Background: The acquisition of oncogenic drivers is a critical feature of cancer progression. For some carcinomas, it is clear that certain genetic drivers occur early in neoplasia and others late. Why these drivers are selected and how these changes alter the neoplasia's fitness is less understood.
View Article and Find Full Text PDFIntegration of transcriptomic and proteomic data should reveal multi-layered regulatory processes governing cancer cell behaviors. Traditional correlation-based analyses have demonstrated limited ability to identify the post-transcriptional regulatory (PTR) processes that drive the non-linear relationship between transcript and protein abundances. In this work, we ideate an integrative approach to explore the variety of post-transcriptional mechanisms that dictate relationships between genes and corresponding proteins.
View Article and Find Full Text PDFBenchmark challenges, such as the Critical Assessment of Structure Prediction (CASP) and Dialogue for Reverse Engineering Assessments and Methods (DREAM) have been instrumental in driving the development of bioinformatics methods. Typically, challenges are posted, and then competitors perform a prediction based upon blinded test data. Challengers then submit their answers to a central server where they are scored.
View Article and Find Full Text PDFConvolutional neural networks (CNNs) have gained steady popularity as a tool to perform automatic classification of whole slide histology images. While CNNs have proven to be powerful classifiers in this context, they fail to explain this classification, as the network engineered features used for modeling and classification are ONLY interpretable by the CNNs themselves. This work aims at enhancing a traditional neural network model to perform histology image modeling, patient classification, and interpretation of the distinctive features identified by the network within the histology whole slide images (WSIs).
View Article and Find Full Text PDFIntroduction: Despite apparently complete surgical resection, approximately half of resected early-stage lung cancer patients relapse and die of their disease. Adjuvant chemotherapy reduces this risk by only 5% to 8%. Thus, there is a need for better identifying who benefits from adjuvant therapy, the drivers of relapse, and novel targets in this setting.
View Article and Find Full Text PDFUtilization of single modality data to build predictive models in cancer results in a rather narrow view of most patient profiles. Some clinical facet s relate strongly to histology image features, e.g.
View Article and Find Full Text PDFSummary: We developed annoPeak, a web application to annotate, visualize and compare predicted protein-binding regions derived from ChIP-seq/ChIP-exo-seq experiments using human and mouse cells. Users can upload peak regions from multiple experiments onto the annoPeak server to annotate them with biological context, identify associated target genes and categorize binding sites with respect to gene structure. Users can also compare multiple binding profiles intuitively with the help of visualization tools and tables provided by annoPeak.
View Article and Find Full Text PDFDisruption of the retinoblastoma (RB) tumor suppressor pathway, either through genetic mutation of upstream regulatory components or mutation of RB1 itself, is believed to be a required event in cancer. However, genetic alterations in the RB-regulated E2F family of transcription factors are infrequent, casting doubt on a direct role for E2Fs in driving cancer. In this work, a mutation analysis of human cancer revealed subtle but impactful copy number gains in E2F1 and E2F3 in hepatocellular carcinoma (HCC).
View Article and Find Full Text PDFE2F-mediated transcriptional repression of cell cycle-dependent gene expression is critical for the control of cellular proliferation, survival, and development. E2F signaling also interacts with transcriptional programs that are downstream of genetic predictors for cancer development, including hepatocellular carcinoma (HCC). Here, we evaluated the function of the atypical repressor genes E2f7 and E2f8 in adult liver physiology.
View Article and Find Full Text PDFE2F3 and MYC are transcription factors that control cellular proliferation. To study their mechanism of action in the context of a regenerating tissue, we isolated both proliferating (crypts) and non-dividing (villi) cells from wild-type and Rb depleted small intestines of mice and performed ChIP-exo-seq (chromatin immunoprecipitation combined with lambda exonuclease digestion followed by high-throughput sequencing). The genome-wide chromatin occupancy of E2F3 and MYC was determined by mapping sequence reads to the genome and predicting preferred binding sites (peaks).
View Article and Find Full Text PDFInactivation of phosphatase and tensin homology deleted on chromosome 10 (PTEN) is linked to increased PI3K-AKT signaling, enhanced organismal growth, and cancer development. Here we generated and analyzed Pten knock-in mice harboring a C2 domain missense mutation at phenylalanine 341 (Pten(FV)), found in human cancer. Despite having reduced levels of PTEN protein, homozygous Pten(FV/FV) embryos have intact AKT signaling, develop normally, and are carried to term.
View Article and Find Full Text PDFRobust mechanisms to control cell proliferation have evolved to maintain the integrity of organ architecture. Here, we investigated how two critical proliferative pathways, Myc and E2f, are integrated to control cell cycles in normal and Rb-deficient cells using a murine intestinal model. We show that Myc and E2f1-3 have little impact on normal G1-S transitions.
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