MicroRNA-Based Risk Score for Predicting Tumor Progression Following Radioactive Iodine Ablation in Well-Differentiated Thyroid Cancer Patients: A Propensity-Score Matched Analysis.

To identify molecular markers that can accurately predict aggressive tumor behavior at the time of surgery, a propensity-matching score analysis of archived specimens yielded two similar datasets of DTC patients (with and without RAI). Bioinformatically selected microRNAs were quantified by qRT-PCR. The risk score was generated using Cox regression and assessed using ROC, C-statistic, and Brier-score. A predictive Bayesian nomogram was established. External validation was performed, and causal network analysis was generated. Within the eight-year follow-up period, progression was reported in 51.5% of cases; of these, 48.6% had the T1a/b stage. Analysis showed upregulation of miR-221-3p and miR-222-3p and downregulation of miR-204-5p in 68 paired cancer tissues (p < 0.001). These three miRNAs were not differentially expressed in RAI and non-RAI groups. The ATA risk score showed poor discriminative ability (AUC = 0.518, p = 0.80). In contrast, the microRNA-based risk score showed high accuracy in predicting tumor progression in the whole cohorts (median = 1.87 vs. 0.39, AUC = 0.944) and RAI group (2.23 vs. 0.37, AUC = 0.979) at the cutoff >0.86 (92.6% accuracy, 88.6% sensitivity, 97% specificity) in the whole cohorts (C-statistics = 0.943/Brier = 0.083) and RAI subgroup (C-statistic = 0.978/Brier = 0.049). The high-score group had a three-fold increased progression risk (hazard ratio = 2.71, 95%CI = 1.86-3.96, p < 0.001) and shorter survival times (17.3 vs. 70.79 months, p < 0.001). Our prognostic microRNA signature and nomogram showed excellent predictive accuracy for progression-free survival in DTC.

Diagnostic and Prognostic Performance of Liquid Biopsy-Derived Exosomal MicroRNAs in Thyroid Cancer Patients: A Systematic Review and Meta-Analysis.

Circulatory tumor-derived exosomal microRNAs (miRNAs) play key roles in cancer development/progression. We aimed to assess the diagnostic/prognostic value of circulating exosomal miRNA in thyroid cancer (TC). A search in PubMed, Scopus, Web of Science, and Science Direct up to 22 May 2021 was performed. The true/false positive (TP/FP) and true/false negative (TN/FN) rates were extracted from each eligible study to obtain the pooled sensitivity, specificity, positive/negative likelihood ratios (PLR/NLR), diagnostic odds ratio (DOR), and their 95% confidence intervals (95%CIs). The meta-analysis included 12 articles consisting of 1164 Asian patients and 540 controls. All miRNAs were quantified using qRT-PCR assays. The pooled sensitivity was 82% (95%CI = 77-86%), pooled specificity was 76% (95%CI = 71-80%), and pooled DOR was 13.6 (95%CI = 8.8-21.8). The best biomarkers with high sensitivity were miR-16-2-3p (94%), miR-223-5p (91%), miR-130a-3p (90%), and miR182-5p (94%). Similarly, they showed high specificity, in addition to miR-34c-5p. Six panels of two to four exosomal miRNAs showed higher diagnostic values with an area under the curve (AUC) ranging from 0.906 to 0.981. The best discriminative ability to differentiate between cancer and non-cancer individuals was observed for miR-146b-5p + miR-223-5p + miR-182-5p (AUC = 0.981, sensitivity = 93.8% (84.9-98.3), specificity = 92.9% (76.5-99.1)). In conclusion, the expression levels of exosomal miRNAs could predict TC.

Site-Specific Metastasis and Survival in Papillary Thyroid Cancer: The Importance of Brain and Multi-Organ Disease.

Introduction-heterogeneity in clinical outcomes and survival was observed in patients with papillary thyroid cancer (PTC) and distant metastases. Here, we investigated the effect of distant metastases sites on survival in PTC patients. Methods-patients with a diagnosis of PTC and known metastases were identified using the Surveillance, Epidemiology, and End Results database (1975-2016). Univariate and multivariate Cox regression analyses were performed to analyze the effect of distant metastases sites on thyroid cancer-specific survival (TCSS) and overall survival (OS). Results-from 89,694 PTC patients, 1819 (2%) developed distant metastasis at the initial diagnosis, of whom 26.3% presented with the multiple-organ disease. The most common metastatic sites were lung (53.4%), followed by bone (28.1%), liver (8.3%), and brain (4.7%). In metastatic patients, thyroid cancer-specific death accounted for 73.2%. Kaplan-Meier curves showed decreased OS in patients with metastases to the brain (median OS = 5 months) and liver (median OS = 6 months) compared to lung (median OS = 10 months) and bone (median OS = 23 months). Moreover, multiple organ metastasis had a higher mortality rate (67.4%) compared to single organ metastasis (51.2%, p < 0.001). Using multivariate analysis, risk factors that significantly influence TCSS and OS were male gender (HR = 1.86, 95% CI = 1.17-2.94, p < 0.001, and HR = 1.90, 95% CI = 1.40-2.57, p = 0.009), higher tumor grade (HR = 7.31, 95% CI = 2.13-25.0, p < 0.001 and HR = 4.76, 95% CI = 3.93-5.76, p < 0.001), multiple organ involvement (HR = 6.52, 95% CI = 1.50-28.39, p = 0.026 and HR = 5.08, 95% CI = 1.21-21.30, p = 0.013), and brain metastasis (HR = 1.82, 95% CI = 1.15-2.89, p < 0.001 and HR = 4.21, 95% CI = 2.20-8.07, p = 0.010). Conclusion-the pattern of distant metastatic organ involvement was associated with variability in OS in PTC. Multi-organ metastasis and brain involvement are associated with lower survival rates in PTC. Knowledge of the patterns of distant metastasis is crucial to personalize the treatment and follow-up strategies.

Hidden in plain sight: The effects of BCG vaccination in the COVID-19 pandemic.

To investigate the relationship between Bacille Calmette-Guérin (BCG) vaccination and SARS-CoV-2 by a bioinformatics approach, two datasets for the SARS-CoV-2 infection group and BCG-vaccinated group were downloaded. Differentially Expressed Genes were identified. Gene ontology and pathways were functionally enriched, and networking was constructed in NetworkAnalyst. Lastly, the correlation between post-BCG vaccination and COVID-19 transcriptome signatures was established. A total of 161 DEGs (113 upregulated DEGs and 48 downregulated genes) were identified in the SARS-CoV-2 group. In the pathway enrichment analysis, a cross-reference of upregulated Kyoto Encyclopedia of Genes and Genomes pathways in SARS-CoV-2 with downregulated counterparts in the BCG-vaccinated group, resulted in the intersection of 45 common pathways, accounting for 86.5% of SARS-CoV-2 upregulated pathways. Of these intersecting pathways, a vast majority were immune and inflammatory pathways with top significance in interleukin-17, tumor necrosis factor, NOD-like receptors, and nuclear factor-κB signaling pathways. Given the inverse relationship of the specific differentially expressed gene pathways highlighted in our results, the BCG-vaccine may play a protective role against COVID-19 by mounting a nonspecific immunological response and further investigation of this relationship is warranted.

A novel gene panel for prediction of lymph-node metastasis and recurrence in patients with thyroid cancer.

BACKGROUND: Although well-differentiated papillary thyroid cancer may remain indolent, lymph node metastases and the recurrence rates are approximately 50% and 20%, respectively. No current biomarkers are able to predict metastatic lymphadenopathy and recurrence in early stage papillary thyroid cancer. Hence, identifying prognostic biomarkers predicting cervical lymph-node metastases would prove very helpful in determining treatment. METHODS: The database of the Cancer Genome Atlas included 495 papillary thyroid cancer samples. Using this database, we developed a machine learning model to define a gene signature that could predict lymph-node metastasis (N0 or N1). Kruskal-Wallis tests, univariate and multivariate logistic and Cox regression models, and Kaplan-Meier analyses were performed to correlate the gene signature with clinical outcomes. RESULTS: We identified a panel of 25 genes and constructed a risk score that can differentiate N0 and N1 papillary thyroid cancer samples (P < .001) with a sensitivity of 86%, a specificity of 62%, a positive predictive value of 93%, and a negative predictive value of 42%. This panel represents an independent biomarker to predict metastatic lymphadenopathy (OR = 8.06, P < .001) specifically in patients with T1 lesions (OR = 7.65, P = .002) and disease-free survival (HR = 2.64, P = .043). CONCLUSION: This novel 25-gene panel may be used as a potential prognostic marker for accurately predicting lymph-node metastasis and disease-free survival in patients with early-stage papillary thyroid cancer.