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Hybridizing mechanistic modeling and deep learning for personalized survival prediction after immune checkpoint inhibitor immunotherapy.
NPJ Syst Biol Appl
August 2024
Mathematics in Medicine Program, Houston Methodist Research Institute, Houston, TX, USA.
We present a study where predictive mechanistic modeling is combined with deep learning methods to predict individual patient survival probabilities under immune checkpoint inhibitor (ICI) immunotherapy. This hybrid approach enables prediction based on both measures that are calculable from mechanistic models of key mechanisms underlying ICI therapy that may not be directly measurable in the clinic and easily measurable quantities or patient characteristics that are not always readily incorporated into predictive mechanistic models. A deep learning time-to-event predictive model trained on a hybrid mechanistic + clinical data set from 93 patients achieved higher per-patient predictive accuracy based on event-time concordance, Brier score, and negative binomial log-likelihood-based criteria than when trained on only mechanistic model-derived values or only clinical data.
View Article and Find Full Text PDFClinical and Genomic Landscape of RAS Mutations in Gynecologic Cancers.
Clin Cancer Res
July 2024
Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Purpose: We aimed to describe RAS mutations in gynecologic cancers as they relate to clinicopathologic and genomic features, survival, and therapeutic implications.
Experimental Design: Gynecologic cancers with available somatic molecular profiling data at our institution between February 2010 and August 2022 were included and grouped by RAS mutation status. Overall survival was estimated by the Kaplan-Meier method, and multivariable analysis was performed using the Cox proportional hazard model.
CD4+ CAR T-cell exhaustion associated with early relapse of multiple myeloma after BCMA CAR T-cell therapy.
Blood Adv
July 2024
Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA.
Article Synopsis
- - Multiple myeloma often relapses after traditional treatments, but CAR T-cell therapy targeting BCMA shows promise, with over 70% of patients responding initially; however, most will relapse.
- - Patients with longer-lasting responses to CAR T-cell treatment tend to have more persistent CAR T cells and a higher presence of CD8+ T-effector memory cells compared to those with shorter responses, who have more exhausted cytotoxic CD4+ CAR T cells.
- - Nonclassical monocytes in the myeloma environment may contribute to CAR T-cell dysfunction and disease progression, highlighting the complex interactions at play in treatment resistance.
Objective: To study morphological features of Hassall's corpuscles (HC) and their microenvironment in newborns with increased thymus mass.
Material And Methods: The study was carried out on autopsy material of children of the first month of life. Based on the thymic index (TI), 2 groups were identified: with normal (conditional norm) and increased TI value (increased thymus weight).
Mechanisms of telomere maintenance and associated therapeutic vulnerabilities in malignant gliomas.
Neuro Oncol
June 2024
The Preston Robert Tisch Brain Tumor Center, Duke University Medical Center, Durham, North Carolina, USA.
A majority of cancers (~85%) activate the enzyme telomerase to maintain telomere length over multiple rounds of cellular division. Telomerase-negative cancers activate a distinct, telomerase-independent mechanism of telomere maintenance termed alternative lengthening of telomeres (ALT). ALT uses homologous recombination to maintain telomere length and exhibits features of break-induced DNA replication.
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