Evidence map›Paper›PMID 37063862›Full record

ArticleFrontiers in immunology2023

CD4+ conventional T cells-related genes signature is a prognostic indicator for ovarian cancer.

Tian Hua, Deng-Xiang Liu, Xiao-Chong Zhang, Shao-Teng Li, Peng Yan, Qun Zhao, Shu-Bo Chen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

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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 1 country.

Tian HuaDepartment of Gynecology, Affiliated Xingtai People Hospital of Hebei Medical University, Xingtai, China.
Deng-Xiang LiuDepartment of Oncology, Affiliated Xingtai People Hospital of Hebei Medical University, Xingtai, China.
Xiao-Chong ZhangDepartment of Oncology, Affiliated Xingtai People Hospital of Hebei Medical University, Xingtai, China.
Shao-Teng LiDepartment of Oncology, Affiliated Xingtai People Hospital of Hebei Medical University, Xingtai, China.
Peng YanDepartment of Oncology, The Second Affiliated Hospital Of Xingtai Medical College, Xingtai, China.
Qun ZhaoDepartment of Oncology, Hebei Medical University, Fourth Hospital, Shijiazhuang, China.
Shu-Bo ChenDepartment of Oncology, Affiliated Xingtai People Hospital of Hebei Medical University, Xingtai, China.
Xingtai People's Hospital · CNFourth Hospital of Hebei Medical University · CNHebei Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: It is believed that ovarian cancer (OC) is the most deadly form of gynecological cancer despite its infrequent occurrence, which makes it one of the most salient public health concerns. Clinical and preclinical studies have revealed that intratumoral CD4+ T cells possess cytotoxic capabilities and were capable of directly killing cancer cells. This study aimed to identify the CD4+ conventional T cells-related genes (CD4TGs) with respect to the prognosis in OC. Methods: We obtained the transcriptome and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD4TGs were first identified from single-cell datasets, then univariate Cox regression was used to screen prognosis-related genes, LASSO was conducted to remove genes with coefficient zero, and multivariate Cox regression was used to calculate riskscore and to construct the CD4TGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), decision curve analysis (DCA), nomogram, and calibration were made to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in risk groups were conducted to explore the tightly correlated pathways with the risk group. The role of riskscore has been further explored in the tumor microenvironment (TME), immunotherapy, and chemotherapy. A risk signature with 11 CD4TGs in OC was finally established in the TCGA database and furtherly validated in several GEO cohorts. Results: High riskscore was significantly associated with a poorer prognosis and proven to be an independent prognostic biomarker by multivariate Cox regression. The 1-, 3-, and 5-year ROC values, DCA curve, nomogram, and calibration results confirmed the excellent prediction power of this model. Compared with the reported risk models, our model showed better performance. The patients were grouped into high-risk and low-risk subgroups according to the riskscore by the median value. The low-risk group patients tended to exhibit a higher immune infiltration, immune-related gene expression and were more sensitive to immunotherapy and chemotherapy. Discussion: Collectively, our findings of the prognostic value of CD4TGs in prognosis and immune response, provided valuable insights into the molecular mechanisms and clinical management of OC.

Indexed as

Ovarian NeoplasmsCalibrationCD4-Positive T-LymphocytesFemaleHumansNomogramsPrognosisTumor MicroenvironmentCD4+ conventional T cellsimmunotherapyovarian cancerprognostic signaturetumor microenvironment

Identifiers

PMID37063862
PMCPMC10104164
OpenAlexW4361267753

What OpenQuestion holds

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LicenceCC BY
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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.