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Integration of histopathological images and multi-dimensional omics analyses predicts molecular features and prognosis in high-grade serous ovarian cancer.

Gynecologic oncology - 1 Oct 2021

Zeng Hao, Chen Linyan, Zhang Mingxuan, Luo Yuling, Ma Xuelei

Abstract excerpt

OBJECTIVE: This study used histopathological image features to predict molecular features, and combined with multi-dimensional omics data to predict overall survival (OS) in high-grade serous ovarian cancer (HGSOC). METHODS: Patients from The Cancer Genome Atlas (TCGA) were distributed into training set (n = 115) and test set (n = 114). In addition, we collected tissue microarrays of 92 patients as an external...

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PMID: 34275655
DOI: 10.1016/j.ygyno.2021.07.015

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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