Evidence map›Paper›PMID 36639648›Full record

SynthesisBMC cancer2023

A meta-validated immune infiltration-related gene model predicts prognosis and immunotherapy sensitivity in HNSCC.

Yinghe Ding, Ling Chu, Qingtai Cao, Hanyu Lei, Xinyu Li, Quan Zhuang

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
9.0field-weighted citation impact, top 2% 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, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Deciphering the Role of Mast Cells in HPV-Related Cancers.International journal of molecular sciences · 2025
    Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Type I conventional dendritic cells and CD8Frontiers in immunology · 2024
    Article
  15. Article
  16. Article
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 1 institution in 2 countries.

Yinghe Ding *Transplantation Center, The 3rd Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
Ling Chu *Department of Pathology, The 3rd Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
Qingtai Cao *Transplantation Center, The 3rd Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
Hanyu LeiTransplantation Center, The 3rd Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
Xinyu LiTransplantation Center, The 3rd Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
Quan ZhuangTransplantation Center, The 3rd Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China. zhuangquansteven@163.com.
Central South University · CN

Funding

National Natural Science Foundation of China 81700658Natural Science Foundation of Hunan Province 2020JJ3058
6 · The paper itself

Abstract

backgroundTumor microenvironment (TME) is of great importance to regulate the initiation and advance of cancer. The immune infiltration patterns of TME have been considered to impact the prognosis and immunotherapy sensitivity in Head and Neck squamous cell carcinoma (HNSCC). Whereas, specific molecular targets and cell components involved in the HNSCC tumor microenvironment remain a twilight zone.

methodsImmune scores of TCGA-HNSCC patients were calculated via ESTIMATE algorithm, followed by weighted gene co-expression network analysis (WGCNA) to filter immune infiltration-related gene modules. Univariate, the least absolute shrinkage and selection operator (LASSO), and multivariate cox regression were applied to construct the prognostic model. The predictive capacity was validated by meta-analysis including external dataset GSE65858, GSE41613 and GSE686. Model candidate genes were verified at mRNA and protein levels using public database and independent specimens of immunohistochemistry. Immunotherapy-treated cohort GSE159067, TIDE and CIBERSORT were used to evaluate the features of immunotherapy responsiveness and immune infiltration in HNSCC.

resultsImmune microenvironment was significantly associated with the prognosis of HNSCC patients. Total 277 immune infiltration-related genes were filtered by WGCNA and involved in various immune processes. Cox regression identified nine prognostic immune infiltration-related genes (MORF4L2, CTSL1, TBC1D2, C5orf15, LIPA, WIPF1, CXCL13, TMEM173, ISG20) to build a risk score. Most candidate genes were highly expressed in HNSCC tissues at mRNA and protein levels. Survival meta-analysis illustrated high prognostic accuracy of the model in the discovery cohort and validation cohort. Higher proportion of progression-free outcomes, lower TIDE scores and higher expression levels of immune checkpoint genes indicated enhanced immunotherapy responsiveness in low-risk patients. Decreased memory B cells, CD8+ T cells, follicular helper T cells, regulatory T cells, and increased activated dendritic cells and activated mast cells were identified as crucial immune cells in the TME of high-risk patients.

conclusionsThe immune infiltration-related gene model was well-qualified and provided novel biomarkers for the prognosis of HNSCC.

Indexed as

AlgorithmsHead and Neck NeoplasmsCytoskeletal ProteinsHumansImmunotherapyIntracellular Signaling Peptides and ProteinsPrognosisSquamous Cell Carcinoma of Head and NeckTranscription FactorsTumor MicroenvironmentCytoskeletal ProteinsIntracellular Signaling Peptides and ProteinsMORF4L2 protein, humanTranscription FactorsWIPF1 protein, humanHead and neck squamous cell carcinomaImmune cell infiltrationImmunotherapy sensitivityPrognostic modelTumor microenvironment

Identifiers

PMID36639648
PMCPMC9837972
OpenAlexW4315866342

What OpenQuestion 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 OpenQuestion graph.