Zlatko Trajanoski

Type, density, and location of immune cells within human colorectal tumors predict clinical outcome

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.

Genesis: cluster analysis of microarray data

A versatile, platform independent and easy to use Java suite for large-scale gene expression analysis was developed. Genesis integrates various tools for microarray data analysis such as filters, normalization and visualization tools, distance measures as well as common clustering algorithms including hierarchical clustering, self-organizing maps, k-means, principal component analysis, and support vector machines. The results of the clustering are transparent across all implemented methods and enable the analysis of the outcome of different algorithms and parameters. Additionally, mapping of gene expression data onto chromosomal sequences was implemented to enhance promoter analysis and investigation of transcriptional control mechanisms.

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.

IMPAIRED GLUCOSE TRANSPORT AS A CAUSE OF DECREASED INSULIN- STIMULATED MUSCLE GLYCOGEN SYNTHESIS IN TYPE 2 DIABETES

BACKGROUND Insulin resistance, a major factor in the pathogenesis of type 2 diabetes mellitus, is due mostly to decreased stimulation of glycogen synthesis in muscle by insulin. The primary rate-controlling step responsible for the decrease in muscle glycogen synthesis is not known, although hexokinase activity and glucose transport have been implicated. METHODS We used a novel nuclear magnetic resonance approach with carbon-13 and phosphorus-31 to measure intramuscular glucose, glucose-6-phosphate, and glycogen concentrations under hyperglycemic conditions (plasma glucose concentration, approximately 180 mg per deciliter [10 mmol per liter]) and hyperinsulinemic conditions in six patients with type 2 diabetes and seven normal subjects. In vivo microdialysis of muscle tissue was used to determine the gradient between plasma and interstitial-fluid glucose concentrations, and open-flow microperfusion was used to determine the concentrations of insulin in interstitial fluid. RESULTS The time course and concentration of insulin in interstitial fluid were similar in the patients with diabetes and the normal subjects. The rates of whole-body glucose metabolism and muscle glycogen synthesis and the glucose-6-phosphate concentrations in muscle were approximately 80 percent lower in the patients with diabetes than in the normal subjects under conditions of matched plasma insulin concentrations. The mean (+/-SD) intracellular glucose concentration was 2.0+/-8.2 mg per deciliter (0.11+/-0.46 mmol per liter) in the normal subjects. In the patients with diabetes, the intracellular glucose concentration was 4.3+/-4.9 mg per deciliter (0.24+/-0.27 mmol per liter), a value that was 1/25 of what it would be if hexokinase were the rate-controlling enzyme in glucose metabolism. CONCLUSIONS Impaired insulin-stimulated glucose transport is responsible for the reduced rate of insulin-stimulated muscle glycogen synthesis in patients with type 2 diabetes mellitus.

In Situ Cytotoxic and Memory T Cells Predict Outcome in Patients With Early-Stage Colorectal Cancer

PURPOSE Many patients who present with early-stage colorectal cancer (International Union Against Cancer TNM stages I and II) are nevertheless at high risk of relapse. We hypothesized that intratumoral immune reaction could influence their prognosis. PATIENTS AND METHODS The intratumoral immune reaction was investigated in 29 tumors by large-scale real-time polymerase chain reaction. Cytotoxic (CD8) and memory (CD45RO) T cells were quantified by immunohistochemical analyses of tissue microarrays from the center (CT) and the invasive margin (IM) of the 602 tumors from two independent cohorts. The results were correlated with tumor recurrence and patient survival. RESULTS Patients with a strong infiltration of CD45RO(+) cells in the tumor exhibited an increased expression of T-helper 1 and cytotoxicity-related genes. Densities of CD45RO(+) and CD8(+) cells in tumor regions (CT/IM) classified the patients into four distinct prognostic groups based on the presence of high density of each marker in each tumor region. The four groups were associated with dramatic differences in disease-free, disease-specific, and overall survival (all P < .0001). Five years after diagnosis, only 4.8% (95% CI, 0.6% to 8.8%) of patients with high densities of CD8(+) plus CD45RO(+) cells had tumor recurrence, and 86.2% (CI, 79.4% to 93.6%) survived. In contrast, the tumor recurred in 75% (95% CI, 17% to 92.5%) of patients with low densities of these cells, and only 27.5% (95% CI, 10.5% to 72%) survived (all P < .0001). Multivariate analyses showed that the immune criteria had independent effects on the rates of complete remission and survival. CONCLUSION The combined analysis of CD8(+) plus CD45RO(+) cells in specific tumor regions could provide a useful criterion for the prediction of tumor recurrence and survival in patients with early-stage colorectal cancer.

Histopathologic-Based Prognostic Factors of Colorectal Cancers Are Associated With the State of the Local Immune Reaction

PURPOSE The prognosis of patients with colorectal cancer has sometimes proved uncertain; thus, the prognostic significance of immune criteria was compared with that of the tumor extension criteria using the American Joint Committee on Cancer/International Union Against Cancer-TNM (AJCC/UICC-TNM) staging system. PATIENTS AND METHODS We studied the intratumoral immune infiltrates in the center of the tumor and in the invasive margin of 599 specimens of stage I to IV colorectal cancers from two independent cohorts. We analyzed these findings in relation to the degree of tumor extension and to the frequency of recurrence. RESULTS Growth of the primary tumor and metastatic spread were associated with decreased intratumoral immune T-cell densities. Sixty percent of patients with high densities of CD8(+) cytotoxic T-lymphocyte infiltrate presented with stage Tis/T1 tumor, whereas no patients with low densities presented with such early-stage tumor. In patients who did not relapse, the density of CD8 infiltrates was inversely correlated with T stage. In contrast, in patients whose tumor recurred, the number of CD8 cells was low regardless of the T stage of the tumor. Univariate analysis showed that the immune score was significantly associated with differences in disease-free, disease-specific, and overall survival (hazard ratio [HR], 0.64, 0.60, and 0.70, respectively; P < .005). Time-dependent receiver operating characteristic curve analysis illustrated the predictive accuracy of the immune parameters (c-index = 65.3%, time-dependent c-index [Cτ] = 66.5%). A final stepwise model for Cox multivariate analysis supports the advantage of the immune score (HR, 0.64; P < .001; Cτ = 67.9%) compared with histopathologic features in predicting recurrence as well as survival. CONCLUSION Assessment of CD8(+) cytotoxic T lymphocytes in combined tumor regions provides an indicator of tumor recurrence beyond that predicted by AJCC/UICC-TNM staging.

A survey of tools for variant analysis of next-generation genome sequencing data

Recent advances in genome sequencing technologies provide unprecedented opportunities to characterize individual genomic landscapes and identify mutations relevant for diagnosis and therapy. Specifically, whole-exome sequencing using next-generation sequencing (NGS) technologies is gaining popularity in the human genetics community due to the moderate costs, manageable data amounts and straightforward interpretation of analysis results. While whole-exome and, in the near future, whole-genome sequencing are becoming commodities, data analysis still poses significant challenges and led to the development of a plethora of tools supporting specific parts of the analysis workflow or providing a complete solution. Here, we surveyed 205 tools for whole-genome/whole-exome sequencing data analysis supporting five distinct analytical steps: quality assessment, alignment, variant identification, variant annotation and visualization. We report an overview of the functionality, features and specific requirements of the individual tools. We then selected 32 programs for variant identification, variant annotation and visualization, which were subjected to hands-on evaluation using four data sets: one set of exome data from two patients with a rare disease for testing identification of germline mutations, two cancer data sets for testing variant callers for somatic mutations, copy number variations and structural variations, and one semi-synthetic data set for testing identification of copy number variations. Our comprehensive survey and evaluation of NGS tools provides a valuable guideline for human geneticists working on Mendelian disorders, complex diseases and cancers.

Gene expression profiling of human mesenchymal stem cells derived from bone marrow during expansion and osteoblast differentiation

BackgroundHuman mesenchymal stem cells (MSC) with the capacity to differentiate into osteoblasts provide potential for the development of novel treatment strategies, such as improved healing of large bone defects. However, their low frequency in bone marrow necessitate ex vivo expansion for further clinical application. In this study we asked if MSC are developing in an aberrant or unwanted way during ex vivo long-term cultivation and if artificial cultivation conditions exert any influence on their stem cell maintenance. To address this question we first developed human oligonucleotide microarrays with 30.000 elements and then performed large-scale expression profiling of long-term expanded MSC and MSC during differentiation into osteoblasts.ResultsThe results showed that MSC did not alter their osteogenic differentiation capacity, surface marker profile, and the expression profiles of MSC during expansion. Microarray analysis of MSC during osteogenic differentiation identified three candidate genes for further examination and functional analysis: ID4, CRYAB, and SORT1. Additionally, we were able to reconstruct the three developmental phases during osteoblast differentiation: proliferation, matrix maturation, and mineralization, and illustrate the activation of the SMAD signaling pathways by TGF-β2 and BMPs.ConclusionWith a variety of assays we could show that MSC represent a cell population which can be expanded for therapeutic applications.

miR-17, miR-19b, miR-20a, and miR-106a are down-regulated in human aging.

Aging is a multifactorial process where deterioration of body functions is driven by stochastic damage while counteracted by distinct genetically encoded repair systems. To better understand the genetic component of aging, many studies have addressed the gene and protein expression profiles of various aging model systems engaging different organisms from yeast to human. The recently identified small non‐coding miRNAs are potent post‐transcriptional regulators that can modify the expression of up to several hundred target genes per single miRNA, similar to transcription factors. Increasing evidence shows that miRNAs contribute to the regulation of most if not all important physiological processes, including aging. However, so far the contribution of miRNAs to age‐related and senescence‐related changes in gene expression remains elusive. To address this question, we have selected four replicative cell aging models including endothelial cells, replicated CD8+ T cells, renal proximal tubular epithelial cells, and skin fibroblasts. Further included were three organismal aging models including foreskin, mesenchymal stem cells, and CD8+ T cell populations from old and young donors. Using locked nucleic acid‐based miRNA microarrays, we identified four commonly regulated miRNAs, miR‐17 down‐regulated in all seven; miR‐19b and miR‐20a, down‐regulated in six models; and miR‐106a down‐regulated in five models. Decrease in these miRNAs correlated with increased transcript levels of some established target genes, especially the cdk inhibitor p21/CDKN1A. These results establish miRNAs as novel markers of cell aging in humans.

CARMAweb: comprehensive R- and bioconductor-based web service for microarray data analysis

CARMAweb (Comprehensive R-based Microarray Analysis web service) is a web application designed for the analysis of microarray data. CARMAweb performs data preprocessing (background correction, quality control and normalization), detection of differentially expressed genes, cluster analysis, dimension reduction and visualization, classification, and Gene Ontology-term analysis. This web application accepts raw data from a variety of imaging software tools for the most widely used microarray platforms: Affymetrix GeneChips, spotted two-color microarrays and Applied Biosystems (ABI) microarrays. R and packages from the Bioconductor project are used as an analytical engine in combination with the R function Sweave, which allows automatic generation of analysis reports. These report files contain all R commands used to perform the analysis and guarantee therefore a maximum transparency and reproducibility for each analysis. The web application is implemented in Java based on the latest J2EE (Java 2 Enterprise Edition) software technology. CARMAweb is freely available at .