Evidence map›Paper›PMID 37121970›Full record

ArticleExperimental & molecular medicine2023

The role of the genomic mutation signature and tumor mutation burden on relapse risk prediction in head and neck squamous cell carcinoma after concurrent chemoradiotherapy.

Hui-Ching Wang, Sin-Hua Moi, Leong-Perng Chan, Chun-Chieh Wu, Jeng-Shiun Du, Pei-Lin Liu, Meng-Chun Chou, Che-Wei Wu, Chih-Jen Huang, Hui-Hua Hsiao and 2 more

Open access · goldAbstract read
In one paragraph

Article in Experimental & molecular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.7field-weighted citation impact, top 17% of its field
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

8 citing papers in PubMed, 5 citations in OpenAlex.

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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

12 authors at 3 institutions in 1 country.

Hui-Ching WangGraduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
Sin-Hua MoiGraduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
Leong-Perng ChanFaculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
Chun-Chieh WuDepartment of Pathology, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
Jeng-Shiun DuGraduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
Pei-Lin LiuDepartment of Nursing, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
Meng-Chun ChouDepartment of Nursing, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
Che-Wei WuFaculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
Chih-Jen HuangFaculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
Hui-Hua HsiaoDepartment of Internal Medicine, Division of Hematology and Oncology, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
Mei-Ren Pan *Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan. mrpan@cc.kmu.edu.tw.
Li-Tzong Chen *Department of Internal Medicine, Division of Hematology and Oncology, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, 807, Taiwan. leochen@nhri.org.tw.
Kaohsiung Medical University · TWKaohsiung Medical University Chung-Ho Memorial Hospital · TWNational Health Research Institutes · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Personalized genetic profiling has focused on improving treatment efficacy and predicting risk stratification by identifying mutated genes and selecting targeted agents according to genetic testing. Therefore, we evaluated the role of genetic profiling and tumor mutation burden (TMB) using next-generation sequencing in patients with head and neck squamous cell carcinoma (HNSC). The relapse mutation signature (RMS) and chromatin remodeling mutation signature (CRMS) were explored to predict the risk of relapse in patients with HNSC treated with concurrent chemoradiotherapy (CCRT) with platinum-based chemotherapy. Patients in the high RMS and CRMS groups showed significantly shorter relapse-free survival than those in the low RMS and CRMS groups, respectively (p < 0.001 and p = 0.006). Multivariate Cox regression analysis showed that extranodal extension, CCRT response, and three somatic mutation profiles (TMB, RMS, and CRMS) were independent risk predictors for HNSC relapse. The predictive nomogram showed satisfactory performance in predicting relapse-free survival in patients with HNSC treated with CCRT.

Indexed as

Carcinoma, Squamous CellHead and Neck NeoplasmsBiomarkers, TumorChemoradiotherapyGenomicsHumansMutationSquamous Cell Carcinoma of Head and NeckBiomarkers, Tumor

Identifiers

PMID37121970
PMCPMC10238468
OpenAlexW4367555522

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LicenceCC BY
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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.