PXD035120

PXD035120 is an original dataset announced via ProteomeXchange.

Title	Plasma proteomics enable differentiation of lung adenocarcinoma from chronic obstructive pulmonary disease (COPD)
Description	Background: Chronic obstructive pulmonary disease (COPD) is a major risk factor for the development of lung adenocarcinoma (AC). AC often develops on underlying COPD, thus the differentiation of both entities by biomarker is challenging. Although survival of AC patients strongly depends on early diagnosis, a biomarker panel for AC detection and differentiation from COPD is still missing. Methods: Plasma samples from 176 patients with AC with or without underlying COPD, COPD patients, and hospital controls were analyzed using mass spectrometry-based proteomics. We performed univariate statistics and additionally evaluated machine learning algorithms regarding the differentiation of AC vs. COPD and AC with COPD vs. COPD. Results: Univariate statistics revealed significantly regulated proteins that were significantly regulated between the patient groups. Furthermore, Random forest classification yielded the best performance for differentiation of AC vs. COPD (area under the curve (AUC) 0.935) and AC with COPD vs. COPD (AUC 0.916). The most influential proteins were identified by permutation feature importance and compared to those identified by univariate testing. Conclusion: We demonstrate the great potential of machine learning for differentiation of highly similar disease entities and present a panel of biomarker candidates that should be considered for the development of a future biomarker panel.
HostingRepository	PRIDE
AnnounceDate	2023-11-14
AnnouncementXML	Submission_2023-11-14_07:57:34.193.xml
DigitalObjectIdentifier	https://dx.doi.org/10.6019/PXD035120
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Supported dataset by repository
PrimarySubmitter	Thilo Bracht
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	S-carboxamidoethyl-L-cysteine; monohydroxylated residue
Instrument	Q Exactive HF

Revision	Datetime	Status	ChangeLog Entry
0	2022-07-06 14:31:20	ID requested
1	2022-10-17 14:42:30	announced
⏵ 2	2023-11-14 07:57:35	announced	2023-11-14: Updated project metadata.

Bracht T, Kleefisch D, Schork K, Witzke KE, Chen W, Bayer M, Hovanec J, Johnen G, Meier S, Ko YD, Behrens T, Br, ü, ning T, Fassunke J, Buettner R, Uszkoreit J, Adamzik M, Eisenacher M, Sitek B, Plasma Proteomics Enable Differentiation of Lung Adenocarcinoma from Chronic Obstructive Pulmonary Disease (COPD). Int J Mol Sci, 23(19):(2022) [pubmed]

10.6019/PXD035120;

submitter keyword: machine learning, random forest, SERPINA3, SAA1, chronic obstructive pulmonary disease, artificial intelligence,Adenocarcinoma of the lung, plasma proteomics

Thilo Bracht
contact affiliation	Department of Anesthesia, Intensive Care Medicine and Pain Therapy, University Hospital Knappschaftskrankenhaus Bochum, Medizinisches Proteom-Center, Ruhr-University Bochum
contact email	thilo.bracht@rub.de
lab head
Thilo Bracht
contact affiliation	Clinical Proteomics
contact email	thilo.bracht@rub.de
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD035120
     1. Label: PRIDE project
     2. Name: Plasma proteomics enable differentiation of lung adenocarcinoma from chronic obstructive pulmonary disease (COPD)