An analysis of trends of incidence and cytohistological correlation of papillary carcinoma of the thyroid gland with evaluation of discordant cases

Sharma, Charu

doi:10.4103/0970-9371.190455

Cited by 14 publications

(8 citation statements)

References 29 publications

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“…The incidence of thyroid cancer has increased rapidly in many countries during recent decades [1]. This change is related to an increase in papillary thyroid cancer (PTC), which is the most common histological subtype of thyroid cancer accounting for approximately 80% of cases [2]. Most PTCs have a slow clinical course and favorable survival rates.…”

Section: Introductionmentioning

confidence: 99%

Gene mutations related to cell adhesion found in lymph node metastasis from papillary thyroid carcinoma by whole exome sequencing

Zeng

et al. 2019

Preprint

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Background: Lymph node metastasis is the most common metastasis associated with papillary thyroid carcinoma (PTC). There are few data on gene mutations associated with lymph node metastasis from PTC. At present, the mechanism underlying lymph node metastasis of PTC is still poorly understood.Methods: Whole exome sequencing (WES) was performed for PTC of 10 primary tumor tissues and 10 lymph node metastasis tissues (non-match) for gene mutations. Gene ontology (GO) analysis was used to study biological functions and processes related to lymph node metastasis. Sanger sequencing was used to verify these genes in the lymph node metastasis group.Results: A total of 2772 gene mutations were identified in the primary tumor group. A total of 3033 gene mutations were enriched in the lymph node metastasis group. There were 50 gene mutations that were found to be present at higher frequency in the lymph node metastasis group than in the primary tumor group. Among 50 gene mutations, nonsynonymous mutations of 5 genes (LPP, MSLN, MAEA, VCAN, and MUC16) involved in cell adhesion were present. Three nonsynonymous mutations were also found in RP1L1, QSER1, and TLR4. These high-frequency genetic mutations that showed significant enrichment were targeted sequencing and validated by Sanger sequencing.Conclusion: Thyroid cancer and corresponding metastatic lymph nodes contain a large number of SNPs and 50 SNP genes associated with lymph node metastasis. Genes related to cell adhesion (LPP, MSLN, MAEA, VCAN, and MUC16) may play an important role in the process of lymph node metastasis. The contribution of BRAF in lymph node metastasis may not be high.

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Section: Introductionmentioning

confidence: 99%

Gene mutations related to cell adhesion found in lymph node metastasis from papillary thyroid carcinoma by whole exome sequencing

Zeng

et al. 2019

Preprint

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“…[131415] However, small focus of papillary carcinoma is often encountered in smears showing only benign findings elsewhere. [16] It is because of its reasonable sensitivity, specificity, and screening requirements that we have chosen FNAC thyroid for training the neural network.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence in Cytopathology: A Neural Network to Identify Papillary Carcinoma on Thyroid Fine-Needle Aspiration Cytology Smears

Sanyal

Mukherjee

Barui

et al. 2018

Journal of Pathology Informatics

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Introduction:Fine-needle aspiration cytology (FNAC) for identification of papillary carcinoma thyroid is a moderately sensitive and specific modality. The present machine learning tools can correctly classify images into broad categories. Training software for recognition of papillary thyroid carcinoma on FNAC smears will be a decisive step toward automation of cytopathology.Aim:The aim of this study is to develop an artificial neural network (ANN) for the purpose of distinguishing papillary carcinoma thyroid and nonpapillary carcinoma thyroid on microphotographs from thyroid FNAC smears.Subjects and Methods:An ANN was developed in the Python programming language. In the training phase, 186 microphotographs from Romanowsky/Pap-stained smears of papillary carcinoma and 184 microphotographs from smears of other thyroid lesions (at ×10 and ×40 magnification) were used for training the ANN. After completion of training, performance was evaluated with a set of 174 microphotographs (66 – nonpapillary carcinoma and 21 – papillary carcinoma, each photographed at two magnifications ×10 and ×40).Results:The performance characteristics and limitations of the neural network were assessed, assuming FNAC diagnosis as gold standard. Combined results from two magnifications showed good sensitivity (90.48%), moderate specificity (83.33%), and a very high negative predictive value (96.49%) and 85.06% diagnostic accuracy. However, vague papillary formations by benign follicular cells identified wrongly as papillary carcinoma remain a drawback.Conclusion:With further training with a diverse dataset and in conjunction with automated microscopy, the ANN has the potential to develop into an accurate image classifier for thyroid FNACs.

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“…Thyroid carcinoma is the cancer with the third fastest increase in diagnosis in the US, and papillary thyroid carcinoma (PTC) comprises 80% of thyroid carcinoma ( 1 , 2 ). PTC occurs more often in women, and although it can occur at any age, even in childhood, the peak incidence is in patients between 30 and 50 years of age ( 3 ). PTC typically has an indolent clinical course and may be cured by thyroidectomy and radioactive iodine therapy, even if metastatic ( 4 ).…”

Section: Introductionmentioning

confidence: 99%

p63 inhibits CD44+/CD24‑ cell proliferation and chemoresistance in papillary thyroid carcinoma cells

Guo

et al. 2017

Exp Ther Med

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Thyroid cancer typically has a good prognosis; however, the risks of recurrence and chemoresistance associated with thyroid cancer remain a cause for concern. Papillary thyroid carcinoma (PTC) comprises 80% of all cases of thyroid carcinoma. A previous study reported that cluster of differentiation (CD) 44+/CD24− PTC cells may contribute to PTC recurrence and chemoresistance; however, the underlying molecular mechanisms remain elusive. In the present study, CD44+/CD24− cells were isolated from the TPC-1 PTC cell line and biological function assays revealed that CD44+/CD24− cells were significantly more proliferative and chemoresistant compared with CD44−/CD24− cells. Furthermore, the expression level of p63 was demonstrated to be negatively correlated with the expression of CD44 in PTC cells. The role of p63 in CD44+/CD24− cell proliferation and chemoresistance was investigated and, the ectopic expression of p63 was observed to significantly inhibit CD44+/CD24− cell proliferation and chemoresistance in vitro and in vivo. In conclusion, the present study indicated that CD44+/CD24− cells contribute to PTC proliferation and chemoresistance and that the suppression of p63 in CD44+/CD24− cells contributes to these effects.

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An analysis of trends of incidence and cytohistological correlation of papillary carcinoma of the thyroid gland with evaluation of discordant cases

Cited by 14 publications

References 29 publications

Gene mutations related to cell adhesion found in lymph node metastasis from papillary thyroid carcinoma by whole exome sequencing

Gene mutations related to cell adhesion found in lymph node metastasis from papillary thyroid carcinoma by whole exome sequencing

Artificial Intelligence in Cytopathology: A Neural Network to Identify Papillary Carcinoma on Thyroid Fine-Needle Aspiration Cytology Smears

p63 inhibits CD44+/CD24‑ cell proliferation and chemoresistance in papillary thyroid carcinoma cells

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