gViz, a novel tool for the visualization of co-expression networks

<p>Abstract</p> <p>Background</p> <p>The quantity of microarray data available on the Internet has grown dramatically over the past years and now represents millions of Euros worth of underused information. One way to use this data is through co-expression analysis. To avoid a certain amount of bias, such data must often be analyzed at the genome scale, for example by network representation. The identification of co-expression networks is an important means to unravel gene to gene interactions and the underlying functional relationship between them. However, it is very difficult to explore and analyze a network of such dimensions. Several programs (Cytoscape, yEd) have already been developed for network analysis; however, to our knowledge, there are no available GraphML compatible programs.</p> <p>Findings</p> <p>We designed and developed gViz, a GraphML network visualization and exploration tool. gViz is built on clustering coefficient-based algorithms and is a novel tool to visualize and manipulate networks of co-expression interactions among a selection of probesets (each representing a single gene or transcript), based on a set of microarray co-expression data stored as an adjacency matrix.</p> <p>Conclusions</p> <p>We present here gViz, a software tool designed to visualize and explore large GraphML networks, combining network theory, biological annotation data, microarray data analysis and advanced graphical features.</p

PathEx: a novel multi factors based datasets selector web tool

<p>Abstract</p> <p>Background</p> <p>Microarray experiments have become very popular in life science research. However, if such experiments are only considered independently, the possibilities for analysis and interpretation of many life science phenomena are reduced. The accumulation of publicly available data provides biomedical researchers with a valuable opportunity to either discover new phenomena or improve the interpretation and validation of other phenomena that partially understood or well known. This can only be achieved by intelligently exploiting this rich mine of information.</p> <p>Description</p> <p>Considering that technologies like microarrays remain prohibitively expensive for researchers with limited means to order their own experimental chips, it would be beneficial to re-use previously published microarray data. For certain researchers interested in finding gene groups (requiring many replicates), there is a great need for tools to help them to select appropriate datasets for analysis. These tools may be effective, if and only if, they are able to re-use previously deposited experiments or to create new experiments not initially envisioned by the depositors. However, the generation of new experiments requires that all published microarray data be completely annotated, which is not currently the case. Thus, we propose the PathEx approach.</p> <p>Conclusion</p> <p>This paper presents PathEx, a human-focused web solution built around a two-component system: one database component, enriched with relevant biological information (expression array, omics data, literature) from different sources, and another component comprising sophisticated web interfaces that allow users to perform complex dataset building queries on the contents integrated into the PathEx database.</p

Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma

SummaryWe describe a comprehensive genomic characterization of adrenocortical carcinoma (ACC). Using this dataset, we expand the catalogue of known ACC driver genes to include PRKAR1A, RPL22, TERF2, CCNE1, and NF1. Genome wide DNA copy-number analysis revealed frequent occurrence of massive DNA loss followed by whole-genome doubling (WGD), which was associated with aggressive clinical course, suggesting WGD is a hallmark of disease progression. Corroborating this hypothesis were increased TERT expression, decreased telomere length, and activation of cell-cycle programs. Integrated subtype analysis identified three ACC subtypes with distinct clinical outcome and molecular alterations which could be captured by a 68-CpG probe DNA-methylation signature, proposing a strategy for clinical stratification of patients based on molecular markers

Phase 2 study of pembrolizumab in patients with advanced rare cancers

Background Patients with advanced rare cancers have poor prognosis and few treatment options. As immunotherapy is effective across multiple cancer types, we aimed to assess pembrolizumab (programmed cell death 1 (PD-1) inhibitor) in patients with advanced rare cancers. Methods In this open-label, phase 2 trial, patients with advanced rare cancers whose tumors had progressed on standard therapies, if available, within the previous 6 months were enrolled in nine tumor-specific cohorts and a 10th cohort for other rare histologies. Pembrolizumab 200 mg was administered intravenously every 21 days. The primary endpoint was non-progression rate (NPR) at 27 weeks; secondary endpoints were safety and tolerability, objective response rate (ORR), and clinical benefit rate (CBR). Results A total of 127 patients treated between August 15, 2016 and July 27, 2018 were included in this analysis. At the time of data cut-off, the NPR at 27 weeks was 28% (95% CI, 19% to 37%). A confirmed objective response (OR) was seen in 15 of 110 (14%) evaluable patients (complete response in one and partial response in 14). CBR, defined as the percentage of patients with an OR or stable disease ≥4 months, was 38% (n=42). Treatment was ongoing in 11 of 15 patients with OR at last follow-up. In the cohort with squamous cell carcinoma (SCC) of the skin, the NPR at 27 weeks was 36%, ORR 31%, and CBR 38%. In patients with adrenocortical carcinoma (ACC), NPR at 27 weeks was 31%, ORR 15%, and CBR 54%. In the patients with carcinoma of unknown primary (CUP), NPR at 27 weeks was 33%, ORR 23%, and CBR 54%. In the paraganglioma–pheochromocytoma cohort, NPR at 27 weeks was 43%, ORR 0%, and CBR 75%. Treatment-related adverse events (TRAEs) occurred in 66 of 127 (52%) patients, and 12 (9%) had grade ≥3 TRAEs. The most common TRAEs were fatigue (n=25) and rash (n=17). There were six deaths, all of which were unrelated to the study drug. Conclusions The favorable toxicity profile and antitumor activity seen in patients with SCC of skin, ACC, CUP, and paraganglioma–pheochromocytoma supports further evaluation of pembrolizumab in this patient population. Trial registration number NCT0272173