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Justin Guinney

Researcher at Sage Bionetworks

Publications -  129
Citations -  21754

Justin Guinney is an academic researcher from Sage Bionetworks. The author has contributed to research in topics: Cancer & Medicine. The author has an hindex of 32, co-authored 97 publications receiving 12819 citations. Previous affiliations of Justin Guinney include Duke University & University of Washington.

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Real-world outcome analysis of patients with advanced gastric and gastroesophageal adenocarcinoma with HER2-low expression treated with first-line therapy.

TL;DR: In this paper , a real-world outcome analysis of a distinct genomically defined underrepresented population was performed using Kaplan-Meier methods, and the authors found that advanced gastric and GEJ patients with HER2-low expression identified by IHC and RNA expression have a poor prognosis with shortest survival.
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A Machine-Learning Tool Concurrently Models Single Omics and Phenome Data for Functional Subtyping and Personalized Cancer Medicine

TL;DR: A new machine learning tool to identify unsupervised clinically-relevant (functional) subtypes and biomarkers by simultaneously integrating clinical phenotypes and single omics data, mainly, transcriptome is reported.

Association of Genetic Ancestry with Molecular Tumor Profiles in Colorectal Cancer

TL;DR: In this paper , associations of colorectal cancer tumor molecular profiles with genetic ancestry were examined, and the association of genetic ancestry proportions and genetic ancestry-imputed race and ethnicity categories with somatic mutations in relevant CRC genes and in expression profiles, including consensus molecular subtypes (CMS).
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Genetic ancestry associations with somatic mutations in a real-world cohort of over 3,000 patients with prostate cancer.

TL;DR: In this article , the authors used 654 ancestry-informative markers to estimate continental ancestry likelihoods for five regions: Africa (AFR), Americas (AMR), East Asia (EAS), Europe (EUR), and South Asia (SAS).
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Dual tissue and plasma testing to improve detection of actionable variants in patients with solid cancers.

TL;DR: In the largest study of its kind, it is shown that dual tumor tissue and ctDNA testing—with samples collected either concurrently or longitudinally—identified more patients with actionable alterations than single modality testing alone and therefore should be considered as part of routine NGS testing.