Evidence map›Paper›PMID 36263048›Full record

ArticleFrontiers in immunology2022

Natural killer cell-related prognosis signature characterizes immune landscape and predicts prognosis of HNSCC.

Hao Chi, Xixi Xie, Yingjie Yan, Gaoge Peng, Dorothee Franziska Strohmer, Guichuan Lai, Songyun Zhao, Zhijia Xia, Gang Tian

Abstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
107citing papers in PubMed, 1 pooled it
–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

107 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  4. Cancer metabolism: bridging tumorigenesis mechanisms to treatment susceptibility.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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47 more citing papers are in PubMed but not listed here.

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

9 authors.

Hao ChiClinical Medical College, Southwest Medical University, Luzhou, China.
Xixi XieSchool of Stomatology, Southwest Medical University, Luzhou, China.
Yingjie YanDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China.
Gaoge PengClinical Medical College, Southwest Medical University, Luzhou, China.
Dorothee Franziska StrohmerDepartment of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany.
Guichuan LaiDepartment of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China.
Songyun ZhaoDepartment of Neurosurgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China.
Zhijia XiaDepartment of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany.
Gang TianDepartment of Laboratory Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Head and neck squamous cell carcinoma (HNSCC), the most common head and neck cancer, is highly aggressive and heterogeneous, resulting in variable prognoses and immunotherapeutic outcomes. Natural killer (NK) cells play essential roles in malignancies' development, diagnosis, and prognosis. The purpose of this study was to establish a reliable signature based on genes related to NK cells (NRGs), thus providing a new perspective for assessing immunotherapy response and prognosis of HNSCC patients. Methods: In this study, NRGs were used to classify HNSCC from the TCGA-HNSCC and GEO cohorts. The genes were evaluated using univariate cox regression analysis based on the differential analysis of normal and tumor samples in TCGA-HNSCC conducted using the "limma" R package. Thereafter, we built prognostic gene signatures using LASSO-COX analysis. External validation was carried out in the GSE41613 cohort. Immunity analysis based on NRGs was performed Results: With the TCGA-HNSCC data, we established a nomogram based on the 17-NRGs signature and a variety of clinicopathological characteristics. The low-risk group exhibited a better effect when it came to immunotherapy. Conclusions: 17-NRGs signature and nomograms demonstrate excellent predictive performance and offer new perspectives for assessing pre-immune efficacy, which will facilitate future precision immuno-oncology research.

Indexed as

Head and Neck NeoplasmsHumansKiller Cells, NaturalNomogramsPrognosisSquamous Cell Carcinoma of Head and NeckHNSCCimmunotherapynatural killer cellprognostic signaturetumor microenvironment

Identifiers

PMID36263048
PMCPMC9575041

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.