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Andre Schultz

Researcher at Stanford University

Publications -  19
Citations -  1563

Andre Schultz is an academic researcher from Stanford University. The author has contributed to research in topics: Gene & Cancer. The author has an hindex of 9, co-authored 17 publications receiving 867 citations. Previous affiliations of Andre Schultz include Rice University & University of Texas MD Anderson Cancer Center.

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A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers

TL;DR: Using 16 key molecular features, five prognostic subtypes were identified and a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories was developed, raising potential implications for immunotherapy.
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Integrated Analysis of TP53 Gene and Pathway Alterations in The Cancer Genome Atlas.

TL;DR: Tumors with TP53 mutations differ from their non-mutated counterparts in RNA, miRNA, and protein expression patterns, with mutant TP53 tumors displaying enhanced expression of cell cycle progression genes and proteins.
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Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

Joshua D. Campbell, +769 more
- 03 Apr 2018 - 
TL;DR: This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas from five sites associated with smoking and/or human papillomavirus.
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A Pan-Cancer Analysis Reveals High-Frequency Genetic Alterations in Mediators of Signaling by the TGF-β Superfamily

Anil Korkut, +760 more
- 24 Oct 2018 - 
TL;DR: An integromic analysis of gene alterations that modulate transforming growth factor β-Smad-mediated signaling in 9,125 tumor samples across 33 cancer types in The Cancer Genome Atlas provides a broad molecular perspective relevant for future functional and therapeutic studies of the diverse cancer pathways mediated by the TGF-β superfamily.
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Reconstruction of Tissue-Specific Metabolic Networks Using CORDA.

TL;DR: A novel algorithm called Cost Optimization Reaction Dependency Assessment (CORDA) is introduced to build genome scale models in a tissue-specific manner and identifies changes in reactions and pathways that are differentially included and present different capacity profiles in cancer compared to healthy tissues.