PXD060017

PXD060017 is an original dataset announced via ProteomeXchange.

Title	Explainable Machine Learning Identifies Factors for Dosage Compensation in Aneuploid Human Cancer Cells
Description	Change in chromosome copy number, or aneuploidy, is a typical feature of cancer cells, which can alter the protein abundance of hundreds or thousands of proteins. Yet, evidence from aneuploid cell lines suggests that the protein dosage changes are to a great extent buffered, and thus the abundance of many proteins is similar to the abundance in euploid cells despite gene copy number changes. Despite ubiquitous occurrence of protein dosage buffering, there is limited understanding of the involved molecular mechanisms. Moreover, whether protein dosage buffering affects all proteins and cells to similar degree, and whether it brings adaptive advantage remains unclear. Here, we established a novel approach to quantify protein dosage buffering in a gene copy-number dependent manner, and show that dosage compensation is wide-spread in cancer cell lines and in-vivo tumor samples, yet the extent of buffering is variable. By devising multifactorial machine learning (ML) models that efficiently predict gene dosage buffering and the usage of explainable ML techniques, we demonstrate that mean gene dependency, protein complex participation, haploinsufficiency and mRNA decay are strongly predictive for buffering. Our analysis also indicates that proteotoxic stress and drug sensitivity is reduced in samples that exhibit high protein buffering on average.
HostingRepository	PRIDE
AnnounceDate	2025-09-12
AnnouncementXML	Submission_2025-09-12_01:54:20.527.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Markus Räschle
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	No PTMs are included in the dataset
Instrument	Q Exactive HF

Revision	Datetime	Status	ChangeLog Entry
0	2025-01-21 06:33:01	ID requested
⏵ 1	2025-09-12 01:54:20	announced

Dataset with its publication pending

submitter keyword: machine learning, cancer, dosage compensation,aneuploidy

Markus Räschle
contact affiliation	Molecular Genetics, RPTU Kaiserslautern
contact email	raeschle@rhrk.uni-kl.de
lab head
Markus Räschle
contact affiliation	Technical University Kaiserslautern
contact email	raeschle@rhrk.uni-kl.de
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/2025/09/PXD060017

PRIDE project URI

• PRIDE
  1. PXD060017
     1. Label: PRIDE project
     2. Name: Explainable Machine Learning Identifies Factors for Dosage Compensation in Aneuploid Human Cancer Cells