Optimization of Convolutional Autoencoder for Feature Extraction in Lung Cancer CTs

https://openworks.mdanderson.org/sumexp21/1247/thumbnail.jp

T cell receptor engineering targeting FOXM1 for the treatment of lung cancer

https://openworks.mdanderson.org/sumexp23/1069/thumbnail.jp

AI in drug discovery and its clinical relevance

The COVID-19 pandemic has emphasized the need for novel drug discovery process. However, the journey from conceptualizing a drug to its eventual implementation in clinical settings is a long, complex, and expensive process, with many potential points of failure. Over the past decade, a vast growth in medical information has coincided with advances in computational hardware (cloud computing, GPUs, and TPUs) and the rise of deep learning. Medical data generated from large molecular screening profiles, personal health or pathology records, and public health organizations could benefit from analysis by Artificial Intelligence (AI) approaches to speed up and prevent failures in the drug discovery pipeline. We present applications of AI at various stages of drug discovery pipelines, including the inherently computational approaches of de novo design and prediction of a drug's likely properties. Open-source databases and AI-based software tools that facilitate drug design are discussed along with their associated problems of molecule representation, data collection, complexity, labeling, and disparities among labels. How contemporary AI methods, such as graph neural networks, reinforcement learning, and generated models, along with structure-based methods, (i.e., molecular dynamics simulations and molecular docking) can contribute to drug discovery applications and analysis of drug responses is also explored. Finally, recent developments and investments in AI-based start-up companies for biotechnology, drug design and their current progress, hopes and promotions are discussed in this article.  Other InformationPublished in:HeliyonLicense: https://creativecommons.org/licenses/by/4.0/See article on publisher's website: https://doi.org/10.1016/j.heliyon.2023.e17575 </p

IL-6 contributes to the suppression of T and NK cell anti-tumor activity in EGFR-mutant NSCLC

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Phase I, Dose-Escalation, Two-Part Trial of the PARP Inhibitor Talazoparib in Patients with Advanced Germline BRCA1/2 Mutations and Selected Sporadic Cancers

Talazoparib inhibits PARP catalytic activity, trapping PARP1 on damaged DNA and causing cell death in BRCA1/2-mutated cells. We evaluated talazoparib therapy in this two-part, phase I, first-in-human trial. Antitumor activity, MTD, pharmacokinetics, and pharmacodynamics of once-daily talazoparib were determined in an open-label, multicenter, dose-escalation study (NCT01286987). The MTD was 1.0 mg/day, with an elimination half-life of 50 hours. Treatment-related adverse events included fatigue (26/71 patients; 37%) and anemia (25/71 patients; 35%). Grade 3 to 4 adverse events included anemia (17/71 patients; 24%) and thrombocytopenia (13/71 patients; 18%). Sustained PARP inhibition was observed at doses ≥0.60 mg/day. At 1.0 mg/day, confirmed responses were observed in 7 of 14 (50%) and 5 of 12 (42%) patients with BRCA mutation–associated breast and ovarian cancers, respectively, and in patients with pancreatic and small cell lung cancer. Talazoparib demonstrated single-agent antitumor activity and was well tolerated in patients at the recommended dose of 1.0 mg/day

Validating DLL3-targeting CAR T in small cell lung cancer

View full abstracthttps://openworks.mdanderson.org/leading-edge/1022/thumbnail.jp

Phase II Trial of Cediranib in Combination With Cisplatin and Pemetrexed in Chemotherapy-Naïve Patients With Unresectable Malignant Pleural Mesothelioma (SWOG S0905).

PurposeAntiangiogenic agents combined with chemotherapy have efficacy in the treatment of unresectable malignant pleural mesothelioma (MPM). Cediranib (AstraZeneca, Cheshire, United Kingdom), a vascular endothelial growth factor receptor and platelet-derived growth factor receptor inhibitor, demonstrated therapeutic potential in a prior phase I trial. We evaluated a phase II trial for efficacy.Patients and methodsSWOG S0905 (ClinicalTrials.gov identifier: NCT01064648) randomly assigned cediranib or placebo with platinum-pemetrexed for six cycles followed by maintenance cediranib or placebo in unresectable chemotherapy-naïve patients with MPM of any histologic subtype. Primary end point was Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 progression-free survival (PFS). Secondary end points included overall survival, PFS by modified RECIST v1.1, response (modified RECIST and RECIST v1.1), disease control, and safety/toxicity. The trial was designed to detect a difference in RECIST v1.1 PFS at the one-sided 0.1 level using a stratified log-rank test.ResultsNinety-two eligible patients were enrolled (75% epithelioid and 25% biphasic or sarcomatoid). The cediranib arm had more grade 3 and 4 diarrhea, dehydration, hypertension, and weight loss. Cediranib improved PFS by RECIST v1.1 (hazard ratio, 0.71; 80% CI, 0.54 to 0.95; P = .062; 7.2 months v 5.6 months) and increased modified RECIST v1.1 response (50% v 20%; P = .006). By modified RECIST v1.1, cediranib numerically increased PFS (hazard ratio, 0.77; 80% CI, 0.59 to 1.02; P = .12; median, 6.9 months v 5.6 months). No significant difference in overall survival was observed.ConclusionThe addition of cediranib to platinum-pemetrexed improved PFS by RECIST v1.1 and response rate by modified RECIST in patients with unresectable MPM. Whereas adding antiangiogenics to chemotherapy has been a successful strategy for some patients, the cediranib toxicity profile and small incremental survival benefit precludes additional development in MPM