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      YAP-Driven Malignant Reprogramming of Epithelial Stem Cells at Single Cell Resolution

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          Abstract

          Tumor initiation represents the first step in tumorigenesis during which normal progenitor cells undergo cell fate transition to cancer. Capturing this process as it occurs in vivo, however, remains elusive. Here we employ cell tracing approaches with spatiotemporally controlled oncogene activation and tumor suppressor inhibition to unveil the processes underlying oral epithelial progenitor cell reprogramming into cancer stem cells (CSCs) at single cell resolution. This revealed the rapid emergence of a distinct stem-like cell state, defined by aberrant proliferative, hypoxic, squamous differentiation, and partial epithelial to mesenchymal (pEMT) invasive gene programs. Interestingly, CSCs harbor limited cell autonomous invasive capacity, but instead recruit myeloid cells to remodel the basement membrane and ultimately initiate tumor invasion. CSC transcriptional programs are conserved in human carcinomas and associated with poor patient survival. These findings illuminate the process of cancer initiation at single cell resolution, thus identifying candidate targets for early cancer detection and prevention.

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          Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

          Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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            WGCNA: an R package for weighted correlation network analysis

            Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at .
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              Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

              The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: ResourcesRole: Writing, Original DraftRole: Writing, Review & EditingRole: SupervisionRole: Project administrationRole: Funding acquisition
                Role: ConceptualizationRole: MethodologyRole: SoftwareRole: ValidationRole: Formal analysisRole: InvestigationRole: Data curationRole: Writing, Original DraftRole: Writing, Review & EditingRole: VisualizationRole: Project administrationRole: Funding acquisition
                Role: SoftwareRole: ValidationRole: Formal analysisRole: InvestigationRole: Data curationRole: Writing, Original DraftRole: Writing, Review & Editing
                Role: SoftwareRole: ValidationRole: Formal analysisRole: InvestigationRole: Data curation
                Role: SoftwareRole: Formal analysisRole: InvestigationRole: Data curationRole: Writing, Review & Editing
                Role: Investigation
                Role: Investigation
                Role: InvestigationRole: Writing, Review & Editing
                Role: Investigation
                Role: Formal analysisRole: Resources
                Role: SoftwareRole: Investigation
                Role: Investigation
                Role: Investigation
                Role: Investigation
                Role: ResourcesRole: Supervision
                Role: ResourcesRole: Writing, Review & EditingRole: Supervision
                Role: ResourcesRole: Writing, Review & EditingRole: Supervision
                Role: ResourcesRole: Writing, Review & EditingRole: Supervision
                Journal
                Res Sq
                ResearchSquare
                Research Square
                American Journal Experts
                27 October 2023
                : rs.3.rs-3426301
                Affiliations
                University of California, San Diego
                University of California San Diego Health Department of Otolaryngology-Head and Neck Surgery and Moores Cancer Center
                La Jolla Institute of Immunology
                University of California San Diego Health Moores Cancer Center
                University of California San Diego Health Moores Cancer Center
                University of California San Diego Health Moores Cancer Center
                University of California Irvine Department of Chemical and Biomolecular Engineering
                La Jolla Institute of Immunology
                University of California San Diego Health Moores Cancer Center
                University of California San Diego Health Moores Cancer Center
                Craniofacial Biology and Department of Orofacial Sciences, University of California, San Francisco
                University of California San Francisco (UCSF)
                University of California San Diego Health Moores Cancer Center
                University of California San Diego Health Moores Cancer Center
                La Jolla Institute of Immunology
                IDEXX Laboratories KK
                University of California San Diego
                University of California Irvine Department of Chemical and Biomolecular Engineering
                Cedars-Sinai Medical Center, Los Angeles
                University of California, San Diego
                Author notes
                Author information
                http://orcid.org/0000-0002-5150-4482
                Article
                10.21203/rs.3.rs-3426301
                10.21203/rs.3.rs-3426301/v1
                10635308
                37961717
                c917ada4-2edb-463d-a588-e60e01ed528f

                This work is licensed under a Creative Commons Attribution 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.

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                tumor initiation,tumor initiating cell,cancer stem cell,squamous cell carcinoma,oral cancer,hnscc,hippo pathway,yap,hpv

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