BackgroundEndoscopic thyroidectomy and robotic thyroidectomy are effective and safe surgical options for thyroid surgery, with excellent cosmetic outcomes. However, in regard to lateral neck dissection (LND), much effort is required to alleviate cervical disfigurement derived from a long incision. Technologic innovations have allowed for endoscopic LND, without the need for extended cervical incisions and providing access to remote sites, including axillary, chest–breast, face-lift, transoral, and hybrid approaches.MethodsA comprehensive review of published literature was performed using the search terms “lateral neck dissection”, “thyroid”, and “endoscopy OR endoscopic OR endoscope OR robotic” in PubMed.ResultsThis review provides an overview of the current knowledge regarding endoscopic LND, and it specifically addresses the following points: 1) the surgical procedure, 2) the indications and contraindications, 3) the complications and surgical outcomes, and 4) the technical advantages and limitations. Robotic LND, totally endoscopic LND, and endoscope-assisted LND are separately discussed.ConclusionsEndoscopic LND is a feasible and safe technique in terms of complete resection of the selected neck levels, complications, and cosmetic outcomes. However, it is recommended to strictly select criteria when expanding the population of eligible patients. A formal indication for endoscopic LND has not yet been established. Thus, a well-designed, multicenter study with a large cohort is necessary to confirm the feasibility, long-term outcomes, oncological safety, and influence of endoscopic LND on patient quality of life (QoL).

Background: Distant metastasis (DM) is not common in differentiated thyroid cancer (DTC). However, it is associated with a significantly poor prognosis. Early detection of high-risk DTC patients is difficult, and the molecular mechanism is still unclear. Therefore, the present study aims to establish a novel predictive model based on clinicopathological parameters and DM-related gene signatures to provide guidelines for clinicians in decision making. Methods: Weighted gene co-expression network analysis (WGCNA) was performed to discover coexpressed gene modules and hub genes associated with DM. Univariate and multivariate analyses were carried out to identify independent clinicopathological risk factors based on The Cancer Genome Atlas (TCGA) database. An integrated nomogram prediction model was established. Finally, real hub genes were validated using the GSE60542 database and various thyroid cell lines. Results: The midnightblue module was most significantly positively correlated with DM (R=0.56, P=9e-06) by as per WGCNA. DLX5 (AUC: 0.769), COX6B2 (AUC: 0.764), and LYPD1 (AUC: 0.760) were determined to be the real hub genes that play a crucial role in predicting DM. Meanwhile, univariate and multivariate analyses demonstrated that T-stage (OR, 15.03; 95% CI, 1.75-319.40; and P=0.024), histologic subtype (OR, 0.17; 95% CI, 0.03-0.92; and P=0.042) were the independent predictors of DM. Subsequently, a nomogram model was constructed based on gene signatures and independent clinical risk factors exhibited good performance. Additionally, the mRNA expressions of real hub genes in the GSE60542 dataset were consistent with TCGA.Conclusions: The present study has provided a reliable model to predict DM in patients with DTC. This model is likely to serve as an individual risk assessment tool in therapeutic decision-making.

BackgroundThis study assessed the safety and oncologic outcomes of robotic thyroidectomy via the bilateral axillary breast approach (BABA RT) for conventional open procedures. The learning curves of BABA RT were further evaluated.MethodsAn exact 1:1 matching analysis was performed to compare the technical safety and oncologic outcomes between robotic thyroidectomy and conventional open surgery. Learning curves were assessed using cumulative summation analysis.ResultsThere was no significant difference in general characteristics, short time outcomes (including transient hypoparathyroidism, transient postoperative hoarseness, hematoma/seroma, mean postoperative hospital stay, and other complications), the number of retrieved central lymph nodes, and recurrence rates between robotic BABA and conventional groups. The mean number of retrieved lateral LNs in the robotic group was significantly less than those in the conventional group. The learning curve for working space making, robotic lobectomy, and total thyroidectomy are approximately 15, 30, and 20 cases, respectively. No differences except for operation time were found between the learning group and the proficient group.ConclusionsRobotic thyroidectomy and neck dissection via BABA are feasible in terms of surgical completeness, surgical safety, and oncological safety. Our results provide a criterion for judging whether the surgeon has entered the stable stage of robotic thyroidectomy via BABA in terms of the operative time.

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Emerging evidence has indicated that N6-methylandenosine (m6A) RNA methylation plays a critical role in cancer development. However, the function of m6A RNA methylation-related long noncoding RNAs (m6A-lncRNAs) in papillary thyroid carcinoma (PTC) has never been reported. This study aimed to investigate the role of m6A-lncRNAs in the prognosis and tumor microenvironment (TME) of PTC. Three subgroups (clusters 1, 2, and 3) were identified by consensus clustering of 19 prognosis-related m6A-lncRNA regulators, of which cluster 1 is preferentially related to unfavorable prognosis, lower immune scores, and distinct immune infiltrate level. A risk-score model was established based on 8 prognosis-related m6A-lncRNAs. Patients with a high-risk score showed a worse prognosis, and the ROC indicated a reliable prediction performance for patients with PTC (AUC = 0.802). As expected, the immune scores, the infiltration levels of immune cells, and ESTIMATE scores in the low-risk subgroups were notably higher (p < 0.001) when compared with those in high-risk subgroups. Furthermore, GSEA analysis revealed that tumor associated pathways, hallmarks, and biological processes were remarkably enriched in the high-risk subgroup. Further analysis indicated that the risk score and age were independent prognostic factors for PTC. An integrated nomogram was constructed that accurately predicted the survival status (AUC = 0.963). Moreover, a lncRNA–miRNA–mRNA regulated network was established based on seven prognosis-related m6A-lncRNAs. In addition, 30 clinical samples and different PTC cells were validated. This is the first study to reveal that m6A-lncRNAs plays a vital role in the prognosis and TME of PTC. To a certain degree, m6A-lncRNAs can be considered as new, promising prognostic biomarkers and treatment targets.