A Novel Urine Exosome Gene Expression Assay to Predict High-grade Prostate Cancer at Initial Biopsy.

IMPORTANCE: Overdiagnosis and overtreatment of indolent prostate cancer (PCA) is a serious health issue in most developed countries. There is an unmet clinical need for noninvasive, easy to administer, diagnostic assays to help assess whether a prostate biopsy is warranted. OBJECTIVE: To determine the performance of a novel urine exosome gene expression assay (the ExoDx Prostate IntelliScore urine exosome assay) plus standard of care (SOC) (ie, prostate-specific antigen [PSA] level, age, race, and family history) vs SOC alone for discriminating between Gleason score (GS)7 and GS6 and benign disease on initial biopsy. DESIGN, SETTING, AND PARTICIPANTS: In training, using reverse-transcriptase polymerase chain reaction (PCR), we compared the urine exosome gene expression assay with biopsy outcomes in 499 patients with prostate-specific antigen (PSA) levels of 2 to 20 ng/mL. The derived prognostic score was then validated in 1064 patients from 22 community practice and academic urology clinic sites in the United States. Eligible participants included PCA-free men, 50 years or older, scheduled for an initial or repeated prostate needle biopsy due to suspicious digital rectal examination (DRE) findings and/or PSA levels (limit range, 2.0-20.0 ng/mL). MAIN OUTCOMES AND MEASURES: Evaluate the assay using the area under receiver operating characteristic curve (AUC) in discrimination of GS7 or greater from GS6 and benign disease on initial biopsy. RESULTS: In 255 men in the training target population (median age 62 years and median PSA level 5.0 ng/mL, and initial biopsy), the urine exosome gene expression assay plus SOC was associated with improved discrimination between GS7 or greater and GS6 and benign disease: AUC 0.77 (95% CI, 0.71-0.83) vs SOC AUC 0.66 (95% CI, 0.58-0.72) (P < .001). Independent validation in 519 patients' urine exosome gene expression assay plus SOC AUC 0.73 (95% CI, 0.68-0.77) was superior to SOC AUC 0.63 (95% CI, 0.58-0.68) (P < .001). Using a predefined cut point, 138 of 519 (27%) biopsies would have been avoided, missing only 5% of patients with dominant pattern 4 high-risk GS7 disease. CONCLUSIONS AND RELEVANCE: This urine exosome gene expression assay is a noninvasive, urinary 3-gene expression assay that discriminates high-grade (≥GS7) from low-grade (GS6) cancer and benign disease. In this study, the urine exosome gene expression assay was associated with improved identification of patients with higher-grade prostate cancer among men with elevated PSA levels and could reduce the total number of unnecessary biopsies.

Gene expression signature of normal cell-of-origin predicts ovarian tumor outcomes.

The potential role of the cell-of-origin in determining the tumor phenotype has been raised, but not adequately examined. We hypothesized that distinct cells-of-origin may play a role in determining ovarian tumor phenotype and outcome. Here we describe a new cell culture medium for in vitro culture of paired normal human ovarian (OV) and fallopian tube (FT) epithelial cells from donors without cancer. While these cells have been cultured individually for short periods of time, to our knowledge this is the first long-term culture of both cell types from the same donors. Through analysis of the gene expression profiles of the cultured OV/FT cells we identified a normal cell-of-origin gene signature that classified primary ovarian cancers into OV-like and FT-like subgroups; this classification correlated with significant differences in clinical outcomes. The identification of a prognostically significant gene expression signature derived solely from normal untransformed cells is consistent with the hypothesis that the normal cell-of-origin may be a source of ovarian tumor heterogeneity and the associated differences in tumor outcome.

Stem cell-like gene expression in ovarian cancer predicts type II subtype and prognosis.

Although ovarian cancer is often initially chemotherapy-sensitive, the vast majority of tumors eventually relapse and patients die of increasingly aggressive disease. Cancer stem cells are believed to have properties that allow them to survive therapy and may drive recurrent tumor growth. Cancer stem cells or cancer-initiating cells are a rare cell population and difficult to isolate experimentally. Genes that are expressed by stem cells may characterize a subset of less differentiated tumors and aid in prognostic classification of ovarian cancer. The purpose of this study was the genomic identification and characterization of a subtype of ovarian cancer that has stem cell-like gene expression. Using human and mouse gene signatures of embryonic, adult, or cancer stem cells, we performed an unsupervised bipartition class discovery on expression profiles from 145 serous ovarian tumors to identify a stem-like and more differentiated subgroup. Subtypes were reproducible and were further characterized in four independent, heterogeneous ovarian cancer datasets. We identified a stem-like subtype characterized by a 51-gene signature, which is significantly enriched in tumors with properties of Type II ovarian cancer; high grade, serous tumors, and poor survival. Conversely, the differentiated tumors share properties with Type I, including lower grade and mixed histological subtypes. The stem cell-like signature was prognostic within high-stage serous ovarian cancer, classifying a small subset of high-stage tumors with better prognosis, in the differentiated subtype. In multivariate models that adjusted for common clinical factors (including grade, stage, age), the subtype classification was still a significant predictor of relapse. The prognostic stem-like gene signature yields new insights into prognostic differences in ovarian cancer, provides a genomic context for defining Type I/II subtypes, and potential gene targets which following further validation may be valuable in the clinical management or treatment of ovarian cancer.

SOCS1 mutation subtypes predict divergent outcomes in diffuse large B-Cell lymphoma (DLBCL) patients.

Suppressor of cytokine signaling 1 (SOCS1) is frequently mutated in primary mediastinal and diffuse large B-cell lymphomas (DLBCL). Currently, the prognostic relevance of these mutations in DLBCL is unknown. To evaluate the value of the SOCS1 mutation status as a prognostic biomarker in DLBCL patients, we performed full-length SOCS1 sequencing in tumors of 154 comprehensively characterized DLBCL patients. We identified 90 SOCS1 mutations in 16% of lymphomas. With respect to molecular consequences of mutations, we defined two distinct subtypes: those with truncating (major) and those with non-truncating mutations (minor), respectively. The SOCS1 mutated subgroup or the minor/major subtypes cannot be predicted on clinical grounds; however, assignment of four established gene-expression profile-based classifiers revealed significant associations of SOCS1 major cases with germinal center and specific pathway activation pattern signatures. Above all, SOCS1 major cases have an excellent overall survival, even better than the GCB-like subgroup. SOCS1 minor cases had a dismal survival, even worse than the ABC gene signature group. The SOCS1 mutation subsets retained prognostic significance in uni- and multivariate analyses. Together our data indicate that assessment of the SOCS1 mutation status is a single gene prognostic biomarker in DLBCL.

iBBiG: iterative binary bi-clustering of gene sets.

MOTIVATION: Meta-analysis of genomics data seeks to identify genes associated with a biological phenotype across multiple datasets; however, merging data from different platforms by their features (genes) is challenging. Meta-analysis using functionally or biologically characterized gene sets simplifies data integration is biologically intuitive and is seen as having great potential, but is an emerging field with few established statistical methods. RESULTS: We transform gene expression profiles into binary gene set profiles by discretizing results of gene set enrichment analyses and apply a new iterative bi-clustering algorithm (iBBiG) to identify groups of gene sets that are coordinately associated with groups of phenotypes across multiple studies. iBBiG is optimized for meta-analysis of large numbers of diverse genomics data that may have unmatched samples. It does not require prior knowledge of the number or size of clusters. When applied to simulated data, it outperforms commonly used clustering methods, discovers overlapping clusters of diverse sizes and is robust in the presence of noise. We apply it to meta-analysis of breast cancer studies, where iBBiG extracted novel gene set-phenotype association that predicted tumor metastases within tumor subtypes. AVAILABILITY: Implemented in the Bioconductor package iBBiG CONTACT: aedin@jimmy.harvard.edu.

Angiogenic mRNA and microRNA gene expression signature predicts a novel subtype of serous ovarian cancer.

Ovarian cancer is the fifth leading cause of cancer death for women in the U.S. and the seventh most fatal worldwide. Although ovarian cancer is notable for its initial sensitivity to platinum-based therapies, the vast majority of patients eventually develop recurrent cancer and succumb to increasingly platinum-resistant disease. Modern, targeted cancer drugs intervene in cell signaling, and identifying key disease mechanisms and pathways would greatly advance our treatment abilities. In order to shed light on the molecular diversity of ovarian cancer, we performed comprehensive transcriptional profiling on 129 advanced stage, high grade serous ovarian cancers. We implemented a, re-sampling based version of the ISIS class discovery algorithm (rISIS: robust ISIS) and applied it to the entire set of ovarian cancer transcriptional profiles. rISIS identified a previously undescribed patient stratification, further supported by micro-RNA expression profiles, and gene set enrichment analysis found strong biological support for the stratification by extracellular matrix, cell adhesion, and angiogenesis genes. The corresponding "angiogenesis signature" was validated in ten published independent ovarian cancer gene expression datasets and is significantly associated with overall survival. The subtypes we have defined are of potential translational interest as they may be relevant for identifying patients who may benefit from the addition of anti-angiogenic therapies that are now being tested in clinical trials.

High Myc activity is an independent negative prognostic factor for diffuse large B cell lymphomas.

Gene expression profiling has recently enabled the reclassification of aggressive non-Hodgkin lymphomas (aNHL) into distinct subgroups. In Burkitt lymphoma (BL) aberrant c-Myc activity results from IG-MYC translocations. However, MYC aberrations are not limited to BLs and then have a negative prognostic impact. In this study, we investigated to which extent aberrant c-Myc activity plays a functional role in other aNHL and whether it is independent from MYC translocations. Based on a combined microarray analysis of human germinal center (GC) B cells transfected with c-Myc and 220 aNHLs cases, we developed a "c-Myc index." This index measures the extent to which lymphomas express c-Myc responsive genes. It comprises genes that are affected in a variety of tumors compared to normal tissue. This supports the view that aberrant c-Myc expression in GC B cells triggers a tumor-like expression pattern. As expected, the "c-Myc index" is very high in molecular Burkitt lymphoma (mBL), but more importantly also high within other aNHL. It constitutes a negative prognostic marker independent of established risk factors and of the presence of a MYC translocation. Our data provide new insights into the role of c-Myc activity in different lymphomas and raises the question of treatment changes for those patients under risk.

Therapeutic implications of GIPC1 silencing in cancer.

GIPC1 is a cytoplasmic scaffold protein that interacts with numerous receptor signaling complexes, and emerging evidence suggests that it plays a role in tumorigenesis. GIPC1 is highly expressed in a number of human malignancies, including breast, ovarian, gastric, and pancreatic cancers. Suppression of GIPC1 in human pancreatic cancer cells inhibits in vivo tumor growth in immunodeficient mice. To better understand GIPC1 function, we suppressed its expression in human breast and colorectal cancer cell lines and human mammary epithelial cells (HMECs) and assayed both gene expression and cellular phenotype. Suppression of GIPC1 promotes apoptosis in MCF-7, MDA-MD231, SKBR-3, SW480, and SW620 cells and impairs anchorage-independent colony formation of HMECs. These observations indicate GIPC1 plays an essential role in oncogenic transformation, and its expression is necessary for the survival of human breast and colorectal cancer cells. Additionally, a GIPC1 knock-down gene signature was used to interrogate publically available breast and ovarian cancer microarray datasets. This GIPC1 signature statistically correlates with a number of breast and ovarian cancer phenotypes and clinical outcomes, including patient survival. Taken together, these data indicate that GIPC1 inhibition may represent a new target for therapeutic development for the treatment of human cancers.

Microarray-based genomic profiling reveals novel genomic aberrations in follicular lymphoma which associate with patient survival and gene expression status.

Follicular lymphoma (FL) is characterized by a large number of chromosomal aberrations. However, their exact genomic extension and involved target genes remain to be determined. For this purpose, we used array-based intermediate-high resolution genomic profiling in combination with Affymetrix gene expression analysis. Tumor specimens from 128 FL patients were analyzed for the presence of genomic aberrations and the results were correlated to clinical data sets and mRNA expression levels. In 114 (89%) of the 128 analyzed cases, a total of 688 genomic aberrations (384 gains/amplifications and 304 losses) were detected. Frequent genomic aberrations were: -1p36 (18%), +2p15 (24%), -3q (14%), -6q (25%), +7p (19%), +7q (23%), +8q (14%), -9p (16%), -11q (15%), +12q (20%), -13q (11%), -17p (16%), +18p (18%), and +18q (28%). Critical segments of these imbalances were delineated to genomic fragments with a minimum size down to 0.2 Mb. By comparison of these with mRNA gene expression data, putative candidate genes were identified. Moreover, we found that deletions affecting the tumor suppressor gene CDKN2A/B on 9p21 were detected in nontransformed FL grade I-II. For this aberration as well as for -6q25 and -6q26, an association with inferior survival was observed.

New insights into the biology and origin of mature aggressive B-cell lymphomas by combined epigenomic, genomic, and transcriptional profiling.

Lymphomas are assumed to originate at different stages of lymphocyte development through chromosomal aberrations. Thus, different lymphomas resemble lymphocytes at distinct differentiation stages and show characteristic morphologic, genetic, and transcriptional features. Here, we have performed a microarray-based DNA methylation profiling of 83 mature aggressive B-cell non-Hodgkin lymphomas (maB-NHLs) characterized for their morphologic, genetic, and transcriptional features, including molecular Burkitt lymphomas and diffuse large B-cell lymphomas. Hierarchic clustering indicated that methylation patterns in maB-NHLs were not strictly associated with morphologic, genetic, or transcriptional features. By supervised analyses, we identified 56 genes de novo methylated in all lymphoma subtypes studied and 22 methylated in a lymphoma subtype-specific manner. Remarkably, the group of genes de novo methylated in all lymphoma subtypes was significantly enriched for polycomb targets in embryonic stem cells. De novo methylated genes in all maB-NHLs studied were expressed at low levels in lymphomas and normal hematopoietic tissues but not in nonhematopoietic tissues. These findings, especially the enrichment for polycomb targets in stem cells, indicate that maB-NHLs with different morphologic, genetic, and transcriptional background share a similar stem cell-like epigenetic pattern. This suggests that maB-NHLs originate from cells with stem cell features or that stemness was acquired during lymphomagenesis by epigenetic remodeling.

Molecular profiling of pediatric mature B-cell lymphoma treated in population-based prospective clinical trials.

The spectrum of entities, the therapeutic strategy, and the outcome of mature aggressive B-cell non-Hodgkin lymphomas (maB-NHLs) differs between children and adolescents on the one hand and adult patients on the other. Whereas adult maB-NHLs have been studied in detail, data on molecular profiling of pediatric maB-NHLs are hitherto lacking. We analyzed 65 cases of maB-NHL from patients up to 18 years of age by gene expression profiling, matrix comparative genomic hybridization (CGH), fluorescent in situ hybridization (FISH), and immunohistochemistry. The majority of the analyzed pediatric patients were treated within prospective trials (n = 49). We compared this group to a series of 182 previously published cases of adult maB-NHL. Gene expression profiling reclassified 31% of morphologically defined diffuse large B-cell lymphomas as molecular Burkitt lymphoma (mBL). The subgroups obtained by molecular reclassification did not show any difference in outcome in children treated with the NHL-Berlin-Frankfurt-Muenster (BFM) protocols. No differences were detectable between pediatric and adult mBL with regard to gene expression or chromosomal imbalances. This is the first report on molecular profiling of pediatric B-NHL showing mBL to be much more prominent in children than suggested by morphologic assessment. Based on molecular profiling mBL is a molecularly homogeneous disease across children and adults.

Gain of chromosome region 18q21 including the MALT1 gene is associated with the activated B-cell-like gene expression subtype and increased BCL2 gene dosage and protein expression in diffuse large B-cell lymphoma.

BACKGROUND: The aim of this study was to determine the impact of a gain of the MALT1 gene on gene expression and clinical parameters in diffuse large B-cell lymphoma. DESIGN AND METHODS: We analyzed 116 cases of diffuse large B-cell lymphoma by fluorescence in situ hybridization, array-based comparative genomic hybridization, and transcriptional profiling. RESULTS: A gain of 18q21 including MALT1 was detected in 44 cases (38%) and was accompanied by a gain of BCL2 in 43 cases. All cases with a 18q21/MALT1 gain showed BCL2 protein whereas 79% in the group without a 18q21/MALT1 gain did so (p<0.001). Cases with 18q21/MALT1 gain more frequently showed an activated B-cell-like (ABC) gene expression signature (65%) than a germinal center B-cell-like (GCB) one (23%) (p<0.001). Ninety-eight genes including MALT1, BCL2, and some selected nuclear factor-kappaB target genes were differentially expressed between the two genetic groups of diffuse large B-cell lymphoma. By global testing of each chromosome, we identified 33 genes, all located on chromosome 18q, which were differentially expressed between the two genetic groups independently of the ABC/GCB status. In multivariate analysis, the 18q21/MALT1 status represented an independent negative prognostic factor for overall survival (p=0.03). CONCLUSIONS: In diffuse large B-cell lymphoma, gain of 18q21 including MALT1 is significantly associated with differential expression of genes located on 18q, the ABC gene expression subtype, increased BCL2 gene and protein expression and might indicate an unfavorable prognosis.

Detecting hierarchical structure in molecular characteristics of disease using transitive approximations of directed graphs.

MOTIVATION: Molecular diagnostics aims at classifying diseases into clinically relevant sub-entities based on molecular characteristics. Typically, the entities are split into subgroups, which might contain several variants yielding a hierarchical model of the disease. Recent years have introduced a plethora of new molecular screening technologies to molecular diagnostics. As a result molecular profiles of patients became complex and the classification task more difficult. RESULTS: We present a novel tool for detecting hierarchical structure in binary datasets. We aim for identifying molecular characteristics, which are stochastically implying other characteristics. The final hierarchical structure is encoded in a directed transitive graph where nodes represent molecular characteristics and a directed edge from a node A to a node B denotes that almost all cases with characteristic B also display characteristic A. Naturally, these graphs need to be transitive. In the core of our modeling approach lies the problem of calculating good transitive approximations of given directed but not necessarily transitive graphs. By good transitive approximation we understand transitive graphs, which differ from the reference graph in only a small number of edges. It is known that the problem of finding optimal transitive approximation is NP-complete. Here we develop an efficient heuristic for generating good transitive approximations. We evaluate the computational efficiency of the algorithm in simulations, and demonstrate its use in the context of a large genome-wide study on mature aggressive lymphomas. AVAILABILITY: The software used in our analysis is freely available from http://compdiag.uni-regensburg.de/software/transApproxs.shtml.

CD30-induced signaling is absent in Hodgkin's cells but present in anaplastic large cell lymphoma cells.

High CD30 expression in classical Hodgkin's lymphoma and anaplastic large cell lymphoma (ALCL) suggests an important pathogenic role of this cytokine receptor. To test this hypothesis, we investigated CD30 signaling in Hodgkin's and ALCL cell lines by different approaches: 1) CD30 stimulation, 2) CD30 down-regulation, and 3) a combination of both. The effects were determined at the RNA (microarray and real-time quantitative RT-PCR), protein (electrophoretic mobility shift analysis, immunoblot, and flow cytometry), and cellular/functional (proliferation and apoptosis) levels. We demonstrate that Hodgkin's cells are virtually CD30 unresponsive. Neither CD30 stimulation nor CD30 silencing of Hodgkin's cells had any significant effect. In contrast, CD30 stimulation of ALCL cells activated nuclear transcription factor-kappaB (NF-kappaB), induced major transcriptional changes, and decreased proliferation. These effects could be abrogated by down-regulation of CD30. Stimulation of CD30 in ALCL cells, stably transfected with a dominant-negative NF-kappaB inhibitor, induced pronounced caspase activation and massive apoptosis. Our data indicate that 1) CD30 signaling is not effective in Hodgkin's cell lines but is effective in ALCL cell lines, 2) CD30 is probably not significantly involved in the pathogenesis of classical Hodgkin's lymphoma, and 3) CD30 stimulation triggers two competing effects in ALCL cells, namely activation of caspases and NF-kappaB-mediated survival. These data suggest that CD30-targeted therapy in ALCL should be combined with NF-kappaB inhibitors to induce effective cell killing.

Ataxia telangiectasia-mutated gene is a possible biomarker for discrimination of infiltrative deep penetrating nevi and metastatic vertical growth phase melanoma.

The deep penetrating nevus (DPN) is a variant of benign melanocytic nevus with clinical and histologic features mimicking vertical growth phase, nodular malignant melanoma (NMM). Because fatal misdiagnosis such as NMM occurs in 29% to 40% of the DPN, molecular differentiation markers are highly desirable. Beyond the clinical demand for precise diagnosis and diagnosis-adapted, preventive therapeutic strategies, the DPN represents a valuable natural model for melanocytic invasion without metastatic potential that per se deserves further investigations. In the present study, at first, we used a genome-wide, microarray-based approach to systematically prescreen for possible molecular markers differentially expressed between selected cases of typical DPN (n=4) and metastatic NMM controls (n=4). Gene expression profiling was done on Affymetrix Human X3P microarrays. Of the 47,000 genes spotted, we identified a list of 227 transcripts, which remained significantly regulated at a false discovery rate of 5%. Subsequently, we verified the expression of a subset of the most interesting transcripts in a larger immunohistochemical series (DPN, n=17; NMM, n=16). Of these transcripts, three were selected for immunohistochemical confirmation: tissue inhibitor of metalloproteinase-2, tumor protein D52, and ataxia telangiectasia-mutated gene (ATM). Additional criteria for selection from the list of 227 significantly regulated transcripts were grouping into functional Ingenuity networks and a known melanoma- or cancer-relevant function. Following these criteria, we detected a highly significant up-regulation of ATM transcription in NMM, which was also mirrored by ATM protein up-regulation. In contrast to the other markers, ATM particularly might serve as a suitable diagnostic and reliable discriminator of DPN/NMM because ATM immunoreactivity also showed a reliable staining consistency within all samples of both entities.

Similarities of ordered gene lists.

MOTIVATION: Many applications of microarray technology in clinical cancer studies aim at detecting molecular features for refined diagnosis. In this paper, we follow an opposite rationale: we try to identify common molecular features shared by phenotypically distinct types of cancer using a meta-analysis of several microarray studies. We present a novel algorithm to uncover that two lists of differentially expressed genes are similar, even if these similarities are not apparent to the eye. The method is based on the ordering in the lists. RESULTS: In a meta-analysis of five clinical microarray studies we were able to detect significant similarities in five of the ten possible comparisons of ordered gene lists. We included studies, where not a single gene can be significantly associated to outcome. The detection of significant similarities of gene lists from different microarray studies is a novel and promising approach. It has the potential to improve upon specialized cancer studies by exploring the power of several studies in one single analysis. Our method is complementary to previous methods in that it does not rely on strong effects of differential gene expression in a single study but on consistent ones across multiple studies.

A biologic definition of Burkitt's lymphoma from transcriptional and genomic profiling.

BACKGROUND: The distinction between Burkitt's lymphoma and diffuse large-B-cell lymphoma is unclear. We used transcriptional and genomic profiling to define Burkitt's lymphoma more precisely and to distinguish subgroups in other types of mature aggressive B-cell lymphomas. METHODS: We performed gene-expression profiling using Affymetrix U133A GeneChips with RNA from 220 mature aggressive B-cell lymphomas, including a core group of 8 Burkitt's lymphomas that met all World Health Organization (WHO) criteria. A molecular signature for Burkitt's lymphoma was generated, and chromosomal abnormalities were detected with interphase fluorescence in situ hybridization and array-based comparative genomic hybridization. RESULTS: We used the molecular signature for Burkitt's lymphoma to identify 44 cases: 11 had the morphologic features of diffuse large-B-cell lymphomas, 4 were unclassifiable mature aggressive B-cell lymphomas, and 29 had a classic or atypical Burkitt's morphologic appearance. Also, five did not have a detectable IG-myc Burkitt's translocation, whereas the others contained an IG-myc fusion, mostly in simple karyotypes. Of the 176 lymphomas without the molecular signature for Burkitt's lymphoma, 155 were diffuse large-B-cell lymphomas. Of these 155 cases, 21 percent had a chromosomal breakpoint at the myc locus associated with complex chromosomal changes and an unfavorable clinical course. CONCLUSIONS: Our molecular definition of Burkitt's lymphoma clarifies and extends the spectrum of the WHO criteria for Burkitt's lymphoma. In mature aggressive B-cell lymphomas without a gene signature for Burkitt's lymphoma, chromosomal breakpoints at the myc locus were associated with an adverse clinical outcome.

Role of calcineurin in stress resistance, morphogenesis, and virulence of a Candida albicans wild-type strain.

By generating a calcineurin mutant of the Candida albicans wild-type strain SC5314 with the help of a new recyclable dominant selection marker, we confirmed that calcineurin mediates tolerance to a variety of stress conditions but is not required for the ability of C. albicans to switch to filamentous growth in response to hypha-inducing environmental signals. While calcineurin was essential for virulence of C. albicans in a mouse model of disseminated candidiasis, deletion of CMP1 did not significantly affect virulence during vaginal or pulmonary infection, demonstrating that the requirement for calcineurin for a successful infection depends on the host niche.

Detecting common gene expression patterns in multiple cancer outcome entities.

Most oncological microarray studies focus on molecular distinctions in different cancer entities. Recently, researchers started using microarrays for investigating molecular commonalities of multiple cancer types. This poses novel bioinformatics challenges. In this paper we describe a method that detects common molecular mechanisms in different cancer entities. The method extends previously described concepts by introducing Meta-Analysis Pattern Matches. In an analysis of four prognostic cancer studies, involving breast cancer, leukemia, and mesothelioma, we are able to identify 42 genes that show consistent up- or down-regulation in patients with a poor disease outcome. These genes complement the set of previously published candidates for universal prognostic markers in cancer.

The functional basis of mycophenolic acid resistance in Candida albicans IMP dehydrogenase.

Candida albicans is an important fungal pathogen of immunocompromised patients. In cell culture, C. albicans is sensitive to mycophenolic acid (MPA) and mizoribine, both natural product inhibitors of IMP dehydrogenase (IMPDH). These drugs have opposing interactions with the enzyme. MPA prevents formation of the closed enzyme conformation by binding to the same site as a mobile flap. In contrast, mizoribine monophosphate, the active metabolite of mizoribine, induces the closed conformation. Here, we report the characterization of IMPDH from wild-type and MPA-resistant strains of C. albicans. The wild-type enzyme displays significant differences from human IMPDHs, suggesting that selective inhibitors that could be novel antifungal agents may be developed. IMPDH from the MPA-resistant strain contains a single substitution (A251T) that is far from the MPA-binding site. The A251T variant was 4-fold less sensitive to MPA as expected. This substitution did not affect the k(cat) value, but did decrease the K(m) values for both substrates, so the mutant enzyme is more catalytically efficient as measured by the value of k(cat)/K(m). These simple criteria suggest that the A251T variant would be the evolutionarily superior enzyme. However, the A251T substitution caused the enzyme to be 40-fold more sensitive to mizoribine monophosphate. This result suggests that A251T stabilizes the closed conformation, and this hypothesis is supported by further inhibitor analysis. Likewise, the MPA-resistant strain was more sensitive to mizoribine in cell culture. These observations illustrate the evolutionary challenge posed by the gauntlet of chemical warfare at the microbial level.