Targeted proteomics-determined multi-biomarker profiles developed classifier for prognosis and immunotherapy responses of advanced cervical cancer.

Autor:	Zhang X; NHC Key Laboratory of Reproduction Regulation, Shanghai Engineering Research Center of Reproductive Health Drug and Devices, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China.; Shanghai-MOST Key Laboratory of Health and Disease Genomics, NHC Key Laboratory of Reproduction Regulation, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China., Li J; Department of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China.; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China., Yang L; College of Plant Protection, Nanjing Agricultural University, Nanjing, China., Zhu Y; Clinical Center of Bio-Therapy at Zhongshan Hospital & Institutes of Biomedical Sciences, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China., Gao R; Clinical Center for Biotherapy at Zhongshan Hospital, Fudan University, Shanghai, China., Zhang T; NHC Key Laboratory of Reproduction Regulation, Shanghai Engineering Research Center of Reproductive Health Drug and Devices, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China.; Shanghai-MOST Key Laboratory of Health and Disease Genomics, NHC Key Laboratory of Reproduction Regulation, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China., Chen X; Shanghai Kelin Clinical Bioinformatics Institute, Shanghai, China., Fu J; LC-Bio Technology Co., Ltd, Hangzhou, China., He G; LC-Bio Technology Co., Ltd, Hangzhou, China., Shi H; NHC Key Laboratory of Reproduction Regulation, Shanghai Engineering Research Center of Reproductive Health Drug and Devices, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China.; Shanghai-MOST Key Laboratory of Health and Disease Genomics, NHC Key Laboratory of Reproduction Regulation, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China., Peng S; Shanghai Medical College of Fudan University, Fudan University, Shanghai, China., Wu X; Department of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China.; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Jazyk:	angličtina
Zdroj:	Frontiers in immunology [Front Immunol] 2024 May 21; Vol. 15, pp. 1391524. Date of Electronic Publication: 2024 May 21 (Print Publication: 2024).
DOI:	10.3389/fimmu.2024.1391524
Abstrakt:	Background: Cervical cancer (CC) poses a global health challenge, with a particularly poor prognosis in cases of recurrence, metastasis, or advanced stages. A single biomarker is inadequate to predict CC prognosis or identify CC patients likely to benefit from immunotherapy, presumably owing to tumor complexity and heterogeneity. Methods: Using advanced Olink proteomics, we analyzed 92 oncology-related proteins in plasma from CC patients receiving immunotherapy, based upon the comparison of protein expression levels of pre-therapy with those of therapy-Cycle 6 in the partial response (PR) group and progressive disease (PD) group, respectively. Results: 55 proteins were identified to exhibit differential expression trends across pre-therapy and post-therapy in both PR and PD groups. Enriched GO terms and KEGG pathways were associated with vital oncological and immunological processes. A logistic regression model, using 5 proteins (ITGB5, TGF-α, TLR3, WIF-1, and ERBB3) with highest AUC values, demonstrated good predictive performance for prognosis of CC patients undergoing immunotherapy and showed potential across different cancer types. The effectiveness of these proteins in prognosis prediction was further validated using TCGA-CESC datasets. A negative correlation and previously unidentified roles of WIF-1 in CC immunotherapy was also first determined. Conclusion: Our findings reveal multi-biomarker profiles effectively predicting CC prognosis and identifying patients benefitting most from immunotherapy, especially for those with limited treatment options and traditionally poor prognosis, paving the way for personalized immunotherapeutic treatments and improved clinical strategies. Competing Interests: Authors JF and GH were employed by the company LC-Bio Technology Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2024 Zhang, Li, Yang, Zhu, Gao, Zhang, Chen, Fu, He, Shi, Peng and Wu.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu