期刊
BIOMEDICINES
卷 10, 期 7, 页码 -出版社
MDPI
DOI: 10.3390/biomedicines10071720
关键词
CRC; irinotecan resistance; multidrug resistance; chemotherapy; integrated bioinformatics analysis
资金
- Institute of Medical Biology of the Polish Academy of Sciences
Different drug combinations, including irinotecan, are important in treating colorectal cancer (CRC). However, chemotherapy often leads to drug resistance. This study compared mRNA expression profiles of CRC cell lines and patient samples to select new candidate genes for irinotecan resistance. The results showed that in vitro models have limitations and cannot fully reflect the complex drug resistance network observed in patients.
Different drug combinations including irinotecan remain some of the most important therapeutic modalities in treating colorectal cancer (CRC). However, chemotherapy often leads to the acquisition of cancer drug resistance. To bridge the gap between in vitro and in vivo models, we compared the mRNA expression profiles of CRC cell lines (HT29, HTC116, and LoVo and their respective irinotecan-resistant variants) with patient samples to select new candidate genes for the validation of irinotecan resistance. Data were downloaded from the Gene Expression Omnibus (GEO) (GSE42387, GSE62080, and GSE18105) and the Human Protein Atlas databases and were subjected to an integrated bioinformatics analysis. The protein-protein interaction (PPI) network of differently expressed genes (DEGs) between FOLFIRI-resistant and -sensitive CRC patients delivered several potential irinotecan resistance markers: NDUFA2, SDHD, LSM5, DCAF4, COX10 RBM8A, TIMP1, QKI, TGOLN2, and PTGS2. The chosen DEGs were used to validate irinotecan-resistant cell line models, proving their substantial phylogenetic heterogeneity. These results indicated that in vitro models are highly limited and favor different mechanisms than in vivo, patient-derived ones. Thus, cell lines can be perfectly utilized to analyze specific mechanisms on their molecular levels but cannot mirror the complicated drug resistance network observed in patients.
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