» Articles » PMID: 35130834

Secreted Protein Markers in Oral Squamous Cell Carcinoma (OSCC)

Overview
Journal Clin Proteomics
Publisher Biomed Central
Date 2022 Feb 8
PMID 35130834
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Oral squamous cell carcinoma (OSCC) is a main cause of oral cancer mortality and morbidity in central south Asia. To improve the clinical outcome of OSCC patients, detection markers are needed, which are preferably non-invasive and thus independent of a tissue biopsy.

Methods: In the present study, we aimed to identify robust candidate protein biomarkers for non-invasive OSCC diagnosis. To this end, we measured the global protein profiles of OSCC tissue lysates to matched normal adjacent mucosa samples (n = 14) and the secretomes of nine HNSCC cell lines using LC-MS/MS-based proteomics.

Results: A total of 5123 tissue proteins were identified, of which 205 were robustly up- regulated (p-value < 0.01, fold change > + 2) in OSCC-tissues compared to normal adjacent tissues. The biological process "Secretion" was highly enriched in this set of proteins. Other upregulated biological pathways included "Unfolded Protein Response", "Spliceosomal complex assembly", "Protein localization to endosome" and "Interferon Gamma Response". Transcription factor analysis implicated Creb3L1, ESRRA, YY, ELF2, STAT1 and XBP as potential regulators. Of the 205 upregulated tissue proteins, 132 were identified in the cancer cell line secretomes, underscoring their potential use as non-invasive biofluid markers. To further prioritize our candidate markers for non-invasive OSCC detection, we integrated our data with public biofluid datasets including OSCC saliva, yielding 25 candidate markers for further study.

Conclusions: We identified several key proteins and processes that are associated with OSCC tissues, underscoring the importance of altered secretion. Cancer-associated OSCC secretome proteins present in saliva have potential to be used as novel non-invasive biomarkers for the diagnosis of OSCC.

Citing Articles

The role of molecular biomarkers in the diagnosis, prognosis, and treatment stratification of oral squamous cell carcinoma: A comprehensive review.

Ravindran S, Ranganathan S, R K, J N, A S, Kannan S J Liq Biopsy. 2025; 7:100285.

PMID: 40027232 PMC: 11863969. DOI: 10.1016/j.jlb.2025.100285.


Integrating omics data and machine learning techniques for precision detection of oral squamous cell carcinoma: evaluating single biomarkers.

Sun Y, Cheng G, Wei D, Luo J, Liu J Front Immunol. 2024; 15:1493377.

PMID: 39691710 PMC: 11649677. DOI: 10.3389/fimmu.2024.1493377.


Biomarkers Identification in the Microenvironment of Oral Squamous Cell Carcinoma: A Systematic Review of Proteomic Studies.

Pomella S, Melaiu O, Cifaldi L, Bei R, Gargari M, Campanella V Int J Mol Sci. 2024; 25(16).

PMID: 39201614 PMC: 11354375. DOI: 10.3390/ijms25168929.


Towards system genetics analysis of head and neck squamous cell carcinoma using the mouse model, cellular platform, and clinical human data.

Zohud O, Lone I, Nashef A, Iraqi F Animal Model Exp Med. 2023; 6(6):537-558.

PMID: 38129938 PMC: 10757216. DOI: 10.1002/ame2.12367.


Biological biomarkers of oral cancer.

Radaic A, Kamarajan P, Cho A, Wang S, Hung G, Najarzadegan F Periodontol 2000. 2023; 96(1):250-280.

PMID: 38073011 PMC: 11163022. DOI: 10.1111/prd.12542.


References
1.
Rodriguez H, Zenklusen J, Staudt L, Doroshow J, Lowy D . The next horizon in precision oncology: Proteogenomics to inform cancer diagnosis and treatment. Cell. 2021; 184(7):1661-1670. PMC: 8459793. DOI: 10.1016/j.cell.2021.02.055. View

2.
Hsu C, Yu J, Peng P, Liu S, Chang Y, Chang K . Secretome profiling of primary cells reveals that THBS2 is a salivary biomarker of oral cavity squamous cell carcinoma. J Proteome Res. 2014; 13(11):4796-807. DOI: 10.1021/pr500038k. View

3.
Hermsen M, Joenje H, Arwert F, Welters M, Braakhuis B, Bagnay M . Centromeric breakage as a major cause of cytogenetic abnormalities in oral squamous cell carcinoma. Genes Chromosomes Cancer. 1996; 15(1):1-9. DOI: 10.1002/(SICI)1098-2264(199601)15:1<1::AID-GCC1>3.0.CO;2-8. View

4.
Bendtsen J, Jensen L, Blom N, von Heijne G, Brunak S . Feature-based prediction of non-classical and leaderless protein secretion. Protein Eng Des Sel. 2004; 17(4):349-56. DOI: 10.1093/protein/gzh037. View

5.
Cox J, Mann M . MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol. 2008; 26(12):1367-72. DOI: 10.1038/nbt.1511. View