ReviewFrontiers in oncology2026
Integrated perspectives on colorectal carcinogenesis: molecular pathogenesis, genomic alterations, diagnostic paradigms, therapeutic interventions and AI-driven directions in precision oncology.
Review in Frontiers in oncology, 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.
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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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3 authors.
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Abstract
Colorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality worldwide, with a notable rise in incidence among younger populations and in developing nations. This review provides an integrative perspective on the molecular pathogenesis, epidemiology, classification, diagnosis, and therapeutic strategies in CRC. We emphasize the pivotal role of three major molecular pathways - chromosomal instability (CIN), microsatellite instability (MSI), and CpG island methylator phenotype (CIMP) and their association with tumor heterogeneity and clinical outcomes. The analysis highlights key risk factors including lifestyle-related variables and genetic predisposition, alongside emerging molecular subtypes that influence prognosis and therapeutic decision-making. Advances in non-invasive diagnostics, such as fecal immunochemical testing (FIT) and novel biomarker discovery, demonstrate potential for improving early detection and screening compliance. Preventive strategies encompassing lifestyle modification, chemoprevention, and vitamin D supplementation, coupled with tailored therapeutic interventions including monoclonal antibodies and targeted therapies, offer promising avenues for reducing disease burden. The review also explores recent advances in multi-omics integration and artificial intelligence driven analytics, which have transformed biomarker discovery, subtype classification, and therapeutic prediction in CRC. Emerging applications of machine learning (ML), radiogenomics, and quantum computing further highlight a paradigm shift toward precision oncology. This review underscores the need for precision oncology approaches that integrate molecular profiling, patient stratification, and personalized treatment to enhance health care delivery and clinical outcomes in CRC.
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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 OpenQuestion graph.