Events

Clinical Whole Genome Sequencing & Research Whole Exome Sequencing/RNA Sequencing Results 75-year-old male with metastatic high-grade urothelial carcinoma 59-year-old patient with clear cell adenocarcinoma of the urethra Cases referred by Dr. Cora Sternberg and presented by Dr. Daniela Guevara

AI Working Group Interactive club, open discussions, and presentations related to Artificial Intelligence Research. “Modeling Highly Multiplexed Imaging Data with Self Supervised Deep Learning – Challenges and Approaches” Presented by: Kyle Finos, Medical Student

Anne O’Donnell Luria, M.D., Ph.D. Co-Director of the Center for Mendelian Genomics (CMG) at the Broad Institute of MIT and Harvard Attending Physician in Genetics and Metabolism, Boston Children’s Hospital Assistant Professor, Harvard Medical School Presenting "Navigating the Unknown: Novel Approaches to Rare Disease Diagnosis.”

Englander Institute for Precision Medicine - Journal Club Discussion Article: Nicheformer: a foundation model for single-cell and spatial omics Presented By: Sean Houghton Senior Bioinformatics Analyst Department of Physiology & Biophysics

We leverage patient-derived 3D organoid models from different cancers, which reproduce the oncogenic programs of human tumors, to reveal cellular and molecular mechanisms underlying tumor-intrinsic sensitivity to IFNg. The talk will address: How intratumoral genetic heterogeneity influences sensitivity to IFNg signaling.How intratumoral genetic heterogeneity influences the expression of IFNg-induced and therapeutically relevant immune checkpoints and soluble mediators. Such insights are key to the development of combination treatments targeting immune checkpoint ligands and tumor-specific vulnerabilities.Given the critical role of IFNg in antitumor immunity, we address how tissue-specific and tumor-intrinsic differences must be considered to identify targetable immunophenotypes and underlying molecular cascades that influence IFNg responsivity and ICB efficacy.About Dr. Anna S. Tocheva: My laboratory integrates cellular and molecular immunological assays with high-throughput proteomic and genomic approaches to study the signaling pathways triggered by immune checkpoints in human T cells. In parallel, we develop scalable approaches that incorporate cancer patient-derived organoids with reconstituted immune cells allowing us to translate these fundamental immunobiology discoveries into functional pre-clinical immunoassays to identify mono- and combination immunotherapies that augment anti-tumor T cell responses. — Anna S. Tocheva, Ph.D. Assistant Professor Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai

Englander Institute for Precision Medicine - Journal Club Discussion Article: Towards a general-purpose foundation model for computational pathology Presented By: Mohamed Omar, M.D. Assistant Professor of Research Department of Pathology and Laboratory Medicine Weill Cornell Medicine

Englander Institute for Precision Medicine Journal Club with snacks! FOXO1 enhances CAR T cell stemness, metabolic fitness and efficacy Presented by Alyssa Duren-Lubanski, Ph.D. Candidate Submit articles for EIPM Journal Club here.

Gürkan Bebek, Ph.D., M.S. Assistant Professor Case Western Reserve University Center for Proteomics and Bioinformatics Graduate Program Director — Systems Biology & Bioinformatics MS Program Department of Nutrition Computer & Data Sciences Department Website: Gurkan Bebek Abstract: "Unveiling the Complexity of Cancer: From Network Analysis to Personalized Medicine" Network analysis is revolutionizing our understanding of cancer, offering insights into its complex mechanisms and paving the way for personalized medicine. We will explore this multifaceted approach, beginning with its ability to decipher the functional consequences of specific mutations. Through the analysis of interactions within biological networks, we can discover how mutations, such as those in the APC gene in colorectal cancer, trigger cascading effects and interfere with cellular pathways. This understanding of dysregulated pathways forms the foundation for patient stratification. By analyzing network alterations in cancer patients, we can group individuals based on their unique pathway disruptions. Features discovered by frequent subgraph mining offer insights into the underlying disease mechanisms. This approach holds potential for both prognosis prediction and the development of tailored treatment strategies. As an example, we will explain discovering distinct patient groups in low-grade glioma using our unsupervised bottom-up approach. Specific subnetwork alterations both validate our approach and reveal previously unknown subgroups with distinct clinical needs. This exploration of network analysis in cancer research highlights its transformative power in unraveling the complexities of this disease and paving the way for more targeted therapies.

Gürkan Bebek, Ph.D., M.S. Assistant Professor Case Western Reserve University Center for Proteomics and Bioinformatics Graduate Program Director — Systems Biology & Bioinformatics MS Program Department of Nutrition Computer & Data Sciences Department Website: Gurkan Bebek