Rxivist logo

MONTE enables serial immunopeptidome, ubiquitylome, proteome, phosphoproteome, acetylome analyses of sample-limited tissues

By Jennifer G. Abelin, Erik J Bergstrom, Hannah B. Taylor, Keith D Rivera, Susan Klaeger, Meagan E Olive, Karl R. Clauser, C. Jackson White, Myranda Maynard, M. Harry Kane, Cadence Pearce, Suzanna Rachimi, Michael A. Gillette, Shankha Satpathy, Namrata D Udeshi, Steven A Carr

Posted 22 Jun 2021
bioRxiv DOI: 10.1101/2021.06.22.449417

Multiomic characterization of patient tissues provides insights into the function of different biological pathways in the context of disease. Much work has been done to serialize proteome and post-translational modification (PTM) analyses to conserve precious patient samples. However, characterizing clinically relevant tissues with multi-ome workflows that have distinct sample processing requirements remains challenging. To overcome the obstacles of combining enrichment workflows that have unique input amounts and utilize both label free and chemical labeling strategies, we developed a highly-sensitive multi-omic networked tissue enrichment (MONTE) workflow for the full analysis of HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome and acetylome all from the same tissue sample. The MONTE workflow enables identification of a median of 9,000 HLA-I peptides, 6,000 HLA-II peptides, 10,000 Ub sites, 12,000 proteins, 20,000 phosphorylation sites and 15,000 acetylation sites from patient LUAD tumors. Because all omes are generated from the exact same tissue sample, there is less biological variability in the data enabling more robust integration. The information available in MONTE datasets facilitates the identification of putative immunotherapeutic targets, such as CT antigens and neoantigens presented by HLA complexes, as well as reveal insights into how disease-specific changes in protein expression, protein degradation, cell signaling, metabolic, and epigenetic pathways are involved in disease pathology and treatment.

Download data

  • Downloaded 753 times
  • Download rankings, all-time:
    • Site-wide: 39,353
    • In cancer biology: 1,067
  • Year to date:
    • Site-wide: 6,430
  • Since beginning of last month:
    • Site-wide: 7,029

Altmetric data


Downloads over time

Distribution of downloads per paper, site-wide


PanLingua

News