ArticleBiomedicines2022
Integrated Bioinformatics Analysis of the Hub Genes Involved in Irinotecan Resistance in Colorectal Cancer.
Article in Biomedicines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 20 citations in OpenAlex.
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- Mendelian Randomization Analysis of Mitochondria-Related Genes and Screening of Prognostic Genes in Colorectal Cancer.Cancer medicine · 2025Article
- Development and validation of a prognostic model for efferocytosis-associated genes in cervical squamous cell carcinoma.Discover oncology · 2025Article
- MiR-3664-3p through suppressingHeliyon · 2025Article
- The Expression Level of SOX Family Transcription Factors' mRNA as a Diagnostic Marker for Osteoarthritis.Journal of clinical medicine · 2025Article
- Predicting patient outcomes with gene-expression biomarkers from colorectal cancer organoids and cell lines.Frontiers in molecular biosciences · 2025Article
- Integrated Single-cell RNA-seq and Bulk RNA-seq Identify Diagnostic Biomarkers for Postmenopausal Osteoporosis.Current medicinal chemistry · 2025Article
- CancerHubs: a systematic data mining and elaboration approach for identifying novel cancer-related protein interaction hubs.Briefings in bioinformatics · 2024Article
- Radial Data Visualization-Based Step-by-Step Eliminative Algorithm to Predict Colorectal Cancer Patients' Response to FOLFOX Therapy.International journal of molecular sciences · 2024Article
- Sm-like 5 knockdown inhibits proliferation and promotes apoptosis of colon cancer cells by upregulating p53, CDKN1A and TNFRSF10B.World journal of gastrointestinal oncology · 2024Article
- Characteristics of ABCC4 and ABCG2 High Expression Subpopulations in CRC-A New Opportunity to Predict Therapy Response.Cancers · 2023Article
- The Comparison of Serum Exosome Protein Profile in Diagnosis of NSCLC Patients.International journal of molecular sciences · 2023Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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