No abstract

Summary By analyzing gene expression data in gliobastoma in combination with matched microRNA profiles, we have uncovered a post-transcriptional regulation layer of surprising magnitude, comprising over 248,000 microRNA (miR)-mediated interactions. These include ~7,000 genes whose transcripts act as miR ‘sponges’ and 148 genes that act through alternative, non-sponge interactions. Biochemical analyses in cell lines confirmed that this network regulates established drivers of tumor initiation and subtype, including PTEN, PDGFRA, RB1, VEGFA, STAT3, and RUNX1, suggesting that these interactions mediate crosstalk between canonical oncogenic pathways. RNA silencing of 13 microRNA-mediated PTEN regulators, whose locus deletions are predictive of PTEN expression variability, was sufficient to downregulate PTEN in a 3′ UTR-dependent manner and to increase tumor-cell growth rates. Thus, this miR-mediated network provides a mechanistic, experimentally validated rationale for the loss of PTEN expression in a large number of glioma samples with an intact PTEN locus.

Efforts to identify and annotate cancer driver genetic lesions have been almost exclusively focused on the analysis of protein coding genes. Here we identify a new long-range acting MYC enhancer controlled by NOTCH1, targeted by recurrent chromosomal duplications in human T-cell acute lymphoblastic leukemia (T-ALL). This highly conserved regulatory element, hereby named N-Me for NOTCH MYC enhancer, is located within a broad super-enhancer region +1.47 Mb from the MYC transcription initiating site, interacts with the MYC proximal promoter and induces orientation-independent MYC expression in reporter assays. Moreover, analysis of N-Me knockout mice demonstrates a selective and essential role of this regulatory element during thymocyte development and in NOTCH1-induced T-ALL. Altogether, these results identify N-Me as a long range oncogenic enhancer directly implicated in the pathogenesis of human leukemia and highlight the fundamental importance of the NOTCH1-MYC regulatory axis in T-cell transformation and as therapeutic target in T-ALL.

The mammary gland is a very dynamic organ that undergoes continuous remodeling. The critical regulators of this process are not fully understood. Here we identify the microRNA cluster miR-424(322)/503 as an important regulator of epithelial involution after pregnancy. Through the generation of a knockout mouse model, we found that regression of the secretory acini of the mammary gland was compromised in the absence of miR-424(322)/503. Mechanistically, we show that miR-424(322)/503 orchestrates cell life and death decisions by targeting BCL-2 and IGF1R (insulin growth factor-1 receptor). Furthermore, we demonstrate that the expression of this microRNA cluster is regulated by TGF-b, a well-characterized regulator of mammary involution. Overall, our data suggest a model in which activation of the TGF-b pathway after weaning induces the transcription of miR-424(322)/503, which in turn down-regulates the expression of key genes. Here, we unveil a previously unknown, multilayered regulation of epithelial tissue remodeling coordinated by the microRNA cluster miR-424(322)/503.

We introduce a method for simultaneous prediction of microRNA–target interactions and their mediated competitive endogenous RNA (ceRNA) interactions. Using high-throughput validation assays in breast cancer cell lines, we show that our integrative approach significantly improves on microRNA–target prediction accuracy as assessed by both mRNA and protein level measurements. Our biochemical assays support nearly 500 microRNA–target interactions with evidence for regulation in breast cancer tumors. Moreover, these assays constitute the most extensive validation platform for computationally inferred networks of microRNA–target interactions in breast cancer tumors, providing a useful benchmark to ascertain future improvements.

HER2-positive (HER2 + ) breast adenocarcinomas are a heterogeneous group in which hormone receptor (HR) status influences therapeutic decisions and patient outcome. By combining genome-wide RNAi screens with regulatory network analysis, we identified STAT3 as a critically activated master regulator of HR − /HER2 + tumors, eliciting tumor dependency in these cells. Mechanistically, HR − /HER2 + cells secrete high levels of the interleukin-6 (IL-6) cytokine, inducing the activation of STAT3, which in turn promotes a second autocrine stimulus to increase S100A8/9 complex (calprotectin) production and secretion. Increased calprotectin levels activate signaling pathways involved in proliferation and resistance. Importantly, we demonstrated that inhibition of the IL-6-Janus kinase 2 (JAK2)-STAT3-calprotectin axis with FDA-approved drugs, alone and in combination with HER2 inhibitors, reduced the tumorigenicity of HR − /HER2 + breast cancers, opening novel targeted therapeutic opportunities.

Autophagy is a highly conserved catabolic process and a major cellular pathway for the degradation of long-lived proteins and cytoplasmic organelles. An increasing body of evidence has unveiled autophagy as an indispensable biological function that helps to maintain normal tissue homeostasis and metabolic fitness that can also lead to severe consequences for the normal cellular functioning when altered. Recent accumulating data point to autophagy as a key player in a wide variety of physiological and pathophysiological conditions in the human endometrium, one of the most proficient self-regenerating tissues in the human body and an instrumental player in placental species reproductive function. The current review highlights the most recent findings regarding the process of autophagy in the normal and cancerous endometrial tissue. Current research efforts aiming to therapeutically exploit autophagy and the methodological approaches used are discussed. Abbreviations: 3-MA: 3-methyladenine; ACACA (acetyl-CoA carboxylase alpha); AICAR: 5-aminoimidazole-4-carboximide riboside; AKT: AKT serine/threonine kinase; AMPK: AMP-activated protein kinase; ATG: autophagy related; ATG12: autophagy related 12; ATG16L1: autophagy related 16 like 1; ATG3: autophagy related 3; ATG4C: autophagy related 4C cysteine peptidase; ATG5: autophagy related 5; ATG7: autophagy related 7; ATG9: autophagy related 9; Baf A1: bafilomycin A 1 ; BAX: BCL2 associated X, apoptosis regulator; BCL2: BCL2 apoptosis regulator; BECN1: beclin 1; CACNA1D: calcium voltage-gated channel subunit alpha1 D; CASP3: caspase 3; CASP7: caspase 7; CASP8: caspase 8; CASP9: caspase 9; CD44: CD44 molecule (Indian blood group); CDH1: cadherin 1; CDKN1A: cyclin dependent kinase inhibitor 1A; CDKN2A: cyclin dependent kinase inhibitor 2A; CMA: chaperone-mediated autophagy; CQ: chloroquine; CTNNB1: catenin beta 1; DDIT3: DNA damage inducible transcript 3; EC: endometrial cancer; EGFR: epidermal growth factor receptor; EH: endometrial hyperplasia; EIF4E: eukaryotic translation initiation factor 4E; EPHB2/ERK: EPH receptor B2; ER: endoplasmic reticulum; ERBB2: er-b2 receptor tyrosine kinase 2; ERVW-1: endogenous retrovirus group W member 1, envelope; ESR1: estrogen receptor 1; FSH: follicle-stimulating hormone; GCG/GLP1: glucagon; GFP: green fluorescent protein; GIP: gastric inhibitory polypeptide; GLP1R: glucagon-like peptide-1 receptor; GLS: glutaminase; H2AX: H2A.X variant histone; HIF1A: hypoxia inducible factor 1 alpha; HMGB1: high mobility group box 1; HOTAIR: HOX transcript antisense RNA; HSPA5: heat shock protein family A (HSP70) member 5; HSPA8: heat shock protein family A (HSP70) member 8; IGF1: insulin like growth factor 1; IL27: interleukin 27; INS: insulin; ISL: isoliquiritigenin; KRAS: KRAS proto-oncogene, GTPase; LAMP2: lysosomal-associated membrane protein 2; lncRNA: long-non-coding RNA; MAP1LC3A/LC3A: microtubule associated protein 1 light chain 3 alpha; MAP1LC3B/LC3B: microtubule associate...

Identifying driver genes in cancer remains a crucial bottleneck in therapeutic development and basic understanding of the disease. We developed Helios, a novel algorithm that integrates genomic data from primary tumors with data from functional RNAi screens to pinpoint driver genes within large recurrently amplified regions of DNA. Applying Helios to breast cancer data identified a set of candidate drivers highly enriched with known drivers (p-value < e−14). 9/10 top scoring Helios genes are known drivers of breast cancer and in vitro validation of 12 novel candidates predicted by Helios found 10 conferred enhanced anchorage independent growth, demonstrating Helios’s exquisite sensitivity and specificity. We extensively characterized RSF-1, a driver identified by Helios whose amplification correlates with poor prognosis, and found increased tumorigenesis and metastasis in mouse models. We have demonstrated a powerful approach for identifying novel driver genes and how it can yield important insights into cancer.