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Item does not contain fulltext The convergence of digital pathology and computer vision is increasingly enabling computers to perform tasks performed by humans. As a result, artificial intelligence (AI) is having an astoundingly positive effect on the field of pathology, including breast pathology. Research using machine learning and the development of algorithms that learn patterns from labeled digital data based on "deep learning" neural networks and feature-engineered approaches to analyze histology images have recently provided promising results. Thus far, image analysis and more complex AI-based tools have demonstrated excellent success performing tasks such as the quantification of breast biomarkers and Ki67, mitosis detection, lymph node metastasis recognition, tissue segmentation for diagnosing breast carcinoma, prognostication, computational assessment of tumor-infiltrating lymphocytes, and prediction of molecular expression as well as treatment response and benefit of therapy from routine H&E images. This review critically examines the literature regarding these applications of AI in the area of breast pathology.

BACKGROUND: The mechanisms driving the transition from inflammation to fibrosis in sarcoidosis patients are poorly understood; prognostic features are lacking. Immune cell profiling may provide insights into pathogenesis and prognostic factors of the disease. This study aimed to establish associations in simultaneous of lymphocyte subset profiles in the blood, bronchoalveolar lavage fluid (BALF), and lung biopsy tissue in the patients with newly diagnosed sarcoidosis. METHODS: A total of 71 sarcoid patients (SPs) and 20 healthy controls (HCs) were enrolled into the study. CD31, CD38, CD44, CD103 positive T lymphocytes in blood and BALF were analysed. Additionally, the densities of CD4, CD8, CD38, CD44, CD103 positive cells in lung tissue biopsies were estimated by digital image analysis. RESULTS: Main findings: (I) increase of percentage of CD3(+)CD4(+)CD38(+) in BALF and blood, and increase of percentage of CD3(+)CD4(+)CD44(+) in BALF in Löfgren syndrome patients comparing with patients without Löfgren syndrome, (II) increase of percentage of CD3(+)CD4(+)103(+) in BALF and in blood in patients without Löfgren syndrome (comparing with Löfgren syndrome patients) and increase of percentage of CD3(+)CD4(+)103(+) in BALF and in blood in more advanced sarcoidosis stage. (III) Increasing percentage of BALF CD3(+)CD4(+)CD31(+) in sarcoidosis patients when comparing with controls independently of presence of Löfgren syndrome, smoking status or stage of sarcoidosis. Several significant correlations were found. CONCLUSIONS: Lymphocyte subpopulations in blood, BALF, and lung tissue were substantially different in SPs at the time of diagnosis compared to HCs. CD3(+)CD4(+)CD31(+) in BALF might be a potential supporting marker for the diagnosis of sarcoidosis. CD3(+)CD4(+)CD38(+) in BALF and blood and CD3(+)CD4(+)CD44(+) in BALF may be markers of the acute immune response in sarcoidosis patients. CD4(+)CD103(+) T-cells in BALF and in blood are markers of the persistent immune response in sarcoidosis patients and are potential prognostic features of the chronic course of this disease.

Automated segmentation of tumor epithelial tissue from histological images is a fundamental aspiration of digital pathology to improve biomarker assessment and tissue diagnosis. Accurate tumour segmentation is an important step in many automated digital image analysis applications to be used in clinical practice. In particular, segmentation of tumour, non-tumour epithelium and stromal tissue compartments on immunohistochemistry images presents a challenge. Many artifacts, such as staining and/or illumination variations, can confound image analysis. In this paper, we propose a cascade-learning approach which can diminish the impact of these artifacts. It consists of (a) a set of novel invariant features that encodes meaningful information about the appearance and shape of the region of interest and (b) a novel level set formulation where contour evolution is driven by a probabilistic model of the appearance of the region (based on fuzzy c-means). The merit of our approach is that it exploits both appearance and shape information and combines them in the tissue classification framework. We evaluate the performance of our approach on the segmentation of tumour epithelium in colorectal cancer. The experimental results show that our approach is robust to staining differences, additive noise, intensity inhomogeneities, and can cope with a limited number of training samples, when compared to the state-of-the-art tumour epithelial segmentation methods.

Within the tumor microenvironment, specifically aligned collagen has been shown to stimulate tumor progression by directing the migration of metastatic cells along its structural framework. Tumor-associated collagen signatures (TACS) have been linked to breast cancer patient outcome. Robust and affordable methods for assessing biological information contained in collagen architecture need to be developed. We have developed a novel artificial neural network (ANN) based approach for tumor collagen segmentation from bright-field histology images and have tested it on a set of tissue microarray sections from early hormone receptor-positive invasive ductal breast carcinoma stained with Sirius Red (1 core per patient, n = 92). We designed and trained ANNs on sets of differently annotated image patches to segment collagen fibers and extracted 37 features of collagen fiber morphometry, density, orientation, texture, and fractal characteristics in the entire cohort. Independent instances of ANN models trained on highly differing annotations produced reasonably concordant collagen segmentation masks and allowed reliable prognostic Cox regression models (with likelihood ratios 14.11–22.99, at p-value

Background and Objectives: It is thought that muscle and bone interact only on a biomechanical level, however, some research is now emerging that links bone and muscle on a cellular level. The aim of this study was to explore associations between physical function, muscle mass and bone density in community-dwelling elderly men with sarcopenia. A secondary goal was to analyze if muscle morphology was associated with bone density and physical functioning. Materials and Methods: Body composition was measured by dual-energy X-ray absorptiometry (DXA). Bone density was evaluated according to WHO criteria. Sarcopenia was diagnosed according to European Working Group on Sarcopenia in Older People (EWGSOP) criteria: low muscle mass and low muscle strength or low physical performance. Microbiopsy of musculus vastus lateralis was performed with a disposable muscle microbiopsy system. The perimeter and cross-sectional area of muscle fibers were calculated using image analysis software in whole slide images, type of fibers and their distribution were evaluated as well. Results: A total of 151 men, 60 years or older were included in this study. Mean age of the subjects was 72.9 ± 8.02 years. Sarcopenia was diagnosed in 45 (29.8%) men. Multiple significant correlations were found between bone mineral density, lean mass, appendicular lean mass, arm and leg lean mass, gait speed, balance test and handgrip strength in sarcopenic men. Lean mass was associated with femoral neck BMD (bone mineral density, r = 0.418, p = 0.006) and handgrip strength (r = 0.553, p &lt, 0.001). In the sarcopenia group, 25 muscle biopsies were examined. In 9 sarcopenic men with T-scores equal or below −2.5, the muscle fiber area had a significant correlation with the balance test (r = 0.73, p = 0.025). Conclusions: In men with sarcopenia, low lean muscle mass was associated with low femoral neck BMD and low muscle strength. In sarcopenic men with osteoporosis, low muscle fiber area was associated with low scores in a balance test.

Breast cancer (BC) categorized as human epidermal growth factor receptor 2 (HER2) borderline [2+ by immunohistochemistry (IHC 2+)] presents challenges for the testing, frequently obscured by intratumoral heterogeneity (ITH). This leads to difficulties in therapy decisions. We aimed to establish prognostic models of overall survival (OS) of these patients, which take into account spatial aspects of ITH and tumor microenvironment by using hexagonal tiling analytics of digital image analysis (DIA). In particular, we assessed the prognostic value of Immunogradient indicators at the tumor–stroma interface zone (IZ) as a feature of antitumor immune response. Surgical excision samples stained for estrogen receptor (ER), progesterone receptor (PR), Ki67, HER2, and CD8 from 275 patients with HER2 IHC 2+ invasive ductal BC were used in the study. DIA outputs were subsampled by HexT for ITH quantification and tumor microenvironment extraction for Immunogradient indicators. Multiple Cox regression revealed HER2 membrane completeness (HER2 MC) (HR: 0.18, p = 0.0007), its spatial entropy (HR: 0.37, p = 0.0341), and ER contrast (HR: 0.21, p = 0.0449) as independent predictors of better OS, with worse OS predicted by pT status (HR: 6.04, p = 0.0014) in the HER2 non-amplified patients. In the HER2-amplified patients, HER2 MC contrast (HR: 0.35, p = 0.0367) and CEP17 copy number (HR: 0.19, p = 0.0035) were independent predictors of better OS along with worse OS predicted by pN status (HR: 4.75, p = 0.0018). In the non-amplified tumors, three Immunogradient indicators provided the independent prognostic value: CD8 density in the tumor aspect of the IZ and CD8 center of mass were associated with better OS (HR: 0.23, p = 0.0079 and 0.14, p = 0.0014, respectively), and CD8 density variance along the tumor edge predicted worse OS (HR: 9.45, p = 0.0002). Combining these three computational indicators of the CD8 cell spatial distribution within the tumor microenvironment augmented prognostic stratification of the patients. In the HER2-amplified group, CD8 cell density in the tumor aspect of the IZ was the only independent immune response feature to predict better OS (HR: 0.22, p = 0.0047). In conclusion, we present novel prognostic models, based on computational ITH and Immunogradient indicators of the IHC biomarkers, in HER2 IHC 2+ BC patients.

Background: The study aims to evaluate the lymph node (LN) response to preoperative chemotherapy and its impact on long-term outcomes in advanced gastric cancer (AGC). Methods: Histological specimens retrieved at gastrectomy from patients who received preoperative chemotherapy were evaluated. LN regression was graded by the adapted tumor regression grading system proposed by Becker. Patients were classified as node-negative (lnNEG) in the case of all negative LN without evidence of previous tumor involvement. Patients with LN metastasis were classified as nodal responders (lnR) in case of a regression score 1a-2 was detected in the LN. Nodal non-responders (lnNR) had a regression score of 3 in all of the metastatic nodes. Survival was compared using Kaplan-Meier and Cox regression analysis. Results: Among 87 patients included in the final analysis 29.9 % were lnNEG, 21.8 % were lnR and 48.3 % were lnNR. Kaplan-Meier curves showed a survival benefit for lnR over lnNR (p=0.03), while the survival of lnR and lnNEG patients was similar. Cox regression confirmed nodal response to be associated with decreased odds for death in univariate (HR: 0.33; 95 % CI 0.11-0.96, p=0.04) and multivariable (HR 0.37; 95 CI% 0.14-0.99, p=0.04) analysis. Conclusions: Histologic regression of LN metastasis after preoperative chemotherapy predicts the increased survival of patients with non-metastatic resectable AGC.

Anti-cancer immunotherapy dramatically changes the clinical management of many types of tumours towards less harmful and more personalized treatment plans than conventional chemotherapy or radiation. Precise analysis of the spatial distribution of immune cells in the tumourous tissue is necessary to select patients that would best respond to the treatment. Here, we introduce a deep learning-based workflow for cell nuclei segmentation and subsequent immune cell identification in routine diagnostic images. We applied our workflow on a set of hematoxylin and eosin (H&E) stained breast cancer and colorectal cancer tissue images to detect tumour-infiltrating lymphocytes. Firstly, to segment all nuclei in the tissue, we applied the multiple-image input layer architecture (Micro-Net, Dice coefficient (DC) 0.79±0.02).We supplemented the Micro-Net with an introduced texture block to increase segmentation accuracy (DC = 0.80 ± 0.02). We preserved the shallow architecture of the segmentation network with only 280 K trainable parameters (e.g. U-net with ∼1900 K parameters, DC = 0.78 ± 0.03). Subsequently, we added an active contour layer to the ground truth images to further increase the performance (DC = 0.81±0.02). Secondly, to discriminate lymphocytes from the set of all segmented nuclei, we explored multilayer perception and achieved a 0.70 classification f-score. Remarkably, the binary classification of segmented nuclei was significantly improved (f-score = 0.80) by colour normalization. To inspect model generalization, we have evaluated trained models on a public dataset that was not put to use during training. We conclude that the proposed workflow achieved promising results and, with little effort, can be employed in multi-class nuclei segmentation and identification tasks.

We aimed to report the results of the implementation of the National Colorectal Cancer (CRC) Screening Program covering all the country. The National Health Insurance Fund (NHIF) reimburses the institutions for performing each service, each procedure within the program has its own administrative code. Information about services provided within the program was retrieved from the database of NHIF starting from the 1 January 2014 to the 31 December 2018. Exact date and type of all provided services, test results, date and results of biopsy and histopathological examination were extracted together with the vital status at the end of follow-up, date of death and date of emigration when applicable for all men and women born between 1935 and 1968. Results were compared with the guidelines of the European Union for quality assurance in CRC screening and diagnosis. The screening uptake was 49.5% (754,061 patients) during study period. Participation rate varied from 16% to 18.1% per year and was higher among women than among men. Proportion of test-positive and test-negative results was similar during all the study period—8.7% and 91.3% annually. Between 9.2% and 13.5% of test-positive patients received a biopsy of which 52.3–61.8% were positive for colorectal adenoma and 4.6–7.3% for colorectal carcinoma. CRC detection rate among test-positive individuals varied between 0.93% and 1.28%. The colorectal cancer screening program in Lithuania coverage must be improved. A screening database is needed to systematically evaluate the impact and performance of the national CRC screening program and quality assurance within the program.

Tumor-associated immune cells have been shown to predict patient outcome in colorectal (CRC) and other cancers. Spatial digital image analysis-based cell quantification increases the informative power delivered by tumor microenvironment features and leads to new prognostic scoring systems. In this study we evaluated the intratumoral density of immunohistochemically stained CD8, CD20 and CD68 cells in 87 cases of CRC (48 were microsatellite stable, MSS, and 39 had microsatellite instability, MSI) in both the intratumoral tumor tissue and within the tumor-stroma interface zone (IZ) which was extracted by a previously developed unbiased hexagonal grid analytics method. Indicators of immune-cell gradients across the extracted IZ were computed and explored along with absolute cell densities, clinicopathological and molecular data, including gene mutation (BRAF, KRAS, PIK3CA) and MSI status. Multiple regression modeling identified (p &lt, 0.0001) three independent prognostic factors: CD8+ and CD20+ Immunogradient indicators, that reflect cell migration towards the tumor, were associated with improved patient survival, while the infiltrative tumor growth pattern was linked to worse patient outcome. These features were combined into CD8-CD20 Immunogradient and immuno-interface scores which outperformed both tumor-node-metastasis (TNM) staging and molecular characteristics, and importantly, revealed high prognostic value both in MSS and MSI CRCs.

Immunohistochemistry (IHC) for ER, PR, HER2, and Ki67 is used to predict outcome and therapy response in breast cancer patients. The current IHC assessment, visual or digital, is based mostly on global biomarker expression levels in the tissue sample. In our study, we explored the prognostic value of digital image analysis of conventional breast cancer IHC biomarkers supplemented with their intratumoral heterogeneity and tissue immune response indicators. Surgically excised tumor samples from 101 female patients with hormone receptor-positive breast cancer (HRBC) were stained for ER, PR, HER2, Ki67, SATB1, CD8, and scanned at 20x. Digital image analysis was performed using the HALO™ platform. Subsequently, hexagonal tiling was used to compute intratumoral heterogeneity indicators for ER, PR and Ki67 expression. Multiple Cox regression analysis revealed three independent predictors of the patient's overall survival: Haralick's texture entropy of PR (HR = 0.19, p = 0.0005), Ki67 Ashman's D bimodality (HR = 3.0, p = 0.01), and CD8+SATB1+ cell density in tumor tissue (HR = 0.32, p = 0.02). Remarkably, the PR and Ki67 intratumoral heterogeneity indicators were prognostically more informative than the rates of their expression. In particular, a distinct non-linear relationship between the rate of PR expression and its intratumoral heterogeneity was observed and revealed a non-linear prognostic effect of PR expression. The independent prognostic significance of CD8+SATB1+ cells infiltrating the tumor could indicate their role in anti-tumor immunity. In conclusion, we suggest that prognostic modeling, based entirely on the computational image-based IHC biomarkers, is possible in HRBC patients. The intratumoral heterogeneity and immune response indicators outperformed both conventional breast cancer IHC and clinicopathological variables while markedly increasing the power of the model.

The nuclear proliferation biomarker Ki67 has potential prognostic, predictive, and monitoring roles in breast cancer. Unacceptable between-laboratory variability has limited its clinical value. The International Ki67 in Breast Cancer Working Group investigated whether Ki67 immunohistochemistry can be analytically validated and standardized across laboratories using automated machine-based scoring. Sets of pre-stained core-cut biopsy sections of 30 breast tumors were circulated to 14 laboratories for scanning and automated assessment of the average and maximum percentage of tumor cells positive for Ki67. Seven unique scanners and 10 software platforms were involved in this study. Pre-specified analyses included evaluation of reproducibility between all laboratories (primary) as well as among those using scanners from a single vendor (secondary). The primary reproducibility metric was intraclass correlation coefficient between laboratories, with success considered to be intraclass correlation coefficient >0.80. Intraclass correlation coefficient for automated average scores across 16 operators was 0.83 (95% credible interval: 0.73–0.91) and intraclass correlation coefficient for maximum scores across 10 operators was 0.63 (95% credible interval: 0.44–0.80). For the laboratories using scanners from a single vendor (8 score sets), intraclass correlation coefficient for average automated scores was 0.89 (95% credible interval: 0.81–0.96), which was similar to the intraclass correlation coefficient of 0.87 (95% credible interval: 0.81–0.93) achieved using these same slides in a prior visual-reading reproducibility study. Automated machine assessment of average Ki67 has the potential to achieve between-laboratory reproducibility similar to that for a rigorously standardized pathologist-based visual assessment of Ki67. The observed intraclass correlation coefficient was worse for maximum compared to average scoring methods, suggesting that maximum score methods may be suboptimal for consistent measurement of proliferation. Automated average scoring methods show promise for assessment of Ki67 scoring, but requires further standardization and subsequent clinical validation.

5-fluorouracil (5-FU) and oxaliplatin (OxaPt) are the main chemotherapeutics for colorectal cancer (CRC). Chemotherapy response rates for advanced CRC remain low, primarily due to intrinsic or acquired chemoresistance. The importance of Notch and Wnt signaling for carcinogenesis of CRC as well as crosstalk of Notch and Wnt signaling with many oncogenic signaling pathways suggest that Notch and Wnt pathways could be responsible for chemoresistance. In this study, we compared changes in Notch and Wnt signaling after 5-FU and OxaPt treatment in CRC cells HCT116 and its chemoresistant sublines HCT116/FU and HCT116/OXA. The levels of Notch1 receptor intracellular domain NICD1 and non-phosphorylated β-catenin, the reporters of Notch and Wnt signaling, were upregulated in untreated chemoresistant HCT116/FU and HCT116/OXA cells. Our data suggest that Notch inhibitor RO4929097 (RO) and Wnt inhibitor XAV939 (XAV) enhance the survival potential of OxaPt-treated cells. The protein level of Notch target gene HES1 was significantly upregulated in chemoresistant HCT116/FU and HCT116/OXA cells, compared to HCT116. HES1 silencing increased viability of HCT116 and its chemoresistant sublines after 5-FU or OxaPt treatment. The results of HES1 downregulation coincide with RO and XAV effects on cell viability of OxaPt-treated cells.

Differentiation of indolent and aggressive prostate carcinoma (PCa) at the time of diagnosis is currently one of the major challenges. This study aimed at identification of prognostic biomarkers to aid in predicting biochemical recurrence (BCR) of the disease. Microarray-based gene expression profiling in tissues of 8 BCR and 8 No-BCR cases revealed expression differences of 455 genes, most of which were down-regulated in BCR cases. Eleven genes were selected for validation by real-time PCR in the first PCa cohort (N = 55), while seven of them were further validated in the second, independent, PCa cohort (N = 53). Down-regulation of MT1E (p < 0.001) and GPR52 (p = 0.002) expression and up-regulated levels of EZH2 (p = 0.025) were specific biomarkers of BCR in at least one of the two PCa cohorts, but only MT1E expression retained the independent prognostic value in a multivariate analysis (p < 0.001). DNA methylation analysis (114 PCa and 24 non-cancerous tissues) showed frequent MT1E methylation in PCa (p < 0.001) and was associated (p < 0.010) with the down-regulated expression in one PCa cohort. The results of our study suggest MT1E down-regulation as a potential feature of aggressive PCa.

More than 90% of solid kidney tumors are cancerous and have to be treated by surgical resection where surgical outcomes and patient prognosis are dependent on the tumor discrimination. The development of alternative approaches based on a new generation of fiber attenuated total reflection (ATR) probes could aid tumor identification even under intra‐surgical conditions. Herein, fiber ATR IR spectroscopy is employed to distinguish normal and cancerous kidney tissues. Freshly resected tissue samples from thirty four patients are investigated under nearly native conditions. Spectral marker bands that allow a reliable discrimination between tumor and normal tissue is identified by a supervised classification algorithm. The absorbance values of the bands at 1025, 1155 and 1240 cm−1 assigned to glycogen and fructose 1,6‐bisphosphatase are used as the clearest markers for the tissue discrimination. Absorbance threshold values for tumor and normal tissue are determined by discriminant analysis. This new approach allows the surgeon to make a clinical diagnosis.

The distribution of tumor-infiltrating lymphocytes (TILs) within the tumor microenvironment provides strong prognostic value, which is increasingly important with the arrival of new immunotherapy modalities. Both visual and image analysis-based assays are developed to assess the immune contexture of the tumors. We propose an automated method based on grid subsampling of microscopy image analysis data to extract the tumor-stroma interface zone (IZ) of controlled width. The IZ is a ranking of tissue areas by their distance to the tumor edge, which is determined by a set of explicit rules. TIL density profiles across the IZ are used to compute a set of novel immunogradient indicators that reflect TIL gradient towards the tumor. We applied this method on CD8 immunohistochemistry images of surgically excised hormone receptor-positive breast and colorectal cancers to predict overall patient survival. In both cohorts, the immunogradient indicators enabled strong and independent prognostic stratification, outperforming clinical and pathologic variables. Patients with breast cancer with low immunogradient levels had a prominent decrease in survival probability 5 years after surgery. Our study provides proof of concept that data-driven, automated, operator-independent IZ sampling enables spatial immune response measurement in the tumor-host interaction frontline for prediction of disease outcomes.

Uncontrolled proliferation is a hallmark of cancer and can be assessed by labelling breast tissue using immunohistochemistry for Ki67, a protein associated with cell proliferation. Accurate measurement of Ki67-positive tumour nuclei is of critical importance, but requires annotation of the tumour regions by a pathologist. This manual annotation process is highly subjective, time-consuming and subject to inter- and intra-annotator experience. To address this challenge, we have developed Proliferation Tumour Marker Network (PTM-NET), a deep learning model that objectively annotates the tumour regions in Ki67-labelled breast cancer digital pathology images using a convolution neural network. Our custom designed deep learning model was trained on 45 immunohistochemical Ki67-labelled whole slide images to classify tumour and non-tumour regions and was validated on 45 whole slide images from two different sources that were stained using different protocols. Our results show a Dice coefficient of 0.74, positive predictive value of 70% and negative predictive value of 88.3% against the manual ground truth annotation for the combined dataset. There were minimal differences between the images from different sources and the model was further tested in oestrogen receptor and progesterone receptor-labelled images. Finally, using an extension of the model, we could identify possible hotspot regions of high proliferation within the tumour. In the future, this approach could be useful in identifying tumour regions in biopsy samples and tissue microarray images.

Introduction: Many theories have been proposed to explain pathogenesis of COPD; however, remains unclear why the majority of smokers (~80%) do not develop COPD, or only develop a mild disease. To explore if COPD has an autoimmune component, the role of T regulatory lymphocytes (Tregs) in the lung tissue of COPD patients is of crucial importance. Material and methods: Bronchial tissue biopsy samples were prospectively collected from 64 patients (39 COPD and 25 controls—15 smokers and 10 non-smokers). The patients with COPD were subdivided into mild/moderate (GOLD stage I−II) and severe/very severe (GOLD stage III−IV) groups. Digital image analysis was performed to estimate densities of CD4+ CD25+ cell infiltrates in double immunohistochemistry slides of the biopsy samples. Blood samples were collected from 42 patients (23 COPD and 19 controls) and tested for CD3+ CD4+ CD25+ bright lymphocytes by flow cytometry. Results: The number of intraepithelial CD4+ CD25+ lymphocytes mm-2 epithelium was significantly lower in the severe/very severe COPD (GOLD III–IV) group as well as in the control non-smokers (NS) group (p < 0,0001). Likewise, the absolute number of Treg (CD3+ CD4+ CD25+ bright) cells in the peripheral blood samples was significantly different between the four groups (p = 0.032). The lowest quantity of Treg cells was detected in the severe/very severe COPD and healthy non-smokers groups. Conclusions: Our findings suggest that severe COPD is associated with lower levels of Tregs in the blood and bronchial mucosa, while higher Tregs levels in the smokers without COPD indicate potential protective effect of Tregs against developing COPD.

Background & Aim Acute kidney injury (AKI) is a life-threatening postoperative complication, affecting 10-30% of treated patients and characterized by the damage to the proximal tubular cells, thereby markedly impairing renal function.1,2,3 15% of patients develop chronic kidney disease (CKD) and fibrosis, eventually managed by hemodialysis and kidney transplantation.4 Mesenchymal stem cells have been shown to possess anti-inflammatory and immunomodulatory properties and be able to aid in tissue repair.5 A link between AKI and CKD has been established and the optimal treatment approach to reduce the high unmet medical need and an economical burden is still being researched.6 Placenta-derived mesenchymal stem cells (PSCs) may be a viable approach to treat AKI and prevent subsequent CKD development. Methods, Results & Conclusion M.: PSCs have been isolated using GMP grade materials, cultivated for three weeks and characterized by yield, viability, flow cytometry and potency in vitro. Wistar rats (8-12 wk) underwent preclinical ischemia-reperfusion injury (IRI). Two experimental groups received treatment. Experimental group (Index) received 3 × 105 of PSCs in the corticomedullar region of each kidney. Control group (Control) received PBS vehicle solution. Survival analysis was carried out till day 7. Urine and blood serum samples were collected on day 0, 3 and 7 and analysed for urine volume/24hrs., protein, creatinine, urea, Na+ and K+. Histological kidney analysis on days 3 and 7 for evaluation of tubular necrosis. R. PSCs had a consistent yield, viability, MSCs markers expression and suppressed proliferation of T cells. Survival rate improved – 100% (Index) vs. 75% (Control). Serum urea and K+ was reduced in index group on day 7 (p Serum creatinine was 1.9 and 1.6 times lower in index group on days 3 and 7, respectively. Na+ was similarly lower after 7 days after PSCs injection. Extensive acute tubular necrosis (ATN) with broad coagulative tubular epithelial necrosis was evident after 3 days in the Control group. Variable extent of ATN without significant coagulative necrosis was observed after 3 and 7 days of Index group. C. Placental derived stem cells have the potential to prevent initial kidney fibrosis cascade through ameliorating initial kidney damage and improving kidney function. A superior 100% survival rate of treated animal group exhibits the potential of characterised PSCs to be used in a larger scale preclinical tumorigenicity and toxicity studies and subsequent clinical first-in-human studies.

Although treatment of colorectal cancer with 5-florouracil and oxaliplatin is widely used, it is frequently followed by a relapse. Therefore, there is an urgent need for profound understanding of chemotherapy resistance mechanisms as well as the profiling of predictive markers for individualized treatment. In this study, we identified the changes in 14 miRNAs in 5-fluouracil and 40 miRNAs in oxaliplatin-resistant cell lines by miRNA sequencing. The decrease in miR-224-5p expression in the 5-fluorouracil-resistant cells correlated with drug insensitivity due to its overexpression-induced drug-dependent apoptosis. On the other hand, the miR-23b/27b/24-1 cluster was overexpressed in oxaliplatin-resistant cells. The knockout of miR-23b led to the partial restoration of oxaliplatin susceptibility, showing the essential role of miR-23b in the development of drug resistance by this cluster. Proteomic analysis identified target genes of miR-23b and showed that endothelial–mesenchymal transition (EMT) was implicated in oxaliplatin insensibility. Data revealed that EMT markers, such as vimentin and SNAI2, were expressed moderately higher in the oxaliplatin-resistant cells and their expression increased further in the less drug-resistant cells, which had miR-23b knockout. This establishes that the balance of EMT contributes to the drug resistance, showing the importance of the miR-23b-mediated fine-tuning of EMT in oxaliplatin-resistant cancer cells.

BACKGROUND AND AIMS Immunohistochemistry (IHC) is an essential component of biomarker research in cancer. Automated biomarker quantification is hampered by the failure of computational algorithms to discriminate 'negative' tumour cells from 'negative' stromal cells. We sought to develop an algorithm for segmentation of tumour epithelium in colorectal cancer (CRC), irrespective of the biomarker expression in the cells. METHODS AND RESULTS We developed tumour parcellation and quantification (TuPaQ) to segment tumour epithelium and parcellate sections into 'epithelium' and 'non-epithelium'. TuPaQ comprises image pre-processing, extraction of regions of interest (ROIs) and quantification of tumour epithelium (total area occupied by epithelium and number of nuclei in the occupied area). A total of 286 TMA cores from CRC were manually annotated and analysed using the commercial halo software to provide ground truth. The performance of TuPaQ was evaluated against the ground truth using a variety of metrics. The image size of each core was 7000 × 7000 pixels and each core was analysed in a matter of seconds. Pixel × pixel analysis showed a sensitivity of 84% and specificity of 95% in detecting epithelium. The mean tumour area obtained by TuPaQ was very close to the area quantified after manual annotation (r = 0.956, P < 0.001). Moreover, quantification of tumour nuclei by TuPaQ correlated very strongly with that of halo (r = 0.891, P < 0.001). CONCLUSION TuPaQ is a very rapid and accurate method of separating the epithelial and stromal compartments of colorectal tumours. This will allow more accurate and objective analysis of immunohistochemistry.

Objective We sought to investigate the impact of self-reported fasting duration times on the lipid profile results and its impact on the cardiovascular risk stratification and metabolic syndrome diagnosis. Subjects and methods We analyzed data from all consecutive individuals evaluated in a comprehensive health examination at the Hospital Israelita Albert Einstein from January to December 2015. We divided these patients in three groups, according to the fasting duration recalled (< 8h, 8-12h and > 12h). We calculated the global cardiovascular risk and diagnosed metabolic syndrome according to the current criteria and estimated their change according to fasting duration. Results A total of 12,196 (42.3 ± 9.2 years-old, 30.2% females) patients were evaluated. The distribution of cardiovascular risk was not different among groups defined by fasting duration in both men and women (p = 0.547 for women and p = 0.329 for men). Similarly, the prevalence of metabolic syndrome was not influenced by the fasting duration (p = 0.431 for women and p = 0.166 for men). Conclusion Self-reported fasting duration had no significant impact on the lipid profile results, including triglyceride levels. Consequently, no changes on the cardiovascular risk stratification using the Framingham risk score nor changes on the prevalence of metabolic syndrome were noted.

Proliferative activity, assessed by Ki67 immunohistochemistry (IHC), is an established prognostic and predictive biomarker of breast cancer (BC). However, it remains under-utilized due to lack of standardized robust measurement methodologies and significant intratumor heterogeneity of expression. A recently proposed methodology for IHC biomarker assessment in whole slide images (WSI), based on systematic subsampling of tissue information extracted by digital image analysis (DIA) into hexagonal tiling arrays, enables computation of a comprehensive set of Ki67 indicators, including intratumor variability. In this study, the tiling methodology was applied to assess Ki67 expression in WSI of 152 surgically removed Ki67-stained (on full-face sections) BC specimens and to test which, if any, Ki67 indicators can predict overall survival (OS). Visual Ki67 IHC estimates and conventional clinico-pathologic parameters were also included in the study. Analysis revealed linearly independent intrinsic factors of the Ki67 IHC variance: proliferation (level of expression), disordered texture (entropy), tumor size and Nottingham Prognostic Index, bimodality, and correlation. All visual and DIA-generated indicators of the level of Ki67 expression provided significant cutoff values as single predictors of OS. However, only bimodality indicators (Ashman's D, in particular) were independent predictors of OS in the context of hormone receptor and HER2 status. From this, we conclude that spatial heterogeneity of proliferative tumor activity, measured by DIA of Ki67 IHC expression and analyzed by the hexagonal tiling approach, can serve as an independent prognostic indicator of OS in BC patients that outperforms the prognostic power of the level of proliferative activity.

Background and aim: Immunoglobulin A nephropathy (IgAN) is the most frequent glomerular disease worldwide and one of the main causes of chronic kidney disease. We aimed to investigate clinicopathological correlations in IgAN patients by gender. Materials and methods: The study was based on a retrospective analysis of renal biopsy data and clinical manifestations of the disease. Consecutive 73 biopsy-proven IgAN cases of male (62%) and female (38%) patients were investigated. Renal biopsies were reviewed using the new Oxford classification assessing the MEST (mesangial hypercellularity, endocapillary hypercellularity, segmental sclerosis/adhesion, tubular atrophy/interstitial fibrosis) score. The most powerful IgAN prognostic risk factors, morphological (segmental glomerulosclerosis and tubular atrophy/interstitial fibrosis) as well as clinical (proteinuria and hypertension) were taken into account in the correlation analysis. The mean rate of renal function decline was expressed as a slope of eGFR during the follow-up (FU) dividing delta GFR with the FU years. Results: The mean age of the patients was 33.7 years (range, 16–76). Follow-up data were available for 64 patients with the mean follow-up of 4.1 years. The mean proteinuria at biopsy was 0.79 g/24 h. The mean arterial pressure (MAP) was 94.5 ± 16.7 mmHg and 7% of the patients were hypertensive. The initial mean estimated glomerular filtration rate (eGFR) was 94.9 ± 30.7 mL/min, at the end of the follow-up it was 86.2 ± 27.1 mL/min. The mean rate of renal function decline was −3.4 ± 11.9 mL/min/1.73 m2 per year in males (P &lt, 0.05) and −0.7 ± 5.3 mL/min/1.73 m2 per year in females. The Spearman correlation analysis confirmed a higher MEST score in the whole cohort and in males correlated with disease progression. In patients with proteinuria below 1.0 g/24 h, disease progression was faster in males. Conclusions: According to the correlation analysis of the main prognostic risk factors, affecting the progression of IgAN, we can conclude that IgA nephropathy in males progresses more rapidly compared to females.

Digital image analysis (DIA) enables higher accuracy, reproducibility, and capacity to enumerate cell populations by immunohistochemistry; however, the most unique benefits may be obtained by evaluating the spatial distribution and intra-tissue variance of markers. The proliferative activity of breast cancer tissue, estimated by the Ki67 labeling index (Ki67 LI), is a prognostic and predictive biomarker requiring robust measurement methodologies. We performed DIA on whole-slide images (WSI) of 302 surgically removed Ki67-stained breast cancer specimens; the tumour classifier algorithm was used to automatically detect tumour tissue but was not trained to distinguish between invasive and non-invasive carcinoma cells. The WSI DIA-generated data were subsampled by hexagonal tiling (HexT). Distribution and texture parameters were compared to conventional WSI DIA and pathology report data. Factor analysis of the data set, including total numbers of tumor cells, the Ki67 LI and Ki67 distribution, and texture indicators, extracted 4 factors, identified as entropy, proliferation, bimodality, and cellularity. The factor scores were further utilized in cluster analysis, outlining subcategories of heterogeneous tumors with predominant entropy, bimodality, or both at different levels of proliferative activity. The methodology also allowed the visualization of Ki67 LI heterogeneity in tumors and the automated detection and quantitative evaluation of Ki67 hotspots, based on the upper quintile of the HexT data, conceptualized as the "Pareto hotspot". We conclude that systematic subsampling of DIA-generated data into HexT enables comprehensive Ki67 LI analysis that reflects aspects of intra-tumor heterogeneity and may serve as a methodology to improve digital immunohistochemistry in general.

Background: The nuclear proliferation biomarker Ki67 has multiple potential roles in breast cancer, including prognosis-based decisions, but unacceptable between-laboratory variability has limited its clinical value. The International Ki67 Working Group (IKWG) has undertaken a systematic program to determine whether Ki67 immunohistochemistry can be analytically validated and standardized across laboratories. Technological advances and broader availability of devices for automated assessment of stained slides raise the possibility that these machines may improve on reproducibility of traditional pathologist-based visual Ki67 assessment. Aims: To characterize reproducibility of automated machine-measured Ki67 expression using slides previously analyzed in the IKWG phase 3 study that evaluated reproducibility of visual Ki67 assessment. Methods: Two sets of 30 previously stained slides containing core-cut biopsy sections of breast tumors were circulated to 14 laboratories for scanning and automated assessment of Ki67 expression. Sites were instructed to return average and maximum percentage of tumor cells positive for Ki67 for each slide, where maximum is designed to reflect “hot spot” analysis. Two laboratories returned scores from 2 operators; not all laboratories reported values for maximum Ki67 scores. Different operators were treated as distinct laboratories in analyses. Sixteen and 10 score sets were available for average and maximum Ki67 analyses, respectively, encompassing 7 unique scanner and 10 software platforms. Pre-specified analyses included evaluation of reproducibility across all laboratories as well as within a subgroup limited to those using Aperio scanners. The primary reproducibility metric was intraclass correlation coefficient between laboratories (ICC), regardless of device platform or software. Results: Geometric means across 30 cases for 16 operators ranged from 11.06% to 38.11% with overall mean 16.75% (95% CI:14.45-19.42) for average scores. Geometric means for 10 operators ranged from 16.44% to 68.73% with overall mean 25.16% (95% CI: 18.71-33.84) for maximum scores. ICC for automated average scores across 16 operators was 0.83 (95% CI: 0.73-0.91) and ICC for maximum scores across 10 operators was 0.63 (95% CI: 0.44-0.80) although one outlier lab dramatically affected results. For the laboratories using the Aperio platform (8 score sets), ICC for automated average scores was 0.89 (95% CI; 0.81-0.96). These results are similar to ICC of 0.87 (95%CI; 0.81-0.93) reported using these same slides in the Phase 3 visual assessment reproducibility study in which observers counted 500 cells per slide (Leung et al, NPJBrCancer, in press). Conclusions: Between-laboratory reproducibility for automated machine assessment of average Ki67 is similar to that for pathologist-based visual assessment of Ki67. However, the observed ICC was markedly numerically lower for the maximum score method compared to the average method, suggesting that the maximum score may not be useful as a reproducible measure of proliferation. Automated average scoring methods show promise for standardization of Ki67 scoring, supporting future studies to clinically validate Ki67. Citation Format: Rimm DL, McShane LM, Leung SCY, Bai Y, Bane AL, Bartlett JMS, Bayani J, Chang MC, Dean M, Denkert C, Enwere E, Galderisi C, Gholap A, Hugh JC, Jadhav A, Kornaga E, Laurinavicius A, Levenson R, Lima J, Miller K, Pantanowitz L, Piper T, Ruan J, Srinivasan M, Virk S, Wu Y, Yang H, Hayes DF, Nielsen TO, Dowsett M. An international multicenter study to evaluate reproducibility of automated scoring methods for assessment of Ki67 in breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-03-01.

Our aim was to evaluate the incidence of biopsy-proven kidney diseases in Lithuania and to compare their changes in three different time intervals. All Lithuanian kidney biopsies were performed in the National Center of Pathology, enabling analysis at the national level. The native kidney biopsy data were reviewed, and incidence of renal disorders and patient demographics were compared during three time intervals: 1994–1999, 2000–2006, and 2007–2012. A total of 5,368 kidney biopsies were performed, including 3,640 native kidney and 1,728 kidney transplant biopsies; 59.5 % (2,165) of the native kidney biopsies were classified as primary glomerulopathies. The most common entity was IgA nephropathy (737; 34.0 %), followed by focal segmental glomerulosclerosis (285; 13.2 %) and membranoproliferative glomerulonephritis (256; 11.8 %). Prominent decrease in incidence of membranoproliferative glomerulonephritis (16.8 to 8.7 % from the first to third time interval) and increase in (mainly, pauci-immune) crescentic glomerulonephritis (6.2 to 15.3 %) were noted over the study period. In a subgroup of 427 pediatric native kidney biopsies, IgAN accounted for 24.9 % of biopsies. The incidence of MCNS increased dramatically from the first to third time interval (6.3 to 25.4 %), while the number of MPGN increased in the second time interval (from 7.2 to 8.9 %) but decreased in the third one (to 4.4 %). Decrease in relative incidence of membranoproliferative glomerulonephritis, most likely, reflects improvement in socioeconomic conditions, while relative increase in crescentic glomerulonephritis is interpreted as improved diagnostics of the disease.

Background The significance of IgM deposits in glomerular mesangium has been controversial since they were first described due to the variations in the both the definitions used and described impact on clinical outcome. The aim of our study was to evaluate the significance of the IgM deposits in the glomerular mesangium for outcomes of nephrotic syndrome (NS) in children. Methods Forty-five children with NS who underwent renal biopsy at tertiary pediatric hospital from January 1st, 2000 to December 31st, 2015 and the pathology diagnosis of minimal change disease, focal segmental glomerulosclerosis and mesangial hypercellularity (MH) were retrospectively analyzed. IgM positivity was defined as ≥1+ imunofluorescence with predominantly mesangial distribution. The patients were stratified into IgM-positive (n = 18) and IgM-negative (n = 27). Results At the end of the median follow-up 4.5 years (range 0.17–13.14), the IgM-positive group was represented by 11 patients (61.1%) in remission, 3 patients (16.7%) with active disease and normal kidney function, 2 (11.1%) patients with active disease and impaired kidney function, 2 (11.1%) patients on renal replacement therapy. Accordingly, the IgM-negative group included 13 patients (48.1%) in remission, 12 (44.4%) with active disease and normal kidney function, 1 (3.7%) with active disease and impaired kidney function, 1 (3.7%) on renal replacement therapy, with no statistical significance between groups (p = 0.186). Conclusions This study did not reveal significant differences of the disease outcomes between IgM-positive and IgM-negative groups.

Objective To investigate the inter-relation between high sensitivity C-reactive protein and glycated hemoglobin in prediction of risk of obstructive sleep apnea. Methods We included all individuals participating in a check-up program at the Preventive Medicine Center of Hospital Israelita Albert Einstein in 2014. The Berlin questionnaire for risk of obstructive sleep apnea was used, and the high sensitivity C-reactive protein and glycated hemoglobin levels were evaluated. Results The sample included 7,115 participants (age 43.4±9.6 years, 24.4% women). The Berlin questionnaire showed changes in 434 (6.1%) individuals. This finding was associated with high sensitivity C-reactive protein and glycated hemoglobin levels (p

Most prostate cancer (PCa) cases are multifocal, and separate foci display histological and molecular heterogeneity. DNA hypermethylation is a frequent alteration in PCa, but interfocal heterogeneity of these changes has not been extensively investigated. Ten pairs of foci from multifocal PCa and 15 benign prostatic hyperplasia (BPH) samples were obtained from prostatectomy specimens, resulting altogether in 35 samples. Methylation-specific PCR (MSP) was used to evaluate methylation status of nine tumor suppressor genes (TSGs), and a set of selected TSGs was quantitatively analyzed for methylation intensity by pyrosequencing. Promoter sequences of the RASSF1 and ESR1 genes were methylated in all paired PCa foci, and frequent (≥75 %) DNA methylation was detected in RARB, GSTP1, and ABCB1 genes. MSP revealed different methylation status of at least one gene in separate foci in 8 out of 10 multifocal tumors. The mean methylation level of ESR1, GSTP1, RASSF1, and RARB differed between the paired foci of all PCa cases. The intensity of DNA methylation in these TSGs was significantly higher in PCa cases than in BPH (p < 0.001). Hierarchical cluster analysis revealed a divergent methylation profile of paired PCa foci, while the foci from separate cases with biochemical recurrence showed similar methylation profile and the highest mean levels of DNA methylation. Our findings suggest that PCa tissue is heterogeneous, as between paired foci differences in DNA methylation status were found. Common epigenetic profile of recurrent tumors can be inferred from our data.

Human epidermal growth factor receptor 2 gene- (HER2-) targeted therapy for breast cancer relies primarily on HER2 overexpression established by immunohistochemistry (IHC) with borderline cases being further tested for amplification by fluorescence in situ hybridization (FISH). Manual interpretation of HER2 FISH is based on a limited number of cells and rather complex definitions of equivocal, polysomic, and genetically heterogeneous (GH) cases. Image analysis (IA) can extract high-capacity data and potentially improve HER2 testing in borderline cases. We investigated statistically derived indicators of HER2 heterogeneity in HER2 FISH data obtained by automated IA of 50 IHC borderline (2+) cases of invasive ductal breast carcinoma. Overall, IA significantly underestimated the conventional HER2, CEP17 counts, and HER2/CEP17 ratio; however, it collected more amplified cells in some cases below the lower limit of GH definition by manual procedure. Indicators for amplification, polysomy, and bimodality were extracted by factor analysis and allowed clustering of the tumors into amplified, nonamplified, and equivocal/polysomy categories. The bimodality indicator provided independent cell diversity characteristics for all clusters. Tumors classified as bimodal only partially coincided with the conventional GH heterogeneity category. We conclude that automated high-capacity nonselective tumor cell assay can generate evidence-based HER2 intratumor heterogeneity indicators to refine GH definitions.

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. (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

Introduction/ Background Gene expression studies have identified molecular subtypes of breast cancer with implications to chemotherapy recommendations. For distinction of these types a combination of hormone receptors and proliferative activity of tumor cells, estimated by Ki67 labeling index from immunohistochemistry (IHC) is used. Clinical studies are frequently based on IHC performed on tissue microarrays (TMA) with variable tissue sampling. This raises the need for evidence-based sampling criteria for individual studies. We present a novel tissue sampling simulation model and demonstrate its application on Ki67 assessment in breast cancer tissue taking into account its intra-tumoral heterogeneity. Aims The aim is, using a novel method for easy virtual TMA simulation, to determine the optimal tissue sampling requirements in the context of variable intra-tissue heterogeneity level of Ki67 immunohistochemistry in breast cancer. Methods Whole slide images (WSI) of 297 primary breast tumors immunohistochemically stained for Ki67 were subjected to digital image analysis (DIA). Percentage of invasive tumor cells stained for Ki67 were computed for hexagonal tiles superimposed on the WSI. From this, intra-tumoral Ki67 heterogeneity indicators (Haralick’s entropy values) were extracted and used to dichotomize the tumors into homogeneous and heterogeneous populations. Simulations with random selection of hexagons, equivalent to 0.75 mm circular diameter, were performed. The tissue sampling requirements were investigated in relation to tumor heterogeneity using linear regression and extended error analysis. Results The sampling requirements were dependent on the heterogeneity of the biomarker expression. To achieve a coefficient error of 10%, 5-6 cores were needed for homogeneous cases, while 11-12 cores for heterogeneous cases. In mixed tumor population, 8 TMA cores were required. Similarly, to achieve the same accuracy, approximately 4,000 nuclei must be counted when the intra-tumor heterogeneity is mixed/unknown. Tumors at the lower scale of proliferative activity would require larger sampling (10-12 TMA cores, or 5,000 nuclei) to achieve the same error measurement results as for highly proliferative tumors. Our data show that optimal tissue sampling for IHC biomarker evaluation is dependent on the heterogeneity of the tissue under study and needs to be determined on a per-use basis. We propose a method that can be applied to determine the TMA sampling strategy for specific biomarkers, tissues and study targets. In addition, our findings highlight the importance of high-capacity computer-based IHC measurement techniques to improve accuracy of the testing., Diagnostic Pathology, Vol 1 No 8 (2016): 13. European Congress on Digital Pathology

Background. Prostate cancer (PCa) is usually a multifocal disease with different foci displaying histological and molecular heterogeneity. Biopsy-based pathology diagnosis of PCa may not be representative of the entire tumour; thus, markers more precisely characterizing every focus of multifocal PCa are highly instrumental for a better testing of PCa. Materials and Methods. Two distant foci of prostate adenocarcinoma were obtained from prostatectomy specimens of ten patients with pT2–pT3 stage PCa. The expression of TMPRSS2 : ERG, TMPRSS2 : ETV1, and TERT was assessed by means of reverse transcription PCR and quantified using the real-time-based approach. Ki-67, ERG, EMA, AMACR, p16, and p53 expression was evaluated by means of immunohistochemistry (IHC) on tissue microarrays (TMA). Results. Two out of ten cases were identified with different Gleason scores in paired foci of PCa. The expression of most of the IHC markers was quite even between TMA cores of each PCa case, with p16 showing the highest level of heterogeneity (44%; 4/9); 80% (8/10) of multifocal PCa expressed different variants of the TMPRSS2 : ERG transcript or showed a varying status of fusion positivity in paired foci, and the expression levels of the transcript were also heterogeneous. Similarly, 90% (9/10) of PCa showed a different positivity for TERT expression in paired foci. Conclusions. Measurement of TMPRSS2 : ERG and TERT expression offers a valuable tool for identifying most aggressive tumour foci and selecting a relevant treatment of PCa. Keywords: prostate cancer, multifocality, TMPRSS2 : ERG, telomerase

Background/Goal: Ki67 expression has been a valuable prognostic marker in breast cancer, but has not seen broad adoption due to lack of standardization between institutions. Automation could represent a solution. Here we tested 3 automated digital image analysis (DIA) platforms including an open source platform to: (i) Investigate the reproducibility of Ki67 measurement across platforms with supervised classifiers performed by the same operator and by multiple operators. (ii) Compare accuracy of the 3 DIA platforms against outcome (prognostic potential). (iii) Assess inter-laboratory reproducibility of a calibrated DIA tool to evaluate Ki67 in breast cancer among 10 participating labs of the International Ki67 in Breast Cancer Working Group (IKWG). Methods: The Mib-1 antibody (Dako) was used to detect Ki67 (dilution 1:100). HALO (H) (IndicaLabs), QuantCenter (QC) (3DHistech), QuPath (QP) (open-source software) digital image analysis (DIA) platforms were used to evaluate Ki67 expression. As a ground truth, we evaluated Ki67 LI with meticulous manual tissue segmentation using the Spectrum Webscope (SW) (Aperio). Calibration was performed using 30 ER+ breast cancer cases from phase 3 of the IKWG initiative where blocks were centrally cut and stained for Ki67. The inter-laboratory analysis was done with 10 participating laboratories divided into 2 groups where members within the same group were given the same set of images. The outcome cohort consisted of 149 breast cancer cases from the Yale Pathology archives in tissue microarray format. Intra-class correlation coefficient (ICC) was used to measure reproducibility with the pre-specified criterion for success being to exceed 0.80. Kaplan-Meier analysis supported with log-rank test was performed to assess prognostic potential. Results: All 3 DIA platforms showed excellent inter-platform reproducibility (ICC: 0.933, CI: 0.879-0.966). Also, excellent reproducibility was found between all DIA platforms and the reference standard Ki67 values of SW (QP ICC: 0.970, CI: 0.936-0.986; H ICC: 0.968, CI: 0.933-0.985; QC ICC: 0.964, CI: 0.919-0.983). The intra-DIA reproducibility was also excellent for all platforms (QP ICC: 0.992, CI: 0.986-0.996; H ICC: 0.972, CI: 0.924-0.988; QC ICC: 0.978, CI: 0.932-0.991). Comparing each DIA against outcome, the hazard ratios were similar (QP=3.309, H=3.077, QC=3.731). The inter-operator reproducibility was particularly high (ICC: 0.962-0.995). As QP is open source software and also showed the lowest intra-DIA platform variability, we selected the QP platform to investigate inter-laboratory reproducibility among 10 IKWG labs. The different-section ICC across the 10 labs was 0.974 (CI: 0.954 - 0.986). The same-section ICC estimate was 0.984 (CI: 0.971-0.992) for group 1 and 0.978 (CI: 0.956-0.989) for group 2. Conclusions: Our results showed outstanding reproducibility both within and between DIA platforms. We also found the platforms essentially indistinguishable with respect to prediction of breast cancer patient outcome. Automated Ki67 evaluation using a calibrated, open-source DIA platform (QuPath) met the pre-specified criterion of success in the multi-institutional setting. Assessment of clinical utility is planned. Citation Format: Acs B, Leung SC, Pelekanou V, Bai Y, Martinez-Morilla S, Toki M, Chang MC, Gholap A, Jadhav A, Hugh JC, Bigras G, Laurinavicius A, Augulis R, Levenson R, Todd A, Piper T, Virk S, van der Vegt B, Hayes DF, Dowsett M, Nielsen TO, Rimm DL. Analytical validation of an automated digital scoring protocol for Ki67: International multicenter collaboration study [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-02-01.

This report up-dates information on the national situation of cervical cancer screening in the member states of the European Union. There is yet high diversity in the status of cervical screening, and rapid changes expected to occur in the situation in many countries. It is important to underline differences in the health care and other components in order to allow a proper interpretation of the summary results published elsewhere in this Special Issue. The brief national descriptions along with up-dated information on the recent references are available from all but one member states.

Aims: Non-alcoholic hepatic steatosis (HS) is associated with hypertension and increased cardiovascular risk. While Blood pressure hyper-reactive response (HRR) during peak exercise indicates an increased risk of incident hypertension and increased cardiovascular risk, no data on the association of non-alcoholic HS and HRR exists. In this study, we have evaluated the association of HS with HRR. Methods: We included 13 410 consecutive individuals with a mean age: 42.4 ± 8.9 years, 3561 (26.6%) female with normal resting blood pressure and without a previous diagnosis of hypertension, who underwent symptom limited exercise treadmill test, abdominal ultrasonography and clinical and laboratory evaluation. HS was detected by abdominal ultrasonography. HRR was defined by a peak exercise systolic blood pressure >220 mmHg and/or elevation of 15 mmHg or more in diastolic blood pressure from rest to peak exercise. Results: The prevalence of HS was 29.5% ( n = 3956). Overall, 4.6% ( n = 619) of the study population presented a HRR. Subjects with HS had a higher prevalence of HRR (8.1 vs. 3.1%, odds ratio 2.8, 95% CI 2.4—3.3, P

Skeletal muscle-derived stem/progenitor cells (MDSPCs) have been thoroughly investigated and already used in preclinical studies. However, therapeutic potential of MDSPCs isolated using preplate isolation technique for acute kidney injury (AKI) has not been evaluated. We aimed to characterize rat MDSPCs, compare them with bone marrow mesenchymal stem cells (BM-MSCs), and evaluate the feasibility of MDSPCs therapy for gentamicin-induced AKI in rats. We have isolated and characterized rat MDSPCs and BM-MSCs. Characteristics of rat BM-MSCs and MDSPCs were assessed by population doubling time, flow cytometry, immunofluorescence staining, RT-PCR, and multipotent differentiation capacity. Gentamicin-induced AKI model in rat was used to examine MDSPCs therapeutic effect. Physiological and histological kidney parameters were determined. MDSPCs exhibited similar immunophenotype, stem cell gene expression, and multilineage differentiation capacities as BM-MSCs, but they demonstrated higher proliferation rate. Single intravenous MDSPCs injection accelerated functional and morphological kidney recovery, as reflected by significantly lower serum creatinine levels, renal injury score, higher urinary creatinine, and GFR levels. PKH-26-labeled MDSPCs were identified within renal cortex 1 and 2 weeks after cell administration, indicating MDSPCs capacity to migrate and populate renal tissue. In conclusion, MDSPCs are capable of mediating functional and histological kidney recovery and can be considered as potential strategy for AKI treatment.

Biological diversity of breast cancer presents challenges for personalized therapy and necessitates multiparametric approaches to understand and manage the disease. Multiple protein biomarkers tested by immunohistochemistry (IHC), followed by digital image analysis and multivariate statistics of the data, have been shown to be effective in exploring latent profiles of tumor tissue immunophenotype. In this study, based on tissue microarrays of 107 patients with hormone receptor (HR) positive invasive ductal breast carcinoma, we investigated the prognostic value of the integrated immunophenotype to predict overall survival (OS) of the patients. A set of 10 IHC markers (ER, PR, HER2, Ki67, AR, BCL2, HIF-1?, SATB1, p53, and p16) was used. The main factor of the variance was characterized by opposite loadings of ER/PR/AR/BCL2 and Ki67/HIF-1?; it was associated with histological grade but did not predict OS. The second factor was driven by SATB1 expression along with moderate positive HIF-1? and weak negative Ki67 loadings. Importantly, this factor did not correlate with any clinicopathologic parameters, but was an independent predictor of better OS. Ki67 and SATB1 did not reach statistical significance as single predictors; however, high Ki67/SATB1 ratio was an independent predictor of worse OS. In addition, our data indicate potential double prognostic meaning of HIF-1? expression in breast cancer and necessitate focused studies, taking into account the immunophenotype interactions and tissue heterogeneity aspects.

Background In Lithuania renal biopsies (RB) have become routine since 1995. Our study attempted to analyze RB for 5 years in Lithuania. Methods We analyzed data of adult patients who underwent native kidney biopsies in 6 renal units in the period between 1995 - 1999. It accounted for 62.5% of all kidney biopsies, done throughout Lithuania. All biopsy specimens were examined by the same pathologist using light- and immunofluorescence microscopy. Results A total of 316 renal biopsies was analyzed; males : females 1.8 : 1. The mean age was 41.4 +/- 16.7 years. The most common indications for biopsy was nephrotic syndrome (29.1%) and urinary abnormalities (27.8%). After exclusion of inadequate biopsies in the remaining 280 RB, primary glomerulonephritis (GN) accounted for 68.7% and secondary GN for 19.5%. The most frequent forms of primary GN were membranoproliferative GN and immunoglobulin A nephropathy (17.9% and 15.4%, respectively), followed by membranous nephropathy (7.1%) and focal segmental glomerulosclerosis (6.8%). Conclusions The main indication for renal biopsy in Lithuania was nephrotic syndrome, which was followed by isolated urinary abnormalities. The leading type of kidney damage was primary glomerulonephritis, which was 2.4 times more frequent in males than in females. The most frequent form of primary glomerulonephritis was membranoproliferative GN, with dominance in males. Immunoglobulin A nephropathy was the second form of primary GN according to the frequency.

A 14-year-old boy presented with asymptomatic right hydronephrosis detected on routine yearly ultrasound examination. Previously, he had at least two normal renal ultrasonograms, 4 years after remission of acute myeloblastic leukemia, treated by AML-BFM-93 protocol. A function of the right kidney and no damage on the left was confirmed by a DMSA scan. Right retroperitoneoscopic nephrectomy revealed 3 renal arteries with the lower pole artery lying on the pelviureteric junction. Histologically chronic tubulointerstitial nephritis was detected. In the pathogenesis of this severe unilateral renal damage, we suspect the exacerbation of deleterious effects of cytostatic therapy on kidneys with intermittent hydronephrosis.

Patients with prostate cancer who have biochemical recurrence after curative therapy are at higher risk for distant metastasis and cancer specific death. Assessment of aberrant DNA methylation in urine might complement currently used clinical prognostic factors and serve as a noninvasive tool for early prediction of biochemical recurrence after radical prostatectomy.Promoter methylation of 7 genes was evaluated by methylation sensitive polymerase chain reaction in 149 prostate cancer tissues, 37 noncancerous prostate tissues and 17 benign prostatic hyperplasia samples. Quantitative polymerase chain reaction was used for DNA methylation analysis of the urine of 253 patients with prostate cancer and 32 with benign prostatic hyperplasia.In prostate cancer tissue the most frequently methylated genes were RASSF1, GSTP1 and RARB, which combined were positively identified in 85% of cases. These genes were also methylated in the urine of 60% of patients with prostate cancer. RASSF1 was methylated in 45% of prostate cancer urine samples with methylation intensity significantly higher in prostate cancer than in benign prostatic hyperplasia cases (p = 0.018). In a univariate model RASSF1 methylation and the total number of methylated genes in prostate cancer tissue were predictive of time to biochemical recurrence (p = 0.019 and 0.043, respectively). On multivariate analysis RASSF1 methylation together with pathological stage was the most significant predictor of biochemical recurrence in patients with Gleason score 6 tumors when analyzed in tissue and urine (p ≤0.001).Hypermethylation of RASSF1 in cancerous tissue and urine from patients with prostate cancer correlated with biochemical recurrence after radical prostatectomy. The prognostic potential of this biomarker deserves further investigation.

Current definition of the metabolic syndrome (MetS) is intended to identify individuals with multiple cardiovascular risk factors related to insulin resistance and central obesity. However, many centrally obese individuals featuring insulin resistance do not meet current criteria for MetS diagnosis

Collapsing glomerulopathy in HIV and non-HIV patients: A clinicopathological and follow-up study. Background Collapsing glomerulopathy (CG) is a pattern of renal injury that is seen in association with HIV infection and that is increasingly recognized in non-HIV patients. Methods A review of native kidney biopsies with CG that were diagnosed between 1979 and 1997 in 18 HIV and 42 non-HIV patients is provided. Results HIV and non-HIV patients with CG were similar in terms of age, sex ratio, serum creatinine, proteinuria, the extent of collapsing and sclerosing glomerular lesions, and interstitial damage. A slight female predominance was found in both groups. In contrast to non-HIV patients, the HIV group was characterized by a high prevalence of blacks (94 vs. 57%), frequent tubuloreticular inclusions (76 vs. 29%), and microcystic tubular changes (72 vs. 40%). In 13 non-HIV patients, CG was associated with a systemic lupus erythematosus (SLE)-like disease (5), hepatitis C virus (HCV) infection (3), HTLV-I infection, MCTD, acute monoblastic leukemia, multiple myeloma, and cerebral arteritis. Overall, the renal survival of human immunodeficiency virus (HIV) and non-HIV patients with CG was not significantly different. Cox regression revealed that HIV infection had an adverse effect on short-term renal survival, with other significant risk factors being extensive interstitial fibrosis, high serum creatinine, proteinuria, and a low percentage of glomeruli with collapse. The slope of reciprocal creatinine was best predicted by the degree of proteinuria. Serum creatinine correlated with the extent of interstitial fibrosis, the male gender, and the percentage of glomeruli with collapse. Proteinuria was best predicted by the extent of effacement of podocyte foot processes. Conclusions CG shares many clinicopathological similarities in HIV and non-HIV patients. In some non-HIV patients, CG was associated with autoimmune diseases, lymphoproliferative disorders, and viral infections.

Proteinuria is a significant complication affecting renal transplant recipients. It is linked to cardiovascular events, a premature death and graft loss. The prevalence of proteinuria is close to 40% of renal transplant recipients per year. The causes of proteinuria are multiple: glomerular disease, anti-HLA class II antibodies, various medications and tubulointerstitial disease of the graft. It is very important to evaluate the cause of proteinuria, to reduce proteinuria and cardiovascular risk.

Digital image analysis (DA) brings new opportunities to enhance breast cancer pathology testing by providing tools to read tissue microscopy-based data in a more precise, accurate, and high-throughput manner. The applications vary from very practical solutions assisting in quantification of biomarker expression to more complex efforts to analyse multi-dimensional data. We present our DA experiments to enhance HER2 immunohistochemistry (IHC) and FISH testing and to explore multiple IHC biomarker variation profiles in breast cancer.