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Exploring Lipidomic Profiles and Their Correlation with Hormone Receptor and HER2 Status in Breast Cancer

ABSTRACT: Dysregulated lipid metabolism promotes the progression of various cancers, including breast cancer. This study aimed to explore the lipidomic profiles of breast cancer patients, providing insights into the correlation between lipid compositions and tumor subtypes characterized by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status. Briefly, 30 breast cancer patients were categorized into four cohorts based on their HR and HER2 status: HR+, HER2 zero (HR+ HER2-0); HR+, HER2 low (HR+ HER2-low); HR+, HER2 pos (HR+ HER2-pos); and HR-, HER2 positive (HR- HER2-pos). Lipidomic profiles were analyzed using high-throughput liquid chromatography-mass spectrometry (LC-MS). Data were processed through principal component analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Random Forest (RF) classification to assess lipidomic variations and significant lipid features among these groups. Profiles of lipids, particularly triglycerides (TG) such as TG (16:0_18:1_18:1) +NH4, were significantly different across the cohorts. PCA and PLS-DA analyses identified unique lipid profiles in the HR+ HER2-pos and HR+ HER2-0 groups, while RF highlighted PIP3(21:2)+NH4 as a crucial lipid feature for accurate patient grouping. Advanced statistical analysis showed significant correlations between lipid carbon chain length and the number of double bonds with the classifications, providing insights into the role of structural lipid properties in tumor biology. Additionally, a clustering heatmap and network analysis indicated significant lipid-lipid interactions. Pathway enrichment analysis showed critical biological pathways, such as the assembly of active LPL and LIPC lipase complexes. In conclusion, the study underscores the importance of lipidomic profiling is crucial in understanding the metabolic alterations associated with different breast cancer subtypes. These findings highlight specific lipid features and interactions that may serve as potential biomarkers for breast cancer classification and target pathways for therapeutic intervention. Furthermore, advanced lipidomic analyses can be integrated to decipher complex biological data, offering a foundation for further research into the role of lipid metabolism in cancer progression.

INSTRUMENT(S): Liquid Chromatography MS - negative - reverse phase, Liquid Chromatography MS - positive - reverse phase

PROVIDER: MTBLS10858 | MetaboLights | 2024-08-16

REPOSITORIES: MetaboLights

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Project description:Breast cancer is a heterogeneous disease for which prognosis and treatment strategies are largely governed by the receptor status (estrogen, progesterone and Her2-neu) of the tumor cells. Gene expression profiling of whole breast tumors further stratifies breast cancer into several molecular subtypes which also co-segregate with the receptor status of the tumor cells. We postulated that cancer associated fibroblasts (CAFs) within the tumor stroma may exhibit subtype specific gene expression profiles and thus contribute to the biology of the disease in a subtype specific manner. Several studies have reported gene expression profile differences between CAFs and normal breast fibroblasts but in none of these studies were the results stratified based on tumor subtypes. To address whether gene expression in breast cancer associated fibroblasts varies between breast cancer subtypes, we compared the gene expression profiles of early passage primary CAFs isolated from twenty human breast cancer samples representing three main subtypes; seven ER+, seven triple negative (TNBC) and six Her2+. We observed significant expression differences between CAFs derived from Her2+ breast cancer and CAFs from TNBC and ER+ cancers, particularly in pathways associated with cytoskeleton and integrin signaling. In the case of Her2+ breast cancer, the signaling pathways found to be selectively up regulated in CAFs may contribute to the more invasive properties and unfavorable prognosis of Her2+ breast cancer. These data demonstrate that in addition to the distinct molecular profiles that characterize the neoplastic cells, CAF gene expression is also differentially regulated in distinct subtypes of breast cancer. We isolated CAFs from twenty primary breast cancer samples representing three main subtypes (ER+ (n=7), TNBC (n=7), Her2+ (n=6)) and performed gene expression profile analyses on RNA isolated from these early passage CAFs. Those samples were done in two batches with 4 samples repeated in both batches. One TNBC sample was found to be an outlier and not used in the analysis.

			Action	DRS
	Lipidomics_table_Negative_and_Postive.xlsx	Xlsx
	31-3P.raw	Raw
	38-1P.raw	Raw
	39-1P.raw	Raw
	40-1P.raw	Raw

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Exploring Lipidomic Profiles and Their Correlation with Hormone Receptor and HER2 Status in Breast Cancer

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