Overview of Next-Generation Sequencing Technologies Slatko, Barton E; Gardner, Andrew F; Ausubel, Frederick M
Current protocols in molecular biology (Print),
04/2018, Letnik:
122, Številka:
1
Journal Article
Nearly all infectious agents contain DNA or RNA genomes, making sequencing an attractive approach for pathogen detection. The cost of high-throughput or next-generation sequencing has been reduced by ...several orders of magnitude since its advent in 2004, and it has emerged as an enabling technological platform for the detection and taxonomic characterization of microorganisms in clinical samples from patients. This review focuses on the application of untargeted metagenomic next-generation sequencing to the clinical diagnosis of infectious diseases, particularly in areas in which conventional diagnostic approaches have limitations. The review covers ( a) next-generation sequencing technologies and common platforms, ( b) next-generation sequencing assay workflows in the clinical microbiology laboratory, ( c) bioinformatics analysis of metagenomic next-generation sequencing data, ( d) validation and use of metagenomic next-generation sequencing for diagnosing infectious diseases, and ( e) significant case reports and studies in this area. Next-generation sequencing is a new technology that has the promise to enhance our ability to diagnose, interrogate, and track infectious diseases.
Background
Gastroesophageal cancers are often grouped together even though cancers that originate in the esophagus often exhibit different histological features, geographical distribution, risk ...factors, and clinical characteristics than those originating in the stomach. Herein, we aimed to compare the molecular characteristics of three different gastroesophageal cancer types: esophageal squamous cell carcinoma (ESCC), esophageal adenocarcinoma (EAC), and gastric adenocarcinoma (GAC).
Subjects, Materials, and Methods
In total, 3,342 gastroesophageal cancers were examined. Next‐generation sequencing was performed on genomic DNA isolated from formalin‐fixed paraffin‐embedded tumor samples using the NextSeq platform. Tumor mutational burden was measured by counting all nonsynonymous missense mutations, and microsatellite instability was examined at over 7,000 target microsatellite loci. Immunohistochemistry and in situ hybridization techniques were also performed.
Results
When compared with EAC and GAC, ESCC showed significantly lower mutational rates within APC, ARID1A, CDH1, KRAS, PTEN, and SMAD4, whereas more frequent mutations were observed in BAP1, CDKN2A, FOXO3, KMT2D, MSH6, NOTCH1, RB1, and SETD2. Human epidermal growth receptor 2 (HER2) overexpression was observed in 13% of EAC compared with 6% of GAC and 1% of ESCC (p < .0001). Compared with EAC and GAC, ESCC exhibited higher expression of programmed death‐ligand 1 (PD‐L1) (27.7% vs. 7.5% vs. 7.7%, p < .0001). We observed that FGF3, FGF4, FGF19, CCND1 (co‐localized on 11q13), and FGFR1 were significantly more amplified in ESCC compared with EAC and GAC (p < .0001).
Conclusion
Molecular comparisons between ESCC, EAC, and GAC revealed distinct differences between squamous cell carcinomas and adenocarcinomas in each platform tested. Different prevalence of HER2/neu overexpression and amplification, and immune‐related biomarkers between ESCC, EAC, and GAC, suggests different sensitivity to HER2‐targeted therapy and immune checkpoint inhibition. These findings bring into question the validity of grouping patients with EAC and ESCC together in clinical trials and provide insight into molecular features that may represent novel therapeutic targets.
Implications for Practice
This study highlights the genomic heterogeneity of gastroesophageal cancers, showing striking molecular differences between tumors originating from different locations. Moreover, this study showed that esophageal squamous cell carcinomas exhibit a unique molecular profile, whereas gastric adenocarcinomas and esophageal adenocarcinomas have some similarities, supporting the fact that adenocarcinomas and squamous cell carcinomas are completely different diseases, irrespective of the tumor location. This raises the question of whether treatment of gastroesophageal tumors should be determined according to histological subtype and molecular targets rather than anatomical site. These findings provide insights that could enable physicians to better select patients and inform therapeutic choices in order to improve clinical outcome.
摘要
背景。 虽然起源于食管的肿瘤与起源于胃部的肿瘤在组织学特征、区域分布、危险因素和临床特征等往往表现不同,但胃食管肿瘤往往被归为一类。在此,我们比较了三种不同类型的胃食管肿瘤的分子特征:食管鳞状细胞癌 (ESCC)、食管腺癌 (EAC) 和胃腺癌 (GAC)。
受试者、材料及方法。 共3 342例胃食管肿瘤患者接受了检查。利用 NextSeq 平台,从福尔马林固定石蜡包埋肿瘤标本中分离出基因组 DNA,进行了下一代测序。通过计数所有非同义错义突变来测量肿瘤突变负担,并在7 000多个靶微卫星位点上检测微卫星不稳定性。同时也使用了免疫组化和原位杂交技术。
结果。 与EAC 和 GAC相比, ESCC在 APC、ARID1A、CDH1、KRAS、PTEN和 SMAD4中的突变率明显降低,而突变更频繁地出现在BAP1、CDKN2A、FOXO3、KMT2D、MSH6、NOTCH1、RB1和 SETD2。观察到 EAC 的人表皮生长因子受体2(HER2) 超表达为13%,而 GAC 为6%,ESCC 为1%(p<0.0001)。与 EAC 和 GAC 相比,ESCC 表现为程序性死亡配体1(PD‐L1)(27.7% vs. 7.5% vs. 7.7%,p<0.000 1)高表达。与 EAC 和 GAC 相比,我们观察到 FGF3、FGF4、FGF19、CCND1 (共定位于11q13)及FGFR1 在 ESCC 中明显扩增 (p<0.0001)。
结论。 通过 ESCC、EAC 和 GAC 的分子比较显示,在每一个平台的测试中,鳞状细胞癌和腺癌之间有明显的差异。ESCC、EAC 和 GAC 之间的 HER2/neu 过表达和扩增以及与免疫相关的生物标记物的不同发生率表明,对 HER2 靶向治疗和免疫检查点抑制剂具有不同的敏感性。这些发现引起了人们对临床试验中将 EAC 和 ESCC 患者归为一组的有效性的质疑,并对可能代表新治疗靶点的分子特征提出了深刻见解。
实践意义: 这项研究突出了胃食管肿瘤的基因组异质性,显示源自不同部位的肿瘤之间有明显的分子差异。此外,本研究还发现食管鳞状细胞癌具有独特的分子特征,而胃腺癌和食管腺癌有一些相似之处,在不考虑肿瘤部位的情况下,这支持了腺癌和鳞状细胞癌是完全不同的疾病这一事实。这就提出了一个问题:是否应该根据组织学亚型和分子靶点而不是解剖部位来确定胃食管肿瘤的治疗方案。这些发现提出的深刻见解使医生能够更好地甄别患者,并告知治疗选项,以改善临床效果。
To improve the precision of targeted and conventional therapy, the molecular profiles of gastroesophageal tumors were assessed, with the aim of comparing the molecular characteristics of esophageal adenocarcinoma, esophageal squamous cell carcinoma, and gastric adenocarcinoma. Results are reported in this article.
ABSTRACT
Here, we describe an overview and update on GeneMatcher (http://www.genematcher.org), a freely accessible Web‐based tool developed as part of the Baylor‐Hopkins Center for Mendelian ...Genomics. We created GeneMatcher with the goal of identifying additional individuals with rare phenotypes who had variants in the same candidate disease gene. We also wanted to facilitate connections to basic scientists working on orthologous genes in model systems with the goal of connecting their work to human Mendelian phenotypes. Meeting these goals will enhance the identification of novel Mendelian genes. Launched in September, 2013, GeneMatcher now has 2,178 candidate genes from 486 submitters spread across 38 countries entered in the database (June 1, 2015). GeneMatcher is also part of the Matchmaker Exchange (http://matchmakerexchange.org/) with an Application Programing Interface enabling submitters to query other databases of genetic variants and phenotypes without having to create accounts and data entries in multiple systems.
Although vast technological advances have been made and genetic software packages are growing in number, it is not a trivial task to analyse SNP data. We announce a new r package, dartr, enabling the ...analysis of single nucleotide polymorphism data for population genomic and phylogenomic applications. dartr provides user‐friendly functions for data quality control and marker selection, and permits rigorous evaluations of conformation to Hardy–Weinberg equilibrium, gametic‐phase disequilibrium and neutrality. The package reports standard descriptive statistics, permits exploration of patterns in the data through principal components analysis and conducts standard F‐statistics, as well as basic phylogenetic analyses, population assignment, isolation by distance and exports data to a variety of commonly used downstream applications (e.g., newhybrids, faststructure and phylogeny applications) outside of the r environment. The package serves two main purposes: first, a user‐friendly approach to lower the hurdle to analyse such data—therefore, the package comes with a detailed tutorial targeted to the r beginner to allow data analysis without requiring deep knowledge of r. Second, we use a single, well‐established format—genlight from the adegenet package—as input for all our functions to avoid data reformatting. By strictly using the genlight format, we hope to facilitate this format as the de facto standard of future software developments and hence reduce the format jungle of genetic data sets. The dartr package is available via the r CRAN network and GitHub.
TP53 mutations are ubiquitous in high‐grade serous ovarian carcinomas (HGSOC), and the presence of TP53 mutation discriminates between high and low‐grade serous carcinomas and is now an important ...biomarker for clinical trials targeting mutant p53. p53 immunohistochemistry (IHC) is widely used as a surrogate for TP53 mutation but its accuracy has not been established. The objective of this study was to test whether improved methods for p53 IHC could reliably predict TP53 mutations independently identified by next generation sequencing (NGS). Four clinical p53 IHC assays and tagged‐amplicon NGS for TP53 were performed on 171 HGSOC and 80 endometrioid carcinomas (EC). p53 expression was scored as overexpression (OE), complete absence (CA), cytoplasmic (CY) or wild type (WT). p53 IHC was evaluated as a binary classifier where any abnormal staining predicted deleterious TP53 mutation and as a ternary classifier where OE, CA or WT staining predicted gain‐of‐function (GOF or nonsynonymous), loss‐of‐function (LOF including stopgain, indel, splicing) or no detectable TP53 mutations (NDM), respectively. Deleterious TP53 mutations were detected in 169/171 (99%) HGSOC and 7/80 (8.8%) EC. The overall accuracy for the best performing IHC assay for binary and ternary prediction was 0.94 and 0.91 respectively, which improved to 0.97 (sensitivity 0.96, specificity 1.00) and 0.95 after secondary analysis of discordant cases. The sensitivity for predicting LOF mutations was lower at 0.76 because p53 IHC detected mutant p53 protein in 13 HGSOC with LOF mutations. CY staining associated with LOF was seen in 4 (2.3%) of HGSOC. Optimized p53 IHC can approach 100% specificity for the presence of TP53 mutation and its high negative predictive value is clinically useful as it can exclude the possibility of a low‐grade serous tumour. 4.1% of HGSOC cases have detectable WT staining while harboring a TP53 LOF mutation, which limits sensitivity for binary prediction of mutation to 96%.
DNA metabarcoding offers new perspectives in biodiversity research. This recently developed approach to ecosystem study relies heavily on the use of next‐generation sequencing (NGS) and thus calls ...upon the ability to deal with huge sequence data sets. The obitools package satisfies this requirement thanks to a set of programs specifically designed for analysing NGS data in a DNA metabarcoding context. Their capacity to filter and edit sequences while taking into account taxonomic annotation helps to set up tailor‐made analysis pipelines for a broad range of DNA metabarcoding applications, including biodiversity surveys or diet analyses. The obitools package is distributed as an open source software available on the following website: http://metabarcoding.org/obitools. A Galaxy wrapper is available on the GenOuest core facility toolshed: http://toolshed.genouest.org.
PDF
