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Research Article

The development of a general drug resistance score model based on MIC50 related gene pairs in colorectal cancer cell lines

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  • Fujian Key Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350122, China

Received date: 2020-01-06

  Revised date: 2020-04-29

  Online published: 2020-05-25

Supported by

Supported by the National Natural Science Foundation of China No(81602738);Young and Middle-Aged Backbone Training Project in the Health System of Fujian Province No(2017-ZQN-56);Fujian Medical University No(2018QH1005)

Abstract

Cancer cell line models are widely used for testing drug sensitivity and in screening for drug resistance markers. However, the general level of drug resistance in cancer cell lines is often ignored by researchers, making it difficult to apply many drug efficacy markers in clinical practice. In this study, we examined 48 colorectal cancer (CRC) cell lines to calculate the correlation coefficients between the IC50 values for 265 drugs. The general drug resistance evaluation index MIC50 was constructed using the median value of 265 drugs’ IC50 values. Genes with positively correlated expression values and a MIC50 which rose to significance were selected for further study. To analyze the effect of general drug resistance on the response status and prognosis in CRC patients, the general drug resistance scoring model was established based on within-sample relative expression orderings of gene pairs. The results demonstrate that more than 99% of the IC50 correlation coefficients of 265 drugs were significantly positive (FDR<0.05), indicating that CRC cell lines possessed general drug resistance characteristics. Furthermore, we identified 602 general drug resistance related genes, and by using Metascape, we identified four functional modules closely related to tumor resistance. A scoring model of 5-FU-based general drug resistance levels consisting of 21 gene pairs was built. After performing χ 2 test, we found that the general drug resistance level in CRC patients was significantly correlated with the response information after accepting 5-FU-based combination drug therapy. Survival analysis showed that the low scoring cohort of patients had a better prognosis than the higher scoring cohort, indicating that the level of basic drug resistance was closely related to the prognosis and drug response status in these patients. These results provide basic theoretical support for further research on the mechanism of combined chemotherapy resistance and the individualized regimen of clinical drug use in patients with CRC.

Cite this article

Huxing Chen, Lei Xu, Jing Li, Zheng Guo, Lu Ao . The development of a general drug resistance score model based on MIC50 related gene pairs in colorectal cancer cell lines[J]. Hereditas(Beijing), 2020 , 42(6) : 577 -585 . DOI: 10.16288/j.yczz.19-336

References

[1] Geeleher P, Cox NJ, Huang RS . Cancer biomarker discovery is improved by accounting for variability in general levels of drug sensitivity in pre-clinical models. Genome Biol, 2016,17(1):190.
[2] Zhang CY, Feng YX, Li P, Fu SB . Study on the relationship between the resistance to MTX and the transport protein superfamily of ATP-binding cassette that induces multiple drug resistance. Hereditas(Beijing), 2006,28(10):1201-1205.
[2] 张春玉, 冯源熙, 李璞, 傅松滨 . 介导多药耐药的ABC转运蛋白超家族与MTX耐药性的关系研究. 遗传, 2006,28(10):1201-1205.
[3] Guo Q, Cao H, Qi X, Li H, Ye P, Wang Z, Wang D, Sun M . Research progress in reversal of tumor multi-drug resistance via natural products. Anticancer Agents Med Chem, 2017,17(11):1466-1476.
[4] Li ST, Lu XR, Chi P, Pan J . Identification of HOXB8 and KLK11 expression levels as potential biomarkers to predict the effects of FOLFOX4 chemotherapy. Future Oncol, 2013,9(5):727-736.
[5] Criscitiello C, Bayar MA, Curigliano G, Symmans FW, Desmedt C, Bonnefoi H, Sinn B, Pruneri G, Vicier C, Pierga JY, Denkert C, Loibl S, Sotiriou C, Michiels S, André F . A gene signature to predict high tumor-infiltrating lymphocytes after neoadjuvant chemotherapy and outcome in patients with triple-negative breast cancer. Ann Oncol, 2018,29(1):162-169.
[6] Watanabe T, Kobunai T, Yamamoto Y, Matsuda K, Ishihara S, Nozawa K, Iinuma H, Konishi T, Horie H, Ikeuchi H, Eshima K, Muto T . Gene expression signature and response to the use of leucovorin, fluorouracil and oxaliplatin in colorectal cancer patients. Clin Transl Oncol, 2011,13(6):419-425.
[7] Qi LS, Chen LB, Li Y, Qin Y, Pan RF, Zhao WY, Gu YY, Wang HW, Wang RP, Chen XQ, Guo Z . Critical limitations of prognostic signatures based on risk scores summarized from gene expression levels: a case study for resected stage I non-small-cell lung cancer. Brief Bioinform, 2016,17(2):233-242.
[8] Eddy JA, Sung J, Geman D, Price ND . Relative expression analysis for molecular cancer diagnosis and prognosis. Technol Cancer Res Treat, 2010,9(2):149-159.
[9] Del Rio M, Mollevi C, Martineau P. Molecular subtypes of metastatic colorectal cancer are predictive of patient response to chemo and targeted therapies( part 1). NCBI,GEO, 2017. .
[10] Del Rio M, Mollevi C, Martineau P . Molecular subtypes of metastatic colorectal cancer are predictive of patient response to chemo and targeted therapies(part 2). NCBI, GEO, 2017. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE72969 .
[11] Shingo Tsuji. CRC samples for FOLFOX therapy prediction. NCBI, GEO, 2011. .
[12] Zhou YY, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, Benner C, Chanda SK . Metascape provides a biologist-oriented resource for the analysis of systems- level datasets. Nat Commun, 2019,10(1):1523.
[13] Benjamini Y, Hochberg Y . Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B, 1995,57(1):289-300.
[14] Bader GD, Hogue CW . An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics, 2003,4:2.
[15] Zhan X, Wang J, Liu Y, Peng YQ, Tan WF . GPCR-like signaling mediated by smoothened contributes to acquired chemoresistance through activating Gli. Mol Cancer, 2014,13:4.
[16] Shigeta K, Ishii Y, Hasegawa H, Okabayashi K, Kitagawa Y . Evaluation of 5-fluorouracil metabolic enzymes as predictors of response to adjuvant chemotherapy outcomes in patients with stage II/III colorectal cancer: a decision- curve analysis. World J Surg, 2014,38(12):3248-3256.
[17] Siegfried Z, Karni R . The role of alternative splicing in cancer drug resistance. Curr Opin Genet Dev, 2018,48:16-21.
[18] Wilding JL, Bodmer WF . Cancer cell lines for drug discovery and development. Cancer Res, 2014,74(9):2377-2384.
[19] Daniel VC, Marchionni L, Hierman JS, Rhodes JT, Devereux WL, Rudin CM, Yung R, Parmigiani G, Dorsch M, Peacock CD, Watkins DN . A primary xenograft model of small-cell lung cancer reveals irreversible changes in gene expression imposed by culture in vitro. Cancer Res, 2009,69(8):3364-3373.
[20] Tong M, Zheng W, Li H, Li X, Ao L, Shen Y, Liang Q, Li J, Hong G, Yan H, Cai H, Li M, Guan Q, Guo Z . Multi-omics landscapes of colorectal cancer subtypes discriminated by an individualized prognostic signature for 5-fluorouracil-based chemotherapy. Oncogenesis, 2016,5(7):e242
[21] Hafner M, Niepel M, Subramanian K, Sorger PK . Designing drug-response experiments and quantifying their results. Curr Protoc Chem Biol, 2017,9(2):96-116.
[22] Sartor ITS, Recamonde-Mendoza M, Ashton-Prolla P . TULP3: A potential biomarker in colorectal cancer? PLoS One, 2019,14(1):e0210762.
[23] Zeng H, Li H, Zhao YN, Chen LY, Ma XL . Transcripto- based network analysis reveals a model of gene activation in tongue squamous cell carcinomas. Head Neck, 2019,41(12):4098-4110.
[24] Miao ZF, Zhao TT, Wang ZN, Xu YY, Song YX, Wu JH, Xu HM . SCC-S2 is overexpressed in colon cancers and regulates cell proliferation. Tumour Biol, 2012,33(6):2099-2106.
[25] Wang J, Gao HY, Liu GH, Gu LN, Yang C, Zhang FM, Liu TB . Tumor necrosis factor α-induced protein 8 expression as a predictor of prognosis and resistance in patients with advanced ovarian cancer treated with neoadjuvant chemotherapy. Hum Pathol, 2018,82:239-248.
[26] Yang W, Wu B, Ma N, Wang YF, Guo JH, Zhu J, Zhao SH . BATF2 reverses multidrug resistance of human gastric cancer cells by suppressing Wnt/β-catenin signaling. In Vitro Cell Dev Biol Anim. 2019,55(6):445-452.
[27] Stebbing J, Shah K, Lit LC, Gagliano T, Ditsiou A, Wang T, Wendler F, Simon T, Szabó KS, O'Hanlon T, Dean M, Roslani AC, Cheah SH, Lee SC, Giamas G, . LMTK3 confers chemo-resistance in breast cancer. Oncogene, 2018,37(23):3113-3130.
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