ArticleCancers2023
Characteristics of ABCC4 and ABCG2 High Expression Subpopulations in CRC-A New Opportunity to Predict Therapy Response.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- Bis-(di-4-phenyl-benzylaminethiocarbonyl)disulfide sensitizes ABCC2/ALDH3A1 overexpressing NSCLC cells to cisplatin.Cancer biology & therapy · 2026Article
- ABCG2 transporter: Structural and functional associations with gout (Review).International journal of molecular medicine · 2026Review
- Serum uric acid and its metabolism-a vital factor in the inflammatory transformation of cancer.Journal of advanced research · 2026Review
- Genetic underpinnings of type-2 diabetes (T2D) with colorectal cancer (CRC): In-silico discovery of common molecular signatures, pathogenetic processes and therapeutic candidates.Journal, genetic engineering & biotechnology · 2026Article
- A preliminary bioinformatic screen to identify SRI SMC2 PSIP1 TLE4 and MSX1 as potential diagnostic and prognostic markers of osteoarthritis.Scientific reports · 2025Article
- The Expression Level of SOX Family Transcription Factors' mRNA as a Diagnostic Marker for Osteoarthritis.Journal of clinical medicine · 2025Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
backgroundOur previous findings proved that ABCC4 and ABCG2 proteins present much more complex roles in colorectal cancer (CRC) than typically cancer-associated functions as drug exporters. Our objective was to evaluate their predictive/diagnostic potential.
methodsCRC patients' transcriptomic data from the Gene Expression Omnibus database (GSE18105, GSE21510 and GSE41568) were discriminated into two subpopulations presenting either high expression levels of ABCC4 (ABCC4 High) or ABCG2 (ABCG2 High). Subpopulations were analysed using various bioinformatical tools and platforms (KEEG, Gene Ontology, FunRich v3.1.3, TIMER2.0 and STRING 12.0).
resultsThe analysed subpopulations present different gene expression patterns. The protein-protein interaction network of subpopulation-specific genes revealed the top hub proteins in ABCC4 High: RPS27A, SRSF1, DDX3X, BPTF, RBBP7, POLR1B, HNRNPA2B1, PSMD14, NOP58 and EIF2S3 and in ABCG2 High: MAPK3, HIST2H2BE, LMNA, HIST1H2BD, HIST1H2BK, HIST1H2AC, FYN, TLR4, FLNA and HIST1H2AJ. Additionally, our multi-omics analysis proved that the ABCC4 expression correlates with substantially increased tumour-associated macrophage infiltration and sensitivity to FOLFOX treatment.
conclusionsABCC4 and ABCG2 may be used to distinguish CRC subpopulations that present different molecular and physiological functions. The ABCC4 High subpopulation demonstrates significant EMT reprogramming, RNA metabolism and high response to DNA damage stimuli. The ABCG2 High subpopulation may resist the anti-EGFR therapy, presenting higher proteolytical activity.
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