Project description:BACKGROUND: Promoter hypermethylation coupled with loss of heterozygosity at the same locus results in loss of gene function in many tumor cells. The "rules" governing which genes are methylated during the pathogenesis of individual cancers, how specific methylation profiles are initially established, or what determines tumor type-specific methylation are unknown. However, DNA methylation markers that are highly specific and sensitive for common tumors would be useful for the early detection of cancer, and those required for the malignant phenotype would identify pathways important as therapeutic targets. METHODS AND FINDINGS: In an effort to identify new cancer-specific methylation markers, we employed a high-throughput global expression profiling approach in lung cancer cells. We identified 132 genes that have 5' CpG islands, are induced from undetectable levels by 5-aza-2'-deoxycytidine in multiple non-small cell lung cancer cell lines, and are expressed in immortalized human bronchial epithelial cells. As expected, these genes were also expressed in normal lung, but often not in companion primary lung cancers. Methylation analysis of a subset (45/132) of these promoter regions in primary lung cancer (n = 20) and adjacent nonmalignant tissue (n = 20) showed that 31 genes had acquired methylation in the tumors, but did not show methylation in normal lung or peripheral blood cells. We studied the eight most frequently and specifically methylated genes from our lung cancer dataset in breast cancer (n = 37), colon cancer (n = 24), and prostate cancer (n = 24) along with counterpart nonmalignant tissues. We found that seven loci were frequently methylated in both breast and lung cancers, with four showing extensive methylation in all four epithelial tumors. CONCLUSIONS: By using a systematic biological screen we identified multiple genes that are methylated with high penetrance in primary lung, breast, colon, and prostate cancers. The cross-tumor methylation pattern we observed for these novel markers suggests that we have identified a partial promoter hypermethylation signature for these common malignancies. These data suggest that while tumors in different tissues vary substantially with respect to gene expression, there may be commonalities in their promoter methylation profiles that represent targets for early detection screening or therapeutic intervention. Experiment Overall Design: We compared the gene expression changes HBEC and NSCLC cells before and after treatment with 5-aza-2'deoxycytidine.

Project description:BACKGROUND:Heritable factors are evidently involved in prostate cancer (PrCa) carcinogenesis, but currently, genetic markers are not routinely used in screening or diagnostics of the disease. More precise information is needed for making treatment decisions to distinguish aggressive cases from indolent disease, for which heritable factors could be a useful tool. The genetic makeup of PrCa has only recently begun to be unravelled through large-scale genome-wide association studies (GWAS). The thus far identified Single Nucleotide Polymorphisms (SNPs) explain, however, only a fraction of familial clustering. Moreover, the known risk SNPs are not associated with the clinical outcome of the disease, such as aggressive or metastasised disease, and therefore cannot be used to predict the prognosis. Annotating the SNPs with deep clinical data together with miRNA expression profiles can improve the understanding of the underlying mechanisms of different phenotypes of prostate cancer. RESULTS:In this study microRNA (miRNA) profiles were studied as potential biomarkers to predict the disease outcome. The study subjects were from Finnish high risk prostate cancer families. To identify potential biomarkers we combined a novel non-parametrical test with an importance measure provided from a Random Forest classifier. This combination delivered a set of nine miRNAs that was able to separate cases from controls. The detected miRNA expression profiles could predict the development of the disease years before the actual PrCa diagnosis or detect the existence of other cancers in the studied individuals. Furthermore, using an expression Quantitative Trait Loci (eQTL) analysis, regulatory SNPs for miRNA miR-483-3p that were also directly associated with PrCa were found. CONCLUSION:Based on our findings, we suggest that blood-based miRNA expression profiling can be used in the diagnosis and maybe even prognosis of the disease. In the future, miRNA profiling could possibly be used in targeted screening, together with Prostate Specific Antigene (PSA) testing, to identify men with an elevated PrCa risk.

Project description:The prostate stroma is a key mediator of epithelial differentiation and development, and potentially plays a role in the initiation and progression of prostate cancer. Isolation and characterization of viable populations of the constituent cell types of prostate tumors could provide valuable insight into the biology of cancer. The CD90+ stromal fibromuscular cells from tumor specimens were isolated by cell-sorting and analyzed by DNA microarray. Dataset analysis was used to compare gene expression between normal and tumor-associated reactive stromal cells. Reactive stroma is characterized by smooth muscle differentiation, prostate down-regulation of SPOCK3, MSMB, CXCL13, and PAGE4, bladder down-regulation of TRPA1, HSD17B2, IL24, and SALL1, and an up-regulation of CXC-chemokines. This study identified a group of differentially expressed genes in CD90+ reactive stromal cells that are potentially involved in organ development and smooth muscle cell differentiation. Experiment Overall Design: A total of 15 arrays were run for the following sample types obtained from 10 patients: Experiment Overall Design: 2 CD90+ prostate tumor-associated stromal: Experiment Overall Design: Patient 1: CP_Str_08-028_CD90posi Experiment Overall Design: Patient 2: 08-032_CP_strom_CD90posi Experiment Overall Design: 2 CD13+ normal bladder stromal: Experiment Overall Design: Patient 3: 06-125_NB_CD13posi Experiment Overall Design: Patient 4: 06-070_NB_str_CD13posi Experiment Overall Design: 1 CD13+ bladder tumor-associated stromal: Experiment Overall Design: Patient 5: 07-008_CB_str_CD13posi Experiment Overall Design: 5 whole tissue prostate cancer and 5 normal tissue from matched pairs: Experiment Overall Design: Patient 6: 05-206_CaP, 05-206_NP Experiment Overall Design: Patient 7: 05-213_CaP, 05-213_NP Experiment Overall Design: Patient 8: 05-214_CaP, 05-214_NP Experiment Overall Design: Patient 9: 05-218_CaP, 05-218_NP Experiment Overall Design: Patient 10: 05-220_CaP, 05-220_NP Experiment Overall Design: Additionally, 8 arrays were run for the following sample types obtained from 7 patients: Experiment Overall Design: 5 CD49a+ normal prostate stromal (PMID 16638148): Experiment Overall Design: Patient 1: CD49a_01-26-04 Experiment Overall Design: Patient 2: CD49a_03-23-04 Experiment Overall Design: Patient 3: CD49a_03-04-04 Experiment Overall Design: Patient 4: CD49a-1_06-02-04 Experiment Overall Design: Patient 5: CD49a-4_06-02-04 Experiment Overall Design: 3 CD26+ prostate cancer (2 biological replicates, 1 sample run twice): Experiment Overall Design: Patient 6: 05-179_CD26t Experiment Overall Design: Patient 6: 05-179_CD26t_2 Experiment Overall Design: Patient 7: 08-032_CP_epi_CD26posi Experiment Overall Design: The following two prostate cancer samples were also included in the analyses: Experiment Overall Design: CD26+ cancer cell, replicate 1 Experiment Overall Design: CD26+ cancer cell, replicate 2 Experiment Overall Design: The tissue samples consisted of prostate tissue specimens obtained from patients undergoing radical prostatectomy under approval by the University of Washington Institutional Review Board. The same approach was used for both cancer-free and cancer-enriched (where at least 85% of the cells in the corresponding frozen section were of cancer) samples. To obtain bladder stromal cells for analysis, tissue specimens were obtained from cystoprostatectomy surgeries. For cell sorting, the collected specimens were processed within hours. Cell types were sorted using monoclonal antibodies specific for tumor-associated prostate stromal cells (CD90), tumor-associated bladder stromal cells (CD13) and normal bladder stromal cells (CD13) with MACS.

Project description:Approximately 25% of hereditary breast cancer cases associated with a strong familial history can be explained by mutations in BRCA1 or BRCA2 and other lower penetrance genes. The remaining high-risk families could be classified as BRCAX (non-BRCA1/2) families, in which no penetrant mutation has been found until now. Gene expression involving alternative splicing represents a well-known mechanism regulating the expression of multiple transcripts encoded by individual genes, which could be involved in cancer development. Thus using RNA-seq methodology, the analysis of transcriptome in immortalized lymphoblastoid cell lines of high-risk breast cancer individuals could reveal transcripts implicated in breast cancer susceptibility and development. RNA was extracted from immortalized lymphoblastoid cell lines of 117 women (affected and unaffected) coming from BRCA1, BRCA2 and BRCAX families. Anova analysis revealed a total of 95 transcripts corresponding to 85 different genes differentially expressed (Bonferroni corrected p-value <0.01) between those groups. Hierarchical clustering allowed distinctive subgrouping of BRCA1/2 subgroups from BRCAX individuals, without regard for the cancer status. We found enrichment for pathways in signaling cascades including mTOR and EIF2-related pathways. No transcripts were differentially expressed between BRCA1 and BRCA2 individuals, however out of 95 transcripts, 67 could discriminate BRCAX from combination of BRCA1 and BRCA2 individuals. On the other hand, 28 transcripts could discriminate affected from unaffected BRCAX individuals. These BRCAX-associated transcripts demonstrated enrichment in Telomere Extension by Telomerase and Double-Strand Break Repair by Non-Homologous End Joining mechanisms. To our knowledge, this represents the first study identifying transcripts differentially expressed in immortalized lymphoblastoid cell lines coming from the major classes of mutation-related breast cancer subgroups, namely BRCA1, BRCA2 and BRCAX. Moreover, some transcripts could discriminate affected from unaffected BRCAX individuals, which could represent potential therapeutic targets for breast cancer treatment.

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MiRNA profiles in Lymphoblastoid Cell Lines of Finnish Prostate Cancer Families

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