Evidence map›Paper›PMID 41930252›Full record

ReviewFrontiers in molecular biosciences2026

Navigating the molecular landscape: integrated multiomics liquid biopsy for biomarker discovery in early detection and monitoring of colorectal cancer.

Xuanqiang Fan, Jinyu Shi, Yiwan Shang, Hui Xu

Abstract readReview
In one paragraph

Review in Frontiers in molecular biosciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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

4 authors.

Xuanqiang Fan *The Third Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou, China.
Jinyu Shi *School of Chinese Medicine, Henan University of Traditional Chinese Medicine, Zhengzhou, China.
Yiwan Shang *School of Chinese Medicine, Henan University of Traditional Chinese Medicine, Zhengzhou, China.
Hui XuThe Third Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The elevated mortality associated with colorectal cancer is largely due to delayed diagnosis and post-treatment disease recurrence, highlighting the urgent clinical need for molecular markers with exceptional sensitivity and specificity to support early detection and longitudinal disease monitoring. Although conventional liquid biopsy methods targeting single analytes have clinical value, they have inherent limitations in terms of early screening sensitivity, specificity, and tissue-of-origin identification. This review systematically catalogs multiomics biomarker discoveries and summarizes integration strategies for liquid biopsy in colorectal cancer, highlighting how the combination of genomic, epigenomic, transcriptomic, proteomic, and metabolomic signals can improve early detection, MRD monitoring, and treatment guidance. By synthesizing the existing literature, we focus on how this integrated approach overcomes the constraints of single-signal detection, comprehensively delineates the molecular landscape of colorectal cancer, and advances the development of high-performance multiomics biomarker panels. Furthermore, this review explores recent progress in the application of bioinformatics and artificial intelligence-driven cross-omics integration models to optimize biomarker panel performance. In summary, this comprehensive analysis of multiomics integration not only clarifies approaches to molecular marker discovery but also provides a theoretical basis for refining clinical management strategies for colorectal cancer, thereby establishing a framework for precision oncology practices built on continuous molecular surveillance.

Indexed as

artificial intelligencebioinformaticscolorectal cancerliquid biopsymolecular markersmultiomics

Identifiers

PMID41930252
PMCPMC13038510

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

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.