ALDH1A3 promotes invasion and metastasis in triple-negative breast cancer by regulating the plasminogen activation pathway

Aldehyde dehydrogenase 1A3 (ALDH1A3) is a cancer stem cell marker that promotes metastasis. Triple-negative breast cancer (TNBC) progression has been linked to ALDH1A3-induced gene expression changes. To investigate the mechanism of ALDH1A3-mediated breast cancer metastasis, we assessed the effect of ALDH1A3 on the expression of proteases and the regulators of proteases that degrade the extracellular matrix, a process that is essential for invasion and metastasis. This revealed that ALDH1A3 regulates the plasminogen activation pathway; it increased the levels and activity of tissue plasminogen activator (tPA) and urokinase plasminogen activator (uPA). This resulted in a corresponding increase in the activity of serine protease plasmin, the enzymatic product of tPA and uPA. The ALDH1A3 product all-trans-retinoic acid similarly increased tPA and plasmin activity. The increased invasion of TNBC cells by ALDH1A3 was plasminogen-dependent. In patient tumours, ALDH1A3 and tPA are co-expressed and their combined expression correlated with the TNBC subtype, high tumour grade and recurrent metastatic disease. Knockdown of tPA in TNBC cells inhibited plasmin generation and lymph node metastasis. These results identify the ALDH1A3-tPA-plasmin axis as a key contributor to breast cancer progression.

The Prostaglandin E2 Pathway and Breast Cancer Stem Cells: Evidence of Increased Signaling and Potential Targeting

Culprits of cancer development, metastasis, and drug resistance, cancer stem cells (CSCs) are characterized by specific markers, active developmental signaling pathways, metabolic plasticity, increased motility, invasiveness, and epithelial-mesenchymal transition. In breast cancer, these cells are often more prominent in aggressive disease, are amplified in drug-resistant tumors, and contribute to recurrence. For breast cancer, two distinct CSC populations exist and are typically defined by CD44+/CD24- cell surface marker expression or increased aldehyde dehydrogenase (ALDH) activity. These CSC populations share many of the same properties but also exhibit signaling pathways that are more active in CD44+/CD24- or ALDH+ populations. Understanding these CSC populations and their shared or specific signaling pathways may lead to the development of novel therapeutic strategies that will improve breast cancer patient outcomes. Herein, we review the current evidence and assess published patient tumor datasets of sorted breast CSC populations for evidence of heightened prostaglandin E2 (PGE₂) signaling and activity in these breast CSC populations. PGE₂ is a biologically active lipid mediator and in cancer PGE₂ promotes tumor progression and poor patient prognosis. Overall, the data suggests that PGE₂ signaling is important in propagating breast CSCs by enhancing inherent tumor-initiating capacities. Development of anti-PGE₂ signaling therapeutics may be beneficial in inhibiting tumor growth and limiting breast CSC populations.

Metabolite profiling reveals a connection between aldehyde dehydrogenase 1A3 and GABA metabolism in breast cancer metastasis

INTRODUCTION

Aldehyde dehydrogenase 1A3 (ALDH1A3) is a cancer stem cell (CSC) marker and in breast cancer it is associated with triple-negative/basal-like subtypes and aggressive disease. Studies on the mechanisms of ALDH1A3 in cancer have primarily focused on gene expression changes induced by the enzyme; however, its effects on metabolism have thus far been unstudied and may reveal novel mechanisms of pathogenesis.

OBJECTIVE

Determine how ALDH1A3 alters the metabolite profile in breast cancer cells and assess potential impacts.

METHOD

Triple-negative MDA-MB-231 tumors and cells with manipulated ALDH1A3 levels were assessed by HPLC-MS metabolomics and metabolite data was integrated with transcriptome data. Mice harboring MDA-MB-231 tumors with or without altered ALDH1A3 expression were treated with γ-aminobutyric acid (GABA) or placebo. Effects on tumor growth, and lungs and brain metastasis were quantified by staining of fixed thin sections and quantitative PCR. Breast cancer patient datasets from TCGA, METABRIC and GEO were used to assess the co-expression of GABA pathway genes with ALDH1A3.

RESULTS

Integrated metabolomic and transcriptome data identified GABA metabolism as a primary dysregulated pathway in ALDH1A3 expressing breast tumors. Both ALDH1A3 and GABA treatment enhanced metastasis. Patient dataset analyses revealed expression association between ALDH1A3 and GABA pathway genes and corresponding increased risk of metastasis.

CONCLUSION

This study revealed a novel pathway affected by ALDH1A3, GABA metabolism. Like ALDH1A3 expression, GABA treatment promotes metastasis. Given the clinical use of GABA mimics to relieve chemotherapy-induced peripheral nerve pain, further study of the effects of GABA in breast cancer progression is warranted.

LncRNA PART1 Promotes Proliferation and Migration, Is Associated with Cancer Stem Cells, and Alters the miRNA Landscape in Triple-Negative Breast Cancer

Triple-negative breast cancers (TNBCs) are aggressive, lack targeted therapies and are enriched in cancer stem cells (CSCs). Novel therapies which target CSCs within these tumors would likely lead to improved outcomes for TNBC patients. Long non-coding RNAs (lncRNAs) are potential therapeutic targets for TNBC and CSCs. We demonstrate that lncRNA prostate androgen regulated transcript 1 (PART1) is enriched in TNBCs and in Aldefluor^high CSCs, and is associated with worse outcomes among basal-like breast cancer patients. Although PART1 is androgen inducible in breast cancer cells, analysis of patient tumors indicates its androgen regulation has minimal clinical impact. Knockdown of PART1 in TNBC cell lines and a patient-derived xenograft decreased cell proliferation, migration, tumor growth, and mammosphere formation potential. Transcriptome analyses revealed that the lncRNA affects expression of hundreds of genes (e.g., myosin-Va, MYO5A; zinc fingers and homeoboxes protein 2, ZHX2). MiRNA 4.0 GeneChip and TaqMan assays identified multiple miRNAs that are regulated by cytoplasmic PART1, including miR-190a-3p, miR-937-5p, miR-22-5p, miR-30b-3p, and miR-6870-5p. We confirmed the novel interaction between PART1 and miR-937-5p. In general, miRNAs altered by PART1 were less abundant than PART1, potentially leading to cell line-specific effects in terms miRNA-PART1 interactions and gene regulation. Together, the altered miRNA landscape induced by PART1 explains most of the protein-coding gene regulation changes (e.g., MYO5A) induced by PART1 in TNBC.

An in vivo genome-wide shRNA screen identifies BCL6 as a targetable biomarker of paclitaxel resistance in breast cancer

Paclitaxel is a common breast cancer drug; however, some tumors are resistant. The identification of biomarkers for paclitaxel resistance or sensitivity would enable the development of strategies to improve treatment efficacy. A genome-wide in vivo shRNA screen was performed on paclitaxel-treated mice with MDA-MB-231 tumors to identify genes associated with paclitaxel sensitivity or resistance. Gene expression of the top screen hits was associated with tumor response (resistance or sensitivity) among patients who received neoadjuvant chemotherapy containing paclitaxel. We focused our validation on screen hit B-cell lymphoma 6 (BCL6), which is a therapeutic target in cancer but for which no effects on drug response have been reported. Knockdown of BCL6 resulted in increased tumor regression in mice treated with paclitaxel. Similarly, inhibiting BCL6 using a small molecule inhibitor enhanced paclitaxel treatment efficacy both in vitro and in vivo in breast cancer models. Mechanism studies revealed that reduced BCL6 enhances the efficacy of paclitaxel by inducing sustained G1/S arrest, concurrent with increased apoptosis and expression of target gene cyclin-dependent kinase inhibitor 1A. In summary, the genome-wide shRNA knockdown screen has identified BCL6 as a potential targetable resistance biomarker of paclitaxel response in breast cancer.

In Vivo Genome-Wide Pooled RNAi Screens in Cancer Cells to Identify Determinants of Chemotherapy/Drug Response

Large-scale RNAi screens (i.e., genome-wide arrays and pools) can reveal the essential biological functions of previously uncharacterized genes. Due to the nature of the selection process involved in screens, RNAi screens are also very useful for identifying genes involved in drug responses. The information gained from these screens could be used to predict a cancer patient's response to a specific drug (i.e., precision medicine) or identify anti-cancer drug resistance genes, which could be targeted to improve treatment outcomes. In this capacity, screens have been most often performed in vitro. However, there is limitation to performing these screens in vitro: genes which are required in only an in vivo setting (e.g., rely on the tumor microenvironment for function) will not be identified. As such, it can be desirable to perform RNAi screens in vivo. Here we outline the additional technical details that should be considered for performing genome-wide RNAi drug screens of cancer cells under in vivo conditions (i.e., tumor xenografts).

Human-specific GAPDH qRT-PCR is an accurate and sensitive method of xenograft metastasis quantification

Metastasis is the primary cause of cancer-related mortality. Experimental models that accurately reflect changes in metastatic burden are essential tools for developing treatments and to gain a better understanding of disease. Murine xenograft tumor models mimic the human scenario and provide a platform for metastasis analyses. An ex vivo quantitative method, gaining favor for its ease and accuracy, is quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR); however, it is currently unclear how well this method correlates with gold-standard histological analysis, and its use has required detection of overexpressed exogenous genes. We have introduced a variation of the qRT-PCR method: human-specific glyceraldehyde 3-phosphate dehydrogenase (GAPDH) qRT-PCR, which allows quantification of metastasis in xenograft models without the requirement of overexpressed exogenous genes. This makes the method easily amenable to many xenograft models without alteration of the cancer cells. We determined that the method is able to detect a few human cells within abundant mouse lung tissue. Further, the human-specific GAPDH qRT-PCR is more sensitive and correlates with histological analysis in terms of determining relative metastatic burden, suggesting that human-specific GAPDH qRT-PCR could be used as a primary method for quantification of disseminated human cells in murine xenograft models.

S100A10 Has a Critical Regulatory Function in Mammary Tumor Growth and Metastasis: Insights Using MMTV-PyMT Oncomice and Clinical Patient Sample Analysis

Simple Summary

The key challenges that face patients during breast cancer therapy is the metastatic spread and aggressiveness of the disease. Thus, the goal of current breast cancer research is to discover new therapeutic and diagnostic targets that limit the aggressive spread of the cancer. In this study, we investigated the role of protein S100A10 (p11) in breast tumor growth, progression, and metastasis using mouse cancer models and patient tumor sample analysis. We have demonstrated in our previous studies that p11 is critical for the function of a proteolytic enzyme–plasmin, which aids in the digestion of the tissues surrounding the tumor and allows the escape of the cancer cells from the breast tissue to organs such as the lungs and bone. Here, we present evidence that genetic deletion of p11 results in smaller and less aggressive mammary tumors in mice. We also observed that the cancer spread to the lungs is dramatically reduced in the absence of p11 gene in mice. Subsequent analysis of breast cancer patient tissues showed a correlation between higher p11 expression and both poor survival and aggressive cancer.

Abstract

S100A10 (p11) is a plasminogen receptor that regulates cellular plasmin generation by cancer cells. In the current study, we used the MMTV-PyMT mouse breast cancer model, patient tumor microarray, and immunohistochemical (IHC) analysis to investigate the role of p11 in oncogenesis. The genetic deletion of p11 resulted in significantly decreased tumor onset, growth rate, and spontaneous pulmonary metastatic burden in the PyMT/p11-KO (knock-out) mice. This phenotype was accompanied by substantial reduction in Ki67 positivity, macrophage infiltration, decreased vascular density in the primary tumors, and decrease in invasive carcinoma and pulmonary metastasis. Surprisingly, IHC analysis of wild-type MMTV-PyMT mice failed to detect p11 expression in the tumors or metastatic tumor cells and loss of p11 did not decrease plasmin generation in the PyMT tumors and cells. Furthermore, tumor cells expressing p11 displayed dramatically reduced lung metastasis when injected into p11-depleted mice, further strengthening the stromal role of p11 in tumor growth and metastasis. Transcriptome analysis of the PyMT tumors from p11-KO mice showed marked reduction in genes such as Areg, Muc1, and S100a8 involved in breast cancer development, progression, and inflammation. The PyMT/p11-KO tumors displayed a remarkable increase in inflammatory cytokines such as interleukin (Il)-6, Il-10, and interferon (Ifn)-γ. Gene expression profiling and IHC of primary breast cancer samples showed that p11 mRNA and protein levels were significantly higher in tumor tissues compared to normal mammary tissue. P11 mRNA expression was significantly associated with poor patient prognosis and significantly elevated in high grade, triple negative (TN) tumors, and tumors with high proliferative index. This is the first study examining the crucial role of p11 in breast tumor development and metastasis, thus emphasizing its potential as a diagnostic and prognostic biomarker in breast cancer.

Decitabine Response in Breast Cancer Requires Efficient Drug Processing and Is Not Limited by Multidrug Resistance

Dysregulation of DNA methylation is an established feature of breast cancers. DNA demethylating therapies like decitabine are proposed for the treatment of triple-negative breast cancers (TNBC) and indicators of response need to be identified. For this purpose, we characterized the effects of decitabine in a panel of 10 breast cancer cell lines and observed a range of sensitivity to decitabine that was not subtype specific. Knockdown of potential key effectors demonstrated the requirement of deoxycytidine kinase (DCK) for decitabine response in breast cancer cells. In treatment-naïve breast tumors, DCK was higher in TNBCs, and DCK levels were sustained or increased post chemotherapy treatment. This suggests that limited DCK levels will not be a barrier to response in patients with TNBC treated with decitabine as a second-line treatment or in a clinical trial. Methylome analysis revealed that genome-wide, region-specific, tumor suppressor gene-specific methylation, and decitabine-induced demethylation did not predict response to decitabine. Gene set enrichment analysis of transcriptome data demonstrated that decitabine induced genes within apoptosis, cell cycle, stress, and immune pathways. Induced genes included those characterized by the viral mimicry response; however, knockdown of key effectors of the pathway did not affect decitabine sensitivity suggesting that breast cancer growth suppression by decitabine is independent of viral mimicry. Finally, taxol-resistant breast cancer cells expressing high levels of multidrug resistance transporter ABCB1 remained sensitive to decitabine, suggesting that the drug could be used as second-line treatment for chemoresistant patients.