scholarly journals Gene Expression Patterns Unveil New Insights in Papillary Thyroid Cancer

Medicina ◽  
2019 ◽  
Vol 55 (8) ◽  
pp. 500 ◽  
Author(s):  
Saftencu ◽  
Braicu ◽  
Cojocneanu ◽  
Buse ◽  
Irimie ◽  
...  
Keyword(s):  
Gene Expression ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Clinical Relevance ◽  
Expression Patterns ◽  
Gene Expression Signature ◽  
Specific Gene ◽  
Endocrine Tumors ◽  
Papillary Thyroid ◽  
Data Set

Background and objectives: Papillary thyroid carcinoma is the most frequent variety of all malignant endocrine tumors. It represents a heterogeneous malignancy with various clinical outcomes, emphasizing the need to identify powerful biomarkers with clinical relevance. Materials and Methods: Available gene expression data (level 3) for thyroid cancers were downloaded from the Cancer Genome Atlas (TCGA), followed by bioinformatic analyses performed on the data set. Results: Based on gene expression analysis, we were able to identify common and specific gene signatures for the three main types of papillary thyroid carcinoma (classical, follicular variant, and tall-cell). The survival rate was not significantly different among the main subtypes, but we were able to identify a biological adhesion signature with impact in patient prognostic. Conclusions: Taken together, the gene expression signature and particular adhesion signature, along with ITGA10 and MSLN in particular, could be used as a prognostic tool with important clinical relevance.

scholarly journals Comprehensive transcriptomic analysis of Papillary Thyroid Cancer: potential biomarkers associated with tumor progression

2019 ◽  
Author(s):  
Nazanin Hosseinkhan ◽  
Maryam Honardoost ◽  
Kevin Blighe ◽  
C.B. Tara Moore ◽  
Mohammad Ebrahim Khamseh
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Stage Iv ◽  
Predictive Biomarkers ◽  
Stage I ◽  
The Cancer Genome Atlas ◽  
Papillary Thyroid ◽  
Validation Data ◽  
Data Set ◽  
Small Subgroup

Abstract Background Identification of stage-specific prognostic/predictive biomarkers could lead to the more efficient clinical management in papillary thyroid carcinoma (PTC). The main objective of this study was to characterize the stage-specific deregulations in gene and miRNA expression in PTC and also to identify potential prognostic biomarkers.Methods 495 RNASeq and 499 miRNASeq PTC samples (stage I-IV) as well as, respectively, 56 and 57 normal samples were retrieved from The Cancer Genome Atlas (TCGA). DESeq2 was used to identify deregulation of genes and miRNAs between sequential stages of PTC. To identify the minority of patients who progress from stage I to higher stages, we additionally performed a clustering analysis focused on the stage I RNASeq data. Moreover a validation study was done on an independent PTC RNASeq study.Results Large amount of heterogeneity in gene expression patterns was observed in stage I PTC patients. LTF and PLA2R1 were identified as two promising biomarkers that exhibited down-regulation in a small subgroup of stage I (both in TCGA and in the validation data set) and in the majority of stage IV patients (in TCGA data set). hsa-miR-205, hsa-miR-509-2, hsa-miR-514-1 and hsa-miR-514-2 were also identified as up-regulated miRNAs in both PTC patients with stage I and stage III.Conclusion Common gene expression alterations in early and advanced stages of PTC, could be used for individualized risk stratification and personalized treatment approach.

scholarly journals The Clinical Relevance of Psammoma Body and Hashimoto Thyroiditis in Papillary Thyroid Carcinoma

Medicine ◽  
2015 ◽  
Vol 94 (44) ◽  
pp. e1881 ◽  
Author(s):  
Ye-Feng Cai ◽  
Qing-Xuan Wang ◽  
Chun-Jue Ni ◽  
Gui-Long Guo ◽  
Quan Li ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Clinical Relevance ◽  
Hashimoto Thyroiditis ◽  
Psammoma Body ◽  
Papillary Thyroid

FOXA1 in breast cancer

2009 ◽  
Vol 11 ◽  
Author(s):  
Harikrishna Nakshatri ◽  
Sunil Badve
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Transcription Factor ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Gene Expression Signature ◽  
Specific Gene ◽  
Breast Cancers ◽  
Transcription Factor Network ◽  
Histopathological Classification

Breast cancer is a heterogeneous disease and classification is important for clinical management. At least five subtypes can be identified based on unique gene expression patterns; this subtype classification is distinct from the histopathological classification. The transcription factor network(s) required for the specific gene expression signature in each of these subtypes is currently being elucidated. The transcription factor network composed of the oestrogen (estrogen) receptor α (ERα), FOXA1 and GATA3 may control the gene expression pattern in luminal subtype A breast cancers. Breast cancers that are dependent on this network correspond to well-differentiated and hormone-therapy-responsive tumours with good prognosis. In this review, we discuss the interplay between these transcription factors with a particular emphasis on FOXA1 structure and function, and its ability to control ERα function. Additionally, we discuss modulators of FOXA1 function, ERα–FOXA1–GATA3 downstream targets, and potential therapeutic agents that may increase differentiation through FOXA1.

scholarly journals TERT Promoter Mutations and Their Impact on Gene Expression Profile in Papillary Thyroid Carcinoma

Cancers ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1597 ◽  
Author(s):  
Dagmara Rusinek ◽  
Aleksandra Pfeifer ◽  
Marta Cieslicka ◽  
Malgorzata Kowalska ◽  
Agnieszka Pawlaczek ◽  
...  
Keyword(s):  
Gene Expression ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Gene Expression Profile ◽  
Expression Profile ◽  
Distant Metastases ◽  
Gene Set Enrichment Analysis ◽  
Braf V600e ◽  
Papillary Thyroid ◽  
Mutational Status

Background: Telomerase reverse transcriptase promoter (TERTp) mutations are related to a worse prognosis in various malignancies, including papillary thyroid carcinoma (PTC). Since mechanisms responsible for the poorer outcome of TERTp(+) patients are still unknown, searching for molecular consequences of TERTp mutations in PTC was the aim of our study. Methods: The studied cohort consisted of 54 PTCs, among them 24 cases with distant metastases. BRAF V600E, RAS, and TERTp mutational status was evaluated in all cases. Differences in gene expression profile between TERTp(+) and TERTp(−) PTCs were examined using microarrays. The evaluation of signaling pathways and gene ontology was based on the Gene Set Enrichment Analysis. Results: Fifty-nine percent (32/54) of analyzed PTCs were positive for at least one mutation: 27 were BRAF(+), among them eight were TERTp(+), and 1 NRAS(+), whereas five other samples harbored RAS mutations. Expression of four genes significantly differed in BRAF(+)TERTp(+) and BRAF(+)TERTp(−) PTCs. Deregulation of pathways involved in key cell processes was observed. Conclusions: TERTp mutations are related to higher PTC aggressiveness. CRABP2 gene was validated as associated with TERTp mutations. However, its potential use in diagnostics or risk stratification in PTC patients needs further studies.

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