ArticleJournal of cellular and molecular medicine2018
The impact on high-grade serous ovarian cancer of obesity and lipid metabolism-related gene expression patterns: the underestimated driving force affecting prognosis.
Article in Journal of cellular and molecular medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- Metabolic Targeting of SREBP1 Reprograms the Obesity-Driven Ascites Immune Microenvironment and Enhances Chemotherapy Response in Obesity-Associated Ovarian Cancer.bioRxiv : the preprint server for biology · 2026Article
- Ovarian tumor microenvironment contributes to tumor progression and chemoresistance.Cancer drug resistance (Alhambra, Calif.) · 2024Review
- Host obesity alters the ovarian tumor immune microenvironment and impacts response to standard of care chemotherapy.Journal of experimental & clinical cancer research : CR · 2023Article
- Article
- Advances and development of prostate cancer, treatment, and strategies: A systemic review.Frontiers in cell and developmental biology · 2022Review
- Obesity and gynecological cancers: A toxic relationship.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2021Article
- A Forgotten Corner in Cancer Immunotherapy: The Role of Lipids.Frontiers in oncology · 2021Review
- A FITM1-Related Methylation Signature Predicts the Prognosis of Patients With Non-Viral Hepatocellular Carcinoma.Frontiers in genetics · 2020Article
- Leptin contributes to the taxol chemoresistance in epithelial ovarian cancer.Oncology letters · 2019Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To investigate whether specific obesity/metabolism-related gene expression patterns affect the survival of patients with ovarian cancer. Clinical and genomic data of 590 samples from the high-grade ovarian serous carcinoma (HGOSC) study of The Cancer Genome Atlas (TCGA) and 91 samples from the Australian Ovarian Cancer Study were downloaded from the International Cancer Genome Consortium (ICGC) portal. Clustering of mRNA microarray and reverse-phase protein array (RPPA) data was performed with 83 consensus driver genes and 144 obesity and lipid metabolism-related genes. Association between different clusters and survival was analyzed with the Kaplan-Meier method and a Cox regression. Mutually exclusive, co-occurrence and network analyses were also carried out. Using RNA and RPPA data, it was possible to identify two subsets of HGOSCs with similar clinical characteristics and cancer driver mutation profiles (e.g. TP53), but with different outcome. These differences depend more on up-regulation of specific obesity and lipid metabolism-related genes than on the number of gene mutations or copy number alterations. It was also found that CD36 and TGF-ß are highly up-regulated at the protein levels in the cluster with the poorer outcome. In contrast, BSCL2 is highly up-regulated in the cluster with better progression-free and overall survival. Different obesity/metabolism-related gene expression patterns constitute a risk factor for prognosis independent of the therapy results in the Cox regression. Prognoses were conditioned by the differential expression of obesity and lipid metabolism-related genes in HGOSCs with similar cancer driver mutation profiles, independent of the initial therapeutic response.
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