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Simple Summary Aberrant alternative splicing is now considered a hallmark of cancer, including breast cancer. This results in the production of novel tumor-specific splice RNA variants, and the activation of biological processes such as epithelial-to-mesenchymal transition, leading to more aggressive phenotypes. The purpose of this study was to explore the role of estrogen receptor α in regulating the expression of RNA-binding proteins in luminal breast cancer cells and to determine the effects of its downregulation at the isoform level by exploring changes in isoform usage and alternative splicing. The findings of this study unravel a novel layer of gene regulation mediated by estrogen receptor α, which is fundamental for breast cancer cell growth as well as epithelial-to-mesenchymal transition. Finally, we foresee that this novel feature should be considered when studying the functional roles of estrogen receptor α in the onset and progression of breast cancer. Abstract Background: The transcriptional activity of estrogen receptor α (ERα) in breast cancer (BC) is extensively characterized. Our group has previously shown that ERα controls the expression of a number of genes in its unliganded form (apoERα), among which a large group of RNA-binding proteins (RBPs) encode genes, suggesting its role in the control of co- and post-transcriptional events. Methods: apoERα-mediated RNA processing events were characterized by the analysis of transcript usage and alternative splicing changes in an RNA-sequencing dataset from MCF-7 cells after siRNA-induced ERα downregulation. Results: ApoERα depletion induced an expression change of 681 RBPs, including 84 splicing factors involved in translation, ribonucleoprotein complex assembly, and 3′end processing. ApoERα depletion results in 758 isoform switching events with effects on 3′end length and the splicing of alternative cassette exons. The functional enrichment of these events shows that post-transcriptional regulation is part of the mechanisms by which apoERα controls epithelial-to-mesenchymal transition and BC cell proliferation. In primary BCs, the inclusion levels of the experimentally identified alternatively spliced exons are associated with overall and disease-free survival. Conclusion: Our data supports the role of apoERα in maintaining the luminal phenotype of BC cells by extensively regulating gene expression at the alternative splicing level.

Post-synthesis modification of biomolecules is an efficient way of regulating and optimizing their functions. The human epitranscriptome includes a variety of more than 100 modifications known to exist in all RNA subtypes. Modifications of non-coding RNAs are particularly interesting since they can directly affect their structure, stability, interaction and function. Indeed, non-coding RNAs such as tRNA and rRNA are the most modified RNA species in eukaryotic cells. In the last 20 years, new functions of non-coding RNAs have been discovered and their involvement in human disease, including cancer, became clear. In this review, we will present the evidence connecting modifications of different non-coding RNA subtypes and their role in cancer.

DSCAM-AS1 is a cancer-related long noncoding RNA with higher expression levels in Luminal A, B, and HER2-positive Breast Carcinoma (BC), where its expression is strongly dependent on Estrogen Receptor Alpha (ER&alpha, ). DSCAM-AS1 expression is analyzed in 30 public datasets and, additionally, by qRT-PCR in tumors from 93 BC patients, to uncover correlations with clinical data. Moreover, the effect of DSCAM-AS1 knockdown on gene expression and alternative splicing is studied by RNA-Seq in MCF-7 cells. We confirm DSCAM-AS1 overexpression in high grade Luminal A, B, and HER2+ BCs and find a significant correlation with disease relapse. In total, 908 genes are regulated by DSCAM-AS1-silencing, primarily involved in the cell cycle and inflammatory response. Noteworthily, the analysis of alternative splicing and isoform regulation reveals 2085 splicing events regulated by DSCAM-AS1, enriched in alternative polyadenylation sites, 3&prime, UTR (untranslated region) shortening and exon skipping events. Finally, the DSCAM-AS1-interacting splicing factor heterogeneous nuclear ribonucleoprotein L (hnRNPL) is predicted as the most enriched RBP for exon skipping and 3&prime, UTR events. The relevance of DSCAM-AS1 overexpression in BC is confirmed by clinical data and further enhanced by its possible involvement in the regulation of RNA processing, which is emerging as one of the most important dysfunctions in cancer.

Recent improvements in cost-effectiveness of high-throughput technologies has allowed RNA sequencing of total transcriptomes suitable for evaluating the expression and regulation of circRNAs, a relatively novel class of transcript isoforms with suggested roles in transcriptional and post-transcriptional gene expression regulation, as well as their possible use as biomarkers, due to their deregulation in various human diseases. A limited number of integrated workflows exists for prediction, characterization, and differential expression analysis of circRNAs, none of them complying with computational reproducibility requirements. We developed Docker4Circ for the complete analysis of circRNAs from RNA-Seq data. Docker4Circ runs a comprehensive analysis of circRNAs in human and model organisms, including: circRNAs prediction, classification and annotation using six public databases, back-splice sequence reconstruction, internal alternative splicing of circularizing exons, alignment-free circRNAs quantification from RNA-Seq reads, and differential expression analysis. Docker4Circ makes circRNAs analysis easier and more accessible thanks to: (i) its R interface, (ii) encapsulation of computational tasks into docker images, (iii) user-friendly Java GUI Interface availability, and (iv) no need of advanced bash scripting skills for correct use. Furthermore, Docker4Circ ensures a reproducible analysis since all its tasks are embedded into a docker image following the guidelines provided by Reproducible Bioinformatics Project.

In the study of genomic regulation, strategies to integrate the data produced by Next Generation Sequencing (NGS)-based technologies in a meaningful ensemble are eagerly awaited and must continuously evolve. Here, we describe an integrative strategy for the analysis of data generated by chromatin immunoprecipitation followed by NGS which combines algorithms for data overlap, normalization and epigenetic state analysis. The performance of our strategy is illustrated by presenting the analysis of data relative to the transcriptional regulator Estrogen Receptor alpha (ERα) in MCF-7 breast cancer cells and of Glucocorticoid Receptor (GR) in A549 lung cancer cells. We went through the definition of reference cistromes for different experimental contexts, the integration of data relative to co-regulators and the overlay of chromatin states as defined by epigenetic marks in MCF-7 cells. With our strategy, we identified novel features of estrogen-independent ERα activity, including FoxM1 interaction, eRNAs transcription and a peculiar ontology of connected genes.

Despite many computational tools were developed to predict circular RNAs (circRNAs), a limited number of work-flows exists to fully analyse a circRNA set ensuring the computational reproducibility of the whole analysis. For this purpose, we designed Docker4Circ, a computational work-flow for a comprehensive circRNAs analysis of a circRNAs composed of four modules: the circRNAs prediction (module 1), the circRNAs classification and annotation (module 2), the circRNAs sequence analysis (module 3), and circRNAs expression analysis (module 4). To ensure reproducibility each function of Docker4Circ was embeded into a docker image following guideline provided by Reproducible Bioinformatics Project (RBP, http://reproducible-bioinformatics.org/). Each function is included in the Docker4Seq R package which already includes different solutions for reproducible bioinformatic analyses. This protocol describes the use of each function of Docker4Circ to analyse the circRNAs predicted from a set of RNA-Seq experiments performed in normal colon and colorectal cancer cell lines. Furthermore, the description of the functions required to compute the expression level of the analysed circRNAs in a set of RNA-Seq experiments of colorectal primary tumors is provided.

Recently the increased cost-effectiveness of high-throughput technologies has made available a large number of RNA sequencing datasets to identify circular RNAs (circRNAs). However, despite many computational tools were developed to predict circRNAs, a limited number of workflows exists to predict and to characterize circRNAs. Moreover, to the best of our knowledge, these available workflows do not ensure computational reproducibility and require advanced bash scripting skills to be correctly installed and used. To cope with these critical aspects we present Docker4Circ, a new computational framework designed for a comprehensive analysis of circRNAs composed of: circRNAs prediction, classification and annotation using public databases, the back-splicing sequence reconstruction; the internal alternative splicing of circularizing exons; the alignment-free circRNAs quantification from RNA-Seq reads, and, finally, their differential expression analysis. Docker4Circ was specifically designed for making easier and more accessible circRNAs analysis thanks to the following features: (i) its R interface; (ii) the encapsulation of its computational tasks into a docker image; (iii) an available user-friendly Java GUI Interface. Furthermore, Docker4Circ ensures a reproducible analysis because all its tasks were embedded into a docker image following the guidelines provided by Reproducible Bioinformatics Project (RBP, http://reproducible-bioinformatics.org/). The effectiveness of Docker4Circ was demonstrated on a real case study whose goal is to characterize the circRNAs predicted in colorectal cancer cell lines and quantified in public RNA-Seq experiments performed on primary tumor tissues. In conclusion, we propose Docker4Circ as a framework for reproducible and comprehensive analyses of circRNAs to efficiently exploit their biological role.

Estrogen receptor-α (ERα) is a ligand-inducible protein which mediates estrogenic hormones signaling and defines the luminal BC phenotype. Recently, we demonstrated that even in absence of ligands ERα (apoERα) binds chromatin sites where it regulates transcription of several protein-coding and lncRNA genes. Noteworthy, apoERα-regulated lncRNAs marginally overlap estrogen-induced transcripts, thus representing a new signature of luminal BC genes. By the analysis of H3K27ac enrichment in hormone-deprived MCF-7 cells, we defined a set of Super Enhancers (SEs) occupied by apoERα, including one mapped in proximity of the DSCAM-AS1 lncRNA gene. This represents a paradigm of apoERα activity since its expression is largely unaffected by estrogenic treatment, despite the fact that E2 increases ERα binding on DSCAM-AS1 promoter. We validated the enrichment of apoERα, p300, GATA3, FoxM1 and CTCF at both DSCAM-AS1 TSS and at its associated SE by ChIP-qPCR. Furthermore, by analyzing MCF-7 ChIA-PET data and by 3C assays, we confirmed long range chromatin interaction between the SE and the DSCAM-AS1 TSS. Interestingly, CTCF and p300 binding showed an enrichment in hormone-depleted medium and in the presence of ERα, elucidating the dynamics of the estrogen-independent regulation of DSCAM-AS1 expression. The analysis of this lncRNA provides a paradigm of transcriptional regulation of a luminal specific apoERα regulated lncRNA.

Demethylation of the long interspersed nuclear element (LINE-1; L1) antisense promoter can result in transcription of neighboring sequences as for the L1-MET transcript produced by the L1 placed in the second intron of MET. To define the role of L1-MET, we investigated the sequence and the transcription of L1-MET in vitro models and heterogeneous breast cancers, previously reported to show other L1-derived transcripts. L1-MET expressing cell lines were initially identified in silico and investigated for L1-MET promoter methylation, cDNA sequence and cell fraction mRNA. The transcriptional level of L1-MET and MET were then evaluated in breast specimens, including 9 cancer cell lines, 41 carcinomas of different subtypes, and 11 normal tissues. In addition to a L1-MET transcript ending at MET exon 21, six novel L1-MET splice variants were identified. Normal breast tissues were negative for the L1-MET expression, whereas the triple-negative breast cancer (TNBC) and the high-grade carcinomas were enriched with the L1-MET mRNA (p = 0.005 and p = 0.018, respectively). In cancer cells and tissues the L1-MET expression was associated with its promoter hypomethylation (ρ = -0.8 and -0.9, respectively). No correlation was found between L1-MET and MET mRNA although L1-MET expressing tumors with higher L1-MET/MET ratio were negative for the MET protein expression (p = 0.006). Besides providing the first identification and detailed description of L1-MET in breast cancer, we clearly demonstrate that higher levels of this transcript specifically recognize a subset of more aggressive carcinomas, mainly TNBC. We suggest the possible evaluation of L1-MET in the challenging diagnosis of early TNBCs.

Circular RNAs are highly stable molecules present in all eukaryotes generated by distinct transcript processing. We have exploited poly(A-) RNA-Seq data generated in our lab in MCF-7 breast cancer cells to define a compilation of exonic circRNAs more comprehensive than previously existing lists. Development of a novel computational tool, named CircHunter, allowed us to more accurately characterize circRNAs and to quantitatively evaluate their expression in publicly available RNA-Seq data from breast cancer cell lines and tumor tissues. We observed and confirmed, by ChIP analysis, that exons involved in circularization events display significantly higher levels of the histone post-transcriptional modification H3K36me3 than non-circularizing exons. This result has potential impact on circRNA biogenesis since H3K36me3 has been involved in alternative splicing mechanisms. By analyzing an Ago-HITS-CLIP dataset we also found that circularizing exons overlapped with an unexpectedly higher number of Ago binding sites than non-circularizing exons. Finally, we observed that a subset of MCF-7 circRNAs are specific to tumor versus normal tissue, while others can distinguish Luminal from other tumor subtypes, thus suggesting that circRNAs can be exploited as novel biomarkers and drug targets for breast cancer.

Estrogen Receptor alpha (ERα) activation by estrogenic hormones induces luminal breast cancer cell proliferation. However, ERα plays also important hormone-independent functions to maintain breast tumor cells epithelial phenotype. We reported previously by RNA-Seq that in MCF-7 cells in absence of hormones ERα down-regulation changes the expression of several genes linked to cellular development, representing a specific subset of estrogen-induced genes. Here, we report regulation of long non-coding RNAs from the same experimental settings. A list of 133 Apo-ERα-Regulated lncRNAs (AER-lncRNAs) was identified and extensively characterized using published data from cancer cell lines and tumor tissues, or experiments on MCF-7 cells. For several features, we ran validation using cell cultures or fresh tumor biopsies. AER-lncRNAs represent a specific subset, only marginally overlapping estrogen-induced transcripts, whose expression is largely restricted to luminal cells and which is able to perfectly classify breast tumor subtypes. The most abundant AER-lncRNA, DSCAM-AS1, is expressed in ERα+ breast carcinoma, but not in pre-neoplastic lesions, and correlates inversely with EMT markers. Down-regulation of DSCAM-AS1 recapitulated, in part, the effect of silencing ERα, i.e. growth arrest and induction of EMT markers. In conclusion, we report an ERα-dependent lncRNA set representing a novel luminal signature in breast cancer cells.

The activation of the LINE-1 sequence located within the second intron of MET leads to the onset of L1-MET transcript. We recently characterized the full L1-MET structure in breast cancer and showed that high levels of this transcript recognize a subset of more aggressive breast carcinomas, mainly of triple negative phenotype. However, at present, the relationship between L1-MET and MET is still poorly understood. In order to elucidate this function, we silenced L1-MET transcription using cells expressing different levels of L1-MET/MET, including lung cancer (A549 and EBC1), gastric cancer (GTL16), and breast cancer (MDA-MB231), that were transiently transfected with Gapmers-LNA (Exiqon), specifically targeting L1-MET sequence. Cell viability and apoptosis were evaluated after 24 h by cell count, Cell Titer Glow (Promega) and propidium iodide/annexin based-cytofluorimeter assays. RNA was purified from sample and control cells to assess the L1-METsilencing by qRT-PCR and to evaluate the gene-expression of a subset of cancer-related genes using Nanostring Technology, whereas western blot analyses were carried out to measure the protein expressions. A significant decrease of cell viability was detected in A549, EBC1 and GTL16, but not in MDA-MB231 cells, characterized by the lowest level of L1-MET overall. In parallel, the highly expressing L1-MET cells showed an increased rate of early and late apoptosis together with a strong reduction of MET gene and its protein expression. On the contrary, in MDA-MB231 cells L1-MET silencing induced only a slight MET gene and protein impairment. Overall, L1-MET knock-down caused a decrease expression of a conserved gene cluster, including a marked reduction of EGFR protein expression. Moreover, L1-MET silenced cells showed lower MET and EGFR phosphorylation, with a downstream silencing effect on pERK and pAKT. Results of cell treatment with the inhibitors of lysosome and proteasome activity bafilomycin and MG-132 ruled out the interaction of L1-MET silencing with protein degradation pathway. This is the first study investigating the function of the L1-MET transcript in cancer models. Our results show that although L1-MET is unable to encode for a protein, its silencing exerts a strong phenotypic effect on different tumor cell types, suggesting potential regulations at the transcriptional level. Note: This abstract was not presented at the meeting. Citation Format: Enrico Berrino, Umberto Miglio, Valentina Miano, Letizia Lanzetti, Silvia Benvenuti, Carla Debernardi, MIchele De Bortoli, Caterina Marchio, Tiziana Venesio, Anna Sapino. L1-MET transcription silencing modulates MET and EGFR gene and their protein expression and induces apoptosis and cell-death in different types of cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 261.

Tab2, originally described as a component of the inflammatory pathway, has been implicated in phenomena of gene de-repression in several contexts, due to its ability to interact with the NCoR corepressor. Tab2 interacts also with steroid receptors and dismisses NCoR from antagonist-bound Estrogen and Androgen Receptors on gene regulatory regions, thus modifying their transcriptional activity and leading to pharmacological resistance in breast and prostate cancer cells. We demonstrated previously that either Tab2 knock-down, or a peptide mimicking the Estrogen Receptor alpha domain interacting with Tab2, restore the antiproliferative response to Tamoxifen in Tamoxifen-resistant breast cancer cells. In this work, we map the domain of Tab2 responsible of Estrogen Receptor alpha interaction. First, using both co-immunoprecipitation and pull-down with recombinant proteins, we found that the central part of Tab2 is primarily responsible for this interaction, and that this region also interacts with Androgen Receptor. Then, we narrowed down the essential interaction region by means of competition assays using recombinant protein pull-down. The interaction motif was finally identified as a small region adjacent to, but not overlapping, the Tab2 MEKK1 phosphorylation sites. A synthetic peptide mimicking this motif efficiently displaced Tab2 from interacting with recombinant Estrogen Receptor alpha in vitro, prompting us to test its efficacy using derivatives of the MCF7 breast carcinoma cell lines that are spontaneously resistant to Tamoxifen. Indeed, we observed that this mimic peptide, made cell-permeable by addition of the TAT minimal carrier domain, reduced the growth of Tamoxifen-resistant MCF7 cells in the presence of Tamoxifen. These data indicate a novel functional domain of the Tab2 protein with potential application in drug design.

Estrogen receptor-α (ERα) has central role in hormone-dependent breast cancer and its ligand-induced functions have been extensively characterized. However, evidence exists that ERα has functions that are independent of ligands. In the present work, we investigated the binding of ERα to chromatin in the absence of ligands and its functions on gene regulation. We demonstrated that in MCF7 breast cancer cells unliganded ERα binds to more than 4,000 chromatin sites. Unexpectedly, although almost entirely comprised in the larger group of estrogen-induced binding sites, we found that unliganded-ERα binding is specifically linked to genes with developmental functions, compared with estrogen-induced binding. Moreover, we found that siRNA-mediated down-regulation of ERα in absence of estrogen is accompanied by changes in the expression levels of hundreds of coding and noncoding RNAs. Down-regulated mRNAs showed enrichment in genes related to epithelial cell growth and development. Stable ERα down-regulation using shRNA, which caused cell growth arrest, was accompanied by increased H3K27me3 at ERα binding sites. Finally, we found that FOXA1 and AP2γ binding to several sites is decreased upon ERα silencing, suggesting that unliganded ERα participates, together with other factors, in the maintenance of the luminal-specific cistrome in breast cancer cells.

The transcription factor signal transducer and activator of transcription 3 (STAT3) acts downstream of many pro-oncogenic signals, including cytokines, growth factors and oncogenes, and is accordingly constitutively active in a wide variety of tumors that often become addicted to it. Moreover, STAT3 is a key player in mediating inflammation-driven tumorigenesis, where its aberrant continuous activation is typically triggered by local or systemic production of the pro-inflammatory cytokine IL-6. We recently showed that mouse embryonic fibroblasts (MEFs) derived from STAT3C k/in mice, which express physiological levels of the constitutively active mutant STAT3C, display features of transformed cells such as increased proliferation, resistance to apoptosis and senescence, and aerobic glycolysis. Here, we show that pre-existing constitutively active STAT3 is sufficient to prime primary MEFs for malignant transformation upon spontaneous immortalization. Transformation is strictly STAT3-dependent and correlates with high resistance to apoptosis and enhanced expression of anti-apoptotic/pro-survival genes. Additionally, hypoxia inducible factor (HIF)-1α level is elevated by twofold and contributes to STAT3 oncogenic activity by supporting high rates of aerobic glycolysis. Thus, constitutively active STAT3, an accepted essential factor for tumor growth/progression, can also act as a first hit in multistep carcinogenesis; this ability to predispose cells to malignant transformation may be particularly relevant in the pro-oncogenic niche represented by chronically inflamed tissues.