Transcriptomic analysis predicts the risk of progression of premalignant lesions in human tongue.

TitleTranscriptomic analysis predicts the risk of progression of premalignant lesions in human tongue.
Publication TypeJournal Article
Year of Publication2023
AuthorsZhang T, Kutler D, Scognamiglio T, Gudas LJ, Tang X-H
JournalDiscov Oncol
Volume14
Issue1
Pagination24
Date Published2023 Feb 23
ISSN2730-6011
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 (nā€‰=ā€‰9) and tongue SCC (nā€‰=ā€‰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.

DOI10.1007/s12672-023-00629-y
Alternate JournalDiscov Oncol
PubMed ID36820942
PubMed Central IDPMC9950315
Grant ListR01 CA205258 / CA / NCI NIH HHS / United States
R01 CA205258 / CA / NCI NIH HHS / United States