Evidence map›Paper›PMID 31741756›Full record

ArticleOncoimmunology

Identification of a prognostic immune signature for cervical cancer to predict survival and response to immune checkpoint inhibitors.

Si Yang, Ying Wu, Yujiao Deng, Linghui Zhou, Pengtao Yang, Yi Zheng, Dai Zhang, Zhen Zhai, Na Li, Qian Hao and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncoimmunology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 96 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
96citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

96 citing papers in PubMed, 1 synthesis or guideline pooled it.

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36 more citing papers are in PubMed but not listed here.

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

13 authors.

Si YangDepartment of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Ying WuDepartment of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Yujiao DengDepartment of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Linghui ZhouDepartment of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Pengtao YangDepartment of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Yi ZhengDepartment of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Dai ZhangDepartment of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Zhen ZhaiDepartment of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Na LiDepartment of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Qian HaoDepartment of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Dingli SongDepartment of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Huafeng KangDepartment of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Zhijun DaiDepartment of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cervical cancer (CC) is a leading cause of cancer-related death in women. Limited studies have investigated whether immune-related genes (IRGs) or tumor immune microenvironment (TIME) could be indicators for CC prognoses. The aim of this study was to develop an improved prognostic signature for CC based on IRGs or TIME to predict survival and response to immune checkpoint inhibitors (ICIs). A prognostic signature was constructed using bioinformatics method and its predictive capability was validated. The mechanisms underlying the signature's predictive capability were explored with CIBERSORT algorithm and mutation analysis. Immunophenoscore (IPS) is validated for ICIs response, and was therefore explored in relation to the signature. A prognostic signature based on 11 IRGs was developed. A multivariate analysis revealed that the 11-IRG signature was an independent prognostic factor for overall survival (OS) and progression-free interval in CC patients. In the 11-IRG signature high-risk group, CD8 T cells and resting mast cells, which are found to associate with better OS in our study, were lower; activated mast cells, associated with poorer OS, were higher, compared with the low-risk group. An IPS analysis suggested that the 11-IRG signature low-risk group, which possessed a higher IPS, represented a more immunogenic phenotype that was more inclined to respond to ICIs. In short, an 11-IRG prognostic signature for predicting CC patients' survival and response to ICIs was firmly established. The predictive capability of this model in CC requires further testing with the goal of better prognostic stratification and treatment management.

Indexed as

cervical cancerimmune checkpoint inhibitor responseImmune signatureprognosistumor immune microenvironment

Identifiers

PMID31741756
PMCPMC6844304

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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.