Massive single cell proteomics for cancer biology

用于癌症生物学的大规模单细胞蛋白质组学

• 批准号: 10707321
• 负责人: Ljiljana Pasa-Tolic
• 金额: $ 64.75万
• 依托单位: BATTELLE PACIFIC NORTHWEST LABORATORIES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-20 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10707321
• 关键词: Address; Architecture; Benchmarking; Bone Marrow; Cancer Biology; Cell Separation; Cell physiology; Cells; Cellular biology; Clinical; Clinical Treatment; Collaborations; Communities; Coupling; Data; Diagnosis; Digestion; Disease Progression; Disease Resistance; Environment; Evolution; Genomics; Goals; Hematopoietic Neoplasms; Heterogeneity; Human; Immune; Individual; Isotope Labeling; Knowledge; Label; Laboratories; Liquid substance; Malignant - descriptor; Malignant Neoplasms; Mass Spectrum Analysis; Methods; Microfluidics; Molecular; Multiple Myeloma; Nature; Outcome; Pathogenesis; Pathologic; Patients; Performance; Peripheral Blood Mononuclear Cell; Phenotype; Plasma; Plasma Cells; Population; Post-Translational Protein Processing; Preparation; Process; Proteins; Proteome; Proteomics; RNA; Research; Resistance; Running; Sampling; Somatic Cell; Specimen; System; Technology; Therapeutic; Transcript; Universities; Washington; Yeasts; cancer proteomics; cell preparation; chimeric antigen receptor T cells; computational pipelines; cost efficient; data acquisition; density; improved; individual variation; innovation; insight; microchip; nanoDroplet; neoplastic cell; next generation; next generation sequencing; personalized medicine; protein biomarkers; protein expression; protein profiling; relapse patients; single cell technology; single-cell RNA sequencing; success; therapy resistant; transcriptomics; tumor; tumor heterogeneity; tumor progression; tumor-immune system interactions

PROJECT SUMMARY/ABSTRACT Single-cell technologies have become the cornerstone of biomedical and cell biology research. Next- generation sequencing-based technologies have enabled large-scale characterization of transcript expressions in single cells from clinical specimens and reveal unexpected cellular heterogeneity related to pathogenesis. However, many integrative studies have shown only low to moderate correlations between the abundance of RNA transcripts and their corresponding proteins, the main determinants of cell phenotype. We hypothesize mass spectrometry-based single-cell proteomics could provide direct insight on the cellular heterogeneity and inform protein markers related to disease progression and resistance to therapy. The overall objective of this project is to develop a high throughput single-cell proteomics (scProteomics) platform to enable the routine analysis of >10,000 single cells at a depth of 2000 proteins in a cost-efficient way. The developed technology will be disseminated to the research community through close collaboration with a commercial partner. We will also apply scProteomics to interrogate the heterogeneity of both malignant plasma cell and immune cell populations from multiple myeloma patients. We will pursue these goals through three specific aims: 1) To establish an ultra-high throughput single-cell preparation method by coupling an enhanced multiplexing method with high-density nested nanoPOTS chips and multi-channel droplet dispensing system; We aim to process >2000 cells in a single microchip, and multiplex-label 36 single cells for a single LC-MS analysis; 2) To advance the throughput, sensitivity, and quantitation accuracy of LC-MS system. A dual-column nanoLC system and a FAIMS-based MS acquisition method will be developed to enable the analysis of >860 cells per day with high quantitation precision; 3) To apply scProteomics to profile ~10,000 plasma and immune cells from MM patients. We will integrate scProteomics with existing scRNA-seq data to explore tumor heterogeneity, chimeric antigen receptor T-cells (CAR-T) markers, and the immune microenvironment in multiple myeloma. This research is highly innovative because the proposed single-cell proteomics platform will be the first of its kind to routinely and reliably characterize > 10,000 single cells at a throughput comparable to single-cell transcriptomics. It is also the first scProteomics study of primary liquid tumor cells isolated from the pathological environment, e.g. bone marrow of MM patients. Statement of Impact: Tumor heterogeneity has indispensable implications in cancer evolution, tumoral spatial organization, and clinical treatment. Single-cell proteomics could provide a basis to unravel these complicated relationships and to clarify the mechanisms of cancer progression and subclone resistance to therapeutic treatments.

项目总结/文摘