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Identification of major factors associated with failed clinical molecular oncology testing performed by next generation sequencing (NGS).

ABSTRACT: DNA analysis by NGS has become important to direct the clinical care of cancer patients. However, NGS is not successful in all cases, and the factors responsible for test failures have not been systematically evaluated.A series of 1528 solid and hematolymphoid tumor specimens was tested by an NGS comprehensive cancer panel during 2012-2014. DNA was extracted and 2×101 bp paired-end sequence reads were generated on cancer-related genes utilizing Illumina HiSeq and MiSeq platforms.Testing was unsuccessful in 343 (22.5%) specimens. The failure was due to insufficient tissue (INST) in 223/343 (65%) cases, insufficient DNA (INS-DNA) in 99/343 (28.9%) cases, and failed library (FL) in 21/343 (6.1%) cases. 87/99 (88%) of the INS-DNA cases had below 10 ng DNA available for testing. Factors associated with INST and INS-DNA failures were site of biopsy (SOB) and type of biopsy (TOB) (both p < 0.0001), and clinical setting of biopsy (CSB, initial diagnosis or recurrence) (p < 0.0001). Factors common to INST and FL were age of specimen (p ≤ 0.006) and tumor viability (p ≤ 0.05). Factors common to INS-DNA and FL were DNA purity and DNA degradation (all p ≤ 0.005). In multivariate analysis, common predictors for INST and INS-DNA included CSB (p = 0.048 and p < 0.0001) and TOB (both p ≤ 0.003), respectively. SOB (p = 0.004) and number of cores (p = 0.001) were specific for INS-DNA, whereas TOB and DNA degradation were associated with FL (p = 0.04 and 0.02, respectively).Pre-analytical causes (INST and INS-DNA) accounted for about 90% of all failed cases; independent of test design. Clinical setting; site and type of biopsy; and number of cores used for testing all correlated with failure. Accounting for these factors at the time of tissue biopsy acquisition could improve the analytic success rate.

SUBMITTER: Al-Kateb H

PROVIDER: S-EPMC5528718 | biostudies-other | 2015 Nov

REPOSITORIES: biostudies-other

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Project description:Radical new possibilities of improved treatment of cancer are on offer from an advanced medical technology already demonstrating its significance: next-generation sequencing (NGS). This refined testing provides unprecedentedly precise diagnoses and permits the use of focused and highly personalized treatments. However, across regions globally, many cancer patients will continue to be denied the benefits of NGS as long as some of the yawning gaps in its implementation remain unattended. The challenges at the regional and national levels are linked because putting the solutions into effect is highly dependent on cooperation between regional- and national-level cooperation, which could be hindered by shortfalls in interpretation or understanding. The aim of the paper was to define and explore the necessary conditions for NGS and make recommendations for effective implementation based on extensive exchanges with policy makers and stakeholders. As a result, the European Alliance for Personalised Medicine (EAPM) developed a maturity framework structured around demand-side and supply-side issues to enable interested stakeholders in different countries to self-evaluate according to a common matrix. A questionnaire was designed to identify the current status of NGS implementation, and it was submitted to different experts in different institutions globally. This revealed significant variability in the different aspects of NGS uptake. Within different regions globally, to ensure those conditions are right, this can be improved by linking efforts made at the national level, where patients have needs and where care is delivered, and at the global level, where major policy initiatives in the health field are underway or in preparation, many of which offer direct or indirect pathways for building those conditions. In addition, in a period when consensus is still incomplete and catching up is needed at a political level to ensure rational allocation of resources-even within individual countries-to enable the best ways to make the necessary provisions for NGS, a key recommendation is to examine where closer links between national and regional actions could complement, support, and mutually reinforce efforts to improve the situation for patients.

Project description:BACKGROUND:Next-Generation Sequencing (NGS) technology has exceptionally increased the ability to sequence DNA in a massively parallel and cost-effective manner. Nevertheless, NGS data analysis requires bioinformatics skills and computational resources well beyond the possibilities of many "wet biology" laboratories. Moreover, most of projects only require few sequencing cycles and standard tools or workflows to carry out suitable analyses for the identification and annotation of genes, transcripts and splice variants found in the biological samples under investigation. These projects can take benefits from the availability of easy to use systems to automatically analyse sequences and to mine data without the preventive need of strong bioinformatics background and hardware infrastructure. RESULTS:To address this issue we developed an automatic system targeted to the analysis of NGS data obtained from large-scale transcriptome studies. This system, we named NGS-Trex (NGS Transcriptome profile explorer) is available through a simple web interface http://www.ngs-trex.org and allows the user to upload raw sequences and easily obtain an accurate characterization of the transcriptome profile after the setting of few parameters required to tune the analysis procedure. The system is also able to assess differential expression at both gene and transcript level (i.e. splicing isoforms) by comparing the expression profile of different samples.By using simple query forms the user can obtain list of genes, transcripts, splice sites ranked and filtered according to several criteria. Data can be viewed as tables, text files or through a simple genome browser which helps the visual inspection of the data. CONCLUSIONS:NGS-Trex is a simple tool for RNA-Seq data analysis mainly targeted to "wet biology" researchers with limited bioinformatics skills. It offers simple data mining tools to explore transcriptome profiles of samples investigated taking advantage of NGS technologies.

Project description:BackgroundIn recent years more than 20 assemblers have been proposed to tackle the hard task of assembling NGS data. A common heuristic when assembling a genome is to use several assemblers and then select the best assembly according to some criteria. However, recent results clearly show that some assemblers lead to better statistics than others on specific regions but are outperformed on other regions or on different evaluation measures. To limit these problems we developed GAM-NGS (Genomic Assemblies Merger for Next Generation Sequencing), whose primary goal is to merge two or more assemblies in order to enhance contiguity and correctness of both. GAM-NGS does not rely on global alignment: regions of the two assemblies representing the same genomic locus (called blocks) are identified through reads' alignments and stored in a weighted graph. The merging phase is carried out with the help of this weighted graph that allows an optimal resolution of local problematic regions.ResultsGAM-NGS has been tested on six different datasets and compared to other assembly reconciliation tools. The availability of a reference sequence for three of them allowed us to show how GAM-NGS is a tool able to output an improved reliable set of sequences. GAM-NGS is also a very efficient tool able to merge assemblies using substantially less computational resources than comparable tools. In order to achieve such goals, GAM-NGS avoids global alignment between contigs, making its strategy unique among other assembly reconciliation tools.ConclusionsThe difficulty to obtain correct and reliable assemblies using a single assembler is forcing the introduction of new algorithms able to enhance de novo assemblies. GAM-NGS is a tool able to merge two or more assemblies in order to improve contiguity and correctness. It can be used on all NGS-based assembly projects and it shows its full potential with multi-library Illumina-based projects. With more than 20 available assemblers it is hard to select the best tool. In this context we propose a tool that improves assemblies (and, as a by-product, perhaps even assemblers) by merging them and selecting the generating that is most likely to be correct.

Project description:BACKGROUND:Next generation sequencing (NGS) has become a universal practice in modern molecular biology. As the throughput of sequencing experiments increases, the preparation of conventional multiplexed libraries becomes more labor intensive. Conventional library preparation typically requires quality control (QC) testing for individual libraries such as amplification success evaluation and quantification, none of which occur until the end of the library preparation process. RESULTS:In this study, we address the need for a more streamlined high-throughput NGS workflow by tethering real-time quantitative PCR (qPCR) to conventional workflows to save time and implement single tube and single reagent QC. We modified two distinct library preparation workflows by replacing PCR and quantification with qPCR using SYBR Green I. qPCR enabled individual library quantification for pooling in a single tube without the need for additional reagents. Additionally, a melting curve analysis was implemented as an intermediate QC test to confirm successful amplification. Sequencing analysis showed comparable percent reads for each indexed library, demonstrating that pooling calculations based on qPCR allow for an even representation of sequencing reads. To aid the modified workflow, a software toolkit was developed and used to generate pooling instructions and analyze qPCR and melting curve data. CONCLUSIONS:We successfully applied fluorescent amplification for next generation sequencing (FA-NGS) library preparation to both plasmids and bacterial genomes. As a result of using qPCR for quantification and proceeding directly to library pooling, the modified library preparation workflow has fewer overall steps. Therefore, we speculate that the FA-NGS workflow has less risk of user error. The melting curve analysis provides the necessary QC test to identify and troubleshoot library failures prior to sequencing. While this study demonstrates the value of FA-NGS for plasmid or gDNA libraries, we speculate that its versatility could lead to successful application across other library types.

Project description:PurposeFor the advances of pediatric oncology next generation sequencing (NGS) research to equitably benefit all children, a diverse and representative sample of participants is needed. However, little is known about demographic and clinical characteristics that differentiate families who decline enrollment in pediatric oncology NGS research.MethodsDemographic and clinical data were retrospectively extracted for 363 pediatric oncology patients (0-21 years) approached for enrollment on Genomes for Kids (G4K), a study examining the feasibility of comprehensive clinical genomic analysis of tumors and paired normal samples. Demographic and clinical factors that significantly differentiated which families declined were subsequently compared to enrollment in Clinical Implementation of Pharmacogenetics (PG4KDS) for 348 families, a pharmacogenomics study with more explicit therapeutic benefit examining genes affecting drug responses and metabolism.ResultsFifty-three (14.6%) families declined enrollment in G4K. Race/ethnicity was the only variable that significantly differentiated study refusal using multivariate logistic regression, with families of black children more likely to decline enrollment compared to families of non-Hispanic or Hispanic white children. Reasons for declining G4K were generally consistent with other pediatric genomics research, with feeling overwhelmed and insurance discrimination fears most frequently cited. Families of black children were also more likely to decline enrollment in PG4KDS. Thirteen (3.7%) of the 348 families approached for both studies declined PG4KDS.ConclusionRace/ethnicity differentiated study declination across two different pediatric oncology genomics studies, suggesting enrollment disparities in the context of pediatric oncology genomics research. Genomics research participant samples that do not fully represent racial and ethnic minorities risk further exacerbating health disparities. Additional work is needed to understand the nuances of parental decision making in genomic research and facilitate enrollment of diverse patient populations.

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Identification of major factors associated with failed clinical molecular oncology testing performed by next generation sequencing (NGS).

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