Detection of low prevalence somatic mutations in solid tumors with ultra-deep targeted sequencing

Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking

BACKGROUND

High-throughput sequencing (HTS) has become the gold standard approach for variant analysis in cancer research. However, somatic variants may occur at low fractions due to contamination from normal cells or tumor heterogeneity; this poses a significant challenge for standard HTS analysis pipelines. The problem is exacerbated in scenarios with minimal tumor DNA, such as circulating tumor DNA in plasma. Assessing sensitivity and detection of HTS approaches in such cases is paramount, but time-consuming and expensive: specialized experimental protocols and a sufficient quantity of samples are required for processing and analysis. To overcome these limitations, we propose a new computational approach specifically designed for the generation of artificial datasets suitable for this task, simulating ultra-deep targeted sequencing data with low-fraction variants and demonstrating their effectiveness in benchmarking low-fraction variant calling.

RESULTS

Our approach enables the generation of artificial raw reads that mimic real data without relying on pre-existing data by using NEAT, a fine-grained read simulator that generates artificial datasets using models learned from multiple different datasets. Then, it incorporates low-fraction variants to simulate somatic mutations in samples with minimal tumor DNA content. To prove the suitability of the created artificial datasets for low-fraction variant calling benchmarking, we used them as ground truth to evaluate the performance of widely-used variant calling algorithms: they allowed us to define tuned parameter values of major variant callers, considerably improving their detection of very low-fraction variants.

CONCLUSIONS

Our findings highlight both the pivotal role of our approach in creating adequate artificial datasets with low tumor fraction, facilitating rapid prototyping and benchmarking of algorithms for such dataset type, as well as the important need of advancing low-fraction variant calling techniques.

Optimizing Insertion and Deletion Detection Using Next-Generation Sequencing in the Clinical Laboratory

Detection of insertions and deletions (InDels) by short-read next-generation sequencing (NGS) technology can be challenging because of frequent misaligned reads. A systematic analysis of short InDels (1 to 30 bases) and fms-related receptor tyrosine kinase 3 (FLT3) internal tandem duplications (ITDs; 6 to 183 bases) from 46 clinical cases of solid or hematologic malignancy processed with a clinical NGS assay identified misaligned reads in every case, ranging from 3% to 100% of reads with the InDel showing mismapped bases. Mismaps also increased with InDel size. As a consequence, the clinical NGS bioinformatics pipeline undercalled the variant allele frequency by 1% to 84%, incorrectly called simultaneous single-base substitutions along with InDels, or did not report an FLT3 ITD that had been detected by capillary electrophoresis. To improve the ability of the pipeline to better detect and quantify InDels, we utilized a software program called Assembly-Based ReAligner (ABRA2) to more accurately remap reads. ABRA2 was able to correct 41% to 100% of the reads with mismapped bases and led to absolute increases in the variant allele frequency from 1% to 61% along with correction of all of the single-base substitutions except for two cases. ABRA2 could also detect multiple FLT3 ITD clones except for one 183-base ITD. Our analysis has found that ABRA2 performs well on short InDels as well as FLT3 ITDs that are <100 bases.

Lipoprotein(a) beyond the kringle IV repeat polymorphism: The complexity of genetic variation in the LPA gene

High lipoprotein(a) [Lp(a)] concentrations are one of the most important genetically determined risk factors for cardiovascular disease. Lp(a) concentrations are an enigmatic trait largely controlled by one single gene (LPA) that contains a complex interplay of several genetic elements with many surprising effects discussed in this review. A hypervariable coding copy number variation (the kringle IV type-2 repeat, KIV-2) generates >40 apolipoprotein(a) protein isoforms and determines the median Lp(a) concentrations. Carriers of small isoforms with up to 22 kringle IV domains have median Lp(a) concentrations up to 5 times higher than those with large isoforms (>22 kringle IV domains). The effect of the apo(a) isoforms are, however, modified by many functional single nucleotide polymorphisms (SNPs) distributed over the complete range of allele frequencies (<0.1% to >20%) with very pronounced effects on Lp(a) concentrations. A complex interaction is present between the apo (a) isoforms and LPA SNPs, with isoforms partially masking the effect of functional SNPs and, vice versa, SNPs lowering the Lp(a) concentrations of affected isoforms. This picture is further complicated by SNP-SNP interactions, a poorly understood role of other polymorphisms such as short tandem repeats and linkage structures that are poorly captured by common R² values. A further layer of complexity derives from recent findings that several functional SNPs are located in the KIV-2 repeat and are thus not accessible to conventional sequencing and genotyping technologies. A critical impact of the ancestry on correlation structures and baseline Lp(a) values becomes increasingly evident.

This review provides a comprehensive overview on the complex genetic architecture of the Lp(a) concentrations in plasma, a field that has made tremendous progress with the introduction of new technologies. Understanding the genetics of Lp(a) might be a key to many mysteries of Lp(a) and booster new ideas on the metabolism of Lp(a) and possible interventional targets.

Histologic and Genotypic Characterization of Lung Cancer in the Inuit Population of the Eastern Canadian Arctic

Inuit are the Indigenous Arctic peoples and residents of the Canadian territory of Nunavut who have the highest global rate of lung cancer. Given lung cancer’s mortality, histological and genomic characterization was undertaken to better understand the disease biology. We retrospectively studied all Inuit cases from Nunavut’s Qikiqtani (Baffin) region, referred to the Ottawa Hospital Cancer Center between 2001 and 2011. Demographics were compiled from medical records and tumor samples underwent pathologic/histologic confirmation. Tumors were analyzed by next generation sequencing (NGS) with a cancer hotspot mutation panel. Of 98 patients, the median age was 66 years and 61% were male. Tobacco use was reported in 87%, and 69% had a history of lung disease (tuberculosis or other). Histological types were: non-small cell lung carcinoma (NSCLC), 81%; small cell lung carcinoma, 16%. Squamous cell carcinoma (SCC) represented 65% of NSCLC. NGS on 55 samples demonstrated mutation rates similar to public lung cancer datasets. In SCC, the STK11 F354L mutation was observed at higher frequency than previously reported. This is the first study to characterize the histologic/genomic profiles of lung cancer in this population. A high incidence of SCC, and an elevated rate of STK11 mutations distinguishes this group from the North American population.

Protein domain-based approaches for the identification and prioritization of therapeutically actionable cancer variants

The tremendous number of cancer variants that can be detected by NGS analyses has required the development of computational approaches to prioritize mutations on the basis of their biological and clinical significance. Standard strategies take a gene-centric approach to the problem, allowing exclusively the identification of highly frequent variants. On the contrary, protein domain (PD)-based approaches allow to identify functionally relevant low frequency variants by searching for mutations that recur on analogous residues across homologous proteins (i.e. containing the same PD). Such approaches enable to transfer information about the effects and druggability from one known mutation to unknown ones. Here we describe how PD-based strategies work, and discuss how they could be exploited for mutation prioritization. The principle that mutations clustered on specific residues of PDs have the same functional consequences and are therapeutically actionable in a similar manner could help the choice of patient-specific targeted drugs, eventually improving the management of cancer patients.

Combined landscape of single-nucleotide variants and copy number alterations in clonal hematopoiesis

Clonal hematopoiesis (CH) in apparently healthy individuals is implicated in the development of hematological malignancies (HM) and cardiovascular diseases. Previous studies of CH analyzed either single-nucleotide variants and indels (SNVs/indels) or copy number alterations (CNAs), but not both. Here, using a combination of targeted sequencing of 23 CH-related genes and array-based CNA detection of blood-derived DNA, we have delineated the landscape of CH-related SNVs/indels and CNAs in 11,234 individuals without HM from the BioBank Japan cohort, including 672 individuals with subsequent HM development, and studied the effects of these somatic alterations on mortality from HM and cardiovascular disease, as well as on hematological and cardiovascular phenotypes. The total number of both types of CH-related lesions and their clone size positively correlated with blood count abnormalities and mortality from HM. CH-related SNVs/indels and CNAs exhibited statistically significant co-occurrence in the same individuals. In particular, co-occurrence of SNVs/indels and CNAs affecting DNMT3A, TET2, JAK2 and TP53 resulted in biallelic alterations of these genes and was associated with higher HM mortality. Co-occurrence of SNVs/indels and CNAs also modulated risks for cardiovascular mortality. These findings highlight the importance of detecting both SNVs/indels and CNAs in the evaluation of CH.

Accurate Detection of Rare Mutant Alleles by Target Base-Specific Cleavage with the CRISPR/Cas9 System

The detection of low-frequency somatic mutations enables early diagnosis of disease; however, base-substitution errors that arise during genomic library preparation and high-throughput sequencing can lead to false diagnostic information. To discriminate true genomic alterations from technical errors, we developed spCas9-assisted true variant labeling sequencing (CARVE-seq), which detects low-frequency mutant alleles with high accuracy. CARVE-seq utilizes single-base discrimination during spCas9 cleavage reactions to exclude technical errors. Ten single nucleotide variants that recurrently occur in tumors were assayed by CARVE-seq using 20 ng reference samples, and 100% positive predictive value and specificity was observed, which proved the highly accurate performance of CARVE-seq.

Novel Genetic Variations in Acute Myeloid Leukemia in Pakistani Population

Acute myeloid leukemia (AML) is a hematological malignancy characterized by clonal expansion of blast cells that exhibit great genetic heterogeneity. In this study, we describe the mutational landscape and its clinico-pathological significance in 26 myeloid neoplasm patients from a South Asian population (Pakistan) by using ultra-deep targeted next-generation DNA sequencing of 54 genes (∼5000×) and its subsequent bioinformatics analysis. The data analysis indicated novel non-silent somatic mutational events previously not reported in AML, including nine non-synonymous and one stop-gain mutations. Notably, two recurrent somatic non-synonymous mutations, i.e., STAG2 (causing p.L526F) and BCORL1 (p.A400V), were observed in three unrelated cases each. The BCOR was found to have three independent non-synonymous somatic mutations in three cases. Further, the SRSF2 with a protein truncating somatic mutation (p.Q88X) was observed for the first time in AML in this study. The prioritization of germline mutations with ClinVar, SIFT, Polyphen2, and Combined Annotation Dependent Depletion (CADD) highlighted 18 predicted deleterious/pathogenic mutations, including two recurrent deleterious mutations, i.e., a novel heterozygous non-synonymous SNV in GATA2 (p.T358P) and a frameshift insertion in NPM1 (p.L258fs), found in two unrelated cases each. The WT1 was observed with three independent potential detrimental germline mutations in three different cases. Collectively, non-silent somatic and/or germline mutations were observed in 23 (88.46%) of the cases (0.92 mutation per case). Furthermore, the pharmGKB database exploration showed a missense SNV rs1042522 in TP53, exhibiting decreased response to anti-cancer drugs, in 19 (73%) of the cases. This genomic profiling of AML provides deep insight into the disease pathophysiology. Identification of pharmacogenomics markers will help to adopt personalized approach for the management of AML patients in Pakistan.

CODEX2: full-spectrum copy number variation detection by high-throughput DNA sequencing

High-throughput DNA sequencing enables detection of copy number variations (CNVs) on the genome-wide scale with finer resolution compared to array-based methods but suffers from biases and artifacts that lead to false discoveries and low sensitivity. We describe CODEX2, as a statistical framework for full-spectrum CNV profiling that is sensitive for variants with both common and rare population frequencies and that is applicable to study designs with and without negative control samples. We demonstrate and evaluate CODEX2 on whole-exome and targeted sequencing data, where biases are the most prominent. CODEX2 outperforms existing methods and, in particular, significantly improves sensitivity for common CNVs.

A comprehensive map of single-base polymorphisms in the hypervariable LPA kringle IV type 2 copy number variation region

Lipoprotein (a) [Lp(a)] concentrations are among the strongest genetic risk factors for cardiovascular disease and present pronounced interethnic and interindividual differences. Approximately 90% of Lp(a) variance is controlled by the LPA gene, which contains a 5.6-kb-large copy number variation [kringle IV type 2 (KIV-2) repeat] that generates >40 protein isoforms. Variants within the KIV-2 region are not called in common sequencing projects, leaving up to 70% of the LPA coding region currently unaddressed. To completely assess the variability in LPA, we developed a sequencing strategy for this region and report here the first map of genetic variation in the KIV-2 region, a comprehensively evaluated ultradeep sequencing protocol, and an easy-to-use variant analysis pipeline. We sequenced 123 Central-European individuals and reanalyzed public data of 2,504 individuals from 26 populations. We found 14 different loss-of-function and splice-site mutations, as well as >100, partially even common, missense variants. Some coding variants were frequent in one population but absent in others. This provides novel candidates to explain the large ethnic and individual differences in Lp(a) concentrations. Importantly, our approach and pipeline are also applicable to other similar copy number variable regions, allowing access to regions that are not captured by common genome sequencing.

Urinary Exosomal and cell-free DNA Detects Somatic Mutation and Copy Number Alteration in Urothelial Carcinoma of Bladder

Urothelial bladder carcinoma (UBC) is characterized by a large number of genetic alterations. DNA from urine is a promising source for liquid biopsy in urological malignancies. We aimed to assess the availability of cell-free DNA (cfDNA) and exosomal DNA (exoDNA) in urine as a source for liquid biopsy in UBC. We included 9 patients who underwent surgery for UBC and performed genomic profiling of tumor samples and matched urinary cfDNA and exoDNA. For mutation analysis, deep sequencing was performed for 9 gene targets and shallow whole genome sequencing (sWGS) was used for the detection of copy number variation (CNV). We analyzed whether genetic alteration in tumor samples was reflected in urinary cfDNA or exoDNA. To measure the similarity between copy number profiles of tumor tissue and urinary DNA, the Pearson’s correlation coefficient was calculated. We found 17 somatic mutations in 6 patients. Of the 17 somatic mutations, 14 and 12 were identified by analysis of cfDNA and exoDNA with AFs of 56.2% and 65.6%, respectively. In CNV analysis using sWGS, although the mean depth was 0.6X, we found amplification of MDM2, ERBB2, CCND1 and CCNE1, and deletion of CDKN2A, PTEN and RB1, all known to be frequently altered in UBC. CNV plots of cfDNA and exoDNA showed a similar pattern with those from the tumor samples. Pearson’s correlation coefficients of tumor vs. cfDNA (0.481) and tumor vs. exoDNA (0.412) were higher than that of tumor vs. normal (0.086). We successfully identified somatic mutations and CNV in UBC using urinary cfDNA and exoDNA. Urinary exoDNA could be another source for liquid biopsy. Also, CNV analysis using sWGS is an alternative strategy for liquid biopsy, providing data from the whole genome at a low cost.

IDH1/2 Mutations Predict Shorter Survival in Chondrosarcoma

Background. Recent studies have shown that isocitrate dehydrogenase 1/2 (IDH1/2)- activating mutations occur in a variety of cancers, including acute myeloid leukaemia, gliomas, and chondrosarcomas (CHS)s. The effect of IDH1/2 mutation on overall survival (OS) has not been reported in CHS. The aim of our study was to assess the prevalence of known cancer-related gene mutations in CHS, as well as their prognostic role in patient survival.

Methods. DNA from FFPE samples of 80 patients (F:M- 1:1.3; mean age: 58 years; range 27-86) with histologically confirmed CHS (G1:29; G2:34; G3:17) was subjected to library preparation with the Ion AmpliSeq Cancer Hotspot Panel v2 and sequenced on the PGM Ion Torrent.

Results. Among the clinical features only histological grade influenced OS. Deep sequencing identified 1784 single nucleotide variants. Of them, 426 were considered to be pathogenic or probably pathogenic. Activating IDH1/2 mutations were found in 27 patients (34%) including 17 R132 IDH1 (21%), 10 R172 IDH2 (13%) and 3 R140 IDH2 variants (4%). Three patients had concurrent IDH1 and IDH2 mutations. The R140 IDH2 mutant has not been reported to date in CHS patients. OS for CHS patients with IDH1/2 mutations was significantly lower than in patients without mutations (93% vs 64%; p<0.001). No other genetic feature of the Cancer Hotspot Panel had an impact on OS.

Conclusions. In CHS, IDH1/2-mutation status and the histological aggressiveness of the CHS are important predictors for OS. The R140 IDH2 may also be a novel target for the treatment of CHS patients.

Low-frequency coding variants in CETP and CFB are associated with susceptibility of exudative age-related macular degeneration in the Japanese population

Age-related macular degeneration (AMD) is a major cause of blindness in the elderly. Previous sequencing studies of AMD susceptibility genes have revealed the association of rare coding variants in CFH, CFI, C3 and C9 in European population; however, the impact of rare or low-frequency coding variants on AMD susceptibility in other populations is largely unknown. To identify the role of low-frequency coding variants on exudative AMD susceptibility in a Japanese population, we analysed the association of coding variants of 34 AMD candidate genes in the two-stage design by a multiplex PCR-based target sequencing method. We used a total of 2,886 (1st: 827, 2nd: 2,059) exudative AMD cases including typical AMD, polypoidal choroidal vasculopathy, and retinal angiomatous proliferation and 9,337 (1st: 3,247 2nd: 6,090) controls. Gene-based analysis found a significant association of low-frequency variants (minor allele frequency (MAF) < 0.05) in CETP, C2 and CFB. The association of CETP remained after conditioned with all known genome-wide association study (GWAS) associated variants. In addition, when we included only disruptive variants, enrichment of rare variants (MAF < 0.01) was also observed after conditioned with all GWAS associated variants (P = 1.03 × 10−6, odds ratio (OR) = 2.48). Haplotype and conditional analysis of the C2-CFB-SKIV2L locus showed a low-frequency variant (R74H) in CFB would be individually associated with AMD susceptibility independent of the GWAS associated SNP. These findings highlight the importance of target sequencing to reveal the impact of rare or low-frequency coding variants on disease susceptibility in different ethnic populations.

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

BRCA1 and BRCA2 genes are implicated in 20-25% of hereditary breast and ovarian cancers. New age sequencing platforms have revolutionized massively parallel sequencing in clinical practice by providing cost effective, rapid, and sensitive sequencing. This study critically evaluates the false positives in multiplex panels and suggests the need for careful analysis. We employed multiplex PCR based BRCA1 and BRCA2 community Panel with ion torrent PGM machine for evaluation of these mutations. Out of all 41samples analyzed for BRCA1 and BRCA2 five were found with 950_951 insA(Asn319fs) at Chr13:32906565 position and one sample with 1032_1033 insA(Asn346fs) at Chr13:32906647, both being frame-shift mutations in BRCA2 gene. 950_951 insA(Asn319fs) mutation is reported as pathogenic allele in NCBI dbSNP. On examination of IGV for all these samples, it was seen that both mutations had 'A' nucleotide insertion at 950, and 1032 position in exon 10 of BRCA2 gene. Sanger Sequencing did not confirm these insertions. Next-generation sequencing shows great promise by allowing rapid mutational analysis of multiple genes in human cancer but our results indicate the need for careful sequence analysis to avoid false positive results.

Low frequency of Fabry disease in patients with common heart disease

PURPOSE

To test the hypothesis that undiagnosed patients with Fabry disease exist among patients affected by common heart disease.

METHODS

Globotriaosylceramide in random whole urine using tandem mass spectroscopy, α-galactosidase A activity in dried blood spots, and next-generation sequencing of pooled or individual genomic DNA samples supplemented by Sanger sequencing.

RESULTS

We tested 2,256 consecutive patients: 852 women (median age 65 years (19-95)) and 1,404 men (median age 65 years (21-92)). The primary diagnoses were coronary artery disease (n = 994), arrhythmia (n = 607), cardiomyopathy (n = 138), and valvular disease (n = 568). Urinary globotriaosylceramide was elevated in 15% of patients and 15 males had low α-galactosidase A activity. GLA variants found included R118C (n = 2), D83N, and D313Y (n = 7); IVS6-22 C>T, IVS4-16 A>G, IVS2+990C>A, 5'UTR-10 C>T (n = 4), IVS1-581 C>T, IVS1-1238 G>A, 5'UTR-30 G>A, IVS2+590C>T, IVS0-12 G>A, IVS4+68A>G, IVS0-10 C>T, IVS2-81-77delCAGCC, IVS2-77delC. Although the pathogenicity of several of these missense mutations and complex intronic haplotypes has been controversial, none of the patients screened in this study were diagnosed definitively with Fabry disease.

CONCLUSION

This population of patients with common heart disease did not contain a substantial number of patients with undiagnosed Fabry disease. GLA gene sequencing is superior to urinary globotriaosylceramide or α-galactosidase A activity in the screening for Fabry disease.

RareVar: A Framework for Detecting Low-Frequency Single-Nucleotide Variants

Accurate identification of low-frequency somatic point mutations in tumor samples has important clinical utilities. Although high-throughput sequencing technology enables capturing such variants while sequencing primary tumor samples, our ability for accurate detection is compromised when the variant frequency is close to the sequencer error rate. Most current experimental and bioinformatic strategies target mutations with ≥5% allele frequency, which limits our ability to understand the cancer etiology and tumor evolution. We present an experimental and computational modeling framework, RareVar, to reliably identify low-frequency single-nucleotide variants from high-throughput sequencing data under standard experimental protocols. RareVar protocol includes a benchmark design by pooling DNAs from already sequenced individuals at various concentrations to target variants at desired frequencies, 0.5%-3% in our case. By applying a generalized, linear model-based, position-specific error model, followed by machine-learning-based variant calibration, our approach outperforms existing methods. Our method can be applied on most capture and sequencing platforms without modifying the experimental protocol.

Ultrasensitive and high-efficiency screen of de novo low-frequency mutations by o2n-seq

Detection of de novo, low-frequency mutations is essential for characterizing cancer genomes and heterogeneous cell populations. However, the screening capacity of current ultrasensitive NGS methods is inadequate owing to either low-efficiency read utilization or severe amplification bias. Here, we present o2n-seq, an ultrasensitive and high-efficiency NGS library preparation method for discovering de novo, low-frequency mutations. O2n-seq reduces the error rate of NGS to 10-5-10-8. The efficiency of its data usage is about 10-30 times higher than that of barcode-based strategies. For detecting mutations with allele frequency (AF) 1% in 4.6 Mb-sized genome, the sensitivity and specificity of o2n-seq reach to 99% and 98.64%, respectively. For mutations with AF around 0.07% in phix174, o2n-seq detects all the mutations with 100% specificity. Moreover, we successfully apply o2n-seq to screen de novo, low-frequency mutations in human tumours. O2n-seq will aid to characterize the landscape of somatic mutations in research and clinical settings.

MAGERI: Computational pipeline for molecular-barcoded targeted resequencing

Unique molecular identifiers (UMIs) show outstanding performance in targeted high-throughput resequencing, being the most promising approach for the accurate identification of rare variants in complex DNA samples. This approach has application in multiple areas, including cancer diagnostics, thus demanding dedicated software and algorithms. Here we introduce MAGERI, a computational pipeline that efficiently handles all caveats of UMI-based analysis to obtain high-fidelity mutation profiles and call ultra-rare variants. Using an extensive set of benchmark datasets including gold-standard biological samples with known variant frequencies, cell-free DNA from tumor patient blood samples and publicly available UMI-encoded datasets we demonstrate that our method is both robust and efficient in calling rare variants. The versatility of our software is supported by accurate results obtained for both tumor DNA and viral RNA samples in datasets prepared using three different UMI-based protocols.

Drug-sensitive FGFR3 mutations in lung adenocarcinoma

BACKGROUND

Lung cancer is the leading cause of cancer-related deaths across the world. In this study, we present therapeutically relevant genetic alterations in lung adenocarcinoma of Indian origin.

MATERIALS AND METHODS

Forty-five primary lung adenocarcinoma tumors were sequenced for 676 amplicons using RainDance cancer panel at an average coverage of 1500 × (reads per million mapped reads). To validate the findings, 49 mutations across 23 genes were genotyped in an additional set of 363 primary lung adenocarcinoma tumors using mass spectrometry. NIH/3T3 cells over expressing mutant and wild-type FGFR3 constructs were characterized for anchorage independent growth, constitutive activation, tumor formation and sensitivity to FGFR inhibitors using in vitro and xenograft mouse models.

RESULTS

We present the first spectrum of actionable alterations in lung adenocarcinoma tumors of Indian origin, and shows that mutations of FGFR3 are present in 20 of 363 (5.5%) patients. These FGFR3 mutations are constitutively active and oncogenic when ectopically expressed in NIH/3T3 cells and using a xenograft model in NOD/SCID mice. Inhibition of FGFR3 kinase activity inhibits transformation of NIH/3T3 overexpressing FGFR3 constructs and growth of tumors driven by FGFR3 in the xenograft models. The reduction in tumor size in the mouse is paralleled by a reduction in the amounts of phospho-ERK, validating the in vitro findings. Interestingly, the FGFR3 mutations are significantly higher in a proportion of younger patients and show a trend toward better overall survival, compared with patients lacking actionable alterations or those harboring KRAS mutations.

CONCLUSION

We present the first actionable mutation spectrum in Indian lung cancer genome. These findings implicate FGFR3 as a novel therapeutic in lung adenocarcinoma.

Microfluidics for genome-wide studies involving next generation sequencing

Next-generation sequencing (NGS) has revolutionized how molecular biology studies are conducted. Its decreasing cost and increasing throughput permit profiling of genomic, transcriptomic, and epigenomic features for a wide range of applications. Microfluidics has been proven to be highly complementary to NGS technology with its unique capabilities for handling small volumes of samples and providing platforms for automation, integration, and multiplexing. In this article, we review recent progress on applying microfluidics to facilitate genome-wide studies. We emphasize on several technical aspects of NGS and how they benefit from coupling with microfluidic technology. We also summarize recent efforts on developing microfluidic technology for genomic, transcriptomic, and epigenomic studies, with emphasis on single cell analysis. We envision rapid growth in these directions, driven by the needs for testing scarce primary cell samples from patients in the context of precision medicine.

Applications of molecular testing in surgical pathology of the head and neck

Molecular testing in routine surgical pathology is becoming an important component of the workup of many different types of tumors. In fact, in some organ systems, guidelines now suggest that the standard of care is to obtain specific molecular panels for tumor classification and/or therapeutic planning. In the head and neck, clinically applicable molecular tests are not as abundant as in other organ systems. Most current head and neck biomarkers are utilized for diagnosis rather than as companion diagnostic tests to predict therapeutic response. As the number of potential molecular biomarker assays increases and cost pressures escalate, the pathologist must be able to navigate the molecular testing pathways. This review explores scenarios in which molecular testing might be beneficial and cost-effective in head and neck pathology.

Droplet-Based Digital PCR: Application in Cancer Research

The efficient characterization of genetic and epigenetic alterations in oncology, virology, or prenatal diagnostics requires highly sensitive and specific high-throughput approaches. Nevertheless, with the use of conventional methods, sensitivity and specificity were largely limited. By partitioning individual target molecules within distinct compartments, digital PCR (dPCR) could overcome these limitations and detect very rare sequences with unprecedented precision and sensitivity. In dPCR, the sample is diluted such that each individual partition will contain no more than one target sequence. Following the assay reaction, the dPCR process provides an absolute value and analyzable quantitative data. The recent coupling of dPCR with microfluidic systems in commercial platforms should lead to an essential tool for the management of patients with cancer, especially adapted to the analysis of precious samples. Applications in cancer research range from the analysis of tumor heterogeneity to that of a range of body fluids. Droplet-based dPCR is indeed particularly appropriate for the emerging field of liquid biopsy analysis. In this review, following an overview of the development in dPCR technology and different strategies based on the use of microcompartments, we will focus particularly on the applications and latest development of microfluidic droplet-based dPCR in oncology.

Long Single-Molecule Reads Can Resolve the Complexity of the Influenza Virus Composed of Rare, Closely Related Mutant Variants

As a result of a high rate of mutations and recombination events, an RNA-virus exists as a heterogeneous "swarm" of mutant variants. The long read length offered by single-molecule sequencing technologies allows each mutant variant to be sequenced in a single pass. However, high error rate limits the ability to reconstruct heterogeneous viral population composed of rare, related mutant variants. In this article, we present two single-nucleotide variants (2SNV), a method able to tolerate the high error rate of the single-molecule protocol and reconstruct mutant variants. 2SNV uses linkage between single-nucleotide variations to efficiently distinguish them from read errors. To benchmark the sensitivity of 2SNV, we performed a single-molecule sequencing experiment on a sample containing a titrated level of known viral mutant variants. Our method is able to accurately reconstruct clone with frequency of 0.2% and distinguish clones that differed in only two nucleotides distantly located on the genome. 2SNV outperforms existing methods for full-length viral mutant reconstruction.

Statistical modeling for sensitive detection of low-frequency single nucleotide variants

Background

Sensitive detection of low-frequency single nucleotide variants carries great significance in many applications. In cancer genetics research, tumor biopsies are a mixture of normal and tumor cells from various subpopulations due to tumor heterogeneity. Thus the frequencies of somatic variants from a subpopulation tend to be low. Liquid biopsies, which monitor circulating tumor DNA in blood to detect metastatic potential, also face the challenge of detecting low-frequency variants due to the small percentage of the circulating tumor DNA in blood. Moreover, in population genetics research, although pooled sequencing of a large number of individuals is cost-effective, pooling dilutes the signals of variants from any individual. Detection of low frequency variants is difficult and can be cofounded by sequencing artifacts. Existing methods are limited in sensitivity and mainly focus on frequencies around 2 % to 5 %; most fail to consider differential sequencing artifacts.

Results

We aimed to push down the frequency detection limit close to the position specific sequencing error rates by modeling the observed erroneous read counts with respect to genomic sequence contexts. 4 distributions suitable for count data modeling (using generalized linear models) were extensively characterized in terms of their goodness-of-fit as well as the performances on real sequencing data benchmarks, which were specifically designed for testing detection of low-frequency variants; two sequencing technologies with significantly different chemistry mechanisms were used to explore systematic errors. We found the zero-inflated negative binomial distribution generalized linear mode is superior to the other models tested, and the advantage is most evident at 0.5 % to 1 % range. This method is also generalizable to different sequencing technologies. Under standard sequencing protocols and depth given in the testing benchmarks, 95.3 % recall and 79.9 % precision for Ion Proton data, 95.6 % recall and 97.0 % precision for Illumina MiSeq data were achieved for SNVs with frequency > = 1 %, while the detection limit is around 0.5 %.

Conclusions

Our method enables sensitive detection of low-frequency single nucleotide variants across different sequencing platforms and will facilitate research and clinical applications such as pooled sequencing, cancer early detection, prognostic assessment, metastatic monitoring, and relapses or acquired resistance identification.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2905-x) contains supplementary material, which is available to authorized users.

Using ultra-sensitive next generation sequencing to dissect DNA damage-induced mutagenesis

Next generation sequencing (NGS) technologies have dramatically improved studies in biology and biomedical science. However, no optimal NGS approach is available to conveniently analyze low frequency mutations caused by DNA damage treatments. Here, by developing an exquisite ultra-sensitive NGS (USNGS) platform “EasyMF” and incorporating it with a widely used supF shuttle vector-based mutagenesis system, we can conveniently dissect roles of lesion bypass polymerases in damage-induced mutagenesis. In this improved mutagenesis analysis pipeline, the initial steps are the same as in the supF mutation assay, involving damaging the pSP189 plasmid followed by its transfection into human 293T cells to allow replication to occur. Then “EasyMF” is employed to replace downstream MBM7070 bacterial transformation and other steps for analyzing damage-induced mutation frequencies and spectra. This pipeline was validated by using UV damaged plasmid after its replication in lesion bypass polymerase-deficient 293T cells. The increased throughput and reduced cost of this system will allow us to conveniently screen regulators of translesion DNA synthesis pathway and monitor environmental genotoxic substances, which can ultimately provide insight into the mechanisms of genome stability and mutagenesis.

Ultra-precise detection of mutations by droplet-based amplification of circularized DNA

Background

NGS (next generation sequencing) has been widely used in studies of biological processes, ranging from microbial evolution to cancer genomics. However, the error rate of NGS (0.1 % ~ 1 %) is still remaining a great challenge for comprehensively investigating the low frequency variations, and the current solution methods have suffered severe amplification bias or low efficiency.

Results

We creatively developed Droplet-CirSeq for relatively efficient, low-bias and ultra-sensitive identification of variations by combining millions of picoliter uniform-sized droplets with Cir-seq. Droplet-CirSeq is entitled with an incredibly low error rate of 3 ~ 5 X 10^-6. To systematically evaluate the performances of amplification uniformity and capability of mutation identification for Droplet-CirSeq, we took the mixtures of two E. coli strains as specific instances to simulate the circumstances of mutations with different frequencies. Compared with Cir-seq, the coefficient of variance of read depth for Droplet-CirSeq was 10 times less (p = 2.6 X 10^-3), and the identified allele frequency presented more concentrated to the authentic frequency of mixtures (p = 4.8 X 10^-3), illustrating a significant improvement of amplification bias and accuracy in allele frequency determination. Additionally, Droplet-CirSeq detected 2.5 times genuine SNPs (p < 0.001), achieved a 2.8 times lower false positive rate (p < 0.05) and a 1.5 times lower false negative rate (p < 0.001), in the case of a 3 pg DNA input. Intriguingly, the false positive sites predominantly represented in two types of base substitutions (G- > A, C- > T). Our findings indicated that 30 pg DNA input accommodated in 5 ~ 10 million droplets resulted in maximal detection of authentic mutations compared to 3 pg (p = 1.2 X 10^-8) and 300 pg input (p = 2.2 X 10^-3).

Conclusions

We developed a method namely Droplet-CirSeq to significantly improve the amplification bias, which presents obvious superiority over the currently prevalent methods in exploitation of ultra-low frequency mutations. Droplet-CirSeq would be promisingly used in the identification of low frequency mutations initiated from extremely low input DNA, such as DNA of uncultured microorganisms, captured DNA of target region, circulation DNA of plasma et al, and its creative conception of rolling circle amplification in droplets would also be used in other low input DNA amplification fields.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2480-1) contains supplementary material, which is available to authorized users.

MIG-seq: an effective PCR-based method for genome-wide single-nucleotide polymorphism genotyping using the next-generation sequencing platform

Restriction-enzyme (RE)-based next-generation sequencing methods have revolutionized marker-assisted genetic studies; however, the use of REs has limited their widespread adoption, especially in field samples with low-quality DNA and/or small quantities of DNA. Here, we developed a PCR-based procedure to construct reduced representation libraries without RE digestion steps, representing de novo single-nucleotide polymorphism discovery, and its genotyping using next-generation sequencing. Using multiplexed inter-simple sequence repeat (ISSR) primers, thousands of genome-wide regions were amplified effectively from a wide variety of genomes, without prior genetic information. We demonstrated: 1) Mendelian gametic segregation of the discovered variants; 2) reproducibility of genotyping by checking its applicability for individual identification; and 3) applicability in a wide variety of species by checking standard population genetic analysis. This approach, called multiplexed ISSR genotyping by sequencing, should be applicable to many marker-assisted genetic studies with a wide range of DNA qualities and quantities.

MSIplus for Integrated Colorectal Cancer Molecular Testing by Next-Generation Sequencing

Molecular analysis of colon cancers currently requires multiphasic testing that uses various assays with different performance characteristics, adding cost and time to patient care. We have developed a single, next-generation sequencing assay to simultaneously evaluate colorectal cancers for mutations in relevant cancer genes (KRAS, NRAS, and BRAF) and for tumor microsatellite instability (MSI). In a sample set of 61 cases, the assay demonstrated overall sensitivity of 100% and specificity of 100% for identifying cancer-associated mutations, with a practical limit of detection at 2% mutant allele fraction. MSIplus was 97% sensitive (34 of 35 MSI-positive cases) and 100% specific (42 of 42 MSI-negative cases) for ascertaining MSI phenotype in a cohort of 78 tumor specimens. These performance characteristics were slightly better than for conventional multiplex PCR MSI testing (97% sensitivity and 95% specificity), which is based on comparison of microsatellite loci amplified from tumor and matched normal material, applied to the same specimen cohort. Because the assay uses an amplicon sequencing approach, it is rapid and appropriate for specimens with limited available material or fragmented DNA. This integrated testing strategy offers several advantages over existing methods, including a lack of need for matched normal material, sensitive and unbiased detection of variants in target genes, and an automated analysis pipeline enabling principled and reproducible identification of cancer-associated mutations and MSI status simultaneously.

An advanced preclinical mouse model for acute myeloid leukemia using patients' cells of various genetic subgroups and in vivo bioluminescence imaging

Acute myeloid leukemia (AML) is a clinically and molecularly heterogeneous disease with poor outcome. Adequate model systems are required for preclinical studies to improve understanding of AML biology and to develop novel, rational treatment approaches. Xenografts in immunodeficient mice allow performing functional studies on patient-derived AML cells. We have established an improved model system that integrates serial retransplantation of patient-derived xenograft (PDX) cells in mice, genetic manipulation by lentiviral transduction, and essential quality controls by immunophenotyping and targeted resequencing of driver genes. 17/29 samples showed primary engraftment, 10/17 samples could be retransplanted and some of them allowed virtually indefinite serial transplantation. 5/6 samples were successfully transduced using lentiviruses. Neither serial transplantation nor genetic engineering markedly altered sample characteristics analyzed. Transgene expression was stable in PDX AML cells. Example given, recombinant luciferase enabled bioluminescence in vivo imaging and highly sensitive and reliable disease monitoring; imaging visualized minimal disease at 1 PDX cell in 10000 mouse bone marrow cells and facilitated quantifying leukemia initiating cells. We conclude that serial expansion, genetic engineering and imaging represent valuable tools to improve the individualized xenograft mouse model of AML. Prospectively, these advancements enable repetitive, clinically relevant studies on AML biology and preclinical treatment trials on genetically defined and heterogeneous subgroups.

AmpliVar: mutation detection in high-throughput sequence from amplicon-based libraries

Conventional means of identifying variants in high-throughput sequencing align each read against a reference sequence, and then call variants at each position. Here, we demonstrate an orthogonal means of identifying sequence variation by grouping the reads as amplicons prior to any alignment. We used AmpliVar to make key-value hashes of sequence reads and group reads as individual amplicons using a table of flanking sequences. Low-abundance reads were removed according to a selectable threshold, and reads above this threshold were aligned as groups, rather than as individual reads, permitting the use of sensitive alignment tools. We show that this approach is more sensitive, more specific, and more computationally efficient than comparable methods for the analysis of amplicon-based high-throughput sequencing data. The method can be extended to enable alignment-free confirmation of variants seen in hybridization capture target-enrichment data.

Gene expression-based prognostic and predictive tools in breast cancer

Genomic assays measuring the expression of multiple genes have made their way into clinical practice and their utilization is now recommended by major international guidelines. A basic property of these tests is their capability to sub-divide patients into high- and low-risk cohorts thereby providing prognostic, and in certain settings, predictive decision support. Here, we summarize commercially available assays for breast cancer including RT-PCR and gene chip-based tests. Given the relative uncertainty in cancer treatment, multigene tests have the potential for a significant cost reduction as they can pinpoint those patients for whom chemotherapy proves to be unnecessary. However, concordance of risk assessment for an individual patient is still far from optimal. Additionally, emerging multigene approaches focus on predicting therapy response, which is a black spot of current tests. Promising techniques include the homologous recombination deficiency score, utilization of massive parallel sequencing to identify driver genes, employment of internet-based meta-analysis tools and investigation of miRNA expression signatures. Combination of multiple simultaneous analyses at diagnosis, including classical histopathological diagnostics, monogenic markers, genomic signatures and clinical parameters will most likely bring maximal benefit for patients. As the main driving force behind such genomic tests is the power to achieve cost reduction due to avoiding unnecessary systemic treatment, the future is most likely to hold a further proliferation of such assays.

Sequence Artifacts in DNA from Formalin-Fixed Tissues: Causes and Strategies for Minimization

BACKGROUND

Precision medicine is dependent on identifying actionable mutations in tumors. Accurate detection of mutations is often problematic in formalin-fixed paraffin-embedded (FFPE) tissues. DNA extracted from formalin-fixed tissues is fragmented and also contains DNA lesions that are the sources of sequence artifacts. Sequence artifacts can be difficult to distinguish from true mutations, especially in the context of tumor heterogeneity, and are an increasing interpretive problem in this era of massively parallel sequencing. Understanding of the sources of sequence artifacts in FFPE tissues and implementation of preventative strategies are critical to improve the accurate detection of actionable mutations.

CONTENT

This mini-review focuses on DNA template lesions in FFPE tissues as the source of sequence artifacts in molecular analysis. In particular, fragmentation, base modification (including uracil and thymine deriving from cytosine deamination), and abasic sites are discussed as indirect or direct sources of sequence artifacts. We discuss strategies that can be implemented to minimize sequence artifacts and to distinguish true mutations from sequence artifacts. These strategies are applicable for the detection of actionable mutations in both single amplicon and massively parallel amplicon sequencing approaches.

SUMMARY

Because FFPE tissues are usually the only available material for DNA analysis, it is important to maximize the accurate informational content from FFPE DNA. Careful consideration of each step in the work flow is needed to minimize sequence artifacts. In addition, validation of actionable mutations either by appropriate experimental design or by orthogonal methods should be considered.

Evaluation of an integrated clinical workflow for targeted next-generation sequencing of low-quality tumor DNA using a 51-gene enrichment panel

Background

Improvements in both performance and cost for next-generation sequencing (NGS) have spurred its rapid adoption for clinical applications. We designed and optimized a pan-cancer target-enrichment panel for 51 well-established oncogenes and tumor suppressors, in conjunction with a bioinformatic pipeline informed by in-process controls and pre- and post-analytical quality control measures.

Methods

The evaluation of this workflow consisted of sequencing mixtures of intact DNA to establish analytical sensitivity and precision, utilization of heuristics to identify systematic artifacts, titration studies of intact and FFPE samples for input optimization, and incorporation of orthogonal sequencing strategies to increase both positive predictive value and variant detection. We also used 128 FFPE samples to assess clinical accuracy and incorporated the previously described quantitative functional index (QFI) for sample qualification as part of detailing complete system performance.

Results

We observed a concordance correlation coefficient of 0.99 between the observed versus expected percent variant at 250 ng input across 4 independent sequencing runs. A subset of the systematic variants were confirmed to be barely detectable on an independent sequencing platform (Wilcox signed-rank test p-value <10⁻¹⁶), and the incorporation of orthogonal sequencing strategies increased the harmonic mean of sensitivity and positive predictive value of mutation detection by 41%. In one cohort of FFPE tumor samples, coverage and inter-platform concordance were positively correlated with the QFI, emphasizing the need for pre-analytical sample quality control to reduce the risk of false positives and negatives. In a separate cohort of FFPE samples, the 51-gene panel achieved 78% sensitivity (95% CI = 56.3, 92.5) with 100% PPV (95% CI = 81.5, 100.0) based on known mutations at 7.9% median abundance. By sequencing specimens using an orthogonal NGS technology, sensitivity was improved to 87.0% (95% CI = 66.4,97.2) while maintaining PPV.

Conclusions

The results highlight the value of process integration in a comprehensive targeted NGS system, enabling both discovery and diagnostic applications, particularly when sequencing low-quality cancer specimens.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-014-0062-0) contains supplementary material, which is available to authorized users.

Detection of minimal residual disease in NPM1-mutated acute myeloid leukemia by next-generation sequencing

Detection of minimal residual disease predicts adverse outcome in patients with acute myeloid leukemia. Currently, minimal residual disease may be detected by RQ-PCR or flow cytometry, both of which have practical and diagnostic limitations. Here, we describe a next-generation sequencing assay for minimal residual disease detection in NPM1-mutated acute myeloid leukemia, which encompasses ∼60% of patients with normal karyotype acute myeloid leukemia. Exon 12 of NPM1 was PCR amplified using sequencing adaptor-linked primers and deep sequenced to enable detection of low-prevalence, acute myeloid leukemia-specific activating mutations. We benchmarked our results against flow cytometry, the standard of care for acute myeloid leukemia minimal residual disease diagnosis at our institution. The performance of both approaches was evaluated using defined dilutions of an NPM1 mutation-positive cell line and longitudinal clinical samples from acute myeloid leukemia patients. Using defined control material, we found this assay sensitive to approximately 0.001% mutant cells, outperforming flow cytometry by an order of magnitude. Next-generation sequencing was precise and semiquantitative over four orders of magnitude. In 22 longitudinal samples from six acute myeloid leukemia patients, next-generation sequencing detected minimal residual disease in all samples deemed negative by flow cytometry. Further, in one-third of patients, sequencing detected alternate NPM1 mutations in addition to the patient's index mutation, consistent with tumor heterogeneity. Next-generation sequencing provides information without prior knowledge of NPM1 mutation subtype or validation of allele-specific probes as required for RQ-PCR assays, and without generation and interpretation of complex multidimensional flow cytometry data. This approach may complement current technologies to enhance patient-specific clinical decision-making.

Simultaneous genomic identification and profiling of a single cell using semiconductor-based next generation sequencing

Combining single-cell methods and next-generation sequencing should provide a powerful means to understand single-cell biology and obviate the effects of sample heterogeneity. Here we report a single-cell identification method and seamless cancer gene profiling using semiconductor-based massively parallel sequencing. A549 cells (adenocarcinomic human alveolar basal epithelial cell line) were used as a model. Single-cell capture was performed using laser capture microdissection (LCM) with an Arcturus® XT system, and a captured single cell and a bulk population of A549 cells (≈ 10⁶ cells) were subjected to whole genome amplification (WGA). For cell identification, a multiplex PCR method (AmpliSeq™ SNP HID panel) was used to enrich 136 highly discriminatory SNPs with a genotype concordance probability of 10^31–35. For cancer gene profiling, we used mutation profiling that was performed in parallel using a hotspot panel for 50 cancer-related genes. Sequencing was performed using a semiconductor-based bench top sequencer. The distribution of sequence reads for both HID and Cancer panel amplicons was consistent across these samples. For the bulk population of cells, the percentages of sequence covered at coverage of more than 100 × were 99.04% for the HID panel and 98.83% for the Cancer panel, while for the single cell percentages of sequence covered at coverage of more than 100 × were 55.93% for the HID panel and 65.96% for the Cancer panel. Partial amplification failure or randomly distributed non-amplified regions across samples from single cells during the WGA procedures or random allele drop out probably caused these differences. However, comparative analyses showed that this method successfully discriminated a single A549 cancer cell from a bulk population of A549 cells. Thus, our approach provides a powerful means to overcome tumor sample heterogeneity when searching for somatic mutations.

Novel droplet platforms for the detection of disease biomarkers

Personalized medicine - healthcare based on individual genetic variation - has the potential to transform the way healthcare is delivered to patients. The promise of personalized medicine has been predicated on the predictive and diagnostic power of genomic and proteomic biomarkers. Biomarker screening may help improve health outcomes, for example, by identifying individuals' susceptibility to diseases and predicting how patients will respond to drugs. Microfluidic droplet technology offers an exciting opportunity to revolutionize the accessibility of personalized medicine. A framework for the role of droplet microfluidics in biomarker detection can be based on two main themes. Emulsion-based microdroplet platforms can provide new ways to measure and detect biomolecules. In addition, microdroplet platforms facilitate high-throughput screening of biomarkers. Meanwhile, surface-based droplet platforms provide an opportunity to develop miniaturized diagnostic systems. These platforms may function as portable benchtop environments that dramatically shorten the transition of a benchtop assay into a point-of-care format.

Mung bean nuclease treatment increases capture specificity of microdroplet-PCR based targeted DNA enrichment

Targeted DNA enrichment coupled with next generation sequencing has been increasingly used for interrogation of select sub-genomic regions at high depth of coverage in a cost effective manner. Specificity measured by on-target efficiency is a key performance metric for target enrichment. Non-specific capture leads to off-target reads, resulting in waste of sequencing throughput on irrelevant regions. Microdroplet-PCR allows simultaneous amplification of up to thousands of regions in the genome and is among the most commonly used strategies for target enrichment. Here we show that carryover of single-stranded template genomic DNA from microdroplet-PCR constitutes a major contributing factor for off-target reads in the resultant libraries. Moreover, treatment of microdroplet-PCR enrichment products with a nuclease specific to single-stranded DNA alleviates off-target load and improves enrichment specificity. We propose that nuclease treatment of enrichment products should be incorporated in the workflow of targeted sequencing using microdroplet-PCR for target capture. These findings may have a broad impact on other PCR based applications for which removal of template DNA is beneficial.

False positives in multiplex PCR-based next-generation sequencing have unique signatures

Next-generation sequencing shows great promise by allowing rapid mutational analysis of multiple genes in human cancers. Recently, we implemented the multiplex PCR-based Ion AmpliSeq Cancer Hotspot Panel (>200 amplicons in 50 genes) to evaluate EGFR, KRAS, and BRAF in lung and colorectal adenocarcinomas. In 10% of samples, automated analysis identified a novel G873R substitution mutation in EGFR. By examining reads individually, we found this mutation in >5% of reads in 50 of 291 samples and also found similar events in 18 additional amplicons. These apparent mutations are present only in short reads and within 10 bases of either end of the read. We therefore hypothesized that these were from panel primers promiscuously binding to nearly complementary sequences of nontargeted amplicons. Sequences around the mutations matched primer binding sites in the panel in 18 of 19 cases, thus likely corresponding to panel primers. Furthermore, because most primers did not show this effect, we demonstrated that next-generation sequencing may be used to better design multiplex PCR primers through iterative elimination of offending primers to minimize mispriming. Our results indicate the need for careful sequence analysis to avoid false-positive mutations that can arise in multiplex PCR panels. The AmpliSeq Cancer panel is a valuable tool for clinical diagnostics, provided awareness of potential artifacts.

Microsatellite instability detection by next generation sequencing

BACKGROUND

Microsatellite instability (MSI) is a useful phenotype in cancer diagnosis and prognosis. Nevertheless, methods to detect MSI status from next generation DNA sequencing (NGS) data are underdeveloped.

METHODS

We developed an approach to detect the MSI phenotype using NGS (mSINGS). The method was used to evaluate mononucleotide microsatellite loci that were incidentally sequenced after targeted gene enrichment and could be applied to gene or exome capture panels designed for other purposes. For each microsatellite locus, the number of differently sized repeats in experimental samples were quantified and compared to a population of normal controls. Loci were considered unstable if the experimental number of repeats was statistically greater than in the control population. MSI status was determined by the fraction of unstable microsatellite loci.

RESULTS

We examined data from 324 samples generated using targeted gene capture assays of 3 different sizes, ranging from a 0.85-Mb to a 44-Mb exome design and incorporating from 15 to 2957 microsatellite markers. When we compared mSING results to MSI-PCR as a gold standard for 108 cases, we found the approach to be both diagnostically sensitive (range of 96.4% to 100% across 3 panels) and specific (range of 97.2% to 100%) for determining MSI status. The fraction of unstable microsatellite markers calculated from sequencing data correlated with the number of unstable loci detected by conventional MSI-PCR testing.

CONCLUSIONS

NGS data can enable highly accurate detection of MSI, even from limited capture designs. This novel approach offers several advantages over existing PCR-based methods.

t(14;18) Translocation: A predictive blood biomarker for follicular lymphoma

PURPOSE

The (14;18) translocation constitutes both a genetic hallmark and critical early event in the natural history of follicular lymphoma (FL). However, t(14;18) is also detectable in the blood of otherwise healthy persons, and its relationship with progression to disease remains unclear. Here we sought to determine whether t(14;18)-positive cells in healthy individuals represent tumor precursors and whether their detection could be used as an early predictor for FL.

PARTICIPANTS AND METHODS

Among 520,000 healthy participants enrolled onto the EPIC (European Prospective Investigation Into Cancer and Nutrition) cohort, we identified 100 who developed FL 2 to 161 months after enrollment. Prediagnostic blood from these and 218 controls were screened for t(14;18) using sensitive polymerase chain reaction-based assays. Results were subsequently validated in an independent cohort (65 case participants; 128 controls). Clonal relationships between t(14;18) cells and FL were also assessed by molecular backtracking of paired prediagnostic blood and tumor samples.

RESULTS

Clonal analysis of t(14;18) junctions in paired prediagnostic blood versus tumor samples demonstrated that progression to FL occurred from t(14;18)-positive committed precursors. Furthermore, healthy participants at enrollment who developed FL up to 15 years later showed a markedly higher t(14;18) prevalence and frequency than controls (P < .001). Altogether, we estimated a 23-fold higher risk of subsequent FL in blood samples associated with a frequency > 10(-4) (odds ratio, 23.17; 95% CI, 9.98 to 67.31; P < .001). Remarkably, risk estimates remained high and significant up to 15 years before diagnosis.

CONCLUSION

High t(14;18) frequency in blood from healthy individuals defines the first predictive biomarker for FL, effective years before diagnosis.

PyClone: statistical inference of clonal population structure in cancer

We introduce PyClone, a statistical model for inference of clonal population structures in cancers. PyClone is a Bayesian clustering method for grouping sets of deeply sequenced somatic mutations into putative clonal clusters while estimating their cellular prevalences and accounting for allelic imbalances introduced by segmental copy-number changes and normal-cell contamination. Single-cell sequencing validation demonstrates PyClone's accuracy.

Targeted-capture massively-parallel sequencing enables robust detection of clinically informative mutations from formalin-fixed tumours

Massively parallel sequencing offers the ability to interrogate a tumour biopsy for multiple mutational changes. For clinical samples, methodologies must enable maximal extraction of available sequence information from formalin-fixed and paraffin-embedded (FFPE) material. We assessed the use of targeted capture for mutation detection in FFPE DNA. The capture probes targeted the coding region of all known kinase genes and selected oncogenes and tumour suppressor genes. Seven melanoma cell lines and matching FFPE xenograft DNAs were sequenced. An informatics pipeline was developed to identify variants and contaminating mouse reads. Concordance of 100% was observed between unfixed and formalin-fixed for reported COSMIC variants including BRAF V600E. mutations in genes not conventionally screened including ERBB4, ATM, STK11 and CDKN2A were readily detected. All regions were adequately covered with independent reads regardless of GC content. This study indicates that hybridisation capture is a robust approach for massively parallel sequencing of FFPE samples.

Evaluation of ultra-deep targeted sequencing for personalized breast cancer care

INTRODUCTION

The increasing number of targeted therapies, together with a deeper understanding of cancer genetics and drug response, have prompted major healthcare centers to implement personalized treatment approaches relying on high-throughput tumor DNA sequencing. However, the optimal way to implement this transformative methodology is not yet clear. Current assays may miss important clinical information such as the mutation allelic fraction, the presence of sub-clones or chromosomal rearrangements, or the distinction between inherited variants and somatic mutations. Here, we present the evaluation of ultra-deep targeted sequencing (UDT-Seq) to generate and interpret the molecular profile of 38 breast cancer patients from two academic medical centers.

METHODS

We sequenced 47 genes in matched germline and tumor DNA samples from 38 breast cancer patients. The selected genes, or the pathways they belong to, can be targeted by drugs or are important in familial cancer risk or drug metabolism.

RESULTS

Relying on the added value of sequencing matched tumor and germline DNA and using a dedicated analysis, UDT-Seq has a high sensitivity to identify mutations in tumors with low malignant cell content. Applying UDT-Seq to matched tumor and germline specimens from the 38 patients resulted in a proposal for at least one targeted therapy for 22 patients, the identification of tumor sub-clones in 3 patients, the suggestion of potential adverse drug effects in 3 patients and a recommendation for genetic counseling for 2 patients.

CONCLUSION

Overall our study highlights the additional benefits of a sequencing strategy, which includes germline DNA and is optimized for heterogeneous tumor tissues.

Amplification and thrifty single-molecule sequencing of recurrent somatic structural variations

Deletion of tumor-suppressor genes as well as other genomic rearrangements pervade cancer genomes across numerous types of solid tumor and hematologic malignancies. However, even for a specific rearrangement, the breakpoints may vary between individuals, such as the recurrent CDKN2A deletion. Characterizing the exact breakpoints for structural variants (SVs) is useful for designating patient-specific tumor biomarkers. We propose AmBre (Amplification of Breakpoints), a method to target SV breakpoints occurring in samples composed of heterogeneous tumor and germline DNA. Additionally, AmBre validates SVs called by whole-exome/genome sequencing and hybridization arrays. AmBre involves a PCR-based approach to amplify the DNA segment containing an SV's breakpoint and then confirms breakpoints using sequencing by Pacific Biosciences RS. To amplify breakpoints with PCR, primers tiling specified target regions are carefully selected with a simulated annealing algorithm to minimize off-target amplification and maximize efficiency at capturing all possible breakpoints within the target regions. To confirm correct amplification and obtain breakpoints, PCR amplicons are combined without barcoding and simultaneously long-read sequenced using a single SMRT cell. Our algorithm efficiently separates reads based on breakpoints. Each read group supporting the same breakpoint corresponds with an amplicon and a consensus amplicon sequence is called. AmBre was used to discover CDKN2A deletion breakpoints in cancer cell lines: A549, CEM, Detroit562, MOLT4, MCF7, and T98G. Also, we successfully assayed RUNX1–RUNX1T1 reciprocal translocations by finding both breakpoints in the Kasumi-1 cell line. AmBre successfully targets SVs where DNA harboring the breakpoints are present in 1:1000 mixtures.

Performance of common analysis methods for detecting low-frequency single nucleotide variants in targeted next-generation sequence data

Next-generation sequencing (NGS) is becoming a common approach for clinical testing of oncology specimens for mutations in cancer genes. Unlike inherited variants, cancer mutations may occur at low frequencies because of contamination from normal cells or tumor heterogeneity and can therefore be challenging to detect using common NGS analysis tools, which are often designed for constitutional genomic studies. We generated high-coverage (>1000×) NGS data from synthetic DNA mixtures with variant allele fractions (VAFs) of 25% to 2.5% to assess the performance of four variant callers, SAMtools, Genome Analysis Toolkit, VarScan2, and SPLINTER, in detecting low-frequency variants. SAMtools had the lowest sensitivity and detected only 49% of variants with VAFs of approximately 25%; whereas the Genome Analysis Toolkit, VarScan2, and SPLINTER detected at least 94% of variants with VAFs of approximately 10%. VarScan2 and SPLINTER achieved sensitivities of 97% and 89%, respectively, for variants with observed VAFs of 1% to 8%, with >98% sensitivity and >99% positive predictive value in coding regions. Coverage analysis demonstrated that >500× coverage was required for optimal performance. The specificity of SPLINTER improved with higher coverage, whereas VarScan2 yielded more false positive results at high coverage levels, although this effect was abrogated by removing low-quality reads before variant identification. Finally, we demonstrate the utility of high-sensitivity variant callers with data from 15 clinical lung cancers.