scholarly journals Reproducibility of SNV-calling in multiple sequencing runs from single tumors

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1508 ◽  
Author(s):  
Dakota Z. Derryberry ◽  
Matthew C. Cowperthwaite ◽  
Claus O. Wilke
Keyword(s):  
Glioblastoma Multiforme ◽  
Large Fraction ◽  
Point Mutations ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Single Nucleotide Variants ◽  
Specific Point ◽  
Single Nucleotide ◽  
Cancer Genome Atlas ◽  
Genome Atlas

We examined 55 technical sequencing replicates of Glioblastoma multiforme (GBM) tumors from The Cancer Genome Atlas (TCGA) to ascertain the degree of repeatability in calling single-nucleotide variants (SNVs). We used the same mutation-calling pipeline on all pairs of samples, and we measured the extent of the overlap between two replicates; that is, how many specific point mutations were found in both replicates. We further tested whether additional filtering increased or decreased the size of the overlap. We found that about half of the putative mutations identified in one sequencing run of a given sample were also identified in the second, and that this percentage remained steady throughout orders of magnitude of variation in the total number of mutations identified (from 23 to 10,966). We further found that using filtering after SNV-calling removed the overlap completely. We concluded that there is variation in the frequency of mutations in GBMs, and that while some filtering approaches preferentially removed putative mutations found in only one replicate, others removed a large fraction of putative mutations found in both.

scholarly journals Analysis of single nucleotide variants of HFE gene and association to survival in The Cancer Genome Atlas GBM data

PLoS ONE ◽  
2017 ◽  
Vol 12 (3) ◽  
pp. e0174778 ◽  
Author(s):  
Sang Y. Lee ◽  
Junjia Zhu ◽  
Anna C. Salzberg ◽  
Bo Zhang ◽  
Dajiang J. Liu ◽  
...  
Keyword(s):  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Hfe Gene ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals A comprehensive analysis of the angiogenesis-related genes in glioblastoma multiforme vs. brain lower grade glioma

2020 ◽  
Vol 78 (1) ◽  
pp. 34-38
Author(s):  
Burcu BITERGE-SUT
Keyword(s):  
Glioblastoma Multiforme ◽  
Malignant Gliomas ◽  
Genetic Alterations ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Lower Grade ◽  
Nonsense Mutations ◽  
Lower Grade Glioma ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Abstract Brain tumors are one of the most common causes of cancer-related deaths around the world. Angiogenesis is critical in high-grade malignant gliomas, such as glioblastoma multiforme. Objective: The aim of this study is to comparatively analyze the angiogenesis-related genes, namely VEGFA, VEGFB, KDR, CXCL8, CXCR1 and CXCR2 in LGG vs. GBM to identify molecular distinctions using datasets available on The Cancer Genome Atlas (TCGA). Methods: DNA sequencing and mRNA expression data for 514 brain lower grade glioma (LGG) and 592 glioblastoma multiforme (GBM) patients were acquired from The Cancer Genome Atlas (TCGA), and the genetic alterations and expression levels of the selected genes were analyzed. Results: We identified six distinct KDR mutations in the LGG patients and 18 distinct KDR mutations in the GBM patients, including missense and nonsense mutations, frame shift deletion and altered splice region. Furthermore, VEGFA and CXCL8 were significantly overexpressed within GBM patients. Conclusions: VEGFA and CXCL8 are important factors for angiogenesis, which are suggested to have significant roles during tumorigenesis. Our results provide further evidence that VEGFA and CXCL8 could induce angiogenesis and promote LGG to progress into GBM. These findings could be useful in developing novel targeted therapeutics approaches in the future.

scholarly journals MicroRNA signatures predict prognosis of patients with glioblastoma multiforme through the Cancer Genome Atlas

Oncotarget ◽  
2017 ◽  
Vol 8 (35) ◽  
pp. 58386-58393 ◽  
Author(s):  
Ying Yuan ◽  
Hua Zhang ◽  
Xuexia Liu ◽  
Zhongming Lu ◽  
Guojun Li ◽  
...  
Keyword(s):  
Glioblastoma Multiforme ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals Evaluating the Prognostic Accuracy of Biomarkers for Glioblastoma Multiforme Using The Cancer Genome Atlas Data

2017 ◽  
Vol 16 ◽  
pp. 117693511773484
Author(s):  
Nan Hu ◽  
Haojie Cheng ◽  
Kevin Zhang ◽  
Randy Jensen
Keyword(s):  
Risk Factors ◽  
Glioblastoma Multiforme ◽  
Roc Curve ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Clinical Risk Factors ◽  
Prognostic Performance ◽  
Prognostic Accuracy ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background: Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor. Previous studies on GBM biomarkers focused on the effect of the biomarkers on overall survival (OS). Until now, no study has been published that evaluates the performance of biomarkers for prognosing OS. We examined the performance of microRNAs, gene expressions, gene signatures, and methylation that were previously identified to be prognostic. In addition, we investigated whether using clinical risk factors in combination with biomarkers can improve the prognostic performance. Methods: The Cancer Genome Atlas, which provides both biomarkers and OS information, was used in this study. The time-dependent receiver operating characteristic (ROC) curve was used to evaluate the prognostic accuracy. Results: For prognosis of OS by 2 years from diagnosis, the area under the ROC curve (AUC) of microRNAs, Mir21 and Mir222, was 0.550 and 0.625, respectively. When age was included in the risk prediction score of these biomarkers, the AUC increased to 0.719 and 0.701, respectively. The SAMSN1 gene expression attains an AUC of 0.563, and the “8-gene” signature identified by Bao achieves an AUC of 0.613. Conclusions: Although some biomarkers are significantly associated with OS, the ability of these biomarkers for prognosing OS events is limited. Incorporating clinical risk factors, such as age, can greatly improve the prognostic performance.

scholarly journals Identification of MicroRNA-Related Tumorigenesis Variants and Genes in the Cancer Genome Atlas (TCGA) Data

Genes ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 953
Author(s):  
Chang Li ◽  
Brian Wu ◽  
Han Han ◽  
Jeff Zhao ◽  
Yongsheng Bai ◽  
...  
Keyword(s):  
Mirna Target ◽  
Cancer Genomics ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Messenger Rnas ◽  
Single Nucleotide Variants ◽  
Functional Variants ◽  
Cancer Genome Atlas ◽  
Risk Of Cancer ◽  
Genome Atlas

MicroRNAs (miRNAs) are a class of small non-coding RNA that can down-regulate their targets by selectively binding to the 3′ untranslated region (3′UTR) of most messenger RNAs (mRNAs) in the human genome. Single nucleotide variants (SNVs) located in miRNA target sites (MTS) can disrupt the binding of targeting miRNAs. Anti-correlated miRNA–mRNA pairs between normal and tumor tissues obtained from The Cancer Genome Atlas (TCGA) can reveal important information behind these SNVs on MTS and their associated oncogenesis. In this study, using previously identified anti-correlated miRNA–mRNA pairs in 15 TCGA cancer types and publicly available variant annotation databases, namely dbNSFP (database for nonsynonymous SNPs’ functional predictions) and dbMTS (database of miRNA target site SNVs), we identified multiple functional variants and their gene products that could be associated with various types of cancers. We found two genes from dbMTS and 33 from dbNSFP that passed our stringent filtering criteria (e.g., pathogenicity). Specifically, from dbMTS, we identified 23 candidate genes, two of which (BMPR1A and XIAP) were associated with diseases that increased the risk of cancer in patients. From dbNSFP, we identified 65 variants located in 33 genes that were likely pathogenic and had a potential causative relationship with cancer. This study provides a novel way of utilizing TCGA data and integrating multiple publicly available databases to explore cancer genomics.

scholarly journals Exceptional Chemotherapy Response in Metastatic Colorectal Cancer Associated With Hyper-Indel–Hypermutated Cancer Genome and Comutation of POLD1 and MLH1

2017 ◽  
pp. 1-12
Author(s):  
Manish R. Sharma ◽  
James T. Auman ◽  
Nirali M. Patel ◽  
Juneko E. Grilley-Olson ◽  
Xiaobei Zhao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Somatic Mutation ◽  
Mutation Rate ◽  
Germ Line ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Response To Chemotherapy ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Purpose A 73-year-old woman with metastatic colon cancer experienced a complete response to chemotherapy with dose-intensified irinotecan that has been durable for 5 years. We sequenced her tumor and germ line DNA and looked for similar patterns in publicly available genomic data from patients with colorectal cancer. Patients and Methods Tumor DNA was obtained from a biopsy before therapy, and germ line DNA was obtained from blood. Tumor and germline DNA were sequenced using a commercial panel with approximately 250 genes. Whole-genome amplification and exome sequencing were performed for POLE and POLD1. A POLD1 mutation was confirmed by Sanger sequencing. The somatic mutation and clinical annotation data files from the colon (n = 461) and rectal (n = 171) adenocarcinoma data sets were downloaded from The Cancer Genome Atlas data portal and analyzed for patterns of mutations and clinical outcomes in patients with POLE- and/or POLD1-mutated tumors. Results The pattern of alterations included APC biallelic inactivation and microsatellite instability high (MSI-H) phenotype, with somatic inactivation of MLH1 and hypermutation (estimated mutation rate > 200 per megabase). The extremely high mutation rate led us to investigate additional mechanisms for hypermutation, including loss of function of POLE. POLE was unaltered, but a related gene not typically associated with somatic mutation in colon cancer, POLD1, had a somatic mutation c.2171G>A [p.Gly724Glu]. Additionally, we noted that the high mutation rate was largely composed of dinucleotide deletions. A similar pattern of hypermutation (dinucleotide deletions, POLD1 mutations, MSI-H) was found in tumors from The Cancer Genome Atlas. Conclusion POLD1 mutation with associated MSI-H and hyper-indel–hypermutated cancer genome characterizes a previously unrecognized variant of colon cancer that was found in this patient with an exceptional response to chemotherapy.

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