Abstract P6-06-21: A 5-gene predictor of triple negative breast cancer outcome that also correlates with immune checkpoint receptor expression

AbstractBreast cancer remains the second most lethal cancer among women in the United States and triple-negative breast cancer is the most aggressive subtype with limited treatment options. Trop2, a cell membrane glycoprotein, is overexpressed in almost all epithelial cancers. In this study, we demonstrate that Trop2 is overexpressed in triple-negative breast cancer (TNBC), and downregulation of Trop2 delays TNBC cell and tumor growth supporting the oncogenic role of Trop2 in breast cancer. Through proteomic profiling, we discovered a metabolic signature comprised of TALDO1, GPI, LDHA, SHMT2, and ADK proteins that were downregulated in Trop2-depleted breast cancer tumors. The identified oncogene-mediated metabolic gene signature is significantly upregulated in TNBC patients across multiple RNA-expression clinical datasets. Our study further reveals that the metabolic gene signature reliably predicts poor survival of breast cancer patients with early stages of the disease. Taken together, our study identified a new five-gene metabolic signature as an accurate predictor of breast cancer outcome.

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Androgen receptor expression in triple-negative breast cancer

10.26226/morressier.596cd2b6d462b80292387085 ◽

2017 ◽

Author(s):

Ievgen Glavynskyi

Keyword(s):

Breast Cancer ◽

Androgen Receptor ◽

Triple Negative Breast Cancer ◽

Triple Negative ◽

Receptor Expression ◽

Androgen Receptor Expression

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Essential amino acid metabolism-related molecular classification in triple-negative breast cancer

Epigenomics ◽

10.2217/epi-2021-0210 ◽

2021 ◽

Vol 13 (16) ◽

pp. 1247-1268

Author(s):

Yajie Zhao ◽

Chunrui Pu ◽

Dechuang Jiao ◽

Jiujun Zhu ◽

Xuhui Guo ◽

...

Keyword(s):

Breast Cancer ◽

Amino Acid ◽

Triple Negative Breast Cancer ◽

Immune Checkpoint ◽

Essential Amino Acid ◽

Triple Negative ◽

Expression Patterns ◽

Molecular Classification ◽

Biological Insight ◽

Metabolic Heterogeneity

Aim: To develop an approach to characterize and classify triple-negative breast cancer (TNBC) tumors based upon their essential amino acid (EAA) metabolic activity. Methods: We performed bioinformatic analyses of genomic, transcriptomic and clinical data in an integrated cohort of 740 TNBC patients from public databases. Results: Based on EAA metabolism-related gene expression patterns, two TNBC subtypes were identified with distinct prognoses and genomic alterations. Patients exhibiting an upregulated EAA metabolism phenotype were more prone to chemoresistance but also expressed higher levels of immune checkpoint genes and may be better candidates for immune checkpoint inhibitor therapy. Conclusion: Metabolic classification based upon EAA profiles offers a novel biological insight into previously established TNBC subtypes and advances current understanding of TNBC’s metabolic heterogeneity.

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