Discovery and Targeting of a Cryptic Human Proteome

Abstract

First-in-class therapeutics require first-in-class biology. Yet despite decades of genomic and proteomic cataloging, vast regions of the human transcriptome remain dark and their encoded proteins invisible. Here we present RyboCypher, an integrated RNA-sequencing and AI-assisted proteogenomics platform that systematically maps the RyboCypher-derived "dark" transcriptome to unannotated peptides, predicting and empirically identifying cryptic proteins across the uncharted genome. Applied to cancer cell lines, patient tumors, and matched healthy tissues, RyboCypher resolved [~]8.3 million dark RNA isoforms and [~]16 million candidate ORFs. Interrogating these against [~]0.5 billion MS/MS spectra from cellular proteomics, membrane proteomics, and immunopeptidomics datasets (comprising a total of >8,000 raw MS data files ([~]7TB of MS data), derived from 2,229 patient samples), we empirically identified [~]80,000 cryptic peptides ([~]10,000 cancer-associated or cancer-upregulated) at View larger version (28K): org.highwire.dtl.DTLVardef@104c385org.highwire.dtl.DTLVardef@1c065ccorg.highwire.dtl.DTLVardef@5b717forg.highwire.dtl.DTLVardef@1788694_HPS_FORMAT_FIGEXP M_FIG C_FIG