基于结直肠癌细胞系MIC50相关基因对的基础耐药 评分模型构建

doi:10.16288/j.yczz.19-336

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Hereditas(Beijing) ›› 2020, Vol. 42 ›› Issue (6): 577-585.doi: 10.16288/j.yczz.19-336

• Research Article • Previous Articles Next Articles

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

Huxing Chen, Lei Xu, Jing Li, Zheng Guo, Lu Ao()

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:2020-01-06 Revised:2020-04-29 Online:2020-06-20 Published:2020-05-25
Contact: Ao Lu E-mail:lukey@fjmu.edu.cn
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

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 MIC₅₀which 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.

Key words: cancer cell lines, general levels of drug resistance, MIC₅₀

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.

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数据集	平台	样本数	联合用药样本	用药类型	文献
GSE72968	GPL570	68	68^a	FUFOL/FOLFOX/FOLFIRI	[9]
GSE72969	GPL570	56	28^b	FOLFOX/FOLFIRI/FOLFIRINOX	[10]
GSE28702	GPL570	83	56^c	FOLFOX	[11]

药物类型	总相关系数数目	正相关系数数目	正相关系数比例(%)
全部药物	8204	8185	99.80
靶向药物	6770	6754	99.76
化疗药物	107	107	100

MCODE	通路ID	通路名称	Log₁₀(P)值
1	R-HSA-373076	视紫红质样受体(class A/1 (rhodopsin-like receptors))	-16.9
1	R-HSA-418594	G alpha (i)信号事件(G alpha (i) signalling events)	-16
1	R-HSA-500792	GPCR配体结合(GPCR ligand binding)	-15.5
2	hsa00240	嘧啶代谢(pyrimidine metabolism)	-5.8
2	hsa01200	碳代谢(carbon metabolism)	-5.7
2	GO:0019693	磷酸核糖代谢过程(ribose phosphate metabolic process)	-5.3
3	R-HSA-416476	G alpha (q)信号事件(G alpha (q) signalling events)	-10.3
3	R-HSA-500792	GPCR配体结合(GPCR ligand binding)	-6.2
3	R-HSA-375276	肽配体结合受体(peptide ligand-binding receptors)	-5.3
4	R-HSA-72163	mRNA剪接-主要途径(mRNA Splicing-Major Pathway)	-8.5
4	R-HSA-72172	mRNA剪接(mRNA Splicing)	-8.4
4	R-HSA-72203	mRNA前体加工(processing of capped intron-containing pre-mRNA)	-8.0

序号	基因对(Ga > Gb)	序号	基因对(Ga > Gb)	序号	基因对(Ga > Gb)
1	BATF2> HDDC2	8	LRP4> ASMTL	15	TBC1D2B> ESPNL
2	BATF2> TAZ	9	SIM2> MBD2	16	TNFAIP8> KCNH2
3	BATF2> TULP3	10	SPRR2G > LMTK3	17	TMEM38B> SLC26A3
4	CELSR3> AGTRAP	11	WFS1> GOLT1A	18	TMEM38B> PCF11
5	EPHX2> KCNH2	12	IL1RL2> OR1D2	19	RHOU > PCF11
6	GSTM3> NID1	13	IL1RL2> ZDHHC14	20	HMGB4> SMIM10
7	GSTM3> NOD1	14	PREB > TMEM60	21	CCDC17> FAM110B

数据集	样本数	低分组响应率	高分组响应率	P值
GSE72968	68	84% (21/25)	37.2% (16/43)	0.00019
GSE72969	28	71.4% (10/14)	28.5% (4/14)	0.02334
GSE28702	56	76% (19/25)	38.7% (12/31)	0.00526

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

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