Thousands of Novel Unannotated Proteins Expand the MHC I Immunopeptidome in Cancer
May 11, 2020·,,,,,
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0 min read
T. ouspenskaia
T. law
K. r. clauser
S. klaeger
S. sarkizova
F. aguet
Dr. Bo Li
E. christian
B. a. knisbacher
P. m. le
C. r. hartigan
H. keshishian
A. apffel
G. oliveira
W. zhang
Y. t. chow
Z. ji
I. jungreis
S. a. shukla
P. bachireddy
M. kellis
G. getz
N. hacohen
D. b. keskin
S. a. carr
C. j. wu
A. regev
Abstract
Tumor epitopes – peptides that are presented on surface-bound MHC I proteins - provide targets for cancer immunotherapy and have been identified extensively in the annotated protein-coding regions of the genome. Motivated by the recent discovery of translated novel unannotated open reading frames (nuORFs) using ribosome profiling (Ribo-seq), we hypothesized that cancer-associated processes could generate nuORFs that can serve as a new source of tumor antigens that harbor somatic mutations or show tumor-specific expression. To identify cancer-specific nuORFs, we generated Ribo-seq profiles for 29 malignant and healthy samples, developed a sensitive analytic approach for hierarchical ORF prediction, and constructed a high-confidence database of translated nuORFs across tissues. Peptides from 3,555 unique translated nuORFs were presented on MHC I, based on analysis of an extensive dataset of MHC I-bound peptides detected by mass spectrometry, with >20-fold more nuORF peptides detected in the MHC I immunopeptidomes compared to whole proteomes. We further detected somatic mutations in nuORFs of cancer samples and identified nuORFs with tumor-specific translation in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs thus expand the pool of MHC I-presented, tumorspecific peptides, targetable by immunotherapies.
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bioRxiv
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Principal Scientist II
Dr. Bo Li is a Principal Scientist at Genentech, Inc. His research focuses on large-scale single-cell genomics data analysis.
Before joining in Genentech, he was an Assistant Professor of Medicine at Harvard Medical School and the director of Bioinformatics and Computational Biology at Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital.
He received his Ph.D. in computer science from UW-Madison and completed two postdoctoral trainings with Dr. Lior Pachter at UC Berkeley and Dr. Aviv Regev at Broad Institute.
He is best known for developing RSEM, an impactful RNA-seq transcript quantification software. RSEM is cited 22,602 times (Google Scholar) and adopted by several big consortia such as TCGA, ENCODE, GTEx and TOPMed.
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