Sonata Jarmalaite

Aberrant p16 promoter methylation in smokers and former smokers with nonsmall cell lung cancer.

Hypermethylation of cytosines in CpG‐rich islands of the promoter regions of regulatory genes has been discovered as a common mechanism of gene silencing during carcinogenesis. We analysed 64 primary lung carcinomas for promoter methylation of the tumour suppressor genes (TSGs) p16 (p16INK4a/CDKN2A) and p14 (p14ARF) by methylation‐specific PCR, in order to evaluate aberrant methylation as a potential biomarker for epigenetic alterations in tobacco‐related lung cancer. Methylation of p16 was observed in 34% (22/64) of the lung tumours examined. In particular, p16 methylation occurred in nonsmall cell lung cancer (NSCLC) only, with 41 % (22/54) of the tumours being positive. The highest frequency was found in large cell carcinoma (5/7, 71%), followed by adenocarcinoma (9/25, 36%) and squamous cell carcinoma (7/21, 33%). Methylation of the p14 gene was less frequent in lung cancer (4/52, 8%). When association with tobacco smoking was analysed, 42% (21/50) of NSCLC from ever smokers exhibited p16 methylation. Interestingly, the analysis revealed a significantly higher risk of p16 methylation in former smokers as compared to current smokers [odds ratio (OR) 5.1; 95% confidence interval (CI) 1.3–22]. The difference was retained after adjustment for age (OR 3.7; 95% CI 0.9–17). The promoter methylation results were then combined with data on genetic alterations determined previously in the same set of tumours. This data similarly showed that p16 methylation in parallel with p53 gene mutation or p14 methylation occurred more frequently in former smokers than in current smokers (44% vs. 14%; P = 0.035). Taken together, our data suggest that analysis of promoter methylation in TSGs may provide a valuable biomarker for identification of groups with an elevated risk of cancer, such as smokers and ex‐smokers.

Immunohistochemistry profiles of breast ductal carcinoma: factor analysis of digital image analysis data

BackgroundMolecular studies of breast cancer revealed biological heterogeneity of the disease and opened new perspectives for personalized therapy. While multiple gene expression-based systems have been developed, current clinical practice is largely based upon conventional clinical and pathologic criteria. This gap may be filled by development of combined multi-IHC indices to characterize biological and clinical behaviour of the tumours. Digital image analysis (DA) with multivariate statistics of the data opens new opportunities in this field.MethodsTissue microarrays of 109 patients with breast ductal carcinoma were stained for a set of 10 IHC markers (ER, PR, HER2, Ki67, AR, BCL2, HIF-1α, SATB1, p53, and p16). Aperio imaging platform with the Genie, Nuclear and Membrane algorithms were used for the DA. Factor analysis of the DA data was performed in the whole group and hormone receptor (HR) positive subgroup of the patients (n = 85).ResultsMajor factor potentially reflecting aggressive disease behaviour (i-Grade) was extracted, characterized by opposite loadings of ER/PR/AR/BCL2 and Ki67/HIF-1α. The i-Grade factor scores revealed bimodal distribution and were strongly associated with higher Nottingham histological grade (G) and more aggressive intrinsic subtypes. In HR-positive tumours, the aggressiveness of the tumour was best defined by positive Ki67 and negative ER loadings. High Ki67/ER factor scores were strongly associated with the higher G and Luminal B types, but also were detected in a set of G1 and Luminal A cases, potentially indicating high risk patients in these categories. Inverse relation between HER2 and PR expression was found in the HR-positive tumours pointing at differential information conveyed by the ER and PR expression. SATB1 along with HIF-1α reflected the second major factor of variation in our patients; in the HR-positive group they were inversely associated with the HR and BCL2 expression and represented the major factor of variation. Finally, we confirmed high expression levels of p16 in Triple-negative tumours.ConclusionFactor analysis of multiple IHC biomarkers measured by automated DA is an efficient exploratory tool clarifying complex interdependencies in the breast ductal carcinoma IHC profiles and informative value of single IHC markers. Integrated IHC indices may provide additional risk stratifications for the currently used grading systems and prove to be useful in clinical outcome studies.Virtual SlidesThe virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1512077125668949

Membrane connectivity estimated by digital image analysis of HER2 immunohistochemistry is concordant with visual scoring and fluorescence in situ hybridization results: algorithm evaluation on breast cancer tissue microarrays

IntroductionThe human epidermal growth factor receptor 2 (HER2) is an established biomarker for management of patients with breast cancer. While conventional testing of HER2 protein expression is based on semi-quantitative visual scoring of the immunohistochemistry (IHC) result, efforts to reduce inter-observer variation and to produce continuous estimates of the IHC data are potentiated by digital image analysis technologies.MethodsHER2 IHC was performed on the tissue microarrays (TMAs) of 195 patients with an early ductal carcinoma of the breast. Digital images of the IHC slides were obtained by Aperio ScanScope GL Slide Scanner. Membrane connectivity algorithm (HER2-CONNECT™, Visiopharm) was used for digital image analysis (DA). A pathologist evaluated the images on the screen twice (visual evaluations: VE1 and VE2). HER2 fluorescence in situ hybridization (FISH) was performed on the corresponding sections of the TMAs. The agreement between the IHC HER2 scores, obtained by VE1, VE2, and DA was tested for individual TMA spots and patients maximum TMA spot values (VE1max, VE2max, DAmax). The latter were compared with the FISH data. Correlation of the continuous variable of the membrane connectivity estimate with the FISH data was tested.ResultsThe pathologist intra-observer agreement (VE1 and VE2) on HER2 IHC score was almost perfect: kappa 0.91 (by spot) and 0.88 (by patient). The agreement between visual evaluation and digital image analysis was almost perfect at the spot level (kappa 0.86 and 0.87, with VE1 and VE2 respectively) and at the patient level (kappa 0.80 and 0.86, with VE1max and VE2max, respectively). The DA was more accurate than VE in detection of FISH-positive patients by recruiting 3 or 2 additional FISH-positive patients to the IHC score 2+ category from the IHC 0/1+ category by VE1max or VE2max, respectively. The DA continuous variable of the membrane connectivity correlated with the FISH data (HER2 and CEP17 copy numbers, and HER2/CEP17 ratio).ConclusionHER2 IHC digital image analysis based on membrane connectivity estimate was in almost perfect agreement with the visual evaluation of the pathologist and more accurate in detection of HER2 FISH-positive patients. Most immediate benefit of integrating the DA algorithm into the routine pathology HER2 testing may be obtained by alerting/reassuring pathologists of potentially misinterpreted IHC 0/1+ versus 2+ cases.Virtual SlidesThe virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1973465132560208.

Epigenetic markers of prostate cancer in plasma circulating DNA

Epigenetic differences are a common feature of many diseases, including cancer, and disease-associated changes have even been detected in bodily fluids. DNA modification studies in circulating DNA (cirDNA) may lead to the development of specific non-invasive biomarkers. To test this hypothesis, we investigated cirDNA modifications in prostate cancer patients with locally confined disease (n = 19), in patients with benign prostate hyperplasias (n = 20) and in men without any known prostate disease (n = 20). This initial discovery screen identified 39 disease-associated changes in cirDNA modification, and seven of these were validated using the sodium bisulfite-based mapping of modified cytosines in both the discovery cohort and an independent 38-patient validation cohort. In particular, we showed that the DNA modification of regions adjacent to the gene encoding ring finger protein 219 distinguished prostate cancer from benign hyperplasias with good sensitivity (61%) and specificity (71%). We also showed that repetitive sequences detected in this study were meaningful, as they indicated a highly statistically significant loss of DNA at the pericentromeric region of chromosome 10 in prostate cancer patients (p = 1.8 × 10(-6)). Based on these strong univariate results, we applied machine-learning techniques to develop a multi-locus biomarker that correctly distinguished prostate cancer samples from unaffected controls with 72% accuracy. Lastly, we used systems biology techniques to integrate our data with publicly available DNA modification and transcriptomic data from primary prostate tumors, thereby prioritizing genes for further studies. These data suggest that cirDNA epigenomics are promising source for non-invasive biomarkers.

The utility of urine-circulating miRNAs for detection of prostate cancer.

Background:In this paper, the utility of urine-circulating microRNAs (miRNAs) as the potential biomarker of prostate cancer (PCa), the second most prevalent male cancer worldwide, was evaluated.Methods:Cancerous (N=56) and non-cancerous (N=16) prostate tissues were analysed on TaqMan Low Density Array, with the initial screening of 754 miRNAs in a subset of the samples. The abundance of selected miRNAs was analysed in urine specimens from two independent cohorts of patients with PCa (N=215 overall), benign prostatic hyperplasia (BPH; N=23), and asymptomatic controls (ASC; N=62) by means of quantitative reverse transcription PCR.Results:Over 100 miRNAs were found deregulated in PCa as compared with non-cancerous prostate tissue. After thorough validation, four miRNAs were selected for the analysis in urine specimens. The abundance of miR-148a and miR-375 in urine was identified as specific biomarkers of PCa in both cohorts. Combined analysis of urine-circulating miR-148a and miR-375 was highly sensitive and specific for PCa in both cohorts (AUC=0.79 and 0.84) and strongly improved the diagnostic power of the PSA test (AUC=0.85, cohort PCa1), including the grey diagnostic zone (AUC=0.90).Conclusions:Quantitative measurement of urine-circulating miR-148a and miR-375 can serve as the non-invasive tool for sensitive and specific detection of PCa.

Analysis of Deregulated microRNAs and Their Target Genes in Gastric Cancer.

Background MicroRNAs (miRNAs) are widely studied non-coding RNAs that modulate gene expression. MiRNAs are deregulated in different tumors including gastric cancer (GC) and have potential diagnostic and prognostic implications. The aim of our study was to determine miRNA profile in GC tissues, followed by evaluation of deregulated miRNAs in plasma of GC patients. Using available databases and bioinformatics methods we also aimed to evaluate potential target genes of confirmed differentially expressed miRNA and validate these findings in GC tissues. Methods The study included 51 GC patients and 51 controls. Initially, we screened miRNA expression profile in 13 tissue samples of GC and 12 normal gastric tissues with TaqMan low density array (TLDA). In the second stage, differentially expressed miRNAs were validated in a replication cohort using qRT-PCR in tissue and plasma samples. Subsequently, we analyzed potential target genes of deregulated miRNAs using bioinformatics approach, determined their expression in GC tissues and performed correlation analysis with targeting miRNAs. Results Profiling with TLDA revealed 15 deregulated miRNAs in GC tissues compared to normal gastric mucosa. Replication analysis confirmed that miR-148a-3p, miR-204-5p, miR-223-3p and miR-375 were consistently deregulated in GC tissues. Analysis of GC patients’ plasma samples showed significant down-regulation of miR-148a-3p, miR-375 and up-regulation of miR-223-3p compared to healthy subjects. Further, using bioinformatic tools we identified targets of replicated miRNAs and performed disease-associated gene enrichment analysis. Ultimately, we evaluated potential target gene BCL2 and DNMT3B expression by qRT-PCR in GC tissue, which correlated with targeting miRNA expression. Conclusions Our study revealed miRNA profile in GC tissues and showed that miR-148a-3p, miR-223-3p and miR-375 are deregulated in GC plasma samples, but these circulating miRNAs showed relatively weak diagnostic performance as sole biomarkers. Target gene analysis demonstrated that BCL2 and DNMT3B expression in GC tissue correlated with their targeting miRNA expression.

Combined Analysis of TMPRSS2-ERG and TERT for Improved Prognosis of Biochemical Recurrence in Prostate Cancer

Prostate cancer (PCa) is a heterogeneous disease with diverse clinical outcomes. TMPRSS2–ERG is the most common gene fusion in PCa, whereas activation of telomerase is a common feature of various malignancies. The aim of our study was to explore the combined utility of these and some other biomarkers in predicting biochemical recurrence after radical prostatectomy. Prostate specimens and urine sediments from 179 previously untreated patients with pT2‐pT3 stage PCa were analyzed for expression of telomerase (TERT and TR) and the TMPRSS2–ERG fusion gene by means of reverse transcription PCR. Real‐time PCR was used for quantification of ERG and SPINK1 expression. In total, 74% (117/158) of the prostate adenocarcinomas were positive for the TMPRSS2–ERG and/or TERT expression. Noninvasively, these transcripts were identified in 31% (19/61) of catheterized urine specimens. Significantly higher expression of ERG was detected in TMPRSS2–ERG‐positive tumors (P < 0.0001), whereas more intense expression of SPINK1 was characteristic for the TMPRSS2–ERG‐negative tumors (P = 0.003). TERT‐positive cases also had elevated levels of ERG (P = 0.016), suggesting a possible link between aberrant expression of ERG and reactivation of TERT in prostate tumors. The cases negative for both transcripts, TMPRSS2–ERG and TERT, rarely recurred (P = 0.014) and showed significantly longer biochemical recurrence‐free period (P = 0.022) as compared to the TMPRSS2–ERG and/or TERT‐positive cases. The results of our study suggest that combined analysis of TMPRSS2–ERG and TERT expression can be a valuable tool for early prediction of biochemical recurrence of PCa after radical prostatectomy.

Frequent down-regulation of ABC transporter genes in prostate cancer.

BackgroundATP-binding cassette (ABC) transporters are transmembrane proteins responsible for the efflux of a wide variety of substrates, including steroid metabolites, through the cellular membranes. For better characterization of the role of ABC transporters in prostate cancer (PCa) development, the profile of ABC transporter gene expression was analyzed in PCa and noncancerous prostate tissues (NPT).MethodsTaqMan Low Density Array (TLDA) human ABC transporter plates were used for the gene expression profiling in 10 PCa and 6 NPT specimens. ABCB1 transcript level was evaluated in a larger set of PCa cases (N = 78) and NPT (N = 15) by real-time PCR, the same PCa cases were assessed for the gene promoter hypermethylation by methylation-specific PCR.ResultsExpression of eight ABC transporter genes (ABCA8, ABCB1, ABCC6, ABCC9, ABCC10, ABCD2, ABCG2, and ABCG4) was significantly down-regulated in PCa as compared to NPT, and only two genes (ABCC4 and ABCG1) were up-regulated. Down-regulation of ABC transporter genes was prevalent in the TMPRSS2-ERG-negative cases.A detailed analysis of ABCB1 expression confirmed TLDA results: a reduced level of the transcript was identified in PCa in comparison to NPT (p = 0.048). Moreover, the TMPRSS2-ERG-negative PCa cases showed significantly lower expression of ABCB1 in comparison to NPT (p = 0.003) or the fusion-positive tumors (p = 0.002). Promoter methylation of ABCB1 predominantly occurred in PCa and was rarely detected in NPT (p < 0.001).ConclusionsThe study suggests frequent down-regulation of the ABC transporter genes in PCa, especially in the TMPRSS2-ERG-negative tumors.

Clinical significance of miRNA host gene promoter methylation in prostate cancer

Abstract Only a part of prostate cancer (PCa) patients has aggressive malignancy requiring adjuvant treatment after radical prostatectomy (RP). Biomarkers capable to predict biochemical PCa recurrence (BCR) after RP would significantly improve preoperative risk stratification and treatment decisions. MicroRNA (miRNA) deregulation has recently emerged as an important phenomenon in tumor development and progression, however, the mechanisms remain largely unstudied. In the present study, based on microarray profiling of DNA methylation in 9 pairs of PCa and noncancerous prostate tissues (NPT), host genes of miR‐155‐5p, miR‐152‐3p, miR‐137, miR‐31‐5p, and miR‐642a, ‐b were analyzed for promoter methylation in 129 PCa, 35 NPT, and 17 benign prostatic hyperplasia samples (BPH) and compared to the expression of mature miRNAs and their selected targets (DNMT1, KDM1A, and KDM5B). The Cancer Genome Atlas dataset was utilized for validation. Methylation of mir‐155, mir‐152, and mir‐137 host genes was PCa‐specific, and downregulation of miR‐155‐5p significantly correlated with promoter methylation. Higher KDM5B expression was observed in samples with methylated mir‐155 or mir‐137 promoters, whereas upregulation of KDM1A and DNMT1 was associated with mir‐155 and mir‐152 methylation status, respectively. Promoter methylation of mir‐155, mir‐152, and mir‐31 was predictive of BCR‐free survival in various Cox models and increased the prognostic value of clinicopathologic factors. In conclusion, methylated mir‐155, mir‐152, mir‐137, and mir‐31 host genes are promising diagnostic and/or prognostic biomarkers of PCa. Methylation status of particular miRNA host genes as independent variables or in combinations might assist physicians in identifying poor prognosis PCa patients preoperatively.

MiRNA profiling of gastrointestinal stromal tumors by next-generation sequencing

Deregulation of miRNAs has been observed virtually in all major types of cancer, whereas the miRNA signature in GIST is not well characterized yet. In this study the first high-throughput miRNA profiling of 15 paired GIST and adjacent normal tissue samples was performed using small RNA-seq approach and differentially expressed miRNAs as well as isomiRNAs were defined. Highly significantly deregulated miRNAs were selected for validation by Taq-Man low-density array in replication group of 40 paired samples. Validated miRNAs were further subjected to enrichment analysis, which revealed significantly enriched KEGG pathways in the main GIST associated pathways. Further, we used an integrated analysis of miRNA-mRNA correlations for KIT and PDGFRA target genes and found a significant correlation between all of the enriched miRNAs and their target gene KIT. Results of the phenotype analysis showed miR-509-3p to be up-regulated in epithelioid and mixed cell types compared to spindle type, whereas miR-215-5p showed negative correlation with risk grade of GIST. These data reveal a detailed miRNA profile of GIST and highlight new candidates that may be important in the development of malignant disease.