PXD071434

PXD071434 is an original dataset announced via ProteomeXchange.

Title	OVERDRIVE: overcoming cancer cell resistance to drugs by supplementary nontoxic molecule predicted by a machine learning tool
Description	Here we aim to test the notion that overcoming cancer cells’ acquired resistance to chemotherapy drugs may be achieved by administrating together with the main drug a molecule that is not toxic by itself but enhances the drug efficacy in killing the resistant cells. Finding such a supplementary molecule is a nontrivial task. Our algorithmic approach, named OVERcoming Drug Resistance by In Vitro cell Exposure (OVERDRIVE), involves exposing drug-sensitive cancer cells to increasing drug concentrations for several weeks followed by a comprehensive proteomic analysis of both the exposed and sensitive cells. Applying a machine learning tool Genome Enhancer to the proteomic data reveals the protein network accounting for the differences between the exposed and naïve cells and predicts molecules that may shift the exposed cell phenotypes to the sensitive one. Experimental validation of the top predicted nontoxic molecules confirmed that the combined treatment of the experimental drug LTCA2940 that targets redox pathways with identified supplementary molecule restored the sensitivity of LTCA2940-resistant cells. The OVERDRIVE approach may pave a way for a strategy to overcoming anticancer resistance to chemotherapy in clinic.
HostingRepository	PRIDE
AnnounceDate	2026-06-08
AnnouncementXML	Submission_2026-06-07_22:11:37.786.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Hezheng Lyu
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: NEWT:9606;
ModificationList	acetylated residue; monohydroxylated residue; deamidated residue; iodoacetamide derivatized residue
Instrument	Orbitrap Exploris 480

Revision	Datetime	Status	ChangeLog Entry
0	2025-12-01 08:33:03	ID requested
⏵ 1	2026-06-07 22:11:38	announced

Lyu H, Gharibi H, Meng Z, Sokolova B, Lundstr, ö, m S, Zhang X, Zubarev RA, Peptide-to-Protein Data Aggregation Using Fisher's Method Improves Target Identification in Chemical Proteomics. Anal Chem, 98(17):12596-12602(2026) [pubmed]

10.1021/acs.analchem.5c08021;

submitter keyword: None

Roman Zubarev
contact affiliation	Division of Physiological Chemistry I, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-17 177 Stockholm, Sweden
contact email	roman.zubarev@ki.se
lab head
Hezheng Lyu
contact affiliation	Karolinska Institutet
contact email	hezheng.lyu@ki.se
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/06/PXD071434

PRIDE project URI

• PRIDE
  1. PXD071434
     1. Label: PRIDE project
     2. Name: OVERDRIVE: overcoming cancer cell resistance to drugs by supplementary nontoxic molecule predicted by a machine learning tool