Dataset Information

TIPE2 acts as a biomarker for tumor aggressiveness and suppresses cell invasiveness in papillary thyroid cancer (PTC).

ABSTRACT:

Background

Tumor necrosis factor (TNF)-alpha-induced protein 8-like 2 (TIPE2 or TNFAIP8L2) is a newly described negative immune regulator and is closely associated with various tumors. However, the expression and roles of TIPE2 in PTC is unknown.

Results

In the present study, TIPE2 upregulation in PTC tissues was found to be negatively associated with tumor size, capsule infiltration, peripheral infiltration and tumor T stage, which could be used to predict tumor invasiveness. TIPE2 overexpression significantly suppressed the viability, proliferation, migration and invasion of PTC cells. Moreover, TIPE2 suppressed tumor invasiveness by inhibiting Rac1, leading to decreased expression of uPA and MMP9.

Conclusions

These results indicate that TIPE2 is a potential biomarker for predicting tumor aggressiveness and suppresses tumor invasiveness in a Rac1-dependent manner.

SUBMITTER: Jia W

PROVIDER: S-EPMC6119276 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

TIPE2 acts as a biomarker for tumor aggressiveness and suppresses cell invasiveness in papillary thyroid cancer (PTC).

Jia Wenyu W Li Zequn Z Chen Junyu J Sun Lei L Liu Chuanqian C Wang Shaping S Chi Jingwei J Niu Jun J Lai Hong H

Cell & bioscience 20180831

<h4>Background</h4>Tumor necrosis factor (TNF)-alpha-induced protein 8-like 2 (TIPE2 or TNFAIP8L2) is a newly described negative immune regulator and is closely associated with various tumors. However, the expression and roles of TIPE2 in PTC is unknown.<h4>Results</h4>In the present study, TIPE2 upregulation in PTC tissues was found to be negatively associated with tumor size, capsule infiltration, peripheral infiltration and tumor T stage, which could be used to predict tumor invasiveness. TIP ...[more]

PMID: 30186591

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Project description:A significant proportion of patients with papillary thyroid cancer (PTC) present with extrathyroidal extension (ETE) and lymph node metastasis (LNM). However, the molecular mechanism of tumor invasiveness in PTC remains to be elucidated. The aim of this study is to understand the role of Hedgehog (Hh) signaling in tumor aggressiveness in patients with PTC. Subjects were patients who underwent thyroidectomy from 2012 to 2013 in a single institution. Frozen or paraffin-embedded tumor tissues with contralateral-matched normal thyroid tissues were collected. Hh signaling activity was analyzed by quantitative RT-PCR (qRT-PCR) and immunohistochemical (IHC) staining. Datasets from Gene Expression Omnibus (GEO) (National Center for Biotechnology Information) were subjected to Gene Set Enrichment Analysis (GSEA). BRAFT1799A and telomerase reverse transcriptase promoter mutation C228T were analyzed by direct sequencing. Among 137 patients with PTC, glioma-associated oncogene homolog 1 (GLI1) group III (patients in whom the ratio of GLI1 messenger ribonucleic acid (mRNA) level in tumor tissue to GLI1 mRNA level in matched normal tissue was in the upper third of the subject population) had elevated risk for ETE (odds ratio [OR] 4.381, 95% confidence interval [CI] 1.414-13.569, P = 0.01) and LNM (OR 5.627, 95% CI 1.674-18.913, P = 0.005). Glioma-associated oncogene homolog 2 (GLI2) group III also had elevated risk for ETE (OR 4.152, 95% CI 1.292-13.342, P = 0.017) and LNM (OR 3.924, 95% CI 1.097-14.042, P = 0.036). GSEA suggested that higher GLI1 expression is associated with expression of the KEGG gene set related to axon guidance (P = 0.031, false discovery rate < 0.05), as verified by qRT-PCR and IHC staining in our subjects.GLI1 and GLI2 expressions were clearly related to aggressive clinicopathological features and aberrant activation of GLI1 involved in the axon guidance pathway. These results may contribute to development of new prognostic markers, as well as novel therapeutic targets.

Project description:The purpose of this study was to identify the optimal tracer kinetic model from T1 -weighted dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data and evaluate whether parameters estimated from the optimal model predict tumor aggressiveness determined from histopathology in patients with papillary thyroid carcinoma (PTC) prior to surgery. In this prospective study, 18 PTC patients underwent pretreatment DCE-MRI on a 3 T MR scanner prior to thyroidectomy. This study was approved by the institutional review board and informed consent was obtained from all patients. The two-compartment exchange model, compartmental tissue uptake model, extended Tofts model (ETM) and standard Tofts model were compared on a voxel-wise basis to determine the optimal model using the corrected Akaike information criterion (AICc) for PTC. The optimal model is the one with the lowest AICc. Statistical analysis included paired and unpaired t-tests and a one-way analysis of variance. Bonferroni correction was applied for multiple comparisons. Receiver operating characteristic (ROC) curves were generated from the optimal model parameters to differentiate PTC with and without aggressive features, and AUCs were compared. ETM performed best with the lowest AICc and the highest Akaike weight (0.44) among the four models. ETM was preferred in 44% of all 3419 voxels. The ETM estimates of Ktrans in PTCs with the aggressive feature extrathyroidal extension (ETE) were significantly higher than those without ETE (0.78 ± 0.29 vs. 0.34 ± 0.18 min-1 , P = 0.005). From ROC analysis, cut-off values of Ktrans , ve and vp , which discriminated between PTCs with and without ETE, were determined at 0.45 min-1 , 0.28 and 0.014 respectively. The sensitivities and specificities were 86 and 82% (Ktrans ), 71 and 82% (ve ), and 86 and 55% (vp ), respectively. Their respective AUCs were 0.90, 0.71 and 0.71. We conclude that ETM Ktrans has shown potential to classify tumors with and without aggressive ETE in patients with PTC.

Project description:Papillary thyroid carcinoma (PTC) is the fastest-growing disease caused by numerous molecular alterations in addition to previously reported DNA mutations. There is a compelling need to identify novel transcriptomic alterations that are associated with the pathogenesis of PTC with potential diagnostic and prognostic implications. Methods: We gathered and compared 242 expression profiles between paired PTC and adjacent normal tissues and identified and validated the coding and long non-coding RNAs (lncRNAs) associated with the extrathyroidal extension (ETE) of 655 PTC patients in two independent cohorts, followed by predicting their interactions with drugs. Co-expression, RNA interaction, Kaplan-Meier survival and multivariate Cox proportional regression analyses were performed to identify dysregulated lncRNAs and genes that correlated with clinical outcomes of PTC. Alternative splicing (AS), RNA circularization, and editing were also compared between transcriptomes to expand the repertoire of molecular alterations in PTC. Results: Numerous genes related to cellular microenvironment and steroid hormone response were associated with the ETE of PTC. Drug susceptibility predictions of the expression signature revealed two highly ranked compounds, 6-bromoindirubin-3'-oxime and lovastatin. Co-expression and RNA interaction analysis revealed the essential role of lncRNAs in PTC pathogenesis by modulating extracellular matrix and cell adhesion. Eight genes and two novel lncRNAs were identified that correlated with the aggressive nature and disease-free survival of PTC. Furthermore, this study provided the transcriptome-wide landscape of circRNAs in PTC and uncovered dissimilar expression profiles among circRNAs originating from the same host gene, suggesting the functional complexity of circRNAs in PTC carcinogenesis. The newly identified AS events in the SERPINA1 and FN1 genes may improve the sensitivity and specificity of these diagnostic biomarkers. Conclusions: Our study uncovered a comprehensive transcriptomic signature associated with the carcinogenesis and aggressive behavior of PTC, as well as presents a catalog of 10 potential biomarkers, which would facilitate PTC prognosis and development of new therapeutic strategies for this cancer.

Dataset Information

TIPE2 acts as a biomarker for tumor aggressiveness and suppresses cell invasiveness in papillary thyroid cancer (PTC).

Background

Results

Conclusions

Publications

TIPE2 acts as a biomarker for tumor aggressiveness and suppresses cell invasiveness in papillary thyroid cancer (PTC).

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