Metabolic profiles of triple-negative and luminal A breast cancer subtypes in African-American identify key metabolic differences

Abstract

Breast cancer, a heterogeneous disease with variable pathophysiology and biology, is classified into four major subtypes. While hormonal- and antibody-targeted therapies are effective in the patients with luminal and HER-2 subtypes, the patients with triple-negative breast cancer (TNBC) subtype do not benefit from these therapies. The incidence rates of TNBC subtype are higher in African-American women, and the evidence indicates that these women have worse prognosis compared to women of European descent. The reasons for this disparity remain unclear but are often attributed to TNBC biology. In this study, we performed metabolic analysis of breast tissues to identify how TNBC differs from luminal A breast cancer (LABC) subtypes within the African-American and Caucasian breast cancer patients, respectively. We used High-Resolution Magic Angle Spinning (HR-MAS) 1H Nuclear magnetic resonance (NMR) to perform the metabolomic analysis of breast cancer and adjacent normal tissues (total n=82 samples). TNBC and LABC subtypes in African American women exhibited different metabolic profiles. Metabolic profiles of these subtypes were also distinct from those revealed in Caucasian women. TNBC in African-American women expressed higher levels of glutathione, choline, and glutamine as well as profound metabolic alterations characterized by decreased mitochondrial respiration and increased glycolysis concomitant with decreased levels of ATP. TNBC in Caucasian women was associated with increased pyrimidine synthesis. These metabolic alterations could potentially be exploited as novel treatment targets for TNBC.

Keywords: African American; Caucasian; NMR; breast cancer; triple-negative.

Figure 1. Tissue metabolite profiles derived from breast cancer patients are different from healthy control individuals

ROC curve for (A) PLS-DA model (based on 27 measured metabolites) with 47 breast cancer patients and 35 healthy controls. (B) PLS-DA model (based on 27 metabolites) with postmenopausal women breast cancer tissue and adjacent control tissue with women of >50 years of age. (C) PLS-DA model (based on the 27 metabolites) with premenopausal women breast cancer tissue and adjacent control tissue with women of <50 years of age.

Figure 2

(A) Heatmap constructed based on clustering results from metabolite profiles of breast cancer (red) and normal (blue) samples. Heatmap features the top twenty-seven metabolites as identified by t-test analysis (p≤0.05). Distance measure is Euclidean and clustering is determined using the Ward algorithm. (B) Linear discriminant analysis of breast cancer samples according to race. LD plot generated for African American (black circle) and Caucasian women (red circle) breast cancer tissues. (C) Linear discriminant analysis of breast cancer samples according to hormonal status. LD plot generated for ER- (blue circle) and ER+ (red circle) breast cancer tissues.

Figure 2

(A) Heatmap constructed based on clustering results from metabolite profiles of breast cancer (red) and normal (blue) samples. Heatmap features the top twenty-seven metabolites as identified by t-test analysis (p≤0.05). Distance measure is Euclidean and clustering is determined using the Ward algorithm. (B) Linear discriminant analysis of breast cancer samples according to race. LD plot generated for African American (black circle) and Caucasian women (red circle) breast cancer tissues. (C) Linear discriminant analysis of breast cancer samples according to hormonal status. LD plot generated for ER- (blue circle) and ER+ (red circle) breast cancer tissues.

Figure 2

(A) Heatmap constructed based on clustering results from metabolite profiles of breast cancer (red) and normal (blue) samples. Heatmap features the top twenty-seven metabolites as identified by t-test analysis (p≤0.05). Distance measure is Euclidean and clustering is determined using the Ward algorithm. (B) Linear discriminant analysis of breast cancer samples according to race. LD plot generated for African American (black circle) and Caucasian women (red circle) breast cancer tissues. (C) Linear discriminant analysis of breast cancer samples according to hormonal status. LD plot generated for ER- (blue circle) and ER+ (red circle) breast cancer tissues.

Figure 3

ROC curve for the results of the PLS-DA model from the 27 metabolites from (A) TNBC, ER-negative, samples and (B) LABC, ER-positive, samples.

Figure 4

Box-and-whisker plots of metabolites with p-values < 0.05 illustrating discrimination between tumor tissues from African American and Caucasian (A) LABC and (B) TNBC. A horizontal line in the middle portion of the box represents the mean. Top and bottom boundaries of boxes show the 75th and 25th percentiles, respectively. Upper and lower whiskers show 95th and 5th percentiles, respectively. Open circles show outliers.

Figure 5

ROC curves for the cross-validated predicted class values obtained using the results of PLS-DA model for African American women with (A) TNBC samples and (B) LABC samples.

Figure 6. Box-and-whisker plots of metabolites with p-values < 0.05 illustrating discrimination between TNBC vs. LABC in African Americans

Horizontal line in the middle portion of the box, mean. Top and bottom boundaries of boxes show the 75th and 25th percentiles, respectively. Upper and lower whiskers show 95th and 5th percentiles, respectively. Open circles show outliers.

Figure 7

All matched pathways according to p values from pathway enrichment analysis and pathway impact values obtained from pathway topology analysis for (A) Metabolites that distinguished tumors and normal adjacent tissues for African Americans. A total of 39 pathways were found to be associated with the metabolites, of which 29 pathways were significant (p<0.05). Glycolysis or gluconeogenesis (1); pyruvate metabolism (2); alanine, aspartate and glutamate metabolism (3); glycine, serine and threonine metabolism (4); glutamine and glutamate metabolism (5); taurine and hypotaurine metabolism (6); (B) Metabolites that distinguished tumors and normal adjacent tissues for Caucasians. A total of 39 pathways were found to be associated with the metabolites, of which one pathway, pyrimidine metabolism (1) was significant. (see also Supplementary Table 1)