Summary Ribosome occupancy measurements enable protein abundance estimation and infer mechanisms of translation. Recent studies have revealed that sequence read lengths in ribosome profiling data are highly variable and carry critical information. Consequently, data analyses require the computation and storage of multiple metrics for a wide range of ribosome footprint lengths. We developed a software ecosystem including a new efficient binary file format named ‘ribo’. Ribo files store all essential data grouped by ribosome footprint lengths. Users can assemble ribo files using our RiboFlow pipeline that processes raw ribosomal profiling sequencing data. RiboFlow is highly portable and customizable across a large number of computational environments with built-in capabilities for parallelization. We also developed interfaces for writing and reading ribo files in the R (RiboR) and Python (RiboPy) environments. Using RiboR and RiboPy, users can efficiently access ribosome profiling quality control metrics, generate essential plots and carry out analyses. Altogether, these components create a software ecosystem for researchers to study translation through ribosome profiling. Availability and implementation For a quickstart, please see https://ribosomeprofiling.github.io. Source code, installation instructions and links to documentation are available on GitHub: https://github.com/ribosomeprofiling. Supplementary information Supplementary data are available at Bioinformatics online.

Ribosome occupancy measurements enable protein abundance estimation and infer mechanisms of translation. Recent studies have revealed that sequence read lengths in ribosome profiling data are highly variable and carry critical information. Consequently, data analyses require the computation and storage of multiple metrics for a wide range of ribosome footprint lengths. We developed a software ecosystem including a new efficient binary file format named 'ribo'. Ribo files store all essential data grouped by ribosome footprint lengths. Users can assemble ribo files using our RiboFlow pipeline that processes raw ribosomal profiling sequencing data. RiboFlow is highly portable and customizable across a large number of computational environments with built-in capabilities for parallelization. We also developed interfaces for writing and reading ribo files in the R (RiboR) and Python (RiboPy) environments. Using RiboR and RiboPy, users can efficiently access ribosome profiling quality control metrics, generate essential plots, and carry out analyses. Altogether, these components create a complete software ecosystem for researchers to study translation through ribosome profiling. Availability and ImplementationFor a quickstart, please see https://ribosomeprofiling.github.io. Source code, installation instructions and links to documentation are available on GitHub: https://github.com/ribosomeprofiling

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477 Background: First-line therapy for metastatic urothelial carcinoma of the bladder (mUC) consists of platinum-based chemotherapy in most patients and PD1/L1 inhibitors in selected patients. Multiple combination chemo-immunotherapy trials failed to show a clear benefit over chemotherapy alone. We sought to use real-world data to evaluate clinical and sociodemographic factors associated with receipt of first-line chemotherapy, immunotherapy or combination chemo-immunotherapy treatment for metastatic bladder cancer and examined differences in overall survival (OS). Methods: We used the National Cancer Database to identify patients with stage IV UCB diagnosed between 2014 and 2018, who were treated with first-line immunotherapy, chemotherapy, or combination treatment. We performed multivariable logistic regression modeling to determine factors associated with treatment receipt. An extension of inverse probability treatment weighting (IPTW) obtained from multinomial logistic regression was used to balance clinical and sociodemographic differences between treatment groups. Adjusted Kaplan-Meier survival analysis and multivariable Cox proportional hazards regression were used to evaluate the association between treatment and OS. Results: A total of 4,169 patients were identified in the cohort; 3,255 (78.1%) were treated with chemotherapy, 601 (14.4%) with immunotherapy, and 313 (7.5%) with combination treatment. Multivariable analysis identified increasing age (RRR: 1.07, 95% CI, 1.06-1.08), comorbidity burden (Charlson-Deyo 2, RRR: 1.65, 95% CI, 1.21-2.24 and Charlson-Deyo 3, RRR: 2.11; 95% CI, 1.51-2.93), and treatment at an academic facility (RRR: 1.26; 95% CI, 1.03-1.53) as independent predictors of receiving immunotherapy. Treatment at an academic facility (RRR: 1.29, 95% CI, 1.01-1.65) was associated with receipt of combination treatment. After IPTW, we found that combination therapy (hazard ratio [HR]: 0.72; 95% CI, 0.62-0.83), but not immunotherapy alone, was associated with improved survival compared to chemotherapy. These data are limited by inability to determine platinum eligibility, and residual confounding. Conclusions: Patients with older age and more comorbidities were more likely to receive immunotherapy than chemotherapy for first-line treatment of metastatic urothelial carcinoma of the bladder. Modest real-world utilization of chemo-immunotherapy was observed to be higher in academic centers and was associated with improved survival compared to chemotherapy. The study is limited by retrospective design; prospective data are necessary to identify patients who may benefit from combination chemo-immunotherapy.

488 Background: Elective nodal irradiation for patients with muscle-invasive bladder cancer (MIBC) undergoing trimodal therapy (TMT) is controversial. In patients with node-negative (N0) MIBC, the benefit of elective whole-pelvis concurrent chemoradiotherapy (WP-CCRT) compared to bladder-only (BO)-CCRT has not been demonstrated. Currently, the National Comprehensive Cancer Network (NCCN) guidelines do not recommend whether to include pelvic nodes in the radiation field. Using real-world data from the National Cancer Database (NCDB), we sought to compare the overall survival (OS) between BO-CCRT and WP-CCRT for MIBC. Methods: Using the 2019 NCDB Participant User File, we identified cases of MIBC diagnosed between 2017 and 2018. We selected patients with clinical T2-T4N0M0 disease receiving TMT as first-line treatment. TMT was defined as transurethral resection of bladder tumor followed by CCRT: 60–65 Gy of RT delivered to the bladder with concurrent single- or multiple-agent chemotherapy. Patients were stratified into BO-CCRT vs. WP-CCRT. Overall survival (OS) analysis was performed using Kaplan-Meier estimates and multivariable Cox proportional hazards regression analysis. The variables included in the multivariable Cox regression model were age, sex, race, comorbidity burden (as per the Charlson-Deyo comorbidity index), facility type, insurance status, median income quartile, rurality, distance from facility, and clinical T stage. Results: A total of 605 patients receiving TMT for MIBC were identified: 162 (26.8%) BO-CCRT and 443 (73.2%) WP-CCRT. The median follow-up time was 25.6 months (interquartile range [IQR]: 4.8-42.6) and 28.7 months (IQR: 3.0-51.6) for BO-CCRT and WP-CCRT, respectively. The median OS was 32.9 months (95% confidence interval [CI] 30.8 – not reached) and 48.3 months (95% CI 39.6 – not reached) for BO-CCRT and WP-CCRT, respectively. However, multivariable Cox regression analysis failed to find an association between WP-CCRT (hazard ratio [HR] 1.08, 95% CI 0.76-1.54) and improved OS, compared to BO-CCRT. Conclusions: Elective nodal-irradiation (WP-CCRT) in the setting of TMT for MIBC was not associated with a benefit in OS compared to BO-CCRT.