bioRxiv ScienceSearch

Biology subjects

Augustin Luna

Publications and source records attributed to Augustin Luna.

2 recordsLinked to original sources

The landscape of T cell infiltration in human cancer and its association with antigen presenting gene expression

One sentence summaryIn silico decomposition of the immune microenvironment among common tumor types identified clear cell renal cell carcinoma as the most highly infiltrated by T-cells and further analysis of this tumor type revealed three distinct and clinically relevant clusters which were validated in an independent cohort.\n\nAbstractInfiltrating T cells in the tumor microenvironment have crucial roles in the competing processes of pro-tumor and anti-tumor immune response. However, the infiltration level of distinct T cell subsets and the signals that draw them into a tumor, such as the expression of antigen presenting machinery (APM) genes, remain poorly characterized across human cancers. Here, we define a novel mRNA-based T cell infiltration score (TIS) and profile infiltration levels in 19 tumor types. We find that clear cell renal cell carcinoma (ccRCC) is the highest for TIS and among the highest for the correlation between TIS and APM expression, despite a modest mutation burden. This finding is contrary to the expectation that immune infiltration and mutation burden are linked. To further characterize the immune infiltration in ccRCC, we use RNA-seq data to computationally infer the infiltration levels of 24 immune cell types in a discovery cohort of 415 ccRCC patients and validate our findings in an independent cohort of 101 ccRCC patients. We find three clusters of tumors that are primarily separated by levels of T cell infiltration and APM gene expression. In ccRCC, the levels of Th17 cells and the ratio of CD8+ T/Treg levels are associated with improved survival whereas the levels of Th2 cells and Tregs are associated with negative clinical outcome. Our analysis illustrates the utility of computational immune cell decomposition for solid tumors, and the potential of this method to guide clinical decision-making.

Cancer Biology

PaxtoolsR: Pathway Analysis in R Using Pathway Commons

PurposePaxtoolsR package enables access to pathway data represented in the BioPAX format and made available through the Pathway Commons webservice for users of the R language. Features include the extraction, merging, and validation of pathway data represented in the BioPAX format. This package also provides novel pathway datasets and advanced querying features for R users through the Pathway Commons webservice allowing users to query, extract, and retrieve data and integrate this data with local BioPAX datasets.\n\nAvailabilityThe PaxtoolsR package is compatible with R 3.1.1 on Windows, Mac OS X, and Linux using Bioconductor 3.0 and is available through the Bioconductor R package repository along with source code and a tutorial vignette describing common tasks, such as data visualization and gene set enrichment analysis. Source code and documentation are at http://bioconductor.org/packages/release/bioc/html/paxtoolsr.html. This plugin is free, open-source and licensed under the GNU Lesser General Public License (LGPL) v3.0.\n\nContactpaxtools@cbio.mskcc.org

Bioinformatics