CCL2/CCR2 axis promotes perineural invasion of salivary adenoid cystic carcinoma via ITGß5-mediated nerve-tumor interaction.

Perineural invasion (PNI) is a notorious feature of salivary adenoid cystic carcinoma (SACC) and other neurotropic tumors. The pathogenesis of PNI that involves the molecular communication between the tumor and the suffered nerve is elusive. The in vitro co-culture assays of SACC cells with dorsal root ganglia (DRG) or neural cells showed that nerve-derived CCL2 activated CCR2 expression in SACC cells, promoting the proliferation, adhesion, migration, and invasion of SACC cells via the ERK1/2/ITGß5 pathway. Meanwhile, SACC-derived exosomes delivered ITGß5 to promote the neurite outgrowth of neural cells or DRG. Blocking of CCL2/CCR2 axis or ITGß5 inhibited the PNI of SACC cells in models in vitro by 3D co-culture of DRG with SACC cells and in vivo by xenografting SACC cells onto the murine sciatic nerve. High levels of ITGß5 in tissues or plasma exosomes were significantly correlated with CCL2 and CCR2 expression in the tissues and associated with PNI and poor prognosis of SACC cases. Our findings revealed a novel reciprocal loop between neural and tumor cells driven by the CCL2/CCR2 axis and exosomal ITGß5 during PNI of SACC. The present study may provide a prospective diagnostic and anti-PNI treatment strategy for SACC patients via targeting the nerve-tumor interactions.

RGIE: A Gene Selection Method Related to Radiotherapy Resistance in Head and Neck Squamous Cell Carcinoma.

BACKGROUND: Head and Neck Squamous Cell Carcinoma (HNSCC) is a malignant tumor with a high degree of malignancy, invasiveness, and metastasis rate. Radiotherapy, as an important adjuvant therapy for HNSCC, can reduce the postoperative recurrence rate and improve the survival rate. Identifying the genes related to HNSCC radiotherapy resistance (HNSCC-RR) is helpful in the search for potential therapeutic targets. However, identifying radiotherapy resistance-related genes from tens of thousands of genes is a challenging task. While interactions between genes are important for elucidating complex biological processes, the large number of genes makes the computation of gene interactions infeasible. METHODS: We propose a gene selection algorithm, RGIE, which is based on ReliefF, Gene Network Inference with Ensemble of Trees (GENIE3) and Feature Elimination. ReliefF was used to select a feature subset that is discriminative for HNSCC-RR, GENIE3 constructed a gene regulatory network based on this subset to analyze the regulatory relationship among genes, and feature elimination was used to remove redundant and noisy features. RESULTS: Nine genes (SPAG1, FIGN, NUBPL, CHMP5, TCF7L2, COQ10B, BSDC1, ZFPM1, GRPEL1) were identified and used to identify HNSCC-RR, which achieved performances of 0.9730, 0.9679, 0.9767, and 0.9885 in terms of accuracy, precision, recall, and AUC, respectively. Finally, qRT-PCR validated the differential expression of the nine signature genes in cell lines (SCC9, SCC9-RR). CONCLUSION: RGIE is effective in screening genes related to HNSCC-RR. This approach may help guide clinical treatment modalities for patients and develop potential treatments.

The development of radioresistant oral squamous carcinoma cell lines and identification of radiotherapy-related biomarkers.

BACKGROUND: In the treatment of oral squamous cell carcinoma (OSCC), radiation resistance remains an important obstacle to patient outcomes. Progress in understanding the molecular mechanisms of radioresistance has been limited by research models that do not fully recapitulate the biological features of solid tumors. In this study, we aimed to develop novel in vitro models to investigate the underlying basis of radioresistance in OSCC and to identify novel biomarkers. METHODS: Parental OSCC cells (SCC9 and CAL27) were repeatedly exposed to ionizing radiation to develop isogenic radioresistant cell lines. We characterized the phenotypic differences between the parental and radioresistant cell lines. RNA sequencing was used to identify differentially expressed genes (DEGs), and bioinformatics analysis identified candidate molecules that may be related to OSCC radiotherapy. RESULTS: Two isogenic radioresistant cell lines for OSCC were successfully established. The radioresistant cells displayed a radioresistant phenotype when compared to the parental cells. Two hundred and sixty DEGs were co-expressed in SCC9-RR and CAL27-RR, and thirty-eight DEGs were upregulated or downregulated in both cell lines. The associations between the overall survival (OS) of OSCC patients and the identified genes were analyzed using data from the Cancer Genome Atlas (TCGA) database. A total of six candidate genes (KCNJ2, CLEC18C, P3H3, PIK3R3, SERPINE1, and TMC8) were closely associated with prognosis. CONCLUSION: This study demonstrated the utility of constructing isogenic cell models to investigate the molecular changes associated with radioresistance. Six genes were identified based on the data from the radioresistant cells that may be potential targets in the treatment of OSCC.

Construction of a combined hypoxia and EMT index for head and neck squamous cell carcinoma.

Objectives: In head and neck squamous cell carcinoma (HNSCC), the interaction between epithelial-mesenchymal transformation (EMT) and hypoxia has been confirmed, and corresponding treatment methods have been investigated. Few studies have examined its combined effects and its potential clinical use, however. As a result, we developed a new scoring system based on EMT and hypoxia. Methods: We combined 200 hypoxia-related genes with 1184 EMT-related genes and finally constructed a score risk model containing 14 characteristic factors named the comprehensive index of EMT and hypoxia (CIEH) by the Lasso-Cox regression and univariate Cox regression method, which is used to predict prognosis and to guide treatment planning in HNSCC patients. Furthermore, we examined HNSCC expression of CIEH-related genes using the human protein atlas database. Results: Based on survival analysis results, CIEH value had a high prognostic value in HNSCC patients, a high CIEH value carries a poor prognostic significance in HNSCC. It is noteworthy that the CIEH value was correlated with tumor immune infiltration. Moreover, the CIEH had significant differences in age, stage, N, laterality, and peripheral nerve invasion, and that the CIEH could be an independent prognostic factor. Conclusions: This study constructed a CIEH model containing 14 characteristic factors, including hypoxia-related genes and EMT genes, that may be able to serve as potential biomarkers for HNSCC. According to the 14 characteristic factors in the CIEH model, a diagnostic kit can be packaged in the future to evaluate the survival of patients before tumor surgery and guide the subsequent treatment plan.

LINC01123 promotes immune escape by sponging miR-214-3p to regulate B7-H3 in head and neck squamous-cell carcinoma.

Numerous studies have shown that long noncoding RNAs (LncRNAs) are involved in the development and immune escape of head and neck squamous-cell carcinoma (HNSCC). However, the specific regulatory mechanisms by which LINC01123 regulates HNSCC and its correlation with immunity remain unclear. Therefore, this study's primary purpose was to explore the mechanisms by which LINC01123 regulates the immune escape and progression of HNSCC. This study confirmed that LINC01123 is competitively bound to miR-214-3p, and miR-214-3p specifically targets B7-H3. The effects of LINC01123, B7-H3, and miR-214-3p on tumor progression, CD8+T-cell-mediated immune response, and the tumorigenicity of HNSCC in vitro and in vivo were examined through the downregulation or upregulation of LINC01123, B7-H3, and miR-214-3p. Our results indicated that LINC01123 and B7-H3 were highly expressed in HNSCC and are associated with poor prognosis in patients. Notably, overexpression of LINC01123 or B7-H3 or downregulation of miR-214-3p inhibited the function of CD8+T cells and promoted the progression of HNSCC. Therefore, LINC01123 acts as a miR-214-3p sponge to inhibit the activation of CD8+T cells and promote the progression of HNSCC by upregulating B7-H3.