scholarly journals Identification of Potential Key Genes for Pathogenesis and Prognosis in Prostate Cancer by Integrated Analysis of Gene Expression Profiles and the Cancer Genome Atlas

2020 ◽  
Vol 10 ◽  
Author(s):  
Shuang Liu ◽  
Wenxin Wang ◽  
Yan Zhao ◽  
Kaige Liang ◽  
Yaojiang Huang
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Integrated Analysis ◽  
Cancer Genome Atlas ◽  
Key Genes ◽  
Genome Atlas

Using machine learning method to identify MYLK as a novel marker to predict biochemical recurrence in prostate cancer

2021 ◽  
Vol 15 (1) ◽  
pp. 29-41
Author(s):  
Peng Qiao ◽  
Di Zhang ◽  
Song Zeng ◽  
Yicun Wang ◽  
Biao Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Biochemical Recurrence ◽  
Surgical Margin ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Support Vector ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Aim: This study aims to identify novel marker to predict biochemical recurrence (BCR) in prostate cancer patients after radical prostatectomy with negative surgical margin. Materials & methods: The Cancer Genome Atlas database, Gene Expression Omnibus database and Cancer Cell Line Encyclopedia database were employed. The ensemble support vector machine-recursive feature elimination method was performed to select crucial gene for BCR. Results: We identified MYLK as a novel and independent biomarker for BCR in The Cancer Genome Atlas training cohort and confirmed in four independent Gene Expression Omnibus validation cohorts. Multi-omic analysis suggested that MYLK was a DNA methylation-driven gene. Additionally, MYLK had significant positive correlations with immune infiltrations. Conclusion: MYLK was identified and validated as a novel, robust and independent biomarker for BCR in prostate cancer.

scholarly journals Screening and Identifying m6A Regulators as an Independent Prognostic Biomarker in Pancreatic Cancer Based on The Cancer Genome Atlas Database

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Bi Lin ◽  
Yangyang Pan ◽  
Dinglai Yu ◽  
Shengjie Dai ◽  
Hongwei Sun ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Tumor Therapy ◽  
Disease Free Survival ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background. Pancreatic cancer is one of the most malignant tumors of the digestive system, and its treatment has rarely progressed for the last two decades. Studies on m6A regulators for the past few years have seemingly provided a novel approach for malignant tumor therapy. m6A-related factors may be potential biomarkers and therapeutic targets. This research is focused on the gene characteristics and clinical values of m6A regulators in predicting prognosis in pancreatic cancer. Methods. In our study, we obtained gene expression profiles with copy number variation (CNV) data and clinical characteristic data of 186 patients with pancreatic cancer from The Cancer Genome Atlas (TCGA) portal. Then, we determined the alteration of m6a regulators and their correlation with clinicopathological features using the log-rank tests, Cox regression model, and chi-square test. Additionally, we validated the prognostic value of m6A regulators in the International Cancer Genome Consortium (ICGC). Results. The results suggested that pancreatic cancer patients with ALKBH5 CNV were associated with worse overall survival and disease-free survival than those with diploid genes. Additionally, upregulation of the writer gene ALKBH5 had a positive correlation with the activation of AKT pathways in the TCGA database. Conclusion. Our study not only demonstrated genetic characteristic changes of m6A-related genes in pancreatic cancer and found a strong relationship between the changes of ALKBH5 and poor prognosis but also provided a novel therapeutic target for pancreatic cancer therapy.

scholarly journals Pan-cancer analysis of transcriptional metabolic dysregulation using The Cancer Genome Atlas

2018 ◽  
Author(s):  
SR Rosario ◽  
MD Long ◽  
HC Affronti ◽  
AM Rowsam ◽  
KH Eng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Metabolic Flux ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Targeted Therapeutics ◽  
Bioinformatics Pipeline ◽  
Metabolic Dysregulation ◽  
Pathway Gene ◽  
Cancer Genome Atlas ◽  
Genome Atlas

AbstractUnderstanding the levels of metabolic dysregulation in different disease settings is vital for the safe and effective incorporation of metabolism-targeted therapeutics in the clinic. Using transcriptomic data from 10,704 tumor and normal samples from The Cancer Genome Atlas, across 26 disease sites, we developed a novel bioinformatics pipeline that distinguishes tumor from normal tissues, based on differential gene expression for 114 metabolic pathways. This pathway dysregulation was confirmed in separate patient populations, further demonstrating the robustness of this approach. A bootstrapping simulation was then applied to assess whether these alterations were biologically meaningful, rather than expected by chance. We provide distinct examples of the types of analysis that can be accomplished with this tool to understand cancer specific metabolic dysregulation, highlighting novel pathways of interest in both common and rare disease sites. Utilizing a pathway mapping approach to understand patterns of metabolic flux, differential drug sensitivity, can accurately be predicted. Further, the identification of Master Metabolic Transcriptional Regulators, whose expression was highly correlated with pathway gene expression, explains why metabolic differences exist in different disease sites. We demonstrate these also have the ability to segregate patient populations and predict responders to different metabolism-targeted therapeutics.

scholarly journals A six-gene-based signature for breast cancer radiotherapy sensitivity prediction

2020 ◽  
Author(s):  
Xing Chen ◽  
Junjie Zheng ◽  
Min ling Zhuo ◽  
Ailong Zhang ◽  
Zhenhui You
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Regression Analysis ◽  
Cox Regression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis ◽  
Breast Cancer Radiotherapy

Abstract Background: Breast cancer (BRCA) represents the most common malignancy among women worldwide that with high mortality. Radiotherapy is a prevalent therapeutic for BRCA that with heterogeneous effectiveness among patients. Methods: we proposed to develop a gene expression-based signature for BRCA radiotherapy sensitivity prediction. Gene expression profiles of BRCA samples from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) were obtained and used as training and independent testing dataset, respectively. Differential expression genes (DEGs) in BRCA tumor samples compared with their paracancerous samples in the training set were identified by using edgeR Bioconductor package followed by dimensionality reduction through autoencoder method and univariate Cox regression analysis to screen genes among DEGs that with significant prognosis significance in patients that were previously treated with radiation. LASSO Cox regression method was applied to screen optimal genes for constructing radiotherapy sensitivity prediction signature. Results: 603 DEGs were obtained in BRCA tumor samples, and seven out of which were retained after univariate cox regression analysis. LASSO Cox regression analysis finally remained six genes based on which the radiotherapy sensitivity prediction model was constructed. The signature was proved to be robust in both training and independent testing sets and an independent marker for BRCA radiotherapy sensitivity prediction. Conclusions: this study should be helpful for BRCA patients’ therapeutics selection and clinical decision.

scholarly journals The role of miR-92b in cholangiocarcinoma patients

2018 ◽  
Vol 33 (3) ◽  
pp. 293-300 ◽  
Author(s):  
Min-hang Zhou ◽  
Hong-wei Zhou ◽  
Mo Liu ◽  
Jun-zhong Sun
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Positive Regulation ◽  
Cancer Genome Atlas ◽  
High Level ◽  
Genome Atlas

Purpose: The role of microRNA (miRNA) in cholangiocarcinoma was not clear. The aim of this study was to find the potential diagnostic and prognostic miRNA in cholangiocarcinoma patients. Methods: The miRNA expression profiles in cholangiocarcinoma patients from The Cancer Genome Atlas and Gene Expression Omnibus (GSE53870) were analyzed. The comparison of overall survival was performed using the Kaplan–Meier method. The targeted genes of prognostic miRNA were identified in miRanda, PicTar, or TargetScan, and their cell signaling pathways were analyzed by the Database for Annotation, Visualization and Integrated Discovery. Results: In The Cancer Genome Atlas and the Gene Expression Omnibus miRNA dataset, miR-92b and miR-99a were found with concordant directionality, up-regulated and down-regulated, respectively. In The Cancer Genome Atlas survival data, patients with the high level of miR-99b had obviously shorter overall survival time ( P=0.038). However, the level of miR-99a was not found to be significant. The 17 shared target genes of miR-92b were identified, such as DAB21IP, BCL21L11, SPHK2, PER2, and TSC1. The related pathways included positive regulation of transcription, positive regulation of cellular biosynthetic process, regulation of programmed cell death, etc. Conclusion: miR-92b was up-regulated in cholangiocarcinoma compared with normal controls. The high level of miR-92b was associated with adverse outcomes in cholangiocarcinoma patients, which might be partly explained by the targeted genes of miR-92b and their signaling pathways.

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