ArticleCellular & molecular biology letters2026
KRAS
Article in Cellular & molecular biology letters, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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
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Authors and funding
11 authors.
Funding
Abstract
backgroundNeoadjuvant chemoradiotherapy (nCRT) is the standard treatment for locally advanced rectal cancer (LARC), yet clinically validated biomarkers for predicting response remain lacking. This study aimed to identify candidate molecular events associated with nCRT response and to develop a pretreatment prediction framework integrating genomic and pathological information.
methodsWhole-exome sequencing (WES) was performed on pretreatment tumors from 67 patients with LARC, and an additional 22 published WES cases were integrated to compare genomic differences between responders (R) and nonresponders (NR). Using histopathological whole-slide images (WSIs; n = 106) and genome-derived features, a weakly supervised, multimodal deep learning fusion model was developed to predict nCRT response. Multiomics profiling was used for exploratory pathway characterization, and functional assays were conducted in colorectal cancer cell lines and mouse models harboring KRAS
resultsWES identified 41 response-associated hotspot codon events. KRAS
conclusionsThe proposed genome-pathology fusion model provides a research-oriented framework for pretreatment prediction and risk stratification of nCRT response in LARC. KRAS
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