GFAPα-IgG, when detected in CSF, is highly specific for an immunotherapy-responsive autoimmune CNS disorder, sometimes with paraneoplastic cause. Ann Neurol 2017;81:298-309.

BackgroundEpithelial ovarian cancer is the leading cause of gynecologic cancer deaths. Most patients respond initially to platinum-based chemotherapy after surgical debulking, however relapse is very common and ultimately platinum resistance emerges. Understanding the mechanism of tumor growth, metastasis and drug resistant relapse will profoundly impact the therapeutic management of ovarian cancer.Methods/Principal FindingsUsing patient tissue microarray (TMA), in vitro and in vivo studies we report a role of of cystathionine-beta-synthase (CBS), a sulfur metabolism enzyme in ovarian carcinoma. We report here that the expression of cystathionine-beta-synthase (CBS), a sulfur metabolism enzyme, is common in primary serous ovarian carcinoma. The in vitro effects of CBS silencing can be reversed by exogenous supplementation with the GSH and H2S producing chemical Na2S. Silencing CBS in a cisplatin resistant orthotopic model in vivo by nanoliposomal delivery of CBS siRNA inhibits tumor growth, reduces nodule formation and sensitizes ovarian cancer cells to cisplatin. The effects were further corroborated by immunohistochemistry that demonstrates a reduction of H&E, Ki-67 and CD31 positive cells in si-RNA treated as compared to scrambled-RNA treated animals. Furthermore, CBS also regulates bioenergetics of ovarian cancer cells by regulating mitochondrial ROS production, oxygen consumption and ATP generation. This study reports an important role of CBS in promoting ovarian tumor growth and maintaining drug resistant phenotype by controlling cellular redox behavior and regulating mitochondrial bioenergetics.ConclusionThe present investigation highlights CBS as a potential therapeutic target in relapsed and platinum resistant ovarian cancer.

No abstract

A B S T R A C T PurposeIn men who are at high-risk of prostate cancer, progression and death from cancer after radical retropubic prostatectomy (RRP), limited prognostic information is provided by established prognostic features. The objective of this study was to develop a model predictive of outcome in this group of patients. MethodsCandidate genes were identified from microarray expression data from 102 laser capture microdissected prostate tissue samples. Candidates were overexpressed in tumor compared with normal prostate and more frequently in Gleason patterns 4 and 5 than in 3. A case control study of 157 high-risk patients, matched on Gleason score and stage with systemic progression or death of prostate cancer as the end point, was used to evaluate the expression of candidate genes and build a multivariate model. Tumor was collected from the highest Gleason score in paraffinembedded blocks and the gene expression was quantified by real-time reverse transcription polymerase chain reaction. Validation of the final model was performed on a separate case-control study of 57 high-risk patients who underwent RRP. ResultsA model incorporating gene expression of topoisomerase-2a, cadherin-10, the fusion status based on ERG, ETV1, and ETV4 expression, and the aneuploidy status resulted in a 0.81 area under the curve (AUC) in receiver operating characteristic statistical analysis for the identification of men with systemic progression and death from high grade prostate cancer. The AUC was 0.79 in the independent validation study. ConclusionThe model can identify men with high-risk prostate cancer who may benefit from more intensive postoperative follow-up and adjuvant therapies.

No abstract