PXD025594

PXD025594 is an original dataset announced via ProteomeXchange.

Title	Cancer tissue classification using supervised machine learning applied to MALDI mass spectrometry imaging
Description	With the current clinical available technologies, not all cancers are staged accurately. Because of this a large percentage of patients are misclassified before treatment, leading to under or over treatment. Therefore, a classification system based on the molecular feature is required to deter-mine the tumour behavior and metastatic potential. Here, we have shown the diagnostic potential of MALDI MSI using supervised machine learning approach in distinguishing cancerous colorectal tissue from normal with an overall accuracy of 98%. Also, shown is the capability of the technique in predicting the presence of metastasis in endometrial cancer with an overall accuracy of 80%. The development of such a model can help in determining the optimum treatment for cancerous pa-tients, reduce morbidity and better patient outcome.
HostingRepository	PRIDE
AnnounceDate	2022-02-17
AnnouncementXML	Submission_2022-02-17_00:53:50.720.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Parul Mittal
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	No PTMs are included in the dataset
Instrument	ultraflex

Revision	Datetime	Status	ChangeLog Entry
0	2021-04-23 06:20:53	ID requested
⏵ 1	2022-02-17 00:53:51	announced

Mittal P, Condina MR, Klingler-Hoffmann M, Kaur G, Oehler MK, Sieber OM, Palmieri M, Kommoss S, Brucker S, McDonnell MD, Hoffmann P, Cancer Tissue Classification Using Supervised Machine Learning Applied to MALDI Mass Spectrometry Imaging. Cancers (Basel), 13(21):(2021) [pubmed]

submitter keyword: Colorectal cancer (CRC), Endometrial cancer (EC), Lymph Node Metastasis (LNM), Machine learning (ML), Matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI)

Prof Peter Hoffmann
contact affiliation	Strand Leader and Lloyd Sansom Chair Biomaterials Engineering and Nanomedicine Future Industries Institute I Building X – X1-10 Mawson Lakes Campus I GPO Box 2471 University of South Australia Adelaide, South Australia 5001 t: +61 8 830 25563 | m: +61 434 079 108 f: +61 8 830 25639
contact email	peter.hoffmann@unisa.edu.au
lab head
Parul Mittal
contact affiliation	Research associate
contact email	pearl106@gmail.com
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/2022/02/PXD025594

PRIDE project URI

• PRIDE
  1. PXD025594
     1. Label: PRIDE project
     2. Name: Cancer tissue classification using supervised machine learning applied to MALDI mass spectrometry imaging