Selecting biomedical data sources according to user preferences

Motivation: Biologists are now faced with the problem of integrating information from multiple heterogeneous public sources with their own experimental data contained in individual sources. The selection of the sources to be considered is thus critically important. Results: Our aim is to support biologists by developing a module based on an algorithm that presents a selection of sources relevant to their query and matched to their own preferences. We approached this task by investigating the characteristics of biomedical data and introducing several preference criteria useful for bioinformaticians. This work was carried out in the framework of a project which aims to develop an integrative platform for the multiple parametric analysis of cancer. We illustrate our study through an elementary biomedical query occurring in a CGH analysis scenario

Identification of a Proliferation Gene Cluster Associated with HPV E6/E7 Expression Level and Viral DNA Load in Invasive Cervical Carcinoma

Specific HPV DNA sequences are associated with more than 90% of invasive carcinomas of the uterine cervix. Viral E6 and E7 oncogenes are key mediators in cell transformation by disrupting TP53 and RB pathways. To investigate molecular mechanisms involved in the progression of invasive cervical carcinoma, we performed a gene expression study on cases selected according to viral and clinical parameters. Using Coupled Two-Way Clustering and Sorting Points Into Neighbourhoods methods, we identified a Cervical Cancer Proliferation Cluster composed of 163 highly correlated transcripts, many of which corresponded to E2F pathway genes controlling cell proliferation, whereas no primary TP53 targets were present in this cluster. The average expression level of the genes of this cluster was higher in tumours with an early relapse than in tumours with a favourable course (P=0.026). Moreover, we found that E6/E7 mRNA expression level was positively correlated with the expression level of the cluster genes and with viral DNA load. These findings suggest that HPV E6/E7 expression level plays a key role in the progression of invasive carcinoma of the uterine cervix via the deregulation of cellular genes controlling tumour cell proliferation. HPV expression level may thus correspond to a biological marker useful for prognosis assessment and specific therapy of the disease

A Small Molecule That Binds and Inhibits the ETV1 Transcription Factor Oncoprotein

Members of the ETS transcription factor family have been implicated in several cancers, where they are often dysregulated by genomic derangement. ETS variant 1 (ETV1) is an ETS factor gene that undergoes chromosomal translocation in prostate cancers and Ewing sarcomas, amplification in melanomas, and lineage dysregulation in gastrointestinal stromal tumors. Pharmacologic perturbation of ETV1 would be appealing in these cancers; however, oncogenic transcription factors are often deemed “undruggable” by conventional methods. Here, we used small-molecule microarray screens to identify and characterize drug-like compounds that modulate the biologic function of ETV1. We identified the 1,3,5-triazine small molecule BRD32048 as a top candidate ETV1 perturbagen. BRD32048 binds ETV1 directly, modulating both ETV1-mediated transcriptional activity and invasion of ETV1-driven cancer cells. Moreover, BRD32048 inhibits p300-dependent acetylation of ETV1, thereby promoting its degradation. These results point to a new avenue for pharmacologic ETV1 inhibition and may inform a general means to discover small molecule perturbagens of transcription factor oncoproteins.National Cancer Institute (U.S.) (Initiative for Chemical Genetics Contract N01-CO-12400)National Cancer Institute (U.S.) (Cancer Target Discovery and Development Network RC2 CA148399

A Small Molecule that Binds and Inhibits the ETV1 Transcription Factor Oncoprotein

Members of the ETS transcription factor family have been implicated in several cancers, where they are often dysregulated by genomic derangement. ETS variant 1 (ETV1) is an ETS factor gene that undergoes chromosomal translocation in prostate cancers and Ewing\u27s sarcomas, amplification in melanomas, and lineage dysregulation in gastrointestinal stromal tumors. Pharmacologic perturbation of ETV1 would be appealing in these cancers; however, oncogenic transcription factors are often deemed “undruggable” by conventional methods. Here, we used small-molecule microarray (SMM) screens to identify and characterize drug-like compounds that modulate the biological function of ETV1. We identified the 1,3,5-triazine small molecule BRD32048 as a top candidate ETV1 perturbagen. BRD32048 binds ETV1 directly, modulating both ETV1-mediated transcriptional activity and invasion of ETV1-driven cancer cells. Moreover, BRD32048 inhibits p300-dependent acetylation of ETV1, thereby promoting its degradation. These results point to a new avenue for pharmacological ETV1 inhibition and may inform a general means to discover small molecule perturbagens of transcription factor oncoproteins

Nuclear Factor I/B is an Oncogene in Small Cell Lung Cancer

Small cell lung cancer (SCLC) is an aggressive cancer often diagnosed after it has metastasized. Despite the need to better understand this disease, SCLC remains poorly characterized at the molecular and genomic levels. Using a genetically engineered mouse model of SCLC driven by conditional deletion of Trp53 and Rb1 in the lung, we identified several frequent, high-magnitude focal DNA copy number alterations in SCLC. We uncovered amplification of a novel, oncogenic transcription factor, Nuclear factor I/B (Nfib), in the mouse SCLC model and in human SCLC. Functional studies indicate that NFIB regulates cell viability and proliferation during transformation.National Cancer Institute (U.S.) (grant P30-CA14051)David H. Koch Institute for Integrative Cancer Research at MIT (Ludwig Center for Molecular Oncology)Howard Hughes Medical InstituteAlfred P. Sloan Foundation (Research Fellowship)International Association for the Study of Lung Cance

A Novel Epigenetic Phenotype Associated With the Most Aggressive Pathway of Bladder Tumor Progression

International audienceBackground: Epigenetic silencing can extend to whole chromosomal regions in cancer. There have been few genome-wide studies exploring its involvement in tumorigenesis.Methods: We searched for chromosomal regions affected by epigenetic silencing in cancer by using Affymetrix microarrays and real-time quantitative polymerase chain reaction to analyze RNA from 57 bladder tumors compared with normal urothelium. Epigenetic silencing was verified by gene re-expression following treatment of bladder cell lines with 5-aza-deoxycytidine, a DNA demethylating agent, and trichostatin A, a histone deacetylase inhibitor. DNA methylation was studied by bisulfite sequencing and histone methylation and acetylation by chromatin immunoprecipitation. Clustering was used to distinguish tumors with multiple regional epigenetic silencing (MRES) from those without and to analyze the association of this phenotype with histopathologic and molecular types of bladder cancer. The results were confirmed with a second panel of 40 tumor samples and extended in vitro with seven bladder cancer cell lines. All statistical tests were two-sided.Results: We identified seven chromosomal regions of contiguous genes that were silenced by an epigenetic mechanism. Epigenetic silencing was not associated with DNA methylation but was associated with histone H3K9 and H3K27 methylation and histone H3K9 hypoacetylation. All seven regions were concordantly silenced in a subgroup of 26 tumors, defining an MRES phenotype. MRES tumors exhibited a carcinoma in situ-associated gene expression signature (25 of 26 MRES tumors vs 0 of 31 non-MRES tumors, P < 10⁻¹⁴), rarely carried FGFR3 mutations (one of 26 vs 22 of 31 non-MRES tumors, P < 10⁻¹⁶), and contained 25 of 33 (76%) of the muscle-invasive tumors. Cell lines derived from aggressive bladder tumors presented epigenetic silencing of the same regions.Conclusions: We have identified an MRES phenotype characterized by the concomitant epigenetic silencing of several chromosomal regions, which, in bladder cancer, is specifically associated with the carcinoma in situ gene expression signature

STAR-Fusion: Fast and Accurate Fusion Transcript Detection from RNA-Seq

Motivation Fusion genes created by genomic rearrangements can be potent drivers of tumorigenesis. However, accurate identification of functionally fusion genes from genomic sequencing requires whole genome sequencing, since exonic sequencing alone is often insufficient. Transcriptome sequencing provides a direct, highly effective alternative for capturing molecular evidence of expressed fusions in the precision medicine pipeline, but current methods tend to be inefficient or insufficiently accurate, lacking in sensitivity or predicting large numbers of false positives. Here, we describe STAR-Fusion, a method that is both fast and accurate in identifying fusion transcripts from RNA-Seq data. Results We benchmarked STAR-Fusion’s fusion detection accuracy using both simulated and genuine Illumina paired-end RNA-Seq data, and show that it has superior performance compared to popular alternative fusion detection methods. Availability and implementation STAR-Fusion is implemented in Perl, freely available as open source software at http://star-fusion.github.io, and supported on Linux

Functional genomics reveals serine synthesis is essential in PHGDH-amplified breast cancer

Cancer cells adapt their metabolic processes to drive macromolecular biosynthesis for rapid cell growth and proliferation[superscript 1, 2]. RNA interference (RNAi)-based loss-of-function screening has proven powerful for the identification of new and interesting cancer targets, and recent studies have used this technology in vivo to identify novel tumour suppressor genes[superscript 3]. Here we developed a method for identifying novel cancer targets via negative-selection RNAi screening using a human breast cancer xenograft model at an orthotopic site in the mouse. Using this method, we screened a set of metabolic genes associated with aggressive breast cancer and stemness to identify those required for in vivo tumorigenesis. Among the genes identified, phosphoglycerate dehydrogenase (PHGDH) is in a genomic region of recurrent copy number gain in breast cancer and PHGDH protein levels are elevated in 70% of oestrogen receptor (ER)-negative breast cancers. PHGDH catalyses the first step in the serine biosynthesis pathway, and breast cancer cells with high PHGDH expression have increased serine synthesis flux. Suppression of PHGDH in cell lines with elevated PHGDH expression, but not in those without, causes a strong decrease in cell proliferation and a reduction in serine synthesis. We find that PHGDH suppression does not affect intracellular serine levels, but causes a drop in the levels of α-ketoglutarate, another output of the pathway and a tricarboxylic acid (TCA) cycle intermediate. In cells with high PHGDH expression, the serine synthesis pathway contributes approximately 50% of the total anaplerotic flux of glutamine into the TCA cycle. These results reveal that certain breast cancers are dependent upon increased serine pathway flux caused by PHGDH overexpression and demonstrate the utility of in vivo negative-selection RNAi screens for finding potential anticancer targets.Susan G. Komen Breast Cancer Foundation (Fellowship)Life Sciences Research Foundation (Fellowship)W. M. Keck FoundationDavid H. Koch Cancer Research FundAlexander and Margaret Stewart TrustNational Institutes of Health (U.S.) (Grant CA103866