Targeting DSG3: from pemphigus to squamous cell carcinoma

Transcriptomic analysis of the effects of the HPV18 E6E7 gene on the cell death mode in esophageal squamous cell carcinoma

Human papillomavirus (HPV) infection is one of the main causes of esophageal carcinoma (ESCA), and its carcinogenic mechanisms in ESCA require further investigation. E6 and E7 are HPV oncogenes, and their genomic integration is a crucial reason for the transformation of host cells into cancer cells. In order to reveal the role of oncogenes E6 and E7 in ESCA cells, the RNA-Seq raw data for HPV18-positive and -negative esophageal squamous cell carcinoma (ESCC) samples derived from the NCBI BioProject database were analyzed, and the differentially expressed genes were identified. Moreover, differentially expressed genes were enriched significantly in multiple cell death pathways, including apoptosis (cyclin-dependent kinase inhibitor 2A, plakophilin 1 and desmoglein 3), pyroptosis (gasdermin A, gasdermin C, NLR family pyrin domain containing 3, absent in melanoma 2, NLR family pyrin domain containing 1 and Toll like receptor 1) and autophagy (Unc-51 like autophagy activating kinase 1, adrenoceptor beta 2). Consequently, the effects of cisplatin-induced apoptosis and Hank's balanced salt solution-induced autophagy, and α-ketoglutarate-induced pyroptosis in the ESCC-expressing E6 and E7 cells were verified. Therefore, the expression of E6E7 may culminate in the inhibition of multiple cell death modes, which may also be one of the mechanisms of oncogene-induced carcinogenesis.

Characterization of Desmoglein 3 (DSG3) as a Sensitive and Specific Marker for Esophageal Squamous Cell Carcinoma

Although P40 and P63 are both sensitive and specific for routine esophageal squamous cell carcinoma (SCC) diagnosis, we recently showed that P40 and P63 immunoreactivities were significantly lower in well-differentiated SCC than those in higher grade tumors. Therefore, a novel esophageal SCC marker, ideally performing better in well-differentiated SCC, is still needed. We characterized desmoglein 3 (DSG3) immunohistochemistry in esophageal SCC, esophageal adenocarcinoma, small-cell lung carcinoma, and large B-cell lymphoma, alongside P40 and CK5/6. The World Health Organization classification was used to grade tumors as well-differentiated (WD), moderately differentiated (MD), or poorly differentiated (PD). There were 20 WD, 26 MD, and 17 PD components among 39 esophageal SCC cases. All esophageal SCC components showed significant DSG3 immunoreactivity (mean, 80%; range, 30%–100%), and the proportions of DSG3 immunoreactive cells were higher in the WD and MD components than in the PD components. No esophageal adenocarcinoma cases showed more than 10% DSG3 immunoreactivity with only weak cytoplasmic staining. With a 5% immunoreactivity cutoff, DSG3 positivity was 100% in all 63 SCC components, 18% in adenocarcinoma cases, and 0% in small-cell lung carcinoma or large B-cell lymphoma cases. The overall DSG3 specificity was 94%. To the best of our knowledge, this is the first study to characterize DSG3 as a sensitive and specific marker for esophageal SCC.

Tumor microenvironment in head and neck squamous cell carcinoma

The tumor microenvironment (TME) of head and neck squamous cell carcinoma (HNSCC) is comprised of cancer-associated fibroblasts (CAFs), immune cells, and other supporting cells. Genetic changes in the carcinoma cells, such as alterations to TP53, NOTCH1, and specific gene expression profiles, contribute to derangements in cancer and microenvironment cells such as increased ROS, overproduction of cytokines, and epithelial to mesenchymal transition (EMT). CAFs are among the most critical elements of the TME contributing to proliferation, invasion, and metastasis. The adaptive immune response is suppressed in HNSCC through overexpression of cytokines, triggered apoptosis of T cells, and alterations in antigen processing machinery. Overexpression of critical cytokines, such as transforming growth factor-β (TGF-β), contributes to EMT, immune suppression, and evolution of CAFs. Inflammation and hypoxia are driving forces in angiogenesis and altered metabolism. HNSCC utilizes glycolytic and oxidative metabolism to fuel tumorigenesis via coupled mechanisms between cancer cell regions and cells of the TME. Increased understanding of the TME in HNSCC illustrates that the long-held notion of "condemned mucosa" reflects a process that extends beyond the epithelial cells to the entire tissue comprised of each of these elements.

A poor prognosis subtype of HNSCC is consistently observed across methylome, transcriptome, and miRNome analysis

PURPOSE

Distant metastasis after treatment is observed in about 20% of squamous cell carcinoma of the head and neck (HNSCC). In the absence of any validated robust biomarker, patients at higher risk for metastasis cannot be provided with tailored therapy. To identify prognostic HNSCC molecular subgroups and potential biomarkers, we have conducted genome-wide integrated analysis of four omic sets of data.

EXPERIMENTAL DESIGN

Using state-of-the-art technologies, a core set of 45 metastasizing and 55 nonmetastasizing human papillomavirus (HPV)-unrelated HNSCC patient samples were analyzed at four different levels: gene expression (transcriptome), DNA methylation (methylome), DNA copy number (genome), and microRNA (miRNA) expression (miRNome). Molecular subgroups were identified by a model-based clustering analysis. Their clinical relevance was evaluated by survival analysis, and functional significance by pathway enrichment analysis.

RESULTS

Patient subgroups selected by transcriptome, methylome, or miRNome integrated analysis are associated with shorter metastasis-free survival (MFS). A common subgroup, R1, selected by all three omic approaches, is statistically more significantly associated with MFS than any of the single omic-selected subgroups. R1 and non-R1 samples display similar DNA copy number landscapes, but more frequent chromosomal aberrations are observed in the R1 cluster (especially loss at 13q14.2-3). R1 tumors are characterized by alterations of pathways involved in cell-cell adhesion, extracellular matrix (ECM), epithelial-to-mesenchymal transition (EMT), immune response, and apoptosis.

CONCLUSIONS

Integration of data across several omic profiles leads to better selection of patients at higher risk, identification of relevant molecular pathways of metastasis, and potential to discover biomarkers and drug targets.