3D genome.The filtered gene pairs were functionally-related epistatic,which increased genetic association with breast cancer.Compared with epistatic gene pairs,the number of filtered gene pairs was greatly reduced.Moreover,the screening efficiency of the combinatorial drugs targeting breast cancer drug combinations increased by more than 3 times(20.4%).Finally,the study screened the combinatorial drugs which can target the common epistatic gene pairs identified by three kinds of software and can target the functionally-related epistatic gene pairs.There are 9 groups of known active combinatorial drugs,of which 5 groups are anti breast cancer combinations,and the screening efficiency has been further improved(66.7%).Finally,we suggests that two of the other three groups of combinatorial drugs(DC002016 and DC002885)have great potential for anti breast cancer,and can provide further guidance for experimental verification.