PXD044935-2

PXD044935 is an original dataset announced via ProteomeXchange.

Title	Proteomics characterization of colon cancer Consensus Molecular Subtypes using data-independent acquisition mass-spectrometry
Description	The Colorectal Cancer Subtyping Consortium established four Consensus Molecular Subtypes (CMS) in colorectal cancer: CMS1 (microsatellite-instability [MSI], Immune), CMS2 (Canonical, epithelial), CMS3 (Metabolic), and CMS4 (Mesenchymal). However, in the clinical practice only patients with MSI tumors have experienced a change in the management of their disease. Proteomics has experimented significant technical advances with the implementation of data-independent acquisition (DIA) as the gold-standard for the analysis of large cohort of patients, providing a dynamic framework of the disease and direct information about the effectors of the biological processes. The aim of this study is the characterization of the proteome of colon cancer CMS by DIA–based proteomics and expand the utility of CMS in the clinical practice. CMS were assigned and differences in the protein profiles between CMS were defined and evaluated using a Systems Biology approach. One hundred fifty-eight paraffin samples from colon cancer patients with stage II-III disease treated with adjuvant chemotherapy were analyzed. After applying quality criteria, 1,940 identified and quantified proteins were used for the analyses. CMS1 had an overexpression of proteins related to immune system, specifically neutrophils, phagocytosis and antimicrobial response, and a glycolytic profile. CMS3 had an overexpression of proteins related to metabolic pathways, while CMS2 showed an intermediate protein profile between CMS1-3, but with a characteristic profile regarding translation, adhesion, and mitochondria and metabolism biological processes. Two proteomics subtypes within CMS2 with different protein characteristics and prognosis were identified. CMS4 was the most different group with an overexpression of proteins related to angiogenesis, extracellular matrix, focal adhesion, and complement activation. In conclusion, DIA LC-MS/MS proteomics characterization of CRC CMS established new features for each CMS, such as a higher mitochondrial activity in CMS2 or an overexpression of proteins related to phagocytosis in CMS1, but also confirmed previous findings established using transcriptomics such as an overexpression of proteins related to angiogenesis in CMS4. In this CMS4 subtype, several adhesion-related proteins suggested a high metastatic profile and a possible chemoresistance that may explain the worse prognosis of this subtype. CMS1 was characterized as immune and glycolitic-active subtype, being the combination of immunotherapy and glycolytic inhibitors a possible therapeutic strategy. Additionally, two different CMS2 proteomics-based subtypes with different prognosis and possible therapeutic targets were identified. These proccesses could be used as therapeutic targets in the future.
HostingRepository	PRIDE
AnnounceDate	2024-10-22
AnnouncementXML	Submission_2024-10-22_07:00:04.737.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Laura Kunz
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	monohydroxylated residue; iodoacetamide derivatized residue
Instrument	Orbitrap Fusion

Revision	Datetime	Status	ChangeLog Entry
0	2023-08-29 10:11:44	ID requested
1	2024-09-30 03:51:51	announced
⏵ 2	2024-10-22 07:00:05	announced	2024-10-22: Updated project metadata.

10.1038/S41416-024-02650-6;

submitter keyword: proteomics,Colon cancer, DIA, LC-MS/MS

Lucía Trilla-Fuertes
contact affiliation	Molecular Oncology Lab, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain
contact email	lucia.lt30@gmail.com
lab head
Laura Kunz
contact affiliation	ETH
contact email	laura.kunz@fgcz.ethz.ch
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD044935
     1. Label: PRIDE project
     2. Name: Proteomics characterization of colon cancer Consensus Molecular Subtypes using data-independent acquisition mass-spectrometry