Evidence map›Paper›PMID 36082469›Full record

ArticleJournal of clinical laboratory analysis2022

Identification of cuproptosis-related subtypes and characterization of the tumor microenvironment landscape in head and neck squamous cell carcinoma.

Juntao Huang, Ziqian Xu, Zhechen Yuan, Lixin Cheng, Chongchang Zhou, 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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

11 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Review
  3. Integrative machine learning and neural networks for identifying PANoptosis-related lncRNA molecular subtypes and constructing a predictive model for head and neck squamous cell carcinoma.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2024
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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

6 authors at 2 institutions in 1 country.

Juntao HuangDepartment of Otolaryngology Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, 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.
Zhechen YuanDepartment of Otolaryngology Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, China.
Lixin ChengDepartment of Otolaryngology Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, China.
Chongchang ZhouDepartment of Otolaryngology Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, China.ORCID https://orcid.org/0000-0002-8728-6819
Yi ShenDepartment of Otolaryngology Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, China.
Ningbo University · CNShanghai 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

backgroundCuproptosis is considered a novel copper-dependent cell death model. In this study, we established a novel scoring system based on 10 cuproptosis-related genes (CRGs) to predict the prognosis and immune landscape of head and neck squamous cell carcinoma (HNSCC).

methodsThe RNA-seq data of HNSCC patients were downloaded from the GEO and TCGA databases and were merged into a novel HNSCC cohort. Multiomics landscape analyses were conducted, including tumor mutation burden (TMB), copy number variations and the interaction network of CRGs. Patients were then divided into different cuproptosis subtypes based on the expression of 10 CRGs and subsequently regrouped into novel gene clusters referring to differentially expressed genes. A cuproptosis score (CS) system was established using principal component analysis. The CIBERSORT, ssGSEA and ESTIMATE algorithms were used to assess the tumor immune microenvironment. Moreover, the immunotherapeutic and chemotherapeutic responses were assessed.

resultsPatients were divided into three cuproptosis subtypes and subsequently regrouped into three gene clusters, reflecting different immune infiltration. Assessed by the CS system, those with higher CSs exhibited worse prognosis and higher TMB frequency. Nevertheless, the immune-related analysis revealed patients in the low-CS group appeared immunosuppressive and easily suffered from immune escape. High CSs possibly show high expression of immune checkpoint genes and enhance chemotherapy sensitivity to cisplatin, docetaxel, and gemcitabine.

conclusionWe established a novel scoring system to predict the prognosis and immune landscape of HNSCC patients. This signature exhibits satisfactory predictive effects and the potential to guide comprehensive treatment for patients.

Indexed as

ApoptosisHead and Neck NeoplasmsSquamous Cell Carcinoma of Head and NeckTumor MicroenvironmentCopperDNA Copy Number VariationsHumansPrognosisTranscriptomeCopperchemotherapycuproptosishead and neck squamous cell carcinomaimmunotherapyprognosis

Identifiers

PMID36082469
PMCPMC9459342
OpenAlexW4289101244

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.