Evidence map›Paper›PMID 35804390›Full record

ArticleWorld journal of surgical oncology2022

A signature of immune-related gene pairs (IRGPs) for risk stratification and prognosis of oral cancer patients.

Yanling Yu, Jing Tian, Yanni Hou, Xinxin Zhang, Linhua Li, Peifu Cong, Lei Ji, Xuri Wang

Open access · goldAbstract read
In one paragraph

Article in World journal of surgical oncology, 2022. 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
0.1field-weighted citation impact, top 61% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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 at 3 institutions in 1 country.

Yanling YuDepartment of Stomatology, Weihai Central Hospital, Weihai, China.
Jing TianDepartment of Stomatology, Feicheng Hospital Affiliated to Shandong First Medical University, Taian, China.
Yanni HouDepartment of Special Dental Care Clinic, Wendeng Stomatology Hospital, Weihai, Shandong, China.
Xinxin ZhangDepartment of Stomatology, Feicheng Hospital Affiliated to Shandong First Medical University, Taian, China.
Linhua LiRepair Department of Stomatology, Shouguang Stomatology Hospital, Weifang, China.
Peifu CongDepartment of Stomatology, Weihai Central Hospital, Weihai, China.
Lei JiOperating room, Weihai Central Hospital, Weihai, China.
Xuri WangDepartment of Stomatology, Weihai Central Hospital, Weihai, China. wangxuri7@163.com.
Weihai Chest Hospital · CNAffiliated Hospital of Taishan Medical University · CNStomatology Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith low response to present immunotherapy, it is imperative to identify new immune-related biomarkers for more effective immunotherapies for oral cancer.

methodsRNA profiles for 390 oral cancer patients and 32 normal samples were downloaded from The Cancer Genome Atlas (TCGA) database and differentially expressed genes (DEGs) were analyzed. Immune genesets from ImmPort repository were overlapped with DEGs. After implementing univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis, key immune-related gene pairs (IRGPs) among the overlapped DEGs for predicting the survival risk were obtained. Then, the cutoff of risk score was calculated by the receiver operating characteristic (ROC) curve to stratify oral cancer patients into high and low-risk groups. Multivariate Cox analysis was used to analyze independent prognostic indicators for oral cancer. Besides, infiltration of immune cells, functional annotation, and mutation analysis of IRGPs were conducted. Biological functions correlated with IRGPs were enriched by Gene Set Enrichment Analysis (GSEA) method.

resultsWe identified 698 differentially expressed genes (DEGs) in response to oral cancer. 17 IRGPs among the DEGs were identified and integrated into a risk score model. Patients in the high-risk group have a significantly worse prognosis than those in the low-risk group in both training (P<0.001) and test (P=0.019) cohorts. Meanwhile, the IRGP model was identified as an independent prognostic factor for oral cancer. Different infiltration patterns of immune cells were found between the high- and low-risk groups that more types of T and B cells were enriched in the low-risk group. More immune-related signaling pathways were highly enriched in the low-risk group and Tenascin C (TNC) was the most frequently mutated gene. We have developed a novel 17-IRGPs signature for risk stratification and prognostic prediction of oral cancer.

conclusionOur study provides a foundation for improved immunotherapy and prognosis and is beneficial to the individualized management of oral cancer patients.

Indexed as

Gene Expression Regulation, NeoplasticMouth NeoplasmsBiomarkers, TumorHumansPrognosisRisk AssessmentBiomarkers, TumorBiomarkerImmune infiltrationImmunotherapyOral cancerPrognosis

Identifiers

PMID35804390
PMCPMC9264557
OpenAlexW4284899382

What OpenQuestion holds

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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.