Evidence map›Paper›PMID 41815545›Full record

ReviewFrontiers in oncology2026

Emerging role of low-frequency somatic mutations in cancer relapse: from early detection to precision oncology.

Eunsoo Kim, Gu Seob Roh, Seong Gyu Kwon

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.

Eunsoo KimCollege of Medicine, Gyeongsang National University, Jinju, Republic of Korea.
Gu Seob RohDepartment of Anatomy, College of Medicine, Metabolic Dysfunction liver disease Research Center, Institute of Medical Science, Gyeongsang National University, Jinju, Republic of Korea.
Seong Gyu KwonDepartment of Anatomy and Convergence Medical Science, College of Medicine, Institute of Medical Science, Gyeongsang National University, Jinju, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Somatic mutations with low variant allele frequencies offer a highly sensitive lens for detecting cancer relapse driven by diverse causes, including clonal evolution and therapy resistance. Advances in next-generation sequencing have enabled robust subclonal variant identification that typically fall below conventional detection limits, supporting a comprehensive understanding of individual molecular profiles that can lead to relapse. These low-level alterations frequently emerge before clinical or radiological relapse and can inform response-adaptive treatment decisions. This review integrates the current biological and technical insights into low-frequency mutations and evaluates their emerging roles in tumor relapse management and precision oncology.

Indexed as

cancer relapselow-VAFnext-generation sequencingsomatic mutationultra-deep sequencing

Identifiers

PMID41815545
PMCPMC12971448

What OpenQuestion holds

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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.