Retroperitoneal lymph node dissection for residual masses after chemotherapy in nonseminomatous germ cell testicular tumor

<p>Abstract</p> <p>Background</p> <p>Retroperitoneal lymph node dissection has been advocated for the management of post-chemotherapy (PC-RPLND) residual masses of non-seminomatous germ cell tumors of the testis (NSGCT). There remains some debate as to the clinical benefit and associated morbidity. Our objective was to report our experience with PC-RPLND in NSGCT.</p> <p>Methods</p> <p>We have reviewed the clinical, pathologic and surgical parameters associated with PC-RPLND in a single institution. Between 1994 and 2008, three surgeons operated 73 patients with residual masses after cisplatin-based chemotherapy for a metastatic testicular cancer. Patients needed to have normal postchemotherapy serum tumor markers, no prior surgical attempts to resect retroperitoneal masses and resectable retroperitoneal tumor mass at surgery to be included in this analysis</p> <p>Results</p> <p>Mean age was 30.4 years old. Fifty-three percent had mixed germ cell tumors. The mean size of retroperitoneal metastasis was 6.3 and 4.0 cm, before and post-chemotherapy, respectively. In 56% of patients, the surgeon was able to perform a nerve sparing procedure. The overall complication rate was 27.4% and no patient died due to surgical complications. The pathologic review showed presence of fibrosis/necrosis, teratoma and viable tumor (non-teratoma) in 27 (37.0%), 30 (41.1%) and 16 (21.9%) patients, respectively. The subgroups presenting fibrosis and large tumors were more likely to have a surgical complication and had less nerve sparing procedures.</p> <p>Conclusion</p> <p>PC-RPLND is a relatively safe procedure. The presence of fibrosis and large residual masses are associated with surgical complications and non-nerve-sparing procedure.</p

Asporin is a stromally expressed marker associated with prostate cancer progression.

BACKGROUND: Prostate cancer shows considerable heterogeneity in disease progression and we propose that markers expressed in tumour stroma may be reliable predictors of aggressive tumour subtypes. METHODS: We have used Kaplan-Meier, univariate and multivariate analysis to correlate the expression of Asporin (ASPN) mRNA and protein with prostate cancer progression in independent cohorts. We used immunohistochemistry and H scoring to document stromal localisation of ASPN in a tissue microarray and mouse prostate cancer model, and correlated expression with reactive stroma, defined using Masson Trichrome staining. We used cell cultures of primary prostate cancer fibroblasts treated with serum-free conditioned media from prostate cancer cell lines to examine regulation of ASPN mRNA in tumour stromal cells. RESULTS: We observed increased expression of ASPN mRNA in a data set derived from benign vs tumour microdissected tissue, and a correlation with biochemical recurrence using Kaplan-Meier and Cox proportional hazard analysis. ASPN protein localised to tumour stroma and elevated expression of ASPN was correlated with decreased time to biochemical recurrence, in a cohort of 326 patients with a median follow up of 9.6 years. Univariate and multivariate analysis demonstrated that ASPN was correlated with progression, as were Gleason score, and clinical stage. Additionally, ASPN expression correlated with the presence of reactive stroma, suggesting that it may be a stromal marker expressed in response to the presence of tumour cells and particularly with aggressive tumour subtypes. We observed expression of ASPN in the stroma of tumours induced by p53 inhibition in a mouse model of prostate cancer, and correlation with neuroendocrine marker expression. Finally, we demonstrated that ASPN transcript expression in normal and cancer fibroblasts was regulated by conditioned media derived from the PC3, but not LNCaP, prostate cancer cell lines. CONCLUSIONS: Our results suggest that ASPN is a stromally expressed biomarker that correlates with disease progression, and is observed in reactive stroma. ASPN expression in stroma may be part of a stromal response to aggressive tumour subtypes.British Journal of Cancer advance online publication, 2 February 2017; doi:10.1038/bjc.2017.15 www.bjcancer.com

A General Framework for Interrogation of mRNA Stability Programs Identifies RNA-Binding Proteins that Govern Cancer Transcriptomes

Widespread remodeling of the transcriptome is a signature of cancer; however, little is known about the post-transcriptional regulatory factors, including RNA-binding proteins (RBPs) that regulate mRNA stability, and the extent to which RBPs contribute to cancer-associated pathways. Here, by modeling the global change in gene expression based on the effect of sequence-specific RBPs on mRNA stability, we show that RBP-mediated stability programs are recurrently deregulated in cancerous tissues. Particularly, we uncovered several RBPs that contribute to the abnormal transcriptome of renal cell carcinoma (RCC), including PCBP2, ESRP2, and MBNL2. Modulation of these proteins in cancer cell lines alters the expression of pathways that are central to the disease and highlights RBPs as driving master regulators of RCC transcriptome. This study presents a framework for the screening of RBP activities based on computational modeling of mRNA stability programs in cancer and highlights the role of post-transcriptional gene dysregulation in RCC. Perron et al. develop a computational approach that models the functional activity of RBPs in individual cancer samples by monitoring their associated RNA stability programs. Applying this method to renal cell carcinoma transcriptomes, the authors identify RBPs that enhance cancer-associated pathways including hypoxia and cell cycle

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Update on HHV-8-Associated Malignancies

The human herpesvirus 8 (HHV-8) is the oncogenic virus associated with Kaposi’s sarcoma (KS) and lymphoproliferative disorders, namely, primary effusion lymphoma and multicentric Castleman’s disease. KS is among the most common malignancies seen in HIV-infected patients despite the decreased incidence of KS in the era of highly active antiretroviral therapy. Advances in molecular pathology reveal HHV-8 tumorigenesis is mediated through molecular mimicry wherein viral-encoded proteins can activate several cellular signaling cascades while evading immune surveillance. This knowledge has led to the evolution of multiple therapeutic strategies against specific molecular targets. Many such therapeutic modalities have shown activity, but none have proven to be curative. Identifying possible prognostic factors is another active area of research. This review summarizes the recent developments in the fields of virus transmission, molecular biology, and treatment of HHV-8-related neoplasms