Antonio Lembo

microRNA-214 contributes to melanoma tumour progression through suppression of TFAP2C

Malignant melanoma is fatal in its metastatic stage. It is therefore essential to unravel the molecular mechanisms that govern disease progression to metastasis. MicroRNAs (miRs) are endogenous non‐coding RNAs involved in tumourigenesis. Using a melanoma progression model, we identified a novel pathway controlled by miR‐214 that coordinates metastatic capability. Pathway components include TFAP2C, homologue of a well‐established melanoma tumour suppressor, the adhesion receptor ITGA3 and multiple surface molecules. Modulation of miR‐214 influences in vitro tumour cell movement and survival to anoikis as well as extravasation from blood vessels and lung metastasis formation in vivo. Considering that miR‐214 is known to be highly expressed in human melanomas, our data suggest a critical role for this miRNA in disease progression and the establishment of distant metastases.

Shortening of 3'UTRs correlates with poor prognosis in breast and lung cancer.

A major part of the post-transcriptional regulation of gene expression is affected by trans-acting elements, such as microRNAs, binding the 3′ untraslated region (UTR) of their target mRNAs. Proliferating cells partly escape this type of negative regulation by expressing shorter 3′ UTRs, depleted of microRNA binding sites, compared to non-proliferating cells. Using large-scale gene expression datasets, we show that a similar phenomenon takes place in breast and lung cancer: tumors expressing shorter 3′ UTRs tend to be more aggressive and to result in shorter patient survival. Moreover, we show that a gene expression signature based only on the expression ratio of alternative 3′ UTRs is a strong predictor of survival in both tumors. Genes undergoing 3′UTR shortening in aggressive tumors of the two tissues significantly overlap, and several of them are known to be involved in tumor progression. However the pattern of 3′ UTR shortening in aggressive tumors in vivo is clearly distinct from analogous patterns involved in proliferation and transformation.

miR-221/222 control luminal breast cancer tumor progression by regulating different targets

α6β4 integrin is an adhesion molecule for laminin receptors involved in tumor progression. We present a link between β4 integrin expression and miR-221/222 in the most prevalent human mammary tumor: luminal invasive carcinomas (Lum-ICs). Using human primary tumors that display different β4 integrin expression and grade, we show that miR-221/222 expression inversely correlates with tumor proliferating index, Ki67. Interestingly, most high-grade tumors express β4 integrin and low miR-221/222 levels. We ectopically transfected miR-221/222 into a human-derived mammary tumor cell line that recapitulates the luminal subtype to investigate whether miR-221/222 regulates β4 expression. We demonstrate that miR-221/222 overexpression results in β4 expression downregulation, breast cancer cell proliferation, and invasion inhibition. The role of miR-221/222 in driving β4 integrin expression is also confirmed via mutating the miR-221/222 seed sequence for β4 integrin 3′UTR. Furthermore, we show that these 2 miRNAs are also key breast cancer cell proliferation and invasion regulators, via the post-transcriptional regulation of signal transducer and activator of transcription 5A (STAT5A) and of a disintegrin and metalloprotease-17 (ADAM-17). We further confirm these data by silencing ADAM-17, using a dominant-negative or an activated STAT5A form. miR-221/222-driven β4 integrin, STAT5A, and ADAM-17 did not occur in MCF-10A cells, denoted “normal” breast epithelial cells, indicating that the mechanism is cancer cell-specific. These results provide the first evidence of a post-transcriptional mechanism that regulates β4 integrin, STAT5A, and ADAM-17 expression, thus controlling breast cancer cell proliferation and invasion. Pre-miR-221/222 use in the aggressive luminal subtype may be a powerful therapeutic anti-cancer strategy.

Identification of p130Cas/ErbB2-dependent invasive signatures in transformed mammary epithelial cells

Understanding transcriptional changes during cancer progression is of crucial importance to develop new and more efficacious diagnostic and therapeutic approaches. It is well known that ErbB2 is overexpressed in about 25% of human invasive breast cancers. We have previously demonstrated that p130Cas overexpression synergizes with ErbB2 in mammary cell transformation and promotes ErbB2-dependent invasion in three-dimensional (3D) cultures of human mammary epithelial cells. Here, by comparing coding and non-coding gene expression profiles, we define the invasive signatures associated with concomitant p130Cas overexpression and ErbB2 activation in 3D cultures of mammary epithelial cells. Specifically, we have found that genes involved in amino acids synthesis (CBS, PHGDH), cell motility, migration (ITPKA, PRDM1), and angiogenesis (HEY1) are upregulated, while genes involved in inflammatory response (SAA1, S100A7) are downregulated. In parallel, we have shown that the expression of specific miRNAs is altered. Among these, miR-200b, miR-222, miR-221, miR-R210, and miR-424 are upregulated, while miR-27a, miR-27b, and miR-23b are downregulated. Overall, this study presents, for the first time, the gene expression changes underlying the invasive behavior following p130Cas overexpression in an ErbB2 transformed mammary cell model.

Subtype-Specific Metagene-Based Prediction of Outcome after Neoadjuvant and Adjuvant Treatment in Breast Cancer

Purpose: In spite of improvements of average benefit from adjuvant/neoadjuvant treatments, there are still individual patients with early breast cancer at high risk of relapse. We explored the association with outcome of robust gene cluster–based metagenes linked to proliferation, ER-related genes, and immune response to identify those high-risk patients. Experimental Design: A total of 3,847 publicly available gene-expression profiles were analyzed (untreated, N = 826; tamoxifen-treated, N = 685; chemotherapy-treated, N = 1,150). Genes poorly performing in formalin-fixed samples were removed. Outcomes of interest were pathologic-complete response (pCR) and distant metastasis-free survival (DMFS). In ER+HER2−, the proliferation and ER-related metagenes were combined to define three risk groups. In HER2+ and ER−HER2− risk groups were defined by tertiles of an immune-related metagene. Results: The high-proliferation/low-ER group of ER+HER2− breast cancer had significantly higher pCR rate [OR, 5.01 (1.76–17.99), P = 0.005], but poorer outcome [HR = 3.73 (1.63–8.51), P = 0.0018] than the low-proliferation/high-ER. A similar association with outcome applied to patients with residual disease (RD) after neoadjuvant chemotherapy (P = 0.01). In ER−HER2− and HER2+ breast cancer, immune metagene in the high tertile was linked to higher pCR [33.7% vs. 11.6% in high and low tertile, respectively; OR, 3.87 (1.79–8.95); P = 0.0009]. In ER−HER2−, after adjuvant/neoadjuvant chemotherapy, 5-year DMFS was 85.4% for high-tertile immune metagene, and 43.9% for low tertile. The outcome association was similar in patients with RD (P = 0.0055). In HER2+ breast cancer treated with chemotherapy the association with risk of relapse was not significant. Conclusions: We developed metagene-based predictors able to define low and high risk of relapse after adjuvant/neoadjuvant therapy. High-risk patients so defined should be preferably considered for trials with investigational agents. Clin Cancer Res; 22(2); 337–45. ©2015 AACR.

A signature inferred from Drosophila mitotic genes predicts survival of breast cancer patients.

Introduction The classification of breast cancer patients into risk groups provides a powerful tool for the identification of patients who will benefit from aggressive systemic therapy. The analysis of microarray data has generated several gene expression signatures that improve diagnosis and allow risk assessment. There is also evidence that cell proliferation-related genes have a high predictive power within these signatures. Methods We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes). Results The DM signature has minimal overlap with the extant signatures and is highly predictive of survival in 5 large breast cancer datasets. In addition, we show that the DM signature outperforms many widely used breast cancer signatures in predictive power, and performs comparably to other proliferation-based signatures. For most genes of the DM signature, an increased expression is negatively correlated with patient survival. The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis. Conclusion This finding highlights cytokinesis as an important marker in breast cancer prognosis and as a possible target for antimitotic therapies.

Roar: Detecting alternative polyadenylation with standard mRNA sequencing libraries

BackgroundPost-transcriptional regulation is a complex mechanism that plays a central role in defining multiple cellular identities starting from a common genome. Modifications in the length of 3’UTRs have been found to play an important role in this context, since alternative 3’ UTRs could lead to differences for example in regulation by microRNAs and cellular localization of the transcripts thus altering their fate.ResultsWe propose a strategy to identify the genes undergoing regulation of 3’ UTR length using RNA sequencing data obtained from standard libraries, thus widely applicable to data originally obtained to perform classical differential expression analyses. We decided to exploit previously annotated APA sites from public databases, in contrast with other approaches recently proposed in which the location of the APA site is inferred from the data together with the relative abundance of the isoforms.We demonstrate the reliability of our method by comparing it to the results of other microarray based or specific RNA-seq libraries methods and show that using APA sites databases results in higher sensitivity compared to de novo site prediction approach.ConclusionsWe implemented the algorithm in a Bioconductor package to facilitate its broad usage in the scientific community. The ability of this approach to detect shortening from libraries with a number of reads comparable to that needed for differential expression analyses makes it useful for investigating if alternative polyadenylation is relevant in a certain biological process without requiring specific experimental assays.

miR-21 coordinates tumor growth and modulates KRIT1 levels

Highlights • miR-21 targets KRIT1.• miR-21 and KRIT1 expression anticorrelate in human breast tumors.• KRIT1 is involved in miR-21-mediated tumor cell growth.

Accurate data processing improves the reliability of Affymetrix gene expression profiles from FFPE samples.

Formalin fixed paraffin-embedded (FFPE) tumor specimens are the conventionally archived material in clinical practice, representing an invaluable tissue source for biomarkers development, validation and routine implementation. For many prospective clinical trials, this material has been collected allowing for a prospective-retrospective study design which represents a successful strategy to define clinical utility for candidate markers. Gene expression data can be obtained even from FFPE specimens with the broadly used Affymetrix HG-U133 Plus 2.0 microarray platform. Nevertheless, important major discrepancies remain in expression data obtained from FFPE compared to fresh-frozen samples, prompting the need for appropriate data processing which could help to obtain more consistent results in downstream analyses. In a publicly available dataset of matched frozen and FFPE expression data, the performances of different normalization methods and specifically designed Chip Description Files (CDFs) were compared. The use of an alternative CDFs together with fRMA normalization significantly improved frozen-FFPE sample correlations, frozen-FFPE probeset correlations and agreement of differential analysis between different tumor subtypes. The relevance of our optimized data processing was assessed and validated using two independent datasets. In this study we demonstrated that an appropriate data processing can significantly improve the reliability of gene expression data derived from FFPE tissues using the standard Affymetrix platform. Tools for the implementation of our data processing algorithm are made publicly available at http://www.biocut.unito.it/cdf-ffpe/.

Abstract P1-07-02: Mesenchymal stem cell regulated microRNAs converge on the speech gene FOXP2 and regulate breast cancer metastasis

About 90% of breast cancer mortalities are due to the spread of breast cancer cells (BCCs) from a primary tumor to distant organs, a process known as metastasis. However, the molecular mechanisms underlying metastasis remain poorly understood. Substantial evidence now supports a major role for the tumor microenvironment (TME) in catalyzing breast cancer metastasis. Indeed, observations indicate that proximal interactions between BCCs and cells of the TME induce altered gene expression programs in BCCs, allowing for the navigation of the various steps of the metastatic cascade. Our group and others observed that breast tumors recruit mesenchymal stem cells (MSCs): multipotent fibroblasts that normally exert tissue maintenance functions. We and others have observed that physical interactions of MSCs with BCCs are sufficient to drive their metastatic dissemination in murine xenograft models, via the induction of epithelial-mesenchymal transition (EMT) and dedifferentiation into stem cell-like states (cancer stem cells, or CSCs), states tightly associated with the capacity to seed new tumors (for example in foreign tissues) and with chemotherapeutic resistance. However, the TME-induced molecular pathways regulating such mechanisms remain poorly understood. MicroRNAs (miRNAs, miRs) are small noncoding RNAs that regulate gene expression via base-pair interactions with messenger RNAs (mRNAs), resulting in mRNA degradation or translational inhibition. Due to their ability to interact with large numbers of target mRNAs simultaneously, miRNAs are major regulators of cell identity, and thereby serve critical roles in metastasis. We performed miRnome-wide screening of MSC-stimulated BCCs to determine if TME interactions might contribute to BCC metastasis via the deregulation of miRNAs. We observed that proximal MSCs induce aberrant expression of a specific set of miRNAs in BCCs, which had not been previously implicated in breast cancer pathogenesis. These miRNAs, led by the transcriptionally co-regulated miR-199a-3p and miR-214, were sufficient to actuate the metastasis of weakly metastatic human BCCs in xenograft models. We observed that exogenous expression of the miRNAs provided BCCs with phenotypes and gene markers characteristic of CSCs, including enhanced tumor initiation capacities. Interestingly, we found that the MSC-induced miRNAs function as an interrelated network, and converge upon a common novel target: the speech associated gene FOXP2. Knockdown of FOXP2 phenocopied the metastatic phenotypes observed in MSC-induced miRNA expressing BCCs. Importantly, elevated levels of the MSC-induced miRNAs or depressed levels of FOXP2 could predict patient prognosis in the clinic. Altogether, our results incriminate FOXP2 and it’s MSC-induced miRNA regulatory network as novel determinants of breast cancer metastasis. Citation Format: Benjamin G Cuiffo, Antoine Campagne, George W Bell, Antonio Lembo, Francesca Orso, Evan Lien, Manoj K Bhasin, Monica Raimo, Summer E Hanson, Andriy Marusyk, Peiman Hematti, Kornelia Polyak, Odette Mariani, Stefano Volinia, Anne Vincent-Salomon, Daniela Taverna, Antoine E Karnoub. Mesenchymal stem cell regulated microRNAs converge on the speech gene FOXP2 and regulate breast cancer metastasis [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-07-02.