Concepts and targets in triple-negative breast cancer: recent results and clinical implications

Saha, Poornima; Nanda, Rachita

doi:10.1177/1758834016657071

Cited by 24 publications

(22 citation statements)

References 48 publications

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“…[10][11][12][13][14] According to clinical studies, response rates to anti-PD-1/PD-L1 therapy range between 5 to 23% within advanced TN breast cancer patients. 15 Higher response rates are linked with PD-L1 positivity. 15 However, not all PD-L1-positive (PD-L1+) tumors respond to anti-PD-1/PD-L1 therapy.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of PD-L1 expression across breast cancer molecular subtypes, in relation to mutation rate, BRCA1-like status, tumor-infiltrating immune cells and survival

et al. 2018

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To better understand the expression pattern of programmed death-ligand 1 (PD-L1) expression in different breast cancer types, we characterized PD-L1 expression in tumor and tumor-infiltrating immune cells, in relation to mutation rate, BRCA1-like status and survival. We analyzed 410 primary treatment-naive breast tumors comprising 162 estrogen receptor-positive (ER+) and HER2−, 101 HER2+ and 147 triple-negative (TN) cancers. Pathologists quantified tumor-infiltrating lymphocytes (TILs) and PD-L1 expression in tumor cells and TILs using whole slides and tissue microarray. Mutation rate was assessed by DNA sequencing, BRCA1-like status using multiplex ligation-dependent probe amplification, and immune landscape by multiplex image analyses of CD4, CD68, CD8, FOXP3, cytokeratin, and PD-L1. Half of PD-L1 scores evaluated by tissue microarray were false negatives compared to whole slide evaluations. We observed at least 1% of PD-L1-positive (PD-L1+) cells in 53.1% of ER+HER2−, 73.3% of HER2+, and 84.4% of TN tumors. PD-L1 expression was higher in ductal compared to lobular carcinomas, also within ER+HER2− tumors (p = 0.04). High PD-L1+ TILs score (> 50%) was independently associated with better outcome in TN tumors (HR = 0.27; 95%CI = 0.10-0.69). Within TN tumors, PD-L1 and TIL scores showed a modest but significant positive association with the number of silent mutations, but no association with BRCA1-like status. Multiplex image analyses indicated that PD-L1 is expressed on multiple immune cells (CD68+ macrophages, CD4+, FOXP3+, and CD8+ T cells) in the breast tumor microenvironment, independent of the PD-L1 status of the tumor cells. We found no evidence that levels of PD-L1 + TILs in TN breast cancer are driven by high mutation rate or BRCA1-like status.

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Section: Introductionmentioning

confidence: 99%

“…15 Higher response rates are linked with PD-L1 positivity. 15 However, not all PD-L1-positive (PD-L1+) tumors respond to anti-PD-1/PD-L1 therapy.…”

Section: Introductionmentioning

confidence: 99%

Assessment of PD-L1 expression across breast cancer molecular subtypes, in relation to mutation rate, BRCA1-like status, tumor-infiltrating immune cells and survival

et al. 2018

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“…8E). The expression of IL-1α was very low in MCF-7 6 cells when compared to SUM159 and thus these experiments were not performed in the former cell line. These results indicated that IL-1α is a direct transcriptional target of FoxQ1 at least in the SUM159 cell line.…”

Section: Il-1α Il-8 and Vegf Are Novel Downstream Transcriptional Tmentioning

confidence: 99%

“…Majority of the invasive mammary ductal carcinomas are broadly grouped into four subtypes, including luminal A type [estrogen receptor positive (ER+ 3 ), progesterone receptor positive (PR+), and human epidermal growth factor receptor 2 positive (HER2+)], luminal B type (ER+/PR+/HER2-), HER2enriched, and basal-like (2,3). Nearly 75% of basal-like breast tumors are triplenegative due to lack of ER, PR, and HER2 expression (6). Further characterization of the disease subtype-independent oncogenic dependencies in breast cancer is necessary to identify novel druggable targets to broaden therapeutic options for different subtypes of breast cancer.…”

Section: Introductionmentioning

confidence: 99%

Novel mechanistic targets of Forkhead box Q1 transcription factor in human breast cancer cells

Kim

Hahm

Singh

et al. 2020

Preprint

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The transcription factor forkhead box Q1 (FoxQ1), which is overexpressed in different solid tumors, has emerged as a key player in the pathogenesis of breast cancer by regulating epithelialmesenchymal transition, maintenance of cancer-stem like cells, and metastasis. However, the mechanism underlying oncogenic function of FoxQ1 is still not fully understood. In this study, we compared the RNA-seq data from FoxQ1 overexpressing SUM159 cells with that of empty vector-transfected control (EV) cells to identify novel mechanistic targets of this transcription factor. Consistent with published results in basal-like subtype, immunohistochemistry revealed upregulation of FoxQ1 protein in luminal-type human breast cancer tissue microarrays when compared to normal mammary tissues. Many previously reported transcriptional targets of FoxQ1 (e.g., E-cadherin, N-cadherin, fibronectin 1, etc.) were verified from the RNA-Seq analysis. FoxQ1 overexpression resulted in downregulation of genes associated with cell cycle checkpoints, M phase, and cellular response to stress/external stimuli as evidenced from the Reactome pathway analysis.Consequently, FoxQ1 overexpression resulted in S, G2M and mitotic arrest in basal-like SUM159 and HMLE cells, but not in luminal-type MCF-7 cells. There were differences in expression of cell cycle-associated proteins between FoxQ1 overexpressing SUM159 and MCF-7 cells. Finally, we show for the first time that FoxQ1 is a direct transcriptional regulator of interleukin (IL)-1α, IL-8, and vascular endothelial growth factor in breast cancer cells. Chromatin immunoprecipitation revealed FoxQ1 occupancy at the promoters of IL-1α, IL-8, and VEGF. In conclusion, the present study reports novel mechanistic targets of FoxQ1 in human breast cancer cells.

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“…Well studied therapeutic targets for TNBC include those proteins in proliferative and survival-dependent pathways, such as epidermal growth factor receptor (EGFR) [16,17], vascular endothelial growth factor receptor (VEGFR) [18], JAK2/STAT3 [19] and PI3K [20,21,22,23], and those control the cell cycle and the DNA damage responses such as Poly-ADP Ribose Polymerase (PARPs) [24,25]. However, the initial results of candidate compounds targeting these proteins from clinical trials [3,26,27,28,29,30] remain modest, highlighting the importance of systematic target discovering, assessing and prioritizing for biological validation and therapeutic exploitation.…”

Section: Introductionmentioning

confidence: 99%

Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes

Liu

Yin

Zhong

et al. 2017

Genes

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With accumulating public omics data, great efforts have been made to characterize the genetic heterogeneity of breast cancer. However, identifying novel targets and selecting the best from the sizeable lists of candidate targets is still a key challenge for targeted therapy, largely owing to the lack of economical, efficient and systematic discovery and assessment to prioritize potential therapeutic targets. Here, we describe an approach that combines the computational evaluation and objective, multifaceted assessment to systematically identify and prioritize targets for biological validation and therapeutic exploration. We first establish the reference gene expression profiles from breast cancer cell line MCF7 upon genome-wide RNA interference (RNAi) of a total of 3689 genes, and the breast cancer query signatures using RNA-seq data generated from tissue samples of clinical breast cancer patients in the Cancer Genome Atlas (TCGA). Based on gene set enrichment analysis, we identified a set of 510 genes that when knocked down could significantly reverse the transcriptome of breast cancer state. We then perform multifaceted assessment to analyze the gene set to prioritize potential targets for gene therapy. We also propose drug repurposing opportunities and identify potentially druggable proteins that have been poorly explored with regard to the discovery of small-molecule modulators. Finally, we obtained a small list of candidate therapeutic targets for four major breast cancer subtypes, i.e., luminal A, luminal B, HER2+ and triple negative breast cancer. This RNAi transcriptome-based approach can be a helpful paradigm for relevant researches to identify and prioritize candidate targets for experimental validation.

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Concepts and targets in triple-negative breast cancer: recent results and clinical implications

Cited by 24 publications

References 48 publications

Assessment of PD-L1 expression across breast cancer molecular subtypes, in relation to mutation rate, BRCA1-like status, tumor-infiltrating immune cells and survival

Assessment of PD-L1 expression across breast cancer molecular subtypes, in relation to mutation rate, BRCA1-like status, tumor-infiltrating immune cells and survival

Novel mechanistic targets of Forkhead box Q1 transcription factor in human breast cancer cells

Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes

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