A Novel Role for the Soluble Isoform of CTLA-4 in Normal, Dysplastic and Neoplastic Oral and Oropharyngeal Epithelia.
Prarthna ClareFarah Al-FatyanBadri RishehKristine S Roberts Nee NellanyFrank James WardRasha Abu-EidPublished in: Cancers (2023)
Background : Head and neck cancer (HNC) has a high mortality rate, with late diagnosis remaining the most important factor affecting patient survival. Therefore, it is imperative to identify markers that aid in early detection and prediction of disease progression. HNCs evade the immune system by different mechanisms, including immune checkpoints. Cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) is an immune checkpoint receptor that downregulates anti-tumour immune responses, with evidence of involvement in HNC. The less studied, alternatively spliced, soluble isoform (sCTLA-4) also plays an immunosuppressive role that contributes to immune escape. We quantified sCTLA-4 in normal, potentially malignant, and malignant oral and oropharyngeal tissues to elucidate any role in tumourigenesis and identify its potential as a biomarker for diagnosis and patient stratification. Methods: Normal, low- and high-grade epithelial dysplasia, and squamous cell carcinoma oral and oropharyngeal biopsies were selectively stained for sCTLA-4 and quantified using the image analysis software QuPath. Results: Distinct sCTLA-4 staining patterns were observed, in which normal epithelial sCTLA-4 expression correlated with keratinocyte differentiation, while disrupted expression, both in intensity and localisation, was observed in dysplastic and neoplastic tissues. Conclusions: Our data indicate an additional, previously unknown role for sCTLA-4 in epithelial cell differentiation and proliferation. Furthermore, our findings suggest the potential of sCTLA-4 as a biomarker for predicting disease progression and patient stratification for targeted HNC therapies.
Keyphrases
- squamous cell carcinoma
- immune response
- high grade
- case report
- poor prognosis
- gene expression
- radiation therapy
- coronary artery disease
- type diabetes
- machine learning
- binding protein
- inflammatory response
- risk factors
- low grade
- cardiovascular disease
- climate change
- signaling pathway
- big data
- free survival
- deep learning
- artificial intelligence
- cardiovascular events