Pornpimol Charoentong

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

Summary: 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. Availability: http://www.ici.upmc.fr/cluego/cluegoDownload.shtml Contact: jerome.galon@crc.jussieu.fr Supplementary information: Supplementary data are available at Bioinformatics online.

Biomolecular Network Reconstruction Identifies T-Cell Homing Factors Associated With Survival in Colorectal Cancer

BACKGROUND & AIMS Colorectal cancer is a complex disease involving immune defense mechanisms within the tumor. Herein, we used data integration and biomolecular network reconstruction to generate hypotheses about the mechanisms underlying immune responses in colorectal cancer that are relevant to tumor recurrence. METHODS Mechanistic hypotheses were formulated on the basis of data from 108 patients and tested using different assays (gene expression, phenome mapping, tissue-microarrays, T-cell receptor [TCR] repertoire). RESULTS This integrative approach revealed that chemoattraction and adhesion play important roles in determining the density of intratumoral immune cells. The presence of specific chemokines (CX3CL1, CXCL10, CXCL9) and adhesion molecules (ICAM1, VCAM1, MADCAM1) correlated with different subsets of immune cells and with high densities of T-cell subpopulations within specific tumor regions. High expression of these molecules correlated with prolonged disease-free survival. Moreover, the expression of certain chemokines associated with particular TCR repertoire and specific TCR use predicted patient survival. CONCLUSIONS Data integration and biomolecular network reconstruction is a powerful approach to uncover molecular mechanisms. This study shows the utility of this approach for the investigation of malignant tumors and other diseases. In colorectal cancer, the expression of specific chemokines and adhesion molecules were found as being critical for high densities of T-cell subsets within the tumor and associated with particular TCR repertoire. Intratumoral-specific TCR use correlated with the prognosis of the patients.

Coordination of Intratumoral Immune Reaction and Human Colorectal Cancer Recurrence

A role for the immune system in controlling the progression of solid tumors has been established in several mouse models. However, the effect of immune responses and tumor escape on patient prognosis in the context of human cancer is poorly understood. Here, we investigate the cellular and molecular parameters that could describe in situ immune responses in human colorectal cancer according to clinical parameters of metastatic lymph node or distant organ invasion (META- or META+ patients). Primary tumor samples of colorectal carcinoma were analyzed by integrating large-scale phenotypic (flow cytometry, 39 patients) and gene expression (real time reverse transcription-PCR, 103 patients) data sets related to immune and protumoral processes. In META- colorectal cancer primary tumors with high densities of T cells, we observed significant positive correlations between markers of innate immune cells [tumor-associated macrophages, dendritic cells, natural killer (NK) cells, and NKT cells] and markers of early-activated T cells. Significant correlations were also observed between markers of cytotoxic and effector memory T-cell subpopulations. These correlation profiles were absent in tumors with low T-cell infiltrates and were altered in META+ tumors with high T-cell infiltrates. We show that the coexpression of genes mediating cytotoxicity (GNLY) and Th1 adaptive immune responses (IRF1) accurately predicted patient survival independently of the metastatic status. High intratumoral mRNA expression of the proangiogenic mediator vascular endothelial growth factor was associated with significantly reduced survival rates in patients expressing high mRNA levels of GNLY. Investigation of the colorectal cancer primary tumor microenvironment allowed us to uncover the association of favorable outcomes with efficient coordination of the intratumoral immune response.

Characterization of the immunophenotypes and antigenomes of colorectal cancers reveals distinct tumor escape mechanisms and novel targets for immunotherapy

BackgroundWhile large-scale cancer genomic projects are comprehensively characterizing the mutational spectrum of various cancers, so far little attention has been devoted to either define the antigenicity of these mutations or to characterize the immune responses they elicit. Here we present a strategy to characterize the immunophenotypes and the antigen-ome of human colorectal cancer.ResultsWe apply our strategy to a large colorectal cancer cohort (n = 598) and show that subpopulations of tumor-infiltrating lymphocytes are associated with distinct molecular phenotypes. The characterization of the antigenome shows that a large number of cancer-germline antigens are expressed in all patients. In contrast, neo-antigens are rarely shared between patients, indicating that cancer vaccination requires individualized strategy. Analysis of the genetic basis of the tumors reveals distinct tumor escape mechanisms for the patient subgroups. Hypermutated tumors are depleted of immunosuppressive cells and show upregulation of immunoinhibitory molecules. Non-hypermutated tumors are enriched with immunosuppressive cells, and the expression of immunoinhibitors and MHC molecules is downregulated. Reconstruction of the interaction network of tumor-infiltrating lymphocytes and immunomodulatory molecules followed by a validation with 11 independent cohorts (n = 1,945) identifies BCMA as a novel druggable target. Finally, linear regression modeling identifies major determinants of tumor immunogenicity, which include well-characterized modulators as well as a novel candidate, CCR8, which is then tested in an orthologous immunodeficient mouse model.ConclusionsThe immunophenotypes of the tumors and the cancer antigenome remain widely unexplored, and our findings represent a step toward the development of personalized cancer immunotherapies.

Computational genomics tools for dissecting tumour-immune cell interactions

Recent breakthroughs in cancer immunotherapy and decreasing costs of high-throughput technologies have sparked intensive research into tumour–immune cell interactions using genomic tools. The wealth of the generated data and the added complexity pose considerable challenges and require computational tools to process, to analyse and to visualize the data. Recently, various tools have been developed and used to mine tumour immunologic and genomic data effectively and to provide novel mechanistic insights. Here, we review computational genomics tools for cancer immunology and provide information on the requirements and functionality in order to assist in the selection of tools and assembly of analytical pipelines.

The thioredoxin system in breast cancer cell invasion and migration.

Metastasis is the most life threatening aspect of breast cancer. It is a multi-step process involving invasion and migration of primary tumor cells with a subsequent colonization of these cells at a secondary location. The aim of the present study was to investigate the role of thioredoxin (Trx1) in the invasion and migration of breast cancer cells and to assess the strength of the association between high levels of Trx1 and thioredoxin reductase (TrxR1) expression with breast cancer patient survival. Our results indicate that the expression of both Trx1 and TrxR1 are statistically significantly increased in breast cancer patient cells compared with paired normal breast tissue from the same patient. Over-expression of Trx1 in MDA-MB-231 breast cancer cell lines enhanced cell invasion in in vitro assays while expression of a redox inactive mutant form of Trx1 (designated 1SS) or the antisense mRNA inhibited cell invasion. Addition of exogenous Trx1 also enhanced cell invasion, while addition of a specific monoclonal antibody that inhibits Trx1 redox function decreased cell invasion. Over-expression of intracellular Trx1 did not increase cell migration but expression of intracellular 1SS inhibited migration. Addition of exogenous Trx1 enhanced cell migration while 1SS had no effect. Treatment with auranofin inhibited TrxR activity, cell migration and clonogenic activity of MDA-MB-231 cells, while increasing reactive oxygen species (ROS) levels. Analysis of 25 independent cohorts with 5910 patients showed that Trx1 and TrxR1 were both associated with a poor patient prognosis in terms of overall survival, distant metastasis free survival and disease free survival. Therefore, targeting the Trx system with auranofin or other specific inhibitors may provide improved breast cancer patient outcomes through inhibition of cancer invasion and migration.

High STAT1 mRNA levels but not its tyrosine phosphorylation are associated with macrophage infiltration and bad prognosis in breast cancer

BackgroundSTAT1 has been attributed a function as tumor suppressor. However, in breast cancer data from microarray analysis indicated a predictive value of high mRNA expression levels of STAT1 and STAT1 target genes belonging to the interferon-related signature for a poor response to therapy. To clarify this issue we have determined STAT1 expression levels and activation by different methods, and investigated their association with tumor infiltration by immune cells. Additionally, we evaluated the interrelationship of these parameters and their significance for predicting disease outcome.MethodsExpression of STAT1, its target genes SOCS1, IRF1, CXCL9, CXCL10, CXCL11, IFIT1, IFITM1, MX1 and genes characteristic for immune cell infiltration (CD68, CD163, PD-L1, PD-L2, PD-1, CD45, IFN-γ, FOXP3) was determined by RT-PCR in two independent cohorts comprising 132 breast cancer patients. For a subset of patients, protein levels of total as well as serine and tyrosine-phosphorylated STAT1 were ascertained by immunohistochemistry or immunoblotting and protein levels of CXCL10 by ELISA.ResultsmRNA expression levels of STAT1 and STAT1 target genes, as well as protein levels of total and serine-phosphorylated STAT1 correlated with each other in neoplastic tissue. However, there was no association between tumor levels of STAT1 mRNA and tyrosine-phosphorylated STAT1 and between CXCL10 serum levels and CXCL10 expression in the tumor. Tumors with increased STAT1 mRNA amounts exhibited elevated expression of genes characteristic for tumor-associated macrophages and immunosuppressive T lymphocytes. Survival analysis revealed an association of high STAT1 mRNA levels and bad prognosis in both cohorts. A similar prognostically relevant correlation with unfavorable outcome was evident for CXCL10, MX1, CD68, CD163, IFN-γ, and PD-L2 expression in at least one collective. By contrast, activation of STAT1 as assessed by the level of STAT1-Y701 phosphorylation was linked to positive outcome. In multivariate Cox regression, the predictive power of STAT1 mRNA expression was lost when including expression of CXCL10, MX1 and CD68 as confounders.ConclusionsOur study confirms distinct prognostic relevance of STAT1 expression levels and STAT1 tyrosine phosphorylation in breast cancer patients and identifies an association of high STAT1 levels with elevated expression of STAT1 target genes and markers for infiltrating immune cells.

Identification of microRNA-mRNA functional interactions in UVB-induced senescence of human diploid fibroblasts

BackgroundCellular senescence can be induced by a variety of extrinsic stimuli, and sustained exposure to sunlight is a key factor in photoaging of the skin. Accordingly, irradiation of skin fibroblasts by UVB light triggers cellular senescence, which is thought to contribute to extrinsic skin aging, although molecular mechanisms are incompletely understood. Here, we addressed molecular mechanisms underlying UVB induced senescence of human diploid fibroblasts.ResultsWe observed a parallel activation of the p53/p21WAF1 and p16INK4a/pRb pathways. Using genome-wide transcriptome analysis, we identified a transcriptional signature of UVB-induced senescence that was conserved in three independent strains of human diploid fibroblasts (HDF) from skin. In parallel, a comprehensive screen for microRNAs regulated during UVB-induced senescence was performed which identified five microRNAs that are significantly regulated during the process. Bioinformatic analysis of miRNA-mRNA networks was performed to identify new functional mRNA targets with high confidence for miR-15a, miR-20a, miR-20b, miR-93, and miR-101. Already known targets of these miRNAs were identified in each case, validating the approach. Several new targets were identified for all of these miRNAs, with the potential to provide new insight in the process of UVB-induced senescence at a genome-wide level. Subsequent analysis was focused on miR-101 and its putative target gene Ezh2. We confirmed that Ezh2 is regulated by miR-101 in human fibroblasts, and found that both overexpression of miR-101 and downregulation of Ezh2 independently induce senescence in the absence of UVB irradiation. However, the downregulation of miR-101 was not sufficient to block the phenotype of UVB-induced senescence, suggesting that other UVB-induced processes induce the senescence response in a pathway redundant with upregulation of miR-101.ConclusionWe performed a comprehensive screen for UVB-regulated microRNAs in human diploid fibroblasts, and identified a network of miRNA-mRNA interactions mediating UVB-induced senescence. In addition, miR-101 and Ezh2 were identified as key players in UVB-induced senescence of HDF.

Bioinformatics for cancer immunology and immunotherapy

Recent mechanistic insights obtained from preclinical studies and the approval of the first immunotherapies has motivated increasing number of academic investigators and pharmaceutical/biotech companies to further elucidate the role of immunity in tumor pathogenesis and to reconsider the role of immunotherapy. Additionally, technological advances (e.g., next-generation sequencing) are providing unprecedented opportunities to draw a comprehensive picture of the tumor genomics landscape and ultimately enable individualized treatment. However, the increasing complexity of the generated data and the plethora of bioinformatics methods and tools pose considerable challenges to both tumor immunologists and clinical oncologists. In this review, we describe current concepts and future challenges for the management and analysis of data for cancer immunology and immunotherapy. We first highlight publicly available databases with specific focus on cancer immunology including databases for somatic mutations and epitope databases. We then give an overview of the bioinformatics methods for the analysis of next-generation sequencing data (whole-genome and exome sequencing), epitope prediction tools as well as methods for integrative data analysis and network modeling. Mathematical models are powerful tools that can predict and explain important patterns in the genetic and clinical progression of cancer. Therefore, a survey of mathematical models for tumor evolution and tumor–immune cell interaction is included. Finally, we discuss future challenges for individualized immunotherapy and suggest how a combined computational/experimental approaches can lead to new insights into the molecular mechanisms of cancer, improved diagnosis, and prognosis of the disease and pinpoint novel therapeutic targets.

TIminer: NGS data mining pipeline for cancer immunology and immunotherapy

Summary: Recently, a number of powerful computational tools for dissecting tumor‐immune cell interactions from next‐generation sequencing data have been developed. However, the assembly of analytical pipelines and execution of multi‐step workflows are laborious and involve a large number of intermediate steps with many dependencies and parameter settings. Here we present TIminer, an easy‐to‐use computational pipeline for mining tumor‐immune cell interactions from next‐generation sequencing data. TIminer enables integrative immunogenomic analyses, including: human leukocyte antigens typing, neoantigen prediction, characterization of immune infiltrates and quantification of tumor immunogenicity. Availability and implementation: TIminer is freely available at http://icbi.i‐med.ac.at/software/timiner/timiner.shtml. Contact: zlatko.trajanoski@i‐med.ac.at Supplementary information: Supplementary data are available at Bioinformatics online.