Amos Kirilovsky

Bio: Amos Kirilovsky is an academic researcher from Pierre-and-Marie-Curie University. The author has contributed to research in topics: Cancer & Colorectal cancer. The author has an hindex of 14, co-authored 20 publications receiving 16344 citations. Previous affiliations of Amos Kirilovsky include Paris Descartes University & French Institute of Health and Medical Research.

Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome

Abstract: The role of the adaptive immune response in controlling the growth and recurrence of human tumors has been controversial. We characterized the tumor-infiltrating immune cells in large cohorts of human colorectal cancers by gene expression profiling and in situ immunohistochemical staining. Collectively, the immunological data (the type, density, and location of immune cells within the tumor samples) were found to be a better predictor of patient survival than the histopathological methods currently used to stage colorectal cancer. The results were validated in two additional patient populations. These data support the hypothesis that the adaptive immune response influences the behavior of human tumors. In situ analysis of tumor-infiltrating immune cells may therefore be a valuable prognostic tool in the treatment of colorectal cancer and possibly other malignancies.

ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks

Abstract: We have developed ClueGO, an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes. ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta pathways and creates a functionally organized GO/pathway term network. It can analyze one or compare two lists of genes and comprehensively visualizes functionally grouped terms. A one-click update option allows ClueGO to automatically download the most recent GO/KEGG release at any time. ClueGO provides an intuitive representation of the analysis results and can be optionally used in conjunction with the GOlorize plug-in.

Effector Memory T Cells, Early Metastasis, and Survival in Colorectal Cancer

Abstract: Background The role of tumor-infiltrating immune cells in the early metastatic invasion of colorectal cancer is unknown. Methods We studied pathological signs of early metastatic invasion (venous emboli and lymphatic and perineural invasion) in 959 specimens of resected colorectal cancer. The local immune response within the tumor was studied by flow cytometry (39 tumors), low-density-array real-time polymerase-chain-reaction assay (75 tumors), and tissue microarrays (415 tumors). Results Univariate analysis showed significant differences in disease-free and overall survival according to the presence or absence of histologic signs of early metastatic invasion (P<0.001). Multivariate Cox analysis showed that an early conventional pathological tumor–node–metastasis stage (P<0.001) and the absence of early metastatic invasion (P=0.04) were independently associated with increased survival. As compared with tumors with signs of early metastatic invasion, tumors without such signs had increased infiltrates of i...

clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters

Abstract: Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters The analysis module and visualization module were combined into a reusable workflow Currently, clusterProfiler supports three species, including humans, mice, and yeast Methods provided in this package can be easily extended to other species and ontologies The clusterProfiler package is released under Artistic-20 License within Bioconductor project The source code and vignette are freely available at http://bioconductororg/packages/release/bioc/html/clusterProfilerhtml

PD-1 Blockade in Tumors with Mismatch-Repair Deficiency

Abstract: BackgroundSomatic mutations have the potential to encode “non-self” immunogenic antigens. We hypothesized that tumors with a large number of somatic mutations due to mismatch-repair defects may be susceptible to immune checkpoint blockade. MethodsWe conducted a phase 2 study to evaluate the clinical activity of pembrolizumab, an anti–programmed death 1 immune checkpoint inhibitor, in 41 patients with progressive metastatic carcinoma with or without mismatch-repair deficiency. Pembrolizumab was administered intravenously at a dose of 10 mg per kilogram of body weight every 14 days in patients with mismatch repair–deficient colorectal cancers, patients with mismatch repair–proficient colorectal cancers, and patients with mismatch repair–deficient cancers that were not colorectal. The coprimary end points were the immune-related objective response rate and the 20-week immune-related progression-free survival rate. ResultsThe immune-related objective response rate and immune-related progression-free survival ...

The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible.

Abstract: A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein-protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein-protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/.

Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome

Abstract: The role of the adaptive immune response in controlling the growth and recurrence of human tumors has been controversial. We characterized the tumor-infiltrating immune cells in large cohorts of human colorectal cancers by gene expression profiling and in situ immunohistochemical staining. Collectively, the immunological data (the type, density, and location of immune cells within the tumor samples) were found to be a better predictor of patient survival than the histopathological methods currently used to stage colorectal cancer. The results were validated in two additional patient populations. These data support the hypothesis that the adaptive immune response influences the behavior of human tumors. In situ analysis of tumor-infiltrating immune cells may therefore be a valuable prognostic tool in the treatment of colorectal cancer and possibly other malignancies.