Proton Pump Inhibitor Use and Efficacy of Nivolumab and Ipilimumab in Advanced Melanoma

The impact of proton pump inhibitors (PPIs) on clinical outcomes with first-line immune checkpoint inhibitors (ICIs) in patients with metastatic melanoma was previously analyzed in the phase II study, CheckMate 069. This retrospective analysis utilized data from three phase II/III studies of first-line ICI therapy in untreated advanced melanoma: CheckMate 066, 067, and 069. All randomized patients with PPI use ≤ 30 days before initiating study treatment were included in the PPI-use subgroup. Possible associations between baseline PPI use and efficacy were evaluated within each treatment arm of each study using multivariable modeling. Approximately 20% of 1505 randomized patients across the studies reported baseline PPI use. The median follow-up was 52.6–58.5 months. Objective response rate (ORR), progression-free survival (PFS), and overall survival analyses provided insufficient evidence of a meaningful association between PPI use and efficacy outcomes with nivolumab-plus-ipilimumab, nivolumab, or ipilimumab therapy. In five of the six ICI treatment arms, 95% confidence intervals for odds ratios or hazard ratios traversed 1. Significant associations were observed in the CheckMate 069 combination arm between PPI use and poorer ORR and PFS. This multivariable analysis found insufficient evidence to support meaningful associations between PPI use and ICI efficacy in patients with advanced melanoma

The consensus molecular subtypes of colorectal cancer

Colorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression-based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMSs) with distinguishing features: CMS1 (microsatellite instability immune, 14%), hypermutated, microsatellite unstable and strong immune activation; CMS2 (canonical, 37%), epithelial, marked WNT and MYC signaling activation; CMS3 (metabolic, 13%), epithelial and evident metabolic dysregulation; and CMS4 (mesenchymal, 23%), prominent transforming growth factor-beta activation, stromal invasion and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intratumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC-with clear biological interpretability-and the basis for future clinical stratification and subtype-based targeted interventions

The Consensus Molecular Subtypes of Colorectal Cancer

Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use -- https://www.nature.com/authors/policies/license.html#termsColorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression-based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMS) with distinguishing features: CMS1 (MSI Immune, 14%), hypermutated, microsatellite unstable, strong immune activation; CMS2 (Canonical, 37%), epithelial, chromosomally unstable, marked WNT and MYC signaling activation; CMS3 (Metabolic, 13%), epithelial, evident metabolic dysregulation; and CMS4 (Mesenchymal, 23%), prominent transforming growth factor β activation, stromal invasion, and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intra-tumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC - with clear biological interpretability - and the basis for future clinical stratification and subtype-based targeted interventions

The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article