scholarly journals p16 Gene Methylation in Colorectal Tumors: Correlation with Clinicopathological Features and Prognostic Value

2005 ◽  
Vol 23 (2) ◽  
pp. 151-155 ◽  
Author(s):  
M.T. Sanz-Casla ◽  
M.L. Maestro ◽  
M. Vidaurreta ◽  
C. Maestro ◽  
M. Arroyo ◽  
...  
Keyword(s):  
Prognostic Value ◽  
Clinicopathological Features ◽  
Colorectal Tumors ◽  
Gene Methylation ◽  
P16 Gene

Clinicopathological signature and prognostic value of RNA:m5C methyltransferases in gliomas

2020 ◽  
Author(s):  
Peng Wang ◽  
Kai Huang ◽  
Miaojing Wu ◽  
Qing Hu ◽  
Chuming Tao ◽  
...  
Keyword(s):  
Overall Survival ◽  
Risk Score ◽  
Prognostic Value ◽  
Cox Regression ◽  
Roc Curves ◽  
Clinicopathological Features ◽  
Gene Set Enrichment Analysis ◽  
Consensus Clustering ◽  
Score Model ◽  
Genome Atlas

Abstract Background: Glioma is the most common primary intracranial tumor, accounting for the vast majority of intracranial malignant tumors. Aberrant expression of RNA:5-methylcytosine(m5C) methyltransferases has recently been the focus of research relating to the occurrence and progression of tumors. However, the prognostic value of RNA:m5C methyltransferases in glioma remains unclear. This study investigated RNA: m5C methyltransferase expression and defined its clinicopathological signature and prognostic value in gliomas. Methods: We systematically studied the RNA-sequence data of RNA:m5C methyltransferases underlying gliomas in the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets and identified different subtypes using Consensus clustering analysis. Gene Ontology (GO) and Gene Set Enrichment analysis (GSEA) was used to annotate the function of these genes. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm analyses were performed to construct the risk score model. Kaplan-Meier method and Receiver operating characteristic (ROC) curves were used to assess the overall survival of glioma patients. Additionally, Cox proportional regression model analysis was developed to address the connections between the risk scores and clinical factors. Results: Consensus clustering of RNA:m5C methyltransferases identified three clusters of gliomas with different prognostic and clinicopathological features. Meanwhile, Functional annotations demonstrated that RNA:m5C methyltransferases were significantly associated with the malignant progression of gliomas. Thereafter, five RNA:m5C methyltransferase genes were screened to construct a risk score model which can be used to predict not only overall survival but also clinicopathological features in gliomas. ROC curves revealed the significant prognostic ability of this signature. In addition, Multivariate Cox regression analyses indicated that the risk score was an independent prognostic factor for glioma outcome. Conclusion: We demonstrated the role of RNA:m5C methyltransferases in the initiation and progression of glioma. We have expanded on the understanding of the molecular mechanism involved, and provided a unique approach to predictive biomarkers and targeted therapy.

scholarly journals The prognostic value of long noncoding RNA SNHG16 on clinical outcomes in human cancers: a systematic review and meta-analysis

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Chenghao Zhang ◽  
Xiaolei Ren ◽  
Jieyu He ◽  
Wanchun Wang ◽  
Chao Tu ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Prognostic Value ◽  
Meta Analysis ◽  
Clinicopathological Features ◽  
Survival Outcomes ◽  
Tumor Type ◽  
Free Survival ◽  
Expression Levels ◽  
Human Cancers ◽  
Tcga Dataset

Abstract Background Cancer has been a worldwide health problem with a high risk of morbidity and mortality, however ideal biomarkers for effective screening and diagnosis of cancer patients are still lacking. Small nucleolar RNA host gene 16 (SNHG16) is newly identified lncRNA with abnormal expression in several human malignancies. However, its prognostic value remains controversial. This meta-analysis aimed to synthesize available data to clarify the association between SNHG16 expression levels and clinical prognosis value in multiple cancers. Methods Extensive literature retrieval was conducted to identify eligible studies, and data regarding SNHG16 expression levels on survival outcomes and clinicopathological features were extracted and pooled for calculation of the hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs). Forest plots were applied to show the association between SNHG16 expression and survival prognosis. Additionally, The Cancer Genome Atlas (TCGA) dataset was screened and extracted for validation of the results in this meta-analysis. Results A total of eight studies comprising 568 patients were included in the final meta-analysis according to the inclusion and exclusion criteria. In the pooled analysis, high SNHG16 expression significantly predicted worse overall survival (OS) in various cancers (HR = 1.87, 95% CI 1.54–2.26, P < 0.001), and recurrence-free survival (RFS) in bladder cancer (HR = 1.68, 95% CI 1.01–2.79, P = 0.045). Meanwhile, stratified analyses revealed that the survival analysis method, tumor type, sample size, and cut-off value did not alter the predictive value of SNHG16 for OS in cancer patients. In addition, compared to the low SNHG16 expression group, patients with high SNHG16 expression were more prone to worse clinicopathological features, such as larger tumor size, advanced clinical stage, lymph node metastasis (LNM) and distant metastasis (DM). Exploration of TCGA dataset further validated that the upregulated SNHG16 expression predicted unfavorable OS and disease-free survival (DFS) in cancer patients. Conclusions The present study implicated that aberrant expression of lncRNA SNHG16 was strongly associated with clinical survival outcomes in various cancers, and therefore might serve as a promising biomarker for predicting prognosis of human cancers.

Clinicopathological features of nonpolypoid colorectal tumors as viewed from the patients' background

2006 ◽  
Vol 41 (4) ◽  
pp. 325-331 ◽  
Author(s):  
Satoshi Abe ◽  
Takeshi Terai ◽  
Naoto Sakamoto ◽  
Kazuko Beppu ◽  
Akihito Nagahara ◽  
...  
Keyword(s):  
Clinicopathological Features ◽  
Colorectal Tumors

scholarly journals High JAK2 Protein Expression Predicts a Poor Prognosis in Patients with Resectable Pancreatic Ductal Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Yang Song ◽  
Mei-Yue Tang ◽  
Wei Chen ◽  
Zhe Wang ◽  
Si-Liang Wang
Keyword(s):  
Protein Expression ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Poor Prognosis ◽  
Prognostic Value ◽  
Survival Curve ◽  
Clinicopathological Features ◽  
Ductal Adenocarcinoma ◽  
Clinicopathological Analysis ◽  
Primary Focus ◽  
The Relationship

Background. Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. The JAK/STAT signaling pathway is involved in pancreatic cancer tumorigenesis. However, the prognostic value of JAK2 expression in resectable PDAC is unclear. Method. In this study, we performed a clinicopathological analysis of 62 resectable PDAC cases with a primary focus on survival. JAK2 expression was examined by immunohistochemistry. The relationship between JAK2 expression and clinicopathological features and prognosis was analyzed. Results. Survival curve analyses revealed that high levels of JAK2 expression predict a poor prognosis in resectable PDAC patients. Multivariate analysis confirmed that JAK2 expression can predict the prognosis of PDAC. Conclusions. Assessment of JAK2 protein expression may be a promising method to predict prognosis in patients with resectable PDAC.

scholarly journals Gastric Mucinous Cancer Histology: Clinicopathological Characteristics and Prognostic Value

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Chen Jian-Hui ◽  
Cai Shi-Rong ◽  
Wu Hui ◽  
Xu Jian-bo ◽  
Wu Kai-Ming ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Prognostic Value ◽  
Clinicopathological Characteristics ◽  
Survival Outcome ◽  
Clinicopathological Features ◽  
Histological Type ◽  
Biological Behavior ◽  
Term Survival ◽  
Long Term Survival

MC tended toward worse tumor biological behavior and long-term survival outcome compared to WMDC. Moreover, MC also showed worse clinicopathological features and survival outcome in some selected patients. For these reasons, MC should be deemed as a special histological type of gastric cancer with worse clinicopathological features and survival outcome.

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