Approach For Mutation Detection Research Articles

Innovative PNA-LB mediated allele-specific LAMP for KRAS mutation profiling on a compact lab-on-a-disc device

Tailored healthcare, an approach focused on individual patients, requires integrating emerging interdisciplinary technologies to develop accurate and user-friendly diagnostic tools. KRAS mutations, prevalent in various common cancers, are crucial determinants in selecting patients for novel KRAS inhibitor therapies. This study presents a novel state-of-the-art Lab-on-a-Disc system utilizing peptide nucleic acids-loop backward (PNA-LB) mediated allele-specific loop-mediated isothermal amplification (LAMP) for detecting the frequent G12D KRAS mutation, signifying its superiority over alternative mutation detection approaches. The designed Lab-on-a-Disc system demonstrated exceptional preclinical and technical precision, accuracy, and versatility. By applying varying cutoff values to PNA- LB LAMP reactions, the assay's sensitivity and specificity were increased by 80 % and 90 %, respectively. The device's key advantages include a robust microfluidic Lab-on-a-Disc design, precise rotary control, and a cutting-edge induction heating module. These features enable multiplexing of LAMP reactions with high reproducibility and repeatability, with CV% values less than 3.5 % and 5.5 %, respectively. The device offers several methods for accurate endpoint result detection, including naked-eye observation, RGB image analysis using Python code, and time of fluorescence (Tf) values. Preclinical specificity and sensitivity, assessed using different cutoffs for Eva-Green fluorescence Tf values and pH-sensitive dyes, demonstrated comparable performance to the best standard methods. Overall, this study represents a significant step towards tailoring treatment strategies for cancer patients through precise and efficient mutation detection technologies.

Abstract 6101: PLASMUT: An R Package for estimating the probability of tumor-specific mutations in cell-free DNA

Abstract Noninvasive approaches for detection of tumor-specific mutations in cell-free DNA (cfDNA) have the potential to track a patient’s response to treatment, enabling effective and timely decisions on therapy. However, mutations in cfDNA arising from clonal hematopoeisis (CH) are common and tumor biopsies for definitive identification of the origin of these mutations are not always available. Sequencing of matched cells from buffy coat and the absence of mutations in these cells has been used to rule-out white blood cell (WBC) mutations, but uneven sequencing depths between matched cfDNA and buffy coat and the fraction of mutant alleles are generally ignored by rule-based tests. A probabilistic approach that quantifies the evidence of tumor-derived mutations in cfDNA is needed. We developed a Bayesian framework to estimate the probability that a mutation identified in cfDNA is tumor specific. Our approach requires the number of reads with a mutant allele in plasma (yp) and WBCs (yw) and the corresponding number of total distinct reads at these locations. The posterior odds that a mutation is tumor-derived (S) versus CH or germline (H) is given by the ratio of the probabilities of observing the distinct reads given each model times the prior odds. Estimation of the Bayes factor is obtained by integrating over the unobserved mutant allele fractions in plasma and WBCs using Monte Carlo importance sampling. We applied this approach to 52 patients with initially unresectable colorectal cancer (CRC) liver metastases in the CAIRO5 clinical trial (NCT02162563), using ultra-deep targeted sequencing of cfDNA from plasma and matched WBCs. Among the CAIRO5 patients analyzed, we identified 95 mutations with moderate evidence of tumor-derived cfDNA mutations (Bayes factor > 10) and 19 mutations that were CH-derived (Bayes factor < 0.1). For a subset of 47 cfDNA mutations with no corresponding mutation identified by WBC sequencing, the evidence of tumor origin was highly variable (Bayes factor range: 0.03 to 5.6). While the standard rule-based approach identifies all of these mutations as tumor-derived, none of these mutations reach a moderate evidence cutpoint (all Bayes factors < 6). As a false positive would lead to identification of cfDNA mutations that do not track tumor burden, requiring even higher levels of evidence (Bayes factor > 99) for the selection of cfDNA mutations could be warranted, and still identifies one or more cfDNA mutations in 43 of the patients. This approach is implemented in the R package PLASMUT available from Bioconductor (doi:10.18129/B9.bioc.plasmut). We developed an approach that quantifies the evidence between two competing models for the origin of mutations in cfDNA. A cutpoint for determination of the probability of tumor-derived cfDNA mutations can be tailored to the disease application, balancing the potential benefits of noninvasive testing with the harms of false positives and negatives. Citation Format: Adith S. Arun, Jamie E. Medina, Stephen Cristiano, Daniel C. Bruhm, Remond J. Fijneman, Gerrit A. Meijer, Alessandro Leal, Victor E. Velculescu, Robert B. Scharpf. PLASMUT: An R Package for estimating the probability of tumor-specific mutations in cell-free DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6101.

Genome-wide direct quantification of in vivo mutagenesis using high-accuracy paired-end and complementary consensus sequencing.

Error-corrected next-generation sequencing (ecNGS) is an emerging technology for accurately measuring somatic mutations. Here, we report paired-end and complementary consensus sequencing (PECC-Seq), a high-accuracy ecNGS approach for genome-wide somatic mutation detection. We characterize a novel 2-aminoimidazolone lesion besides 7,8-dihydro-8-oxoguanine and the resulting end-repair artifacts originating from NGS library preparation that obscure the sequencing accuracy of NGS. We modify library preparation protocol for the enzymatic removal of end-repair artifacts and improve the accuracy of our previously developed duplex consensus sequencing method. Optimized PECC-Seq shows an error rate of<5×10-8 with consensus bases compressed from approximately 25 Gb of raw sequencing data, enabling the accurate detection of low-abundance somatic mutations. We apply PECC-Seq to the quantification of in vivo mutagenesis. Compared with the classic gpt gene mutation assay using gpt delta transgenic mice, PECC-Seq exhibits high sensitivity in quantitatively measuring dose-dependent mutagenesis induced by Aristolochic acid I (AAI). Moreover, PECC-Seq specifically characterizes the distinct genome-wide mutational signatures of AAI, Benzo[a]pyrene, N-Nitroso-N-ethylurea and N-nitrosodiethylamine and reveals the mutational signature of Quinoline in common mouse models. Overall, our findings demonstrate that high-accuracy PECC-Seq is a promising tool for genome-wide somatic mutagenesis quantification and for invivo mutagenicity testing.

Molecular Modeling Unveils the Effective Interaction of B-RAF Inhibitors with Rare B-RAF Insertion Variants.

The Food and Drug Administration (FDA) has approved MAPK inhibitors as a treatment for melanoma patients carrying a mutation in codon V600 of the BRAF gene exclusively. However, BRAF mutations outside the V600 codon may occur in a small percentage of melanomas. Although these rare variants may cause B-RAF activation, their predictive response to B-RAF inhibitor treatments is still poorly understood. We exploited an integrated approach for mutation detection, tumor evolution tracking, and assessment of response to treatment in a metastatic melanoma patient carrying the rare p.T599dup B-RAF mutation. He was addressed to Dabrafenib/Trametinib targeted therapy, showing an initial dramatic response. In parallel, in-silico ligand-based homology modeling was set up and performed on this and an additional B-RAF rare variant (p.A598_T599insV) to unveil and justify the success of the B-RAF inhibitory activity of Dabrafenib, showing that it could adeptly bind both these variants in a similar manner to how it binds and inhibits the V600E mutant. These findings open up the possibility of broadening the spectrum of BRAF inhibitor-sensitive mutations beyond mutations at codon V600, suggesting that B-RAF V600 WT melanomas should undergo more specific investigations before ruling out the possibility of targeted therapy.

Two CRISPR/Cas12a-based methods for fast and accurate detection of single-base mutations.

Current single-base mutation detection approaches are time-consuming, labor-intensive, and costly. This highlights the critical need for speedy and accurate technology capable of detecting single-base alterations. Using clustered regularly interspaced short palindromic repeats/associated protein 12a (CRISPR/Cas12a), two fundamental approaches for getting 100% differentiation of single-base mutations have been established, by which fluorescence signals could be detected for variants but not for wild strains. The first method required both polymerase chain reaction (PCR) and CRISPR/Cas12a cleavage: By introducing a mismatched base at the 3' end of the primers and adjusting the PCR settings, the wild strain strand amplifications were completely blocked prior to CRISPR/Cas12a cleavage. The parameters for Method 1 (PCR+CRISPR/Cas12a) could be easily controlled and adjusted to attain a sensitivity of one copy (about 6 copies μL-1). The second method included isothermal recombinase polymerase amplification (RPA) and CRISPR/Cas12a cleavage: By introducing an extra mismatched base adjacent to the single-base mutant site by RPA (IMAS-RPA), the RPA products from the wild strains were rendered incapable of triggering the cleavage activity of CRISPR/Cas12a. Method 2 (IMAS-RPA) was rapid and easy to implement (can be finished within 1h). Because each method has its own set of advantages, the laboratory environment-appropriate methods can be selected independently. Both approaches are expected to aid in clinical diagnosis to some extent in the near future.

Preclinical workup using long-read amplicon sequencing provides families with de novo pathogenic variants access to universal preimplantation genetic testing.

Can long-read amplicon sequencing be beneficial for preclinical preimplantation genetic testing (PGT) workup in couples with a de novo pathogenic variant in one of the prospective parents? Long-read amplicon sequencing represents a simple, rapid and cost-effective preclinical PGT workup strategy that provides couples with de novo pathogenic variants access to universal genome-wide haplotyping-based PGT programs. Universal PGT combines genome-wide haplotyping and copy number profiling to select embryos devoid of both familial pathogenic variants and aneuploidies. However, it cannot be directly applied in couples with a de novo pathogenic variant in one of the partners due to the absence of affected family members required for phasing the disease-associated haplotype. This is a prospective study, which includes 32 families that were enrolled in the universal PGT program at the University Hospital of Leuven between 2018 and 2022. We implemented long-read amplicon sequencing during the preclinical PGT workup to deduce the parental origin of the disease-associated allele in the affected partner, which can then be traced in embryos during clinical universal PGT cycles. To identify the parental origin of the disease-associated allele, genomic DNA from the carrier of the de novo pathogenic variant and his/her parent(s) was used for preclinical PGT workup. Primers flanking the de novo variant upstream and downstream were designed for each family. Following long-range PCR, amplicons that ranged 5-10 kb in size, were sequenced using Pacific Bioscience and/or Oxford Nanopore platforms. Next, targeted variant calling and haplotyping were performed to identify parental informative single-nucleotide variants (iSNVs) linked to the de novo mutation. Following the preclinical PGT workup, universal PGT via genome-wide haplotyping was performed for couples who proceeded with clinical PGT cycle. In parallel, 13 trophectoderm (TE) biopsies from three families that were analyzed by universal PGT, were also used for long-read amplicon sequencing to explore this approach for embryo direct mutation detection coupled with targeted long-read haplotyping. The parental origin of the mutant allele was identified in 24/32 affected individuals during the preclinical PGT workup stage, resulting in a 75% success rate. On average, 5.95 iSNVs (SD = 4.5) were detected per locus of interest, and the average distance of closest iSNV to the de novo variant was ∼1750 bp. In 75% of those cases (18/24), the de novo mutation occurred on the paternal allele. In the remaining eight families, the risk haplotype could not be established due to the absence of iSNVs linked to the mutation or inability to successfully target the region of interest. During the time of the study, 12/24 successfully analyzed couples entered the universal PGT program, and three disease-free children have been born. In parallel to universal PGT analysis, long-read amplicon sequencing of 13 TE biopsies was also performed, confirming the segregation of parental alleles in the embryo and the results of the universal PGT. The main limitation of this approach is that it remains targeted with the need to design locus-specific primers. Because of the restricted size of target amplicons, the region of interest may also remain non-informative in the absence of iSNVs. Targeted haplotyping via long-read amplicon sequencing, particularly using Oxford Nanopore Technologies, provides a valuable alternative for couples with de novo pathogenic variants that allows access to universal PGT. Moreover, the same approach can be used for direct mutation analysis in embryos, as a second line confirmation of the preclinical PGT result or as a potential alternative PGT procedure in couples, where additional family members are not available. This work was supported by KU Leuven funding (no. C1/018 to J.R.V.) and Fonds Wetenschappelijk Onderzoek (1241121N to O.T.). J.R.V. is co-inventor of a patent ZL910050-PCT/EP2011/060211-WO/2011/157846 'Methods for haplotyping single-cells' and ZL913096-PCT/EP2014/068315-WO/2015/028576 'Haplotyping and copy number typing using polymorphic variant allelic frequencies' licensed to Agilent Technologies. All other authors have no conflict of interest to declare. N/A.

Technical Validation and Clinical Implications of Ultrasensitive PCR Approaches for EGFR-Thr790Met Mutation Detection in Pretreatment FFPE Samples and in Liquid Biopsies from Non-Small Cell Lung Cancer Patients.

In pretreatment tumor samples of EGFR-mutated non-small cell lung cancer (NSCLC) patients, EGFR-Thr790Met mutation has been detected in a variable prevalence by different ultrasensitive assays with controversial prognostic value. Furthermore, its detection in liquid biopsy (LB) samples remains challenging, being hampered by the shortage of circulating tumor DNA (ctDNA). Here, we describe the technical validation and clinical implications of a real-time PCR with peptide nucleic acid (PNA-Clamp) and digital droplet PCR (ddPCR) for EGFR-Thr790Met detection in diagnosis FFPE samples and in LB. Limit of blank (LOB) and limit of detection (LOD) were established by analyzing negative and low variant allele frequency (VAF) FFPE and LB specimens. In a cohort of 78 FFPE samples, both techniques showed an overall agreement (OA) of 94.20%. EGFR-Thr790Met was detected in 26.47% of cases and was associated with better progression-free survival (PFS) (16.83 ± 7.76 vs. 11.47 ± 1.83 months; p = 0.047). In LB, ddPCR was implemented in routine diagnostics under UNE-EN ISO 15189:2013 accreditation, increasing the detection rate of 32.43% by conventional methods up to 45.95%. During follow-up, ddPCR detected EGFR-Thr790Met up to 7 months before radiological progression. Extensively validated ultrasensitive assays might decipher the utility of pretreatment EGFR-Thr790Met and improve its detection rate in LB studies, even anticipating radiological progression.

Genome-wide detection of ultralow-frequency substitution mutations in cultures of mouse lymphoma L5178Y cells and Caenorhabditis elegans worms by PacBio sequencing.

Many conventional genetic toxicology assays require specialized cell cultures or animals and can only detect mutations that inactivate the function of a reporter gene. These limitations make such assays incompatible with many toxicological models but could be overcome by the development of techniques capable of directly detecting genome-wide somatic mutations through DNA sequencing. PacBio sequencing can generate almost error-free consensus reads by repeatedly inspecting both DNA strands from circularized molecules (a method known as PacBio HiFi). In this study, we show that PacBio HiFi can detect genome-wide ultralow-frequency substitution mutations in cultures of mouse lymphoma L5178Y cells and Caenorhabditis elegans worms. The mutation frequencies (MFs) of unexposed samples in both models were ~1 × 10-7 mutations per base pair. Compared to these controls, PacBio HiFi detected MF increases of 23-fold in cultures of L5178Y cells exposed to 5 mM ethyl methanosulfonate (EMS) for 4h, and 5-, 12-, and 29-fold in cultures of C. elegans worms exposed to 12.5, 25, and 50 mM EMS for 4h, respectively. In both models, the mutation spectra of controls were diverse, while those derived from EMS-exposed samples were dominated by C:G → T:A transitions. To validate these results, clone sequencing analyses were performed on the same cultures of L5178Y cells. The results obtained by clone sequencing and PacBio HiFi were almost identical. Our results suggest that PacBio sequencing could be used for the detection, quantitation, and characterization of mutations in any DNA-containing sample, including those that are not compatible with conventional mutation detection approaches.

Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample

BackgroundAccurate detection of somatic mutations is challenging but critical in understanding cancer formation, progression, and treatment. We recently proposed NeuSomatic, the first deep convolutional neural network-based somatic mutation detection approach, and demonstrated performance advantages on in silico data.ResultsIn this study, we use the first comprehensive and well-characterized somatic reference data sets from the SEQC2 consortium to investigate best practices for using a deep learning framework in cancer mutation detection. Using the high-confidence somatic mutations established for a cancer cell line by the consortium, we identify the best strategy for building robust models on multiple data sets derived from samples representing real scenarios, for example, a model trained on a combination of real and spike-in mutations had the highest average performance.ConclusionsThe strategy identified in our study achieved high robustness across multiple sequencing technologies for fresh and FFPE DNA input, varying tumor/normal purities, and different coverages, with significant superiority over conventional detection approaches in general, as well as in challenging situations such as low coverage, low variant allele frequency, DNA damage, and difficult genomic regions

Whole-Transcriptome Analysis by RNA Sequencing for Genetic Diagnosis of Mendelian Skin Disorders in the Context of Consanguinity

Among the approximately 8000 Mendelian disorders, >1000 have cutaneous manifestations. In many of these conditions, the underlying mutated genes have been identified by DNA-based techniques which, however, can overlook certain types of mutations, such as exonic-synonymous and deep-intronic sequence variants. Whole-transcriptome sequencing by RNA sequencing (RNA-seq) can identify such mutations and provide information about their consequences. We analyzed the whole transcriptome of 40 families with different types of Mendelian skin disorders with extensive genetic heterogeneity. The RNA-seq data were examined for variant detection and prioritization, pathogenicity confirmation, RNA expression profiling, and genome-wide homozygosity mapping in the case of consanguineous families. Among the families examined, RNA-seq was able to provide information complementary to DNA-based analyses for exonic and intronic sequence variants with aberrant splicing. In addition, we tested the possibility of using RNA-seq as the first-tier strategy for unbiased genome-wide mutation screening without information from DNA analysis. We found pathogenic mutations in 35 families (88%) with RNA-seq in combination with other next-generation sequencing methods, and we successfully prioritized variants and found the culprit genes. In addition, as a novel concept, we propose a pipeline that increases the yield of variant calling from RNA-seq by concurrent use of genome and transcriptome references in parallel. Our results suggest that "clinical RNA-seq" could serve as a primary approach for mutation detection in inherited diseases, particularly in consanguineous families, provided that tissues and cells expressing the relevant genes are available for analysis.

184 Whole-transcriptome analysis by RNA-Seq for genetic diagnosis of Mendelian skin disorders in the context of consanguinity

Among the ∼8,000 Mendelian disorders, over 1,000 of them have cutaneous manifestations. In many of these conditions, the underlying mutated genes have been identified by DNA-based techniques, which, however, can overlook certain types of mutations, such as exonic-synonymous and deep-intronic sequence variants. Whole-transcriptome sequencing by RNA-Seq can identify such mutations and provide information of their consequences. We have analyzed the whole transcriptome of 40 families with different types of Mendelian skin disorders with extensive genetic heterogeneity. The RNA-Seq data were examined for variant detection and prioritization, pathogenicity confirmation, RNA expression profiling as well as genome-wide homozygosity mapping in the case of consanguineous families. Among the families examined, RNA-Seq was able to provide information complementary to DNA-based analyses for exonic and intronic sequence variants with aberrant splicing. In addition, we tested the possibility of using RNA-Seq as the first-tier strategy for unbiased genome-wide mutation screening without information from DNA analysis. We found pathogenic mutations in 35 families (∼88%) with RNA-Seq in combination with other NGS methods, and we successfully prioritized variants and found the culprit genes. In addition, as a novel concept, we propose a pipeline that increases the yield of variant calling from RNA-Seq by concurrent use of genome and transcriptome references in parallel. Our results suggest that “clinical RNA-Seq” could serve as a primary approach for mutation detection in inherited diseases, particularly in consanguineous families, provided that tissues and cells expressing the relevant genes are available for analysis.

Short-range template switching in great ape genomes explored using pair hidden Markov models.

Many complex genomic rearrangements arise through template switch errors, which occur in DNA replication when there is a transient polymerase switch to an alternate template nearby in three-dimensional space. While typically investigated at kilobase-to-megabase scales, the genomic and evolutionary consequences of this mutational process are not well characterised at smaller scales, where they are often interpreted as clusters of independent substitutions, insertions and deletions. Here we present an improved statistical approach using pair hidden Markov models, and use it to detect and describe short-range template switches underlying clusters of mutations in the multi-way alignment of hominid genomes. Using robust statistics derived from evolutionary genomic simulations, we show that template switch events have been widespread in the evolution of the great apes' genomes and provide a parsimonious explanation for the presence of many complex mutation clusters in their phylogenetic context. Larger-scale mechanisms of genome rearrangement are typically associated with structural features around breakpoints, and accordingly we show that atypical patterns of secondary structure formation and DNA bending are present at the initial template switch loci. Our methods improve on previous non-probabilistic approaches for computational detection of template switch mutations, allowing the statistical significance of events to be assessed. By specifying realistic evolutionary parameters based on the genomes and taxa involved, our methods can be readily adapted to other intra- or inter-species comparisons.

Genetic Lesions in Russian CLL Patients with the Most Common Stereotyped Antigen Receptors

Background: The features of the IGHV gene repertoire in CLL have been widely discussed in the last 20 years. In approximately 30% of cases of CLL, highly homologous "stereotyped" antigen receptors (SARs) are expressed, representing quasi identical amino acid sequences. Associations with age, disease severity, and cytogenetic aberrations have already been reported for certain SARs. It should be noted that the predictive value of certain SARs could be higher than that of IGHV mutation status. Several SAR subgroups have already been identified as independent prognostic factors in CLL (CLL#1, CLL#2, CLL#8 demonstrate an extremely aggressive course of the disease, CLL#4 - indolent). It was also shown that SAR subgroups may associate with distinct profiles of genetic lesions. Aim: To study the frequency of cytogenetic aberrations and mutations in the TP53, NOTCH1, and SF3B1 genes in CLL patients with the most common SARs in Russia. Methods: The study included 62 patients with CLL diagnosed and followed up from 2012 to 2020. Sequencing of the IGHV gene and SAR assignment were done according to the ERIC recommendations. NOTCH1 gene mutations (exon 34) were assessed by fragment analysis or by NGS using primers described by Campregher et al. TP53 gene mutations (exons 2-11) were determined using NGS according to Pavlova et al. SF3B1 gene mutations (exons 14-16) were studied in 26 patients by NGS. 51 patients underwent a FISH study for the presence of 17p13/TP53 deletions; 29 - additionally for 11q23/ATM and 13q14 deletions (Abbott, USA). Results: CLL#1, CLL#6, and CLL#3 are the most common SAR subsets in Russian CLL patients. Here we report data for 30 patients with CLL#1, 17 with CLL#6, and 15 with CLL#3. In CLL#1 group, 10 (33.3%) patients had mutations in the TP53 gene. In 7 cases, the mutation burden exceeded 35%, in three patients it was less than 10%. In 7 (23.3%) patients, mutations in the NOTCH1 gene were detected, in 5 - c.7544_7545delCT, in 1 - c.7558_7561delCTTC and in 1 - p.Q2444X. Simultaneous mutations in the NOTCH1 and TP53 genes were found in two patients. Deletion 17p13was found in 8 patients from 25 studied (32%). In 7 patients TP53 mutation and del17p13 were observed simultaneously. Deletion 11q23 was found in 6 out of 15 patients (40%). No cases with the simultaneous occurrence of del11q23 and del17p13 or mutations in the TP53 gene were observed. SF3B1 gene mutations in this group were not investigated. In the CLL#6 group, 6 (35.3%) patients had mutations in the TP53 gene (in two of them two clones with different TP53 mutations were observed). In one case, the mutation was less than 10%. In 4 (23.5%) patients NOTCH1 gene mutations (all c.7544_7545delCT) were detected, in two cases the mutation burden was less than 5%. Simultaneous NOTCH1 and TP53 gene mutations were found in two patients. Deletion 17p13 was found in 4 patients from 14 studied (28.5%). In 3 patients TP53 mutations and del17p13 were observed simultaneously. Deletion 11q23 was found in 1 patient out of 10. No SF3B1 gene mutations were found in this group (in 11 patients tested). In CLL#3 group, only 2 (13%) patients had mutations in the TP53 gene, with one having 2 different clones and the other having 4 (this patient also had del17p13, the only one in this group). Also, only 2 (13%) patients had c.7544_7545delCT deletion in the NOTCH1 gene. SF3B1 gene mutations were found in 8 (53.3%) patients. Conclusions: Our data show that in CLL#1, CLL#6, and CLL#3 subsets genetic lesions are much more common than in CLL patients in general. This is in part consistent with earlier European studies. However, in our sample, TP53 mutations and del17p13 are much more frequent in CLL#1 and CLL#6 groups. This may be due to a more sensitive approach (NGS) for mutation detection we used. Furthermore, our cohort included patients relapsed after the FCR treatment. The discrepancy in the detection rate of del11q23 in the CLL#1 subset can be explained by the small sample. Also, population differences in the development of the disease cannot be ruled out. Further studies of genetic lesions associated with certain SAR subgroups may improve diagnostics and therapy of CLL and impact the understanding of disease pathogenesis. Disclosures No relevant conflicts of interest to declare.

Longitudinal Genomic Characterization Using Cell-Free DNA in Patients with Idiopathic Aplastic Anemia

The molecular profile of clonal hematopoiesis in patients (pts) with idiopathic aplastic anaemia (iAA) has been shown to predict response to immunosuppressive therapy (IST). Moreover, clonal evolution is associated with transformation of iAA to aggressive myeloid malignancies such as myelodysplastic syndrome (MDS) and acute myeloid leukaemia (AML). Detection of somatic mutations may help identify pts more likely to respond to IST and also those at increased risk of transformation however the predictive value of detecting mutations at a single timepoint is limited. Longitudinal detection of changes in mutation profile over time may improve prediction of transformation risk, however due to bone marrow hypocellularity DNA quality and quantity from pts with iAA is frequently suboptimal. Serial mutation analysis of cell-free DNA (cfDNA) is one approach that may overcome this problem as the majority of cfDNA originates from hematopoietic cells and mutations detected in this compartment have been shown to closely resemble those detected from peripheral blood (PB) / bone marrow (BM) analysis in other haematological malignancies. We aimed to characterise longitudinal genomic changes in pts with iAA and contrast mutation detection in the cellular compartment with those detected in cfDNA. Fifteen pts (10 female and 5 male) with a diagnosis of iAA were included (median age 35 years (range 17 - 78)); eleven were newly diagnosed (within six months of diagnosis) and four were two or more years post diagnosis. Cellular DNA (PB or BM aspirate) and cfDNA were collected upon study enrolment and cfDNA samples were collected longitudinally for each pt. Somatic mutations in cellular samples were assessed using custom targeted next generation sequencing panels with an analytical sensitivity of ~1%. cfDNA samples were assessed using a custom anchored multiplex PCR panel with molecular barcodes with an analytical sensitivity of ~0.5%. Twenty-nine genes were assessed in both cellular and cfDNA. Somatic mutations were detected in 13 of 15 (87%) pts at the first sampled timepoint, with two or more mutations detected in seven pts. Overall 27 mutations were detected in seven genes including PIGA (n=12), DNMT3A (n=5), ASXL1 (n=5), BCOR (n=2), BCORL1, NPM1 and RUNX1 (n=1 each) with a higher proportion detected in cfDNA (25 of 27) compared to cellular DNA (22 of 27). Mutations unique to cfDNA were in PIGA (n=3), ASXL1 (n=1) and DNMT3A (n=1) and those unique to cellular DNA were in NPM1 (n=1) and PIGA (n=1). The variant allele frequency (VAF) was &amp;lt;10% for 26 of 27 mutations (median cellular and cfDNA VAF 1.78% and 1.19% respectively), highlighting the need for sensitive mutation detection approaches in the setting of iAA regardless of the compartment tested. We next assessed the mutation dynamics in cfDNA over time by analysing a median of 3 (range 2 - 4) sequential samples per pt (median follow-up interval 670 days, range 249 - 923). 20 of 25 cfDNA mutations were detected in longitudinal cfDNA at similar VAF, including PIGA (n=9), BCOR (n=2), DNMT3A (n=5), ASXL1 (n=3) and RUNX1 (n=1). Five mutations in PIGA (n=2), ASXL1 (n=2) and BCORL1 (n=1) became undetectable over time. Importantly, acquisition of new mutations during follow-up was observed in four pts (total of 13 new cfDNA mutations detected). Three out of these four pts experienced disease transformation to hematological malignancy (MDS n=2, AML n=1), with acquired mutations in SETBP1, NPM1, NRAS, KRAS, WT1 and KIT. Importantly, these mutations often went from undetectable to relatively high VAF within a short interval (5 - 13 months) which is important to consider when designing molecular screening schedules to potentially pre-empt transformation. In summary, our data shows that cfDNA mutation profiling in pts with iAA is technically feasible and is able to detect additional mutations not detectable in the cellular compartment. Importantly, we demonstrate the limitations of analysis of both compartments in the context of low VAF mutations, suggesting that concurrent testing of both cellular and cfDNA may increase the sensitivity for detecting low frequency events. Our data also suggests that longitudinal changes in mutation profile may improve identification of pts at high risk of transformation to hematological malignancy. The optimal frequency of monitoring and the magnitude of increased risk requires validation in prospective trials. GLR and LCF contributed equally to this work Disclosures Szer: Alexion Pharmaceuticals Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Apellis: Consultancy; Pfizer: Honoraria, Speakers Bureau; Takeda: Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau; Prevail Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees. Bajel:Astellas: Honoraria; Novartis: Honoraria; Amgen: Honoraria, Speakers Bureau; Pfizer: Honoraria; Abbvie: Honoraria. Blombery:Novartis: Consultancy; Invivoscribe: Honoraria; Amgen: Consultancy; Janssen: Honoraria.

Research Techniques Made Simple: Whole-Transcriptome Sequencing by RNA-Seq for Diagnosis of Monogenic Disorders

Mendelian disorders with cutaneous manifestations comprise a genotypically heterogeneous group of over 1,000 diseases, and in most of them mutant genes have been identified. Mutation detection approaches in these diseases have largely focused on DNA analysis by next-generation sequencing techniques, including gene-targeted sequencing panels as well as whole-exome and whole-genome sequencing. Genome-wide homozygosity mapping (HM), based on DNA polymorphism, has also assisted in the identification of candidate genes in families with consanguinity. However, specific pathogenic variants have not been disclosed in many individual patients when analyzed by next-generation sequencing, and in particular, DNA-based analysis failed to identify many of the mutations impacting on splicing or gene expression. Whole-transcriptome sequencing by RNA sequencing (RNA-Seq), with appropriate bioinformatics, provides a robust tool to identify additional mutations to facilitate genetic diagnosis in genodermatoses. RNA-Seq can be used for variant calling and HM similar to DNA-based approaches, but it also allows for the identification of mutations that result in aberrant transcriptome expression, as displayed by heatmap analysis, and altered splicing patterns of RNA, as visualized by Sashimi plots. Thus, clinical RNA-Seq extends molecular diagnostics of rare genodermatoses, and it could provide a reliable first-tier diagnostic approach to extend mutation databases in patients with heritable skin diseases.

Live births following preimplantation genetic testing for dynamic mutation diseases by karyomapping: a report of three cases.

The preimplantation genetic testing for monogenic defects (PGT-M) is a beneficial strategy for the patients suffering from a Mendelian disease, which could protect their offspring from inheriting the disease. The purpose of this study is to report the effectiveness of PGT-M based on karyomapping for three cases of dynamic mutation diseases with trinucleotide repeat expansion. PGT-M was carried out on three couples, whose family members were diagnosed with Huntington's disease or spinocerebellar ataxias 2 or 12. The whole genome amplification was obtained using the multiple displacement amplification (MDA) method. Then, karyomapping was performed to detect the allele that is carrying the trinucleotide repeat expansion using single nucleotide polymorphism (SNP) linkage analyses, and the copy number variations (CNVs) of the embryos were also identified. Prenatal diagnosis was performed to validate the accuracy of PGT-M. PGT-M was successfully performed on the three couples, and they accepted the transfers of euploid blastocysts without the relevant pathogenic allele. The clinical pregnancies were acquired and the prenatal diagnosis of the three families confirmed the effectiveness of karyomapping. The three born babies were healthy and free of the pathogenic alleles HTT, ATXN2, or PPP2R2B corresponding to Huntington's disease, spinocerebellar ataxias 2 or 12, respectively. This study shows that karyomapping is a highly powerful and efficient approach for dynamic mutation detection in preimplantation embryos. In this work, we first report the birth of healthy babies that are free of the pathogenic gene for dynamic mutation diseases in patients receiving PGT-M by karyomapping.

Abstract P2-11-06: Assessment of ESR1 genomic aberrations and their role in endocrine therapy resistance in breast cancer

Abstract Background: Endocrine therapy (ET) is an effective treatment of estrogen receptor positive (ER+) breast cancer (BC). However, not all ER+ cancers respond to ET and many eventually acquire resistance. Genomic aberrations in ESR1 have been reported to play a role in resistance to treatment. ESR1 mutations (ESRMs), reported in 10-50% of metastatic or recurrent BCs treated with aromatase inhibitors (AIs), can lead to constitutive activation and reduced sensitivity to ET. The incidence and clinical implications of ESR1 amplification (ESRA) is not well-established. A variety of structural rearrangements involving ESR1 have been reported in primary BCs, with some more strongly associated with tamoxifen and AI resistance. This study aimed to establish a rapid, reliable and cost-effective method to screen and monitor ESR1 genomic aberrations in clinical BC tissue samples and relate these to the 1st line and subsequent ETs patients received. Patients: • Cohort A - 20 post-menopausal women (PMW) with ER+ BC who had acquired resistance to AIs and received subsequent lines of ET. Previous NGS data were available for these patients. • Cohort (B) - 425 ER+ BC patients, with paired matched tissue samples from the primary and progressive/recurrent cancer on 1st line ET; sites included local recurrence (25%), nodal recurrence (29%), distant recurrence (3%) and primary progression on neoadjuvant ET (44%). Median follow-up 10 years. All patients received 2nd line ET, 14% developed a further recurrence on 2nd line ET. Methods: ESRMs were assessed by allele-specific real-time quantitative (rt-qPCR) and digital droplet PCR (ddPCR) assays, a novel fluorometric in situ mutation detection (ISMD) approaches and AmpliSeq targeted sequencing. ESRA and ESR1 fusions were detected by targeted sequencing and validated using FISH and custom ligation assays for commonly-reported fusion proteins (currently ESR1-e6&amp;gt;YAP1 and ESR1-e6&amp;gt;PCDH11X), respectively. Results: Results from ddPCR and ISMD were consistent with NGS findings in cohort A. There was expansion of D538G mutant clones with acquired resistance in 5/20 patients (25%). ESR1 copy number gain was seen in 11/20 patients (55%) in resistant samples. Gene amplification was confirmed by FISH in 6, corresponding to those with the highest gain from the NGS data. In cohort B, recurrent/resistant samples (including 2nd recurrences) with matched primaries are currently being screened for ESR1 genomic aberrations using all methods allowing for a comprehensive comparison. This will allow full characterisation of mutations, copy number changes and gene fusions in the largest cohort of ET resistant cancers to date. Results will be interpreted in the context of 1st line ET (51% Tamoxifen, 34% non-steroidal AI, 8% exemestane, 7% other ET) and 2nd line ET in the 14% of patients who developed a 2nd recurrence. ESR1 genomic aberrations have been identified in 38% of samples to date, with specific aberrations associated with particular ETs. Discussion: • A reliable, robust and cost-effective methodology for the detection and quantitation of ESR1 aberrations in clinical BC samples has been developed and compared with NGS and targeted sequencing approaches. • This method would allow rapid screening for key aberrations with the potential to inform selection of 2nd line therapy. • Multiplexing of fluorometric assays may enable in situ clonality analysis that allows visualisation of multiple genomic driver aberrations simultaneously. • In the largest cohort of patients with resistance to ET to date, there is a high incidence of ESR1 genomic aberrations. These are associated with specific ETs. Analysis between these changes and response, disease-free and overall breast cancer-specific survival on 2nd line ET is currently ongoing. Citation Format: Carlos Martinez-Perez, Charlene Kay, James Meehan, Mark Gray, Rebecca Swan, Lorna Renshaw, Jane Keys, Andrew H Sims, Olga Oikonomidou, J Michael Dixon, Arran K Turnbull. Assessment of ESR1 genomic aberrations and their role in endocrine therapy resistance in breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-11-06.

PDTM-42. CROSS-PLATFORM PROFILING OF ctDNA USING ddPCR: STANDARDIZATION OF THE LIQUID BIOPSY FOR PEDIATRIC DIFFUSE MIDLINE GLIOMA

Abstract INTRODUCTION Pediatric diffuse midline glioma (DMG) with histone H3 mutations (80%), are highly morbid tumors with poor response to therapy. We previously detected H3 mutations in circulating tumor DNA (ctDNA) from CSF derived from children with DMG and high grade glioma. Here, we describe a high-throughput, sensitive and specific approach for H3 mutation detection and quantification in plasma and CSF specimens, validated across multiple centers. METHODS DNA extracted from tissue-validated H3.3K27M specimens (4 tumor, 5 CSF, 4 plasma) and pediatric glioma cell lines (1 wild-type, 1 H3.3K27M) were used to standardize ddPCR workflows. ctDNA extracted from 500uL of CSF or plasma was pre-amplified using sequence-specific primers, then analyzed on RainDance and BioRad ddPCR systems using two sets of custom primers and fluorescent LNA probes (Assays A and B). H3 mutation allelic frequency (MAF) was determined across specimens, and validated through parallel analysis of additional matched H3.3K27M tumor tissue, CSF and plasma specimens (n=3). RESULTS ctDNA processing and detection was standardized across three institutions and two platforms with sensitive, specific and reproducible H3 mutation detection. H3K27M mutations were detected in as little as 0.3-2pg input DNA on both platforms, with comparable MAFs across instruments and assays. RainDance yielded greater overall positive droplet number detection (increased sensitivity). Differences in optimal sample input volume between platforms were circumvented by vacuum concentration or dilution to maintain equal input DNA. Assay A yielded superior specificity so was used for subsequent matched specimen analysis. Mutation detection in plasma, as in previous studies, remained challenging due to low [ctDNA], while CSF analysis yielded reliable results across assays and platforms. CONCLUSIONS We demonstrate the utility of liquid biopsy for identifying H3K27M mutations in plasma and CSF via ddPCR with low starting [DNA], representing a rapid, minimally invasive method for diagnosis and therapeutic monitoring of DMG.

Development of a blood-based cancer screening assay with a novel multivariate cancer risk score (MCRS) model by integrating shallow WGS data and plasma protein markers.

45 Background: Despite the increase of our knowledge about carcinogenesis and recent successful development of innovative cancer drugs, cancer mortality has only slightly decreased in the past decades. Cancer early detection is probably the most cost-effective means to reduce cancer mortality as prognosis is much better when cancer is detected and treated at the early stage. Recently studies have demonstrated that blood-based mutation detection approaches may be effective to identify asymptomatic cancer patients from general population. Methods: Here we reported a novel multivariate cancer risk score (MCRS) model that interrogates shallow whole genome sequencing (WGS) data from cell-free DNA (cfDNA) and protein markers results in a single blood draw. Results: In a prospective clinical study consisting of 76 stage I-IV cancer patients and 152 normal individuals, the MCRS model demonstrated 60% sensitivity at 98.5% specificity. In order to validate clinical utility of the MCRS model in detection of cancer patients, we collated the data from a previous study of occult maternal malignancies from 1.93 million pregnant women undergoing NIPT test between 2016 and 2017. 466 out of the 639 pregnant women who tested positive for multiple chromosomal aneuploidies (MCAs) in the initial NIPTs (i.e. 0.06 - 0.1x WGS), have also underwent the protein markers test. Out of the 466 subjects, 39 maternal malignant cancer cases were diagnosed with a median follow-up of 399 days (IR, 303 - 487 days) by imaging and histology. The cancer patients presented a wide spectrum of cancer types, the most frequent being breast cancer (10 cases), liver cancer (8) and lymphoma (8), at stage II to IV. This subgroup of 466 subjects was selected as an independent validation cohort for our study. Through our new method, we analyzed shallow WGS and proteins data. The MCRS model allowed 28 of the 39 (71.8%) cancer cases to be identified with a positive predictive value of 73.7% and specificity of 97.7%. Conclusions: Taken together, these data demonstrate the MCRS model holds promise for detecting cancer in asymptomatic individuals, particularly in the populations at high risk of cancer.

An optimized ultra-deep massively parallel sequencing with unique molecular identifier tagging for detection and quantification of circulating tumor DNA from lung cancer patients.

55 Background: The identification and quantification of actionable mutations are of critical importance for effective genotype-directed therapies, prognosis and drug response monitoring in patients with non-small-cell lung cancer (NSCLC). Although tumor tissue biopsy remains the gold standard for diagnosis of NSCLC, the analysis of plasma circulating tumor DNA (ctDNA), known as liquid biopsy, has recently emerged as an alternative and noninvasive approach for exploring tumor genetic constitution. In this study, we developed a mutation detection approach for liquid biopsy using ultra-deep massively parallel sequencing (MPS) with unique molecular identifier (UID) tagging and evaluated its performance for the identification and quantification of tumor-derived mutations from plasma of patients with advanced NSCLC. Methods: Tissue biopsy and plasma samples were collected from a total of 58 patients diagnosed with NSCLC in Vietnam. Genetic alterations in four driver genes including EGFR, KRAS, NRAS and BRAF were identified by using ultra-deep MPS combined with UID tagging. Subsequently, the concordance rate of mutation testing between matched plasma and tissue samples was assessed. Additionally, a commercially available ddPCR (Bio-rad) assay was used to conduct a cross-platform comparison with ultra-deep MPS for the detection and quantification of the three most common actionable EGFR mutations (del19, L858R and T790M). Results: Compared to the mutations detected in paired tissue samples, the plasma based ultra-deep MPS achieved high concordance rate of 87.5%. Cross-platform comparison with droplet digital PCR demonstrated comparable detection performance (91.4% concordance, Cohen's kappa coefficient of 0.85 with 95% CI = 0.72 – 0.97) and great reliability in quantification of mutation allele frequency (Intraclass correlation coefficient of 0.96 with 95% CI = 0.90 – 0.98). Conclusions: Our results highlight the potential application of liquid biopsy using ultra-deep MPS as a routine assay in clinical practice for both detection and quantification of actionable mutation landscape in NSCLC patients.