Identification of tumor microenvironment-related prognostic biomarkers for ovarian tumor disease-free survival

Keyu Pan; Sijia Cai

doi:10.1117/12.3021672

8 January 2024 Identification of tumor microenvironment-related prognostic biomarkers for ovarian tumor disease-free survival

Keyu Pan, Sijia Cai

Author Affiliations +

Proceedings Volume 12924, Third International Conference on Biological Engineering and Medical Science (ICBioMed2023); 1292445 (2024) https://doi.org/10.1117/12.3021672
Event: 3rd International Conference on Biological Engineering and Medical Science (ICBioMed2023), 2023, ONLINE, United Kingdom

Abstract

Serous ovarian cancer (SeOvCa) is a lethal disease and it has a late-stage diagnosis and high recurrence rates. This study used The Cancer Genome Atlas (TCGA) data to identify immune-related genes and establish a prognostic model for SeOvCa recurrence. Differential gene expression analysis was described, resulting in the selection of 14 significant genes. The TME score, incorporating these genes, correlated with poorer survival outcomes. Combining these genes with known ovarian cancer genes improved the prognostic model. This study indicates the importance of the tumor microenvironment in SeOvCa prognosis and provides insights for personalized treatment strategies.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Keyu Pan and Sijia Cai "Identification of tumor microenvironment-related prognostic biomarkers for ovarian tumor disease-free survival", Proc. SPIE 12924, Third International Conference on Biological Engineering and Medical Science (ICBioMed2023), 1292445 (8 January 2024); https://doi.org/10.1117/12.3021672

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