ArticleCurrent medicinal chemistry2026
Identification of Drug-resistant Cell Subpopulations in Colorectal Cancer Through Single-cell Analysis and Exploration of Potential Therapeutic Strategies.
Article in Current medicinal chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
introductionThe therapeutic efficacy of Colorectal Cancer (CRC) is often compromised by resistance to the standard chemotherapy agent oxaliplatin.
methodsThis study obtained single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database. Differentially Expressed Genes (DEGs) between resistant and sensitive epithelial subpopulations were identified, followed by enrichment analysis. Pseudotemporal trajectory and cell-cell communication were analyzed using Monocle2 and CellChat, respectively. The candidate drug was predicted by Connectivity Map (cMAP) analysis. External validation included assessment of the EpC2 signature in an oxaliplatin-resistant cell line dataset (GSE76092), survival analysis using The Cancer Genome Atlas (TCGA) cohorts, and re-analysis of the GSE179784 dataset to assess the reproducibility of EpC2-like subpopulations and their DNA Damage Repair (DDR) scores.
resultsCell subpopulations were divided into 10 clusters. Among them, epithelial cells comprised 5 subpopulations, with EPC2 identified as a potential oxaliplatin-resistant subset. DEGs were enriched in the TNF and IL-17 pathways. External validation confirmed the enrichment of EpC2 in resistant cell lines and its association with poor survival. Pseudotemporal trajectory revealed that epithelial cells underwent state transitions, forming two distinct branches. The resistant group exhibited enrichment in RNA splicing and NF-κB pathways. Cell-cell communication analysis revealed interactions involving MDK- NCL and PPIA-BSG. Dasatinib was predicted as a candidate drug. DISCUSSION: We identified an oxaliplatin-resistant subpopulation of Epithelial Cells (EpC2) in CRC, elucidated its multi-layered resistance mechanisms, and integrated multi- omics and cMAP database analyses to predict a potential intervention drug.
conclusionThis study provided potential therapeutic possibilities for oxaliplatin resistance, contributing to CRC treatment.
Indexed as
Identifiers
42003098What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.