Secondary Transcriptomic Analysis of Triple-Negative Breast Cancer Reveals Reliable Universal and Subtype-Specific Mechanistic Markers

Abstract

Background/Objectives: Breast cancer is diagnosed in 2.3 million women each year and kills 685,000 (~30% of patients) worldwide. The prognosis for many breast cancer subtypes has improved due to treatments targeting the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). In contrast, patients with triple-negative breast cancer (TNBC) tumors, which lack all three commonly targeted membrane markers, more frequently relapse and have lower survival rates due to a lack of tumor-selective TNBC treatments. We aim to investigate TNBC mechanistic markers that could be targeted for treatment. Methods: We performed a secondary TNBC analysis of 196 samples across 10 publicly available bulk RNA-sequencing studies to better understand the molecular mechanism(s) of disease and predict robust mechanistic markers that could be used to improve the mechanistic understanding of and diagnostic capabilities for TNBC. Results: Our analysis identified ~12,500 significant differentially expressed genes (FDR-adjusted p-value < 0.05), including KIF14 and ELMOD3, and two significantly modulated pathways. Additionally, our novel findings include highly accurate mechanistic markers identified using machine learning methods, including CIDEC (97.1% accuracy alone), CD300LG, ASPM, and RGS1 (98.9% combined accuracy), as well as TNBC subtype-differentiating mechanistic markers, including the targets PDE3B, CFD, IFNG, and ADM, which have associated therapeutics that can potentially be repurposed to improve treatment options. We then experimentally and computationally validated a subset of these findings. Conclusions: The results of our analyses can be used to better understand the mechanism(s) of disease and contribute to the development of improved diagnostics and/or treatments for TNBC.

Keywords: ASPM; CD300LG; CIDEC; RGS1; RNA-sequencing; TNBC; TNMD; drug repurposing; prognosis; transcriptional mechanistic marker.

Figure 1

Expression and functionality of top DEGs and mechanistic markers. (A) Expression of top-ranking genes that differentiate TNBC from healthy samples after z-score normalization by gene. Gene products with higher expression in TNBC are represented in red, while gene products with lower expression in TNBC are represented in blue. (B) Expression of top-ranking genes that differentiate TNBC from healthy samples after z-score normalization by sample. (C) Clusters of STRING-db protein–protein interactions among the top 20 mechanistic markers, including 7 downregulated lipid accessibility controllers and 5 upregulated gene products, 4 of which are mitotic. (D) Protein–protein interactions between 14 of the top 20 DEGs, which are involved in mitosis and were heavily upregulated. (E) Protein–protein interactions between 11 upregulated KIF family proteins and/or BRCA1 and BRCA2. (F) Protein–protein interactions between 9 ACMG cancer-related genes, BRCA1 and BRCA2, and 15 KIF family proteins. * ASPM, RGS1, and KIF14 are included in the list of top DEGs and top mechanistic markers. FO082814.1 expression is not shown.

Figure 2

Principal component analysis chart. (A) Principal component analysis (PCA) chart showing relatedness of samples, colored by disease status (TNBC vs. Healthy). (B) PCA chart with samples colored by study of origin from the Gene Expression Omnibus (GEO). (C) Following TNBC subtype prediction, samples (circles) in PCA chart were color-coded according to their predicted subtype, as listed in the subtype key. Subtypes include basal-like 1 (BL1), basal-like 2 (BL2), ER-like (ERlike), healthy (Healthy), immunomodulatory (IM), luminal androgen receptor (LAR), mesenchymal (M), mesenchymal stem-like (MSL), and unspecified (UNS).

Figure 3

Triple-negative breast cancer shows the dysregulation of KIF14 and TNMD gene products. Immunoblots for KIF14 and TNMD were performed on lysates of primary human breast epithelial cells (PMECs), a triple-negative breast cancer cell line (MDA-MB-231) (TNBC), and a colorectal cancer cell line (CT-26). Student’s t-test was used to compare each group against the control primary cells. Asterisks denote the level of significance observed as follows: *, p  ≤  0.05; “ns” indicates not significant. Please see Supplementary File S10 for the uncropped Western blots and densitometry information.