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Next-generation sequencing-based method shows increased mutation detection sensitivity in an Indian retinoblastoma cohort.

ABSTRACT: Retinoblastoma (Rb) is the most common primary intraocular cancer of childhood and one of the major causes of blindness in children. India has the highest number of patients with Rb in the world. Mutations in the RB1 gene are the primary cause of Rb, and heterogeneous mutations are distributed throughout the entire length of the gene. Therefore, genetic testing requires screening of the entire gene, which by conventional sequencing is time consuming and expensive.In this study, we screened the RB1 gene in the DNA isolated from blood or saliva samples of 50 unrelated patients with Rb using the TruSight Cancer panel. Next-generation sequencing (NGS) was done on the Illumina MiSeq platform. Genetic variations were identified using the Strand NGS software and interpreted using the StrandOmics platform.We were able to detect germline pathogenic mutations in 66% (33/50) of the cases, 12 of which were novel. We were able to detect all types of mutations, including missense, nonsense, splice site, indel, and structural variants. When we considered bilateral Rb cases only, the mutation detection rate increased to 100% (22/22). In unilateral Rb cases, the mutation detection rate was 30% (6/20).Our study suggests that NGS-based approaches increase the sensitivity of mutation detection in the RB1 gene, making it fast and cost-effective compared to the conventional tests performed in a reflex-testing mode.

SUBMITTER: Singh J

PROVIDER: S-EPMC4985049 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Next-generation sequencing-based method shows increased mutation detection sensitivity in an Indian retinoblastoma cohort.

Singh Jaya J Mishra Avshesh A Pandian Arunachalam Jayamuruga AJ Mallipatna Ashwin C AC Khetan Vikas V Sripriya S S Kapoor Suman S Agarwal Smita S Sankaran Satish S Katragadda Shanmukh S Veeramachaneni Vamsi V Hariharan Ramesh R Subramanian Kalyanasundaram K Mannan Ashraf U AU

Molecular vision 20160816

<h4>Purpose</h4>Retinoblastoma (Rb) is the most common primary intraocular cancer of childhood and one of the major causes of blindness in children. India has the highest number of patients with Rb in the world. Mutations in the RB1 gene are the primary cause of Rb, and heterogeneous mutations are distributed throughout the entire length of the gene. Therefore, genetic testing requires screening of the entire gene, which by conventional sequencing is time consuming and expensive.<h4>Methods</h4> ...[more]

PMID: 27582626

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Project description:BackgroundMulti-sample comparison is commonly used in cancer genomics studies. By using next-generation sequencing (NGS), a mutation's status in a specific sample can be measured by the number of reads supporting mutant or wildtype alleles. When no mutant reads are detected, it could represent either a true negative mutation status or a false negative due to an insufficient number of reads, so-called "coverage". To minimize the chance of false-negative, we should consider the mutation status as "unknown" instead of "negative" when the coverage is inadequately low. There is no established method for determining the coverage threshold between negative and unknown statuses. A common solution is to apply a universal minimum coverage (UMC). However, this method relies on an arbitrarily chosen threshold, and it does not take into account the mutations' relative abundances, which can vary dramatically by the type of mutations. The result could be misclassification between negative and unknown statuses.MethodsWe propose an adaptive mutation-specific negative (MSN) method to improve the discrimination between negative and unknown mutation statuses. For a specific mutation, a non-positive sample is compared with every known positive sample to test the null hypothesis that they may contain the same frequency of mutant reads. The non-positive sample can only be claimed as "negative" when this null hypothesis is rejected with all known positive samples; otherwise, the status would be "unknown".ResultsWe first compared the performance of MSN and UMC methods in a simulated dataset containing varying tumor cell fractions. Only the MSN methods appropriately assigned negative statuses for samples with both high- and low-tumor cell fractions. When evaluated on a real dual-platform single-cell sequencing dataset, the MSN method not only provided more accurate assessments of negative statuses but also yielded three times more available data after excluding the "unknown" statuses, compared with the UMC method.ConclusionsWe developed a new adaptive method for distinguishing unknown from negative statuses in multi-sample comparison NGS data. The method can provide more accurate negative statuses than the conventional UMC method and generate a remarkably higher amount of available data by reducing unnecessary "unknown" calls.

Project description:Retinoblastoma (RB) is the most common malignant childhood tumor of the eye and results from inactivation of both alleles of the RB1 gene. Nowadays RB genetic diagnosis requires classical chromosome investigations, Multiplex Ligation-dependent Probe Amplification analysis (MLPA) and Sanger sequencing. Nevertheless, these techniques show some limitations. We report our experience on a cohort of RB patients using a combined approach of Next-Generation Sequencing (NGS) and RB1 custom array-Comparative Genomic Hybridization (aCGH).A total of 65 patients with retinoblastoma were studied: 29 cases of bilateral RB and 36 cases of unilateral RB. All patients were previously tested with conventional cytogenetics and MLPA techniques. Fifty-three samples were then analysed using NGS. Eleven cases were analysed by RB1 custom aCGH. One last case was studied only by classic cytogenetics. Finally, it has been tested, in a lab sensitivity assay, the capability of NGS to detect artificial mosaicism series in previously recognized samples prepared at 3 different mosaicism frequencies: 10, 5, 1 %.Of the 29 cases of bilateral RB, 28 resulted positive (96.5 %) to the genetic investigation: 22 point mutations and 6 genomic rearrangements (four intragenic and two macrodeletion). A novel germline intragenic duplication, from exon18 to exon 23, was identified in a proband with bilateral RB. Of the 36 available cases of unilateral RB, 8 patients resulted positive (22 %) to the genetic investigation: 3 patients showed point mutations while 5 carried large deletion. Finally, we successfully validated, in a lab sensitivity assay, the capability of NGS to accurately measure level of artificial mosaicism down to 1 %.NGS and RB1-custom aCGH have demonstrated to be an effective combined approach in order to optimize the overall diagnostic procedures of RB. Custom aCGH is able to accurately detect genomic rearrangements allowing the characterization of their extension. NGS is extremely accurate in detecting single nucleotide variants, relatively simple to perform, cost savings and efficient and has confirmed a high sensitivity and accuracy in identifying low levels of artificial mosaicisms.

Dataset Information

Next-generation sequencing-based method shows increased mutation detection sensitivity in an Indian retinoblastoma cohort.

Publications

Next-generation sequencing-based method shows increased mutation detection sensitivity in an Indian retinoblastoma cohort.

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