Background: Tobacco exposure (through smoking or chewing) is one of the predominant risk factors associated with the development of oral squamous cell carcinoma (OSCC). Despite the growing number of patients diagnosed with OSCC, there are few circulating biomarkers for identifying individuals at a higher risk of developing the disease. Successful identification of candidate molecular markers for risk assessment could aid in the early detection of oral lesions and potentially be used for community screening of high-risk populations.

Objective: Identification of differentially expressed proteins in the serum of oral cancer patients which can serve as biomarkers for the diagnosis of the onset of oral cancer among tobacco users.

Methods: We employed a tandem mass tag (TMT)-based quantitative proteomics approach to study alterations in the serum proteomes of OSCC patients based on their tobacco exposure habits (chewing and smoking) compared to healthy individuals with no history of using any form of tobacco or any symptoms of the disease.

Results: Mass spectrometry-based analysis resulted in the identification of distinct signatures in the serum of OSCC patients who either chewed or smoked tobacco. Pathway analysis revealed opposing effects of dysregulated proteins enriched in the complement-coagulation signaling cascades with a high expression of the Serpin family of proteins observed in OSCC patients who chewed tobacco compared to healthy individuals whereas these proteins showed decreased levels in OSCC patients who smoked. ELISA-based validation further confirmed our findings revealing higher expression of SERPINA6 and SERPINF1 across serum of OSCC patients who chewed tobacco compared to healthy individuals.

Conclusions: This study serves as a benchmark for the identification of serum-based protein markers that may aid in the identification of high-risk patients who either chew tobacco or smoke tobacco.

Download full-text PDF

Source
http://dx.doi.org/10.3233/CBM-203077DOI Listing

Publication Analysis

Top Keywords

oscc patients
20
oral cancer
12
compared healthy
12
patients chewed
12
tobacco
10
cancer tobacco
8
tobacco exposure
8
patients
8
healthy individuals
8
serum oscc
8

Similar Publications

Objectives: To assess the usefulness of sentinel lymph node biopsy (SLNB) in patients with early-stage oral squamous cell carcinoma (OSCC).

Materials And Methods: Seventy-five patients (mean age 62 years) diagnosed with cT1-2 N0 underwent SLNB with Tc, lymphoscintigraphy/SPECT-CT, and gamma probe detection with intraoperative histological examination of the resected sentinel lymph nodes (SLNs). Elective neck dissection was performed during the same surgical procedure of primary tumor resection when malignant deposits were detected microscopically.

View Article and Find Full Text PDF

Modeling the lymph node stromal cells in oral squamous cell carcinoma: insights into the stromal cues in nodal metastasis.

Hum Cell

January 2025

Integrated Head and Neck Oncology Program (DSRG-5), Mazumdar Shaw Medical Foundation, Narayana Health, Bangalore, India.

The study explores the development and characterization of lymph node stromal cell cultures (LNSCs) from patients with oral squamous cell carcinoma (OSCC), highlighting the importance of understanding tumor-node cross-talk for effective prognostic and therapeutic interventions. Herein, we describe the development and characterization of primary lymph node stromal cells (LNSCs, N = 14) from nodes of metastatic and non-metastatic OSCC patients. Primary cultures were established by the explant method from positive (N + ; N = 2), and negative nodes (N0; N = 4) of the metastatic patients (N = 3) as well as negative (N0; N = 8) nodes from non-metastatic (N = 4) patients.

View Article and Find Full Text PDF

Background: Depth of invasion (DOI) significantly influences prognosis and treatment strategies in oral squamous cell carcinoma (OSCC). Accurate preoperative imaging, such as contrast-enhanced computed tomography (CECT), alongside postoperative histopathological evaluations, aids in determining DOI. This study evaluates the correlation between radiological DOI (rDOI), macroscopic DOI (PDOI), and microscopic DOI (pDOI) in OSCC.

View Article and Find Full Text PDF

Lymph node metastasis in level IIb neck dissection for clinically node-negative oral squamous cell carcinoma patients: an 11-year retrospective study.

Int J Oral Maxillofac Surg

January 2025

Service de Chirurgie Maxillo-Faciale et Stomatologie, Université de Bordeaux, CHU Bordeaux, Bordeaux, France. Electronic address:

The most common complication associated with selective neck dissection is spinal accessory nerve dysfunction and shoulder disability, which result from level IIb dissection. The main objective of this study was to evaluate the incidence of level IIb lymph node metastasis in clinically node-negative (cN0) oral squamous cell carcinoma (OSCC) patients. Patients presenting with cN0 OSCC between November 2012 and November 2023 were included retrospectively.

View Article and Find Full Text PDF

Diagnosis of lymph node metastasis in oral squamous cell carcinoma by an MRI-based deep learning model.

Oral Oncol

January 2025

Department of Oral and Maxillofacial Surgery, Guanghua School of Stomatology, Hospital of Stomatology, Sun Yat-sen University, Guangzhou, Guangdong, China; Guangdong Province Key Laboratory of Stomatology, Guangzhou, Guangdong, China. Electronic address:

Background: Cervical lymph node metastasis (LNM) is a well-established poor prognosticator of oral squamous cell carcinoma (OSCC), in which occult metastasis is a subtype that makes prediction challenging. Here, we developed and validated a deep learning (DL) model using magnetic resonance imaging (MRI) for the identification of LNM in OSCC patients.

Methods: This retrospective diagnostic study developed a three-stage DL model by 45,664 preoperative MRI images from 723 patients in 10 Chinese hospitals between January 2015 and October 2020.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!