C1QA and COMP: plasma-based biomarkers for early diagnosis of pancreatic neuroendocrine tumors

• Published in: Scientific reports Vol. 13; no. 1; pp. 21021 - 12
• Main Authors: Gorai, Priya Kumari, Bharti, Prahalad Singh, Kumar, Shashi, Rajacharya, Girish H., Bandyopadhyay, Sabyasachi, Pal, Sujoy, Dhingra, Renu, Kumar, Rakesh, Nikolajeff, Fredrik, Kumar, Saroj, Rani, Neerja
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 29.11.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 631/337/475; 631/67/1504/1713; 631/67/1857; Biomarkers; Biomarkers, Tumor - analysis; Biomedical Engineering; Down-regulation; Early Detection of Cancer; Humanities and Social Sciences; Humans; Mass spectrometry; Mass spectroscopy; Medicinsk teknik; multidisciplinary; Neuroendocrine tumors; Neuroendocrine Tumors - pathology; Pancreas; Pancreatic cancer; Pancreatic Neoplasms - pathology; Proteins; Proteomics; Science; Science (multidisciplinary); Therapeutic targets
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-48323-x

Pancreatic Neuroendocrine tumors (PanNET) are challenging to diagnose and often detected at advanced stages due to a lack of specific and sensitive biomarkers. This study utilized proteomics as a valuable approach for cancer biomarker discovery; therefore, mass spectrometry-based proteomic profiling was conducted on plasma samples from 12 subjects (3 controls; 5 Grade I, 4 Grade II PanNET patients) to identify potential proteins capable of effectively distinguishing PanNET from healthy controls. Data are available via ProteomeXchange with the identifier PXD045045. 13.2% of proteins were uniquely identified in PanNET, while 60% were commonly expressed in PanNET and controls. 17 proteins exhibiting significant differential expression between PanNET and controls were identified with downstream analysis. Further, 5 proteins (C1QA, COMP, HSP90B1, ITGA2B, and FN1) were selected by pathway analysis and were validated using Western blot analysis. Significant downregulation of C1QA (p = 0.001: within groups, 0.03: control vs. grade I, 0.0013: grade I vs. grade II) and COMP (p = 0.011: within groups, 0.019: control vs grade I) were observed in PanNET Grade I & II than in controls. Subsequently, ELISA on 38 samples revealed significant downregulation of C1QA and COMP with increasing disease severity. This study shows the potential of C1QA and COMP in the early detection of PanNET, highlighting their role in the search for early-stage (Grade-I and Grade-II) diagnostic markers and therapeutic targets for PanNET.