Identification of latent biomarkers in connection with progression and prognosis in oral cancer by comprehensive bioinformatics analysis

Inflammatory Stimulation Upregulates the Receptor Transporter Protein 4 (RTP4) in SIM-A9 Microglial Cells

The receptor transporter protein 4 (RTP4) is a receptor chaperone protein that targets class A G-protein coupled receptor (GPCR)s. Recently, it has been found to play a role in peripheral inflammatory regulation, as one of the interferon-stimulated genes (ISGs). However, the detailed role of RTP4 in response to inflammatory stress in the central nervous system has not yet been fully understood. While we have previously examined the role of RTP4 in the brain, particularly in neuronal cells, this study focuses on its role in microglial cells, immunoreactive cells in the brain that are involved in inflammation. For this, we examined the changes in the RTP4 levels in the microglial cells after exposure to inflammatory stress. We found that lipopolysaccharide (LPS) treatment (0.1~1 µg/mL, 24 h) significantly upregulated the RTP4 mRNA levels in the microglial cell line, SIM-A9. Furthermore, the interferon (IFN)-β mRNA levels and extracellular levels of IFN-β were also increased by LPS treatment. This upregulation was reversed by treatment with neutralizing antibodies targeting either the interferon receptor (IFNR) or toll-like receptor 4 (TLR4), and with a TLR4 selective inhibitor, or a Janus kinase (JAK) inhibitor. On the other hand, the mitogen-activated protein kinase kinase (MEK) inhibitor, U0126, significantly enhanced the increase in RTP4 mRNA following LPS treatment, whereas the PKC inhibitor, calphostin C, had no effect. These findings suggest that in microglial cells, LPS-induced inflammatory stress activates TLR4, leading to the production of type I IFN, the activation of IFN receptor and JAK, and finally, the induction of RTP4 gene expression. Based on these results, we speculate that RTP4 functions as an inflammation-responsive molecule in the brain. However, further research is needed to fully understand its role.

Unraveling IFI44L's biofunction in human disease

Interferon-induced protein 44-like (IFI44L) is regarded as an immune-related gene and is a member of interferon-stimulated genes (ISGs). They participate in network transduction, and its own epigenetic modifications, apoptosis, cell-matrix formation, and many other pathways in tumors, autoimmune diseases, and viral infections. The current review provides a comprehensive overview of the onset and biological mechanisms of IFI44L and its potential clinical applications in malignant tumors and non-neoplastic diseases.

Establishment of prognosis model of hepatocellular carcinoma based on prognosis related gene analysis and study on gene regulation mechanism of model

Objective

To analyze the expression and mechanism of prognosis related differentially expressed genes (DEGs) in hepatocellular carcinoma (HCC), and establish a prognosis risk model of prognosis related DEGs.

Methods

Transcriptome data and clinical information of 374 HCC samples were downloaded from TCGA data. Kaplan-Meier (KM) survival analysis screened prognostic genes in DEGs. Protein-protein interaction (PPI) network was constructed based on prognostic genes and key genes were screened. Cox regression was used to analyze the key genes and construct the prognostic risk model, calculate the risk score of each patient, divide the patients into low-risk group and high-risk group according to the median risk value, use KM analysis method for survival analysis and draw the survival curve, and use receiver operating characteristic (ROC) curve to evaluate the prognostic risk model, The relationship between risk score and clinicopathological features of HCC patients was analyzed. GEPIA and the human protein atlas (HPA) databases were used for expression verification of model genes. The mirDIP database is used to analyze the regulatory network of model genes. GSCAlite platform is used to analyze the mechanism and drug sensitivity of model genes.

Results

A total of 1987 DEGs were extracted from the transcriptome data of HCC and normal samples, of which 258 were related to the prognosis of HCC (P < 0.01). Six key genes (CDK1, CCNA2, BUB1, CDC20, CCNB1 and TOP2A) were screened from the PPI network based on prognostic related genes, and the prognostic risk model was established. Survival analysis showed that the overall survival rate of patients in the high-risk group was significantly lower than that in the low-risk group (P < 0.01). The AUC values of 1, 3 and 5 years in the prognostic risk model were 0.716, 0.678 and 0.633. Multivariate Cox regression analysis showed that patient age and patient risk score were independent risk factors for the prognosis of HCC. The model gene is highly expressed in HCC and can promote apoptosis, cell cycle and EMT pathway. In addition, the high expression of model gene produced drug resistance to trametinib, selumetinib and RDEA119 (refametinib).

Conclusion

The prognostic risk model based on six prognostic related DEGs is an independent prognostic factor of HCC, which can effectively predict the survival and prognosis of HCC patients.

Identification of RTP4 facilitating ovarian cancer by bioinformatics analysis and experimental validation

Ovarian cancer (OV) is the most malignant gynecological tumor in women, with poor prognosis and high mortality rate. This study aims to identify hub genes in OV and explore the role of Receptor transporter 4 (RTP4) in OV progression. Common differentially expressed genes (DEGs) were screened from two microarray datasets. GO and KEGG enrichment analysis were performed. Protein-protein interaction (PPI) network was constructed by STING. Kaplan-Meier plotter was used to analyze prognosis. The effect of target gene on immune infiltration was analyzed by TIMER. The proliferation, migration, and invasion of OV cells were measured by CCK-8, wound healing assay, and trans-well assay, respectively. A total of 293 common DEGs were selected from GSE12470 and GSE16709 datasets. Hub genes, EPCAM, KIFC1, RTP4, TAGLN, and ZFP36 were selected by PPI network. Kaplan-Meier plotter demonstrated that high expression of RTP4 was related to low overall survival in OV patients. The TIMER result showed that high expression of RTP4 promoted immune infiltration of CD8+ T cells, B cells, neutrophils, and dendritic cells in OV. Moreover, silencing RTP4 significantly inhibited the proliferation, migration, and invasion of OV cells. RTP4 was associated with the poor prognosis in OV. In summary, silencing RTP4 inhibited the proliferation, migration, and invasion of OV cells, having the potential to be a novel therapeutic target for OV.

Ethanol extract of Vanilla planifolia stems reduces PAK6 expression and induces cell death in glioblastoma cells

Glioblastoma multiforme (GBM) is a malignant tumour with a poor prognosis. Therefore, potential treatment strategies and novel therapeutic targets have gained increased attention. Our data showed that the ethanol extract of Vanilla planifolia stem (VAS) significantly decreased the viability and the colony formation of GBM cells. Moreover, VAS induced the cleavage of MAP1LC3, a marker of autophagy. Further RNA-seq and bioinformatic analysis revealed 4248 differentially expressed genes (DEGs) between VAS-treated GBM cells and the control cells. Protein-protein interactions between DEGs with fold changes less than -3 and more than 5 were further analysed, and we found that 16 and 9 hub DEGs, respectively, were correlated with other DEGs. Further qPCR experiments confirmed that 14 hub DEGs was significantly downregulated and 9 hub DEGs was significantly upregulated. In addition, another significantly downregulated DEG, p21-activated kinase 6 (PAK6), was correlated with the overall survival of GBM patients. Further validation experiments confirmed that VAS significantly reduced the mRNA and protein expression of PAK6, which led to the abolition of cell viability and colony formation. These findings demonstrated that VAS reduced cell viability, suppressed colony formation and induced autophagy and revealed PAK6 and other DEGs as potential therapeutic targets for GBM treatment.

Leveraging technology-driven strategies to untangle omics big data: circumventing roadblocks in clinical facets of oral cancer

Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, owing to its extreme degree of invasiveness and aggressive inclination. The early occurrences of this cancer can be clinically deceiving leading to a poor overall survival rate. The primary concerns from a clinical perspective include delayed diagnosis, rapid disease progression, resistance to various chemotherapeutic regimens, and aggressive metastasis, which collectively pose a substantial threat to prognosis. Conventional clinical practices observed since antiquity no longer offer the best possible options to circumvent these roadblocks. The world of current cancer research has been revolutionized with the advent of state-of-the-art technology-driven strategies that offer a ray of hope in confronting said challenges by highlighting the crucial underlying molecular mechanisms and drivers. In recent years, bioinformatics and Machine Learning (ML) techniques have enhanced the possibility of early detection, evaluation of prognosis, and individualization of therapy. This review elaborates on the application of the aforesaid techniques in unraveling potential hints from omics big data to address the complexities existing in various clinical facets of oral cancer. The first section demonstrates the utilization of omics data and ML to disentangle the impediments related to diagnosis. This includes the application of technology-based strategies to optimize early detection, classification, and staging via uncovering biomarkers and molecular signatures. Furthermore, breakthrough concepts such as salivaomics-driven non-invasive biomarker discovery and omics-complemented surgical interventions are articulated in detail. In the following part, the identification of novel disease-specific targets alongside potential therapeutic agents to confront oral cancer via omics-based methodologies is presented. Additionally, a special emphasis is placed on drug resistance, precision medicine, and drug repurposing. In the final section, we discuss the research approaches oriented toward unveiling the prognostic biomarkers and constructing prediction models to capture the metastatic potential of the tumors. Overall, we intend to provide a bird's eye view of the various omics, bioinformatics, and ML approaches currently being used in oral cancer research through relevant case studies.

Role of miR-21 in the diagnosis of colorectal cancer: Meta-analysis and bioinformatics

Advanced colorectal cancer (CRC) has a bad prognosis and is challenging to cure. Therefore, there is an urgent need for an effective early diagnosis marker. MicroRNA-21 (miR-21) regulates the expression of multiple cancer target genes. The objective of this study was to assess the diagnostic role of miR-21 in CRC.A meta-analysis of PubMed, Cochrane Library, EMBASE, and Web of Science databases was performed with a carefully designed search strategy to identify records related to the diagnostic role of miR-21 in CRC. TCGA data was used to search for different microRNAs in colorectal cancer samples and surrounding tissues. In addition, potential target genes for miR-21 were predicted and evaluated by functional analysis. We conducted a meta-analysis for 10 studies, including 728 blood samples of patients with CRC and 472 healthy controls. The combined sensitivity and specificity of miR-21 to diagnose colorectal cancer were 0.79 (95% CI: 0.67-0.87) and 0.92 (95% CI: 0.85-0.96), respectively. The combined positive likelihood ratio (PLR) was 10.20 (95% CI: 4.8-21.5), the combined negative likelihood ratio (NLR) was 0.23 (95% CI: 0.14-0.37), the diagnostic odds ratio (DOR) was 45.00 (95% CI:15-132), the area under the summary receiver operating characteristic curve (SROC) for the included studies was 0.93(95%CI: 0.91-0.95). Simultaneously, TCGA data showed that miR-21 was a differential microRNA in colorectal cancer tissues and adjacent tissues, and it was an up-regulated gene. After verification by three databases, 48 target genes of miR-21 were obtained. Through GO enrichment analysis, it was found that the target genes were mainly distributed in the fiber center, the molecular function was mainly focused on cytokine receptor binding, and the biological process was mainly focused on ubiquitin-dependent protein catabolism mediated by the proteasome. KEGG pathway analysis showed that the target genes were mainly distributed in tumor pathways.

The Clinical Significance and Role of CXCL1 Chemokine in Gastrointestinal Cancers

One area of cancer research is the interaction between cancer cells and immune cells, in which chemokines play a vital role. Despite this, a comprehensive summary of the involvement of C-X-C motif ligand 1 (CXCL1) chemokine (also known as growth-regulated gene-α (GRO-α), melanoma growth-stimulatory activity (MGSA)) in cancer processes is lacking. To address this gap, this review provides a detailed analysis of CXCL1's role in gastrointestinal cancers, including head and neck cancer, esophageal cancer, gastric cancer, liver cancer (hepatocellular carcinoma (HCC)), cholangiocarcinoma, pancreatic cancer (pancreatic ductal adenocarcinoma), and colorectal cancer (colon cancer and rectal cancer). This paper presents the impact of CXCL1 on various molecular cancer processes, such as cancer cell proliferation, migration, and invasion, lymph node metastasis, angiogenesis, recruitment to the tumor microenvironment, and its effect on immune system cells, such as tumor-associated neutrophils (TAN), regulatory T (T_reg) cells, myeloid-derived suppressor cells (MDSCs), and macrophages. Furthermore, this review discusses the association of CXCL1 with clinical aspects of gastrointestinal cancers, including its correlation with tumor size, cancer grade, tumor-node-metastasis (TNM) stage, and patient prognosis. This paper concludes by exploring CXCL1's potential as a therapeutic target in anticancer therapy.

RTP4, a Biomarker Associated with Diagnosing Pulmonary Tuberculosis and Pan-Cancer Analysis

Background

Pulmonary tuberculosis (PTB) is a global epidemic of infectious disease; the purpose of our study was to explore new potential biomarkers for the diagnosis of pulmonary tuberculosis and to use the biomarkers for further pan-cancer analysis.

Methods

Four microarray gene expression sets were downloaded from the GEO public databases and conducted for further analysis. Healthy control (HC) samples and samples of pulmonary tuberculosis (PTB) were calculated with enrichment scores in folate biosynthesis pathways. The scores acted as a new phenotype combined with clinical information (control or PTB) for subsequent analysis. Weight gene coexpression network analysis (WGCNA) was used to seek the modules mostly related to PTB and folate biosynthesis in training sets. Twenty-nine coexistence genes were screened by intersecting the genes in the green-yellow module of GSE28623 and the brown module of GSE83456. We used the protein-protein interaction network analysis to narrow the gene range to search for hub genes. Then, we downloaded the unified and standardized pan-cancer data set from the UCSC database for correlations between biomarkers and prognosis and tumor stage differences.

Results

Eventually, RTP4 was selected as a biomarker. To verify the reliability of this biomarker, an area under the ROC (AUC) was calculated in gene sets (GSE28623, GSE83456, and GSE34608). Lastly, to explore the difference in RTP4 expression before and after antituberculosis treatment, the GSE31348 gene set was enrolled to compare the expressions in weeks 0 and 26. The results showed significant differences between these two time points (p < 0.001). RTP4 was significantly upregulated in the pulmonary tuberculosis group compared to the healthy control group in three gene sets and downregulated after antituberculosis therapy in one gene set. These results suggest that RTP4 can be used as a potential biomarker in diagnosing tuberculosis. The results of pan-cancer analysis showed that high expression of RTP4 in 4 tumor types was positively correlated with poor prognosis and high expression of RTP4 in 6 tumor types was negatively correlated with poor prognosis. We found significant differences in the expression of the RTP4 gene at different stages in 5 types of tumors.

Conclusion

RTP4 might be a new potential biomarker for diagnosing pulmonary tuberculosis.

DDX60 selectively reduces translation off viral type II internal ribosome entry sites

Co-opting host cell protein synthesis is a hallmark of many virus infections. In response, certain host defense proteins limit mRNA translation globally, albeit at the cost of the host cell's own protein synthesis. Here, we describe an interferon-stimulated helicase, DDX60, that decreases translation from viral internal ribosome entry sites (IRESs). DDX60 acts selectively on type II IRESs of encephalomyocarditis virus (EMCV) and foot and mouth disease virus (FMDV), but not by other IRES types or by 5' cap. Correspondingly, DDX60 reduces EMCV and FMDV (type II IRES) replication, but not that of poliovirus or bovine enterovirus 1 (BEV-1; type I IRES). Furthermore, replacing the IRES of poliovirus with a type II IRES is sufficient for DDX60 to inhibit viral replication. Finally, DDX60 selectively modulates the amount of translating ribosomes on viral and in vitro transcribed type II IRES mRNAs, but not 5' capped mRNA. Our study identifies a novel facet in the repertoire of interferon-stimulated effector genes, the selective downregulation of translation from viral type II IRES elements.

An oxidative stress-related prognostic signature for indicating the immune status of oral squamous cell carcinoma and guiding clinical treatment

Oral squamous cell carcinoma (OSCC) is the eighth most common cancer worldwide and presents high mortality. Oxidative stress, caused by reactive oxygen species accumulation, plays a crucial role in tumorigenesis, cancer progression, and drug resistance. Nevertheless, the specific prognostic and clinical values of oxidative stress-related genes (OSGs) in OSCC remain unclear. Here, we developed an oxidative stress-related prognostic signature according to mRNA expression data from The Cancer Genome Atlas (TCGA) database and evaluated its connections with the prognosis, clinical features, immune status, immunotherapy, and drug sensitivity of OSCC through a series of bioinformatics analyses. Finally, we filtered out six prognostic OSGs to construct a prognostic signature. On the basis of both TCGA-OSCC and GSE41613 cohorts, the signature was proven to be an independent prognostic factor with high accuracy and was confirmed to be an impactful indicator for predicting the prognosis and immune status of patients with OSCC. Additionally, we found that patients with high-risk scores may obtain greater benefit from immune checkpoint therapy compared to those with low-risk scores, and the risk score presented a close interaction with the tumor microenvironment and chemotherapy sensitivity. The prognostic signature may provide a valid and robust predictive tool that could predict the prognosis and immune status and guide clinicians to develop personalized therapeutic strategies for patients with OSCC.

Prognostic biomarker IL17A correlated with immune infiltrates in head and neck cancer

Background

The underlying functions and mechanisms of the Th17 pathway in Head and neck squamous cell carcinoma (HNSCC) progression and tumor immunology are still unclear. We investigated the correlation between IL17A expression and certain clinical parameters, tumor-infiltrating immune cells (TIICs) in TCGA HNSCC samples.

Methods

HNSCC files from the TCGA database were analyzed to obtain data on immune system infiltrates, gene expression, and related clinical information. R (Version 3.6.3) software, GEPIA, and TIMER online analysis tools were used to profile the relationship between the expression of IL17A and the prognosis, clinical stages, survival status and immune cell tumor-infiltrating levels of HNSCC patients. GEPIA and TIMER online analysis tools were used to verify the data.

Results

The expression of IL17A was significantly decreased in tumor tissues from HNSCC. IL17A expression was associated with M, N stage, lymphovascular invasion, and patients OS event. GSEA revealed that IL17A was closely related to humoral immune response, T cells response, and cytokine signal. TCGA database and TIMER online analysis indicated that the B cells and T cells levels were correlated with IL17A. The correlation between IL17A expression and correlated genes was analyzed.

Conclusions

IL-17A plays a key role in HNSCC. The levels of IL17A are important values for the determination of the occurrence and development of the HNSCC. The IL17A and correlated genes may be potential immunotherapeutic targets for HNSCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02703-1.

MicroRNA-155 expression is associated with pulpitis progression by targeting SHIP1

BACKGROUND

Pulpitis is a commonly seen oral inflammation condition in clinical practice, it can cause much pain for the patient and may induce infections in other systems. Much is still unknown for the pathogenic mechanism of pulpitis. In this work, we discovered that the expression of miR-155 was associated with dental pulpal inflammation both in vivo and in vitro.

METHODS AND RESULTS

Our experiments of LPS stimulated odontoblast cell line MDPC-23 showed miR-155 could act as a positive regulator by increasing the production of pro-inflammatory cytokines IL-1β and IL-6 during inflammatory responses, whereas knockdown of miR-155 can reverse the effects. Bioinformatics analysis demonstrated that SHIP1 is a direct target of miR-155 in odontoblasts, this result was further verified at both mRNA and protein level. Inhibition of miR-155 resulted in the downregulation of inflammation factors, while co-transfection of si-SHIP1 and miR-155 inhibitor promoted the inflammatory responses. Treatment with miR-155 mimic or si-SHIP1 up-regulated the protein level of p-PI3K and p-AKT. By contrast, miR-155 inhibitor exerted the opposite effects. miR-155 mimics could upregulate the gene expression of IL-1β and IL-6. Co-transfection of LY294002 and miR-155 mimic attenuated the inflammatory responses. Consistent with in vitro results, miR-155^-/- mice could alleviate inflammatory response, as well as decrease the activation of p-PI3K and p-AKT, whereas increase the activation of SHIP1.

CONCLUSIONS

Our data revealed a novel role for miR-155 in regulation of dental pulpal inflammatory response by targeting SHIP1 through PI3K/AKT signaling pathway.

Construction of miRNA-lncRNA-mRNA co-expression network affecting EMT-mediated cisplatin resistance in ovarian cancer

Platinum resistance is one of the major concerns in ovarian cancer treatment. Recent evidence shows the critical role of epithelial-mesenchymal transition (EMT) in this resistance. Epithelial-like ovarian cancer cells show decreased sensitivity to cisplatin after cisplatin treatment. Our study prospected the association between epithelial phenotype and response to cisplatin in ovarian cancer. Microarray dataset GSE47856 was acquired from the GEO database. After identifying differentially expressed genes (DEGs) between epithelial-like and mesenchymal-like cells, the module identification analysis was performed using weighted gene co-expression network analysis (WGCNA). The gene ontology (GO) and pathway analyses of the most considerable modules were performed. The protein-protein interaction network was also constructed. The hub genes were specified using Cytoscape plugins MCODE and cytoHubba, followed by the survival analysis and data validation. Finally, the co-expression of miRNA-lncRNA-TF with the hub genes was reconstructed. The co-expression network analysis suggests 20 modules relating to the Epithelial phenotype. The antiquewhite4, brown and darkmagenta modules are the most significant non-preserved modules in the Epithelial phenotype and contain the most differentially expressed genes. GO, and KEGG pathway enrichment analyses on these modules divulge that these genes were primarily enriched in the focal adhesion, DNA replication pathways and stress response processes. ROC curve and overall survival rate analysis show that the co-expression pattern of the brown module's hub genes could be a potential prognostic biomarker for ovarian cancer cisplatin resistance.

Establishment of prognostic risk model and drug sensitivity based on prognostic related genes of esophageal cancer

At present, the treatment of esophageal cancer (EC) is mainly surgical and drug treatment. However, due to drug resistance, these therapies can not effectively improve the prognosis of patients with the EC. Therefore, a multigene prognostic risk scoring system was constructed by bioinformatics analysis method to provide a theoretical basis for the prognosis and treatment decision of EC. The gene expression profiles and clinical data of esophageal cancer patients were gathered from the Cancer Genome Atlas TCGA database, and the differentially expressed genes (DEGs) were screened by R software. Genes with prognostic value were screened by Kaplan Meier analysis, followed by functional enrichment analysis. A cox regression model was used to construct the prognostic risk score model of DEGs. ROC curve and survival curve were utilized to evaluate the performance of the model. Univariate and multivariate Cox regression analysis was used to evaluate whether the model has an independent prognostic value. Network tool mirdip was used to find miRNAs that may regulate risk genes, and Cytoscape software was used to construct gene miRNA regulatory network. GSCA platform is used to analyze the relationship between gene expression and drug sensitivity. 41 DEGs related to prognosis were pre-liminarily screened by survival analysis. A prognostic risk scoring model composed of 8 DEGs (APOA2, COX6A2, CLCNKB, BHLHA15, HIST1H1E, FABP3, UBE2C and ERO1B) was built by Cox regression analysis. In this model, the prognosis of the high-risk score group was poor (P < 0.001). The ROC curve showed that (AUC = 0.862) the model had a good performance in predicting prognosis. In Cox regression analysis, the comprehensive risk score can be employed as an independent prognostic factor of the EC. HIST1H1E, UBE2C and ERO1B interacted with differentially expressed miRNAs. High expression of HIST1H1E was resistant to trametinib, selumetinib, RDEA119, docetaxel and 17-AAG, High expression of UBE2C was resistant to masitinib, and Low expression of ERO1B made the EC more sensitive to FK866. We constructed an EC risk score model composed of 8 DEGs and gene resistance analysis, which can provide reference for prognosis prediction, diagnosis and treatment of the EC patients.

The role of postoperative radiotherapy in pN1 oral cavity cancer without extranodal extension

Background

The administration of postoperative radiotherapy remains controversial in pN1 oral cavity cancer patients without extranodal extension. The aim is to determine whether postoperative radiotherapy reduces the neck recurrence rate and improves the survival outcomes of pN1 patients.

Methods

This study consecutively enrolled 1056 patients with newly diagnosed oral squamous cell carcinoma who underwent tumor wide excision and neck dissection from September 2002 to November 2019. One hundred two pN1 patients without extranodal extension were eligible for analysis. Then, a subgroup analysis of 40 patients was performed after patients with other adverse risk factors (positive margins, close margins, lymphovascular invasion, perineural invasion, tumor depth ≥ 10 mm, and poor histological differentiation) were excluded.

Results

Of the 102 eligible pN1 patients, 26 patients received surgery alone, and 76 received postoperative radiotherapy. No significant differences were observed in the neck recurrence rate (7.7% vs. 15.8%, p = 0.30). Similarly, in patients without other adverse risk factors, no significant differences were observed in the neck recurrence rate (5% vs. 20%, p = 0.15) between surgery alone group and postoperative radiotherapy group. Moreover, no significant difference was found in the neck recurrence-free survival rate, overall survival, and disease-specific survival (77.1% vs. 52.5%, p = 0.42, 83.5% vs. 64.5%, p = 0.81, and 88.2% vs. 67.9%, p = 0.34, respectively).

Conclusion

Postoperative radiotherapy did not significantly decrease the probability of neck recurrence and survival outcomes in pN1 patients without extranodal extension. Radical surgery alone may be considered sufficient treatment for pN1 patients without other adverse risk factors.