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PATH-SURVEYOR: pathway level survival enquiry for immuno-oncology and drug repurposing.
Obermayer, Alyssa N; Chang, Darwin; Nobles, Gabrielle; Teng, Mingxiang; Tan, Aik-Choon; Wang, Xuefeng; Chen, Y Ann; Eschrich, Steven; Rodriguez, Paulo C; Grass, G Daniel; Meshinchi, Soheil; Tarhini, Ahmad; Chen, Dung-Tsa; Shaw, Timothy I.
Afiliação
  • Obermayer AN; Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA.
  • Chang D; Department of Immunology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA.
  • Nobles G; Morsani College of Medicine, University of South Florida, Tampa, FL, 33612, USA.
  • Teng M; Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA.
  • Tan AC; Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA.
  • Wang X; Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, 84112, USA.
  • Chen YA; Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA.
  • Eschrich S; Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA.
  • Rodriguez PC; Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA.
  • Grass GD; Department of Immunology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA.
  • Meshinchi S; Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA.
  • Tarhini A; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Chen DT; Children's Oncology Group, Monrovia, CA, USA.
  • Shaw TI; Department of Cutaneous Oncology, H Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
BMC Bioinformatics ; 24(1): 266, 2023 Jun 28.
Article em En | MEDLINE | ID: mdl-37380943
ABSTRACT
Pathway-level survival analysis offers the opportunity to examine molecular pathways and immune signatures that influence patient outcomes. However, available survival analysis algorithms are limited in pathway-level function and lack a streamlined analytical process. Here we present a comprehensive pathway-level survival analysis suite, PATH-SURVEYOR, which includes a Shiny user interface with extensive features for systematic exploration of pathways and covariates in a Cox proportional-hazard model. Moreover, our framework offers an integrative strategy for performing Hazard Ratio ranked Gene Set Enrichment Analysis and pathway clustering. As an example, we applied our tool in a combined cohort of melanoma patients treated with checkpoint inhibition (ICI) and identified several immune populations and biomarkers predictive of ICI efficacy. We also analyzed gene expression data of pediatric acute myeloid leukemia (AML) and performed an inverse association of drug targets with the patient's clinical endpoint. Our analysis derived several drug targets in high-risk KMT2A-fusion-positive patients, which were then validated in AML cell lines in the Genomics of Drug Sensitivity database. Altogether, the tool offers a comprehensive suite for pathway-level survival analysis and a user interface for exploring drug targets, molecular features, and immune populations at different resolutions.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Leucemia Mieloide Aguda / Melanoma Tipo de estudo: Prognostic_studies Limite: Child / Humans Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Leucemia Mieloide Aguda / Melanoma Tipo de estudo: Prognostic_studies Limite: Child / Humans Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos