Evidence map›Paper›PMID 35522142›Full record

ArticleJournal of clinical laboratory analysis2022

Construction of a necroptosis-related lncRNA signature to predict the prognosis and immune microenvironment of head and neck squamous cell carcinoma.

Juntao Huang, Ziqian Xu, Bing Mei Teh, Chongchang Zhou, Zhechen Yuan, Yunbin Shi, Yi Shen

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical laboratory analysis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

16 citing papers in PubMed, 17 citations in OpenAlex.

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  2. MGenes & diseases · 2024
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  15. A Novel Necroptosis-Related lncRNA Signature for Osteosarcoma.Computational and mathematical methods in medicine · 2022
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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

7 authors at 3 institutions in 2 countries.

Juntao HuangDepartment of Otolaryngology Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, Zhejiang, China.ORCID https://orcid.org/0000-0002-0206-9365
Ziqian XuDepartment of Dermatology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Bing Mei TehDepartment of Ear Nose and Throat, Head and Neck Surgery, Eastern Health, Box Hill, Victoria, Australia.
Chongchang ZhouDepartment of Otolaryngology Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, Zhejiang, China.ORCID https://orcid.org/0000-0002-8728-6819
Zhechen YuanDepartment of Otolaryngology Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, Zhejiang, China.
Yunbin ShiDepartment of Otolaryngology Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, Zhejiang, China.
Yi ShenDepartment of Otolaryngology Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, Zhejiang, China.
Ningbo University · CNEastern Health · AUShanghai Jiao Tong University · CN

Funding

National Natural Science Foundation of China 81670920Ningbo Natural Science Foundation 2018A610363Ningbo Public Science Research Foundation 2021S170Zhejiang Provincial Medical and Health Science Research Foundation 2020KY274Zhejiang Provincial Medical and Health Science Research Foundation 2020RC107Zhejiang Provincial Medical and Health Science Research Foundation 2022KY1086
6 · The paper itself

Abstract

backgroundPrevious studies have determined that necroptosis-related genes are potential biomarkers in head and neck squamous cell carcinoma (HNSCC). Herein, we established a novel risk model based on necroptosis-related lncRNAs (nrlncRNAs) to predict the prognosis of HNSCC patients.

methodsTranscriptome and related information were obtained from TCGA database, and an nrlncRNA signature was established based on univariate Cox analysis and least absolute shrinkage and selection operator Cox regression. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) analysis were used to evaluate the model, and a nomogram for survival prediction was established. Gene set enrichment analysis, immune analysis, drug sensitivity analysis, correlation with N6-methylandenosin (m6A), and tumor stemness analysis were performed. Furthermore, the entire set was divided into two clusters for further discussion.

resultsA novel signature was established with six nrlncRNAs. The areas under the ROC curves (AUCs) for 1-, 3-, and 5-year overall survival (OS) were 0.699, 0.686, and 0.645, respectively. Patients in low-risk group and cluster 2 had a better prognosis, more immune cell infiltration, higher immune function activity, and higher immune scores; however, patients in high-risk group and cluster 1 were more sensitive to chemotherapy. Moreover, the risk score had negative correlation with m6A-related gene expression and tumor stemness.

conclusionAccording to this study, we constructed a novel signature with nrlncRNA pairs to predict the survival of HNSCC patients and guide immunotherapy and chemotherapy. This may possibly promote the development of individualized and precise treatment for HNSCC patients.

Indexed as

Head and Neck NeoplasmsRNA, Long NoncodingHumansNecroptosisPrognosisSquamous Cell Carcinoma of Head and NeckTumor MicroenvironmentRNA, Long Noncodinghead and neck squamous cell carcinomaimmunotherapylong non-coding RNAnecroptosisprognosis

Identifiers

PMID35522142
PMCPMC9169178
OpenAlexW4229010823

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.