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Objective To evaluate the feasibility of detecting actionable gene mutations in circulating tumor DNA (ctDNA) in patients with advanced non-small-cell lung cancer (NSCLC) using targeted next-generation sequencing (NGS). Materials and methods In total 50 plasma samples from patients newly diagnosed with advanced NSCLC or resistant to first-line tyrosine kinase inhibitors (TKIs) were subjected to deep sequencing on a seven-gene panel (BRAF, EGFR, ERBB2, KRAS, NRAS, PIK3CA, PTEN) incorporated with molecular barcodes to improve accuracy in variant detection. When possible, results were compared with those from matched tissue samples. Results At least one alteration in the ctDNA was detected in 44 out of 50 patients (88%); EGFR was the most frequently mutated gene. Half the total number of patients (50%, 25 of 50) had at least one actionable genetic alteration with targeted therapies available for treatment. Our results showed a high concordance rate of 81% in detection of EGFR mutation between 26 matched tissue and plasma samples. For progressive patients, from whom tissue is mostly unavailable, the resistant EGFR T790 M mutation was validated using the droplet digital polymerase chain reaction (ddPCR), yielding a concordance of 92% between alternative platforms. Conclusion Our study demonstrated that therapeutically actionable mutations can be detected with high accuracy in ctDNA using NGS. This promising approach offers alternative and non-invasive diagnostic methods for treatment guidance and clinical monitoring.

Background Lipid storage myopathy (LSM) is a diverse group of lipid metabolic disorders with great variations in the clinical phenotype and age of onset. Classical multiple acyl-CoA dehydrogenase deficiency (MADD) is known to occur secondary to mutations in electron transfer flavoprotein dehydrogenase (ETFDH) gene. Whole exome sequencing (WES) with clinical correlations can be useful in identifying genomic alterations for targeted therapy. Case presentation We report a patient presented with severe muscle weakness and exercise intolerance, suggestive of LSM. Diagnostic testing demonstrated lipid accumulation in muscle fibres and elevated plasma acyl carnitine levels. Exome sequencing of the proband and two of his unaffected siblings revealed compound heterozygous mutations, c.250G > A (p.Ala84Thr) and c.770A > G (p.Tyr257Cys) in the ETFDH gene as the probable causative mutations. In addition, a previously unreported variant c.1042C > T (p.Arg348Trp) in ACOT11 gene was found. This missense variant was predicted to be deleterious but its association with lipid storage in muscle is unclear. The diagnosis of MADD was established and the patient was treated with riboflavin which resulted in rapid clinical and biochemical improvement. Conclusions Our findings support the role of WES as an effective tool in the diagnosis of highly heterogeneous disease and this has important implications in the therapeutic strategy of LSM treatment. Electronic supplementary material The online version of this article (10.1186/s12920-018-0356-8) contains supplementary material, which is available to authorized users.

Underrepresentation of Asian genomes has hindered population and medical genetics research on Asians, leading to population disparities in precision medicine. By whole-genome sequencing of 4,810 Singapore Chinese, Malays, and Indians, we found 98.3 million SNPs and small insertions or deletions, over half of which are novel. Population structure analysis demonstrated great representation of Asian genetic diversity by three ethnicities in Singapore and revealed a Malay-related novel ancestry component. Furthermore, demographic inference suggested that Malays split from Chinese ∼24,800 years ago and experienced significant admixture with East Asians ∼1,700 years ago, coinciding with the Austronesian expansion. Additionally, we identified 20 candidate loci for natural selection, 14 of which harbored robust associations with complex traits and diseases. Finally, we show that our data can substantially improve genotype imputation in diverse Asian and Oceanian populations. These results highlight the value of our data as a resource to empower human genetics discovery across broad geographic regions. Agency for Science, Technology and Research (A*STAR) National Medical Research Council (NMRC) National Research Foundation (NRF) Accepted version We acknowledge H.M. Kang, S. Das, A. Tan, F. Zhang, J. Terhorst, P.-R. Loh, and G. Hellenthal for helpful discussions and support from all participants and clinical research coordinators of the contributing cohorts and studies: the TTSH Healthy Control Workgroup, the SEED cohort, the Asian Sudden Cardiac Death in Heart Failure Study, the Singapore Heart Failure Outcomes and Phenotypes (SHOP) cohort, the Asian neTwork for Translational Research and Cardiovascular Trials (ATTRaCT), the Parkinson’s Disease Study, the Peranakan Genome Study, the Platinum Asian Genomes Project, the Bariatric Surgery Study, the National Heart Centre Singapore Biobank and SingHEART cohorts, and the GUSTO and S-PRESTO study groups. This study was supported by Singapore’s A*STAR (core funding and IAF-PP H17/01/a0/007), BMRC (SPF2014/001, SPF2013/002, SPF2014/003, SPF2014/004, and SPF2014/005), NMRC (CIRG/1371/2013, CIRG/1417/2015, CIRG/1488/ 2018, CSA-SI/0012/2017, CG/017/2013, CG/M006/2017_NHCS, TCR/013- NNI/2014, STaR/0011/2012, STaR2013/001, STaR/014/2013, STaR/0026/ 2015, TCR/006-NUHS/2013, TCR/012-NUHS/2014, TCR/004-NUS/2008, TCR/012-NUHS/2014, and center grants 2010-13 and 2013-2017), NRF (NRFF2016-03), National University of Singapore, SingHealth and DukeNUS, and Alexandra Health small innovative grant SIGII/15203 and funding from Huazhong University of Science and Technology, the Tanoto Foundation, the Lee Foundation, the Boston Scientific Investigator Sponsored Research Program and Bayer, the NSF (DEB-1753489), and the Alfred P. Sloan Foundation. The computation was partially performed on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg).

Background Genetic determinants of drug response remain stable throughout life and offer great promise to patient-tailored drug therapy. The adoption of pharmacogenetic (PGx) testing in patient care requires accurate, cost effective and rapid genotyping with clear guidance on the use of the results. Hence, we evaluated a 32 SNPs panel for implementing PGx testing in clinical laboratories. Methods We designed a 32-SNP panel for PGx testing in clinical laboratories. The variants were selected using the clinical annotations of the Pharmacogenomics Knowledgebase (PharmGKB) and include polymorphisms of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 genes. The CYP2D6 gene allele quantification was determined simultaneously with TaqMan copy number assays targeting intron 2 and exon 9 regions. The genotyping results showed high call rate accuracy according to concordance with genotypes identified by independent analyses on Sequenome massarray and droplet digital PCR. Furthermore, 506 genomic samples across three major ethnic groups of Singapore (Malay, Indian and Chinese) were analysed on our workflow. Results We found that 98% of our study subjects carry one or more CPIC actionable variants. The major alleles detected include CYP2C9*3, CYP2C19*2, CYP2D6*10, CYP2D6*36, CYP2D6*41, CYP3A5*3 and VKORC1*2. These translate into a high percentage of intermediate (IM) and poor metabolizer (PM) phenotypes for these genes in our population. Conclusion Genotyping may be useful to identify patients who are prone to drug toxicity with standard doses of drug therapy in our population. The simplicity and robustness of this PGx panel is highly suitable for use in a clinical laboratory.