PROLIFERATION OF B AND T CELLS IN MIXED LYMPHOCYTE CULTURES

Electrophoretically fractionated CBA/Ca spleen T cells alone respond to allogeneic cells in one-way MLC and to PHA. They do not respond to E. coli LPS. B cells alone do not respond to allogeneic cells nor to PHA, but do respond to LPS. When karyotypically distinguishable syngeneic mixtures of T and B lymphocytes are stimulated with allogeneic cells, at the most 5% of mitoses on 5–9th culture day are of B cell origin. This indicates that B cells are not substantially recruited to proliferate in the MLC

Detection of breast cancer lymph node metastases in frozen sections with a point-of care low-cost microscope scanner

Background Detection of lymph node metastases is essential in breast cancer diagnostics and staging, affecting treatment and prognosis. lntraoperative microscopy analysis of sentinel lymph node frozen sections is standard for detection of axillary metastases but requires access to a pathologist for sample analysis. Remote analysis of digitized samples is an alternative solution but is limited by the requirement for high-end slide scanning equipment. Objective To determine whether the image quality achievable with a low-cost, miniature digital microscope scanner is sufficient for detection of metastases in breast cancer lymph node frozen sections. Methods Lymph node frozen sections from 79 breast cancer patients were digitized using a prototype miniature microscope scanner and a high-end slide scanner. Images were independently reviewed by two pathologists and results compared between devices with conventional light microscopy analysis as ground truth. Results Detection of metastases in the images acquired with the miniature scanner yielded an overall sensitivity of 91% and specificity of 99% and showed strong agreement when compared to light microscopy (k = 0.91). Strong agreement was also observed when results were compared to results from the high-end slide scanner (k = 0.94). A majority of discrepant cases were micrometastases and sections of which no anticytokeratin staining was available. Conclusion Accuracy of detection of metastatic cells in breast cancer sentinel lymph node frozen sections by visual analysis of samples digitized using low-cost, point-of-care microscopy is comparable to analysis of digital samples scanned using a high-end, whole slide scanner. This technique could potentially provide a workflow for digital diagnostics in resource-limited settings, facilitate sample analysis at the point-of-care and reduce the need for trained experts on-site during surgical procedures.Peer reviewe

Deep learning based tissue analysis predicts outcome in colorectal cancer

Image-based machine learning and deep learning in particular has recently shown expert-level accuracy in medical image classification. In this study, we combine convolutional and recurrent architectures to train a deep network to predict colorectal cancer outcome based on images of tumour tissue samples. The novelty of our approach is that we directly predict patient outcome, without any intermediate tissue classification. We evaluate a set of digitized haematoxylin-eosin-stained tumour tissue microarray (TMA) samples from 420 colorectal cancer patients with clinicopathological and outcome data available. The results show that deep learning-based outcome prediction with only small tissue areas as input outperforms (hazard ratio 2.3; CI 95% 1.79-3.03; AUC 0.69) visual histological assessment performed by human experts on both TMA spot (HR 1.67; CI 95% 1.28-2.19; AUC 0.58) and whole-slide level (HR 1.65; CI 95% 1.30-2.15; AUC 0.57) in the stratification into low-and high-risk patients. Our results suggest that state-of-the-art deep learning techniques can extract more prognostic information from the tissue morphology of colorectal cancer than an experienced human observer.Peer reviewe

Identification of tumor epithelium and stroma in tissue microarrays using texture analysis

<p>Abstract</p> <p>Background</p> <p>The aim of the study was to assess whether texture analysis is feasible for automated identification of epithelium and stroma in digitized tumor tissue microarrays (TMAs). Texture analysis based on local binary patterns (LBP) has previously been used successfully in applications such as face recognition and industrial machine vision. TMAs with tissue samples from 643 patients with colorectal cancer were digitized using a whole slide scanner and areas representing epithelium and stroma were annotated in the images. Well-defined images of epithelium (n = 41) and stroma (n = 39) were used for training a support vector machine (SVM) classifier with LBP texture features and a contrast measure C (LBP/C) as input. We optimized the classifier on a validation set (n = 576) and then assessed its performance on an independent test set of images (n = 720). Finally, the performance of the LBP/C classifier was evaluated against classifiers based on Haralick texture features and Gabor filtered images.</p> <p>Results</p> <p>The proposed approach using LPB/C texture features was able to correctly differentiate epithelium from stroma according to texture: the agreement between the classifier and the human observer was 97 per cent (kappa value = 0.934, <it>P </it>< 0.0001) and the accuracy (area under the ROC curve) of the LBP/C classifier was 0.995 (CI95% 0.991-0.998). The accuracy of the corresponding classifiers based on Haralick features and Gabor-filter images were 0.976 and 0.981 respectively.</p> <p>Conclusions</p> <p>The method illustrates the capability of automated segmentation of epithelial and stromal tissue in TMAs based on texture features and an SVM classifier. Applications include tissue specific assessment of gene and protein expression, as well as computerized analysis of the tumor microenvironment.</p> <p>Virtual slides</p> <p>The virtual slide(s) for this article can be found here: <url>http://www.diagnosticpathology.diagnomx.eu/vs/4123422336534537</url></p

New prostate cancer grade grouping system predicts survival after radical prostatectomy

Histological Gleason grading of prostate cancer has been through modifications and conjoined into a Grade Grouping system recently. The aim of this study was to determine whether the new Grade Grouping system predicts disease-specific and all-cause mortality after radical prostatectomy. We constructed a clinical database consisting of all consecutively radical prostatectomy treated men between 1983 and 1998 and between 2000 and 2005 at the Helsinki University Hospital and at the Turku University Hospital, respectively. Patients' all-cause and prostate cancer specific mortality information was updated in November 2015 from the Finnish Cancer Registry. Secondary therapy information was also available from the patients' records at Helsinki. Univariate and multivariate statistical analyses were performed to assess predictive significance of the Grade Grouping system. Grade Grouping associated independently with increased risk of prostate cancer specific mortality within 15 years of follow-up in a multivariable model containing age at operation, diagnostic prostate-specific antigen, pathological stage and lymph node status at operation. Additionally, the all-cause mortality-free survival time and time to secondary therapies were different between the Grade Groups, emphasized in the subanalysis of Grade Groups 1-2 versus Grade Groups 3-5. We can conclude that the new Grade Grouping system is feasible in predicting prostate cancer specific survival after radical surgical treatment. Grade Grouping offers a simpler way to interpret the predicted course of the disease to individual patients and thus may help in justifying more conservative follow-up approaches, especially in the lower Grade Group patients. (C) 2018 The Authors. Published by Elsevier Inc.Peer reviewe

Phospholipase PLA2G7, associated with aggressive prostate cancer, promotes prostate cancer cell migration and invasion and is inhibited by statins

Prostate cancer is the second leading cause of cancer mortality in men in developed countries. Due to the heterogeneous nature of the disease, design of novel personalized treatments is required to achieve efficient therapeutic responses. We have recently identified phospholipase 2 group VII (PLA2G7) as a potential drug target especially in ERG oncogene positive prostate cancers. Here, the expression profile of PLA2G7 was studied in 1137 prostate cancer and 409 adjacent non-malignant prostate tissues using immunohistochemistry to validate its biomarker potential and putative association with disease progression. In order to reveal the molecular alterations induced by PLA2G7 impairment, lipidomic and gene expression profiling was performed in response to PLA2G7 silencing in cultured prostate cancer cells. Moreover, the antineoplastic effect of statins combined with PLA2G7 impairment was studied in prostate cancer cells to evaluate the potential of repositioning of in vivo compatible drugs developed for other indications towards anti-cancer purposes. The results indicated that PLA2G7 is a cancer-selective biomarker in 50% of prostate cancers and associates with aggressive disease. The alterations induced by PLA2G7 silencing highlighted the potential of PLA2G7 inhibition as an anti-proliferative, pro-apoptotic and anti-migratorial therapeutic approach in prostate cancer. Moreover, the anti-proliferative effect of PLA2G7 silencing was potentiated by lipid-lowering statins in prostate cancer cells. Taken together, our results support the potential of PLA2G7 as a biomarker and a drug target in prostate cancer and present a rationale for combining PLA2G7 inhibition with the use of statins in prostate cancer management

Podocalyxin Is a Marker of Poor Prognosis in Pancreatic Ductal Adenocarcinoma

Aim of the Study Podocalyxin-like 1 is a transmembrane glyco-protein whose overexpression associates in many cancers with poor prognosis and unfavorable clinicopathological characteristics. Until now, its prognostic value has never been studied in pancreatic ductal adenocarcinoma (PDAC). The aim of this study was to investigate podocalyxin expression in PDAC by a novel monoclonal antibody and a commercially available polyclonal antibody. Patients and Materials With tissue microarrays and immuno-histochemistry, podocalyxin expression evaluation involved 168 PDAC patients. The associa-tions of the podocalyxin tumor expression with clinicopathological variables were explored by Fisher's exact test and the linear-by-linear test. Survival analyses were by Kaplan-Meier anal-ysis and the Cox proportional hazard model. Results The polyclonal antibody revealed membranous podocalyxin expression in 73 (44.0%) specimens and the monoclonal antibody was highly expressed in 36 (21.8%) cases. Membranous expression by the polyclonal antibody was associated with T classification (p=0.045) and perineural invasion (p=0.005), and high expression by the mono-clonal antibody with poor differentiation (p=0.033). High podocalyxin expression associated significantly with higher risk of death from PDAC by both the polyclonal antibody (hazard ratio (HR) = 1.62; 95% confidence interval (CI) 1.12-2.33; p=0.01) and the monoclonal antibody (HR = 2.10, 95% CI 1.38-3.20; p=/<20%), and perivascular invasion (respectively as HR = 2.03; 95% CI 1.32-3.13, p=0.001; and as HR = 2.36; 95% CI 1.47-3.80, p Conclusion We found podocalyxin to be an independent factor for poor prognosis in PDAC. To our knowledge, this is the first such report of its prognostic value.Peer reviewe

PROX1 and beta-catenin are prognostic markers in pancreatic ductal adenocarcinoma

Background: The Wnt/beta-catenin pathway has a key role in regulating cellular processes and its aberrant signaling can lead to cancer development. The role of beta-catenin expression in pancreatic ductal adenocarcinoma is somewhat controversial. Transcription factor PROX1 is a target of Wnt/beta-catenin signaling and it is involved in carcinogenesis through alterations in its expression. The actions can be either oncogenic or tumor suppressive depending on the tissue. The aim of this study was to investigate PROX1 and beta-catenin expression in pancreatic ductal adenocarcinoma (PDAC). Methods: Expression of PROX1 and beta-catenin were evaluated in 156 patients by immunohistochemistry of tissue microarrays. Associations between tumor marker expression and clinicopathological parameters were assessed by the Fischer's exact-test or the linear-by-linear association test. The Kaplan-Meier method and log-rank test were used for survival analysis. Uni- and multivariate survival analyses were carried out by the Cox regression proportional hazard model. Results: High PROX1 expression was seen in 74 (48 %) tumors, and high beta-catenin expression in 100 (65 %). High beta-catenin expression was associated with lower tumor grade (p = 0.025). High PROX1 and beta-catenin expression associated significantly with lower risk of death from PDAC in multivariate analysis (HR = 0.63; 95 % CI 0.42-0.95, p = 0.026; and HR = 0.54; 95 % CI 0.35-0.82, p = 0.004; respectively). The combined high expression of PROX1 and beta-catenin also predicted lower risk of death from PDAC (HR = 0.46; 95 % CI 0.28-0.76, p = 0.002). Conclusion: In conclusion, high PROX1 and beta-catenin expression were independent factors for better prognosis in pancreatic ductal adenocarcinoma.Peer reviewe

Associations of PTEN and ERG with Magnetic Resonance Imaging Visibility and Assessment of Non–organ-confined Pathology and Biochemical Recurrence After Radical Prostatectomy

Background: Diagnosing clinically significant prostate cancer (PCa) is challenging, but may be facilitated by biomarkers and multiparametric magnetic resonance imaging (MRI). Objective: To determine the association between biomarkers phosphatase and tensin homolog (PTEN) and ETS-related gene (ERG) with visible and invisible PCa lesions in MRI, and to predict biochemical recurrence (BCR) and non-organ-confined (non-OC) PCa by integrating clinical, MRI, and biomarker-related data. Design, setting, and participants: A retrospective analysis of a population-based cohort of men with PCa, who underwent preoperative MRI followed by radical prostatectomy (RP) during 2014-2015 in Helsinki University Hospital (n = 346), was conducted. A tissue microarray corresponding to the MRI-visible and MRI-invisible lesions in RP specimens was constructed and stained for PTEN and ERG. Outcome measurements and statistical analysis: Associations of PTEN and ERG with MRI-visible and MRI-invisible lesions were examined (Pearson's chi 2 test), and predictions of non-OC disease together with clinical and MRI parameters were determined (area under the receiver operating characteristic curve and logistic regression analyses). BCR prediction was analyzed by Kaplan-Meier and Cox proportional hazard analyses. Results and limitations: Patients with MRI-invisible lesions (n = 35) had less PTEN loss and ERG-positive expression compared with patients (n = 90) with MRI-visible lesions (17.2% vs 43.3% [p = 0.006]; 8.6% vs 20.0% [p = 0.125]). Patients with invisible lesions had better, but not statistically significantly improved, BCR-free survival probability in Kaplan-Meier analyses (p = 0.055). Rates of BCR (5.7% vs 21.1%; p = 0.039), extraprostatic extension (11.4% vs 44.6%; p < 0.001), seminal vesicle invasion (0% vs 21.1%; p = 0.003), and lymph node metastasis (0% vs 12.2%; p = 0.033) differed between the groups in favor of patients with MRI-invisible lesions. Biomarkers had no independent role in predicting non-OC disease or BCR. The short follow-up period was a limitation. Conclusions: PTEN loss, BCR, and non-OC RP findings were more often encountered with MRI-visible lesions. Patient summary: Magnetic resonance imaging (MRI) of the prostate misses some cancer lesions. MRI-invisible lesions seem to be less aggressive than MRI-visible lesions. (C) 2020 European Association of Urology. Published by Elsevier B.V. All rights reserved.Peer reviewe