Arvydas Laurinavicius

Preclinical study of SZ2080 material 3D microstructured scaffolds for cartilage tissue engineering made by femtosecond direct laser writing lithography

Over the last decade DLW employing ultrafast pulsed lasers has become a well-established technique for the creation of custom-made free-form three-dimensional (3D) microscaffolds out of a variety of materials ranging from proteins to biocompatible glasses. Its potential applications for manufacturing a patients specific scaffold seem unlimited in terms of spatial resolution and geometry complexity. However, despite few exceptions in which live cells or primitive organisms were encapsulated into a polymer matrix, no demonstration of an in vivo study case of scaffolds generated with the use of such a method was performed. Here, we report a preclinical study of 3D artificial microstructured scaffolds out of hybrid organic-inorganic (HOI) material SZ2080 fabricated using the DLW technique. The created 2.1 × 2.1 × 0.21 mm(3) membrane constructs are tested both in vitro by growing isolated allogeneic rabbit chondrocytes (Cho) and in vivo by implanting them into rabbit organisms for one, three and six months. An ex vivo histological examination shows that certain pore geometry and the pre-growing of Cho prior to implantation significantly improves the performance of the created 3D scaffolds. The achieved biocompatibility is comparable to the commercially available collagen membranes. The successful outcome of this study supports the idea that hexagonal-pore-shaped HOI microstructured scaffolds in combination with Cho seeding may be successfully implemented for cartilage tissue engineering.

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

A methodology to ensure and improve accuracy of Ki67 labelling index estimation by automated digital image analysis in breast cancer tissue

IntroductionImmunohistochemical Ki67 labelling index (Ki67 LI) reflects proliferative activity and is a potential prognostic/predictive marker of breast cancer. However, its clinical utility is hindered by the lack of standardized measurement methodologies. Besides tissue heterogeneity aspects, the key element of methodology remains accurate estimation of Ki67-stained/counterstained tumour cell profiles. We aimed to develop a methodology to ensure and improve accuracy of the digital image analysis (DIA) approach.MethodsTissue microarrays (one 1-mm spot per patient, n = 164) from invasive ductal breast carcinoma were stained for Ki67 and scanned. Criterion standard (Ki67-Count) was obtained by counting positive and negative tumour cell profiles using a stereology grid overlaid on a spot image. DIA was performed with Aperio Genie/Nuclear algorithms. A bias was estimated by ANOVA, correlation and regression analyses. Calibration steps of the DIA by adjusting the algorithm settings were performed: first, by subjective DIA quality assessment (DIA-1), and second, to compensate the bias established (DIA-2). Visual estimate (Ki67-VE) on the same images was performed by five pathologists independently.ResultsANOVA revealed significant underestimation bias (P < 0.05) for DIA-0, DIA-1 and two pathologists’ VE, while DIA-2, VE-median and three other VEs were within the same range. Regression analyses revealed best accuracy for the DIA-2 (R-square = 0.90) exceeding that of VE-median, individual VEs and other DIA settings. Bidirectional bias for the DIA-2 with overestimation at low, and underestimation at high ends of the scale was detected. Measurement error correction by inverse regression was applied to improve DIA-2-based prediction of the Ki67-Count, in particular for the clinically relevant interval of Ki67-Count < 40%. Potential clinical impact of the prediction was tested by dichotomising the cases at the cut-off values of 10, 15, and 20%. Misclassification rate of 5-7% was achieved, compared to that of 11-18% for the VE-median-based prediction.ConclusionsOur experiments provide methodology to achieve accurate Ki67-LI estimation by DIA, based on proper validation, calibration, and measurement error correction procedures, guided by quantified bias from reference values obtained by stereology grid count. This basic validation step is an important prerequisite for high-throughput automated DIA applications to investigate tissue heterogeneity and clinical utility aspects of Ki67 and other immunohistochemistry (IHC) biomarkers.

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.

DNA methylation at the putative promoter region of the human dopamine D2 receptor gene.

DNA methylation was investigated in the putative promoter region of the human dopamine D2 receptor gene (DRD2). Twenty-two DNA samples from two types of cells differentially expressing D2 receptors, striatum and lymphocytes, were subjected to bisulphite modification-based mapping of methylated cytosines. In the tested region, the DNA from lymphocytes exhibited a significantly higher degree of methylation than that from striata. In addition, a significantly higher proportion of methylated to unmethylated cytosines was detected in DRD2 from the right than the left striatum, and a trend towards a greater degree of methylation was detected in older than in younger individuals. These DRD2 methylation findings are consistent with dopamine D2 receptor binding data from the literature which support the idea that DNA methylation plays a role in regulation of DRD2 expression.

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.

Recent advances in standards for Collaborative Digital Anatomic Pathology.

ContextCollaborative Digital Anatomic Pathology refers to the use of information technology that supports the creation and sharing or exchange of information, including data and images, during the complex workflow performed in an Anatomic Pathology department from specimen reception to report transmission and exploitation. Collaborative Digital Anatomic Pathology can only be fully achieved using medical informatics standards. The goal of the international integrating the Healthcare Enterprise (IHE) initiative is precisely specifying how medical informatics standards should be implemented to meet specific health care needs and making systems integration more efficient and less expensive.ObjectiveTo define the best use of medical informatics standards in order to share and exchange machine-readable structured reports and their evidences (including whole slide images) within hospitals and across healthcare facilities.MethodsSpecific working groups dedicated to Anatomy Pathology within multiple standards organizations defined standard-based data structures for Anatomic Pathology reports and images as well as informatic transactions in order to integrate Anatomic Pathology information into the electronic healthcare enterprise.ResultsThe DICOM supplements 122 and 145 provide flexible object information definitions dedicated respectively to specimen description and Whole Slide Image acquisition, storage and display. The content profile “Anatomic Pathology Structured Report” (APSR) provides standard templates for structured reports in which textual observations may be bound to digital images or regions of interest. Anatomic Pathology observations are encoded using an international controlled vocabulary defined by the IHE Anatomic Pathology domain that is currently being mapped to SNOMED CT concepts.ConclusionRecent advances in standards for Collaborative Digital Anatomic Pathology are a unique opportunity to share or exchange Anatomic Pathology structured reports that are interoperable at an international level. The use of machine-readable format of APSR supports the development of decision support as well as secondary use of Anatomic Pathology information for epidemiology or clinical research.

Non‐linear optical microscopy of kidney tumours

The unregulated cancer cell growth leads to strong alterations in morphology and composition of the tissue. The combination of coherent anti-Stokes Raman scattering, two-photon excited fluorescence and second harmonic generation enables a high resolution imaging with strong information on tissue composition and can then provide useful information for tumour diagnosis. Here we present the potential of multimodal non-linear microscopy for imaging of renal tumours. Using cryosections of human oncocytoma and carcinoma, the method gave a detailed insight in cancer morphology and composition, enabling to discern between normal kidney tissue, tumour and necrosis. Several features significant for the diagnosis were clearly visualised without use of any staining. Translation of this method in clinical pathology will greatly improve speed and quality of the analyses.

Slow progressive FSGS associated with an F392L WT1 mutation

Constitutional missense mutations in the WT1 gene are usually associated with the Denys-Drash syndrome, characterized by a rapid progressive nephropathy, male pseudohermaphroditism, and an increased risk for Wilms tumor. We report here a patient with scrotal hypospadias and a slow progressive nephropathy due to focal and segmental glomerulosclerosis. WT1 mutation analysis revealed a constitutional missense mutation in exon 9 resulting in an exchange F392L. This mutation has previously been reported by others in a patient with a similar mild course of nephropathy. In contrast, a mutation in the corresponding codon of exon 8 (F364L) was previously found by us in a patient with a very rapid progression to end-stage renal disease. Whether the position of a mutation may influence the course of the nephropathy must be evaluated in a larger patient cohort. The individual tumor risk for this alteration cannot be given at present because neither of the two patients has shown evidence of a Wilms tumor or a gonadoblastoma to date.

Digital pathology evaluation of complement C4d component deposition in the kidney allograft biopsies is a useful tool to improve reproducibility of the scoring.

Complement C4d component deposition in kidney allograft biopsies is an established marker of antibody-mediated rejection. In the Banff 07 classification of renal allograft pathology, semi-quantitative evaluation of the proportion of C4d-positive peritubular capilaries (PTC) is used. We aimed to explore the potential of digital pathology tools to obtain quantitative and reproducible measure of C4d deposition in the renal allograft tissue.34 routine kidney allograft biopsies immunohistochemically stained for C4d were included in the study and were evaluated by a qualified pathologist twice, recording an approximate percentage of positive PTC and glomerular area. The same slides were scanned by Aperio ScanScope scanner. Two layers of annotations were created: layer of glomeruli and the remaining non-glomerular area. Image analysis was performed with Aperio Positive Pixel Count algorithm to quantify the proportion of C4d-positive pixels in the area analysed. The percentage of positive (defined as 2+ and 3+) pixels in glomeruli and non-glomerular area was obtained and compared to the percentage of C4d-positive PTC and C4d-positive area of glomeruli recorded by the pathologist.The correlation of digital and manual C4d-positive area scoring in glomeruli was very high (r= 0.89, p<0.0001), while the correlation for non-glomerular (digital) and PTC (manual) area was moderate (r=0.60, p<0.001). The correlation between digital and manual evaulation of C4d in non-glomerular area after exclusion of C4d-positive arterioles from analysis did not improve substantially (r = 0.59, p < 0.001). Reproducibility of digital and manual results was evaluated. For C4d deposition in PTC, agreement between the first and the second digital C4d evaluation (after re-drawing annotations) was perfect (κ=0.96, CI 0.91÷1.00) while agreement between two subsequent manual C4d scorings was substantial (κ = 0.67, CI 0.47 ÷ 0.88). Similarly, for C4d deposition in the glomeruli, agreement of digital evaluation was perfect (κ=1) while for manual scorings it was substantial (κ = 0.76, CI 0.64 ÷ 0.88).Digital evaluation of C4d deposition in allograft kidney correlates with pathologist‘s scoring and exceeds the latter in reproducibilty. Therefore, it provides a useful tool to control for intraobserver and interobserver variability and may serve as quality assurance measure for allograft pathology diagnosis and research.