Multilayer OMIC data in medullary thyroid carcinoma identifies the STAT3 pathway as a potential therapeutic target in RETM918T tumors

Purpose: Medullary thyroid carcinoma (MTC) is a rare disease with few genetic drivers, and the etiology specific to each known susceptibility mutation remains unknown. Exploiting multilayer genomic data, we focused our interest on the role of aberrant DNA methylation in MTC development.Experimental Design: We performed genome-wide DNA methylation profiling assessing more than 27,000 CpGs in the largest MTC series reported to date, comprising 48 molecularly characterized tumors. mRNA and miRNA expression data were available for 33 and 31 tumors, respectively. Two human MTC cell lines and 101 paraffin-embedded MTCs were used for validation.Results: The most distinctive methylome was observed for RETM918T-related tumors. Integration of methylation data with mRNA and miRNA expression data identified genes negatively regulated by promoter methylation. These in silico findings were confirmed in vitro for PLCB2, DKK4, MMP20, and miR-10a, -30a, and -200c. The mutation-specific aberrant methylation of PLCB2, DKK4, and MMP20 was validated in 25 independent MTCs by bisulfite pyrosequencing. The methylome and transcriptome data underscored JAK/Stat pathway involvement in RETM918T MTCs. Immunostaining [immunohistochemistry (IHC)] for the active form of signaling effector STAT3 was performed in a series of 101 MTCs. As expected, positive IHC was associated with RETM918T-bearing tumors (P < 0.02). Pharmacologic inhibition of STAT3 activity increased the sensitivity to vandetanib of the RETM918T-positive MTC cell line, MZ-CRC-1.Conclusions: Multilayer OMIC data analysis uncovered methylation hallmarks in genetically defined MTCs and revealed JAK/Stat signaling effector STAT3 as a potential therapeutic target for the treatment of RETM918T MTCs.This work was supported by the Fondo de Investigaciones Sanitarias (FIS) project PI14/00240 and the Comunidad de Madrid (Grant S2011/BMD-2328 TIRONET) to MR. LI-P is supported by the Centro de Investigacion Biomédica en Red de Enfermedades Raras (CIBERER). VM was supported by a predoctoral fellowship from the "la Caixa"/CNIO international PhD programme. CM-C is supported by a postdoctoral fellowship from the Fundación AECC

PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data

BACKGROUND: Large-sequencing cancer genome projects have shown that tumors have thousands of molecular alterations and their frequency is highly heterogeneous. In such scenarios, physicians and oncologists routinely face lists of cancer genomic alterations where only a minority of them are relevant biomarkers to drive clinical decision-making. For this reason, the medical community agrees on the urgent need of methodologies to establish the relevance of tumor alterations, assisting in genomic profile interpretation, and, more importantly, to prioritize those that could be clinically actionable for cancer therapy. RESULTS: We present PanDrugs, a new computational methodology to guide the selection of personalized treatments in cancer patients using the variant lists provided by genome-wide sequencing analyses. PanDrugs offers the largest database of drug-target associations available from well-known targeted therapies to preclinical drugs. Scoring data-driven gene cancer relevance and drug feasibility PanDrugs interprets genomic alterations and provides a prioritized evidence-based list of anticancer therapies. Our tool represents the first drug prescription strategy applying a rational based on pathway context, multi-gene markers impact and information provided by functional experiments. Our approach has been systematically applied to TCGA patients and successfully validated in a cancer case study with a xenograft mouse model demonstrating its utility. CONCLUSIONS: PanDrugs is a feasible method to identify potentially druggable molecular alterations and prioritize drugs to facilitate the interpretation of genomic landscape and clinical decision-making in cancer patients. Our approach expands the search of druggable genomic alterations from the concept of cancer driver genes to the druggable pathway context extending anticancer therapeutic options beyond already known cancer genes. The methodology is public and easily integratable with custom pipelines through its programmatic API or its docker image. The PanDrugs webtool is freely accessible at http://www.pandrugs.org .The authors thank Joaquín Dopazo, Patricia León, and José Carbonell for kindly providing the modelled pathways employed in PanDrugs implementation; and Michael Tress for his helpful comments and suggestions in the earlier version of the manuscript.S

Differential expression of microRNA miR-150-5p in IgA nephropathy as a potential mediator and marker of disease progression

Understanding why certain patients with IgA nephropathy progress to kidney failure while others maintain normal kidney function remains a major unanswered question. To help answer this, we performed miRNome profiling by next generation sequencing of kidney biopsies in order to identify microRNAs specifically associated with the risk of IgA nephropathy progression. Following sequencing and validation in independent cohorts, four microRNAs (-1505p,-155-5p, -146b-5p, -135a-5p) were found to be differentially expressed in IgA nephropathy progressors compared to non-progressors, and patients with thin membrane nephropathy, lupus nephritis and membranous nephropathy, and correlated with estimated glomerular filtration rate, proteinuria, and the Oxford MEST-C scores (five histological features that are independent predictors of clinical outcome). Each individual microRNA increased the discrimination score of the International IgAN Prediction Tool, although due to the small number of samples the results did not reach statistical significance. miR-150-5p exhibited the largest amplitude of expression between cohorts and displayed the best discrimination between IgA nephropathy progressors and nonprogressors by receiver operating curve analysis (AUC: 0.8). However, expression was similarly upregulated in kidneys with established fibrosis and low estimated glomerular filtration rates at the time of biopsy. Consistent with a more generic role in kidney fibrosis, in situ hybridization revealed that miR-150-5p was found in lymphoid infiltrates, and areas of proliferation and fibrosis consistent with the known drivers of progression. Thus, miR-150-5p may be a potential functional mediator of kidney fibrosis that may add value in predicting risk of progression in IgA nephropathy and other kidney diseases

Decoding myofibroblast origins in human kidney fibrosis

Data repository for the manuscript: Kuppe, Ibrahim et al. "Decoding myofibroblast origins in human kidney fibrosis", 2020. Please also consult the supplemental data in the paper, and the data availability statement in hte manuscript for raw FASTQ files for mouse data. For further data requests and questions, please contact Dr. Rafael Kramann ([email protected]) File Details: - Human in vitro PDGFRb+ RNA-seq (bulk RNA-seq data for various NKD2 knock-out and knock-in clones) * invitro_bulk_rnaseq.tar.gz: Salmon output for all samples. Please see the manuscript for further information. - UUO Mouse FACS sorted PDGFRa+/b+ ATAC-Seq * mouse_uuo_pdgfrab_atacseq.bw: BigWig Signal file for ATAC-Seq data, PDGFRa+/b+ FACS sorted cells from day 10 UUO mouse kidneys (average of two biological replicates) * mouse_uuo_pdgfrab_motifs.meme: Motifs identified based on the ATAC-Seq data and further analyzed in the paper - UUO and Sham Mouse FACS sorted PDGFRa+/b+ scRNA-seq (10x Genomics) * Mouse_PDGFRab.tar.gz: contains the count data derived by Alevin/Salmon for the cells analyzed in the paper in matrix market format (.mtx). column data include cell cluster annotations. - UUO and Sham Mouse FACS sorted PDGFRb+ scRNA-seq (SmartSeq2) * Mouse_PDGFRa.tar.gz: contains the expression data for the cells analyzed in the paper in matrix market format (.mtx). column data include cell cluster annotations. - Human FACS sorted CD10+ scRNA-seq (10x Genomics) * Human_CD10plus.tar.gz: contains the count data derived by Alevin/Salmon for the cells analyzed in the paper in matrix market format (.mtx). column data include cell cluster annotations. - Human FACS sorted CD10- scRNA-seq (10x Genomics) * Human_CD10minus.tar.gz: contains the count data derived by Alevin/Salmon for the cells analyzed in the paper in matrix market format (.mtx). column data include cell cluster annotations. - Human FACS sorted PDGFRb+ scRNA-seq (10x Genomics) * Human_PDGFRb.tar.gz: contains the count data derived by Alevin/Salmon for the cells analyzed in the paper in matrix market format (.mtx). column data include cell cluster annotations. * HumanPDGFRBpositive_Nkd2_grnboost2.csv: Gene Regulatory Network obtained by GRNboost2 on genes correlated with NKD2 in Fibroblast (Mesenchymal) cells. See manuscript for details. * Human_PDGFRBplus_TFanalysis.tar.gz: TF analysis based on single cell RNA-seq for promoter and distal regions. See manuscript for details. - github_files.tar.gz: RData Objects associated with the paper code repository (https://github.com/mahmoudibrahim/KidneyMap

Functional screen of MSI2 interactors identifies an essential role for SYNCRIP in myeloid leukemia stem cells

The identity of the RNA-binding proteins (RBPs) that govern cancer stem cells remains poorly characterized. The MSI2 RBP is a central regulator of translation of cancer stem cell programs. Through proteomic analysis of the MSI2-interacting RBP network and functional shRNA screening, we identified 24 genes required for in vivo leukemia. Syncrip was the most differentially required gene between normal and myeloid leukemia cells. SYNCRIP depletion increased apoptosis and differentiation while delaying leukemogenesis. Gene expression profiling of SYNCRIP-depleted cells demonstrated a loss of the MLL and HOXA9 leukemia stem cell program. SYNCRIP and MSI2 interact indirectly though shared mRNA targets. SYNCRIP maintains HOXA9 translation, and MSI2 or HOXA9 overexpression rescued the effects of SYNCRIP depletion. Altogether, our data identify SYNCRIP as a new RBP that controls the myeloid leukemia stem cell program. We propose that targeting these RBP complexes might provide a novel therapeutic strategy in leukemia