PXD047546

PXD047546 is an original dataset announced via ProteomeXchange.

Title	Spatial omics based machine learning (SOML) algorithms for the early detection of hepatocellular carcinoma.
Description	Hepatocellular carcinoma (HCC) is the seventh most common cancer in the world and accounts for over 800,000 deaths annually, making it the second most lethal cancer. Poor chemotherapeutic agents against HCC have necessitated the importance of early detection and surgical intervention in patient management. However, the search for biomarkers of HCC have proved difficult, as serum and tissue proteomics, transcriptomics and genomics have proved inconclusive. We have utilized a novel spatial-omics based glycan imaging method to identify glycan changes that occur directly in HCC tissue. Glycan changes included branched, fucosylated and high mannose glycan. Importantly, using matching serum samples, we were able to identify the glycans that are altered in tissue and also in the serum of individuals with HCC. Glycoproteomics was used to identify the proteins containing these glycan structures. To translate these findings, we utilized a novel multi-plexed antibody panel based glycan imaging method, which allowed us to examine all the glycans associated with the identified glycoproteins. These glycan changes, found in serum, and directly associated with the tumor, were used to create a diagnostic algorithm to detect HCC. These spatial omics based, machine learning (SOML) algorithms were tested in a discovery set (n=201) and an external validation set (n=192). AUROC values ranged from 0.95 in the discovery set and 0.91 in the independent external validation set. In conclusion, we present the development and application of a new biomarker platform that can be used to examine the glycans associated with disease.
HostingRepository	PRIDE
AnnounceDate	2025-05-06
AnnouncementXML	Submission_2025-05-06_12:22:47.298.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Jennifer Bethard
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	fucosylated residue
Instrument	Orbitrap Exploris 480

Revision	Datetime	Status	ChangeLog Entry
0	2023-12-05 13:11:05	ID requested
⏵ 1	2025-05-06 12:22:48	announced

10.1038/s43856-024-00677-7;

Wang M, Grauzam S, Bayram MF, Dressman J, DelaCourt A, Blaschke C, Liang H, Scott D, Huffman G, Black A, Ochoa-Rios S, Lewin D, Angel PM, Drake RR, Ball L, Bethard J, Castellino S, Kono Y, Kubota N, Hoshida Y, Quirk L, Yopp A, Gopal P, Singal A, Mehta AS, Spatial omics-based machine learning algorithms for the early detection of hepatocellular carcinoma. Commun Med (Lond), 4(1):258(2024) [pubmed]

submitter keyword: Glycan, spatial-omics,HCC, Imaging, MALDI_TOF

Anand S. Mehta1
contact affiliation	Medical University of South Carolina, Department of Cell and Molecular Pharmacology, Charleston, SC 29425, United States
contact email	mehtaa@musc.edu
lab head
Jennifer Bethard
contact affiliation	Medical University of SC
contact email	bethard@musc.edu
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/2025/05/PXD047546

PRIDE project URI

• PRIDE
  1. PXD047546
     1. Label: PRIDE project
     2. Name: Spatial omics based machine learning (SOML) algorithms for the early detection of hepatocellular carcinoma.