Evidence map›Paper›PMID 37645963›Full record

ArticlebioRxiv : the preprint server for biology2023

Multi-omic stratification of the missense variant cysteinome.

Heta Desai, Samuel Ofori, Lisa Boatner, Fengchao Yu, Miranda Villanueva, Nicholas Ung, Alexey I Nesvizhskii, Keriann Backus

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 12 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Heta DesaiBiological Chemistry Department, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA.
Samuel OforiBiological Chemistry Department, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA.
Lisa BoatnerBiological Chemistry Department, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA.
Fengchao YuDepartment of Pathology, University of Michigan, Ann Arbor, MI, 48109, USA.
Miranda VillanuevaBiological Chemistry Department, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA.
Nicholas UngBiological Chemistry Department, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA.
Alexey I NesvizhskiiDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA.
Keriann BackusBiological Chemistry Department, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA.
University of California, Los Angeles · USUniversity of Michigan · US

Funding

COMPUTATIONAL TOOLS FOR MASS SPECTROMETRY-BASED INTERACTOME DATAR01GM094231 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Alexey I Nesvizhskii · 2010 to 2026
$5.4M
Michigan Center for Translational Cancer Proteogenomics-Diversity SupplementU24CA271037 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Saravana Mohan Dhanasekaran, Alexey I Nesvizhskii · 2022 to 2026
$4.4M
NCI NIH HHS U24 CA271037NIGMS NIH HHS R01 GM094231
6 · The paper itself

Abstract

Cancer genomes are rife with genetic variants; one key outcome of this variation is gain-ofcysteine, which is the most frequently acquired amino acid due to missense variants in COSMIC. Acquired cysteines are both driver mutations and sites targeted by precision therapies. However, despite their ubiquity, nearly all acquired cysteines remain uncharacterized. Here, we pair cysteine chemoproteomics-a technique that enables proteome-wide pinpointing of functional, redox sensitive, and potentially druggable residues-with genomics to reveal the hidden landscape of cysteine acquisition. For both cancer and healthy genomes, we find that cysteine acquisition is a ubiquitous consequence of genetic variation that is further elevated in the context of decreased DNA repair. Our chemoproteogenomics platform integrates chemoproteomic, whole exome, and RNA-seq data, with a customized 2-stage false discovery rate (FDR) error controlled proteomic search, further enhanced with a user-friendly FragPipe interface. Integration of CADD predictions of deleteriousness revealed marked enrichment for likely damaging variants that result in acquisition of cysteine. By deploying chemoproteogenomics across eleven cell lines, we identify 116 gain-of-cysteines, of which 10 were liganded by electrophilic druglike molecules. Reference cysteines proximal to missense variants were also found to be pervasive, 791 in total, supporting heretofore untapped opportunities for proteoform-specific chemical probe development campaigns. As chemoproteogenomics is further distinguished by sample-matched combinatorial variant databases and compatible with redox proteomics and small molecule screening, we expect widespread utility in guiding proteoform-specific biology and therapeutic discovery.

Identifiers

PMID37645963
PMCPMC10461992
OpenAlexW4385837670

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.