Evidence map›Paper›PMID 41098273›Full record

ReviewCureus2025

Emerging Non-Invasive Biomarkers for Early Detection of Gastrointestinal Cancers.

Adeshpal Singh, Hemanth Kesani, Tareq Mohammed Saleh, Manju Rai

Abstract readReview
In one paragraph

Review in Cureus, 2025. 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. Article
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.

Adeshpal SinghInternal Medicine, Government Medical College, Amritsar, Amritsar, IND.
Hemanth KesaniInternal Medicine, Narayana Medical College, Nellore, IND.
Tareq Mohammed SalehInternal Medicine, Emilio Aguinaldo College School of Medicine, Manila, PHL.
Manju RaiBiotechnology, Shri Venkateshwara University, Gajraula, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastrointestinal (GI) cancers remain a leading cause of global cancer-related morbidity and mortality, underscoring the need for reliable biomarkers to improve early detection, risk stratification, and treatment monitoring. Over the past decade, significant progress has been made in identifying circulating and tissue-based biomarkers, including cell-free DNA, microRNAs, and metabolomic profiles, that offer potential for enhancing diagnostic accuracy and prognostic prediction. Integration of multi-omics approaches, spanning genomics, transcriptomics, proteomics, and metabolomics, has further expanded the biomarker landscape, enabling a more comprehensive understanding of tumor biology and individualized patient trajectories. Artificial intelligence and machine learning models are increasingly being applied to analyze complex datasets, yielding promising results in cancer risk prediction and progression monitoring. Despite these advances, translation into routine clinical practice is limited by technical variability, high costs, lack of standardized protocols, and the need for large-scale, multicenter validation studies. Moreover, ethical concerns, regulatory hurdles, and risks of overdiagnosis remain important barriers. Future directions emphasize the development of point-of-care biomarker testing kits, the incorporation of personalized screening strategies based on genetic and lifestyle risk profiles, and greater international collaboration for biomarker harmonization. Collectively, these advances highlight the transformative potential of biomarkers in reshaping GI cancer management, while also pointing to critical challenges that must be addressed to achieve meaningful clinical adoption.

Indexed as

artificial intelligence in healthbiomarkerscancer screeningcirculating tumor dnaearly detectiongastrointestinal cancersmetabolomicsmicrornamulti-omicsprecision oncology

Identifiers

PMID41098273
PMCPMC12520648

What OpenQuestion holds

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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 OpenQuestion graph.