Evidence map›Paper›PMID 35713693›Full record

ArticleArchives of gynecology and obstetrics2023

Comprehensive analysis of novel prognosis-related proteomic signature effectively improve risk stratification and precision treatment for patients with cervical cancer.

Xiaoyu Ji, Guangdi Chu, Yulong Chen, Jinwen Jiao, Teng Lv, Qin Yao

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Article in Archives of gynecology and obstetrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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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.

Xiaoyu Ji *Department of Obstetrics and Gynecology, Affiliated Hospital of Qingdao University, No. 1677 Wutaishan Road, Qingdao, 266000, China.
Guangdi Chu *Department of Urology, Affiliated Hospital of Qingdao University, No. 16 Jiangsu Road, Qingdao, 266000, China.
Yulong ChenDepartment of Obstetrics and Gynecology, Affiliated Hospital of Qingdao University, No. 1677 Wutaishan Road, Qingdao, 266000, China.
Jinwen JiaoDepartment of Obstetrics and Gynecology, Affiliated Hospital of Qingdao University, No. 1677 Wutaishan Road, Qingdao, 266000, China.
Teng LvDepartment of Obstetrics and Gynecology, Affiliated Hospital of Qingdao University, No. 1677 Wutaishan Road, Qingdao, 266000, China.
Qin YaoDepartment of Obstetrics and Gynecology, Affiliated Hospital of Qingdao University, No. 1677 Wutaishan Road, Qingdao, 266000, China. dr_yaoqin@126.com.ORCID http://orcid.org/0000-0003-1546-1048

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveCervical cancer (CC) is one of the most common types of malignant female cancer, and its incidence and mortality are not optimistic. Protein panels can be a powerful prognostic factor for many types of cancer. The purpose of our study was to investigate a proteomic panel to predict the survival of patients with common CC. METHODS AND

resultsThe protein expression and clinicopathological data of CC were downloaded from The Cancer Proteome Atlas and The Cancer Genome Atlas database, respectively. We selected the prognosis-related proteins (PRPs) by univariate Cox regression analysis and found that the results of functional enrichment analysis were mainly related to apoptosis. We used Kaplan-Meier analysis and multivariable Cox regression analysis further to screen PRPs to establish a prognostic model, including BCL2, SMAD3, and 4EBP1-pT70. The signature was verified to be independent predictors of OS by Cox regression analysis and the area under curves. Nomogram and subgroup classification were established based on the signature to verify its clinical application. Furthermore, we looked for the co-expressed proteins of three-protein panel as potential prognostic proteins.

conclusionA proteomic signature independently predicted OS of CC patients, and the predictive ability was better than the clinicopathological characteristics. This signature can help improve prediction for clinical outcome and provides new targets for CC treatment.

Indexed as

Uterine Cervical NeoplasmsFemaleHumansNomogramsPrognosisProteomicsRisk AssessmentCervical cancerPrognosisProteomic panelTCGATCPA

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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 Socratic graph.