GPR87 is an overexpressed G-protein coupled receptor in squamous cell carcinoma of the lung

Lung cancer is the leading cause of cancer death worldwide. The overall 5-year survival after therapy is about 16% and there is a clear need for better treatment options, such as therapies targeting specific molecular structures. G-protein coupled receptors (GPCRs), as the largest family of cell surface receptors, represent an important group of potential targets for diagnostics and therapy. We therefore used laser capture microdissection and GPCR-focused Affymetrix microarrays to examine the expression of 929 GPCR transcripts in tissue samples of 10 patients with squamous cell carcinoma and 7 with adenocarcinoma in order to identify novel targets in non-small cell lung carcinoma (NSCLC). The relative gene expression levels were calculated in tumour samples compared to samples of the neighbouring alveolar tissue in every patient. Based on this unique study design, we identified 5 significantly overexpressed GPCRs in squamous cell carcinoma, in the following decreasing order of expression: GPR87 > CMKOR1 > FZD10 > LGR4 > P2RY11. All are non-olfactory and GRAFS (glutamate, rhodopsin, adhesion, frizzled/taste2, secretin family) classified. GPR87, LGR4 and CMKOR1 are orphan receptors. GPR87 stands out as a candidate for further target validation due to its marked overexpression and correlation on a mutation-based level to squamous cell carcinoma.

Gene expression variation between distinct areas of breast cancer measured from paraffin-embedded tissue cores

BACKGROUND: Diagnosis and prognosis in breast cancer are mainly based on histology and immunohistochemistry of formalin-fixed, paraffin-embedded (FFPE) material. Recently, gene expression analysis was shown to elucidate the biological variance between tumors and molecular markers were identified that led to new classification systems that provided better prognostic and predictive parameters. Archived FFPE samples represent an ideal source of tissue for translational research, as millions of tissue blocks exist from routine diagnostics and from clinical studies. These should be exploited to provide clinicians with more accurate prognostic and predictive information. Unfortunately, RNA derived from FFPE material is partially degraded and chemically modified and reliable gene expression measurement has only become successful after implementing novel and optimized procedures for RNA isolation, demodification and detection. METHODS: In this study we used tissue cylinders as known from the construction of tissue microarrays. RNA was isolated with a robust protocol recently developed for RNA derived from FFPE material. Gene expression was measured by quantitative reverse transcription PCR. RESULTS: Sixteen tissue blocks from 7 patients diagnosed with multiple histological subtypes of breast cancer were available for this study. After verification of appropriate localization, sufficient RNA yield and quality, 30 tissue cores were available for gene expression measurement on TaqMan(R) Low Density Arrays (16 invasive ductal carcinoma (IDC), 8 ductal carcinoma in situ (DCIS) and 6 normal tissue), and 14 tissue cores were lost. Gene expression values were used to calculate scores representing the proliferation status (PRO), the estrogen receptor status and the HER2 status. The PRO scores measured from entire sections were similar to PRO scores determined from IDC tissue cores. Scores determined from normal tissue cores consistently revealed lower PRO scores than cores derived from IDC or DCIS of the same block or from different blocks of the same patient. CONCLUSION: We have developed optimized protocols for RNA isolation from histologically distinct areas. RNA prepared from FFPE tissue cores is suitable for gene expression measurement by quantitative PCR. Distinct molecular scores could be determined from different cores of the same tumor specimen.

Integrative analysis of RUNX1 downstream pathways and target genes

BACKGROUND: The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML). The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia. RESULTS: Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1) cell lines with RUNX1 mutations from FPD-AML patients, 2) over-expression of RUNX1 and CBFbeta, and 3) Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFbeta. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes. CONCLUSION: This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease progression in both familial and sporadic leukemia as well as therapeutic implications.

MicroRNA-140 is expressed in differentiated human articular chondrocytes and modulates interleukin-1 responses

OBJECTIVE: MicroRNA (miRNA) are a class of noncoding small RNAs that act as negative regulators of gene expression. MiRNA exhibit tissue-specific expression patterns, and changes in their expression may contribute to pathogenesis. The objectives of this study were to identify miRNA expressed in articular chondrocytes, to determine changes in osteoarthritic (OA) cartilage, and to address the function of miRNA-140 (miR-140). METHODS: To identify miRNA specifically expressed in chondrocytes, we performed gene expression profiling using miRNA microarrays and quantitative polymerase chain reaction with human articular chondrocytes compared with human mesenchymal stem cells (MSCs). The expression pattern of miR-140 was monitored during chondrogenic differentiation of human MSCs in pellet cultures and in human articular cartilage from normal and OA knee joints. We tested the effects of interleukin-1beta (IL-1beta) on miR-140 expression. Double-stranded miR-140 (ds-miR-140) was transfected into chondrocytes to analyze changes in the expression of genes associated with OA. RESULTS: Microarray analysis showed that miR-140 had the largest difference in expression between chondrocytes and MSCs. During chondrogenesis, miR-140 expression in MSC cultures increased in parallel with the expression of SOX9 and COL2A1. Normal human articular cartilage expressed miR-140, and this expression was significantly reduced in OA tissue. In vitro treatment of chondrocytes with IL-1beta suppressed miR-140 expression. Transfection of chondrocytes with ds-miR-140 down-regulated IL-1beta-induced ADAMTS5 expression and rescued the IL-1beta-dependent repression of AGGRECAN gene expression. CONCLUSION: This study shows that miR-140 has a chondrocyte differentiation-related expression pattern. The reduction in miR-140 expression in OA cartilage and in response to IL-1beta may contribute to the abnormal gene expression pattern characteristic of OA.

Detection of cryptic pathogenic copy number variations and constitutional loss of heterozygosity using high resolution SNP microarray analysis in 117 patients referred for cytogenetic analysis and impact on clinical practice

BACKGROUND: Microarray genome analysis is realising its promise for improving detection of genetic abnormalities in individuals with mental retardation and congenital abnormality. Copy number variations (CNVs) are now readily detectable using a variety of platforms and a major challenge is the distinction of pathogenic from ubiquitous, benign polymorphic CNVs. The aim of this study was to investigate replacement of time consuming, locus specific testing for specific microdeletion and microduplication syndromes with microarray analysis, which theoretically should detect all known syndromes with CNV aetiologies as well as new ones. METHODS: Genome wide copy number analysis was performed on 117 patients using Affymetrix 250K microarrays. RESULTS: 434 CNVs (195 losses and 239 gains) were found, including 18 pathogenic CNVs and 9 identified as "potentially pathogenic". Almost all pathogenic CNVs were larger than 500 kb, significantly larger than the median size of all CNVs detected. Segmental regions of loss of heterozygosity larger than 5 Mb were found in 5 patients. CONCLUSIONS: Genome microarray analysis has improved diagnostic success in this group of patients. Several examples of recently discovered "new syndromes" were found suggesting they are more common than previously suspected and collectively are likely to be a major cause of mental retardation. The findings have several implications for clinical practice. The study revealed the potential to make genetic diagnoses that were not evident in the clinical presentation, with implications for pretest counselling and the consent process. The importance of contributing novel CNVs to high quality databases for genotype-phenotype analysis and review of guidelines for selection of individuals for microarray analysis is emphasised.

Microarray-based detection of 90 antibiotic resistance genes of gram-positive bacteria

A disposable microarray was developed for detection of up to 90 antibiotic resistance genes in gram-positive bacteria by hybridization. Each antibiotic resistance gene is represented by two specific oligonucleotides chosen from consensus sequences of gene families, except for nine genes for which only one specific oligonucleotide could be developed. A total of 137 oligonucleotides (26 to 33 nucleotides in length with similar physicochemical parameters) were spotted onto the microarray. The microarrays (ArrayTubes) were hybridized with 36 strains carrying specific antibiotic resistance genes that allowed testing of the sensitivity and specificity of 125 oligonucleotides. Among these were well-characterized multidrug-resistant strains of Enterococcus faecalis, Enterococcus faecium, and Lactococcus lactis and an avirulent strain of Bacillus anthracis harboring the broad-host-range resistance plasmid pRE25. Analysis of two multidrug-resistant field strains allowed the detection of 12 different antibiotic resistance genes in a Staphylococcus haemolyticus strain isolated from mastitis milk and 6 resistance genes in a Clostridium perfringens strain isolated from a calf. In both cases, the microarray genotyping corresponded to the phenotype of the strains. The ArrayTube platform presents the advantage of rapidly screening bacteria for the presence of antibiotic resistance genes known in gram-positive bacteria. This technology has a large potential for applications in basic research, food safety, and surveillance programs for antimicrobial resistance.

CCND1/CyclinD1 status in metastasizing bladder cancer: a prognosticator and predictor of chemotherapeutic response

The CCND1 gene encodes the protein CyclinD1, which is an important promoter of the cell cycle and a prognostic and predictive factor in different cancers. CCND1 is amplified to a substantial proportion in various tumors, and this may contribute to CyclinD1 overexpression. In bladder cancer, information about the clinical relevance of CCND1/CyclinD1 alterations is limited. In the present study, amplification status of CCND1 and expression of CyclinD1 were evaluated by fluorescence in situ hybridization and immunohistochemistry on tissue microarrays from 152 lymph node-positive urothelial bladder cancers (one sample each from the center and invasion front of the primary tumors, two samples per corresponding lymph node metastasis) treated by cystectomy and lymphadenectomy. CCND1 amplification status and the percentage of immunostained cancer cells were correlated with histopathological tumor characteristics, cancer-specific survival and response to adjuvant chemotherapy. CCND1 amplification in primary tumors was homogeneous in 15% and heterogeneous in 6% (metastases: 22 and 2%). Median nuclear CyclinD1 expression in amplified samples was similar in all tumor compartments (60-70% immunostained tumor nuclei) and significantly higher than in non-amplified samples (5-20% immunostained tumor nuclei; P<0.05). CCND1 status and CyclinD1 expression were not associated with primary tumor stage or lymph node tumor burden. CCND1 amplification in primary tumors (P=0.001) and metastases (P=0.02) and high nuclear CyclinD1 in metastases (P=0.01) predicted early cancer-related death independently. Subgroup analyses showed that chemotherapy was particularly beneficial in patients with high nuclear CyclinD1 expression in the metastases, whereas expression in primary tumors and CCND1 status did not predict chemotherapeutic response. In conclusion, CCND1 amplification status and CyclinD1 expression are independent risk factors in metastasizing bladder cancer. High nuclear CyclinD1 expression in lymph node metastases predicts favorable response to chemotherapy. This information may help to personalize prognostication and administration of adjuvant chemotherapy.

Characterization and Clinical Relevance of ALDHbright Populations in Prostate Cancer

PURPOSE High aldehyde dehydrogenase (ALDH) has been suggested to selectively mark cells with high tumorigenic potential in established prostate cancer cell lines. However, the existence of cells with high ALDH activity (ALDH(bright)) in primary prostate cancer specimens has not been shown so far. We investigated the presence, phenotype, and clinical significance of ALDH(bright) populations in clinical prostate cancer specimens. EXPERIMENTAL DESIGN We used ALDEFLUOR technology and fluorescence-activated cell-sorting (FACS) staining to identify and characterize ALDH(bright) populations in cells freshly isolated from clinical prostate cancer specimens. Expression of genes encoding ALDH-specific isoforms was evaluated by quantitative real-time PCR in normal prostate, benign prostatic hyperplasia (BPH), and prostate cancer tissues. ALDH1A1-specific expression and prognostic significance were assessed by staining two tissue microarrays that included more than 500 samples of BPH, prostatic intraepithelial neoplasia (PIN), and multistage prostate cancer. RESULTS ALDH(bright) cells were detectable in freshly excised prostate cancer specimens (n = 39) and were mainly included within the EpCAM((+)) and Trop2((+)) cell populations. Although several ALDH isoforms were expressed to high extents in prostate cancer, only ALDH1A1 gene expression significantly correlated with ALDH activity (P < 0.01) and was increased in cancers with high Gleason scores (P = 0.03). Most importantly, ALDH1A1 protein was expressed significantly more frequently and at higher levels in advanced-stage than in low-stage prostate cancer and BPH. Notably, ALDH1A1 positivity was associated with poor survival (P = 0.02) in hormone-naïve patients. CONCLUSIONS Our data indicate that ALDH contributes to the identification of subsets of prostate cancer cells of potentially high clinical relevance.

Clinical and molecular features of methicillin-resistant, coagulase-negative staphylococci of pets and horses

OBJECTIVES To determine the antibiotic resistance and fingerprint profiles of methicillin-resistant coagulase-negative staphylococci (MRCoNS) from animal infections among different practices and examine the history of antibiotic treatment. METHODS Isolates were identified by mass spectrometry and tested for antimicrobial resistance by broth dilution, microarrays and sequence analysis of the topoisomerases. Diversity was assessed by PFGE, icaA PCR and staphylococcal cassette chromosome mec (SCCmec), arginine catabolic mobile element (ACME) and multilocus sequence typing. Clinical records were examined retrospectively. RESULTS MRCoNS were identified as Staphylococcus epidermidis (n=20), Staphylococcus haemolyticus (n=17), Staphylococcus hominis (n=3), Staphylococcus capitis (n=1), Staphylococcus cohnii (n=1) and Staphylococcus warneri (n=1). PFGE identified one clonal lineage in S. hominis isolates and several in S. haemolyticus and S. epidermidis. Fourteen sequence types were identified in S. epidermidis, with sequence type 2 (ST2) and ST5 being predominant. Ten isolates contained SCCmec IV, seven contained SCCmec V and the others were non-typeable. ACMEs were detected in 11 S. epidermidis isolates. One S. hominis and 10 S. epidermidis isolates were icaA positive. In addition to mecA-mediated β-lactam resistance, the most frequent resistance was to gentamicin/kanamycin [aac(6')-Ie-aph(2')-Ia, aph(3')-III] (n=34), macrolides/lincosamides [erm(C), erm(A), msr, lnu(A)] (n=31), tetracycline [tet(K)] (n=22), streptomycin [str, ant(6)-Ia] (n=20), trimethoprim [dfr(A), dfr(G)] (n=17), sulfamethoxazole (n = 34) and fluoroquinolones [amino acid substitutions in GyrA and GrlA] (n=30). Clinical data suggest selection through multiple antibiotic courses and emphasize the importance of accurate diagnosis and antibiograms. CONCLUSIONS MRCoNS from animal infection sites are genetically heterogeneous multidrug-resistant strains that represent a new challenge in the prevention and therapy of infections in veterinary clinics.

Extended-spectrum cephalosporin-resistant Escherichia coli in community, specialized outpatient clinic and hospital settings in Switzerland

OBJECTIVES Resistance to extended-spectrum cephalosporins (ESCs) in Escherichia coli can be due to the production of ESBLs, plasmid-mediated AmpCs (pAmpCs) or chromosomal AmpCs (cAmpCs). Information regarding type and prevalence of β-lactamases, clonal relations and plasmids associated with the bla genes for ESC-R E. coli (ESC-R-Ec) detected in Switzerland is lacking. Moreover, data focusing on patients referred to the specialized outpatient clinics (SOCs) are needed. METHODS We analysed 611 unique E. coli isolated during September-December 2011. ESC-R-Ec were studied with microarrays, PCR/DNA sequencing for blaESBLs, blapAmpCs, promoter region of blacAmpC, IS elements, plasmid incompatibility group, and also implementing transformation, aIEF, rep-PCR and MLST. RESULTS The highest resistance rates were observed in the SOCs, whereas those in the hospital and community were lower (e.g. quinolone resistance of 22.6%, 17.2% and 9.0%, respectively; P = 0.003 for SOCs versus community). The prevalence of ESC-R-Ec in the three settings was 5.3% (n = 11), 7.8% (n = 22) and 5.7% (n = 7), respectively. Thirty isolates produced CTX-M ESBLs (14 were CTX-M-15), 5 produced CMY-2 pAmpC and 5 hyper-expressed cAmpCs due to promoter mutations. Fourteen isolates were of sequence type 131 (ST131; 10 with CTX-M-15). blaCTX-M and blaCMY-2 were associated with an intact or truncated ISEcp1 and were mainly carried by IncF, IncFII and IncI1plasmids. CONCLUSIONS ST131 producing CTX-M-15 is the predominant clone. The prevalence of ESC-R-Ec (overall 6.5%) is low, but an unusual relatively high frequency of AmpC producers (25%) was noted. The presence of ESC-R-Ec in the SOCs and their potential ability to be exchanged between hospital and community should be taken into serious consideration.

Non-phenotypic tests to detect and characterize antibiotic resistance mechanisms in Enterobacteriaceae

In the past 2 decades, we have observed a rapid increase of infections due to multidrug-resistant Enterobacteriaceae. Regrettably, these isolates possess genes encoding for extended-spectrum β-lactamases (e.g., blaCTX-M, blaTEM, blaSHV) or plasmid-mediated AmpCs (e.g., blaCMY) that confer resistance to last-generation cephalosporins. Furthermore, other resistance traits against quinolones (e.g., mutations in gyrA and parC, qnr elements) and aminoglycosides (e.g., aminoglycosides modifying enzymes and 16S rRNA methylases) are also frequently co-associated. Even more concerning is the rapid increase of Enterobacteriaceae carrying genes conferring resistance to carbapenems (e.g., blaKPC, blaNDM). Therefore, the spread of these pathogens puts in peril our antibiotic options. Unfortunately, standard microbiological procedures require several days to isolate the responsible pathogen and to provide correct antimicrobial susceptibility test results. This delay impacts the rapid implementation of adequate antimicrobial treatment and infection control countermeasures. Thus, there is emerging interest in the early and more sensitive detection of resistance mechanisms. Modern non-phenotypic tests are promising in this respect, and hence, can influence both clinical outcome and healthcare costs. In this review, we present a summary of the most advanced methods (e.g., next-generation DNA sequencing, multiplex PCRs, real-time PCRs, microarrays, MALDI-TOF MS, and PCR/ESI MS) presently available for the rapid detection of antibiotic resistance genes in Enterobacteriaceae. Taking into account speed, manageability, accuracy, versatility, and costs, the possible settings of application (research, clinic, and epidemiology) of these methods and their superiority against standard phenotypic methods are discussed.

Next-generation tissue microarray (ngTMA) increases the quality of biomarker studies: an example using CD3, CD8, and CD45RO in the tumor microenvironment of six different solid tumor types

Background Tissue microarray (TMA) technology revolutionized the investigation of potential biomarkers from paraffin-embedded tissues. However, conventional TMA construction is laborious, time-consuming and imprecise. Next-generation tissue microarrays (ngTMA) combine histological expertise with digital pathology and automated tissue microarraying. The aim of this study was to test the feasibility of ngTMA for the investigation of biomarkers within the tumor microenvironment (tumor center and invasion front) of six tumor types, using CD3, CD8 and CD45RO as an example. Methods Ten cases each of malignant melanoma, lung, breast, gastric, prostate and colorectal cancers were reviewed. The most representative H&E slide was scanned and uploaded onto a digital slide management platform. Slides were viewed and seven TMA annotations of 1 mm in diameter were placed directly onto the digital slide. Different colors were used to identify the exact regions in normal tissue (n = 1), tumor center (n = 2), tumor front (n = 2), and tumor microenvironment at invasion front (n = 2) for subsequent punching. Donor blocks were loaded into an automated tissue microarrayer. Images of the donor block were superimposed with annotated digital slides. Exact annotated regions were punched out of each donor block and transferred into a TMA block. 420 tissue cores created two ngTMA blocks. H&E staining and immunohistochemistry for CD3, CD8 and CD45RO were performed. Results All 60 slides were scanned automatically (total time < 10 hours), uploaded and viewed. Annotation time was 1 hour. The 60 donor blocks were loaded into the tissue microarrayer, simultaneously. Alignment of donor block images and digital slides was possible in less than 2 minutes/case. Automated punching of tissue cores and transfer took 12 seconds/core. Total ngTMA construction time was 1.4 hours. Stains for H&E and CD3, CD8 and CD45RO highlighted the precision with which ngTMA could capture regions of tumor-stroma interaction of each cancer and the T-lymphocytic immune reaction within the tumor microenvironment. Conclusion Based on a manual selection criteria, ngTMA is able to precisely capture histological zones or cell types of interest in a precise and accurate way, aiding the pathological study of the tumor microenvironment. This approach would be advantageous for visualizing proteins, DNA, mRNA and microRNAs in specific cell types using in situ hybridization techniques.

Diagnostic and prognostic implications of the PAX8-PPARγ translocation in thyroid carcinomas-a TMA-based study of 226 cases

AIMS Follicular thyroid carcinoma (FTC) has been a diagnostic challenge for decades. The PAX8-PPARγ rearrangement has been detected in FTC and classic papillary thyroid carcinomas (PTCs). The aims of this study were to assess the presence of PAX8-PPARγ by using tissue microarrays in a large cohort of different thyroid neoplasms, and to assess its diagnostic and prognostic implications. METHODS AND RESULTS Fluorescence in-situ hybridization (FISH) analysis for PAX8-PPARγ was performed on 226 thyroid tumours, comprising FTCs (n = 59), PTCs (n = 126), poorly differentiated thyroid carcinomas (PDs; n = 34), follicular thyroid adenomas (FTAs; n = 5), and follicular tumours of unknown malignant potential (FTUMPs; n = 2). PAX8-PPARγ was detected in 12% of FTCs, 1% of PTCs, 7% of PDs, and in both cases of FTUMP. There was no correlation between the extent of capsular or vascular invasion and PAX8-PPARγ, or between lymph node or haematogenous metastasis and PAX8-PPARγ. Overall survival (OS), tumour-specific survival (TSS) and relapse-free-survival (RFS) were not influenced by PAX8-PPARγ. CONCLUSIONS In this study, we demonstrate for the first time the presence of PAX8-PPARγ in PDs and FTUMPs, whereas in FTCs and PTCs the prevalence of PAX8-PPARγ is lower than previously reported. PAX8-PPARγ did not correlate with invasiveness or affect prognosis in any tumour type.

Targeting the Blood-brain Barrier with a Non-canonical Iron-mimicry Mechanism

Treatment of central nervous system (CNS) diseases is limited by the blood-brain barrier (BBB), a selective vascular interface restricting passage of most molecules from blood into brain. Specific transport systems have evolved allowing circulating polar molecules to cross the BBB and gain access to the brain parenchyma. However, to date, few ligands exploiting such systems have proven clinically viable in the setting of CNS diseases. We reasoned that combinatorial phage-display screenings in vivo would yield peptides capable of crossing the BBB and allow for the development of ligand-directed targeting strategies of the brain. Here we show the identification of a peptide mediating systemic targeting to the normal brain and to an orthotopic human glioma model. We demonstrate that this peptide functionally mimics iron through an allosteric mechanism and that a non-canonical association of (i) transferrin, (ii) the iron-mimic ligand motif, and (iii) transferrin receptor mediates binding and transport of particles across the BBB. We also show that in orthotopic human glioma xenografts, a combination of transferrin receptor over-expression plus extended vascular permeability and ligand retention result in remarkable brain tumor targeting. Moreover, such tumor targeting attributes enables Herpes simplex virus thymidine kinase-mediated gene therapy of intracranial tumors for molecular genetic imaging and suicide gene delivery with ganciclovir. Finally, we expand our data by analyzing a large panel of primary CNS tumors through comprehensive tissue microarrays. Together, our approach and results provide a translational avenue for the detection and treatment of brain tumors.

SURVIVAL PREDICTION FOR BRAIN TUMOR PATIENTS USING GENE EXPRESSION DATA

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.