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

ISOLATION AND MOLECULAR IDENTIFICATION OF POTENTIALLY PATHOGENIC Escherichia coli AND Campylobacter jejuni IN FERAL PIGEONS FROM AN URBAN AREA IN THE CITY OF LIMA, PERU

SUMMARY Feral pigeons (Columbia livia) live in close contact with humans and other animals. They can transmit potentially pathogenic and zoonotic agents. The objective of this study was to isolate and detect strains of diarrheagenic Escherichia coli and Campylobacter jejuniof urban feral pigeons from an area of Lima, Peru. Fresh dropping samples from urban parks were collected for microbiological isolation of E. coli strains in selective agar, and Campylobacterby filtration method. Molecular identification of diarrheagenic pathotypes of E.coliand Campylobacter jejuni was performed by PCR. Twenty-two parks were sampled and 16 colonies of Campylobacter spp. were isolated. The 100% of isolates were identified as Campylobacter jejuni. Furthermore, 102 colonies of E. coli were isolated and the 5.88% resulted as Enteropathogenic (EPEC) type and 0.98% as Shiga toxin-producing E. coli (STEC). The urban feral pigeons of Lima in Peru can act as a reservoir or carriers of zoonotic potentially pathogenic enteric agents

Partial Inhibition of the 6-Phosphofructo-2-Kinase/Fructose-2,6-Bisphosphatase-3 (PFKFB3) Enzyme in Myeloid Cells Does Not Affect Atherosclerosis

Background: The protein 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase-3 (PFKFB3) is a key stimulator of glycolytic flux. Systemic, partial PFKFB3 inhibition previously decreased total plaque burden and increased plaque stability. However, it is unclear which cell type conferred these positive effects. Myeloid cells play an important role in atherogenesis, and mainly rely on glycolysis for energy supply. Thus, we studied whether myeloid inhibition of PFKFB3-mediated glycolysis in Ldlr(-/-)LysMCre(+/-)Pfkfb3(fl/fl) (Pfkfb3(fl/fl)) mice confers beneficial effects on plaque stability and alleviates cardiovascular disease burden compared to Ldlr(-/-)LysMCre(+/-)Pfkfb3(wt/wt) control mice (Pfkfb3(wt/wt)).Methods and Results: Analysis of atherosclerotic human and murine single -cell populations confirmed PFKFB3/Pfkfb3 expression in myeloid cells, but also in lymphocytes, endothelial cells, fibroblasts and smooth muscle cells. Pfkfb3(wt/wt) and Pfkfb3(fl/fl) mice were fed a 0.25% cholesterol diet for 12 weeks. Pfkfb3(fl/fl) bone marrow-derived macrophages (BMDMs) showed 50% knockdown of Pfkfb3 mRNA. As expected based on partial glycolysis inhibition, extracellular acidification rate as a measure of glycolysis was partially reduced in Pfkfb3(fl/fl) compared to Pfkfb3(wt/wt) BMDMs. Unexpectedly, plaque and necrotic core size, as well as macrophage (MAC3), neutrophil (Ly6G) and collagen (Sirius Red) content were unchanged in advanced Pfkfb3(fl/fl) lesions. Similarly, early lesion plaque and necrotic core size and total plaque burden were unaffected.Conclusion: Partial myeloid knockdown of PFKFB3 did not affect atherosclerosis development in advanced or early lesions. Previously reported positive effects of systemic, partial PFKFB3 inhibition on lesion stabilization, do not seem conferred by monocytes, macrophages or neutrophils. Instead, other Pfkfb3-expressing cells in atherosclerosis might be responsible, such as DCs, smooth muscle cells or fibroblasts

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

Kidney fibrosis is the hallmark of chronic kidney disease progression; however, at present no antifibrotic therapies exist1–3. The origin, functional heterogeneity and regulation of scar-forming cells that occur during human kidney fibrosis remain poorly understood1,2,4. Here, using single-cell RNA sequencing, we profiled the transcriptomes of cells from the proximal and non-proximal tubules of healthy and fibrotic human kidneys to map the entire human kidney. This analysis enabled us to map all matrix-producing cells at high resolution, and to identify distinct subpopulations of pericytes and fibroblasts as the main cellular sources of scar-forming myofibroblasts during human kidney fibrosis. We used genetic fate-tracing, time-course single-cell RNA sequencing and ATAC–seq (assay for transposase-accessible chromatin using sequencing) experiments in mice, and spatial transcriptomics in human kidney fibrosis, to shed light on the cellular origins and differentiation of human kidney myofibroblasts and their precursors at high resolution. Finally, we used this strategy to detect potential therapeutic targets, and identified NKD2 as a myofibroblast-specific target in human kidney fibrosis

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