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Integrating machine learning and single-cell trajectories to analyze T-cell exhaustion to predict prognosis and immunotherapy in colon cancer patients
ConclusionIn this study, we systematically explored the T-cell exhaustion trajectory in COAD and developed a TES model to assess prognosis and provide guidelines for the treatment decision. This discovery gave rise to a fresh concept for novel therapeutic procedures for the clinical treatment of COAD.
Source: Frontiers in Immunology - May 3, 2023 Category: Allergy & Immunology Source Type: research

Cancers, Vol. 13, Pages 3903: Identification of CNGB1 as a Predictor of Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer
Rakesh Heer Cisplatin-based neoadjuvant chemotherapy (NAC) is recommended prior to radical cystectomy for muscle-invasive bladder cancer (MIBC) patients. Despite a 5–10% survival benefit, some patients do not respond and experience substantial toxicity and delay in surgery. To date, there are no clinically approved biomarkers predictive of response to NAC and their identification is urgently required for more precise delivery of care. To address this issue, a multi-methods analysis approach of machine learning and differential gene expression analysis was undertaken on a cohort of 30 MIBC cases highly selected for an...
Source: Cancers - August 2, 2021 Category: Cancer & Oncology Authors: Anastasia C. Hepburn Nicola Lazzarini Rajan Veeratterapillay Laura Wilson Jaume Bacardit Rakesh Heer Tags: Article Source Type: research

Abstract 5323: Integrated computational cell-line modeling of drug sensitivity and high-throughput siRNA screening reveals novel molecular biomarkers for conventional chemotherapy
Conclusions: We present an integrated approach that combines a novel Bayesian multi-task learning model with high-throughput siRNA screens. Our approach aims to uncover sets of important aberrations and allows for the subtyping of drugs based on similarities in targets and mechanisms of action. We integrate our results with high-throughput RNAi experiments to identify synthetic lethal events in specific therapeutic context. Citation Format: Olga H. Nikolova, Mehmet Gönen, Rodrigo Dienstmann, In Sock Jang, Russell Moser, Silvia Cermelli, Chang Xu, Ryan M. Mitchell, Eduardo Mendez, Carla Grandori, Christopher Kemp, Stephen ...
Source: Cancer Research - September 30, 2014 Category: Cancer & Oncology Authors: Nikolova, O. H., Gonen, M., Dienstmann, R., Jang, I. S., Moser, R., Cermelli, S., Xu, C., Mitchell, R. M., Mendez, E., Grandori, C., Kemp, C., Friend, S., Guinney, J., Margolin, A. Tags: Molecular and Cellular Biology Source Type: research