Modeling recursive RNA interference.

An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments

Poly(ADP-ribose) polymerase family member 14 (PARP14) is a novel effector of the JNK2-dependent pro-survival signal in multiple myeloma

Copyright @ 2013 Macmillan Publishers Limited. This is the author's accepted manuscript. The final published article is available from the link below.Regulation of cell survival is a key part of the pathogenesis of multiple myeloma (MM). Jun N-terminal kinase (JNK) signaling has been implicated in MM pathogenesis, but its function is unclear. To elucidate the role of JNK in MM, we evaluated the specific functions of the two major JNK proteins, JNK1 and JNK2. We show here that JNK2 is constitutively activated in a panel of MM cell lines and primary tumors. Using loss-of-function studies, we demonstrate that JNK2 is required for the survival of myeloma cells and constitutively suppresses JNK1-mediated apoptosis by affecting expression of poly(ADP-ribose) polymerase (PARP)14, a key regulator of B-cell survival. Strikingly, we found that PARP14 is highly expressed in myeloma plasma cells and associated with disease progression and poor survival. Overexpression of PARP14 completely rescued myeloma cells from apoptosis induced by JNK2 knockdown, indicating that PARP14 is critically involved in JNK2-dependent survival. Mechanistically, PARP14 was found to promote the survival of myeloma cells by binding and inhibiting JNK1. Moreover, inhibition of PARP14 enhances the sensitization of MM cells to anti-myeloma agents. Our findings reveal a novel regulatory pathway in myeloma cells through which JNK2 signals cell survival via PARP14, and identify PARP14 as a potential therapeutic target in myeloma.Kay Kendall Leukemia Fund, NIH, Cancer Research UK, Italian Association for Cancer Research and the Foundation for Liver Research

Design of small molecule-responsive microRNAs based on structural requirements for Drosha processing

MicroRNAs (miRNAs) are prevalent regulatory RNAs that mediate gene silencing and play key roles in diverse cellular processes. While synthetic RNA-based regulatory systems that integrate regulatory and sensing functions have been demonstrated, the lack of detail on miRNA structure–function relationships has limited the development of integrated control systems based on miRNA silencing. Using an elucidated relationship between Drosha processing and the single-stranded nature of the miRNA basal segments, we developed a strategy for designing ligand-responsive miRNAs. We demonstrate that ligand binding to an aptamer integrated into the miRNA basal segments inhibits Drosha processing, resulting in titratable control over gene silencing. The generality of this control strategy was shown for three aptamer–small molecule ligand pairs. The platform can be extended to the design of synthetic miRNAs clusters, cis-acting miRNAs and self-targeting miRNAs that act both in cis and trans, enabling fine-tuning of the regulatory strength and dynamics. The ability of our ligand-responsive miRNA platform to respond to user-defined inputs, undergo regulatory performance tuning and display scalable combinatorial control schemes will help advance applications in biological research and applied medicine

Regulation of Human Bone Marrow Stromal Cell Proliferation and Differentiation Capacity by Glucocorticoid Receptor and AP-1 Crosstalk

Although marrow adipocytes and osteoblasts derive from a common bone marrow stromal cells (BMSCs), the mechanisms that underlie osteoporosis-associated bone loss and marrow adipogenesis during prolonged steroid treatment are unclear. We show in human BMSCs (hBMSCs) that glucocorticoid receptor (GR) signaling in response to high concentrations of glucocorticoid (GC) supports adipogenesis but inhibits osteogenesis by reducing c-Jun expression and hBMSC proliferation. Conversely, significantly lower concentrations of GC, which permit hBMSC proliferation, are necessary for normal bone mineralization. In contrast, platelet-derived growth factor (PDGF) signaling increases both JNK/c-Jun activity and hBMSC expansion, favoring osteogenic differentiation instead of adipogenesis. Indeed, PDGF antagonizes the proadipogenic qualities of GC/GR signaling. Thus our results reveal a novel c-Jun-centered regulatory network of signaling pathways in differentiating hBMSCs that controls the proliferation-dependent balance between osteogenesis and adipogenesis

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

PARP14 promotes the warburg effect in hepatocellular carcinoma by inhibiting JNK1-dependent PKM2 phosphorylation and activation

Most tumour cells use aerobic glycolysis (the Warburg effect) to support anabolic growth and evade apoptosis. Intriguingly, the molecular mechanisms that link the Warburg effect with the suppression of apoptosis are not well understood. In this study, using loss-of-function studies in vitro and in vivo, we show that the anti-apoptotic protein poly(ADP-ribose) polymerase (PARP)14 promotes aerobic glycolysis in human hepatocellular carcinoma (HCC) by maintaining low activity of the pyruvate kinase M2 isoform (PKM2), a key regulator of the Warburg effect. Notably, PARP14 is highly expressed in HCC primary tumours and associated with poor patient prognosis. Mechanistically, PARP14 inhibits the pro-apoptotic kinase JNK1, which results in the activation of PKM2 through phosphorylation of Thr365. Moreover, targeting PARP14 enhances the sensitization of HCC cells to anti-HCC agents. Our findings indicate that the PARP14-JNK1-PKM2 regulatory axis is an important determinant for the Warburg effect in tumour cells and provide a mechanistic link between apoptosis and metabolism