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David M. Hwang

Researcher at Sunnybrook Health Sciences Centre

Publications -  184
Citations -  9146

David M. Hwang is an academic researcher from Sunnybrook Health Sciences Centre. The author has contributed to research in topics: Lung transplantation & Lung. The author has an hindex of 48, co-authored 179 publications receiving 7241 citations. Previous affiliations of David M. Hwang include Toronto General Hospital & University Health Network.

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A Genome-Based Resource for Molecular Cardiovascular Medicine Toward a Compendium of Cardiovascular Genes

TL;DR: These data represent the most extensive compilation of cardiovascular gene expression information to date and represent a first-generation genome-based resource for molecular cardiovascular medicine.
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A986S polymorphism of the calcium-sensing receptor and circulating calcium concentrations.

TL;DR: The CASR A986S polymorphism is a likely candidate locus for genetic predisposition to various bone and mineral disorders in which extracellular calcium concentrations have a prominent part.
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A Grading System for Invasive Pulmonary Adenocarcinoma: A Proposal From the International Association for the Study of Lung Cancer Pathology Committee.

TL;DR: A grading system based on the predominant and high-grade patterns is practical and prognostic for invasive pulmonary adenocarcinoma.
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Biomarker testing and time to treatment decision in patients with advanced nonsmall-cell lung cancer

TL;DR: Awaiting biomarker testing results can delay treatment decisions and treatment initiation for patients with advanced NSCLC, and this may be avoided by incorporating reflex biomarkerTesting into diagnostic algorithms forNSCLC at the level of the pathologist, and further education of specialists involved in obtaining diagnostic cancer specimens to ensure they are sufficient for molecular testing.
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The Promises and Challenges of Tumor Mutation Burden as an Immunotherapy Biomarker: A Perspective from the International Association for the Study of Lung Cancer Pathology Committee

TL;DR: Effective prediction of response to ICI therapy will likely require integration of TMB with a host of other potential biomarkers, including tumor genomic driver alterations, tumor-immune milieu, and other features of the host immune system.