Evidence map›Paper›PMID 42222405›Full record

ReviewFrontiers in oncology2026

Integrated perspectives on colorectal carcinogenesis: molecular pathogenesis, genomic alterations, diagnostic paradigms, therapeutic interventions and AI-driven directions in precision oncology.

Sidharth Kumar N, Sai Kiruthiga S, Magesh Ramasamy

Abstract readReview
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Sidharth Kumar NDepartment of Biotechnology, Faculty of Biomedical Sciences & Technology, Sri Ramachandra Institute of Higher Education and Research (DU), Chennai, India.
Sai Kiruthiga SDepartment of Biotechnology, Faculty of Biomedical Sciences & Technology, Sri Ramachandra Institute of Higher Education and Research (DU), Chennai, India.
Magesh RamasamyDepartment of Biotechnology, Faculty of Biomedical Sciences & Technology, Sri Ramachandra Institute of Higher Education and Research (DU), Chennai, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

chromosomal instabilitycolorectal cancerhealth caremachine learningmicrosatellite instabilityquantum computing

Identifiers

PMID42222405
PMCPMC13215890

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.