&lt;p&gt;Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis&lt;/p&gt;

Wang, Shengnan; Wu, Jing; Guo, Congcong; Shang, Hongxia; Yao, Jinming; Liao, Lin; Dong, Jianjun

doi:10.2147/cmar.s250792

Cited by 12 publications

(5 citation statements)

References 51 publications

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“…CENPF is already known as thyroid carcinoma biomarker, involved in migration and proliferation[ 61 ]. Interestingly, anaplastic TC, the most aggressive histological TC is enriched in genes involved in the mitosis progression including CENPF , NEK2 and NUSAP1 [ 62 , 63 ] . We also identified several aging-dependent TFs that are upregulated in TCs, such as FOXM1 and SOX11, both of which have fundamental roles in tumorigenesis and aggressiveness.…”

Section: Discussionmentioning

confidence: 99%

An Integrative Multi-Omics Analysis of The Molecular Links between Aging and Aggressiveness in Thyroid Cancers

Ruiz¹,

Kandil²,

Alhassan³

et al. 2023

Aging and disease

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Aging modifies risk in all cancers, but age is used as a clinical staging criterion uniquely in thyroid cancer (TC). The molecular drivers of age-dependent TC onset and aggressiveness remain poorly understood. We applied an integrative, multi-omics data analysis approach to characterize these signatures. Our analysis reveals that aging, independent of BRAF V600E mutational status, drives a significant accumulation of aggressiveness-related markers and poorer survival outcomes, most noticeably at age 55 and over. We identified that chromosomal alterations in loci 1p/1q as aging-associated drivers of aggressiveness, and that depleted infiltration with tumor surveillant CD8+T and follicular helper T cells, dysregulation of proteostasis- and senescence-related processes, and ERK1/2 signaling cascade are key features of the aging thyroid and TC onset/progression and aggressiveness in aging patients but not in young individuals. A panel of 23 genes, including those related to cell division such as CENPF, ERCC6L, and the kinases MELK and NEK2, were identified and rigorously characterized as aging-dependent and aggressiveness-specific markers. These genes effectively stratified patients into aggressive clusters with distinct phenotypic enrichment and genomic/transcriptomic profiles. This panel also showed excellent performance in predicting metastasis stage, BRAF V600E , TERT promoter mutation, and survival outcomes and was superior to the American Thyroid Association (ATA) methodology in predicting aggressiveness risk. Our analysis established clinically relevant biomarkers for TC aggressiveness factoring in aging as an important component.

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Section: Discussionmentioning

confidence: 99%

An Integrative Multi-Omics Analysis of The Molecular Links between Aging and Aggressiveness in Thyroid Cancers

Ruiz¹,

Kandil²,

Alhassan³

et al. 2023

Aging and disease

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“…Although it accounts for only 2% of all THCA, ATC has a high mortality rate and was the main cause of THCA death (2). Moreover, epidemiological surveys showed that the incidence of ATC increased from 1973 to 2014 (12). Therefore, it is clinically significant to explore effective treatment methods to improve the prognosis of ATC patients.…”

Section: Discussionmentioning

confidence: 99%

“…We obtained ATC gene expression profiling datasets (11,12), GSE65144 GSE33630, GSE29265 (no citation), and GSE53157, from the GEO (https://www.ncbi.nlm.nih. gov/geo/) database.…”

Section: Transcriptome Data Acquisition and Pre-processingmentioning

confidence: 99%

Expression of colorectal neoplasia differentially expressed in anaplastic thyroid carcinoma and its effect on cancer cell proliferation

Zhao

et al. 2022

Ann Transl Med

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Background: The incidence of anaplastic thyroid cancer (ATC) is high among human cancers. Colorectal neoplasia differentially expressed (CRNDE) is highly expressed in common tumors, and is therefore a potential molecular target for anti-tumor therapy. However, the function of CRNDE in ATC remains elusive. Methods:The Gene Expression Omnibus (GEO) database was used to screen the differential expression of long-noncoding RNA (lncRNA) in ATC tissues. The Cancer Genome Atlas (TCGA) database was used to analyze the expression of CRNDE in thyroid cancer (THCA) tissues and its impact on patient prognosis.Quantitative real-time PCR (qRT-PCR) was used to determine the expression level of CRNDE in tumor and control tissues. The biological function of CRNDE in THCA was explored using TCGA RNA sequencing (RNA-seq) data analysis. ATC cell lines with low and high CRNDE expression were selected for CRNDE siRNA transfection, and the proliferation of cells was detected in each group. Results:The GEO and TCGA databases analysis results showed that CRNDE was highly expressed in ATC tissues, which is related to the poor prognosis of THCA patients. Also, the expression of CRNDE in the ATC cell line, ARO (human thyroid cancer cell line), was relatively high, while the expression in sw579 is relatively low. Therefore, ARO and sw579 were chosen for CRNDE small interfering RNA (siRNA) transfection. Compared with negative control (si-NC), the expression of CRNDE in si-CRNDE-1, si-CRNDE-2, and si-CRNDE-3 was reduced, indicating that the inhibitory effect was significantly enhanced and the cell proliferation ability was reduced, and the cell cycle is arrested in the G0/G1 phase. Finally, it was found that the wnt3a, β-catenin, and cyclinD1 protein expressions of si-CRNDE-1 and si-CRNDE-2 were significantly reduced. Conclusions:The high expression of CRNDE in ATC tissues may promote the proliferation of ATC cells by regulating the Wnt/β-catenin signaling pathway. CRNDE may be a potential molecular target for the treatment of ATC.

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“…The DEMGs were then subjected to functional enrichment and protein-protein interaction (PPI) analyses. PPI analysis was set with an interaction score of 0.4 [19,20] and exclusion of hidden disconnected nodes. The interaction data were imported into Cytoscape to find hub genes based on Degree, Maximum Neighborhood component (MNC), Closeness, and Maximal Clique Centrality (MCC) algorithms.…”

Section: Plos Onementioning

confidence: 99%

Identification of abdominal aortic aneurysm subtypes based on mechanosensitive genes

Sheng,

Zeng,

Huang

et al. 2024

PLoS ONE

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Background Rupture of abdominal aortic aneurysm (rAAA) is a fatal event in the elderly. Elevated blood pressure and weakening of vessel wall strength are major risk factors for this devastating event. This present study examined whether the expression profile of mechanosensitive genes correlates with the phenotype and outcome, thus, serving as a biomarker for AAA development. Methods In this study, we identified mechanosensitive genes involved in AAA development using general bioinformatics methods and machine learning with six human datasets publicly available from the GEO database. Differentially expressed mechanosensitive genes (DEMGs) in AAAs were identified by differential expression analysis. Molecular biological functions of genes were explored using functional clustering, Protein–protein interaction (PPI), and weighted gene co-expression network analysis (WGCNA). According to the datasets (GSE98278, GSE205071 and GSE165470), the changes of diameter and aortic wall strength of AAA induced by DEMGs were verified by consensus clustering analysis, machine learning models, and statistical analysis. In addition, a model for identifying AAA subtypes was built using machine learning methods. Results 38 DEMGs clustered in pathways regulating ‘Smooth muscle cell biology’ and ‘Cell or Tissue connectivity’. By analyzing the GSE205071 and GSE165470 datasets, DEMGs were found to respond to differences in aneurysm diameter and vessel wall strength. Thus, in the merged datasets, we formally created subgroups of AAAs and found differences in immune characteristics between the subgroups. Finally, a model that accurately predicts the AAA subtype that is more likely to rupture was successfully developed. Conclusion We identified 38 DEMGs that may be involved in AAA. This gene cluster is involved in regulating the maximum vessel diameter, degree of immunoinflammatory infiltration, and strength of the local vessel wall in AAA. The prognostic model we developed can accurately identify the AAA subtypes that tend to rupture.

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<p>Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis</p>

Cited by 12 publications

References 51 publications

An Integrative Multi-Omics Analysis of The Molecular Links between Aging and Aggressiveness in Thyroid Cancers

An Integrative Multi-Omics Analysis of The Molecular Links between Aging and Aggressiveness in Thyroid Cancers

Expression of colorectal neoplasia differentially expressed in anaplastic thyroid carcinoma and its effect on cancer cell proliferation

Identification of abdominal aortic aneurysm subtypes based on mechanosensitive genes

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