Evidence map›Paper›PMID 42164467›Full record

ArticleOncology letters2026

A novel prognostic biomarker combining

Yuli Li, Ting Hou, Hongjie Liu, Haiwei Du, Li Qiu, Yajing Zhang, Guiping Zhang, Yuan Tang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncology letters, 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

8 authors.

Yuli LiDepartment of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China.
Ting HouDepartment of Medical Affairs, Burning Rock Biotech, Guangzhou, Guangdong 510000, P.R. China.
Hongjie LiuDepartment of Medical Affairs, Burning Rock Biotech, Guangzhou, Guangdong 510000, P.R. China.
Haiwei DuDepartment of Medical Affairs, Burning Rock Biotech, Guangzhou, Guangdong 510000, P.R. China.
Li QiuDepartment of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China.
Yajing ZhangDepartment of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China.
Guiping ZhangDepartment of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China.
Yuan TangDepartment of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung squamous cell carcinoma (LUSC) is a prevalent subtype of lung cancer, which is primarily characterized by poor prognosis due to the lack of targeted therapies, while a large proportion of patients show limited response to chemotherapy. The present study aimed to identify predictive chemotherapy biomarkers based on genomic alterations in LUSC. Non-negative matrix factorization clustering was applied to classify patients with LUSC into distinct subgroups based on genomic alterations. Subsequently, chemotherapy efficacy was predicted via exploring gene signatures, and the results were validated using The Cancer Genome Atlas database (TCGA). A total of four distinct clusters were classified. Cluster 1 and

Indexed as

chemotherapy efficacyclustergene signaturelung squamous cell carcinomaprognostic marker

Identifiers

PMID42164467
PMCPMC13184589

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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.