Project description:Lung cancer remains the leading cause of cancer-related mortality worldwide, with limited treatment options for advanced stages. This proteogenomics study aims to integrate multi-omics approaches, including proteomics, genomics, and transcriptomics, to elucidate the molecular mechanisms underlying lung cancer progression and treatment resistance. By leveraging cutting-edge technologies, this study seeks to identify novel biomarkers and therapeutic targets, enabling personalized medicine strategies to improve patient outcomes. The integration of proteogenomic data will provide a comprehensive understanding of tumor biology, revealing critical pathways and interactions that drive tumorigenesis and immune evasion.
Project description:Therapeutic approaches to treat melanoma include small molecule drugs that target activating protein mutations in pro-growth signaling pathways like the MAPK pathway. While beneficial to the approximately 50% of patients with activating BRAFV600 mutation, mono- and combination therapy with MAPK inhibitors is ultimately associated with acquired resistance. To better characterize the mechanisms of MAPK inhibitor resistance in melanoma, we utilize patient-derived xenografts and apply proteogenomic approaches leveraging genomic, transcriptomic, and proteomic technologies that permit the identification of resistance-specific alterations and therapeutic vulnerabilities. A specific challenge for proteogenomic applications comes at the level of data curation to enable multi-omics data integration. Here, we present a proteogenomic approach that uses custom curated databases to identify unique resistance-specific alternations in melanoma PDX models of acquired MAPK inhibitor resistance. We demonstrate this approach with a NRASQ61L melanoma PDX model from which resistant tumors were developed following treatment with a MEK inhibitor. Our multi-omics strategy addresses current challenges in bioinformatics by leveraging development of custom curated proteogenomics databases derived from individual resistant melanoma that evolves following MEK inhibitor treatment and is scalable to comprehensively characterize acquired MAPK inhibitor resistance across patient-specific models and genomic subtypes of melanoma.
Project description:The diazotroph Trichodesmium is an important contributor to marine dinitrogen (N2) fixation, supplying so-called new N to phytoplankton in typically N-limited ocean regions. Identifying how iron (Fe) and phosphorus (P) influence Trichodesmium activity and biogeography is an ongoing area of study, where predicting patterns of resource stress is complicated in part by the uncertain bioavailability of organically complexed Fe and P. Here, a comparison of 26 metaproteomes from picked Trichodesmium colonies identified significantly different patterns between three ocean regions: the western tropical South Pacific, the western North Atlantic, and the North Pacific Subtropical Gyre. Trichodesmium metaproteomes across these regions significantly differed in KEGG submodule signals, and vector fitting showed that dissolved Fe, phosphate, and temperature significantly correlated with regional proteome patterns. Populations in the western tropical South Pacific appeared to modulate their proteomes in response to both Fe and P stress, including a comparatively low relative abundance of the N2 fixation marker protein, NifH. Significant increases in the relative abundance of both Fe and P stress marker proteins previously validated in culture studies suggested that Trichodesmium populations in the western North Atlantic and North Pacific were P-stressed and Fe-stressed, respectively. These patterns recapitulate established regional serial and co-limitation patterns of resource stress on phytoplankton communities. Evaluating community stress patterns may therefore predict resource controls on diazotroph biogeography. These data highlight how Trichodesmium modulates its metabolism in the field and provide an opportunity to more accurately constrain controls on Trichodesmium biogeography and N2 fixation.
Project description:Therapeutic approaches to treat melanoma include small molecule drugs that target activating protein mutations in pro-growth signaling pathways like the MAPK pathway. While beneficial to the approximately 50% of patients with activating BRAFV600 mutation, mono- and combination therapy with MAPK inhibitors is ultimately associated with acquired resistance. To better characterize the mechanisms of MAPK inhibitor resistance in melanoma, we utilize patient-derived xenografts and apply proteogenomic approaches leveraging genomic, transcriptomic, and proteomic technologies that permit the identification of resistance-specific alterations and therapeutic vulnerabilities. A specific challenge for proteogenomic applications comes at the level of data curation to enable multi-omics data integration. Here, we present a proteogenomic approach that uses custom curated databases to identify unique resistance-specific alternations in melanoma PDX models of acquired MAPK inhibitor resistance. We demonstrate this approach with a NRASQ61L melanoma PDX model from which resistant tumors were developed following treatment with a MEK inhibitor. Our multi-omics strategy addresses current challenges in bioinformatics by leveraging development of custom curated proteogenomics databases derived from individual resistant melanoma that evolves following MEK inhibitor treatment and is scalable to comprehensively characterize acquired MAPK inhibitor resistance across patient-specific models and genomic subtypes of melanoma.