Evidence map›Paper›PMID 39962932›Full record

ArticleOral diseases2025

Deciphering Disulfidptosis-Linked lncRNA Patterns as Potential HNSCC Biomarkers.

Qi Chen, Xiao Shi, Yuanyuan Bao, Yue Chen

Abstract read
In one paragraph

Article in Oral diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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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

2 citing papers in PubMed.

  1. Review
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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

4 authors.

Qi ChenDivision of Life Sciences and Medicine, Department of Dermatology, Anhui Provincial Hospital, The First Affiliated Hospital of the University of Science and Technology of China (USTC), Hefei, China.
Xiao ShiDivision of Life Sciences and Medicine, Department of Gastroenterology, Anhui Provincial Hospital, The First Affiliated Hospital of the University of Science and Technology of China (USTC), Hefei, China.
Yuanyuan BaoCCIC Huatongwei International Inspection (Suzhou) Co., Ltd, Suzhou, China.
Yue ChenDivision of Life Sciences and Medicine, Department of Surgery, Anhui Provincial Hospital, The First Affiliated Hospital of the University of Science and Technology of China (USTC), Hefei, China.ORCID https://orcid.org/0000-0001-8888-1452

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOur investigation sought to uncover the intrinsic features of Head and Neck Squamous Cell Carcinoma (HNSCC), particularly the role of long non-coding RNAs implicated in disulfidptosis (DRLs). MATERIALS AND

methodsWe carried out lncRNA-mRNA RNA-Seq studies on HNSCC cells and harnessed the data from The Cancer Genome Atlas (TCGA), which includes 522 HNSCC tumors and 44 normal specimens. Bioinformatics evaluations aided in recognizing DRLs and estimating their prognostic value. Furthermore, we built a predictive model related to the chosen DRLs to scrutinize its linkage with the patients' prognosis. We also dug into tumor mutation loads and responses to chemotherapy.

resultsOur study identified three key DRLs (LINC02434, AC245041.2, and LINC02762) with considerable correlation to HNSCC prognosis. The risk model, utilizing these DRLs, successfully categorized patients into high-risk and low-risk clusters, uncovering differential survival trajectories. Moreover, the same risk model conveyed unique prognostic potential in HNSCC. Surveying the tumor microenvironment unfolded disparities between the groups, hinting toward potential implications for tactics in immunotherapy. We recognized distinct chemotherapeutic drugs with fluctuating responses across the risk clusters and molecular categories.

conclusionThis investigation not only sheds light on prospective therapeutic pathways but also enhances our grasp of the molecular intricacies of HNSCC.

Indexed as

Biomarkers, TumorHead and Neck NeoplasmsRNA, Long NoncodingSquamous Cell Carcinoma of Head and NeckDisulfidptosisHumansPrognosisTumor MicroenvironmentBiomarkers, TumorRNA, Long Noncodingdisulfidptosisdrug sensitivityhead and neck squamous cell carcinomaLncRNAprognosis

Identifiers

PMID39962932
PMCPMC12291421

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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.