Browsing by Author "Guinney, Justin"
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Item Open Access The Geometry of Cancer(2009) Guinney, JustinCancer is a complex, multifaceted disease that operates through dynamic changes in the genome. Cancer is best understood through the process that generates it -- random mutations operated on by natural selection -- and several global hallmarks that describe its broad mechanisms. While many genes, protein interactions, and pathways have been enumerated as a kind of ``parts'' list for cancer, researchers are attempting to synthesize broader models for inferring and predicting cancer behavior using high-throughput data and integrative analyses.
The focus of this thesis is on the development of two novel methods that are optimized for the analysis of complex cancer phenotypes. The first method incorporates ideas from gradient learning with multitask learning to assess statistical dependencies across multiple related data sets. The second method integrates multiscale analysis on graphs and manifolds developed in applied harmonic analysis with sparse factor models, a mainstay of applied statistics. This method generates multiscale factors that are used for inferring hierarchical associations within complex biological networks. The primary biological focus is the inference of gene and pathway dependencies associated with cancer progression and metastatic disease in prostate cancer. Significant findings include evidence of Skp2 degradation of the cell-cycle regulator p27, and the upstream deregulation of the TGF-beta pathway, driving prostate cancer recurrence.
Item Open Access The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution.(Cell, 2020-04) Rozenblatt-Rosen, Orit; Regev, Aviv; Oberdoerffer, Philipp; Nawy, Tal; Hupalowska, Anna; Rood, Jennifer E; Ashenberg, Orr; Cerami, Ethan; Coffey, Robert J; Demir, Emek; Ding, Li; Esplin, Edward D; Ford, James M; Goecks, Jeremy; Ghosh, Sharmistha; Gray, Joe W; Guinney, Justin; Hanlon, Sean E; Hughes, Shannon K; Hwang, E Shelley; Iacobuzio-Donahue, Christine A; Jané-Valbuena, Judit; Johnson, Bruce E; Lau, Ken S; Lively, Tracy; Mazzilli, Sarah A; Pe'er, Dana; Santagata, Sandro; Shalek, Alex K; Schapiro, Denis; Snyder, Michael P; Sorger, Peter K; Spira, Avrum E; Srivastava, Sudhir; Tan, Kai; West, Robert B; Williams, Elizabeth H; Human Tumor Atlas NetworkCrucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.