Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

Additional file 1: of Network analysis of an in vitro model of androgen-resistance in prostate cancer

Table S1.  Top 15 pathways for the human differentially expressed genes. Table S2. Top 15 pathways for the cell line deferentially expressed genes. Figure S1. Differencially expressed cell line genes overlaid on KEGG hsa04010 MAPK signaling pathway. Figure S2. Differentially expressed cell line genes overlaid on KEGG hsa04151 PI3K-Akt signaling pathway-Homo sapiens (human). Figure S3. Differentially expressed human tumour genes overlaid on KEGG hsa04010 MAPK signaling pathway. Figure S4. Differentially expressed human tumour genes overlaid on KEGG hsa04151 PI3K-Akt signaling pathway-Homo sapiens (human). (PDF 460 kb

Dynamics of the T4 Bacteriophage DNA Packasome Motor: ENDONUCLEASE VII RESOLVASE RELEASE OF ARRESTED Y-DNA SUBSTRATES*

Conserved bacteriophage ATP-based DNA translocation motors consist of a multimeric packaging terminase docked onto a unique procapsid vertex containing a portal ring. DNA is translocated into the empty procapsid through the portal ring channel to high density. In vivo the T4 phage packaging motor deals with Y- or X-structures in the replicative concatemer substrate by employing a portal-bound Holliday junction resolvase that trims and releases these DNA roadblocks to packaging. Here using dye-labeled packaging anchored 3.7-kb Y-DNAs or linear DNAs, we demonstrate FRET between the dye-labeled substrates and GFP portal-containing procapsids and between GFP portal and single dye-labeled terminases. We show using FRET-fluorescence correlation spectroscopy that purified T4 gp49 endonuclease VII resolvase can release DNA compression in vitro in prohead portal packaging motor anchored and arrested Y-DNA substrates. In addition, using active terminases labeled at the N- and C-terminal ends with a single dye molecule, we show by FRET distance of the N-terminal GFP-labeled portal protein containing prohead at 6.9 nm from the N terminus and at 5.7 nm from the C terminus of the terminase. Packaging with a C-terminal fluorescent terminase on a GFP portal prohead, FRET shows a reduction in distance to the GFP portal of 0.6 nm in the arrested Y-DNA as compared with linear DNA; the reduction is reversed by resolvase treatment. Conformational changes in both the motor proteins and the DNA substrate itself that are associated with the power stroke of the motor are consistent with a proposed linear motor employing a terminal-to-portal DNA grip-and-release mechanism

Abstracts of International Conference on Innovations in Business Management

This book contains abstracts of the various research ideas of the academic community and practitioners of management presented at the International Conference on Innovations in Business Management (ICIBM 2020). The researchers have contributed toward various themes of the conference such as sustainable economy, supply chain, women-empowerment, export-import, microfinance, government policies, etc. We strongly believe that it will open up further scope for in-depth research in various disciplines of business management. Best wishes to the participants to have detailed discussions on the above-said wide range of areas. Conference Title: International Conference on Innovations in Business ManagementConference Acronym: ICIBM 2020Conference Date: 16-17 January 2020Conference Location: ICFAI University, Dehradun, IndiaConference Organizers: ICFAI Business School, ICFAI University, Dehradun, India & University of Derby, United Kingdo