Integrated Analysis of Multiple Microarray Datasets Identifies a Reproducible Survival Predictor in Ovarian Cancer

BACKGROUND: Public data integration may help overcome challenges in clinical implementation of microarray profiles. We integrated several ovarian cancer datasets to identify a reproducible predictor of survival. METHODOLOGY/PRINCIPAL FINDINGS: Four microarray datasets from different institutions comprising 265 advanced stage tumors were uniformly reprocessed into a single training dataset, also adjusting for inter-laboratory variation ("batch-effect"). Supervised principal component survival analysis was employed to identify prognostic models. Models were independently validated in a 61-patient cohort using a custom array genechip and a publicly available 229-array dataset. Molecular correspondence of high- and low-risk outcome groups between training and validation datasets was demonstrated using Subclass Mapping. Previously established molecular phenotypes in the 2(nd) validation set were correlated with high and low-risk outcome groups. Functional representational and pathway analysis was used to explore gene networks associated with high and low risk phenotypes. A 19-gene model showed optimal performance in the training set (median OS 31 and 78 months, p < 0.01), 1(st) validation set (median OS 32 months versus not-yet-reached, p = 0.026) and 2(nd) validation set (median OS 43 versus 61 months, p = 0.013) maintaining independent prognostic power in multivariate analysis. There was strong molecular correspondence of the respective high- and low-risk tumors between training and 1(st) validation set. Low and high-risk tumors were enriched for favorable and unfavorable molecular subtypes and pathways, previously defined in the public 2(nd) validation set. CONCLUSIONS/SIGNIFICANCE: Integration of previously generated cancer microarray datasets may lead to robust and widely applicable survival predictors. These predictors are not simply a compilation of prognostic genes but appear to track true molecular phenotypes of good- and poor-outcome

NRF2-driven miR-125B1 and miR-29B1 transcriptional regulation controls a novel anti-apoptotic miRNA regulatory network for AML survival

Transcription factor NRF2 is an important regulator of oxidative stress. It is involved in cancer progression, and has abnormal constitutive expression in acute myeloid leukaemia (AML). Posttranscriptional regulation by microRNAs (miRNAs) can affect the malignant phenotype of AML cells. In this study, we identified and characterised NRF2-regulated miRNAs in AML. An miRNA array identified miRNA expression level changes in response to NRF2 knockdown in AML cells. Further analysis of miRNAs concomitantly regulated by knockdown of the NRF2 inhibitor KEAP1 revealed the major candidate NRF2-mediated miRNAs in AML. We identified miR-125B to be upregulated and miR-29B to be downregulated by NRF2 in AML. Subsequent bioinformatic analysis identified putative NRF2 binding sites upstream of the miR-125B1 coding region and downstream of the mir-29B1 coding region. Chromatin immunoprecipitation analyses showed that NRF2 binds to these antioxidant response elements (AREs) located in the 5′ untranslated regions of miR-125B and miR-29B. Finally, primary AML samples transfected with anti-miR-125B antagomiR or miR-29B mimic showed increased cell death responsiveness either alone or co-treated with standard AML chemotherapy. In summary, we find that NRF2 regulation of miR-125B and miR-29B acts to promote leukaemic cell survival, and their manipulation enhances AML responsiveness towards cytotoxic chemotherapeutics

Purine Nucleoside Phosphorylase mediated molecular chemotherapy and conventional chemotherapy: A tangible union against chemoresistant cancer

Background Late stage Ovarian Cancer is essentially incurable primarily due to late diagnosis and its inherent heterogeneity. Single agent treatments are inadequate and generally lead to severe side effects at therapeutic doses. It is crucial to develop clinically relevant novel combination regimens involving synergistic modalities that target a wider repertoire of cells and lead to lowered individual doses. Stemming from this premise, this is the first report of two- and three-way synergies between Adenovirus-mediated Purine Nucleoside Phosphorylase based gene directed enzyme prodrug therapy (PNP-GDEPT), docetaxel and/or carboplatin in multidrug-resistant ovarian cancer cells. Methods The effects of PNP-GDEPT on different cellular processes were determined using Shotgun Proteomics analyses. The in vitro cell growth inhibition in differentially treated drug resistant human ovarian cancer cell lines was established using a cell-viability assay. The extent of synergy, additivity, or antagonism between treatments was evaluated using CalcuSyn statistical analyses. The involvement of apoptosis and implicated proteins in effects of different treatments was established using flow cytometry based detection of M30 (an early marker of apoptosis), cell cycle analyses and finally western blot based analyses. Results Efficacy of the trimodal treatment was significantly greater than that achieved with bimodal- or individual treatments with potential for 10-50 fold dose reduction compared to that required for individual treatments. Of note was the marked enhancement in apoptosis that specifically accompanied the combinations that included PNP-GDEPT and accordingly correlated with a shift in the expression of anti- and pro-apoptotic proteins. PNP-GDEPT mediated enhancement of apoptosis was reinforced by cell cycle analyses. Proteomic analyses of PNP-GDEPT treated cells indicated a dowregulation of proteins involved in oncogenesis or cancer drug resistance in treated cells with accompanying upregulation of apoptotic- and tumour- suppressor proteins. Conclusion Inclusion of PNP-GDEPT in regular chemotherapy regimens can lead to significant enhancement of the cancer cell susceptibility to the combined treatment. Overall, these data will underpin the development of regimens that can benefit patients with late stage ovarian cancer leading to significantly improved efficacy and increased quality of life

GWAS Meets Microarray: Are the Results of Genome-Wide Association Studies and Gene-Expression Profiling Consistent? Prostate Cancer as an Example

Genome-wide association studies (GWASs) and global profiling of gene expression (microarrays) are two major technological breakthroughs that allow hypothesis-free identification of candidate genes associated with tumorigenesis. It is not obvious whether there is a consistency between the candidate genes identified by GWAS (GWAS genes) and those identified by profiling gene expression (microarray genes).We used the Cancer Genetic Markers Susceptibility database to retrieve single nucleotide polymorphisms from candidate genes for prostate cancer. In addition, we conducted a large meta-analysis of gene expression data in normal prostate and prostate tumor tissue. We identified 13,905 genes that were interrogated by both GWASs and microarrays. On the basis of P values from GWASs, we selected 1,649 most significantly associated genes for functional annotation by the Database for Annotation, Visualization and Integrated Discovery. We also conducted functional annotation analysis using same number of the top genes identified in the meta-analysis of the gene expression data. We found that genes involved in cell adhesion were overrepresented among both the GWAS and microarray genes.We conclude that the results of these analyses suggest that combining GWAS and microarray data would be a more effective approach than analyzing individual datasets and can help to refine the identification of candidate genes and functions associated with tumor development

Quantitative copy number analysis by Multiplex Ligation-dependent Probe Amplification (MLPA) of BRCA1-associated breast cancer regions identifies BRCAness

Our group has previously employed array Comparative Genomic Hybridization (aCGH) to assess the genomic patterns of BRCA1-mutated breast cancers. We have shown that the so-called BRCA1-like(aCGH) profile is also present in about half of all triple-negative sporadic breast cancers and is predictive for benefit from intensified alkylating chemotherapy. As aCGH is a rather complex method, we translated the BRCA1(aCGH) profile to a Multiplex Ligation-dependent Probe Amplification (MLPA) assay, to identify both BRCA1-mutated breast cancers and sporadic cases with a BRCA1-like(aCGH) profile. The most important genomic regions of the original aCGH based classifier (3q22-27, 5q12-14, 6p23-22, 12p13, 12q21-23, 13q31-34) were mapped to a set of 34 MLPA probes. The training set consisted of 39 BRCA1-like(aCGH) breast cancers and 45 non-BRCA1-like(aCGH) breast cancers, which had previously been analyzed by aCGH. The BRCA1-like(aCGH) group consisted of germline BRCA1-mutated cases and sporadic tumours with low BRCA1 gene expression and/or BRCA1 promoter methylation. We trained a shrunken centroids classifier on the training set and validation was performed on an independent test set of 40 BRCA1-like(aCGH) breast cancers and 32 non-BRCA1-like(aCGH) breast cancer tumours. In addition, we validated the set prospectively on 69 new triple-negative tumours. BRCAness in the training set of 84 tumours could accurately be predicted by prediction analysis of microarrays (PAM) (accuracy 94%). Application of this classifier on the independent validation set correctly predicted BRCA-like status of 62 out of 72 breast tumours (86%). Sensitivity and specificity were 85% and 87%, respectively. When the MLPA-test was subsequently applied to 46 breast tumour samples from a randomized clinical trial, the same survival benefit for BRCA1-like tumours associated with intensified alkylating chemotherapy was shown as was previously reported using the aCGH assay. Since the MLPA assay can identify BRCA1-deficient breast cancer patients, this method could be applied both for clinical genetic testing and as a predictor of treatment benefit. BRCA1-like tumours are highly sensitive to chemotherapy with DNA damaging agents, and most likely to poly ADP ribose polymerase (PARP)-inhibitors. The MLPA assay is rapid and robust, can easily be multiplexed, and works well with DNA derived from paraffin-embedded tissue

Epidermal Stem Cells Are Defined by Global Histone Modifications that Are Altered by Myc-Induced Differentiation

Activation of Myc induces epidermal stem cells to exit their niche and differentiate into sebocytes and interfollicular epidermis, a process that is associated with widespread changes in gene transcription. We have identified chromatin modifications that are characteristic of epidermal stem cells and investigated the effects of Myc activation. Quiescent stem cells in the interfollicular epidermis and the hair follicle bulge had high levels of tri-methylated histone H3 at lysine 9 and H4 at lysine 20. Chromatin in both stem cell populations was hypoacteylated at histone H4 and lacked mono-methylation of histone H4 at lysine 20. Myc-induced exit from the stem cell niche correlated with increased acetylation at histone H4 and transiently increased mono-methylation at lysine 20. The latter was replaced by epigenetic modifications that are largely associated with chromatin silencing: di-methylation at histone H3 lysine 9 and histone H4 lysine 20. These modifications correlated with changes in the specific histone methyltransferases Set8 and Ash-1. The Myc-induced switch from mono- to di-methylated H4K20 required HDAC activity and was blocked by the HDAC inhibitor trichostatin A (TSA). TSA treatment induced a similar epidermal phenotype to activation of Myc, and activation of Myc in the presence of TSA resulted in massive stimulation of terminal differentiation. We conclude that Myc-induced chromatin modifications play a major role in Myc-induced exit from the stem cell compartment

Oncoproteomic Analysis Reveals Co-Upregulation of RELA and STAT5 in Carboplatin Resistant Ovarian Carcinoma

Ovarian cancer is one of the most lethal types of female malignancy. Although most patients are initially responsive to platinum-based chemotherapy, almost all develop recurrent chemoresistant tumors and succumb to their diseases. Elucidating the pathogenesis underlying drug resistance is fundamental to the development of new therapeutics, leading to improved clinical outcomes in these patients.We compared the proteomes of paired primary and recurrent post-chemotherapy ovarian high-grade serous carcinomas from nine ovarian cancer patients using CIEF/Nano-RPLC coupled with ESI-Tandem MS. As compared to their primary tumors, more than half of the recurrent tumors expressed higher levels of several proteins including CP, FN1, SYK, CD97, AIF1, WNK1, SERPINA3, APOD, URP2, STAT5B and RELA (NF-kappaB p65), which were also validated by quantitative RT-PCR. Based on shRNA screening for the upregulated genes in in vitro carboplatin-resistant cells, we found that simultaneous knockdown of RELA and STAT5B was most effective in sensitizing tumor cells for carboplatin treatment. Similarly, the NF-kappaB inhibitor, BMS-345541, and the STAT5 inhibitor, Dasatinib, significantly enhanced cell sensitivity to carboplatin. Moreover, both RELA and STAT5 are known to bind to the promoter region of Bcl-X, regulating its promoter activity. In this regard, augmented Bcl-xL expression was detected in carboplatin-resistant cells. Combined ectopic expression of RELA and STAT5B enhanced Bcl-xL promoter activity while treatment with BMS-345541 and Dasatinib decreased it. Chromatin immunoprecipitation of the Bcl-X promoter region using a STAT5 antibody showed induction of RELA and STAT5 DNA-binding segments both in naïve cells treated with a high concentration of carboplatin as well as in carboplatin-resistant cells.Proteomic analysis identified RELA and STAT5 as two major proteins associated with carboplatin resistance in ovarian tumors. Our results further showed that NF-kappaB and STAT5 inhibitor could sensitize carboplatin-resistant cells and suggest that such inhibitors can be used to benefit patients with carboplatin-resistant recurrent ovarian cancer

The HDAC Inhibitor FK228 Enhances Adenoviral Transgene Expression by a Transduction-Independent Mechanism but Does Not Increase Adenovirus Replication

The histone deacetylase inhibitor FK228 has previously been shown to enhance adenoviral transgene expression when cells are pre-incubated with the drug. Upregulation of the coxsackie adenovirus receptor (CAR), leading to increased viral transduction, has been proposed as the main mechanism. In the present study, we found that the highest increase in transgene expression was achieved when non-toxic concentrations of FK228 were added immediately after transduction, demonstrating that the main effect by which FK228 enhances transgene expression is transduction-independent. FK228 had positive effects both on Ad5 and Ad5/f35 vectors with a variety of transgenes and promoters, indicating that FK228 works mainly by increasing transgene expression at the transcriptional level. In some cases, the effects were dramatic, as demonstrated by an increase in CD40L expression by FK228 from 0.3% to 62% when the murine prostate cancer cell line TRAMP-C2 was transduced with Ad[CD40L]. One unexpected finding was that FK228 decreased the transgene expression of an adenoviral vector with the prostate cell-specific PPT promoter in the human prostate adenocarcinoma cell lines LNCaP and PC-346C. This is probably a consequence of alteration of the adenocarcinoma cell lines towards a neuroendocrine differentiation after FK228 treatment. The observations in this study indicate that FK228 enhances adenoviral therapy by a transduction-independent mechanism. Furthermore, since histone deacetylase inhibitors may affect the differentiation of cells, it is important to keep in mind that the activity and specificity of tissue- and tumor-specific promoters may also be affected

RASOnD - A comprehensive resource and search tool for RAS superfamily oncogenes from various species

<p>Abstract</p> <p>Background</p> <p>The Ras superfamily plays an important role in the control of cell signalling and division. Mutations in the Ras genes convert them into active oncogenes. The Ras oncogenes form a major thrust of global cancer research as they are involved in the development and progression of tumors. This has resulted in the exponential growth of data on Ras superfamily across different public databases and in literature. However, no dedicated public resource is currently available for data mining and analysis on this family. The present database was developed to facilitate straightforward accession, retrieval and analysis of information available on Ras oncogenes from one particular site.</p> <p>Description</p> <p>We have developed the RAS Oncogene Database (RASOnD) as a comprehensive knowledgebase that provides integrated and curated information on a single platform for oncogenes of Ras superfamily. RASOnD encompasses exhaustive genomics and proteomics data existing across diverse publicly accessible databases. This resource presently includes overall 199,046 entries from 101 different species. It provides a search tool to generate information about their nucleotide and amino acid sequences, single nucleotide polymorphisms, chromosome positions, orthologies, motifs, structures, related pathways and associated diseases. We have implemented a number of user-friendly search interfaces and sequence analysis tools. At present the user can (i) browse the data (ii) search any field through a simple or advance search interface and (iii) perform a BLAST search and subsequently CLUSTALW multiple sequence alignment by selecting sequences of Ras oncogenes. The Generic gene browser, GBrowse, JMOL for structural visualization and TREEVIEW for phylograms have been integrated for clear perception of retrieved data. External links to related databases have been included in RASOnD.</p> <p>Conclusions</p> <p>This database is a resource and search tool dedicated to Ras oncogenes. It has utility to cancer biologists and cell molecular biologists as it is a ready source for research, identification and elucidation of the role of these oncogenes. The data generated can be used for understanding the relationship between the Ras oncogenes and their association with cancer. The database updated monthly is freely accessible online at <url>http://202.141.47.181/rasond/</url> and <url>http://www.aiims.edu/RAS.html</url>.</p