Significance of the BRAF mRNA Expression Level in Papillary Thyroid Carcinoma: An Analysis of The Cancer Genome Atlas Data

The Association between Lymphocytic Thyroiditis and Papillary Thyroid Cancer Harboring Mutant BRAF: A Systematic Review and Meta-Analysis

Background: Papillary thyroid cancer (PTC) and lymphocytic thyroiditis (LT) co-occur with a prevalence of about 30%. PTC harboring BRAFV600E (PTC-BRAF) confers a worse prognosis, but it is unclear if LT alters prognostic features and recurrence of PTC. Objective: We compared the prevalence of PTC-BRAF with and without LT. The risk of adverse pathological features in (i) PTC in the presence and absence of BRAF mutation, irrespective of LT status, was compared to (ii) PTC in the presence and absence of LT, irrespective of BRAF status. Methods: We searched PubMed, Embase, and Web of Science Core Collection for observational studies published from 2010 to June 2023 on adult patients with PTC. The search strategy yielded 47 studies with relevant data. Data of baseline characteristics, clinicopathological features, and the quality assessment tool were extracted by two reviewers. The study was registered with PROSPERO (CRD42023437492). Results: Of the 47 studies, 39 studies with a total cohort of 28 143, demonstrated that the odds of PTC-BRAF were significantly lower in the presence of LT compared to its absence (odds ratio [OR] 0.53, 95% confidence interval [CI]: 0.48-0.58, p < 0.00001). In PTC-BRAF patients, there was a positive association of central neck nodal disease (CNND), PTC > 1 cm, extra-thyroidal extension, American Joint Committee on Cancer (AJCC) Stage 3-4, and multifocality with pooled ORs of 1.54 (95% CI: 1.16-2.04), 1.14 (95% CI: 0.82-1.58), 1.66 (95% CI: 1.40-1.97), 1.53 (95% CI: 1.35-1.75), and 1.24 (95% CI: 1.11-1.40) respectively, compared to wild-type PTC, irrespective of LT status. In the same studies, PTC with LT patients had lower pooled ORs of 0.64 (95% CI: 0.51-0.81) for CNND, 0.83 (95% CI: 0.73-0.95) for PTC > 1 cm, 0.71 (95% CI: 0.58-0.86) for ETE, 0.84 (95% CI: 0.75-0.94) for AJCC Stage 3-4 compared to PTC without LT, irrespective of BRAF status. PTC recurrence was not affected by BRAF or LT, with pooled ORs of 1.12 (95% CI: 0.66-1.90, p = 0.67) and 0.60 (95% CI: 0.28-1.30, p = 0.20) respectively. Similar results were seen with recurrence expressed as hazard ratio in this limited data-set. Conclusion: The odds of PTC-BRAF are significantly lower in the presence of LT than without. PTC with LT, irrespective of BRAF status, was significantly associated with better prognostic factors. Further studies are required to evaluate if LT inhibits PTC-BRAF, and whether this is relevant to the role of immunotherapy in advanced thyroid cancer.

Uncovering key molecular mechanisms in the early and late-stage of papillary thyroid carcinoma using association rule mining algorithm

OBJECTIVE

Thyroid Cancer (TC) is the most frequent endocrine malignancy neoplasm. It is the sixth cause of cancer in women worldwide. The treatment process could be expedited by identifying the controlling molecular mechanisms at the early and late stages, which can contribute to the acceleration of treatment schemes and the improvement of patient survival outcomes. In this work, we study the significant mRNAs through Machine Learning Algorithms in both the early and late stages of Papillary Thyroid Cancer (PTC).

METHOD

During the course of our study, we investigated various methods and techniques to obtain suitable results. The sequence of procedures we followed included organizing data, using nested cross-validation, data cleaning, and normalization at the initial stage. Next, to apply feature selection, a t-test and binary Non-Dominated Sorting Genetic Algorithm II (NSGAII) were chosen to be employed. Later on, during the analysis stage, the discriminative power of the selected features was evaluated using machine learning and deep learning algorithms. Finally, we considered the selected features and utilized Association Rule Mining algorithm to identify the most important ones for improving the decoding of dominant molecular mechanisms in PTC through its early and late stages.

RESULT

The SVM classifier was able to distinguish between early and late-stage categories with an accuracy of 83.5% and an AUC of 0.78 based on the identified mRNAs. The most significant genes associated with the early and late stages of PTC were identified as (e.g., ZNF518B, DTD2, CCAR1) and (e.g., lnc-DNAJB6-7:7, RP11-484D2.3, MSL3P1), respectively.

CONCLUSION

Current study reveals a clear picture of the potential candidate genes that could play a major role not only in the early stage, but also throughout the late one. Hence, the findings could be of help to identify therapeutic targets for more effective PTC drug developments.

BRAF, TERT and HLA-G Status in the Papillary Thyroid Carcinoma: A Clinicopathological Association Study

As BRAF, TERT, HLA-G, and microRNAs have been individually associated with papillary thyroid carcinoma (PTC), we aimed to evaluate the individual and collaborative role of these markers in PTC in the same patient cohort. HLA-G and BRAF tumor expression was evaluated by immunohistochemistry. Using molecular methods, BRAFV600E and TERT promoter mutations were evaluated in thyroid fine needle aspirates. MicroRNA tumor profiling was investigated using massively parallel sequencing. We observed strong HLA-G (67.96%) while BRAF (62.43%) staining was observed in PTC specimens. BRAF overexpression was associated with poor response to therapy. The BRAFV600E (52.9%) and TERTC228T (13%) mutations were associated with extrathyroidal extension, advanced-age, and advanced-stage cancer. The TERT rs2853669 CC+TC genotypes (38%) were overrepresented in metastatic tumors. Nine modulated microRNAs targeting the BRAF, TERT, and/or HLA-G genes were observed in PTC and involved with cancer-related signaling pathways. The markers were individually associated with PTC features, emphasizing the synergistic effect of BRAFV600E and TERTC228T; however, their collaborative role on PTC outcome was not fully demonstrated. The differentially expressed miRNAs targeting the BRAF and/or HLA-G genes may explain their increased expression in the tumor milieu.

Generation and Differentiation of Adult Tissue-Derived Human Thyroid Organoids

Total thyroidectomy as part of thyroid cancer treatment results in hypothyroidism requiring lifelong daily thyroid hormone replacement. Unbalanced hormone levels result in persistent complaints such as fatigue, constipation, and weight increase. Therefore, we aimed to investigate a patient-derived thyroid organoid model with the potential to regenerate the thyroid gland. Murine and human thyroid-derived cells were cultured as organoids capable of self-renewal and which expressed proliferation and putative stem cell and thyroid characteristics, without a change in the expression of thyroid tumor-related genes. These organoids formed thyroid-tissue-resembling structures in culture. (Xeno-)transplantation of 600,000 dispersed organoid cells underneath the kidney capsule of a hypothyroid mouse model resulted in the generation of hormone-producing thyroid-resembling follicles. This study provides evidence that thyroid-lineage-specific cells can form organoids that are able to self-renew and differentiate into functional thyroid tissue. Subsequent (xeno-)transplantation of these thyroid organoids demonstrates a proof of principle for functional miniature gland formation.

Correlation between telomerase reverse transcriptase messenger RNA expression and survival of patients with papillary thyroid carcinoma

BACKGROUND

Telomerase reverse transcriptase promoter mutations were recently found to be associated with poorer prognosis in patients with papillary thyroid carcinoma. Correlation between telomerase reverse transcriptase messenger RNA expression and survival of patients with papillary thyroid carcinoma has not been determined.

METHODS

Clinical information, somatic mutations, and RNA sequencing of 492 papillary thyroid carcinoma patients were obtained from The Cancer Genome Atlas. Correlations between messenger RNA expression and clinicopathologic variables were evaluated. Recursive partitioning regression trees were used to find cutoffs predicting survival. Differentially expressed gene analysis was performed by Edge-R, and Database for Annotation, Visualization and Integrated Discovery 6.7 was used to pathway analysis.

RESULTS

Telomerase reverse transcriptase messenger RNA expression was positively correlated with stages II and IV and high MACIS Prognostic Score for Papillary Thyroid Carcinoma. Using a telomerase reverse transcriptase messenger RNA level of 2.854 as a cutoff, patients with higher telomerase reverse transcriptase messenger RNA expression showed poorer overall survival (hazard ratio = 20.7). The higher telomerase reverse transcriptase messenger RNA group showed upregulation of 2,255 genes, with enrichment of carcinogenic pathways.

CONCLUSION

Higher telomerase reverse transcriptase messenger RNA expression was associated with poorer survival in patients with papillary thyroid carcinoma and was a better predictor for death than telomerase reverse transcriptase promoter mutations. Measuring telomerase reverse transcriptase messenger RNA expression in thyroid cancer tissue may allow early identification of papillary thyroid carcinoma patients with worse overall survival.

Expression based biomarkers and models to classify early and late-stage samples of Papillary Thyroid Carcinoma

INTRODUCTION

Recently, the rise in the incidences of thyroid cancer worldwide renders it to be the sixth most common cancer among women. Commonly, Fine Needle Aspiration biopsy predominantly facilitates the diagnosis of the nature of thyroid nodules. However, it is inconsiderable in determining the tumor's state, i.e., benign or malignant. This study aims to identify the key RNA transcripts that can segregate the early and late-stage samples of Thyroid Carcinoma (THCA) using RNA expression profiles.

MATERIALS AND METHODS

In this study, we used the THCA RNA-Seq dataset of The Cancer Genome Atlas, consisting of 500 cancer and 58 normal (adjacent non-tumorous) samples obtained from the Genomics Data Commons (GDC) data portal. This dataset was dissected to identify key RNA expression features using various feature selection techniques. Subsequently, samples were classified based on selected features employing different machine learning algorithms.

RESULTS

Single gene ranking based on the Area Under the Receiver Operating Characteristics (AUROC) curve identified the DCN transcript that can classify the early-stage samples from late-stage samples with 0.66 AUROC. To further improve the performance, we identified a panel of 36 RNA transcripts that achieved F1 score of 0.75 with 0.73 AUROC (95% CI: 0.62-0.84) on the validation dataset. Moreover, prediction models based on 18-features from this panel correctly predicted 75% of the samples of the external validation dataset. In addition, the multiclass model classified normal, early, and late-stage samples with AUROC of 0.95 (95% CI: 0.84-1), 0.76 (95% CI: 0.66-0.85) and 0.72 (95% CI: 0.61-0.83) on the validation dataset. Besides, a five protein-coding transcripts panel was also recognized, which segregated cancer and normal samples in the validation dataset with F1 score of 0.97 and 0.99 AUROC (95% CI: 0.91-1).

CONCLUSION

We identified 36 important RNA transcripts whose expression segregated early and late-stage samples with reasonable accuracy. The models and dataset used in this study are available from the webserver CancerTSP (http://webs.iiitd.edu.in/raghava/cancertsp/).

A meta-analysis evaluating the relationship between B-type Raf kinase mutation and cervical lymphatic metastasis in papillary thyroid cancer

BACKGROUND

B-type Raf kinase (BRAF) mutation is proved to be a critical predictive factor in papillary thyroid cancer (PTC) with aggressive characteristics. However, the association between BRAF mutation and cervical lymphatic metastasis in PTC is controversial.

METHODS

We searched papers on the study of BRAF mutation and cervical lymphatic metastasis in PTC patients through PubMed, Web of Science, Embase, and Cochranelibrary. The BRAF (+) cases, BRAF (-) cases, and cervical lymphphatic metastatic cases in both BRAF (+) and BRAF (-) groups were collected. After Quality assessment, statistical Analysis (funnel plot and Harbord evaluation, Random-effect model, heterogeneity, subgroup analysis, sensitivity analysis, and metacum analysis) were done by the Review Manager (RevMan) 5.3 and stata14 statistical software.

RESULTS

There were 78 cross-section studies which met our inclusion criteria. And all of them had no selection bias, publication bias, or any other bias. A significant association existed between BRAF mutation and cervical lymph node metastasis (LNM) (odds ratio [OR] = 1.63; 95% confidence interval [CI]: 1.44-1.84; P < .05). Overall, 46 studies were conducted among East Asians. Twenty four articles had provided the data of central lymph node metastasis (CLNM), 11 articles with the data of lateral lymph node metastasis (LLNM), and classic/conventional PTC (CPTC) was analyzed in 10 studies. Subgroup analyses were performed based on ethnicity, metastatic site, and subtype of PTC. Significant association between BRAF (+) mutation and cervical LNM were indicated in East Asians (OR = 1.73; 95% CI: 1.49-2.02; P < .05), in non-East Asians (OR = 1.57; 95% CI: 1.26-1.96; P < .05), and in CLNM (OR = 1.80; 95% CI: 1.56-2.07; P < .05). While no significant association was found in LLNM (OR = 1.37; 95% CI: 0.76-2.48; P = .29 > .05) and in CPTC (OR = 1.32; 95% CI: 0.97-1.80; P = .08 > .05). We did not find any other major changes when sensitivity analysis was performed. The metacum analysis showed no significant association existed before 2012. While a significant association began to exist between BRAF mutation and LNM from 2012, and this association became stable from 2017.

CONCLUSIONS

We consider that a significant association exists between BRAF mutation and cervical LNM. Further meta-analysis on subgroup may reveal some valuable factors between BRAF gene mutation and LNM. And we do not recommend that BRAF (+) as the biomarker for LNM in PTC.

A potential biomarker hsa-miR-200a-5p distinguishing between benign thyroid tumors with papillary hyperplasia and papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common endocrine cancer with a significantly increase of the incidence recently. Several cytokines, such as thyroid peroxidase (TPO), cluster of differentiation 56 (CD56), Galectin-3, mesothelial cell (MC), cytokeratin 19 (CK19) and BRAF (B-raf) were recommended to be tested by immunohistochemistry (IHC) for a definitive diagnosis, but were still limited in clinical use because of their relative lower sensitivity and specificity. MicroRNA (miRNA), as a new molecular biomarkers, however, has not been reported yet so far. To address this, hsa-miR-200a-5p, a miRNA, was selected and detected in PTC patients by in situ hybrization with benign thyroid tumor with papillary hyperplasia as a control, and the differential expression of hsa-miR-200a-5p between fresh PTC tissues and control was detected by qRT-PCR. Expressive levels of cytokines of TPO, CD56, Galectin-3, MC, CK19 and B-raf were also detected by immunohistochemistry. The correlation was analyzed by SPSS software using Spearman methods. As expected, the hsa-miR-200a-5p expressive level was significantly increased in PTC patients, compared to that of control, and was consistent with that of TPO, CD56, Galectin-3, MC, CK19 and B-raf. In addition, expression of hsa-miR-200a-5p showed negative correlation to that of TPO (rs = - 0.734; **: P < 0.01) and CD56 (rs = - 0.570; **: P < 0.01), but positive correlation to that of Galectin-3 (rs = 0.601; **: P < 0.01), MC (rs = 0.508; **: P < 0.01), CK19 (rs = 0.712; **: P < 0.01) and B-raf (rs = 0.378; **: P < 0.01). PTC and papillary benign thyroid papillary hyperplasia are difficult to distinguish in morphology, so requiring immunohistochemistry to further differentiate the diagnosis, however, for the existing clinical common diagnostic marker for immunohistochemistry, the sensitivity and accuracy are low, it is easy to miss diagnosis. Therefore, there is an urgent need for a rapid and sensitive molecular marker. So miR-200a-5p can be used to assist in the diagnosis of PTC at the molecular level, and as a biomarker, can be effectively used to distinguish between PTC and benign thyroid tumor with papillary hyperplasia.

Recurrence-associated genes in papillary thyroid cancer: An analysis of data from The Cancer Genome Atlas

BACKGROUND

Recurrence of papillary thyroid cancer is not uncommon, but incorporating clinicopathologic parameters to predict recurrence is suboptimal. The aim of this study was to identify systemically recurrence-associated genes using The Cancer Genome Atlas RNA sequencing database.

METHODS

A total of 504 patients with transcriptome sequencing data of the primary neoplasm were included in this study. High and low levels of expression of each gene were defined by median splits. Differences in recurrence-free survival were compared using Kaplan-Meier curves and log-rank tests. Recurrence-associated genes were subjected to functional enrichment analyses with Kyoto Encyclopedia of Genes and Genomes annotation databases and Ingenuity Pathway Analysis.

RESULTS

We found that 1,807 genes were associated with recurrence-free survival. There were 676 genes of which high expression was associated with a greater risk of recurrence. These genes were enriched in pathways involved in cell cycle regulation and DNA repair. Among 1,131 genes of which low expression was associated with recurrence, Kyoto Encyclopedia of Genes and Genomes-annotated functions were metabolism, calcium signaling, glycan biosynthesis, and the Notch signaling pathway. Canonical pathways identified by Ingenuity Pathway Analysis included RXR function, nitric oxide signaling, interleukin-8 signaling, and nutrient sensing. In addition, low expression of the majority of thyroid differentiation genes was associated with a significantly less recurrence-free survival.

CONCLUSION

Upregulation of cell cycle-regulating and DNA repair genes appears to have a negative impact on recurrence-free survival in patients with papillary thyroid cancer. Furthermore, recurrence is associated with thyroid dedifferentiation.