A case series of two cases of juxta-adrenal schwannoma presenting as adrenal mass lesion and review of the literature

Schwannomas are rare tumors in the retroperitoneal location. They can pose a diagnostic dilemma when presenting as an adrenal mass lesion due to their imaging characteristics. We report two cases of juxta-adrenal schwannomas presenting as symptomatic adrenal mass lesions. In both the cases, the clinical examination and functional evaluation was unremarkable and the radiological examination revealed a mixed intense adrenal mass lesion in one case with predominantly hyperintense areas and a very hyperintense lesion in another, in T2-weighted images, mimicking a adrenocortical malignancy and a pheochromocytoma respectively. Both cases were treated by surgical excision. Histopathological examination established the correct diagnosis of schwannoma, which was confirmed by immunohistochemical staining. Juxta-adrenal schwannoma is rare tumors of the retroperitoneum, which should also be borne in mind whenever encountering large nonsecreting adrenal tumors. We report a unique imaging characteristic, which helps in preoperative identification these rare lesions

Nuclear morphometrics and chromatin condensation patterns as disease biomarkers using a mobile microscope

10.1371/journal.pone.0218757PLoS ONE147e021875

Clinical and pathologic factors predicting reclassification in active surveillance cohorts

ABSTRACT The incidence of small, lower risk well-differentiated prostate cancer is increasing and almost half of the patients with this diagnosis are candidates for initial conservative management in an attempt to avoid overtreatment and morbidity associated with surgery or radiation. A proportion of patients labeled as low risk, candidates for Active Surveillance (AS), harbor aggressive disease and would benefit from definitive treatment. The focus of this review is to identify clinicopathologic features that may help identify these less optimal AS candidates. A systematic Medline/PubMed Review was performed in January 2017 according to PRISMA guidelines; 83 articles were selected for full text review according to their relevance and after applying limits described. For patients meeting AS criteria including Gleason Score 6, several factors can assist in predicting those patients that are at higher risk for reclassification including higher PSA density, bilateral cancer, African American race, small prostate volume and low testosterone. Nomograms combining these features improve risk stratification. Clinical and pathologic features provide a significant amount of information for risk stratification (>70%) for patients considering active surveillance. Higher risk patient subgroups can benefit from further evaluation or consideration of treatment. Recommendations will continue to evolve as data from longer term AS cohorts matures

Machine Learning for Nuclear Mechano-Morphometric Biomarkers in Cancer Diagnosis

Current cancer diagnosis employs various nuclear morphometric measures. While these have allowed accurate late-stage prognosis, early diagnosis is still a major challenge. Recent evidence highlights the importance of alterations in mechanical properties of single cells and their nuclei as critical drivers for the onset of cancer. We here present a method to detect subtle changes in nuclear morphometrics at single-cell resolution by combining fluorescence imaging and deep learning. This assay includes a convolutional neural net pipeline and allows us to discriminate between normal and human breast cancer cell lines (fibrocystic and metastatic states) as well as normal and cancer cells in tissue slices with high accuracy. Further, we establish the sensitivity of our pipeline by detecting subtle alterations in normal cells when subjected to small mechano-chemical perturbations that mimic tumor microenvironments. In addition, our assay provides interpretable features that could aid pathological inspections. This pipeline opens new avenues for early disease diagnostics and drug discovery.National Science Foundation (U.S.) (1651995)United States. Defense Advanced Research Projects Agency (W911NF-16-1-0551)United States. Office of Naval Research (N00014-17-1-2147

Predicting cell lineages using autoencoders and optimal transport

10.1371/journal.pcbi.1007828PLoS Computational Biology164e100782

Screening of urine identifies PLA2G16 as a field defect methylation biomarker for prostate cancer detection.

BackgroundProstate cancer (PC) is a multifocal disease. DNA methylation alterations are not restricted to the immediate peritumor environment, but spatially widespread in the adjacent and distant histologically normal prostate tissues. In the current study, we utilized high-throughput methylation arrays to identify epigenetic changes in the urine from men with and without cancer.Design, setting, and participantsDNA urine samples were enriched for methylated fragments using MBD methyl-binding antibodies and applied to high density CytoScanHD arrays. Significant loci were validated using quantitative pyrosequencing and binary logistic regression modeling applied to urine sample analyses in a training (n = 83) and validation approach (n = 84). Methylation alterations in prostate tissues using pyrosequencing at the PLA2G16 locus were examined in 38 histologically normal specimens from men with (TA, n = 26) and without (NTA, n = 12) cancer and correlated to gene expression.ResultsMethylation microarrays identified 3,986 loci showing significantly altered methylation in the urine samples from patients with PC compared to those without (TA vs NTA; pConclusionPLA2G16 methylation defines an extensive field defect in histologically normal prostate tissue associated with PC. PLA2G16 methylation in urine and prostate tissues can detect the presence of PC

Multi-domain translation between single-cell imaging and sequencing data using autoencoders

The development of single-cell methods for capturing different data modalities including imaging and sequencing has revolutionized our ability to identify heterogeneous cell states. Different data modalities provide different perspectives on a population of cells, and their integration is critical for studying cellular heterogeneity and its function. While various methods have been proposed to integrate different sequencing data modalities, coupling imaging and sequencing has been an open challenge. We here present an approach for integrating vastly different modalities by learning a probabilistic coupling between the different data modalities using autoencoders to map to a shared latent space. We validate this approach by integrating single-cell RNA-seq and chromatin images to identify distinct subpopulations of human naive CD4+ T-cells that are poised for activation. Collectively, our approach provides a framework to integrate and translate between data modalities that cannot yet be measured within the same cell for diverse applications in biomedical discovery.ISSN:2041-172

Combination therapy with androgen deprivation for hormone sensitive prostate cancer: A new frontier

Androgen deprivation therapy (ADT) has been the standard of care for the last 75 years in metastatic hormone sensitive prostate cancer (PCa). However, this approach is rarely curative. Recent clinical trials have demonstrated that ADT combined with other agents, notably docetaxel and abiraterone, lead to improved survival. The mechanisms surrounding this improved cancer outcomes are incompletely defined. The response of cancer cells to ADT includes apoptosis and cell death, but a significant fraction remains viable. Our laboratory has demonstrated both in vitro and in vivo that cellular senescence occurs in a subset of these cells. Cellular senescence is a phenotype characterized by cell cycle arrest, senescence-associated β-galactosidase (SA-β-gal), and a hypermetabolic state. Positive features of cellular senescence include growth arrest and immune stimulation, although persistence may release cytokines and growth factors that are detrimental. Senescent tumor cells generate a catabolic state with increased glycolysis, protein turnover and other metabolic changes that represent targets for drugs, like metformin, to be applied in a synthetic lethal approach. This review examines the response to ADT and the putative role of cellular senescence as a biomarker and therapeutic target in this context. Keywords: Prostate cancer, Cellular senescence, Androgen deprivation therapy, Combination therapy, Synthetic lethal targeting, Metformin, Statin

Dysregulation of Sirtuin 2 (SIRT2) and histone H3K18 acetylation pathways associates with adverse prostate cancer outcomes

Abstract Background Histones undergo extensive post-translational modifications and this epigenetic regulation plays an important role in modulating transcriptional programs capable of driving cancer progression. Acetylation of histone H3K18, associated with gene activation, is enhanced by P300 and opposed by the deacetylase Sirtuin2 (SIRT2). As these enzymes represent an important target for cancer therapy, we sought to determine whether the underlying genes are altered during prostate cancer (PCa) progression. Methods Tissue microarrays generated from 71 radical prostatectomy patients were initially immunostained for H3K18Ac, P300 and SIRT2. Protein levels were quantified using VECTRA automation and correlated with clinicopathologic parameters. The Cancer Genome Atlas (TGCA, n = 499) and Gene Expression Omnibus (n = 504) databases were queried for expression, genomic and clinical data. Statistics were performed using SPSSv23. Results Nuclear histone H3K18Ac staining increases in primary cancer (p = 0.05) and further in metastases (p < 0.01) compared to benign on tissue arrays. P300 protein expression increases in cancer (p = 0.04) and metastases (p < 0.001). A progressive decrease in nuclear SIRT2 staining occurs comparing benign to cancer or metastases (p = 0.04 and p = 0.03 respectively). Decreased SIRT2 correlates with higher grade cancer (p = 0.02). Time to Prostate Specific Antigen (PSA) recurrence is shorter in patients exhibiting high compared to low H3K18Ac expression (350 vs. 1542 days respectively, P = 0.03). In GEO, SIRT2 mRNA levels are lower in primary and metastatic tumors (p = 0.01 and 0.001, respectively). TGCA analysis demonstrates SIRT2 deletion in 6% and increasing clinical stage, positive margins and lower PSA recurrence-free survival in patients with SIRT2 loss/deletion (p = 0.01, 0.04 and 0.04  respectively). In this dataset, a correlation between decreasing SIRT2 and increasing P300 mRNA expression occurs in tumor samples (R = −0.46). Conclusions In multiple datasets, decreases in SIRT2 expression portend worse clinicopathologic outcomes. Alterations in SIRT2-H3K18Ac suggest altered P300 activity and identify a subset of tumors that could benefit from histone deacetylation inhibition

Additional file 1: Table S1. of Dysregulation of Sirtuin 2 (SIRT2) and histone H3K18 acetylation pathways associates with adverse prostate cancer outcomes

Clinicopathological characteristics of TMA array patients This table describes the clinical and pathological characteristics of the 71 patients, whose samples were used for TMA construction. (DOCX 13 kb