Dataset Information

The clinical application of SNP-based next-generation sequencing (SNP-NGS) for evaluation of chimerism and microchimerism after HLA-mismatched stem cell microtransplantation.

ABSTRACT: Genetic diagnostic methods for evaluation of chimerism after HSCT, such as STR-PCR and XY-FISH, have limited sensitivity. When donor chimerism is in the micro range (< 1%), deviations in the accuracy of assessment are the most significant disadvantage of these common methods. We developed a highly sensitive method that applies SNPs based on NGS in order to explore the value of donor cell microchimerism in microtransplantation (MST). This improved SNP-NGS approach has higher sensitivity (0.01-0.05%) and only requires a small amount of DNA (8-200 ng). We retrospectively analyzed the clinical data of 48 patients with AML who received HLA-mismatched stem cell MST at our center to assess the impact of microchimerism on clinical prognosis. Patients whose duration of microchimerism was > 10.5 months (median) had a relapse rate of 26.1%, and had better 5-year LFS and OS (73.4% and 82.6%). In contrast, patients whose duration of microchimerism was < 10.5 months had a higher relapse rate (69.6%), and their 5-year LFS and OS were 30.4% and 43.5%. In conclusion, duration of donor chimerism is highly valuable for assessment of survival and prognosis in patients with AML who have received HLA-mismatched stem cell MST, especially the intermediate-risk group.

SUBMITTER: Li W

PROVIDER: S-EPMC9588463 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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The clinical application of SNP-based next-generation sequencing (SNP-NGS) for evaluation of chimerism and microchimerism after HLA-mismatched stem cell microtransplantation.

Li Weiyang W Xu Yi Y Feng Yufeng Y Zhou Haixia H Ma Xiao X Wu Depei D Chen Suning S Sun Aining A

International journal of hematology 20220708 5

Genetic diagnostic methods for evaluation of chimerism after HSCT, such as STR-PCR and XY-FISH, have limited sensitivity. When donor chimerism is in the micro range (< 1%), deviations in the accuracy of assessment are the most significant disadvantage of these common methods. We developed a highly sensitive method that applies SNPs based on NGS in order to explore the value of donor cell microchimerism in microtransplantation (MST). This improved SNP-NGS approach has higher sensitivity (0.01-0.0 ...[more]

PMID: 35802296

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Project description:Genomic loss of mismatched human leukocyte antigen (HLA loss) is one of the most vital immune escape mechanisms of leukemic cells after allogeneic hematopoietic stem cell transplantation (allo-HSCT). However, the methods currently used for HLA loss analysis have some shortcomings. Limited literature has been published, especially in lymphoid malignancies. This study aims to evaluate the incidences, risk factors of HLA loss, and clinical outcomes of HLA loss patients. In all, 160 patients undergoing partially mismatched related donor (MMRD) transplantation from 18 centers in China were selected for HLA loss analysis with the next-generation sequencing (NGS)-based method, which was validated by HLA-KMR. Variables of the prognostic risk factors for HLA loss or HLA loss-related relapse were identified with the logistic regression or the Fine and Gray regression model. An HLA loss detection system, HLA-CLN [HLA chimerism for loss of heterozygosity (LOH) analysis by NGS], was successfully developed. Forty (25.0%) patients with HLA loss were reported, including 27 with myeloid and 13 with lymphoid malignancies. Surprisingly, 6 of those 40 patients did not relapse. The 2-year cumulative incidences of HLA loss (22.7% vs 22.0%, P = 0.731) and HLA loss-related relapse (18.4% vs 20.0%, P = 0.616) were similar between patients with myeloid and lymphoid malignancies. The number of HLA mismatches (5/10 vs <5/10) was significantly associated with HLA loss in the whole cohort [odds ratio (OR): 3.15, P = 0.021] and patients with myeloid malignancies (OR: 3.94, P = 0.021). A higher refined-disease risk index (OR: 6.91, P = 0.033) and donor-recipient ABO incompatibility (OR: 4.58, P = 0.057) contributed to HLA loss in lymphoid malignancies. To sum up, HLA-CLN could overcome the limitations of HLA-KMR and achieve a better HLA coverage for more patients. The clinical characteristics and outcomes were similar in patients with HLA loss between myeloid and lymphoid malignancies. In addition, the results suggested that a patient with HLA loss might not always relapse.

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.

Dataset Information

The clinical application of SNP-based next-generation sequencing (SNP-NGS) for evaluation of chimerism and microchimerism after HLA-mismatched stem cell microtransplantation.

Publications

The clinical application of SNP-based next-generation sequencing (SNP-NGS) for evaluation of chimerism and microchimerism after HLA-mismatched stem cell microtransplantation.

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