Evidence map›Paper›PMID 42358548›Full record

ReviewFrontiers in oncology2026

Long-read sequencing for cancer liquid biopsy: advancing precision oncology.

Grace Guzman, Analiz Rodriguez

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Grace GuzmanDepartment of Neurosurgery, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Analiz RodriguezDepartment of Neurosurgery, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liquid biopsy, which involves the study of tumor-derived genetic material shed into circulating body fluids, is a rapidly emerging minimally invasive approach for cancer diagnosis and monitoring. Most current cancer liquid biopsy workflows depend on short-read sequencing (SRS). However, SRS methods remain limited in their ability to detect and resolve structural variants (SVs), haplotype phasing, fusion transcripts, and epigenetic modifications. Long-read sequencing (LRS) technologies, including single-molecule real-time (SMRT) and nanopore sequencing, offer opportunities to overcome these limitations by preserving long-range molecular information and enabling multimodal characterization of tumor-derived material in biofluids. In this mini-review, we discuss the emerging role of LRS in cancer liquid biopsy, with primary emphasis on cell-free DNA (cfDNA) and circulating tumor DNA (ctDNA). We summarize recent studies using LRS-based liquid biopsy across multiple cancer types. Particular focus is placed on cancer types most actively investigated to date, such as lung, brain, and pediatric cancers, in which LRS-based liquid biopsy has shown promise in detecting SVs, methylation patterns, and tumor-of-origin (TOF) signals that may not be fully captured by SRS approaches. We also examine current technical and translational barriers of LRS in cancer liquid biopsy, such as pre-analytical variability, cost, and high computational demands. As sequencing technologies and analytical pipelines continue to advance, LRS is likely to serve as a complementary component of multimodal liquid biopsy strategies in precision oncology.

Indexed as

cancer liquid biopsycfDNA (cell-free DNA)ctDNA (circulating tumor DNA)long-read sequencing (LRS)precision oncology

Identifiers

PMID42358548
PMCPMC13290525

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.