Detection Of Single Nucleotide Variants Research Articles

Targeted RNA-Sequencing Enables Detection of Relevant Translocations and Single Nucleotide Variants and Provides a Method for Classification of Hematological Malignancies-RANKING.

Patients with hematological malignancies (HMs) carry a wide range of chromosomal and molecular abnormalities that impact their prognosis and treatment. Since no current technique can detect all relevant abnormalities, technique(s) are chosen depending on the reason for referral, and abnormalities can be missed. We tested targeted transcriptome sequencing as a single platform to detect all relevant abnormalities and compared it to current techniques. We performed RNA-sequencing of 1385 genes (TruSight RNA Pan-Cancer, Illumina) in bone marrow from 136 patients with a primary diagnosis of HM. We then applied machine learning to expression profile data to perform leukemia classification, a method we named RANKING. Gene fusions for all the genes in the panel were detected, and overexpression of the genes EVI1, CCND1, and BCL2 was quantified. Single nucleotide variants/indels were analyzed in acute myeloid leukemia (AML), myelodysplastic syndrome and patients with acute lymphoblastic leukemia (ALL) using a virtual myeloid (54 genes) or lymphoid panel (72 genes). RANKING correctly predicted the leukemia classification of all AML and ALL samples and improved classification in 3 patients. Compared to current methods, only one variant was missed, c.2447A>T in KIT (RT-PCR at 10-4), and BCL2 overexpression was not seen due to a t(14; 18)(q32; q21) in 2% of the cells. Our RNA-sequencing method also identified 6 additional fusion genes and overexpression of CCND1 due to a t(11; 14)(q13; q32) in 2 samples. Our combination of targeted RNA-sequencing and data analysis workflow can improve the detection of relevant variants, and expression patterns can assist in establishing HM classification.

Peptide-Affinity Precipitation of Extracellular Vesicles and Cell-Free DNA Improves Sequencing Performance for the Detection of Pathogenic Mutations in Lung Cancer Patient Plasma.

Liquid biopsy is a minimally-invasive diagnostic method that may improve access to molecular profiling for non-small cell lung cancer (NSCLC) patients. Although cell-free DNA (cf-DNA) isolation from plasma is the standard liquid biopsy method for detecting DNA mutations in cancer patients, the sensitivity can be highly variable. Vn96 is a peptide with an affinity for both extracellular vesicles (EVs) and circulating cf-DNA. In this study, we evaluated whether peptide-affinity (PA) precipitation of EVs and cf-DNA from NSCLC patient plasma improves the sensitivity of single nucleotide variants (SNVs) detection and compared observed SNVs with those reported in the matched tissue biopsy. NSCLC patient plasma was subjected to either PA precipitation or cell-free methods and total nucleic acid (TNA) was extracted; SNVs were then detected by next-generation sequencing (NGS). PA led to increased recovery of DNA as well as an improvement in NGS sequencing parameters when compared to cf-TNA. Reduced concordance with tissue was observed in PA-TNA (62%) compared to cf-TNA (81%), mainly due to identification of SNVs in PA-TNA that were not observed in tissue. EGFR mutations were detected in PA-TNA with 83% sensitivity and 100% specificity. In conclusion, PA-TNA may improve the detection limits of low-abundance alleles using NGS.

Simultaneous Detection of CNVs and SNVs Improves the Diagnostic Yield of Fetuses with Ultrasound Anomalies and Normal Karyotypes.

The routine assessment to determine the genetic etiology for fetal ultrasound anomalies follows a sequential approach, which usually takes about 6–8 weeks turnaround time (TAT). We evaluated the clinical utility of simultaneous detection of copy number variations (CNVs) and single nucleotide variants (SNVs)/small insertion-deletions (indels) in fetuses with a normal karyotype with ultrasound anomalies. We performed CNV detection by chromosomal microarray analysis (CMA) or low pass CNV-sequencing (CNV-seq), and in parallel SNVs/indels detection by trio-based clinical exome sequencing (CES) or whole exome sequencing (WES). Eight-three singleton pregnancies with a normal fetal karyotype were enrolled in this prospective observational study. Pathogenic or likely pathogenic variations were identified in 30 cases (CNVs in 3 cases, SNVs/indels in 27 cases), indicating an overall molecular diagnostic rate of 36.1% (30/83). Two cases had both a CNV of uncertain significance (VOUS) and likely pathogenic SNV, and one case carried both a VOUS CNV and an SNV. We demonstrated that simultaneous analysis of CNVs and SNVs/indels can improve the diagnostic yield of prenatal diagnosis with shortened reporting time, namely, 2–3 weeks. Due to the relatively long TAT for sequential procedure for prenatal genetic diagnosis, as well as recent sequencing technology advancements, it is clinically necessary to consider the simultaneous evaluation of CNVs and SNVs/indels to enhance the diagnostic yield and timely TAT, especially for cases in the late second trimester or third trimester.

Highly accurate long-read HiFi sequencing data for five complex genomes

The PacBio® HiFi sequencing method yields highly accurate long-read sequencing datasets with read lengths averaging 10–25 kb and accuracies greater than 99.5%. These accurate long reads can be used to improve results for complex applications such as single nucleotide and structural variant detection, genome assembly, assembly of difficult polyploid or highly repetitive genomes, and assembly of metagenomes. Currently, there is a need for sample data sets to both evaluate the benefits of these long accurate reads as well as for development of bioinformatic tools including genome assemblers, variant callers, and haplotyping algorithms. We present deep coverage HiFi datasets for five complex samples including the two inbred model genomes Mus musculus and Zea mays, as well as two complex genomes, octoploid Fragaria × ananassa and the diploid anuran Rana muscosa. Additionally, we release sequence data from a mock metagenome community. The datasets reported here can be used without restriction to develop new algorithms and explore complex genome structure and evolution. Data were generated on the PacBio Sequel II System.

Improvement of Molecular Diagnosis Using Domain-Level Single-Nucleotide Variants by Eliminating Unexpected Secondary Structures.

Identification of single-nucleotide variants (SNVs) is of great significance in molecular diagnosis. The problem that should not be ignored in the identification process is that the unexpected secondary structure of the target nucleic acid may greatly affect the detection accuracy. Herein, we proposed a conditional domain-level SNV diagnosis strategy, in which the subsequent SNV detection can only be carried out after eliminating the unexpected secondary structure of target DNA. Specifically, the target DNA is assembled into a rigid double strand, which makes folding the target DNA difficult and the unexpected secondary structure is eliminated. Based on this double-stranded structure, specially designed probes are used to detect double-stranded properties and report abundant domain-level oligonucleotide information to improve the effective information in the detection results and complete domain-level SNV diagnosis. If the unexpected secondary structure is not eliminated, the detector will first detect it and feed back to us, ensuring the accuracy of the subsequent detection results. With the occurrence (or not) of SNV and the change of the SNV site, in the proof-of-concept experiment, we successfully identified the four homologous sequences to be tested related to BRAF gene.

Development of a high-resolution molecular marker for tracking Phaeocystis globosa genetic diversity through comparative analysis of chloroplast genomes

The phytoplankton Phaeocystis globosa thrives in a wide range of marine regions and plays an important role in climate control. It can also form harmful algal blooms (HABs) that threaten environments and impact important coastal infrastructures. Mechanisms underlying the formation of P. globosa blooms still remain poorly understood. Accumulating evidence suggests that P. globosa has high genetic diversity and different P. globosa strains may have differential contributions to the development of P. globosa blooms. However, due to the lack of molecular markers with adequate resolution for distinguishing P. globosa genetic diversity, such differential contributions by different P. globosa strains could not be accurately ascertained. As such, high-resolution molecular markers need to be developed and applied to distinguish P. globosa genetic diversity. In this study, we undertook to define high-resolution molecular marker by assembling and comparing the whole chloroplast genomes of P. globosa strains isolated from different regions of the world. Through comparative analysis of P. globosa cpDNAs and detection of single nucleotide variations (SNVs), a molecular marker pgcp1 with improved resolution was developed. The pgcp1 demonstrated the highest resolution compared with other regions including 18S rDNA V4 region, 28S rDNA D1–D2 region and rbcL region, through genetic distance and phylogenetic analysis of 13 P. globosa strains. Molecular analysis of environmental samples and strains collected in multiple expeditions from a wide range of ocean regions including multiple regions in China, Vietnam, Thailand and Western Pacific using pgcp1 as the molecular marker displayed high genetic diversity of P. globosa with at least four major P. globosa clades. In conclusion, we have developed pgcp1 as a high-resolution molecular marker for the harmful algal bloom species P. globosa, which can be used to track intra-species genetic diversity and dynamics of P. globosa during bloom development.

MLH1 single-nucleotide variant in circulating tumor DNA predicts overall survival of patients with hepatocellular carcinoma

Liquid biopsy can provide a strong basis for precision medicine. We aimed to identify novel single-nucleotide variants (SNVs) in circulating tumor DNA (ctDNA) in patients with hepatocellular carcinoma (HCC). Deep sequencing of plasma-derived ctDNA from 59 patients with HCC was performed using a panel of 2924 SNVs in 69 genes. In 55.9% of the patients, at least one somatic mutation was detected. Among 25 SNVs in 12 genes, four frequently observed SNVs, MLH1 (13%), STK11 (13%), PTEN (9%), and CTNNB1 (4%), were validated using droplet digital polymerase chain reaction with ctDNA from 62 patients with HCC. Three candidate SNVs were detected in 35.5% of the patients, with a frequency of 19% for MLH1 chr3:37025749T>A, 11% for STK11 chr19:1223126C>G, and 8% for PTEN chr10:87864461C>G. The MLH1 and STK11 SNVs were also confirmed in HCC tissues. The presence of the MLH1 SNV, in combination with an increased ctDNA level, predicted poor overall survival among 107 patients. MLH1 chr3:37025749T>A SNV detection in ctDNA is feasible, and thus, ctDNA can be used to detect somatic mutations in HCC. Furthermore, the presence or absence of the MLH1 SNV in ctDNA, combined with the ctDNA level, can predict the prognosis of patients with HCC.

Diagnostic value of digital droplet polymerase chain reaction and digital multiplexed detection of single-nucleotide variants in pancreatic cytology specimens collected by EUS-guided FNA

EUS-guided FNA is recommended as a first-line procedure for the histopathologic diagnosis of pancreatic cancer. Molecular analysis of EUS-FNA samples might be used as an auxiliary tool to strengthen the diagnosis. The current study aimed to evaluate the diagnostic performances of K-ras testing using droplet digital polymerase chain reaction (ddPCR) and a novel single-nucleotide variant (SNV) assay performed on pancreatic EUS-FNA samples. EUS-FNA specimens from 31 patients with pancreatic masses (22 pancreatic ductal adenocarcinomas, 7 chronic pancreatitis, and 2 pancreatic neuroendocrine tumors) were included in the study. K-ras testing was initially performed by ddPCR. In addition, mutational status was evaluated using an SNV assay by NanoString technology, using digital enumeration of unique barcoded probes to detect 97 SNVs from 24 genes of clinical significance. The overall specificity and sensitivity of cytologic examination were 100% and 63%, respectively. K-ras mutation testing was performed using ddPCR, and the sensitivity increased to 87% with specificity 90%. The SNV assay detected at least 1 variant in 90% of pancreatic ductal adenocarcinoma samples; the test was able to detect 2 K-ras codon 61 mutations in 2 cases of pancreatic ductal adenocarcinoma, which were missed by ddPCR. The overall diagnostic accuracy of the cytologic examination alone was 74%, and it increased to 91% when the results of both molecular tests were considered for the cases with negative and inconclusive results. The current study illustrated that integration of K-ras analysis with cytologic evaluation, especially in inconclusive cases, can enhance the diagnostic accuracy of EUS-FNA for pancreatic lesions.

A Rapid, SuperSelective Method for Detection of Single Nucleotide Variants in Caenorhabditis elegans.

With the widespread use of single nucleotide variants generated through mutagenesis screens and genome editing technologies, there is pressing need for an efficient and low-cost strategy to genotype single nucleotide substitutions. We have developed a rapid and inexpensive method for detection of point mutants through optimization of SuperSelective (SS) primers for end-point PCR in Caenorhabditis elegans. Each SS primer consists of a 5′ “anchor” that hybridizes to the template, followed by a noncomplementary “bridge,” and a “foot” corresponding to the target allele. The foot sequence is short, such that a single mismatch at the terminal 3′ nucleotide destabilizes primer binding and prevents extension, enabling discrimination of different alleles. We explored how length and sequence composition of each SS primer segment affected selectivity and efficiency in various genetic contexts in order to develop simple rules for primer design that allow for differentiation between alleles over a broad range of annealing temperatures. Manipulating bridge length affected amplification efficiency, while modifying the foot sequence altered discriminatory power. Changing the anchor position enabled SS primers to be used for genotyping in regions with sequences that are challenging for standard primer design. After defining primer design parameters, we demonstrated the utility of SS primers for genotyping crude C. elegans lysates, suggesting that this approach could also be used for SNP mapping and screening of CRISPR mutants. Further, since SS primers reliably detect point mutations, this method has potential for broad application in all genetic systems.

Direct Enhanced Detection of Multiple Circulating Tumor DNA Variants in Unprocessed Plasma by Magnetic-Assisted Bioelectrocatalytic Cycling.

The detection of single-nucleotide variants (SNVs) in circulating tumor DNA (ctDNA) in liquid biopsies has increasingly been shown to exhibit unique benefits for early detection or minimal residual disease monitoring in cancer. Yet, current clinically validated assays for ctDNA SNV detection are challenged by (i) time-consuming and laborious spin column-based ctDNA purification protocols, (ii) limited detection specificity to discriminate between mutated SNVs from large excess of closely similar wild-type sequences, and (iii) insufficient detection sensitivity required for trace ctDNA target analysis in blood. Herein, a ctDNA assay is demonstrated to tackle these triple key issues by fusing magnetics for quick ctDNA enrichment directly from unprocessed blood, selected bioenzyme activities for rapid discrimination, and molecular amplification of target SNVs, and designed magnetic-assisted bioelectrocatalytic cycling of DNA-intercalating and freely diffusing redox probes for electrochemical signal intensification. The described ctDNA SNV assay enables the detection of clinically relevant ctDNA SNVs in melanoma (BRAFV600E, KITL576P, and NRASQ61K) from unprocessed plasma samples with unprecedented 0.005% detection sensitivity, ultrabroad dynamic range over four orders of magnitude, and excellent single-base specificity.

Abstract 179: Comprehensive genomic profiling of solid tumors for key targeted and immuno-oncology biomarkers using Ion Torrent NGS technology on the Oncomine Comprehensive Assay Plus (OCA Plus)

Abstract Comprehensive genomic profiling (CGP) of tumor samples by next-generation sequencing is used to support clinical and translational research into the genetic variants that serve as biomarkers for diagnosis, prognosis and potential therapeutic response. However, as these assays grow in size to meet the expanding demands of users, it is challenging to maintain performance in the face of limited sample input necessitated by small sample volumes and to provide a simple and fast sample to report workflow with limited hands-on time. We, therefore, developed OCA Plus to meet user needs for a large CGP assay with excellent performance. Gene content was prioritized based on potential clinical relevance and variant prevalence in solid tumors. Over 500 genes were selected including genes in the indication statements of approved drug labels, clinical guidelines, and in the enrollment criteria of clinical trials. In addition, driver genes were selected in key pathways including DNA repair and immune checkpoint response. Amplicon design strategies were optimized accordingly for key hotspots, full coding sequences or copy number variation (CNV). The assay used Ion AmpliSeq™ technology with manual library preparation or automated templating on the Ion Chef™ System and sequencing on the Ion GeneStudio™ S5 platform. Twenty ng of purified DNA was routinely used as input. An automated tumor-only workflow for variant calling and sample quality reporting was provided within Ion Reporter™ Software. Streamlined access to reporting of variant relevance was enabled by Oncomine™ Reporter. In development studies of cancer cell line and formaldehyde-fixed, paraffin-embedded (FFPE) tumor samples, the assay displayed excellent uniformity (98% and 94%, respectively). Detection of single nucleotide variants and indels in cell lines and FFPE samples showed >95% sensitivity and PPV. Detection of CNV gain and loss in cell lines and FFPE samples showed >95% sensitivity and PPV. Assessment of tumor mutational burden (TMB) using publicly available whole-exome cancer sequencing data as well as test cell lines and FFPE samples showed high concordance with whole exome sequencing (R2 > 0.90). MSI sensitivity and specificity was >95% as tested using a diverse set of tumor samples. Targeted fusions were reported with 100% sensitivity and specificity when tested with commercially available controls. Total time from purified DNA to end of sequencing was < 2 days with < 3 hours of hands-on time and the time from post-sequencing to report generation was < 2 hours. Oncomine Comprehensive Assay (OCA Plus) was developed to support CGP and routine clinical research in oncology. The assay design and informatics workflow were optimized to support low input and rapid sample-to-report turn-around time, which will accelerate clinical and translational research. Citation Format: Vinay Mittal, Jennifer Kilzer, Dinesh Cyanam, Janice Au-Young, Santhoshi Bandla, Gary Bee, Sameh El-Difrawy, Aren Ewing, Rajesh Gottimukkala, Mohit Gupta, Nickolay Khazanov, Anelia Kraltcheva, Amir Marcovitz, Scott Myrand, Rose Putler, Yu-Ting Tseng, Warren Tom, Cristina Van Loy, James Veitch, Paul Williams, Elaine Wong-Ho, Huimin Xie, Chenchen Yang, Zheng Zang, Seth Sadis. Comprehensive genomic profiling of solid tumors for key targeted and immuno-oncology biomarkers using Ion Torrent NGS technology on the Oncomine Comprehensive Assay Plus (OCA Plus) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 179.

Parallel detection of single nucleotide variants and copy number variants with exome analysis: Validation in a cohort of 700 undiagnosed patients.

Copy number variants (CNVs) are significant causes of rare and undiagnosed diseases. Parallel detection of single nucleotide variants (SNVs) and CNVs with exome analysis, if feasible, would shorten the diagnostic closure in a timely manner. We validated such “parallel” approach through a cohort study of 791 undiagnosed patients. In addition to routine exome analysis, we applied an innovative algorithm EXCAVATOR2 which enhances sensitivity by paradoxically exploiting read depth data that covers nonexonic regions where baits were not originally intended to hybridize. About 48 patients had copy number variations, 42 deletions, and 6 duplications with a resolution of 0.51–14.7 mega base pairs. Importantly from a clinical standpoint, we identified three patients with “dual diagnosis” due to concurrent pathogenic CNV and SNV. We suggest “hitting two birds with one stone” approach to exome data is an efficient strategy in deciphering undiagnosed patients and may well be considered as a first‐tier genetic test.

Combining competitive sequestration with nonlinear hybridization chain reaction amplification: an ultra-specific and highly sensitive sensing strategy for single-nucleotide variants

Highly specific and sensitive detection of single-nucleotide variants (SNVs) is of central importance in disease diagnosis and pharmacogenomics. However, it remains a great challenge to successfully detect very low amounts of mutant SNV sequences in real samples in which a SNV sequence may be surrounded by high levels of closely related wild-type sequences. Herein, we propose an ultra-specific and highly sensitive SNV sensing strategy by combining the competitive sequestration with the nonlinear hybridization chain reaction (HCR) amplification. The rationally designed sequestration hairpin can effectively sequester the large amount of wild-type sequence and thus dramatically improve the hybridization specificity in recognizing SNVs. To improve the detection sensitivity, a new fluorescent signal probe is fabricated by intercalating SYBR Green I dye into the nonlinear HCR based DNA dendrimer to further bind with SNVs for signal amplification. The hyperbranched DNA dendrimer possesses large numbers of DNA duplexes for dye intercalation, thus the signal probe shows strong fluorescence intensity, leading to large fluorescence signal amplification. Taking advantage of the improved hybridization specificity of the competitive sequestration and the enhanced fluorescence response of the nonlinear HCR amplification, the developed sensing strategy enables ultra-specific and highly sensitive detection of SNVs. Taking human pancreatic cancers and colorectal carcinomas related KRAS gene mutations as models, the developed strategy shows remarkably high specificity against 17 SNVs (discrimination factors ranged from 126 to 1001 with a median of 310), and achieves high sensitivity for 6 KRAS mutations (the best resultant detection limit reached 15 pM for KRAS G13D (c.38G > A)). Notably, combined with PCR amplification, our SNV sensing strategy could detect KRAS G12D (c.35G > A) from extracted human genomic DNA samples at abundance as low as 0.05%. This work expands the rule set of designing specific and sensitive SNV sensing strategies and shows promising potential application in clinical diagnosis.

Comparison of Multiple Displacement Amplification (MDA) and Multiple Annealing and Looping-Based Amplification Cycles (MALBAC) in Limited DNA Sequencing Based on Tube and Droplet.

Whole genome amplification (WGA) is crucial for whole genome sequencing to investigate complex genomic alteration at the single-cell or even single-molecule level. Multiple displacement amplification (MDA) and multiple annealing and looping based amplification cycles (MALBAC) are two most widely applied WGA methods, which have different advantages and disadvantages, dependent on research objectives. Herein, we compared the MDA and MALBAC to provide more information on their performance in droplets and tubes. We observed that the droplet method could dramatically reduce the amplification bias and retain the high accuracy of replication than the conventional tube method. Furthermore, the droplet method exhibited higher efficiency and sensitivity for both homozygous and heterozygous single nucleotide variants (SNVs) at the low sequencing depth. In addition, we also found that MALBAC offered a greater uniformity and reproducibility and MDA showed a better efficiency of genomic coverage and SNV detection. Our results provided insights that will allow future decision making.

Validation of a next generation sequencing assay for BRCA1, BRCA2, CHEK2 and PALB2 genetic testing

BRCA1, BRCA2, CHEK2 and PALB2 genes are associated with hereditary breast and ovarian cancer syndrome. Genetic testing of these genes is of increasing importance to guide therapeutic and management decisions. In this study, we evaluated the performance of a next generation sequencing (NGS) assay for the complete analysis of BRCA1, BRCA2, CHEK2 and PALB2 genes using Agilent's SureMASTR BRCA Screen that enabled the detection of single nucleotide variants (SNVs), small insertions/deletions (indels) and copy number variations (CNVs) in a single-tube PCR based library preparation. The results showed 100% sensitivity and specificity on a set of 52 known samples from de-identified patients and external quality assessment program. A concordance rate of 87.5% was achieved in the comparison of variant classification with the external laboratories. The high accuracy of the assay supports the use of SureMASTR BRCA Screen in clinical diagnostic laboratories (SureMASTR BRCA Screen is for research use only, not for use in diagnostic procedures).

A newly developed capture-based sequencing panel for genomic assay of lung cancer.

The increase in genetic alterations targeted by specific chemotherapy in lung cancer has led to the need for universal use of more comprehensive genetic testing, which has highlighted the development of a lung cancer diagnostic panel using next-generation sequencing. We developed a hybridization capture-based massively parallel sequencing assay named Friendly, Integrated, Research-based, Smart and Trustworthy (FIRST)-lung cancer panel (LCP), and evaluated its performance. FIRST-LCP comprises 64 lung cancer-related genes to test for various kinds of genetic alterations including single nucleotide variations (SNVs), insertions and deletions (indels), copy number variations (CNVs), and structural variations. To assess the performance of FIRST-LCP, we compiled test sets using HapMap samples or tumor cell lines with disclosed genetic information, and also tested our clinical lung cancer samples whose genetic alterations were known by conventional methods. FIRST-LCP accomplished high sensitivity (99.4%) and specificity (100%) of the detection of SNVs. High precision was also achieved, with intra- or inter-run concordance rate of 0.99, respectively. FIRST-LCP detected indels and CNVs close to the expected allele frequency and magnitude, respectively. Tests with samples from lung cancer patients also identified all SNVs, indels and fusions. Based on the current state of the art, continuous application of the panel design and analysis pipeline following up-to-date knowledge could ensure precision medicine for lung cancer patients.

Defining the mutational landscape of 3,217 primary breast cancer transcriptomes through large-scale RNA-seq within the Sweden Cancerome Analysis Network: Breast Project (SCAN-B; NCT03430492).

518 Background: Breast cancer is a disease of genomic alterations, of which the complete panorama of somatic mutations and how these relate to molecular subtypes and therapy response is incompletely understood. The Sweden Cancerome Analysis Network-Breast project (SCAN-B; ClinicalTrials.gov NCT02306096) is a multi-center population-based ongoing prospective observational study elucidating the global transcriptomic profiles for thousands of patients and tumors using RNA sequencing. Since September 2010, over 15,000 patients with breast cancer have been enrolled at 9 hospitals across a wide geography of Sweden, comprising greater than 90% of all eligible patients in the catchment area. Methods: Within SCAN-B, we developed an optimized bioinformatics pipeline for detection of single nucleotide variants and small insertions and deletions from RNA-seq data. From this, we describe the mutational landscape of 3,217 primary breast cancer transcriptomes, and relate it to patient overall survival in a real-world setting (median follow-up 75 months, range 2-105 months). Results: We demonstrate that RNA-seq can be used to call mutations in important breast cancer genes such as PIK3CA, TP53, ESR1, and ERBB2, as well as mutation status of key molecular pathways and tumor mutational burden, identify mutations in one or more potentially druggable genes in 85.3% percent of cases, and reveal significant relationships to patient outcome within specific treatment groups. To make this rich and growing mutational portraiture of breast cancer available for the wider research community, we developed an open source interactive web application, SCAN-B MutationExplorer, publicly accessible at http://oncogenomics.bmc.lu.se/MutationExplorer . Conclusions: These results add another dimension to the use of RNA-seq as a potential clinical tool, where both gene expression-based signatures and gene mutation-based biomarkers can be interrogated simultaneously and in real-time within one week of tumor sampling.

Ultrasensitive multiplex detection of structural rearrangements in ALK, RET, ROS1 and PD-L1 using a comprehensive next-generation sequencing assay.

3572 Background: Oncogenic structural rearrangements (SR) in ALK, RET and ROS1 are well-described in lung cancer, and confer sensitivity to targeted therapy. SR disrupting the 3’UTR of PD-L1 gene have been reported in multiple cancer types and can potentially predict response to checkpoint immunotherapy. An amplicon-based next-generation sequencing (NGS) platform technology (AmpliMARK), previously optimized for detection of single nucleotide variations (SNVs), microsatellite instability and viral DNA, was extended to the multiplex detection of SR in ALK, RET, ROS1 and PD-L1 in cell-free DNA (cfDNA) and tumor tissue DNA. Methods: A hybrid primer-extension and adapter-ligation based method allowing detection of SR in a fusion-partner agnostic manner was utilized for multiplex target capture of genomic regions of ALK, RET, ROS1 and PD-L1 SR. Analytical validation was performed using admixtures of fragmented genomic DNA from an ALK SR-positive cell line, commercial standards containing RET and ROS1 SR, and synthetic PD-L1 SR gene constructs. Clinical performance was assessed in cfDNA samples from lung cancer patients and tumor tissue DNA samples from natural killer(NK)/T-cell lymphoma patients. Results: Detection of SR could be achieved to an allele frequency detection limit of 0.5% with sensitivity of 89.5% and specificity of 100% in admixture samples mimicking cfDNA. In an unselected series of 374 lung cancer cases, actionable SR for ALK, RET and ROS1 were detected in cfDNA of 9 samples, for an overall detection rate of 2.4%, and 1.8% (3 out of 168) when restricted to treatment-naive lung cancer cases only. In 29 NK/T-cell lymphoma tumor tissue samples, 9 samples were positive for PD-L1 SR, which were orthogonally confirmed by whole-genome sequencing, targeted sequencing or Sanger sequencing for a concordance rate of 100% across all samples. For 1 NK/T-cell lymphoma tumor tissue sample where matched plasma was available, the same PD-L1 SR was also detected in cfDNA. Conclusions: We have demonstrated and validated a comprehensive amplicon-based NGS assay for ultrasensitive multiplex detection of structural rearrangements in ALK, RET, ROS1 and PD-L1 across both cfDNA and tumor tissue DNA in analytical and clinical contexts. Ongoing studies will further evaluate the performance and utility of this assay across a larger number of clinical samples for the detection of these SR as well as additional cancer-associated SR involving NTRK1/2/3, FGFR2/3 and TMPRSS2.

Molecular inversion probe-rolling circle amplification with single-strand poly-T luminescent copper nanoclusters for fluorescent detection of single-nucleotide variant of SMN gene in diagnosis of spinal muscular atrophy

In this study, a simple fluorescent detection of survival motor neuron gene (SMN) in diagnosis of spinal muscular atrophy (SMA) based on nucleic acid amplification test and the poly-T luminescent copper nanoclusters (CuNCs) was established. SMA is a severely genetic diseases to cause infant death in clinical, and detection of SMN gene is a powerful tool for pre- and postnatal diagnosis of this disease. This study utilized the molecular inversion probe for recognition of nucleotide variant between SMN1 (c.840 C) and SMN2 (c.840 C > T) genes, and rolling circle amplification with a universal primer for production of poly-T single-strand DNA. Finally, the fluorescent CuNCs were formed on the poly-T single-strand DNA template with addition of CuSO4 and sodium ascorbate. The fluorescence of CuNCs was only detected in the samples with the presence of SMN1 gene controlling the disease of SMA. After optimization of experimental conditions, this highly efficient method was performed under 50 °C for DNA ligation temperature by using 2U Ampligase, 3 h for rolling circle amplification, and the formation of the CuNCs by mixing 500 μM Cu2+ and 4 mM sodium ascorbate. Additionally, this highly efficient method was successfully applied for 65 clinical DNA samples, including 4 SMA patients, 4 carriers and 57 wild individuals. This label-free detection strategy has the own potential to not only be a general method for detection of SMN1 gene in diagnosis of SMA disease, but also served as a tool for detection of other single nucleotide polymorphisms or nucleotide variants in genetic analysis through designing the different sensing probes.

Development and Validation of a Next-Generation Sequencing Panel for Syndromic and Nonsyndromic Hearing Loss.

Deafness and hearing loss are common conditions that can be seen independently or as part of a syndrome and are often mediated by genetic causes. We sought to develop and validate a hereditary hearing loss panel (HHLP) to detect single nucleotide variants (SNVs), insertions and deletions (indels), and copy number variants (CNVs) in 166 genes related to nonsyndromic and syndromic hearing loss. We developed a custom-capture next-generation sequencing (NGS) reagent to detect all coding regions, ±10 flanking bp, for the 166 genes related to nonsyndromic and syndromic hearing loss. Our validation consisted of testing 52 samples to establish accuracy, reproducibility, and analytical sensitivity. In addition to NGS, supplementary methods, including multiplex ligation-dependent probe amplification, long-range PCR, and Sanger sequencing, were used to ensure coverage of regions that had high complexity or homology. We observed 100% positive and negative percentage agreement for detection of SNVs (n = 362), small indels (1-22 bp, n = 25), and CNVs (gains, n = 8; losses, n = 17). Finally, we showed that this assay was able to detect variants with a variant allele frequency ≥20% for SNVs and indels and ≥30% to 35% for CNVs. We validated an HHLP that detects SNVs, indels, and CNVs in 166 genes related to syndromic and nonsyndromic hearing loss. The results of this assay can be utilized to confirm a diagnosis of hearing loss and related syndromic disorders associated with known causal genes.