Development of a risk scoring system for patients with papillary thyroid cancer

Pak, Kyoungjune; Kim, Yun Hak; Suh, Sunghwan; Goh, Tae Sik; Jeong, Dae Cheon; Kim, Seong Jang; Kim, In Joo; Han, Myoung‐Eun; Oh, Sae‐Ock

doi:10.1111/jcmm.14208

Cited by 14 publications

(11 citation statements)

References 29 publications

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“…In addition, the eighth edition of AJCC was generated to predict the risk of survival (death), not the risk of recurrence; however, since the eighth edition of the AJCC and the 2015 ATA guideline are the most commonly used prognostic systems in clinical settings, we adopted both of them in this study. Furthermore, since we developed our RSS based on data from previous meta-analyses, we could not include risk factors that were not reported in the meta-analyses, such as mRNA [ 20 ] or miRNA markers [ 21 ].…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Risk Scoring System Derived from Meta-Analyses of Papillary Thyroid Cancer

et al. 2020

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Background: The aim of this study was to develop a scoring system to stratify the risk of papillary thyroid cancer (PTC) and to select the proper management. Methods: We performed a systematic search of MEDLINE and Embase. Data regarding patients' prognoses were obtained from the included studies. Odds ratios (ORs) with statistical significance were extracted from the publications. To generate a risk scoring system (RSS), ORs were summed (RSS1), and summed after natural-logarithmic transformation (RSS2). RSS1 and RSS2 were compared to the eighth edition of the American Joint Committee on Cancer (AJCC) staging system and the 2015 American Thyroid Association (ATA) guidelines for thyroid nodules and differentiated thyroid carcinoma. Results: Five meta-analyses were eligible for inclusion in the study. Eight variables (sex, tumour size, extrathyroidal extension, BRAF mutation, TERT mutation, histologic subtype, lymph node metastasis, and distant metastasis) were included. RSS1 was the best of the analysed models. Conclusion: We developed and validated a new RSS derived from previous meta-analyses for patients with PTC. This RSS seems to be superior to previously published systems.

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Section: Discussionmentioning

confidence: 99%

Development and Validation of a Risk Scoring System Derived from Meta-Analyses of Papillary Thyroid Cancer

et al. 2020

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“…To identify the involvement of GABRQ in ccRCC, experiments need to be conducted at the protein level. However, there are numerous studies that have determined prognostic biomarkers based on mRNA expression (for example oncotype DX (30), MammaPrint (31) and gene signatures tests (19,32–34)). Although the present study did not confirm GABRQ function at the protein level, mRNA-based studies are emerging in this field, and represent time- and cost-effective methods.…”

Section: Discussionmentioning

confidence: 99%

GABRQ expression is a potential prognostic marker for patients with clear cell renal cell carcinoma

Lee

Hong

et al. 2019

Oncol Lett

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Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. Novel biomarkers of ccRCC may provide crucial information on tumor features and prognosis. The present study aimed to determine whether the expression of γ-aminobutyric acid (GABA) A receptor subunit θ (GABRQ) could serve as a novel prognostic marker of ccRCC. GABA is the main inhibitory neurotransmitter in the brain that activates the receptor GABAA, which is comprised of three subunit isoforms: GABRA3, GABRB3 and GABRQ. A recent study reported that GABRQ is involved in the initiation and progression of hepatocellular carcinoma; however, the role of GABRQ in ccRCC remains unknown. In the present study, clinical and transcriptomic data were obtained from cohorts of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). Differential GABRQ expression levels among early (TI and II), late (TIII and IV), nonmetastatic (M0) and metastatic (M1, primary tumor) stages of ccRCC samples were then identified. Furthermore, the use of GABRQ as a prognostic gene was analyzed using Uno's C-index based on the time-dependent area under the curve (AUC), the AUC of the receiver operating characteristic curve at 5 years, the Kaplan-Meier survival curve and multivariate analysis. The survival curve analysis revealed that low GABRQ mRNA expression was significantly associated with a poor prognosis of ccRCC (P<0.001 and P=0.0012 for TCGA and ICGC data, respectively). In addition, analyses of the C-index and AUC values further supported this discriminatory power. Furthermore, the prognostic value of GABRQ mRNA expression was confirmed by multivariate Cox regression analysis. Taken together, these results suggested that GABRQ mRNA expression may be considered as a novel prognostic biomarker of ccRCC.

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“…Tumor RNA sequencing (RNA-seq) data have been used to identify prognostic genes or gene signatures, some of which have been incorporated into clinical guidelines ( Ha et al, 2019 ; Pak et al, 2019 ). Several studies have been conducted on clinical predictors of survival, and the prognostic clinical factors reported so far include age, extent of resection, Karnofsky Performance Scale score, duration of symptoms, and tumor grade in GBM ( Lacroix et al, 2001 ; McGirt et al, 2009 ).…”

Section: Introductionmentioning

confidence: 99%

SOCS3 is Related to Cell Proliferation in Neuronal Tissue: An Integrated Analysis of Bioinformatics and Experiments

Sung

Lee

et al. 2021

Front. Genet.

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Glioma is the most common primary malignant tumor that occurs in the central nervous system. Gliomas are subdivided according to a combination of microscopic morphological, molecular, and genetic factors. Glioblastoma (GBM) is the most aggressive malignant tumor; however, efficient therapies or specific target molecules for GBM have not been developed. We accessed RNA-seq and clinical data from The Cancer Genome Atlas, the Chinese Glioma Genome Atlas, and the GSE16011 dataset, and identified differentially expressed genes (DEGs) that were common to both GBM and lower-grade glioma (LGG) in three independent cohorts. The biological functions of common DEGs were examined using NetworkAnalyst. To evaluate the prognostic performance of common DEGs, we performed Kaplan-Meier and Cox regression analyses. We investigated the function of SOCS3 in the central nervous system using three GBM cell lines as well as zebrafish embryos. There were 168 upregulated genes and 50 downregulated genes that were commom to both GBM and LGG. Through survival analyses, we found that SOCS3 was the only prognostic gene in all cohorts. Inhibition of SOCS3 using siRNA decreased the proliferation of GBM cell lines. We also found that the zebrafish ortholog, socs3b, was associated with brain development through the regulation of cell proliferation in neuronal tissue. While additional mechanistic studies are necessary, our results suggest that SOCS3 is an important biomarker for glioma and that SOCS3 is related to the proliferation of neuronal tissue.

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Development of a risk scoring system for patients with papillary thyroid cancer

Cited by 14 publications

References 29 publications

Development and Validation of a Risk Scoring System Derived from Meta-Analyses of Papillary Thyroid Cancer

Development and Validation of a Risk Scoring System Derived from Meta-Analyses of Papillary Thyroid Cancer

GABRQ expression is a potential prognostic marker for patients with clear cell renal cell carcinoma

SOCS3 is Related to Cell Proliferation in Neuronal Tissue: An Integrated Analysis of Bioinformatics and Experiments

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