Prediction and pan-cancer analysis of mammalian transcripts involved in target directed miRNA degradation.

It is currently unknown how many RNA transcripts are able to induce degradation of microRNAs (miRNA) via the mechanism known as target-directed miRNA degradation (TDMD). We developed TDMDfinder, a computational pipeline that identifies 'high confidence' TDMD interactions in the Human and Mouse transcriptomes by combining sequence alignment and feature selection approaches. Our predictions suggested that TDMD is widespread, with potentially every miRNA controlled by endogenous targets. We experimentally tested 37 TDMDfinder predictions, of which 17 showed TDMD effects as measured by RT-qPCR and small RNA sequencing, linking the miR-17, miR-19, miR-30, miR-221, miR-26 and miR-23 families to novel endogenous TDMDs. In some cases, TDMD was found to affect different members of the same miRNA family selectively. Features like complementarity to the miRNA 3' region, bulge size and hybridization energy appeared to be the main factors determining sensitivity. Computational analyses performed using the multiomic TCGA platform substantiated the involvement of many TDMD transcripts in human cancer and highlighted 36 highly significant interactions, suggesting TDMD as a new potential oncogenic mechanism. In conclusion, TDMDfinder provides the first inventory of bona fide human and mouse TDMDs. Available as a free webtool, TDMDfinder allows users to search for any TDMD interaction of interest by customizing its selection criteria.

Pan-cancer onco-signatures reveal a novel mitochondrial subtype of luminal breast cancer with specific regulators.

BACKGROUND: Somatic alterations in cancer cause dysregulation of signaling pathways that control cell-cycle progression, apoptosis, and cell growth. The effect of individual alterations in these pathways differs between individual tumors and tumor types. Recognizing driver events is a complex task requiring integrating multiple molecular data, including genomics, epigenomics, and functional genomics. A common hypothesis is that these driver events share similar effects on the hallmarks of cancer. The availability of large-scale multi-omics studies allows for inferring these common effects from data. Once these effects are known, one can then deconvolve in every individual patient whether a given genomics alteration is a driver event. METHODS: Here, we develop a novel data-driven approach to identify shared oncogenic expression signatures among tumors. We aim to identify gene onco-signature for classifying tumor patients in homogeneous subclasses with distinct prognoses and specific genomic alterations. We derive expression pan-cancer onco-signatures from TCGA gene expression data using a discovery set of 9107 primary pan-tumor samples together with respective matched mutational data and a list of known cancer-related genes from COSMIC database. RESULTS: We use the derived ono-signatures to state their prognostic significance and apply them to the TCGA breast cancer dataset as proof of principle of our approach. We uncover a "mitochondrial" sub-group of Luminal patients characterized by its biological features and regulated by specific genetic modulators. Collectively, our results demonstrate the effectiveness of onco-signatures-based methodologies, and they also contribute to a comprehensive understanding of the metabolic heterogeneity of Luminal tumors. CONCLUSIONS: These findings provide novel genomics evidence for developing personalized breast cancer patient treatments. The onco-signature approach, demonstrated here on breast cancer, is general and can be applied to other cancer types.

The immunologic constant of rejection classification refines the prognostic value of conventional prognostic signatures in breast cancer.

BACKGROUND: The immunologic constant of rejection (ICR) is a broad phenomenon of Th-1 immunity-mediated, tissue-specific destruction. METHODS: We tested the prognostic value of a 20-gene ICR expression signature in 8766 early breast cancers. RESULTS: Thirty-three percent of tumours were ICR1, 29% ICR2, 23% ICR3, and 15% ICR4. In univariate analysis, ICR4 was associated with a 36% reduction in risk of metastatic relapse when compared with ICR1-3 (p = 2.30E-03). In multivariate analysis including notably the three major prognostic signatures (Recurrence score, 70-gene signature, ROR-P), ICR was the strongest predictive variable (p = 9.80E-04). ICR showed no prognostic value in the HR+/HER2- subtype, but prognostic value in the HER2+ and TN subtypes. Furthermore, in each molecular subtype and among the tumours defined as high risk by the three prognostic signatures, ICR4 patients had a 41-75% reduction in risk of relapse as compared with ICR1-3 patients. ICR added significant prognostic information to that provided by the clinico-genomic models in the overall population and in each molecular subtype. ICR4 was independently associated with achievement of pathological complete response to neoadjuvant chemotherapy (p = 2.97E-04). CONCLUSION: ICR signature adds prognostic information to that of current proliferation-based signatures, with which it could be integrated to improve patients' stratification and guide adjuvant treatment.

Systems biology analysis reveals NFAT5 as a novel biomarker and master regulator of inflammatory breast cancer.

BACKGROUND: Inflammatory breast cancer (IBC) is the most rare and aggressive variant of breast cancer (BC); however, only a limited number of specific gene signatures with low generalization abilities are available and few reliable biomarkers are helpful to improve IBC classification into a molecularly distinct phenotype. We applied a network-based strategy to gain insight into master regulators (MRs) linked to IBC pathogenesis. METHODS: In-silico modeling and Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) on IBC/non-IBC (nIBC) gene expression data (n = 197) was employed to identify novel master regulators connected to the IBC phenotype. Pathway enrichment analysis was used to characterize predicted targets of candidate genes. The expression pattern of the most significant MRs was then evaluated by immunohistochemistry (IHC) in two independent cohorts of IBCs (n = 39) and nIBCs (n = 82) and normal breast tissues (n = 15) spotted on tissue microarrays. The staining pattern of non-neoplastic mammary epithelial cells was used as a normal control. RESULTS: Using in-silico modeling of network-based strategy, we identified three top enriched MRs (NFAT5, CTNNB1 or ß-catenin, and MGA) strongly linked to the IBC phenotype. By IHC assays, we found that IBC patients displayed a higher number of NFAT5-positive cases than nIBC (69.2% vs. 19.5%; p-value = 2.79 10(-7)). Accordingly, the majority of NFAT5-positive IBC samples revealed an aberrant nuclear expression in comparison with nIBC samples (70% vs. 12.5%; p-value = 0.000797). NFAT5 nuclear accumulation occurs regardless of WNT/ß-catenin activated signaling in a substantial portion of IBCs, suggesting that NFAT5 pathway activation may have a relevant role in IBC pathogenesis. Accordingly, cytoplasmic NFAT5 and membranous ß-catenin expression were preferentially linked to nIBC, accounting for the better prognosis of this phenotype. CONCLUSIONS: We provide evidence that NFAT-signaling pathway activation could help to identify aggressive forms of BC and potentially be a guide to assignment of phenotype-specific therapeutic agents. The NFAT5 transcription factor might be developed into routine clinical practice as a putative biomarker of IBC phenotype.

Endogenous transcripts control miRNA levels and activity in mammalian cells by target-directed miRNA degradation.

Little is known about miRNA decay. A target-directed miRNA degradation mechanism (TDMD) has been suggested, but further investigation on endogenous targets is necessary. Here, we identify hundreds of targets eligible for TDMD and show that an endogenous RNA (Serpine1) controls the degradation of two miRNAs (miR-30b-5p and miR-30c-5p) in mouse fibroblasts. In our study, TDMD occurs when the target is expressed at relatively low levels, similar in range to those of its miRNAs (100-200 copies per cell), and becomes more effective at high target:miRNA ratios (>10:1). We employ CRISPR/Cas9 to delete the miR-30 responsive element within Serpine1 3'UTR and interfere with TDMD. TDMD suppression increases miR-30b/c levels and boosts their activity towards other targets, modulating gene expression and cellular phenotypes (i.e., cell cycle re-entry and apoptosis). In conclusion, a sophisticated regulatory layer of miRNA and gene expression mediated by specific endogenous targets exists in mammalian cells.

Identification of genetic determinants of breast cancer immune phenotypes by integrative genome-scale analysis.

Cancer immunotherapy is revolutionizing the clinical management of several tumors, but has demonstrated limited activity in breast cancer. The development of more effective treatments is hindered by incomplete knowledge of the genetic determinant of immune responsiveness. To fill this gap, we mined copy number alteration, somatic mutation, and expression data from The Cancer Genome Atlas (TCGA). By using RNA-sequencing data from 1,004 breast cancers, we defined distinct immune phenotypes characterized by progressive expression of transcripts previously associated with immune-mediated rejection. The T helper 1 (Th-1) phenotype (ICR4), which also displays upregulation of immune-regulatory transcripts such as PDL1, PD1, FOXP3, IDO1, and CTLA4, was associated with prolonged patients' survival. We validated these findings in an independent meta-cohort of 1,954 breast cancer gene expression data. Chromosome segment 4q21, which includes genes encoding for the Th-1 chemokines CXCL9-11, was significantly amplified only in the immune favorable phenotype (ICR4). The mutation and neoantigen load progressively decreased from ICR4 to ICR1 but could not fully explain immune phenotypic differences. Mutations of TP53 were enriched in the immune favorable phenotype (ICR4). Conversely, the presence of MAP3K1 and MAP2K4 mutations were tightly associated with an immune-unfavorable phenotype (ICR1). Using both the TCGA and the validation dataset, the degree of MAPK deregulation segregates breast tumors according to their immune disposition. These findings suggest that mutation-driven perturbations of MAPK pathways are linked to the negative regulation of intratumoral immune response in breast cancer. Modulations of MAPK pathways could be experimentally tested to enhance breast cancer immune sensitivity.

Comparison between invasive breast cancer with extensive peritumoral vascular invasion and inflammatory breast carcinoma: a clinicopathologic study of 161 cases.

OBJECTIVES: Extensive peritumoral neoplastic lymphovascular invasion (ePVI) is a marker of aggressiveness in invasive breast carcinoma (BC). METHODS: We explored the impact of ePVI on different BC subtypes. In a total of 2,116 BCs, 91 ePVI-BCs, 70 inflammatory breast carcinomas (IBCs), and 114 casual BCs as a control group (CG-BC) were recruited. RESULTS: Patients affected by ePVI-BC were younger, had larger tumors, higher histologic grade, elevated Ki-67 score, Her2/neu overexpressed, and more lymph node metastases compared with CG-BC (P < .001). Interestingly, only younger mean age at diagnosis differentiated patients with ePVI-BC from patients affected by IBC. ePVI-BC showed a clinical outcome intermediate between the prognoses of IBC and CG-BC. CONCLUSIONS: Results suggest that ePVI-BC and IBC may share some pathologic processes, providing a novel perspective on the heterogeneity of BC. Epidemiologic data and molecular studies on gene expression features are needed to rationally classify these tumors into their identified subtypes.