The potential influence of long non-coding RNA PRKG1-AS1 on oral squamous cell carcinoma: A comprehensive study based on bioinformatics and in vitro validation

Noncoding RNAs in oral cancer

Oral cancer (OC) is the most prevalent subtype of cancer arising in the head and neck region. OC risk is mainly attributed to behavioral risk factors such as exposure to tobacco and excessive alcohol consumption, and a lesser extent to viral infections such as human papillomaviruses and Epstein-Barr viruses. In addition to these acquired risk factors, heritable genetic factors have shown to be associated with OC risk. Despite the high incidence, biomarkers for OC diagnosis are lacking and consequently, patients are often diagnosed in advanced stages. This delay in diagnosis is reflected by poor overall outcomes of OC patients, where 5-year overall survival is around 50%. Among the biomarkers proposed for cancer detection, noncoding RNA (ncRNA) can be considered as one of the most promising categories of biomarkers due to their role in virtually all cellular processes. Similar to other cancer types, changes in expressions of ncRNAs have been reported in OC and a number of ncRNAs have diagnostic, prognostic, and therapeutic potential. Moreover, some ncRNAs are capable of regulating gene expression by various mechanisms. Therefore, elucidating the current literature on the four main types of ncRNAs namely, microRNA, lncRNA, snoRNA, piwi-RNA, and circular RNA in the context of OC pathogenesis is timely and would enable further improvements and innovations in diagnosis, prognosis, and treatment of OC. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development.

Characterization of the m6A regulator-mediated methylation modification patterns in oral squamous cell carcinoma

N⁶-methyladenosine (m⁶A) is a form of posttranscriptional modification that plays important roles in cancer including oral squamous cell carcinoma (OSCC). Most studies to date have focused on a limited number of regulators and oncogenic pathways, thus failing to provide comprehensive insight into the dynamic effects of m⁶A modification. In addition, the role of m⁶A modification in shaping immune cell infiltration in OSCC has yet to be clarified. This study was designed to assess m⁶A modification dynamics in OSCC and to understand how such modifications influence clinical immunotherapeutic treatment outcomes. m⁶A modification patterns linked with 23 m⁶A regulators were analyzed in 437 OSCC patients from TCGA and GEO cohorts. These patterns were then quantified through m⁶A score based on algorithms derived from a principal component analysis (PCA) approach. The m⁶A modification patterns of OSCC samples were grouped into two clusters based on the m⁶A regulators expression, and immune cell infiltration was linked with the 5-year survival outcomes of patients in these clusters. 1575 genes associated with OSCC patient prognosis were identified and used to re-cluster these samples into two groups. Patients in clusters exhibiting higher levels of m⁶A regulator expression exhibited poorer overall survival (OS), whereas patients with high m⁶A scores survived for longer (p < 0.001). The overall mortality rates in the groups of patients with low and high m⁶A scores were 55% and 40%, respectively, and the m⁶A score distributions in clusters of patients grouped by m⁶A modification patterns and gene expression further supported the link between a high m⁶A score and better prognostic outcomes. Immunophenoscore (IPS) values for patients in different m⁶A score groups suggested that the use of PD-1-specific antibodies or CTLA-4 inhibitors alone or in combination would yield superior treatment outcomes in patients in the high-m⁶A score group relative to the low-m⁶A score group. m⁶A modification patterns are relevant to heterogeneity in OSCC. Detailed analyses of m⁶A modification patterns may thus offer novel insight regarding immune cell infiltration within the OSCC tumor microenvironment, guiding novel efforts to provide patients with more effective immunotherapeutic interventions.

The role of long noncoding RNAs as regulators of the epithelial–Mesenchymal transition process in oral squamous cell carcinoma cells

Oral squamous cell carcinoma (OSCC) is a highly invasive and relatively prevalent cancer, accounting for around 3% of all cancers diagnosed. OSCC is associated with bad outcomes, with only 50% overall survival (OS) after five years. The ability of OSCC to invade local and distant tissues relies on the induction of the epithelial–mesenchymal transition (EMT), wherein epithelial cells shed their polarity and cell-to-cell contacts and acquire mesenchymal characteristics. Consequently, a comprehensive understanding of how tumor cell EMT induction is regulated has the potential of direct attempts to prevent tumor progression and metastasis, resulting in better patient outcomes. Several recent studies have established the significance of particular long noncoding RNAs (lncRNAs) in the context of EMT induction. Moreover, lncRNAs regulate a vast array of oncogenic pathways. With a focus on the mechanisms by which the underlined lncRNAs shape the metastatic process and a discussion of their potential utility as clinical biomarkers or targets for therapeutic intervention in patients with OSCC, the present review thus provides an overview of the EMT-related lncRNAs that are dysregulated in OSCC.

Impact of Non-Coding RNAs on Chemotherapeutic Resistance in Oral Cancer

Drug resistance in oral cancer is one of the major problems in oral cancer therapy because therapeutic failure directly results in tumor recurrence and eventually in metastasis. Accumulating evidence has demonstrated the involvement of non-coding RNAs (ncRNAs), such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), in processes related to the development of drug resistance. A number of studies have shown that ncRNAs modulate gene expression at the transcriptional or translational level and regulate biological processes, such as epithelial-to-mesenchymal transition, apoptosis, DNA repair and drug efflux, which are tightly associated with drug resistance acquisition in many types of cancer. Interestingly, these ncRNAs are commonly detected in extracellular vesicles (EVs) and are known to be delivered into surrounding cells. This intercellular communication via EVs is currently considered to be important for acquired drug resistance. Here, we review the recent advances in the study of drug resistance in oral cancer by mainly focusing on the function of ncRNAs, since an increasing number of studies have suggested that ncRNAs could be therapeutic targets as well as biomarkers for cancer diagnosis.

Development of a lncRNA-based prognostic signature for oral squamous cell carcinoma

BACKGROUND

We aimed to establish a long noncoding RNA (lncRNA)-based signature for accurately predicting prognosis and guiding the personalized clinical management of oral squamous cell carcinoma (OSCC).

METHODS

OSCC RNA sequencing profiles were acquired from The Cancer Genome Atlas and Gene Expression Omnibus. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were performed to construct a lncRNA-based prognostic signature. Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curves and calibration curves were used to assess the effectiveness and accuracy of the signature. Additionally, we conducted single-sample gene-set enrichment analysis to infer the different degrees of immunocyte infiltration. Weighted correlation network analysis, enrichment analysis and Spearman's correlation analysis were implemented to screen immune-related genes that interact with the lncRNA signature.

RESULTS

In total, 14 lncRNAs were defined as potential prognostic biomarkers. Based on these lncRNAs, patients were divided into low- and high-risk subgroups with different survival times (p < 0.001). In addition, the reliability of the prognostic signature was verified by Kaplan-Meier analysis, ROC analysis and calibration curves. Patients in the low-risk group exhibited more significant immune cell infiltration. Simultaneously, a potential regulatory network consisting of 8 lncRNAs and 159 protein-coding genes in the top 10 immune-related biological process terms was constructed.

CONCLUSIONS

Our findings suggested that the 14-lncRNA signature has satisfactory performance in predicting the prognosis of OSCC, thereby providing new insights to the pathogenesis, clinical patient management and therapeutic intervention. The different immune cell infiltration statuses of OSCC patients may encourage immunotherapy.

Identification of hub lncRNAs in head and neck cancer based on weighted gene co-expression network analysis and experiments

Head and neck squamous cell carcinoma (HNSCC) ranks as the sixth most common cancer among systemic malignant tumors, with 600 000 new cases occurring every year worldwide. Since HNSCC has high heterogeneity and complex pathogenesis, no effective prognostic indicator has yet been identified. Here, we aimed to identify a lncRNA signature associated with the prognosis of HNSCC as a potential new biomarker. LncRNA expression data were downloaded from The Cancer Genome Atlas database. A polygenic risk score model was constructed by using Lasso-Cox regression analysis. Weighted gene co-expression network analysis (WGCNA) was applied to analyze the co-expression modules of lncRNAs associated with the prognosis of HNSCC. The robustness of the signature was validated in testing and external cohorts. Polymerase chain reaction was performed to detect the expression levels of identified lncRNAs in cancer and adjacent tissues. We constructed an 8-lncRNA signature (LINC00567, LINC00996, MTOR-AS1, PRKG1-AS1, RAB11B-AS1, RPS6KA2-AS1, SH3BP5-AS1, ZNF451-AS1) that could be used as an independent prognostic factor of HNSCC. The signature showed strong robustness and had stable prediction performance in different cohorts. WGCNA results showed that modules related to risk score mainly participated in biological processes such as blood vessel development, positive regulation of catabolic processes, and regulation of growth. The prognostic risk score model based on lncRNA for HNSCC may help clinicians conduct individualized treatment plans.

Dysregulation of FOXD2-AS1 promotes cell proliferation and migration and predicts poor prognosis in oral squamous cell carcinoma: a study based on TCGA data

FOXD2 adjacent opposite strand RNA 1 (FOXD2-AS1) plays an important role in the pathogenesis of some cancers. However, its functional role in oral squamous cell carcinoma (OSCC) remains largely unknown. In this study, we conducted expressional and functional analyses of FOXD2-AS1 using data from the Cancer Genome Atlas (TCGA) and in vitro OSCC assays. FOXD2-AS1 dysregulation was remarkably associated with radiation therapy, anatomic location, high histologic grade, and lymphovascular invasion (P < 0.05). A nomogram based on FOXD2-AS1 expression was constructed for use as a diagnostic indicator for OSCC patients, and multivariate cox regression analysis showed that FOXD2-AS1 expression was an independent prognostic factor for OSCC patients. KEGG, gene set enrichment analysis, and immune infiltration evaluations indicated that FOXD2-AS1 was involved in tumor progression via epithelial-to-mesenchymal transition and cell cycle regulation and was negatively associated with mast cell, DCs, iDCs, and B cells. FOXD2-AS1 silencing suppressed the proliferation and migration of Cal27 cells. Our findings showed that an aberrantly high FOXD2-AS1 expression predicts poor prognosis in OSCC; FOXD2-AS1 may act as an oncogenic protein by regulating cell proliferation and migration and may suppress adaptive immunity by modulating the number and function of antigen-presenting cells.