ArticleCancers2026
Prognostic Impact of RTK-RAS Alterations in FOLFOX-Treated Early-Onset Colorectal Cancer Revealed by Artificial Intelligence-Driven Precision Oncology.
Article in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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
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
2 citing papers in PubMed.
- Deciphering RTK-RAS and MAPK Pathway Dependencies in Gemcitabine-Treated Pancreatic Ductal Adenocarcinoma Through Conversational Artificial Intelligence.International journal of molecular sciences · 2026Article
- Conversational Artificial Intelligence Agents-Enabled Dissection of RTK-RAS and MAPK Pathway Dependencies in Gemcitabine-Treated Pancreatic Ductal Adenocarcinoma (PDAC).medRxiv : the preprint server for health sciences · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
BACKGROUND/
objectivesEarly-onset colorectal cancer (EOCRC; diagnosed before age 50) is rising at an accelerated rate, with a disproportionate impact on underserved populations. While alterations in the receptor tyrosine kinase-RAS (RTK-RAS) signaling pathway play a fundamental role in colorectal cancer (CRC) biology, their prognostic significance in the setting of FOLFOX chemotherapy-particularly across different age groups and ancestral backgrounds-remains insufficiently characterized. We sought to characterize age-, ancestry-, and treatment-specific associations between RTK-RAS alterations and clinical outcomes using an AI-enabled precision oncology framework.
methodsWe analyzed 2515 CRC cases, including 266 Hispanic/Latino (H/L) and 2249 non-Hispanic White (NHW) patients, stratified by age at onset, ancestry, and FOLFOX treatment status. Mutation frequencies were assessed using Fisher's exact and chi-square tests, while overall survival was analyzed with Kaplan-Meier methods. The AI-HOPE and AI-HOPE-RTK-RAS conversational artificial intelligence platforms were used to integrate clinical, genomic, and treatment data via multi-parameter, natural language-based queries.
resultsIn early-onset Hispanic/Latino patients, ERBB2 and NF1 mutations occurred at significantly lower frequencies in FOLFOX-treated cases compared with untreated cases (
conclusionsRTK-RAS pathway alterations demonstrate strong age-, ancestry-, and treatment-specific prognostic effects and may serve as precision biomarkers of differential chemotherapy response. AI-enabled analytics substantially accelerated integrative biomarker discovery, supporting their utility for advancing precision oncology in EOCRC.
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Registered trials
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