Evidence map›Paper›PMID 42023149›Full record

ArticleiScience2026

LCPBert: ProtBERT-based early-stage lung cancer prediction from T cell receptor beta sequences.

Xin Yang, Yuwei Zhou, Zixuan Zhang, Huaichao Luo, Jian Huang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 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

5 authors.

Xin YangDepartment of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Yuwei ZhouDepartment of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Zixuan ZhangDepartment of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Huaichao LuoDepartment of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China.
Jian HuangDepartment of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early detection of lung cancer remains challenging due to limitations of current methods. We developed LCPBert, a deep learning framework leveraging peripheral blood T cell receptor beta (TCRβ) repertoires for early detection of lung cancer. LCPBert accurately discriminated lung cancer-associated TCRs (test AUC = 0.82). Based on LCRI (lung cancer risk index), LCPBert robustly stratified lung cancer risk in the external validation cohort: healthy donors (0.111 ± 0.058), benign pulmonary nodules (0.184 ± 0.113), lung cancer (0.296 ± 0.166;

Indexed as

biological sciencescancer systems biologyimmunological methodsimmunology

Identifiers

PMID42023149
PMCPMC13098609

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.