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Melanoma: HELP
Articles by Reena Shakya
Based on 3 articles published since 2010
(Why 3 articles?)
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Between 2010 and 2020, Reena Shakya wrote the following 3 articles about Melanoma.
 
+ Citations + Abstracts
1 Article Synergy from gene expression and network mining (SynGeNet) method predicts synergistic drug combinations for diverse melanoma genomic subtypes. 2019

Regan-Fendt, Kelly E / Xu, Jielin / DiVincenzo, Mallory / Duggan, Megan C / Shakya, Reena / Na, Ryejung / Carson, William E / Payne, Philip R O / Li, Fuhai. ·Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA. · Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. · Target Validation Shared Resource, The Ohio State University, Columbus, OH, USA. · Institute for Informatics, Washington University in St. Louis, St. Louis, MO, USA. · Institute for Informatics, Washington University in St. Louis, St. Louis, MO, USA. Fuhai.Li@wustl.edu. · Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA. Fuhai.Li@wustl.edu. ·NPJ Syst Biol Appl · Pubmed #30820351.

ABSTRACT: Systems biology perspectives are crucial for understanding the pathophysiology of complex diseases, and therefore hold great promise for the discovery of novel treatment strategies. Drug combinations have been shown to improve durability and reduce resistance to available first-line therapies in a variety of cancers; however, traditional drug discovery approaches are prohibitively cost and labor-intensive to evaluate large-scale matrices of potential drug combinations. Computational methods are needed to efficiently model complex interactions of drug target pathways and identify mechanisms underlying drug combination synergy. In this study, we employ a computational approach, SynGeNet (Synergy from Gene expression and Network mining), which integrates transcriptomics-based connectivity mapping and network centrality analysis to analyze disease networks and predict drug combinations. As an exemplar of a disease in which combination therapies demonstrate efficacy in genomic-specific contexts, we investigate malignant melanoma. We employed SynGeNet to generate drug combination predictions for each of the four major genomic subtypes of melanoma (BRAF, NRAS, NF1, and triple wild type) using publicly available gene expression and mutation data. We validated synergistic drug combinations predicted by our method across all genomic subtypes using results from a high-throughput drug screening study across. Finally, we prospectively validated the drug combination for

2 Article The Exportin-1 Inhibitor Selinexor Exerts Superior Antitumor Activity when Combined with T-Cell Checkpoint Inhibitors. 2017

Farren, Matthew R / Hennessey, Rebecca C / Shakya, Reena / Elnaggar, Omar / Young, Gregory / Kendra, Kari / Landesman, Yosef / Elloul, Sivan / Crochiere, Marsha / Klebanov, Boris / Kashyap, Trinayan / Burd, Christin E / Lesinski, Gregory B. ·Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia. · Department of Molecular Genetics, The Ohio State University, Columbus, Ohio. · Department of Molecular Virology, Immunology, and Medical Genetics, The Ohio State University, Columbus, Ohio. · Target Validation Shared Resource, The Ohio State University, Columbus, Ohio. · Division of Internal Medicine, The Ohio State University, Columbus, Ohio. · Center for Biostatistics, The Ohio State University, Columbus, Ohio. · Karyopharm Therapeutics, Newton, Massachusetts. · Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia. gregory.b.lesinski@emory.edu. ·Mol Cancer Ther · Pubmed #28148715.

ABSTRACT: Selinexor, a selective inhibitor of nuclear export (SINE) compound targeting exportin-1, has previously been shown to inhibit melanoma cell growth

3 Article Stromal Senescence By Prolonged CDK4/6 Inhibition Potentiates Tumor Growth. 2017

Guan, Xiangnan / LaPak, Kyle M / Hennessey, Rebecca C / Yu, Christina Y / Shakya, Reena / Zhang, Jianying / Burd, Christin E. ·Department of Molecular Genetics, The Ohio State University, Columbus, Ohio. · Department of Cancer Biology and Genetics, The Ohio State University, Columbus, Ohio. · Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio. · The Ohio State University Comprehensive Cancer Center - Arthur G. James Cancer Hospital and Richard J. Solove Research Institute, Columbus, Ohio. · Department of Molecular Genetics, The Ohio State University, Columbus, Ohio. burd.25@osu.edu. ·Mol Cancer Res · Pubmed #28039358.

ABSTRACT: Senescent cells within the tumor microenvironment (TME) adopt a proinflammatory, senescence-associated secretory phenotype (SASP) that promotes cancer initiation, progression, and therapeutic resistance. Here, exposure to palbociclib (PD-0332991), a CDK4/6 inhibitor, induces senescence and a robust SASP in normal fibroblasts. Senescence caused by prolonged CDK4/6 inhibition is DNA damage-independent and associated with Mdm2 downregulation, whereas the SASP elicited by these cells is largely reliant upon NF-κB activation. Based upon these observations, it was hypothesized that the exposure of nontransformed stromal cells to PD-0332991 would promote tumor growth. Ongoing clinical trials of CDK4/6 inhibitors in melanoma prompted a validation of this hypothesis using a suite of genetically defined melanoma cells (i.e.,