Extended pelvic lymph node dissection at the time of robot-assisted radical prostatectomy: Impact of surgical volume on efficacy and complications in a single-surgeon series

INTRODUCTION: We assessed the impact of surgical volume on perioperative outcomes and complications of robotic extended pelvic lymph node dissection (ePLND). METHODS: From November 2008 to October 2012, a total of 233 consecutive patients with intermediate- or high-risk clinically localized prostate cancer underwent robot-assisted radical prostatectomy (RARP) and ePLND by a single, experienced open and laparoscopic surgeon. Data were prospectively collected. Complications were classified according to the Modified Clavien System. Complications potentially related to ePLND were documented. The minimum follow-up was 3 months. To evaluate the impact of surgical volume on the results, 4 patient subgroups (subgroup 1: cases 1-59; 2: 60-117; 3: 118-175; 4: 176-233) were compared using the Chi-squared and Kruskal-Wallis tests. RESULTS: The mean (range) operative time for ePLND was 79 minutes (range: 48-144), with a steady performance over time (p = 0.784). The count of resected lymph nodes plateaued after 60 procedures (mean [range]: 13 [range: 6-32], 15 [range: 7-34], 17 [range: 8-41], 16 [range: 8-42] in Groups 1 to 4, respectively, p = 0.001). Tumour lymph node involvement was 12% in Groups 1 and 2, 7% in Group 3 and 9% in Group 4 (p = 0.075). Overall, 115 complications were reported in 98/233 patients (42%), with a significant decrease after 175 cases (p = 0.028). In Group 4, 3 patients reported an ePLND-related bleeding requiring open revision. Lymphoceles were detected in 10/233 patients (4.2%) and 1 patient (1.7%) in each of the Groups 2 to 4 required a percutaneous drainage. CONCLUSIONS: A surgeon with extensive experience is expected to achieve a safe learning curve for ePLND during RARP. A learning curve of 60 cases is suggested for optimal lymph node yield

Treatment Outcomes for Men with Clinical Stage II Nonseminomatous Germ Cell Tumours Treated with Primary Retroperitoneal Lymph Node Dissection: A Systematic Review

CONTEXT Guidelines recommend primary retroperitoneal lymph node dissection (RPLND) as a treatment option for tumour marker-negative stage II nonseminomatous germ cell tumour (NSGCT). OBJECTIVE To review the literature on oncological outcomes for men with stage II NSGCT treated with RPLND. EVIDENCE ACQUISITION A systematic review of studies describing clinicopathological outcomes following primary RPLND in stage II NSGCT was conducted in the MEDLINE, EMBASE, and Cochrane Database of Systematic Reviews databases according to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) statement. Baseline data, perioperative and postoperative parameters, and oncological outcomes were collected. EVIDENCE SYNTHESIS In total, 12 of 4387 studies were included, from which we collected data for 835 men. Among men with clinical stage II NSGCT, pathological stage II was confirmed in 615 of 790 patients (78%). Most studies administered adjuvant chemotherapy in cases with large lymph nodes, multiple affected lymph nodes, or persistently elevated tumour markers. Recurrence was observed in 12-40% of patients without adjuvant chemotherapy and 0-4% of patients who received adjuvant chemotherapy. CONCLUSIONS The literature describing RPLND in clinical stage II NSGCT is heterogeneous and no meta-analysis was possible, but RPLND can provide accurate staging and may be curative in selected patients. PATIENT SUMMARY We reviewed the literature to summarise results after surgical removal of enlarged lymph nodes in the back of the abdomen in men with testis cancer. This procedure provides accurate information on how far the cancer has spread and may provide a cure in selected patients

Open Versus Robotic Cystectomy: A Propensity Score Matched Analysis Comparing Survival Outcomes

Background: To assess the differential effect of robotic assisted radical cystectomy (RARC) versus open radical cystectomy (ORC) on survival outcomes in matched analyses performed on a large multicentric cohort. Methods: The study included 9757 patients with urothelial bladder cancer (BCa) treated in a consecutive manner at each of 25 institutions. All patients underwent radical cystectomy with bilateral pelvic lymphadenectomy. To adjust for potential selection bias, propensity score matching 2:1 was performed with two ORC patients matched to one RARC patient. The propensity-matched cohort included 1374 patients. Multivariable competing risk analyses accounting for death of other causes, tested association of surgical technique with recurrence and cancer specific mortality (CSM), before and after propensity score matching. Results: Overall, 767 (7.8%) patients underwent RARC and 8990 (92.2%) ORC. The median follow-up before and after propensity matching was 81 and 102 months, respectively. In the overall population, the 3-year recurrence rates and CSM were 37% vs. 26% and 34% vs. 24% for ORC vs. RARC (all p values > 0.1), respectively. On multivariable Cox regression analyses, RARC and ORC had similar recurrence and CSM rates before and after matching (all p values > 0.1). Conclusions: Patients treated with RARC and ORC have similar survival outcomes. This data is helpful in consulting patients until long term survival outcomes of level one evidence is available

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

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

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

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

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation