scholarly journals PPARγ Targets-Derived Diagnostic and Prognostic Index for Papillary Thyroid Cancer

Cancers ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 5110
Author(s):  
Jaehyung Kim ◽  
Soo Young Kim ◽  
Shi-Xun Ma ◽  
Seok-Mo Kim ◽  
Su-Jin Shin ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Monozygotic Twins ◽  
Prognostic Index ◽  
Machine Learning Algorithms ◽  
Small Subset ◽  
Papillary Thyroid ◽  
Normal Tissues ◽  
Diagnosis And Prognosis ◽  
Perfect Performance

In most cases, papillary thyroid cancer (PTC) is highly curable and associated with an excellent prognosis. Yet, there are several clinicopathological features that lead to a poor prognosis, underscoring the need for a better genomic strategy to refine prognostication and patient management. We hypothesized that PPARγ targets could be potential markers for better diagnosis and prognosis due to the variants found in PPARG in three pairs of monozygotic twins with PTC. Here, we developed a 10-gene personalized prognostic index, designated PPARGi, based on gene expression of 10 PPARγ targets. Through scRNA-seq data analysis of PTC tissues derived from patients, we found that PPARGi genes were predominantly expressed in macrophages and epithelial cells. Machine learning algorithms showed a near-perfect performance of PPARGi in deciding the presence of the disease and in selecting a small subset of patients with poor disease-specific survival in TCGA-THCA and newly developed merged microarray data (MMD) consisting exclusively of thyroid cancers and normal tissues.

scholarly journals Down-regulation of DANCR acts as a potential biomarker for papillary thyroid cancer diagnosis

2019 ◽  
Vol 39 (4) ◽  
Author(s):  
Ke Zhang ◽  
Jing Lv ◽  
Xiaowei Peng ◽  
Jianqiu Liu ◽  
Cuilin Li ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Expression Profiles ◽  
Expression Level ◽  
Papillary Thyroid ◽  
Normal Tissues ◽  
Cancer Breast ◽  
Tumor Tissues ◽  
Potential Biomarker ◽  
Reverse Transcription Quantitative Pcr

AbstractLong non-coding RNAs (lncRNAs) have been reported to be dysregulated and play a crucial role in the progression of cancer. LncRNA DANCR has recently been revealed to be involved in tumorigenesis of numerous types of cancer, including osteosarcoma, gastric cancer, breast cancer, hepatocellular carcinoma, and colorectal cancer. However, the expression profiles and biological relevance of DANCR in papillary thyroid cancer (PTC) have not yet been reported. In the present study, the expression level of DANCR in PTC tissues and adjacent normal tissues was detected by reverse transcription-quantitative PCR in PTC patients, and then we analyzed the association with clinical pathological characteristics of patients and DANCR expressions. These results demonstrated that the expression of DANCR was notably decreased in tumor tissues in comparison with adjacent normal tissues (P<0.001). Furthermore, the present study found that DANCR expression level was correlated to T grade (P<0.01) and TNM stage (P=0.017). The present study demonstrated that DANCR was associated with PTC aggressive clinical features and may serve as a diagnostic biomarker for detecting PTC patients.

scholarly journals Development an Immune-Associated LncRNA Prognostic Index for Papillary Thyroid Cancer

2020 ◽  
Author(s):  
Min Mao ◽  
Rong-zhi Huang ◽  
Zhu Yu ◽  
Jie Zheng ◽  
Hai-qi Liang ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Correlation Analysis ◽  
Papillary Thyroid Cancer ◽  
Pearson Correlation ◽  
Prognostic Index ◽  
Gene Set Enrichment Analysis ◽  
Papillary Thyroid ◽  
Immune System Development ◽  
Pearson Correlation Analysis ◽  
The Impact

Abstract BACKGROUND: Papillary thyroid cancer (PTC) is the most common pathological type of thyroid cancer and its incidence is still on the rise worldwide. Our study aimed to provide an understanding of papillary thyroid cancer in immunological aspects and prompt its clinical diagnosis and treatment.METHODS: We obtained RNA-FPKM data and clinical data of papillary thyroid cancer (PTC) samples from the TCGA data portal. Immune-related genes (IRGs) were selected from Molecular Signatures Database v7.0. The immune-related lncRNAs were identified by constructing DELs-IRGs co-expression networks. Cox regression and Kaplan-Meier methods were used to construct immune-related lncRNAs prognosis index (IRLPI) and analyze the impact of IRLPI on overall survival. Gene Set Enrichment Analysis (GSEA) was performed by clusterProfiler R package to explore the potential molecular mechanism in TCGA dataset. The relationship between immune cell types and IRLPI were explored by using Pearson correlation analysis.RESULTS: A total of 478 primary PTC samples were collected for the analysis. 162 immune-related lncRNAs were identified in immune-lncRNAs co-expression network. And 7 lncRNAs were extracted to develop the IRLPI. Patients with high-IRLPI showed poor survival probability (P =0.00052) and IRLPI was identified as an independent prognostic factor (HR: 2.329, 95%CI: 1.481-2.664, p =2.54e-4). ROC curve declared a promising prognosis ability of IRLPI. PCA proved that IRLPI reflected different immune environment and biological processes. GSEA indicated that immune system development is the main different biological process between high- and low-IRLPI group. Furthermore, IRLPI was proved that it related with multiple immune cells and immune responses by Pearson correlation analysis.CONCLUSION: Our results showed that immune-related lncRNAs prognosis index (IRLPI) could serve as a potential prognostic model in papillary thyroid cancer and play an important role in the immunotherapies and surveillance of PTC.

scholarly journals Identification of Hub lncRNAs Along With lncRNA-miRNA-mRNA Network for Effective Diagnosis and Prognosis of Papillary Thyroid Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Haiyan Li ◽  
Feng Liu ◽  
Xiaoyang Wang ◽  
Menglong Li ◽  
Zhihui Li ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Prognostic Indicators ◽  
Validation Dataset ◽  
Papillary Thyroid ◽  
Cerna Network ◽  
Diagnosis And Prognosis ◽  
Potential Biomarkers

Long noncoding RNAs (lncRNAs) play important roles in tumorigenesis and progression of different cancers and they have been potential biomarkers for cancer diagnosis and prognosis. As the most common endocrine malignancy, precise diagnosis and prognosis of papillary thyroid cancer (PTC) is of great clinical significance. Here, we aim to identify new hub lncRNAs for marking PTC and constructed prognostics signatures based on lncRNA- miRNA-mRNA competing endogenous RNAs (ceRNA) network to predict overall survival (OS) and disease-free survival (DFS) respectively. Five reliable hub lncRNAs were identified by integrating differential genes of four Gene Expression Omnibus (GEO) gene chips using the RobustRankAggreg (RRA) method. Based on differential analyses and interaction prediction, a lncRNA-mRNA co-expression network and a lncRNA-miRNA-mRNA ceRNA network were established. Then a comprehensive function characterization of the five hub lncRNAs was performed, including validation dataset testing, receiver operating characteristic (ROC) curve analysis, and functional analysis on two networks. All results suggest that these five hub lncRNAs could be potential biomarkers for marking PTC. The ceRNA network was used to identify RNAs which were associated with PTC prognosis. Two prognostic signatures were developed using univariate and step-wise multivariate Cox regression analyses and both of them were independent prognostic indicators for PTC OS and DFS. Tumor microenvironment difference analysis between high and low-risk patients showed that dendritic cells activated and macrophages M0 may be a possible target for immunotherapy of PTC. In addition, disclosing the potential drugs that may reverse the expression of hub genes may improve the prognosis of patients with PTC. Here, connectivity map (CMap) analysis indicates that three bioactive chemicals (pioglitazone, benserazide, and SB-203580) are promising therapeutic agents for PTC. So, the paper presents a comprehensive study on diagnosis, prognosis, and potential drug screening for PTC based on the five hub lncRNAs identified by us.

scholarly journals Development of a prognostic index based on an immunogenomic landscape analysis of papillary thyroid cancer

Aging ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 480-500 ◽  
Author(s):  
Peng Lin ◽  
Yi-nan Guo ◽  
Lin Shi ◽  
Xiao-jiao Li ◽  
Hong Yang ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Prognostic Index ◽  
Landscape Analysis ◽  
Papillary Thyroid

scholarly journals Cell division cycle 45 promotes papillary thyroid cancer progression via regulating cell cycle

Tumor Biology ◽  
2017 ◽  
Vol 39 (5) ◽  
pp. 101042831770534 ◽  
Author(s):  
Jing Sun ◽  
Run Shi ◽  
Sha Zhao ◽  
Xiaona Li ◽  
Shan Lu ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Cell Division ◽  
Papillary Thyroid Cancer ◽  
Cancer Progression ◽  
Biological Significance ◽  
Cell Division Cycle ◽  
The Cancer Genome Atlas ◽  
Papillary Thyroid ◽  
Normal Tissues

Cell division cycle 45 was reported to be overexpressed in some cancer-derived cell lines and was predicted to be a candidate oncogene in cervical cancer. However, the clinical and biological significance of cell division cycle 45 in papillary thyroid cancer has never been investigated. We determined the expression level and clinical significance of cell division cycle 45 using The Cancer Genome Atlas, quantitative real-time polymerase chain reaction, and immunohistochemistry. A great upregulation of cell division cycle 45 was observed in papillary thyroid cancer tissues compared with adjacent normal tissues. Furthermore, overexpression of cell division cycle 45 positively correlates with more advanced clinical characteristics. Silence of cell division cycle 45 suppressed proliferation of papillary thyroid cancer cells via G1-phase arrest and inducing apoptosis. The oncogenic activity of cell division cycle 45 was also confirmed in vivo. In conclusion, cell division cycle 45 may serve as a novel biomarker and a potential therapeutic target for papillary thyroid cancer.

scholarly journals A Comprehensive Expression Profile of tRNA-Derived Fragments in Papillary Thyroid Cancer

2020 ◽  
pp. 1-7
Author(s):  
Chunfu Zhu ◽  
Shiting Shan ◽  
Yuting Wang ◽  
Chunfu Zhu
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Thyroid Tumor ◽  
Biological Processes ◽  
Papillary Thyroid ◽  
Normal Tissues ◽  
Non Coding Rna ◽  
Malignant Thyroid Tumor ◽  
Fresh Frozen

Objective: In recent years, the incidence of thyroid cancer has been increasing. Papillary thyroid cancer (PTC) is the most common type of malignant thyroid tumor, accounting for approximately 85% of thyroid cancer cases. Although the genetic background of PTC has been studied extensively, relatively little is known about the role of small non-coding RNA (sncRNA) in this disease. tRNA-derived fragments (tRFs) represent a newly discovered class of sncRNAs that exist in many species and play a role in many biological processes. Methods: In this study, we used RNA sequencing to analyse the expression of tRFs in fresh frozen specimens from PTC tissues and normal tissues adjacent to the tumors. Through this analysis, we identified 49 unique tRFs and transfer RNA halves and then performed quantitative PCR to determine the expression levels of these molecules and to make bioinformatic predictions. Conclusion: In this report, we provide a comprehensive catalog of tRFs in PTC and assess the abnormal expression of these fragments. These preliminary findings can be used as the basis for further research regarding the functional role of tRFs in patients with PTC.

scholarly journals Identification of a Four-miRNA Signature Predicts Prognosis in Papillary Thyroid Cancer

2021 ◽  
Author(s):  
YANG FAN ◽  
Hongzhong zhou
Keyword(s):  
Thyroid Cancer ◽  
High Risk ◽  
Papillary Thyroid Cancer ◽  
Papillary Thyroid ◽  
Normal Tissues ◽  
Significant Difference ◽  
Differentially Expressed Mirnas ◽  
Score Model ◽  
New Biomarkers

Abstract Background: In newly diagnosed patients with thyroid cancer, papillary thyroid cancer (PTC), accounts for ninety percent of all cases. Although PTC is known as a relatively adolescent malignant disease, there still is a high possibility of recurrence in PTC patients, who suffered from poor prognosis. Therefore, new biomarkers are necessary to guide more effective stratification of PTC patients and personalization of therapy to avoid overtreatment or inadequate treatment. Accumulating evidence demonstrates that miRNAs have broad application prospects as diagnostic biomarkers in cancer. Methods: The present study aims to explore novel markers consists of miRNA-associated signature for PTC prognostication, utilizing data from the TCGA database. We obtained and analyzed data of 497 PTC patients from the TCGA. The patients were randomly assigned to a training cohort or testing cohort. Results: We discovered 237 differentially expressed miRNAs in tumorous thyroid tissues comparing to normal tissues The effect evaluation of excavated differently expressed miRNAs was conducted by our risk score model. We then successfully generated a four-miRNA potential prognostic signature, which reliably distinguishes patients from high risk and low risk with a significant difference in overall survival (P <0.01) and was effective in predicting five-year disease survival. Conclusions: Our results indicated a four miRNAs signature that has a robust predicting effect on the prognosis of PTC. Therefore, we would recommend more radical treatment and closer follow-up of high-risk individuals.

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