Interactions among tumor subtype, <scp>PPARγ</scp> expression, and adipose proliferation shape outcomes in breast cancer

Breast cancer progression is influenced by tumor subtype, metabolic environment, and patient factors, including menopausal status and BMI. In this study, we utilized publicly available data to investigate the prognostic relevance of PPARγ gene's expression across different subgroups. We also examined adipose tissue proliferation in patients with various tumor subtypes and phenotypic cohorts. We analyzed RNA-seq data from primary breast cancer patients in the TCGA-BRCA cohort, stratifying patients by PPARγ expression, menopausal status, and tumor receptor subtype. Kaplan-Meier analyses revealed that high PPARγ expression was associated with improved overall survival, particularly in premenopausal patients. Complementing this, we analyzed PET-CT scans from breast cancer patients in the ACRIN-6888 trial, focusing on standardized uptake value (SUV) metrics of a cell cycle tracer, 3'-deoxy-3'-[18F]-fluorothymidine (<sup>18</sup>F-FLT) in visceral and subcutaneous adipose tissue. Postmenopausal patients had lower visceral adipose tissue SUV<sub>mean</sub>, and patients with ER+ or non-TNBC tumors showed lower SUV<sub>peak</sub> and SUV<sub>max</sub> of both adipose tissue types, indicating metabolic/proliferative reprogramming of adipose tissue based on tumor subtype. We hypothesize that PPARγ expression and adipose proliferation differentially affect survival across subtypes and menopausal status, providing deeper insight into PPARγ as a therapeutic target in breast cancer and the potential implications for precision medicine treatments.

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Publication Details

Journal
Physiological Reports
Published
2025-11-01
DOI
https://doi.org/10.14814/phy2.70649
Citations
1
Primary Topic
Peroxisome Proliferator-Activated Receptors
Type
article
Field-Weighted Citation Impact
0.81

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article

Interactions among tumor subtype, PPARγ expression, and adipose proliferation shape outcomes in breast cancer

Katie Liu, Rachel J. Perry, Curtis J. Perry, Gautham Ramshankar et al.
1 citations
Physiological Reports
Peroxisome Proliferator-Activated Receptors
0.81
article

Interactions among tumor subtype, PPARγ expression, and adipose proliferation shape outcomes in breast cancer

Katie Liu, Rachel J. Perry, Curtis J. Perry, Gautham Ramshankar, Aditya Shah, Ryan Liu
article en
1 citations

Abstract

Breast cancer progression is influenced by tumor subtype, metabolic environment, and patient factors, including menopausal status and BMI. In this study, we utilized publicly available data to investigate the prognostic relevance of PPARγ gene's expression across different subgroups. We also examined adipose tissue proliferation in patients with various tumor subtypes and phenotypic cohorts. We analyzed RNA-seq data from primary breast cancer patients in the TCGA-BRCA cohort, stratifying patients by PPARγ expression, menopausal status, and tumor receptor subtype. Kaplan-Meier analyses revealed that high PPARγ expression was associated with improved overall survival, particularly in premenopausal patients. Complementing this, we analyzed PET-CT scans from breast cancer patients in the ACRIN-6888 trial, focusing on standardized uptake value (SUV) metrics of a cell cycle tracer, 3'-deoxy-3'-[18F]-fluorothymidine (<sup>18</sup>F-FLT) in visceral and subcutaneous adipose tissue. Postmenopausal patients had lower visceral adipose tissue SUV<sub>mean</sub>, and patients with ER+ or non-TNBC tumors showed lower SUV<sub>peak</sub> and SUV<sub>max</sub> of both adipose tissue types, indicating metabolic/proliferative reprogramming of adipose tissue based on tumor subtype. We hypothesize that PPARγ expression and adipose proliferation differentially affect survival across subtypes and menopausal status, providing deeper insight into PPARγ as a therapeutic target in breast cancer and the potential implications for precision medicine treatments.

Physiological ReportsVol. 13(21)
Brown University (US), Yale Cancer Center (US), Yale University (US), Iowa Academy of Science (US), Suffolk Horse Society (GB)
National Institutes of Health, National Cancer Institute
Openalex Percentile: Top 22%
Peroxisome Proliferator-Activated Receptors
0.81
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