ArticleCancers2026
Conversational AI-Enabled Precision Oncology Reveals Context-Dependent MAPK Pathway Alterations in Hispanic/Latino and Non-Hispanic White Colorectal Cancer Stratified by Age and FOLFOX Exposure.
Article in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
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Who cites it
6 citing papers in PubMed.
- Application of Systems Genetics to Investigate Molecular Pathology of Early-Onset Colorectal Cancer.Chemical biology & drug design · 2026Review
- Pathway-Centric Comparative Molecular Profiling of Sézary Syndrome and Primary Cutaneous CD8Cancers · 2026Article
- A Conversational Artificial Intelligence Framework for Comparative Pathway-Level Profiling of Sézary Syndrome and Primary Cutaneous CD8medRxiv : the preprint server for health sciences · 2026Article
- 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-Enabled Molecular Characterization of Sézary Syndrome Reveals Distinct Pathway-Level Alterations Compared with Non-Sézary Cutaneous T-Cell Lymphoma.medRxiv : the preprint server for health 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
backgroundColorectal cancer (CRC) demonstrates substantial clinical and biological diversity across age groups, ancestral backgrounds, and treatment settings, alongside a rising incidence of early-onset disease (EOCRC). The mitogen-activated protein kinase (MAPK) pathway is a major driver of CRC development and therapy response; however, the distribution and prognostic value of MAPK alterations across distinct patient subgroups remain unclear.
methodsWe analyzed 2515 CRC tumors with harmonized demographic, clinical, genomic, and treatment metadata. Patients were stratified by ancestry (Hispanic/Latino [H/L] vs. non-Hispanic White [NHW]), age at diagnosis (early-onset [EO] vs. late-onset [LO]), and FOLFOX chemotherapy exposure. MAPK pathway alterations were identified using a curated gene set encompassing canonical EGFR-RAS-RAF-MEK-ERK signaling components and regulatory nodes. Conversational artificial intelligence (AI-HOPE and AI-HOPE-MAPK) enabled natural language-driven cohort construction and exploratory analytics; findings were validated using Fisher's exact testing, chi-square analyses, and Kaplan-Meier survival estimates.
resultsMAPK pathway disruption demonstrated marked heterogeneity across ancestry and treatment contexts. Among EO H/L patients,
conclusionsAlthough MAPK alterations are pervasive in CRC, their distribution varies meaningfully by ancestry, age, and treatment exposure. These findings highlight
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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 Socratic graph.