Dataset Information

Assessment of the clinical utility of four NGS panels in myeloid malignancies. Suggestions for NGS panel choice or design.

ABSTRACT: The diagnosis of myeloid neoplasms (MN) has significantly evolved through the last few decades. Next Generation Sequencing (NGS) is gradually becoming an essential tool to help clinicians with disease management. To this end, most specialized genetic laboratories have implemented NGS panels targeting a number of different genes relevant to MN. The aim of the present study is to evaluate the performance of four different targeted NGS gene panels based on their technical features and clinical utility. A total of 32 patient bone marrow samples were accrued and sequenced with 3 commercially available panels and 1 custom panel. Variants were classified by two geneticists based on their clinical relevance in MN. There was a difference in panel's depth of coverage. We found 11 discordant clinically relevant variants between panels, with a trend to miss long insertions. Our data show that there is a high risk of finding different mutations depending on the panel of choice, due both to the panel design and the data analysis method. Of note, CEBPA, CALR and FLT3 genes, remains challenging the use of NGS for diagnosis of MN in compliance with current guidelines. Therefore, conventional molecular testing might need to be kept in place for the correct diagnosis of MN for now.

SUBMITTER: Aguilera-Diaz A

PROVIDER: S-EPMC6980571 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Assessment of the clinical utility of four NGS panels in myeloid malignancies. Suggestions for NGS panel choice or design.

Aguilera-Diaz Almudena A Vazquez Iria I Ariceta Beñat B Mañú Amagoia A Blasco-Iturri Zuriñe Z Palomino-Echeverría Sara S Larrayoz María José MJ García-Sanz Ramón R Prieto-Conde María Isabel MI Del Carmen Chillón María M Alfonso-Pierola Ana A Prosper Felipe F Fernandez-Mercado Marta M Calasanz María José MJ

PloS one 20200124 1

The diagnosis of myeloid neoplasms (MN) has significantly evolved through the last few decades. Next Generation Sequencing (NGS) is gradually becoming an essential tool to help clinicians with disease management. To this end, most specialized genetic laboratories have implemented NGS panels targeting a number of different genes relevant to MN. The aim of the present study is to evaluate the performance of four different targeted NGS gene panels based on their technical features and clinical util ...[more]

PMID: 31978184

Similar Datasets

Project description:MicroRNAs are small non-coding RNAs that influence gene expression by binding to the 3' UTR of target mRNAs in order to repress protein synthesis. Soon after discovery, microRNA dysregulation has been associated to several pathologies. In particular, they have often been reported as differentially expressed in healthy and tumor samples. This fact suggested that microRNAs are likely to be good candidate biomarkers for cancer diagnosis and personalized medicine. With the advent of Next-Generation Sequencing (NGS), measuring the expression level of the whole miRNAome at once is now routine. Yet, the collaborative effort of sharing data opens to the possibility of population analyses. This context motivated us to perform an in-silico study to distill cancer-specific panels of microRNAs that can serve as biomarkers. We observed that the problem of finding biomarkers can be modeled as a two-class classification task where, given the miRNAomes of a population of healthy and cancerous samples, we want to find the subset of microRNAs that leads to the highest classification accuracy. We fulfill this task leveraging on a sensible combination of data mining tools. In particular, we used: differential evolution for candidate selection, component analysis to preserve the relationships among miRNAs, and SVM for sample classification. We identified 10 cancer-specific panels whose classification accuracy is always higher than 92%. These panels have a very little overlap suggesting that miRNAs are not only predictive of the onset of cancer, but can be used for classification purposes as well. We experimentally validated the contribution of each of the employed tools to the selection of discriminating miRNAs. Moreover, we tested the significance of each panel for the corresponding cancer type. In particular, enrichment analysis showed that the selected miRNAs are involved in oncogenesis pathways, while survival analysis proved that miRNAs can be used to evaluate cancer severity. Summarizing: results demonstrated that our method is able to produce cancer-specific panels that are promising candidates for a subsequent in vitro validation.

Dataset Information

Assessment of the clinical utility of four NGS panels in myeloid malignancies. Suggestions for NGS panel choice or design.

Publications

Assessment of the clinical utility of four NGS panels in myeloid malignancies. Suggestions for NGS panel choice or design.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets