Frequent down-regulation of ABC transporter genes in prostate cancer

Background: ATP-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). Methods: TaqMan 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. Results: Expression 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). Conclusions: The study suggests frequent down-regulation of the ABC transporter genes in PCa, especially in the TMPRSS2-ERG-negative tumors

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

<p>Abstract</p> <p>Introduction</p> <p>The 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.</p> <p>Methods</p> <p>HER2 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 <it>in situ </it>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 patient's 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.</p> <p>Results</p> <p>The 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).</p> <p>Conclusion</p> <p>HER2 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.</p

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

<p>Abstract</p> <p>Background</p> <p>Molecular 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.</p> <p>Methods</p> <p>Tissue 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).</p> <p>Results</p> <p>Major 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.</p> <p>Conclusion</p> <p>Factor 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.</p> <p>Virtual Slides</p> <p>The virtual slide(s) for this article can be found here: <url>http://www.diagnosticpathology.diagnomx.eu/vs/1512077125668949</url></p

Towards a European Health Research and Innovation Cloud (HRIC)

The European Union (EU) initiative on the Digital Transformation of Health and Care (Digicare) aims to provide the conditions necessary for building a secure, flexible, and decentralized digital health infrastructure. Creating a European Health Research and Innovation Cloud (HRIC) within this environment should enable data sharing and analysis for health research across the EU, in compliance with data protection legislation while preserving the full trust of the participants. Such a HRIC should learn from and build on existing data infrastructures, integrate best practices, and focus on the concrete needs of the community in terms of technologies, governance, management, regulation, and ethics requirements. Here, we describe the vision and expected benefits of digital data sharing in health research activities and present a roadmap that fosters the opportunities while answering the challenges of implementing a HRIC. For this, we put forward five specific recommendations and action points to ensure that a European HRIC: i) is built on established standards and guidelines, providing cloud technologies through an open and decentralized infrastructure; ii) is developed and certified to the highest standards of interoperability and data security that can be trusted by all stakeholders; iii) is supported by a robust ethical and legal framework that is compliant with the EU General Data Protection Regulation (GDPR); iv) establishes a proper environment for the training of new generations of data and medical scientists; and v) stimulates research and innovation in transnational collaborations through public and private initiatives and partnerships funded by the EU through Horizon 2020 and Horizon Europe

Epigenetic Biomarkers of Renal Cell Carcinoma for Liquid Biopsy Tests

Renal cell carcinomas (RCC) account for 2–3% of the global cancer burden and are characterized by the highest mortality rate among all genitourinary cancers. However, excluding conventional imagining approaches, there are no reliable diagnostic and prognostic tools available for clinical use at present. Liquid biopsies, such as urine, serum, and plasma, contain a significant amount of tumor-derived nucleic acids, which may serve as non-invasive biomarkers that are particularly useful for early cancer detection, follow-up, and personalization of treatment. Changes in epigenetic phenomena, such as DNA methylation level, expression of microRNAs (miRNAs), and long noncoding RNAs (lncRNAs), are observed early during cancer development and are easily detectable in biofluids when morphological changes are still undetermined by conventional diagnostic tools. Here, we reviewed recent advances made in the development of liquid biopsy-derived DNA methylation-, miRNAs- and lncRNAs-based biomarkers for RCC, with an emphasis on the performance characteristics. In the last two decades, a mass of circulating epigenetic biomarkers of RCC were suggested, however, most of the studies done thus far analyzed biomarkers selected from the literature, used relatively miniature, local, and heterogeneous cohorts, and suffered from a lack of sufficient validations. In summary, for improved translation into the clinical setting, there is considerable demand for the validation of the existing pool of RCC biomarkers and the discovery of novel ones with better performance and clinical utility

Surveillance of cfDNA Hot Spot Mutations in NSCLC Patients during Disease Progression

Non-small cell cancer (NSCLC) has been identified with a great variation of mutations that can be surveyed during disease progression. The aim of the study was to identify and monitor lung cancer-specific mutations incidence in cell-free DNA as well as overall plasma cell-free DNA load by means of targeted next-generation sequencing. Sequencing libraries were prepared from cell-free DNA (cfDNA) isolated from 72 plasma samples of 41 patients using the Oncomine Lung cfDNA panel covering hot spot regions of 11 genes. Sequencing was performed with the Ion Torrent™ Ion S5™ system. Four genes were detected with highest mutation incidence: KRAS (43.9% of all cases), followed by ALK (36.6%), TP53 (31.7%), and PIK3CA (29.3%). Seven patients had co-occurring KRAS + TP53 (6/41, 14.6%) or KRAS + PIK3CA (7/41, 17.1%) mutations. Moreover, the mutational status of TP53 as well an overall cell-free DNA load were confirmed to be predictors of poor progression-free survival (HR = 2.5 [0.8–7.7]; p = 0.029 and HR = 2.3 [0.9–5.5]; p = 0.029, respectively) in NSCLC patients. In addition, TP53 mutation status significantly predicts shorter overall survival (HR = 3.4 [1.2–9.7]; p TP53 mutation incidence as well as a cell-free DNA load can be used as biomarkers for NSCLC monitoring and can help to detect the disease progression prior to radiological confirmation of the status