4.7 Article

Proteomics Analysis of Gastric Cancer Patients with Diabetes Mellitus

Journal

JOURNAL OF CLINICAL MEDICINE
Volume 10, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/jcm10030407

Keywords

gastric cancer (GC); diabetes mellitus (DM); proteomics; label free quantification (LFQ)

Funding

  1. Norte Portugal Regional Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF) [NORTE-01-0145-FEDER-000003]
  2. FEDER-Fundo Europeu de Desenvolvimento Regional-funds through the COMPETE 2020-Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020
  3. Portuguese funds through FCT-Fundacao para a Ciencia e a Tecnologia/Ministerio da Ciencia, Tecnologia e Inovacao-in the framework of the project Institute for Research and Innovation in Health Sciences [POCI-01-0145-FEDER-007274]
  4. Portuguese Mass Spectrometry Network
  5. National Roadmap of Research Infrastructures of Strategic Relevance [ROTEIRO/0028/2013, LISBOA-01-0145-FEDER-022125]

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This study characterized the proteomic profile of gastric cancer in patients with type 2 diabetes mellitus, revealing differentially expressed proteins associated with various biological processes and diseases. The results supported the association between diabetes, metabolic disorders, and related diseases, providing valuable insights into potential protein targets for further investigation.
Proteomics is a powerful approach to study the molecular mechanisms of cancer. In this study, we aim to characterize the proteomic profile of gastric cancer (GC) in patients with diabetes mellitus (DM) type 2. Forty GC tissue samples including 19 cases from diabetic patients and 21 cases from individuals without diabetes (control group) were selected for the proteomics analysis. Gastric tissues were processed following the single-pot, solid-phase-enhanced sample preparation approach-SP3 and enzymatic digestion with trypsin. The resulting peptides were analyzed by LC-MS Liquid Chromatography-Mass Spectrometry (LC-MS). The comparison of protein expression levels between GC samples from diabetic and non-diabetic patients was performed by label-free quantification (LFQ). A total of 6599 protein groups were identified in the 40 samples. Thirty-seven proteins were differentially expressed among the two groups, with 16 upregulated and 21 downregulated in the diabetic cohort. Statistical overrepresentation tests were considered for different annotation sets including the Gene Ontology(GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Disease functional databases. Upregulated proteins in the GC samples from diabetic patients were particularly enriched in respiratory electron transport and alcohol metabolic biological processes, while downregulated proteins were associated with epithelial cancers, intestinal diseases, and cell-cell junction cellular components. Taken together, these results support the data already obtained by previous studies that associate diabetes with metabolic disorders and diabetes-associated diseases, such as Alzheimer's and Parkinson's, and also provide valuable insights into seven GC-associated protein targets, claudin-3, polymeric immunoglobulin receptor protein, cadherin-17, villin-1, transglutaminase-2, desmoglein-2, and mucin-13, which warrant further investigation.

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