An Integrative Transcriptomic Analysis of a Stemness-Associated Gene Set on Ovarian Cancer Recurrence
Year: 2026
Type: preprint
Abstract: Ovarian cancer (OC) is a highly lethal gynaecological malignancy, with a five-year survival rate of less than 30%. Although most patients initially respond to platinum-based chemotherapy, disease relapse occurs in approximately 70–80% of cases, largely due to persistence of cancer stem cells (CSCs). In this study, we investigated the expression of a literature-supported set of six stemness-associated genes previously implicated in OC recurrence: ALDH1A1, ALDH1A2, ALDH1A3, NANOG, PROM1 (CD133), and SOX2, in primary OC (POC) (n=421) and recurrent OC (ROC) (n=62). RNA-seq datasets were obtained from “The Cancer Genome Atlas Program (TCGA)”. An ovarian cancer stem cell (OCSC) dataset obtained from the “Gene Expression Omnibus (GEO)” was used as a reference for comparing tumor profiles with the POC and ROC groups. Differential expression between POC and ROC was assessed using statistical tests, and the findings were experimentally validated by qRT-PCR (POC (n = 8); ROC (n = 8)). In the TCGA dataset, SOX2 and PROM1 were upregulated in ROC compared with POC, while ALDH1A1 showed decreased expression. qRT-PCR validation confirmed significant upregulation of SOX2 and PROM1 in recurrent tumors, supporting their association with CSC-related transcriptional programs in recurrent disease. In contrast, ALDH1A1 showed a statistically significant increase in the qRT-PCR cohort, a trend opposite to the TCGA dataset, while ALDH1A3 showed a slight but consistent elevation, and ALDH1A2 remained unchanged. These findings suggest that OC recurrence is associated with expression alterations in transcriptional and metabolic stem cell-related regulators, consistent with the enrichment of OCSC-like features observed in recurrent tumors.
Source: Research Square
Institution: Istanbul University
Language: English
Topic: Cancer Cells and Metastasis
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7166462412