AI Article Synopsis

  • The 5-year survival rate for oral squamous cell carcinomas (SCC), including tongue SCC, has remained stagnant over recent decades, emphasizing the need for better predictive measures for early-stage disorders.
  • A study performed transcriptomic analysis on samples from patients with oral potentially malignant disorders (OPMD) and SCC, revealing greater molecular changes in SCCs and shared alterations that indicate a progression toward malignancy.
  • Findings suggest categorizing OPMDs and SCCs into specific subclasses for better patient prognosis and treatment options, and identified a gene set that could potentially predict which OPMDs may develop into SCC in the future.

Article Abstract

The 5-year survival rate for patients with oral squamous cell carcinomas (SCC), including tongue SCC, has not significantly improved over the last several decades. Oral potentially malignant disorders (OPMD), including oral dysplasias, are oral epithelial disorders that can develop into oral SCCs. To identify molecular characteristics that might predict conversion of OPMDs to SCCs and guide treatment plans, we performed global transcriptomic analysis of human tongue OPMD (n = 9) and tongue SCC (n = 11) samples with paired normal margin tissue from patients treated at Weill Cornell Medicine. Compared to margin tissue, SCCs showed more transcript changes than OPMDs. OPMDs and SCCs shared some altered transcripts, but these changes were generally greater in SCCs than OPMDs. Both OPMDs and SCCs showed altered signaling pathways related to cell migration, basement membrane disruption, and metastasis. We suggest that OPMDs are on the path toward malignant transformation. Based on patterns of gene expression, both OPMD and tongue SCC samples can be categorized into subclasses (mesenchymal, classical, basal, and atypical) similar to those seen in human head and neck SCC (HNSCC). These subclasses of OPMDs have the potential to be used to stratify patient prognoses and therapeutic options for tongue OPMDs. Lastly, we identified a gene set (ELF5; RPTN; IGSF10; CRMP1; HTR3A) whose transcript changes have the power to classify OPMDs and SCCs and developed a Firth logistic regression model using the changes in these transcripts relative to paired normal tissue to validate pathological diagnosis and potentially predict the likelihood of an OPMD developing into SCC, as data sets become available.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9950315PMC
http://dx.doi.org/10.1007/s12672-023-00629-yDOI Listing

Publication Analysis

Top Keywords

opmds sccs
16
tongue scc
12
opmds
9
transcriptomic analysis
8
human tongue
8
paired normal
8
margin tissue
8
transcript changes
8
opmds opmds
8
sccs
7

Similar Publications

Article Synopsis
  • The 5-year survival rate for oral squamous cell carcinomas (SCC), including tongue SCC, has remained stagnant over recent decades, emphasizing the need for better predictive measures for early-stage disorders.
  • A study performed transcriptomic analysis on samples from patients with oral potentially malignant disorders (OPMD) and SCC, revealing greater molecular changes in SCCs and shared alterations that indicate a progression toward malignancy.
  • Findings suggest categorizing OPMDs and SCCs into specific subclasses for better patient prognosis and treatment options, and identified a gene set that could potentially predict which OPMDs may develop into SCC in the future.
View Article and Find Full Text PDF

Oral cancer is a public health problem worldwide with approximately 300,000 new cases diagnosed every year and more than 170,000 deaths annually. Squamous cell carcinoma (SCC) accounts for approximately 90% of all oral malignancies and it is frequently preceded by lesions known as oral potentially malignant disorders (OPMDs). Screening programs for early detection of oral lesions have been conducted.

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!