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Other than slight prolongation of duration of bladder irrigation and hospital stay, the intermittent or continuous use of anticoagulant therapy did not adversely affect outcomes of HoLEP, suggesting that this approach is an attractive approach for such patients, especially when the prostate is extremely large.

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Background: Metastatic testicular sex cord stromal tumors of the testis (MSCSTs) comprise an extremely uncommon form of genitourinary malignancy. Objective: To perform comprehensive genomic profiling (CGP) to enable the search for potential therapy targets. Design, setting, and participants: Ten patients with testicular Leydig cell tumors (LCTs), six with Sertoli cell tumors (SCTs), and three with undifferentiated sex cord stromal tumors (USCSTs) and a comparison group of 366 patients with ovarian sex cord stromal tumors (SCSTs) underwent hybrid-capture-based CGP to evaluate all classes of genomic alterations (GAs). The tumor mutational burden (TMB) was determined on 1.1 Mbp of sequenced DNA, and microsatellite instability (MSI) was determined on 114 loci. Intervention: CGP on tumor samples. Outcome measurements and statistical analysis: Descriptive analyses and differences between histological subgroups were reported. Results and limitations: In these patients, all of whom had metastatic disease at the time of sequencing, the primary testis tumor was sequenced in six (32%) patients and a metastatic site in 13 (68%) patients. The overall frequencies of GAs were similar in LCTs, SCTs, and USCSTs, ranging from 3.0 to 3.5 GAs/tumor. The most frequent untargetable GAs included CTNNB1 and CDKN2A/B, both ranging from 20% to 33% of cases. Targetable GAs were uncommon in all MSCST subgroups, but several tumors showed potential for cell-cycle inhibitors (CDK4 in LCTs), mTOR inhibitors (RICTOR, NF2, and PTEN in all three tumor types), hedgehog inhibitors (PTCH1 in LCTs), and poly(ADP-ribose) polymerase inhibitors (BAP1 in SCTs). No MSI-high status was identified. The TMB was also low in all MSCST groups, and tumors featuring a TMB of !10 mutations/Mb were not identified. GA findings from ovarian SCSTs largely recapitulated those from MSCSTs. A lack of clinical outcome correlation is a limitation of the present analyses. Conclusions: Rare cases of testicular MSCSTs have GAs linked to potential targeted therapy benefits on CGP. In contrast, the lack of MSI-high status and an overall low TMB indicate a likely lack of benefit for immunotherapies. Patient summary: Genomic profiling can guide clinical research and disclose therapeutic opportunities for patients with rare testicular cancers for which standard therapies are lacking.

PURPOSE To develop an artificial intelligence (AI)–based model for identifying patients with lymph node (LN) metastasis based on digital evaluation of primary tumors and train the model using cystectomy specimens available from The Cancer Genome Atlas (TCGA) Project; patients from our institution were included for validation of the leave-out test cohort. METHODS In all, 307 patients were identified for inclusion in the study (TCGA, n = 294; in-house, n = 13). Deep learning models were trained from image patches at 2.5×, 5×, 10×, and 20× magnifications, and spatially resolved prediction maps were combined with microenvironment (lymphocyte infiltration) features to derive a final patient-level AI score (probability of LN metastasis). Training and validation included 219 patients (training, n = 146; validation, n = 73); 89 patients (TCGA, n = 75; in-house, n = 13) were reserved as an independent testing set. Multivariable logistic regression models for predicting LN status based on clinicopathologic features alone and a combined model with AI score were fit to training and validation sets. RESULTS Several patients were determined to have positive LN metastasis in TCGA (n = 105; 35.7%) and in-house (n = 3; 23.1%) cohorts. A clinicopathologic model that considered using factors such as age, T stage, and lymphovascular invasion demonstrated an area under the curve (AUC) of 0.755 (95% CI, 0.680 to 0.831) in the training and validation cohorts compared with the cross validation of the AI score (likelihood of positive LNs), which achieved an AUC of 0.866 (95% CI, 0.812 to 0.920; P = .021). Performance in the test cohort was similar, with a clinicopathologic model AUC of 0.678 (95% CI, 0.554 to 0.802) and an AI score of 0.784 (95% CI, 0.702 to 0.896; P = .21). In addition, the AI score remained significant after adjusting for clinicopathologic variables ( P = 1.08 × 10−9), and the combined model significantly outperformed clinicopathologic features alone in the test cohort with an AUC of 0.807 (95% CI, 0.702 to 0.912; P = .047). CONCLUSION Patients who are at higher risk of having positive LNs during cystectomy can be identified on primary tumor samples using novel AI-based methodologies applied to digital hematoxylin and eosin–stained slides.

The molecular chaperone Heat shock protein 90 (Hsp90) is essential for the folding, stability, and activity of several drivers of oncogenesis. Hsp90 inhibitors are currently under clinical evaluation for cancer treatment, however their efficacy is limited by lack of biomarkers to optimize patient selection. We have recently identified the tumor suppressor tuberous sclerosis complex 1 (Tsc1) as a new co-chaperone of Hsp90 that affects Hsp90 binding to its inhibitors. Highly variable mutations of TSC1 have been previously identified in bladder cancer and correlate with sensitivity to the Hsp90 inhibitors. Here we showed loss of TSC1 leads to hypoacetylation of Hsp90-K407/K419 and subsequent decreased binding to the Hsp90 inhibitor ganetespib. Pharmacologic inhibition of histone deacetylases (HDACs) restores acetylation of Hsp90 and sensitizes Tsc1-mutant bladder cancer cells to ganetespib, resulting in apoptosis. Our findings suggest that TSC1 status may predict response to Hsp90 inhibitors in patients with bladder cancer, and co-targeting HDACs can sensitize tumors with Tsc1 mutations to Hsp90 inhibitors.

PURPOSE: We investigated the association between race and FT among previous patients with cancer. Studies show that patients with cancer experience financial toxicity (FT) because of their cancer treatment. METHODS: Data on individuals with a cancer history were collected in this cross-sectional study during 2012, 2014, and 2017, from the US Health Information National Trends Survey. This survey is conducted by mail with monetary compensation as an incentive. We specifically assessed responses to two questions: Has cancer hurt you financially? Have you been denied health insurance because of cancer? Multivariable logistic regression analyses were used to assess the associations between these questions and race. RESULTS: Of 10,592 individuals participating, 1,328 men and women (12.5%) with a cancer history were assessed. Compared with Blacks, Whites were found to have a higher rate of insurance (95.4% v 90.0%), were more likely to receive cancer treatment (93.9% v 85%), and had a higher rate of surgical treatment than Blacks (77% v 60%), Hispanics (55%), and others (77%, 60%, 55%, and 74.2%, respectively, P < .001). On multivariable analysis, Blacks were more than five times as likely to be denied insurance (odds ratio, 5.003; 95% CI, 2.451 to 10.213; P < .001) and more than twice as likely to report being hurt financially because of cancer (odds ratio, 2.448; 95% CI, 1.520 to 3.941; P < .001) than Whites. Of all cancer groups analyzed (genitourinary, gynecologic, gastrointestinal, and breast), genitourinary malignancies were the only group in which the rate of reporting being hurt financially varied in a statistically significant manner (Whites 36.7%, Hispanics 62.5%, and Blacks 59.3%, P = .004). CONCLUSION: Our data suggest that race is significantly associated with FT because of cancer. Awareness of racial inequality with regards to FT should be raised among health care workers.