Sterile inflammation via TRPM8 RNA-dependent TLR3-NF-kB/IRF3 activation promotes antitumor immunity in prostate cancer.

Inflammation is a common condition of prostate tissue, whose impact on carcinogenesis is highly debated. Microbial colonization is a well-documented cause of a small percentage of prostatitis cases, but it remains unclear what underlies the majority of sterile inflammation reported. Here, androgen- independent fluctuations of PSA expression in prostate cells have lead us to identify a prominent function of the Transient Receptor Potential Cation Channel Subfamily M Member 8 (TRPM8) gene in sterile inflammation. Prostate cells secret TRPM8 RNA into extracellular vesicles (EVs), which primes TLR3/NF-kB-mediated inflammatory signaling after EV endocytosis by epithelial cancer cells. Furthermore, prostate cancer xenografts expressing a translation-defective form of TRPM8 RNA contain less collagen type I in the extracellular matrix, significantly more infiltrating NK cells, and larger necrotic areas as compared to control xenografts. These findings imply sustained, androgen-independent expression of TRPM8 constitutes as a promoter of anticancer innate immunity, which may constitute a clinically relevant condition affecting prostate cancer prognosis.

Functional annotation of human long noncoding RNAs via molecular phenotyping.

Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-to-date lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.

ABEMUS: platform-specific and data-informed detection of somatic SNVs in cfDNA.

MOTIVATION: The use of liquid biopsies for cancer patients enables the non-invasive tracking of treatment response and tumor dynamics through single or serial blood drawn tests. Next-generation sequencing assays allow for the simultaneous interrogation of extended sets of somatic single-nucleotide variants (SNVs) in circulating cell-free DNA (cfDNA), a mixture of DNA molecules originating both from normal and tumor tissue cells. However, low circulating tumor DNA (ctDNA) fractions together with sequencing background noise and potential tumor heterogeneity challenge the ability to confidently call SNVs. RESULTS: We present a computational methodology, called Adaptive Base Error Model in Ultra-deep Sequencing data (ABEMUS), which combines platform-specific genetic knowledge and empirical signal to readily detect and quantify somatic SNVs in cfDNA. We tested the capability of our method to analyze data generated using different platforms with distinct sequencing error properties and we compared ABEMUS performances with other popular SNV callers on both synthetic and real cancer patients sequencing data. Results show that ABEMUS performs better in most of the tested conditions proving its reliability in calling low variant allele frequencies somatic SNVs in low ctDNA levels plasma samples. AVAILABILITY AND IMPLEMENTATION: ABEMUS is cross-platform and can be installed as R package. The source code is maintained on Github at http://github.com/cibiobcg/abemus, and it is also available at CRAN official R repository. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Translating Proteomic Into Functional Data: An High Mobility Group A1 (HMGA1) Proteomic Signature Has Prognostic Value in Breast Cancer.

Cancer is a very heterogeneous disease, and biological variability adds a further level of complexity, thus limiting the ability to identify new genes involved in cancer development. Oncogenes whose expression levels control cell aggressiveness are very useful for developing cellular models that permit differential expression screenings in isogenic contexts. HMGA1 protein has this unique property because it is a master regulator in breast cancer cells that control the transition from a nontumorigenic epithelial-like phenotype toward a highly aggressive mesenchymal-like one. The proteins extracted from HMGA1-silenced and control MDA-MB-231 cells were analyzed using label-free shotgun mass spectrometry. The differentially expressed proteins were cross-referenced with DNA microarray data obtained using the same cellular model and the overlapping genes were filtered for factors linked to poor prognosis in breast cancer gene expression meta-data sets, resulting in an HMGA1 protein signature composed of 21 members (HRS, HMGA1 reduced signature). This signature had a prognostic value (overall survival, relapse-free survival, and distant metastasis-free survival) in breast cancer. qRT-PCR, Western blot, and immunohistochemistry analyses validated the link of three members of this signature (KIFC1, LRRC59, and TRIP13) with HMGA1 expression levels both in vitro and in vivo and wound healing assays demonstrated that these three proteins are involved in modulating tumor cell motility. Combining proteomic and genomic data with the aid of bioinformatic tools, our results highlight the potential involvement in neoplastic transformation of a restricted list of factors with an as-yet-unexplored role in cancer. These factors are druggable targets that could be exploited for the development of new, targeted therapeutic approaches in triple-negative breast cancer.

Specific mesothelial signature marks the heterogeneity of mesenchymal stem cells from high-grade serous ovarian cancer.

Mesenchymal stem/stromal cells (MSCs) are the precursors of various cell types that compose both normal and cancer tissue microenvironments. In order to support the widely diversified parenchymal cells and tissue organization, MSCs are characterized by a large degree of heterogeneity, although available analyses of molecular and transcriptional data do not provide clear evidence. We have isolated MSCs from high-grade serous ovarian cancers (HG-SOCs) and various normal tissues (N-MSCs), demonstrated their normal genotype and analyzed their transcriptional activity with respect to the large comprehensive FANTOM5 sample dataset. Our integrative analysis conducted against the extensive panel of primary cells and tissues of the FANTOM5 project allowed us to mark the HG-SOC-MSCs CAGE-seq transcriptional heterogeneity and to identify a cell-type-specific transcriptional activity showing a significant relationship with primary mesothelial cells. Our analysis shows that MSCs isolated from different tissues are highly heterogeneous. The mesothelial-related gene signature identified in this study supports the hypothesis that HG-SOC-MSCs are bona fide representatives of the ovarian district. This finding indicates that HG-SOC-MSCs could actually derive from the coelomic mesothelium, suggesting that they might be linked to the epithelial tumor through common embryological precursors.

Casting a wider net: The clinical potential of EV transcriptomics in multi-analyte liquid biopsy.

Cancer cells release cell-free DNA (cfDNA) and extracellular vesicles (EVs) into the bloodstream, allowing disease non-invasive monitoring. In this issue of Cancer Cell, Casanova-Salas et al. analyze cfDNA, EV-DNA, and EV-RNA in prostate cancer longitudinal cohorts treated with androgen receptor signaling inhibitors and taxanes, identifying signals reflecting tumor adaptation processes.

Extracellular Vesicles heterogeneity through the lens of multiomics.

Extracellular vesicles (EVs) are heterogenous in size, biogenesis, cargo and function. Beside small EVs, aggressive tumor cells release a population of particularly large EVs, namely large oncosomes (LO). This study provides the first resource of label-free quantitative proteomics of LO and small EVs obtained from distinct cancer cell types (prostate, breast, and glioma). This dataset was integrated with a SWATH Proteomic assay on LO, rigorously isolated from the plasma of patients with metastatic prostate cancer (PC). Proteins enriched in LO, which were identified also at the RNA level, and found in plasma LO significantly correlated with PC progression. Single EV RNA-Seq of the PC cell-derived LO confirmed some of the main findings from the bulk RNA-Seq, providing first evidence that single cell technologies can be successfully applied to EVs. This multiomics resource of cancer EVs can be leveraged for developing a multi-analyte approach for liquid biopsy.

Noninvasive Detection of Neuroendocrine Prostate Cancer through Targeted Cell-free DNA Methylation.

Castration-resistant prostate cancer (CRPC) is a heterogeneous disease associated with phenotypic subtypes that drive therapy response and outcome differences. Histologic transformation to castration-resistant neuroendocrine prostate cancer (CRPC-NE) is associated with distinct epigenetic alterations, including changes in DNA methylation. The current diagnosis of CRPC-NE is challenging and relies on metastatic biopsy. We developed a targeted DNA methylation assay to detect CRPC-NE using plasma cell-free DNA (cfDNA). The assay quantifies tumor content and provides a phenotype evidence score that captures diverse CRPC phenotypes, leveraging regions to inform transcriptional state. We tested the design in independent clinical cohorts (n = 222 plasma samples) and qualified it achieving an AUC > 0.93 for detecting pathology-confirmed CRPC-NE (n = 136). Methylation-defined cfDNA tumor content was associated with clinical outcomes in two prospective phase II clinical trials geared towards aggressive variant CRPC and CRPC-NE. These data support the application of targeted DNA methylation for CRPC-NE detection and patient stratification. SIGNIFICANCE: Neuroendocrine prostate cancer is an aggressive subtype of treatment-resistant prostate cancer. Early detection is important, but the diagnosis currently relies on metastatic biopsy. We describe the development and validation of a plasma cell-free DNA targeted methylation panel that can quantify tumor fraction and identify patients with neuroendocrine prostate cancer noninvasively. This article is featured in Selected Articles from This Issue, p. 384.

International Society for Extracellular Vesicles Workshop. QuantitatEVs: multiscale analyses, from bulk to single extracellular vesicle.

The 'QuantitatEVs: multiscale analyses, from bulk to single vesicle' workshop aimed to discuss quantitative strategies and harmonized wet and computational approaches toward the comprehensive analysis of extracellular vesicles (EVs) from bulk to single vesicle analyses with a special focus on emerging technologies. The workshop covered the key issues in the quantitative analysis of different EV-associated molecular components and EV biophysical features, which are considered the core of EV-associated biomarker discovery and validation for their clinical translation. The in-person-only workshop was held in Trento, Italy, from January 31st to February 2nd, 2023, and continued in Milan on February 3rd with "Next Generation EVs", a satellite event dedicated to early career researchers (ECR). This report summarizes the main topics and outcomes of the workshop.

Integrating extracellular vesicle and circulating cell-free DNA analysis using a single plasma aliquot improves the detection of HER2 positivity in breast cancer patients.

Multi-analyte liquid biopsies represent an emerging opportunity for non-invasive cancer assessment. We developed ONCE (ONe Aliquot for Circulating Elements), an approach for the isolation of extracellular vesicles (EV) and cell-free DNA (cfDNA) from a single aliquot of blood. We assessed ONCE performance to classify HER2-positive early-stage breast cancer (BrCa) patients by combining EV-associated RNA (EV-RNA) and cfDNA signals on n=64 healthy donors (HD) and non-metastatic BrCa patients. Specifically, we isolated EV-enriched samples by a charge-based (CB) method and investigated EV-RNA and cfDNA by next-generation sequencing (NGS) and by digital droplet PCR (ddPCR). Sequencing of cfDNA and EV-RNA from HER2- and HER2+ patients demonstrated concordance with in situ molecular analyses of matched tissues. Combined analysis of the two circulating analytes by ddPCR showed increased sensitivity in ERBB2/HER2 detection compared to single nucleic acid components. Multi-analyte liquid biopsy prediction performance was comparable to tissue-based sequencing results from TCGA. Also, imaging flow cytometry analysis revealed HER2 protein on the surface of EV isolated from the HER2+ BrCa plasma, thus corroborating the potential relevance of studying EV as companion analyte to cfDNA. This data confirms the relevance of combining cfDNA and EV-RNA for HER2 cancer assessment and supports the ONCE as a valuable tool for multi-analytes liquid biopsies' clinical implementation.

Circulating RNAs in prostate cancer patients.

Growing bodies of evidence have demonstrated that the identification of prostate cancer (PCa) biomarkers in the patients' blood and urine may remarkably improve PCa diagnosis and progression monitoring. Among diverse cancer-derived circulating materials, extracellular RNA molecules (exRNAs) represent a compelling component to investigate cancer-related alterations. Once outside the intracellular environment, exRNAs circulate in biofluids either in association with protein complexes or encapsulated inside extracellular vesicles (EVs). Notably, EV-associated RNAs (EV-RNAs) were used for the development of several assays (such as the FDA-approved Progensa Prostate Cancer Antigen 3 (PCA3 test) aiming at improving early PCa detection. EV-RNAs encompass a mixture of species, including small non-coding RNAs (e.g. miRNA and circRNA), lncRNAs and mRNAs. Several methods have been proposed to isolate EVs and relevant RNAs, and to perform RNA-Seq studies to identify potential cancer biomarkers. However, EVs in the circulation of a cancer patient include a multitude of diverse populations that are released by both cancer and normal cells from different tissues, thereby leading to a heterogeneous EV-RNA-associated transcriptional signal. Decrypting the complexity of such a composite signal is nowadays the major challenge faced in the identification of specific tumor-associated RNAs. Multiple deconvolution algorithms have been proposed so far to infer the enrichment of cancer-specific signals from gene expression data. However, novel strategies for EVs sorting and sequencing of RNA associated to single EVs populations will remarkably facilitate the identification of cancer-related molecules. Altogether, the studies summarized here demonstrate the high potential of using EV-RNA biomarkers in PCa and highlight the urgent need of improving technologies and computational approaches to characterize specific EVs populations and their relevant RNA cargo.

Allele-specific genomic data elucidate the role of somatic gain and copy-number neutral loss of heterozygosity in cancer.

Pan-cancer studies sketched the genomic landscape of the tumor types spectrum. We delineated the purity- and ploidy-adjusted allele-specific profiles of 4,950 patients across 27 tumor types from the Cancer Genome Atlas (TCGA). Leveraging allele-specific data, we reclassified as loss of heterozygosity (LOH) 9% and 7% of apparent copy-number wild-type and gain calls, respectively, and overall observed more than 18 million allelic imbalance somatic events at the gene level. Reclassification of copy-number events revealed associations between driver mutations and LOH, pointing out the timings between the occurrence of point mutations and copy-number events. Integrating allele-specific genomics and matched transcriptomics, we observed that allele-specific gene status is relevant in the regulation of TP53 and its targets. Further, we disclosed the role of copy-neutral LOH in the impairment of tumor suppressor genes and in disease progression. Our results highlight the role of LOH in cancer and contribute to the understanding of tumor progression.

Fast mutual exclusivity algorithm nominates potential synthetic lethal gene pairs through brute force matrix product computations.

Mutual Exclusivity analysis of genomic aberrations contributes to the exploration of potential synthetic lethal (SL) relationships thus guiding the nomination of specific cancer cells vulnerabilities. When multiple classes of genomic aberrations and large cohorts of patients are interrogated, exhaustive genome-wide analyses are not computationally feasible with commonly used approaches. Here we present Fast Mutual Exclusivity (FaME), an algorithm based on matrix multiplication that employs a logarithm-based implementation of the Fisher's exact test to achieve fast computation of genome-wide mutual exclusivity tests; we show that brute force testing for mutual exclusivity of hundreds of millions of aberrations combinations can be performed in few minutes. We applied FaME to allele-specific data from whole exome experiments of 27 TCGA studies cohorts, detecting both mutual exclusivity of point mutations, as well as allele-specific copy number signals that span sets of contiguous cytobands. We next focused on a case study involving the loss of tumor suppressors and druggable genes while exploiting an integrated analysis of both public cell lines loss of function screens data and patients' transcriptomic profiles. FaME algorithm implementation as well as allele-specific analysis output are publicly available at https://github.com/demichelislab/FaME.

Two distinct immunopathological profiles in autopsy lungs of COVID-19.

Coronavirus Disease 19 (COVID-19) is a respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has grown to a worldwide pandemic with substantial mortality. Immune mediated damage has been proposed as a pathogenic factor, but immune responses in lungs of COVID-19 patients remain poorly characterized. Here we show transcriptomic, histologic and cellular profiles of post mortem COVID-19 (n = 34 tissues from 16 patients) and normal lung tissues (n = 9 tissues from 6 patients). Two distinct immunopathological reaction patterns of lethal COVID-19 are identified. One pattern shows high local expression of interferon stimulated genes (ISGhigh) and cytokines, high viral loads and limited pulmonary damage, the other pattern shows severely damaged lungs, low ISGs (ISGlow), low viral loads and abundant infiltrating activated CD8+ T cells and macrophages. ISGhigh patients die significantly earlier after hospitalization than ISGlow patients. Our study may point to distinct stages of progression of COVID-19 lung disease and highlights the need for peripheral blood biomarkers that inform about patient lung status and guide treatment.

HMGA1 promotes breast cancer angiogenesis supporting the stability, nuclear localization and transcriptional activity of FOXM1.

BACKGROUND: Breast cancer is the most common malignancy in women worldwide. Among the breast cancer subtypes, triple-negative breast cancer (TNBC) is the most aggressive and the most difficult to treat. One of the master regulators in TNBC progression is the architectural transcription factor HMGA1. This study aimed to further explore the HMGA1 molecular network to identify molecular mechanisms involved in TNBC progression. METHODS: RNA from the MDA-MB-231 cell line, silenced for HMGA1 expression, was sequenced and, with a bioinformatic analysis, molecular partners HMGA1 could cooperate with in regulating common downstream gene networks were identified. Among the putative partners, the FOXM1 transcription factor was selected. The relationship occurring between HMGA1 and FOXM1 was explored by qRT-PCR, co-immunoprecipitation and protein stability assays. Subsequently, the transcriptional activity of HMGA1 and FOXM1 was analysed by luciferase assay on the VEGFA promoter. The impact on angiogenesis was assessed in vitro, evaluating the tube formation ability of endothelial cells exposed to the conditioned medium of MDA-MB-231 cells silenced for HMGA1 and FOXM1 and in vivo injecting MDA-MB-231 cells, silenced for the two factors, in zebrafish larvae. RESULTS: Here, we discover FOXM1 as a novel molecular partner of HMGA1 in regulating a gene network implicated in several breast cancer hallmarks. HMGA1 forms a complex with FOXM1 and stabilizes it in the nucleus, increasing its transcriptional activity on common target genes, among them, VEGFA, the main inducer of angiogenesis. Furthermore, we demonstrate that HMGA1 and FOXM1 synergistically drive breast cancer cells to promote tumor angiogenesis both in vitro in endothelial cells and in vivo in a zebrafish xenograft model. Moreover, using a dataset of breast cancer patients we show that the co-expression of HMGA1, FOXM1 and VEGFA is a negative prognostic factor of distant metastasis-free survival and relapse-free survival. CONCLUSIONS: This study reveals FOXM1 as a crucial interactor of HMGA1 and proves that their cooperative action supports breast cancer aggressiveness, by promoting tumor angiogenesis. Therefore, the possibility to target HMGA1/FOXM1 in combination should represent an attractive therapeutic option to counteract breast cancer angiogenesis.

High-throughput assessment of the antibody profile in ovarian cancer ascitic fluids.

The identification of effective biomarkers for early diagnosis, prognosis, and response to treatments remains a challenge in ovarian cancer (OC) research. Here, we present an unbiased high-throughput approach to profile ascitic fluid autoantibodies in order to obtain a tumor-specific antigen signature in OC. We first reported the reactivity of immunoglobulins (Igs) purified from OC patient ascites towards two different OC cell lines. Using a discovery set of Igs, we selected tumor-specific antigens from a phage display cDNA library. After biopanning, 700 proteins were expressed as fusion protein and used in protein array to enable large-scale immunoscreening with independent sets of cancer and noncancerous control. Finally, the selected antigens were validated by ELISA. The initial screening identified eight antigenic clones: CREB3, MRPL46, EXOSC10, BCOR, HMGN2, HIP1R, OLFM4, and KIAA1755. These antigens were all validated by ELISA in a study involving ascitic Igs from 153 patients (69 with OC, 34 with other cancers and 50 without cancer), with CREB3 showing the highest sensitivity (86.95%) and specificity (98%). Notably, we were able to identify an association between the tumor-associated (TA) antibody response and the response to a first-line tumor treatment (platinum-based chemotherapy). A stronger association was found by combining three antigens (BCOR, CREB3, and MRLP46) as a single antibody signature. Measurement of an ascitic fluid antibody response to multiple TA antigens may aid in the identification of new prognostic signatures in OC patients and shift attention to new potentially relevant targets.

Mutant p53 tunes the NRF2-dependent antioxidant response to support survival of cancer cells.

NRF2 (NFE2L2) is one of the main regulators of the antioxidant response of the cell. Here we show that in cancer cells NRF2 targets are selectively upregulated or repressed through a mutant p53-dependent mechanism. Mechanistically, mutant p53 interacts with NRF2, increases its nuclear presence and resides with NRF2 on selected ARE containing gene promoters activating the transcription of a specific set of genes while leading to the transcriptional repression of others. We show that thioredoxin (TXN) is a mutant p53-activated NRF2 target with pro-survival and pro-migratory functions in breast cancer cells under oxidative stress, while heme oxygenase 1 (HMOX1) is a mutant p53-repressed target displaying opposite effects. A gene signature of NRF2 targets activated by mutant p53 shows a significant association with bad overall prognosis and with mutant p53 status in breast cancer patients. Concomitant inhibition of thioredoxin system with Auranofin and of mutant p53 with APR-246 synergizes in killing cancer cells expressing p53 gain-of-function mutants.

An NF-κB signature predicts low-grade glioma prognosis: a precision medicine approach based on patient-derived stem cells.

Background: While recent genome-wide association studies have suggested novel low-grade glioma (LGG) stratification models based on a molecular classification, we explored the potential clinical utility of patient-derived cells. Specifically, we assayed glioma-associated stem cells (GASC) that are patient-derived and representative of the glioma microenvironment. Methods: By next-generation sequencing, we analyzed the transcriptional profile of GASC derived from patients who underwent anaplastic transformation either within 48 months (GASC-BAD) or ≥7 years (GASC-GOOD) after surgery. Gene set enrichment and pathway enrichment analyses were applied. The prognostic role of a nuclear factor-kappaB (NF-κB) signature derived from GASC-BAD was tested in 530 newly diagnosed diffuse LGG patients comprised within The Cancer Genome Atlas (TCGA) database. The prognostic value of the GASC upstream regulator p65 NF-κB was assessed, by univariate and multivariate Cox analyses, in a single center case study, including 146 grade II LGGs. Results: The key elements differentiating the transcriptome of GASC isolated from LGG with different prognoses were mostly related to hallmarks of cancer (eg, inflammatory/immune process, NF-κB activation). Consistently, the NF-κB signature extrapolated from the GASC study was prognostic in the dataset of TCGA. Finally, the nuclear expression of the NF-kB-p65 protein, assessed using an inexpensive immunohistochemical method, was an independent predictor of both overall survival and malignant progression-free survival in 146 grade II LGGs. Conclusion: This study demonstrates for the first time the independent prognostic role of NF-kB activation in LGG and outlines the role of patient-based stem cell models as a tool for precision medicine approaches.

PIN1 in breast development and cancer: a clinical perspective.

Mammary gland development, various stages of mammary tumorigenesis and breast cancer progression have the peptidyl-prolyl cis/trans isomerase PIN1 at their centerpiece, in virtue of the ability of this unique enzyme to fine-tune the dynamic crosstalk between multiple molecular pathways. PIN1 exerts its action by inducing conformational and functional changes on key cellular proteins, following proline-directed phosphorylation. Through this post-phosphorylation signal transduction mechanism, PIN1 controls the extent and direction of the cellular response to a variety of inputs, in physiology and disease. This review discusses PIN1's roles in normal mammary development and cancerous progression, as well as the clinical impact of targeting this enzyme in breast cancer patients.

Epigenetic silencing of miR-296 and miR-512 ensures hTERT dependent apoptosis protection and telomere maintenance in basal-type breast cancer cells.

The catalytic subunit of the telomerase complex, hTERT, ensures unlimited proliferative potential of cancer cells by maintaining telomere function and protecting from apoptosis. Using a miRNA screening approach we identified miR-296-5p and miR-512-5p as miRNAs that target hTERT in breast cancer cells. Ectopic miR-296-5p and miR-512-5p reduce telomerase activity, drive telomere shortening and cause proliferation defects by enhancing senescence and apoptosis in breast cancer cells. In line with the relevance of hTERT expression for human cancer we found that miR-296-5p and miR-512-5p expression is reduced in human breast cancer. Accordingly, high expression of miR-296-5p and miR-512-5p target genes including hTERT is linked with significantly reduced distant metastasis free survival and relapse free survival of basal type breast cancer patients. This suggests relevance of the identified miRNAs in basal type breast cancer. Epigenetic silencing of miR-296 and miR-512 encoding genes is responsible for low levels of miR-296-5p and miR-512-5p expression in basal type breast cancer cells. Disrupting gene silencing results in a dramatic upregulation of miR-296-5p and miR-512-5p levels leading to reduced hTERT expression and increased sensitivity to the induction of apoptosis. Altogether, our data suggest that epigenetic regulatory circuits in basal type breast cancer may contribute to high hTERT levels by silencing miR-296-5p and miR-512-5p expression, thereby contributing to the aggressiveness of basal type breast cancer.