A growing number of long non-coding RNAs (lncRNAs) have been linked to squamous cell carcinoma of the head and neck (SCCHN). A subclass of lncRNAs, termed enhancer RNAs (eRNAs), are derived from enhancer regions and could contribute to enhancer function. In this study, we developed an integrated data analysis approach to identify key eRNAs in SCCHN. Tissue-specific enhancer-derived RNAs and their regulated genes previously predicted using the computational pipeline PreSTIGE, were considered as putative eRNA-target pairs. The interactive web servers, TANRIC (the Atlas of Noncoding RNAs in Cancer) and cBioPortal, were used to explore the RNA levels and clinical data from the Cancer Genome Atlas (TCGA) project. Requiring that key eRNAs should show significant associations with overall survival (Kaplan–Meier log-rank test, p < 0.05) and the predicted target (correlation coefficient r > 0.4, p < 0.001), we identified five key eRNA candidates. The most significant survival-associated eRNA was AP001056.1 with ICOSLG encoding an immune checkpoint protein as its regulated target. Another 1640 genes also showed significant correlation with AP001056.1 (r > 0.4, p < 0.001), with the “immune system process” being the most significantly enriched biological process (adjusted p < 0.001). Our results suggest that AP001056.1 is a key immune-related eRNA in SCCHN with a positive impact on clinical outcome.

Transfer-RNA-derived fragments (tRFs) are a class of small non-coding RNAs that are functionally different from their parental transfer RNAs (tRNAs). tRFs can regulate gene expression by several mechanisms, and are involved in a variety of pathological processes. Here, we aimed at understanding the composition and abundance of tRFs in squamous cell carcinoma of the head and neck (SCCHN), and evaluated the potential of tRFs as prognostic markers in this cancer type. We obtained tRF expression data from The Cancer Genome Atlas (TCGA) HNSC cohort (523 patients) using MINTbase v2.0, and correlated to available TCGA clinical data. RNA-binding proteins were predicted according to the calculated Position Weight Matrix (PWM) score from the RNA-Binding Protein DataBase (RBPDB). A total of 10,158 tRFs were retrieved and a high diversity in expression levels was seen. Fifteen tRFs were found to be significantly associated with overall survival (Kaplan-Meier survival analysis, log rank test p-value < 0.01). The top prognostic marker, tRF-20-S998LO9D (p < 0.001), was further measured in tumor and tumor-free samples from 16 patients with squamous cell carcinoma of the oral tongue and 12 healthy controls, and was significantly upregulated in tumor compared to matched tumor-free tongue (p < 0.001). Results suggest that tRFs are useful prognostic markers in SCCHN.

Human cells are subjected to continuous challenges by different genotoxic stress attacks. DNA damage leads to erroneous mutations, which can alter the function of oncogenes or tumor suppressors, resulting in cancer development. To circumvent this, cells activate the DNA damage response (DDR), which mainly involves cell cycle regulation and DNA repair processes. The tumor suppressor p53 plays a pivotal role in the DDR by halting the cell cycle and facilitating the DNA repair processes. Various pathways and factors participating in the detection and repair of DNA have been described, including scores of RNA-binding proteins (RBPs) and RNAs. It has become increasingly clear that p53’s role is multitasking, and p53 mRNA regulation plays a prominent part in the DDR. This review is aimed at covering the p53 RNA metabolism linked to the DDR and highlights the recent findings.

DNA and RNA binding proteins (DRBPs) are a broad class of molecules that regulate numerous cellular processes across all living organisms, creating intricate dynamic multilevel networks to control nucleotide metabolism and gene expression. These interactions are highly regulated, and dysregulation contributes to the development of a variety of diseases, including cancer. An increasing number of proteins with DNA and/or RNA binding activities have been identified in recent years, and it is important to understand how their activities are related to the molecular mechanisms of cancer. In addition, many of these proteins have overlapping functions, and it is therefore essential to analyze not only the loss of function of individual factors, but also to group abnormalities into specific types of activities in regard to particular cancer types. In this review, we summarize the classes of DNA-binding, RNA-binding, and DRBPs, drawing particular attention to the similarities and differences between these protein classes. We also perform a cross-search analysis of relevant protein databases, together with our own pipeline, to identify DRBPs involved in cancer. We discuss the most common DRBPs and how they are related to specific cancers, reviewing their biochemical, molecular biological, and cellular properties to highlight their functions and potential as targets for treatment.

Oral cancers are surrounded by epithelium that histologically might seem normal, but genetically has aberrations. In patients with squamous cell carcinoma of the oral tongue (SCCOT), it is therefore important to study not only the tumor but also the clinically tumor-free contralateral tongue tissue that remains in the patient after treatment to map changes of prognostic and/or diagnostic value. The transporter associated with antigen processing (TAP) dimer is a key factor in the process of activating cytotoxic T cells. By downregulating the expression of TAP, tumor cells can escape cytotoxic T cell recognition. Biopsies from tumor and clinically tumor-free contralateral tongue tissue in 21 patients with SCCOT were analyzed together with tongue biopsies from 14 healthy individuals, which served as the control group. Dividing patients into TAP1-high and TAP1-low groups according to the median TAP1 level in tumor-free samples showed that patients with lower TAP1 mRNA levels in tumor-free samples had better overall (p = 0.003) and disease-free survival (p = 0.002). The results showing that TAP1 levels in tumor-free tongue tissue contralateral to the SCCOT correlate with survival is an important contribution to early diagnosis and follow up of SCCOT.

Squamous cell carcinoma of the oral tongue (SCCOT) represents an aggressive malignancy characterized by high metastatic potential and significant heterogeneity in its tumor microenvironment. The tumor‐stroma ratio (TSR) has emerged as a prognostic biomarker, with higher stromal content frequently correlating with worse survival outcomes. Traditional approaches using the standard 50% TSR cutoff may not be optimal for SCCOT, and visual TSR estimation introduces variability during TSR region annotation. This study aimed to develop and validate a dedicated TSR estimation model for SCCOT by incorporating representative TSR regions from the invasive tumor front of whole slide images and to determine the optimal TSR threshold for prognostic stratification. Using hematoxylin and eosin‐stained images from The Cancer Genome Atlas as a discovery cohort and whole slide images from Norrland's University Hospital Umea, Sweden (NUS) as a validation cohort, we developed a computational model to estimate TSR. The model demonstrated a high correlation with pathologist‐based TSR estimation in both discovery (R = 0.848, p < 0.01) and validation (R = 0.783, p < 0.01) cohorts. The optimal 55% cutoff identified by the model improved prognostic accuracy over the traditional 50% threshold, with patients having high stroma within the tumor invasive front showing worse overall (log‐rank p = 0.006) and disease‐specific (log‐rank p = 0.016) survival. Our computational TSR model for SCCOT demonstrates that automated TSR estimation enhances prognostic accuracy at an optimal cutoff of 55%, contributing to more precise risk stratification and potentially enabling personalized treatment strategies in SCCOT management.