Next-generation sequencing indicates false-positive MRD results and better predicts prognosis after SCT in patients with childhood ALL

Category: Other Introduction/Purpose: Foot infections are often polymicrobial with diverse microbiomes. Accurate identification of the main pathogen in diabetic foot ulcer (DFU) remain challenging due to contamination or negative cultures often leading to ineffective post-surgical antibiotic treatment. Application of molecular diagnostics, such as next generation sequencing (NGS) has been explored as an alternative to standard culture in orthopaedic infections. NGS is highly sensitive and detects an entire bacterial genome along with pharmacologic resistant genes in a given sample. We sought to investigate the potential use of NGS for accurate diagnosis and quantification of various species in infected DFU. We hypothesize that NGS will provide a more accurate means of diagnosing and profiling microorganisms in infected DFU compared to the standard culture method. Methods: We investigated 30 infected DFU patients who underwent surgical treatment by a single academic orthopaedic surgeon from October 2018 to September 2019. The average age of the patient was 60.4 (range 33-82) years-old. Surgical procedures performed were irrigation and debridement (12), toe or ray amputation (13), calcanectomies (4), and below-knee amputation (1). Infected bone specimens were obtained intraoperatively and processed for standard culture and NGS. Quantitative PCR was performed to determine the bacterial burden present in the sample. DNA was amplified by PCR from a highly conserved region of the rRNA gene in the bacteria (16S rRNA). Once a high level of DNA was generated and determined, it was compared against NIH GenBank database. Concordance between the standard culture and NGS was assessed. Results: In 28 of 29 patients, pathogens were identified by both NGS and culture, with complete consistency of organisms in 13 cases (concordance rate: 43.3%). NGS provided relative quantitative measures and the presence of antibiotic resistant genes for each pathogen. In NGS, Anaerococcus species (79.3%) was the most common organism, followed by Streptococcus species (44.8%), Prevotella species (44.8%), Finegoldia magna (44.8%). In culture, S. aureus (58.6%) was the most common, followed by Streptococcus species (34.5%), coagulase-negative Staphylococci (24.1%), Corynebacterium species (20.7%). On average, NGS revealed 5.1 (1-11) number of pathogens, whereas standard culture revealed 2.6 (1-6) pathogens in a given sample. NGS identified 2 cases with false positive standard culture and detected antibiotic resistant organisms in 15 specimens. Conclusion: NGS is an emerging method of microbial identification in orthopedic infection. It is particularly helpful in profiling diverse microbes in polymicrobial infected DFU. It can identify major pathogens and may correct false positive or false negative culture. NGS may allow a faster invitation of postoperative targeted antibiotic therapy. [Table: see text]

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Next-Generation Sequencing Confirmation of Real-Time RT-PCR False Positive Influenza-A Virus Detection in Waterfowl and Swine Swab Samples

Journal of Next Generation Sequencing & Applications ◽

10.4172/2469-9853.1000134 ◽

2016 ◽

Vol 3 (2) ◽

Cited By ~ 3

Author(s):

Lu H ◽

Yi Tang ◽

Lin Lin

Keyword(s):

Next Generation Sequencing ◽

Real Time ◽

Influenza A Virus ◽

False Positive ◽

Influenza A ◽

Virus Detection ◽

Next Generation ◽

Rt Pcr ◽

Generation Sequencing

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Detection of false positive mutations in BRCA gene by next generation sequencing

Familial Cancer ◽

10.1007/s10689-016-9955-8 ◽

2016 ◽

Vol 16 (3) ◽

pp. 311-317 ◽

Cited By ~ 4

Author(s):

Moushumi Suryavanshi ◽

Dushyant Kumar ◽

Manoj Kumar Panigrahi ◽

Meenakshi Chowdhary ◽

Anurag Mehta

Keyword(s):

Next Generation Sequencing ◽

False Positive ◽

Next Generation ◽

Brca Gene ◽

Generation Sequencing

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Learnings From Precision Clinical Trial Matching for Oncology Patients Who Received NGS Testing

JCO Clinical Cancer Informatics ◽

10.1200/cci.20.00142 ◽

2021 ◽

pp. 231-238

Author(s):

Neha M. Jain ◽

Alison Culley ◽

Christine M. Micheel ◽

Travis J. Osterman ◽

Mia A. Levy

Keyword(s):

Clinical Trial ◽

Next Generation Sequencing ◽

False Positive ◽

False Positives ◽

Genomic Profile ◽

Next Generation ◽

Oncology Patients ◽

Initial Trial ◽

Individual Trial ◽

Generation Sequencing

PURPOSE Tumor next-generation sequencing reports typically generate trial recommendations for patients based on their diagnosis and genomic profile. However, these require additional refinement and prescreening, which can add to physician burden. We wanted to use human prescreening efforts to efficiently refine these trial options and also elucidate the high-value parameters that have a major impact on efficient trial matching. METHODS Clinical trial recommendations were generated based on diagnosis and biomarker criteria using an informatics platform and were further refined by manual prescreening. The refined results were then compared with the initial trial recommendations and the reasons for false-positive matches were evaluated. RESULTS Manual prescreening significantly reduced the number of false positives from the informatics generated trial recommendations, as expected. We found that trial-specific criteria, especially recruiting status for individual trial arms, were a high value parameter and led to the largest number of automated false-positive matches. CONCLUSION Reflex clinical trial matching approaches that refine trial recommendations based on the clinical details as well as trial-specific criteria have the potential to help alleviate physician burden for selecting the most appropriate trial for their patient. Investing in publicly available resources that capture the recruiting status of a trial at the cohort or arm level would, therefore, allow us to make meaningful contributions to increase the clinical trial enrollments by eliminating false positives.

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A novel approach to improve detection of somatic DNA variants in solid tumors by next-generation sequencing from FFPE samples.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.e22177 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. e22177-e22177 ◽

Cited By ~ 2

Author(s):

Nitin Udar ◽

Robert Haigis ◽

Thomas Gros ◽

Agda Karina Lucio-Eterovic ◽

Qingxiu Zhang ◽

...

Keyword(s):

Next Generation Sequencing ◽

Deep Sequencing ◽

False Positive ◽

Limit Of Detection ◽

Low Frequency ◽

Sample Type ◽

Next Generation ◽

Novel Approach ◽

Ffpe Samples ◽

Generation Sequencing

e22177 Background: Low frequency variant detection by sequencing is a highly desired goal for therapy selection in cancer especially the detection of actionable targets. The lower limit of detection using Sanger sequening is ~20% minor allele frequency (MAF). Deep sequencing of target genes using next generation sequencing (NGS) is gaining popularity. Formalin Fixed Paraffin Embedded (FFPE) tissue is the most common sample type in solid tumor histopathology. However, because the fixation process fragments DNA and damages it at varying frequencies, downstream processes can potentially misclassify modified bases and generate artifacts. We have developed a protocol that addresses both of these issues in a multiplex assay that involves deep sequencing using NGS of targets implicated in lung, gastric, colon, melanoma and ovarian cancers. Methods: The sample set includes 168 FFPE samples and 82 non FFPE samples. TruSeq Custom Amplicon technology was used to generate libraries for targets across 26 genes. Deep sequencing was done on a NGS platform (Illumina-MiSeq). Results: The DNA quality test, which surveys multiple genomic targets by qPCR, was an accurate determinant of DNA amplifiability and yielded a 99% sample success rate. A sensitivity of <5% MAF was achieved by sequencing at a depth of 1,000X for all targets. In order to differentiate true low frequency variants from fixation and other artifacts, our novel approach investigates each of the two DNA strands independently. The information is bioinformatically combined to distinguish true variants from artifacts. Testing of the FFPE samples with a 5% MAF cut off using the two strand approach reduced the potential false positive rate by ~ 40% when compared to information from only one strand of DNA. A comparative analysis of matched FF and FFPE sample showed that a high percentage of false positive calls were present even in the fresh frozen samples at this high level of sensitivity, if only using information from one strand. Conclusions: This protocol, efficiently and accurately detect low frequency variants by NGS in DNA extracted from FFPE tissues.

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rmvPFBAM: Removing Primers from BAM Files Based on Amplicon-Based Next-Generation Sequencing and Cloud Computing When Analyzing Personal Genome Data

Scientific Programming ◽

10.1155/2021/6536470 ◽

2021 ◽

Vol 2021 ◽

pp. 1-6

Author(s):

Yanjun Ma

Keyword(s):

Next Generation Sequencing ◽

False Positive ◽

Large Scale ◽

Genomic Data ◽

Next Generation Sequencing Data ◽

Personal Genome ◽

Next Generation ◽

Sequencing Data ◽

Personal Genomic ◽

Generation Sequencing

Personal genomic data constitute one important part of personal health data. However, due to the large amount of personal genomic data obtained by the next-generation sequencing technology, special tools are needed to analyze these data. In this article, we will explore a tool analyzing cloud-based large-scale genome sequencing data. Analyzing and identifying genomic variations from amplicon-based next-generation sequencing data are necessary for the clinical diagnosis and treatment of cancer patients. When processing the amplicon-based next-generation sequencing data, one essential step is removing primer sequences from the reads to avoid detecting false-positive mutations introduced by nonspecific primer binding and primer extension reactions. At present, the removing primer tools usually discard primer sequences from the FASTQ file instead of BAM file, but this method could cause some downstream analysis problems. Only one tool (BAMClipper) removes primer sequences from BAM files, but it only modified the CIGAR value of the BAM file, and false-positive mutations falling in the primer region could still be detected based on its processed BAM file. So, we developed one cutting primer tool (rmvPFBAM) removing primer sequences from the BAM file, and the mutations detected based on the processed BAM file by rmvPFBAM are highly credible. Besides that, rmvPFBAM runs faster than other tools, such as cutPrimers and BAMClipper.

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Live births after simultaneous avoidance of monogenic diseases and chromosome abnormality by next-generation sequencing with linkage analyses

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1523297113 ◽

2015 ◽

Vol 112 (52) ◽

pp. 15964-15969 ◽

Cited By ~ 70

Author(s):

Liying Yan ◽

Lei Huang ◽

Liya Xu ◽

Jin Huang ◽

Fei Ma ◽

...

Keyword(s):

Next Generation Sequencing ◽

Linkage Analysis ◽

False Positive ◽

Chromosome Abnormality ◽

False Negative ◽

Genetic Diagnosis ◽

Next Generation ◽

Linkage Analyses ◽

Monogenic Diseases ◽

Generation Sequencing

In vitro fertilization (IVF), preimplantation genetic diagnosis (PGD), and preimplantation genetic screening (PGS) help patients to select embryos free of monogenic diseases and aneuploidy (chromosome abnormality). Next-generation sequencing (NGS) methods, while experiencing a rapid cost reduction, have improved the precision of PGD/PGS. However, the precision of PGD has been limited by the false-positive and false-negative single-nucleotide variations (SNVs), which are not acceptable in IVF and can be circumvented by linkage analyses, such as short tandem repeats or karyomapping. It is noteworthy that existing methods of detecting SNV/copy number variation (CNV) and linkage analysis often require separate procedures for the same embryo. Here we report an NGS-based PGD/PGS procedure that can simultaneously detect a single-gene disorder and aneuploidy and is capable of linkage analysis in a cost-effective way. This method, called “mutated allele revealed by sequencing with aneuploidy and linkage analyses” (MARSALA), involves multiple annealing and looping-based amplification cycles (MALBAC) for single-cell whole-genome amplification. Aneuploidy is determined by CNVs, whereas SNVs associated with the monogenic diseases are detected by PCR amplification of the MALBAC product. The false-positive and -negative SNVs are avoided by an NGS-based linkage analysis. Two healthy babies, free of the monogenic diseases of their parents, were born after such embryo selection. The monogenic diseases originated from a single base mutation on the autosome and the X-chromosome of the disease-carrying father and mother, respectively.

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