Biomarker Value of miR-221 and miR-222 as Potential Substrates in the Differential Diagnosis of Papillary Thyroid Cancer Based on Data Synthesis and Bioinformatics Approach

Advances and challenges in thyroid cancer: The interplay of genetic modulators, targeted therapies, and AI-driven approaches

Thyroid cancer continues to exhibit a rising incidence globally, predominantly affecting women. Despite stable mortality rates, the unique characteristics of thyroid carcinoma warrant a distinct approach. Differentiated thyroid cancer, comprising most cases, is effectively managed through standard treatments such as thyroidectomy and radioiodine therapy. However, rarer variants, including anaplastic thyroid carcinoma, necessitate specialized interventions, often employing targeted therapies. Although these drugs focus on symptom management, they are not curative. This review delves into the fundamental modulators of thyroid cancers, encompassing genetic, epigenetic, and non-coding RNA factors while exploring their intricate interplay and influence. Epigenetic modifications directly affect the expression of causal genes, while long non-coding RNAs impact the function and expression of micro-RNAs, culminating in tumorigenesis. Additionally, this article provides a concise overview of the advantages and disadvantages associated with pharmacological and non-pharmacological therapeutic interventions in thyroid cancer. Furthermore, with technological advancements, integrating modern software and computing into healthcare and medical practices has become increasingly prevalent. Artificial intelligence and machine learning techniques hold the potential to predict treatment outcomes, analyze data, and develop personalized therapeutic approaches catering to patient specificity. In thyroid cancer, cutting-edge machine learning and deep learning technologies analyze factors such as ultrasonography results for tumor textures and biopsy samples from fine needle aspirations, paving the way for a more accurate and effective therapeutic landscape in the near future.

Effective Use of microRNA, BRAF and Sonographic Risk Assessment in Bethesda III Thyroid Nodules Requires a Different Approach to Nodules with Features of Nuclear Atypia and Other Types of Atypia

The aim of the study was to analyze the diagnostic usefulness of the combined assessment of the ultrasound risk category of the nodule (evaluated with EU-TIRADS system), the presence of BRAF V600E mutation and the expression of selected microRNAs (miR-146b, miR-221 and miR-222) in Bethesda category III thyroid nodules, separately for cases with nuclear atypia (AUS-nuclear) and cases with other types of atypia (AUS-other). We evaluated 161 nodules (66 AUS-nuclear and 95 AUS-other) with known results of postoperative histopathological examination. The rate of cancer and the rate of PTC among cancers were nearly three times higher in the AUS-nuclear than the AUS-other group. For AUS-nuclear nodules, the most effective diagnostic panel included, in addition to repeat FNA, the assessment of BRAF V600E mutation and the expression of miR-146b and miR-222 (sensitivity: 93.5%, specificity: 80.0%). For AUS-other nodules, a two-step procedure was most effective: at the first stage, forgoing surgical treatment in subjects with a benign repeat FNA outcome, and, at the second stage, the assessment of miR-222 expression and the EU-TIRADS category (sensitivity: 92.3%, specificity: 76.8%). The optimal use of molecular methods in the diagnostics of category III thyroid nodules requires a separate approach for nodules with nuclear atypia and nodules with other types of atypia.

New biomarkers: prospect for diagnosis and monitoring of thyroid disease

After the metabolic syndrome and its components, thyroid disorders represent the most common endocrine disorders, with increasing prevalence in the last two decades. Thyroid dysfunctions are distinguished by hyperthyroidism, hypothyroidism, or inflammation (thyroiditis) of the thyroid gland, in addition to the presence of thyroid nodules that can be benign or malignant. Thyroid cancer is typically detected via an ultrasound (US)-guided fine-needle aspiration biopsy (FNAB) and cytological examination of the specimen. This approach has significant limitations due to the small sample size and inability to characterize follicular lesions adequately. Due to the rapid advancement of high-throughput molecular biology techniques, it is now possible to identify new biomarkers for thyroid neoplasms that can supplement traditional imaging modalities in postoperative surveillance and aid in the preoperative cytology examination of indeterminate or follicular lesions. Here, we review current knowledge regarding biomarkers that have been reliable in detecting thyroid neoplasms, making them valuable tools for assessing the efficacy of surgical procedures or adjunctive treatment after surgery. We are particularly interested in providing an up-to-date and systematic review of emerging biomarkers, such as mRNA and non-coding RNAs, that can potentially detect thyroid neoplasms in clinical settings. We discuss evidence for miRNA, lncRNA and circRNA dysregulation in several thyroid neoplasms and assess their potential for use as diagnostic and prognostic biomarkers.

The clinical implications of circulating microRNAs as potential biomarkers in screening oral squamous cell carcinoma

Background

Recent studies have highlighted the biomarker role of circulating miRNAs in oral squamous cell carcinoma (OSCC), indicating their potential application as early diagnostic markers for OSCC. However, the diagnostic results have proven inconclusive. This study was conducted to evaluate the diagnostic value of circulating miRNAs for OSCC diagnosis.

Methods

Eligible published studies were identified by a literature search carried out in several databases by using combinations of keywords associated with OSCC, circulating miRNAs, and diagnosis. The bivariate meta-analysis model was adopted to summarize the pooled parameters. Afterwards, we thoroughly explored the sources of heterogeneity after evaluating the risk of bias.

Results

A total of 60 studies focusing on 41 circulating miRNAs were included. The pooled sensitivity, specificity, and AUC were 0.75 (95%CI: 0.69-0.80), 0.76 (0.70-0.81), 0.82 (0.79-0.85), respectively. Subgroup analyses showed that miRNA combinations were more accurate than single miRNAs. Additionally, plasma may be a better matrix for miRNAs assays in OSCC diagnosis as the plasma-based miRNA assay had a higher level of diagnostic accuracy than serum-based miRNA assay. Subgroup analyses also suggested that using circulating miRNAs for OSCC diagnosis is more effective in Caucasians than in Asian ethnic groups. Finally, circulating miRNA assays based on large sample sizes have superior diagnostic accuracy than small sample sizes.

Conclusion

Circulating miRNAs might be applied as effective surrogate biomarkers for early diagnosis of OSCC. Nevertheless, future larger-scale prospective studies should be performed to enhance the diagnostic efficiency and investigate the miRNA combinations with more pronounced accuracy.

Thyroid Cancer Persistence in Patients with Unreliable Thyroglobulin Measurement: Circulating microRNA as Candidate Alternative Biomarkers

BACKGROUND

We aimed to evaluate the role of circulating miRNAs as a biomarker of the persistence of papillary thyroid cancer (PTC) in patients with an "uninformative" thyroglobulin (Tg) measurement.

METHODS

We prospectively enrolled 49 consecutive PTC patients with Tg-positive antibodies (TgAb) who had undergone a (near)-total thyroidectomy and ¹³¹I therapy (RIT). The serum thyroid stimulating hormone (TSH), Tg, and TgAb levels were measured before and at 6 and 12 months after RIT, respectively. The serum miRNA (221, 222, 375, 155, and 146b) levels were measured simultaneously.

RESULTS

The response to the initial therapy was assessed according to the 2015 ATA criteria. A decrease in 50% or more of serum miRNA over time was observed in 41/49 PTC patients, who showed an excellent response (ER), but six and two patients were classified to have an indeterminate/incomplete biochemical or incomplete structural response to initial therapy.

CONCLUSION

Serum miRNA kinetics emerge as a promising biomarker for the early detection of a persistent disease in PTC patients with uninformative Tg results.

Expression Profile and Diagnostic Significance of MicroRNAs in Papillary Thyroid Cancer

The incidence of papillary thyroid cancer (PTC) has increased in recent years. To improve the diagnostic management of PTC, we propose the use of microRNAs (miRNAs) as a biomarker. Our aim in this study was to evaluate the miRNA expression pattern in PTC using NanoString technology. We identified ten miRNAs deregulated in PTC compared with reference tissue: miR-146b-5p, miR-221-3p, miR-221-5p, miR-34-5p, miR-551b-3p, miR-152-3p, miR-15a-5p, miR-31-5p, and miR-7-5p (FDR < 0.05; |fold change (FC)| ≥ 1.5). The gene ontology (GO) analysis of differentially expressed miRNA (DEM) target genes identified the predominant involvement of epidermal growth factor receptor (EGFR), tyrosine kinase inhibitor resistance, and pathways in cancer in PTC. The highest area under the receiver operating characteristic (ROC) curve (AUC) for DEMs was found for miR-146-5p (AUC = 0.770) expression, indicating possible clinical applicability in PTC diagnosis. The combination of four miRNAs (miR-152-3p, miR-221-3p, miR-551b-3p, and miR-7-5p) showed an AUC of 0.841. Validation by real-time quantitative polymerase chain reactions (qRT-PCRs) confirmed our findings. The introduction of an miRNA diagnostic panel based on the results of our study may help to improve therapeutic decision making for questionable cases. The use of miRNAs as biomarkers of PTC may become an aspect of personalized medicine.

Immune-and Metabolism-Associated Molecular Classification of Ovarian Cancer

Ovarian cancer (OV) is a complex gynecological disease, and its molecular characteristics are not clear. In this study, the molecular characteristics of OV subtypes based on metabolic genes were explored through the comprehensive analysis of genomic data. A set of transcriptome data of 2752 known metabolic genes was used as a seed for performing non negative matrix factorization (NMF) clustering. Three subtypes of OV (C1, C2 and C3) were found in analysis. The proportion of various immune cells in C1 was higher than that in C2 and C3 subtypes. The expression level of immune checkpoint genes TNFRSF9 in C1 was higher than that of other subtypes. The activation scores of cell cycle, RTK-RAS, Wnt and angiogenesis pathway and ESTIMATE immune scores in C1 group were higher than those in C2 and C3 groups. In the validation set, grade was significantly correlated with OV subtype C1. Functional analysis showed that the extracellular matrix related items in C1 subtype were significantly different from other subtypes. Drug sensitivity analysis showed that C2 subtype was more sensitive to immunotherapy. Survival analysis of differential genes showed that the expression of PXDN and CXCL11 was significantly correlated with survival. The results of tissue microarray immunohistochemistry showed that the expression of PXDN was significantly correlated with tumor size and pathological grade. Based on the genomics of metabolic genes, a new OV typing method was developed, which improved our understanding of the molecular characteristics of human OV.