6-MONTH INTERN – RESEARCH AND EARLY DEVELOPMENT - BIOINFORMATICS AND COMPUTATIONAL BIOLOGY (GRADUATE LEVEL)
Organisation Name: GENENTECH
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Department Overview: The mission of the Bioinformatics & Computational Biology group is to provide the information systems including the methods, software, databases, infrastructure, and training required for Research to access and analyze DNA and protein sequence information and related biological data. To utilize these information systems to analyze biological information and to identify genes of therapeutic interest. Here are some examples of the projects we have for interns this summer… Intern Qualifications: Background in bioinformatics, biostatistics, computational biology, genetics, genomics or related field is recommended Familiarity with Linux working environment and high-performance computing is required Proficiency in R is greatly preferred, skills with other high-level programming languages and experience in standard bioinformatics toolkits and programs highly desired Good understanding of concepts in cancer biology/genomics and/or familiarity with high-throughput sequencing technologies Lab skills not needed, but is a plus Project #1: Wnt signaling is a critical signaling pathway that is required for the development and maintenance of numerous adult tissue. This is well illustrated in the intestinal tract, for instance, where Wnt activity is restricted to population of stem cells that fuel tissue maintenance and regeneration after damage. Coincidently, Wnt signaling is often aberrantly deployed by cancers derived from the intestine. As an example, virtually all human colorectal cancers are initiated by hyperactivation of Wnt signaling, through loss of function of the tumor suppressor APC. Recent evidence suggests that the Wnt activated state found in normal stem cells differs from the one triggered by an APC mutation in colon cancer stem cells. These differences could form the basis of novel cancer dependencies. This project aims at cataloguing and comparing the Wnt driven cell states between normal and cancer intestinal stem cells. To this end, RNA seq and ATAC seq will be derived from primary intestinal organoids that are Wnt hyperactivated through various means, including APC truncation to recapitulate cancer initiation or Wnt ligand stimulation to reflect normal stem cell physiology. Intern Responsibilities: Integrate information from Bulk RNA seq, scRNA-seq and ATAC seq experiments in combination with previously generated in-house bulk RNA-seq as well as publicly. available resources to gain insights into Wnt hyperactivated states. Identify similarities and differences of Wnt activated states between normal and cancer intestinal stem cells. Generate hypothesis on pursuit of potential actionable targets derived from bioinformatic analysis. Project #2: Our lab aims to understand the mechanisms of TDB-induced lymphocyte redistribution using spatial transcriptomics. T cell-dependent bispecific (TDB) antibodies promote T cell-mediated killing of cancer cells by binding the T cell receptor (TCR) CD3 subunit on T cells and a tumor antigen expressed on cancer cells. Despite their clinical promise, transient lymphopenia (margination) is a pronounced pharmacological effect of such CD3-targeting antibodies. In order to improve patient outcomes, it is of crucial importance to pinpoint the factor(s) that fully account for the observed in vivo effects. Therefore, our aim is to determine the kinetics and molecular drivers of T cell trafficking into normal tissue versus tumors. Intern Responsibilities: Integrate information from scRNA-seq and spatial transcriptomics experiments in combination with previously generated in-house bulk RNA-seq as well as publicly available resources to gain insights into the process of T cell margination. Benchmark and apply deconvolution methods to characterize cells captured through spatial transcriptomics assays with the goal to better understand T cell infiltration and trafficking. Identify similarities and differences of T cells that have trafficked to normal tissues versus tumors.
