Prognostication of Soft Tissue Sarcomas Based on Chromosome 17q Gene and Protein Status: Evaluation of TOP2A, HER-2/neu, and Survivin

Topoisomerase 2 alpha (), HER-2/ and are genes that lie on chromosome 17 and correlate with the prognosis and prediction of target-driven therapy against tumors. In a previous study, we showed that TOP2A transcripts levels were significantly higher in soft tissue sarcomas (STS) than in benign tumors and desmoid-type fibromatoses (FM). Because these genes have been insufficiently examined in STS, we aimed to identify alterations in TOP2A and HER-2 expression by fluorescent in situ hybridization and immunohistochemistry, as well as that of survivin, and correlate them with clinicopathologic findings to assess their prognostic value. Eighteen FM and 244 STS were included. Fluorescent in situ hybridization and immunohistochemistry were performed on a tissue microarray. TOP2A and survivin were more highly expressed in sarcomas than in FM. TOP2A was an independent predictor of an unfavorable prognosis; it was combined with formerly established prognostic factors (primarily histologic grade and tumor size at diagnosis) to create a prognostic index that evaluated overall survival. Gene amplification/polysomy (13%) did not correlate with protein overexpression. Survivin and HER-2 expression were not associated with patient outcomes. These findings might become valuable in the management of patients with STS and possibly in the prospective evaluation of responses to new target-driven therapies.

Prognostic significance of CD24 and claudin-7 immunoexpression in ductal invasive breast cancer

This study aimed to identify the CD24 and CD44 immunophenotypes within invasive ductal breast carcinoma (I DC) subgroups defined by immunohistochesmistry markers and to determine its influence on prognosis as well as its association with the expression of Ki-67, cytokeratins (CK5 and CK 18) and claudin-7. Immunohistochemical expression of CD44 and CD24 alone or in combination was investigated in 95 IDC cases arranged in a tissue microarray (TMA). The association with subgroups defined as luminal A and B; HER2 rich and triple negative, or with the other markers and prognosis was analyzed. CD44(+)/CD24(-) and CD44(-)/CD24(+) were respectively present in 8.4% and 16.8% of the tumors, a lack of both proteins was detected in 6.3%, while CD441(-)/CD24(+) was observed in 45.3% of the tumors. Although there was no significant correlation between subgroups and different phenotypes, the CD44(+)/CD24(-) phenotype was more common in the basal subgroups but absent in HER2 tumors, whereas luminal tumors are enriched in CD44(-)/CD24(+) and CD44(+)/CD24(+) cells. The frequency of CD44(+)/CD24(-) or CD44(-)/CD24(+) was not associated with clinical characteristics or biological markers. There was also no significant association of these phenotypes with the event free (DFS) and overall survival (OS). Single CD44(+) was evident in 57.9% of the tumors and was marginally associated to grading and not to any other tumor characteristics as well as OS and DFS. CD24(+) was positive in 74.7% of the tumors, showing a significant association with estrogen receptor, progesterone receptor and Ki-67 and a marginal association with CKI8 and claudin-7. Expression of claudin-7 and Ki-67 did not associate with the cancer subgroups, while a positive association between CK18 and the luminal subgroups was found (P=0.03). CK5, CK18 and Ki-67 expression had no influence in OS or DFS. Single CD24(+) (P=0.07) and claudin-7 positivity (P=0.05) were associated with reduced time of recurrence, suggesting a contribution of these markers to aggressiveness of breast cancer.

SET protein accumulates in HNSCC and contributes to cell survival: Antioxidant defense, Akt phosphorylation and AVOs acidification

Objectives: Determination of the SET protein levels in head and neck squamous cell carcinoma (HNSCC) tissue samples and the SET role in cell survival and response to oxidative stress in HNSCC cell lineages. Materials and Methods: SET protein was analyzed in 372 HNSCC tissue samples by immunohistochemistry using tissue microarray and HNSCC cell lineages. Oxidative stress was induced with the pro-oxidant tert-butylhydroperoxide (50 and 250 mu M) in the HNSCC HN13 cell lineage either with (siSET) or without (siNC) SET knockdown. Cell viability was evaluated by trypan blue exclusion and annexin V/propidium iodide assays. It was assessed caspase-3 and -9, PARP-1, DNA fragmentation, NM23-H1, SET, Akt and phosphorylated Akt (p-Akt) status. Acidic vesicular organelles (AVOs) were assessed by the acridine orange assay. Glutathione levels and transcripts of antioxidant genes were assayed by fluorometry and real time PCR, respectively. Results: SET levels were up-regulated in 97% tumor tissue samples and in HNSCC cell lineages. SiSET in HN13 cells (i) promoted cell death but did not induced caspases, PARP-1 cleavage or DNA fragmentation, and (ii) decreased resistance to death induced by oxidative stress, indicating SET involvement through caspase-independent mechanism. The red fluorescence induced by siSET in HN13 cells in the acridine orange assay suggests SET-dependent prevention of AVOs acidification. NM23-H1 protein was restricted to the cytoplasm of siSET/siNC HN13 cells under oxidative stress, in association with decrease of cleaved SET levels. In the presence of oxidative stress, siNC HN13 cells showed lower GSH antioxidant defense (GSH/GSSG ratio) but higher expression of the antioxidant genes PRDX6, SOD2 and TXN compared to siSET HN13 cells. Still under oxidative stress, p-Akt levels were increased in siNC HN13 cells but not in siSET HN13, indicating its involvement in HN13 cell survival. Similar results for the main SET effects were observed in HN12 and CAL 27 cell lineages, except that HN13 cells were more resistant to death. Conclusion: SET is potential (i) marker for HNSCC associated with cancer cell resistance and (ii) new target in cancer therapy. (C) 2012 Elsevier Ltd. All rights reserved.

Identification of protein expression signatures in gastric carcinomas using clustering analysis

Background and Aim: The identification of gastric carcinomas (GC) has traditionally been based on histomorphology. Recently, DNA microarrays have successfully been used to identify tumors through clustering of the expression profiles. Random forest clustering is widely used for tissue microarrays and other immunohistochemical data, because it handles highly-skewed tumor marker expressions well, and weighs the contribution of each marker according to its relatedness with other tumor markers. In the present study, we e identified biologically- and clinically-meaningful groups of GC by hierarchical clustering analysis of immunohistochemical protein expression. Methods: We selected 28 proteins (p16, p27, p21, cyclin D1, cyclin A, cyclin B1, pRb, p53, c-met, c-erbB-2, vascular endothelial growth factor, transforming growth factor [TGF]-beta I, TGF-beta II, MutS homolog-2, bcl-2, bax, bak, bcl-x, adenomatous polyposis coli, clathrin, E-cadherin, beta-catenin, mucin (MUC) 1, MUC2, MUC5AC, MUC6, matrix metalloproteinase [ MMP]-2, and MMP-9) to be investigated by immunohistochemistry in 482 GC. The analyses of the data were done using a random forest-clustering method. Results: Proteins related to cell cycle, growth factor, cell motility, cell adhesion, apoptosis, and matrix remodeling were highly expressed in GC. We identified protein expressions associated with poor survival in diffuse-type GC. Conclusions: Based on the expression analysis of 28 proteins, we identified two groups of GC that could not be explained by any clinicopathological variables, and a subgroup of long-surviving diffuse-type GC patients with a distinct molecular profile. These results provide not only a new molecular basis for understanding the biological properties of GC, but also better prediction of survival than the classic pathological grouping.

A Bayesian Approach for Decision Making on the Identification of Genes with Different Expression Levels: An Application to Escherichia coli Bacterium Data

A common interest in gene expression data analysis is to identify from a large pool of candidate genes the genes that present significant changes in expression levels between a treatment and a control biological condition. Usually, it is done using a statistic value and a cutoff value that are used to separate the genes differentially and nondifferentially expressed. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating sequentially credibility intervals from predictive densities which are constructed using the sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained report evidence that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a well-known publicly available data set on Escherichia coli bacterium.

Biochemical and metabolic profiles of Trichoderma strains isolated from common bean crops in the Brazilian Cerrado, and potential antagonism against Sclerotinia sclerotiorum

Some species of Trichoderma have successfully been used in the commercial biological control of fungal pathogens, e.g., Sclerotinia sclerotiorum, an economically important pathogen of common beans (Phaseolus vulgaris L.). The objectives of the present study were (1) to provide molecular characterization of Trichoderma strains isolated from the Brazilian Cerrado; (2) to assess the metabolic profile of each strain by means of Biolog FF Microplates; and (3) to evaluate the ability of each strain to antagonize S. sclerotiorum via the production of cell wall-degrading enzymes (CWDEs), volatile antibiotics, and dual-culture tests. Among 21 isolates, we identified 42.86 % as Trichoderma asperellum, 33.33 % as Trichoderma harzianum, 14.29 % as Trichoderma tomentosum, 4.76 % as Trichoderma koningiopsis, and 4.76 % as Trichoderma erinaceum. Trichoderma asperellum showed the highest CWDE activity. However, no species secreted a specific group of CWDEs. Trichoderma asperellum 364/01, T. asperellum 483/02, and T. asperellum 356/02 exhibited high and medium specific activities for key enzymes in the mycoparasitic process, but a low capacity for antagonism. We observed no significant correlation between CWDE and antagonism, or between metabolic profile and antagonism. The diversity of Trichoderma species, and in particular of T. harzianum, was clearly reflected in their metabolic profiles. Our findings indicate that the selection of Trichoderma candidates for biological control should be based primarily on the environmental fitness of competitive isolates and the target pathogen. (C) 2012 The British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Single-cell expression analysis of BMP15 and GDF9 in mature oocytes and BMPR2 in cumulus cells of women with polycystic ovary syndrome undergoing controlled ovarian hyperstimulation

To detect expression of bone morphogenetic protein 15 (BMP15) and growth differentiation factor 9 (GDF9) in oocytes, and their receptor type 2 receptor for BMPs (BMPR2) in cumulus cells in women with polycystic ovary syndrome (PCOS) undergoing in vitro fertilization (IVF), and determine if BMPR2, BMP15, and GDF9 expression correlate with hyperandrogenism in FF of PCOS patients. Prospective case-control study. Eighteen MII-oocytes and their respective cumulus cells were obtained from 18 patients with PCOS, and 48 MII-oocytes and cumulus cells (CCs) from 35 controls, both subjected to controlled ovarian hyperstimulation (COH), and follicular fluid (FF) was collected from small (10-14 mm) and large (> 18 mm) follicles. RNeasy Micro Kit (Qiagen(A (R))) was used for RNA extraction and gene expression was quantified in each oocyte individually and in microdissected cumulus cells from cumulus-oocyte complexes retrieved from preovulatory follicles using qRT-PCR. Chemiluminescence and RIA assays were used for hormone assays. BMP15 and GDF9 expression per oocyte was higher among women with PCOS than the control group. A positive correlation was found between BMPR2 transcripts and hyperandrogenism in FF of PCOS patients. Progesterone values in FF were lower in the PCOS group. We inferred that BMP15 and GDF9 transcript levels increase in mature PCOS oocytes after COH, and might inhibit the progesterone secretion by follicular cells in PCOS follicles, preventing premature luteinization in cumulus cells. BMPR2 expression in PCOS cumulus cells might be regulated by androgens.

Intratumoral Lymphatic Vessel Density in Vulvar Squamous Cell Carcinomas: A Possible Association With Favorable Prognosis

Lymphatic vessels serve as major routes for regional dissemination, and therefore, lymph node status is a key indicator of prognosis. To predict lymph node metastasis, tumor lymphatic density and lymphangiogenesis-related molecules have been studied in various tumor types. To our knowledge, no previous studies have evaluated the role of intratumoral lymphatic vessel density (LVD) in the behavior of vulvar carcinomas. The aim of this study was to analyze intratumoral LVD in relation to patient survival and well-characterized prognostic factors for cancer. Thirty-five patients with vulvar squamous cell carcinoma underwent vulvectomy and dissection of regional lymph nodes. Clinical records were reviewed, in addition to histological grade, peritumoral lymphatic invasion, and depth of infiltration for each case. Tissue microarray paraffin blocks were created, and lymphatic vessels were detected using immunohistochemical staining of podoplanin (D2-40 antibody). Intratumoral LVD was quantified by counting the number of stained vessels. Higher values for intratumoral LVD were associated with low-grade and low-stage tumors, and with tumors without lymphatic invasion and reduced stromal infiltration. In a univariate analysis, high intratumoral LVD was associated with a higher rate of overall survival and a lower rate of lymph node metastasis. Our results suggest that increased intratumoral LVD is associated with favorable prognosis in vulvar squamous carcinomas.

Combined expression of BUB1B, DLGAP5, and PINK1 as predictors of poor outcome in adrenocortical tumors: validation in a Brazilian cohort of adult and pediatric patients

Background: A recent microarray study identified a set of genes whose combined expression patterns were predictive of poor outcome in a cohort of adult adrenocortical tumors (ACTs). The difference between the expression values measured by qRT-PCR of DLGAP5 and PINK1 genes was the best molecular predictor of recurrence and malignancy. Among the adrenocortical carcinomas, the combined expression of BUB1B and PINK1 genes was the most reliable predictor of overall survival. The prognostic and molecular heterogeneity of ACTs raises the need to study the applicability of these molecular markers in other cohorts. Objective: To validate the combined expression of BUB1B, DLGAP5, and PINK1 as outcome predictor in ACTs from a Brazilian cohort of adult and pediatric patients. Patients and methods: BUB1B, DLGAP5, and PINK1 expression was assessed by quantitative PCR in 53 ACTs from 52 patients - 24 pediatric and 28 adults (one pediatric patient presented a bilateral asynchronous ACT). Results: DLGAP5 PINK1 and BUB1B PINK1 were strong predictors of disease-free survival and overall survival, respectively, among adult patients with ACT. In the pediatric cohort, these molecular predictors were only marginally associated with disease-free survival but not with overall survival. Conclusion: This study confirms the prognostic value of the combined expression of BUB1B, DLGAP5, and PINK1 genes in a Brazilian group of adult ACTs. Among pediatric ACTs, other molecular predictors of outcome are required.

A feature selection approach for identification of signature genes from SAGE data

Abstract Background One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements. Results A new framework to select specific genes that distinguish different biological states based on the analysis of SAGE data is proposed. The new framework applies the bolstered error for the identification of strong genes that separate the biological states in a feature space defined by the gene expression of a training set. Credibility intervals defined from a probabilistic model of SAGE measurements are used to identify the genes that distinguish the different states with more reliability among all gene groups selected by the strong genes method. A score taking into account the credibility and the bolstered error values in order to rank the groups of considered genes is proposed. Results obtained using SAGE data from gliomas are presented, thus corroborating the introduced methodology. Conclusion The model representing counting data, such as SAGE, provides additional statistical information that allows a more robust analysis. The additional statistical information provided by the probabilistic model is incorporated in the methodology described in the paper. The introduced method is suitable to identify signature genes that lead to a good separation of the biological states using SAGE and may be adapted for other counting methods such as Massive Parallel Signature Sequencing (MPSS) or the recent Sequencing-By-Synthesis (SBS) technique. Some of such genes identified by the proposed method may be useful to generate classifiers.

Simcluster: clustering enumeration gene expression data on the simplex space

Abstract Background Transcript enumeration methods such as SAGE, MPSS, and sequencing-by-synthesis EST "digital northern", are important high-throughput techniques for digital gene expression measurement. As other counting or voting processes, these measurements constitute compositional data exhibiting properties particular to the simplex space where the summation of the components is constrained. These properties are not present on regular Euclidean spaces, on which hybridization-based microarray data is often modeled. Therefore, pattern recognition methods commonly used for microarray data analysis may be non-informative for the data generated by transcript enumeration techniques since they ignore certain fundamental properties of this space. Results Here we present a software tool, Simcluster, designed to perform clustering analysis for data on the simplex space. We present Simcluster as a stand-alone command-line C package and as a user-friendly on-line tool. Both versions are available at: http://xerad.systemsbiology.net/simcluster. Conclusion Simcluster is designed in accordance with a well-established mathematical framework for compositional data analysis, which provides principled procedures for dealing with the simplex space, and is thus applicable in a number of contexts, including enumeration-based gene expression data.

GEDI: a user-friendly toolbox for analysis of large-scale gene expression data

Abstract Background Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experience difficulties when they attempting to use those methods in their research. Here we present an user-friendly toolbox which allows large-scale gene expression analysis to be carried out by biomedical researchers with limited programming skills. Results Here, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al. Conclusion GEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology.

Molecular determinants of caste differentiation in the highly eusocial honeybee Apis mellifera

Abstract Background In honeybees, differential feeding of female larvae promotes the occurrence of two different phenotypes, a queen and a worker, from identical genotypes, through incremental alterations, which affect general growth, and character state alterations that result in the presence or absence of specific structures. Although previous studies revealed a link between incremental alterations and differential expression of physiometabolic genes, the molecular changes accompanying character state alterations remain unknown. Results By using cDNA microarray analyses of >6,000 Apis mellifera ESTs, we found 240 differentially expressed genes (DEGs) between developing queens and workers. Many genes recorded as up-regulated in prospective workers appear to be unique to A. mellifera, suggesting that the workers' developmental pathway involves the participation of novel genes. Workers up-regulate more developmental genes than queens, whereas queens up-regulate a greater proportion of physiometabolic genes, including genes coding for metabolic enzymes and genes whose products are known to regulate the rate of mass-transforming processes and the general growth of the organism (e.g., tor). Many DEGs are likely to be involved in processes favoring the development of caste-biased structures, like brain, legs and ovaries, as well as genes that code for cytoskeleton constituents. Treatment of developing worker larvae with juvenile hormone (JH) revealed 52 JH responsive genes, specifically during the critical period of caste development. Using Gibbs sampling and Expectation Maximization algorithms, we discovered eight overrepresented cis-elements from four gene groups. Graph theory and complex networks concepts were adopted to attain powerful graphical representations of the interrelation between cis-elements and genes and objectively quantify the degree of relationship between these entities. Conclusion We suggest that clusters of functionally related DEGs are co-regulated during caste development in honeybees. This network of interactions is activated by nutrition-driven stimuli in early larval stages. Our data are consistent with the hypothesis that JH is a key component of the developmental determination of queen-like characters. Finally, we propose a conceptual model of caste differentiation in A. mellifera based on gene-regulatory networks.

Global transcriptional response of Caulobacter crescentus to iron availability

Abstract Background In the alpha subclass of proteobacteria iron homeostasis is controlled by diverse iron responsive regulators. Caulobacter crescentus, an important freshwater α-proteobacterium, uses the ferric uptake repressor (Fur) for such purpose. However, the impact of the iron availability on the C. crescentus transcriptome and an overall perspective of the regulatory networks involved remain unknown. Results In this work we report the identification of iron-responsive and Fur-regulated genes in C. crescentus using microarray-based global transcriptional analyses. We identified 42 genes that were strongly upregulated both by mutation of fur and by iron limitation condition. Among them, there are genes involved in iron uptake (four TonB-dependent receptor gene clusters, and feoAB), riboflavin biosynthesis and genes encoding hypothetical proteins. Most of these genes are associated with predicted Fur binding sites, implicating them as direct targets of Fur-mediated repression. These data were validated by β-galactosidase and EMSA assays for two operons encoding putative transporters. The role of Fur as a positive regulator is also evident, given that 27 genes were downregulated both by mutation of fur and under low-iron condition. As expected, this group includes many genes involved in energy metabolism, mostly iron-using enzymes. Surprisingly, included in this group are also TonB-dependent receptors genes and the genes fixK, fixT and ftrB encoding an oxygen signaling network required for growth during hypoxia. Bioinformatics analyses suggest that positive regulation by Fur is mainly indirect. In addition to the Fur modulon, iron limitation altered expression of 113 more genes, including induction of genes involved in Fe-S cluster assembly, oxidative stress and heat shock response, as well as repression of genes implicated in amino acid metabolism, chemotaxis and motility. Conclusions Using a global transcriptional approach, we determined the C. crescentus iron stimulon. Many but not all of iron responsive genes were directly or indirectly controlled by Fur. The iron limitation stimulon overlaps with other regulatory systems, such as the RpoH and FixK regulons. Altogether, our results showed that adaptation of C. crescentus to iron limitation not only involves increasing the transcription of iron-acquisition systems and decreasing the production of iron-using proteins, but also includes novel genes and regulatory mechanisms.

Cell organisation, sulphur metabolism and ion transport-related genes are differentially expressed in Paracoccidioides brasiliensis mycelium and yeast cells

Abstract Background Mycelium-to-yeast transition in the human host is essential for pathogenicity by the fungus Paracoccidioides brasiliensis and both cell types are therefore critical to the establishment of paracoccidioidomycosis (PCM), a systemic mycosis endemic to Latin America. The infected population is of about 10 million individuals, 2% of whom will eventually develop the disease. Previously, transcriptome analysis of mycelium and yeast cells resulted in the assembly of 6,022 sequence groups. Gene expression analysis, using both in silico EST subtraction and cDNA microarray, revealed genes that were differential to yeast or mycelium, and we discussed those involved in sugar metabolism. To advance our understanding of molecular mechanisms of dimorphic transition, we performed an extended analysis of gene expression profiles using the methods mentioned above. Results In this work, continuous data mining revealed 66 new differentially expressed sequences that were MIPS(Munich Information Center for Protein Sequences)-categorised according to the cellular process in which they are presumably involved. Two well represented classes were chosen for further analysis: (i) control of cell organisation – cell wall, membrane and cytoskeleton, whose representatives were hex (encoding for a hexagonal peroxisome protein), bgl (encoding for a 1,3-β-glucosidase) in mycelium cells; and ags (an α-1,3-glucan synthase), cda (a chitin deacetylase) and vrp (a verprolin) in yeast cells; (ii) ion metabolism and transport – two genes putatively implicated in ion transport were confirmed to be highly expressed in mycelium cells – isc and ktp, respectively an iron-sulphur cluster-like protein and a cation transporter; and a putative P-type cation pump (pct) in yeast. Also, several enzymes from the cysteine de novo biosynthesis pathway were shown to be up regulated in the yeast form, including ATP sulphurylase, APS kinase and also PAPS reductase. Conclusion Taken together, these data show that several genes involved in cell organisation and ion metabolism/transport are expressed differentially along dimorphic transition. Hyper expression in yeast of the enzymes of sulphur metabolism reinforced that this metabolic pathway could be important for this process. Understanding these changes by functional analysis of such genes may lead to a better understanding of the infective process, thus providing new targets and strategies to control PCM.