Evidence map›Paper›PMID 34040608›Full record

ArticleFrontiers in immunology2021

Development and Validation of a CD8+ T Cell Infiltration-Related Signature for Melanoma Patients.

Yuan Yuan, Zheng Zhu, Ying Lan, Saili Duan, Ziqing Zhu, Xi Zhang, Guoyin Li, Hui Qu, Yanhui Feng, Hui Cai and 1 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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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

11 authors.

Yuan YuanSchool of Engineering and Applied Sciences, Harvard University, Cambridge, MA, United States.
Zheng ZhuDepartment of Medicine, Brigham and Women's Hospital, Boston, MA, United States.
Ying LanSchool of Nursing, Yueyang Vocational and Technical College, Yueyang, China.
Saili DuanDepartment of Oncology, The Third Xiangya Hospital of Central South University, Changsha, China.
Ziqing ZhuDepartment of Oncology, The Third Xiangya Hospital of Central South University, Changsha, China.
Xi ZhangDepartment of Oncology, The Third Xiangya Hospital of Central South University, Changsha, China.
Guoyin LiCollege of Life Science and Agronomy, Zhoukou Normal University, Zhoukou, China.
Hui QuDepartment of Plastic Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Taiyuan, China.
Yanhui FengDepartment of Oncology, The Third Xiangya Hospital of Central South University, Changsha, China.
Hui CaiDepartment of Orthopaedics, Loudi Central Hospital, Loudi, China.
Zewen SongDepartment of Oncology, The Third Xiangya Hospital of Central South University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: Immunotherapy shows efficacy in only a subset of melanoma patients. Here, we intended to construct a risk score model to predict melanoma patients' sensitivity to immunotherapy. Methods: Integration analyses were performed on melanoma patients from high-dimensional public datasets. The CD8+ T cell infiltration related genes (TIRGs) were selected Results: 184 candidate TIRGs were identified in melanoma patients. Based on the candidate TIRGs, melanoma patients were classified into three clusters which were characterized by different immune activity. Six signature genes were further screened out of 184 TIRGs and a representative risk score for patient survival was constructed based on these six signature genes. The risk score served as an indicator for the level of CD8+ T cell infiltration and acted as an independent prognostic factor for the survival of melanoma patients. By using the risk score, we achieved a good predicting result for the response of cancer patients to immunotherapy. Moreover, pan-cancer analysis revealed the risk score could be used in a wide range of non-hematologic tumors. Conclusions: Our results showed the potential of using signature gene-based risk score as an indicator to predict melanoma patients' sensitivity to immunotherapy.

Indexed as

BiomarkersAlgorithmsBiomarkers, TumorCD8-Positive T-LymphocytesComputational BiologyDatabases, GeneticGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLymphocytes, Tumor-InfiltratingMelanomaMutationPrognosisProportional Hazards ModelsTranscriptomeTumor MicroenvironmentBiomarkersBiomarkers, TumorCD8+ T cellsimmune responseimmunotherapymelanomasingle cell RNA sequencing analysis

Identifiers

PMID34040608
PMCPMC8141567

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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.