Detection Of Single Nucleotide Variants Research Articles

Identification of Genomic Biomarkers of Disease Progression and Survival in Primary CNS Lymphoma.

The determination of the genetic subtypes of primary CNS lymphoma (PCNSL) and their relationship to differential chemo-immunotherapeutic response has not been established. There is a particular need for genomic biomarkers that identify patients with newly-diagnosed PCNSL at high risk of early progression and death. We applied targeted next-generation sequencing for detection of recurrent single nucleotide variants, copy number alterations and zygosity abnormalities in diagnostic specimens from 78 PCNSL patients treated with a standard methotrexate-based regimen, to identify prognostically significant molecular subgroups. All patients received induction immunochemotherapy and 44 proceeded to dose-intensive consolidation. Genomic aberrations at four loci were associated with 91% of lymphoma progression events and all 15 deaths: (1) chromosome 6p copy-neutral loss of heterozygosity (CN-LOH) or focal homozygous deletion (HD) at 6p21.3, and mutations of tumor suppressor genes (2) BTG1, (3) ETV6 and (4) TP53. Cox regression multivariate analysis demonstrated a high risk of progression in patients with aberrations at these loci. Genomic aberrations at these loci were also associated with significantly shorter survival. Lower expression of HLA-DR was associated with 6p CN-LOH/6p21.3 HD and inferior prognosis. These genomic aberrations identify a high-risk molecular subgroup that may inform risk stratification in PCNSL. Further elucidation of the mechanisms of therapeutic resistance associated with the high-risk genetic phenotype is requisite to facilitate precision medicine and progress in therapy.

Advances in Genotyping Detection of Fragmented Nucleic Acids.

Single nucleotide variant (SNV) detection is pivotal in various fields, including disease diagnosis, viral screening, genetically modified organism (GMO) identification, and genotyping. However, detecting SNVs presents significant challenges due to the fragmentation of nucleic acids caused by cellular apoptosis, molecular shearing, and physical degradation processes such as heating. Fragmented nucleic acids often exhibit variable lengths and inconsistent breakpoints, complicating the accurate detection of SNVs. This article delves into the underlying causes of nucleic acid fragmentation and synthesizes the strengths and limitations of next-generation sequencing technology, high-resolution melting curves, molecular probes, and CRISPR-based approaches for SNV detection in fragmented nucleic acids. By providing a detailed comparative analysis, it seeks to offer valuable insights for researchers working to overcome the challenges of SNV detection in fragmented samples, ultimately advancing the accurate and efficient detection of single nucleotide variants across diverse applications.

MiniSNV: accurate and fast single nucleotide variant calling from nanopore sequencing data.

Nanopore sequence technology has demonstrated a longer read length and enabled to potentially address the limitations of short-read sequencing including long-range haplotype phasing and accurate variant calling. However, there is still room for improvement in terms of the performance of single nucleotide variant (SNV) identification and computing resource usage for the state-of-the-art approaches. In this work, we introduce miniSNV, a lightweight SNV calling algorithm that simultaneously achieves high performance and yield. miniSNV utilizes known common variants in populations as variation backgrounds and leverages read pileup, read-based phasing, and consensus generation to identify and genotype SNVs for Oxford Nanopore Technologies (ONT) long reads. Benchmarks on real and simulated ONT data under various error profiles demonstrate that miniSNV has superior sensitivity and comparable accuracy on SNV detection and runs faster with outstanding scalability and lower memory than most state-of-the-art variant callers. miniSNV is available from https://github.com/CuiMiao-HIT/miniSNV.

Quantifying allele-specific CRISPR editing activity with CRISPECTOR2.0.

Off-target effects present a significant impediment to the safe and efficient use of CRISPR-Casgenome editing. Since off-target activity is influenced by the genomic sequence, the presence of sequence variants leads to varying on- and off-target profiles among different alleles or individuals. However, a reliable tool that quantifies genome editing activity in an allelic context is not available. Here, we introduce CRISPECTOR2.0, an extended version of our previously published software tool CRISPECTOR, with an allele-specific editing activity quantification option. CRISPECTOR2.0 enables reference-free, allele-aware, precise quantification of on- and off-target activity, by using de novo sample-specific single nucleotide variant (SNV) detection and statistical-based allele-calling algorithms. We demonstrate CRISPECTOR2.0 efficacy in analyzing samples containing multiple alleles and quantifying allele-specific editing activity, using data from diverse cell types, including primary human cells, plants, and an original extensive human cell line database. We identified instances where an SNV induced changes in the protospacer adjacent motif sequence, resulting in allele-specific editing. Intriguingly, differential allelic editing was also observed in regions carrying distal SNVs, hinting at the involvement of additional epigenetic factors. Our findings highlight the importance of allele-specific editing measurement as a milestone in the adaptation of efficient, accurate, and safe personalized genome editing.

One-base-mismatch CRISPR-based transistors for single nucleotide resolution assay

An effective strategy for accurately detecting single nucleotide variants (SNVs) is of great significance for genetic research and diagnostics. However, strict amplification conditions, complex experimental instruments, and specialized personnel are required to obtain a satisfactory tradeoff between sensitivity and selectivity for SNV discrimination. In this study, we present a CRISPR-based transistor biosensor for the rapid and highly selective detection of SNVs in viral RNA. By introducing a synthetic mismatch in the crRNA, the CRISPR-Cas13a protein can be engineered to capture the target SNV RNA directly on the surface of the graphene channel. This process induces a fast electrical signal response in the transistor, obviating the need for amplification or reporter molecules. The biosensor exhibits a detection limit for target RNA as low as 5 copies in 100 μL, which is comparable to that of real-time quantitative polymerase chain reaction (PCR). Its operational range spans from 10 to 5 × 105 copy mL–1 in artificial saliva solution. This capability enables the biosensor to discriminate between wild-type and SNV RNA within 15 min. By introducing 10 μL of swab samples during clinical testing, the biosensor provides specific detection of respiratory viruses in 19 oropharyngeal specimens, including influenza A, influenza B, and variants of SARS-CoV-2. This study emphasizes the CRISPR-transistor technique as a highly accurate and sensitive approach for field-deployable nucleic acid screening or diagnostics.

Mutation-Selected Amplification droplet digital PCR: A new single nucleotide variant detection assay for [formula omitted] mutant in tumor and plasma samples

The early detection of gene mutations in physiological and pathological processes is a powerful approach to guide decisions in precision medicine. However, detecting low-copy mutant DNA from clinical samples poses a challenge due to the enrichment of wild-type DNA backgrounds. In this study, we devised a novel strategy, named Mutation-Selected Amplification droplet digital PCR (MSA-ddPCR), to quantitatively analyze single nucleotide variants (SNVs) at low variant allele frequencies (VAFs). Using TP53R249S (a hotspot mutation associated with hepatocellular carcinoma) as a model, we optimized the concentration ratio of primers, the annealing temperature and nucleic acid amplification modifiers. Subsequently, we evaluated the linear range and precision of MSA-ddPCR by detecting TP53R249S and TP53wild-type (TP53WT) plasmid DNA, respectively. MSA-ddPCR demonstrated superior ability to discriminate between mutant DNA and wild-type DNA compared to traditional TaqMan-MGB PCR. We further applied MSA-ddPCR to analyze the TP53R249S mutation in 20 plasma samples and 15 formalin-fixed paraffin-embedded (FFPE) tissue samples, and assessed the agreement rates between MSA-ddPCR and amplicon high-throughput sequencing. The results showed that the limit of blanks of MSA-ddPCR are 0.449 copies μL−1 in the FAM channel and 0.452 copies μL−1 in the VIC channel. MSA-ddPCR could accurately quantify VAFs as low as 0.01 %, surpassing existing PCR and next-generation sequencing (NGS) methods. In the detection of clinical samples, a high correlation was found between MSA-ddPCR and amplicon high-throughput sequencing. Additionally, MSA-ddPCR outperformed sequencing methods in terms of detection time and simplicity of data analysis. MSA-ddPCR can be easily implemented into clinical practice and serve as a robust tool for detecting mutant genes due to its high sensitivity and accuracy.

Whole-exome-based single nucleotide variants and copy number analysis for prenatal diagnosis of compound heterozygosity of SMPD4.

Biallelic loss-of-function variants in SMPD4 cause a rare and severe neurodevelopmental disorder. These variants have been identified in a group of children with neurodevelopmental disorders with microcephaly, arthrogryposis, and structural brain anomalies. SMPD4 encodes a sphingomyelinase that hydrolyzes sphingomyelin into ceramide at neutral pH and can thereby affect membrane lipid homeostasis. SMPD4 localizes to the membranes of the endoplasmic reticulum and nuclear envelope and interacts with nuclear pore complexes. For the efficient prenatal diagnosis of rare and undiagnosed diseases, the parallel detection of copy number variants (CNVs) and single nucleotide variants using whole-exome analysis is required. A physical examination of the parents was performed. Karyotype and whole-exome analysis were performed for the fetus and the parents. A fetus with microcephaly and arthrogryposis; biallelic null variants (c.387-1G>A; Chr2[GRCh38]: g.130142742_130202459del) were detected by whole-exome sequencing (WES). We have reported for the first time the biallelic loss-of-function mutations in SMPD4 in patients born to unrelated parents in China. WES could replace chromosomal microarray analysis and copy number variation sequencing as a more cost-effective genetic test for detecting CNVs and diagnosing highly heterogeneous conditions.

Comparative analysis of genetic variants in pleural fluids and solid tissue biopsies of pleural mesothelioma patients: Implications for molecular heterogeneity assessment

ObjectivesThis study aims to determine whether the sequencing of DNA extracted from pleural fluids (PFs) of Pleural Mesothelioma (PM) patients accurately represents the genetic information obtained from the solid tissue counterpart biopsies with particular attention to the identification of single nucleotide variants (SNVs). Materials and methodsSingle pleural biopsy, PFs, and blood were collected from PM patients. DNA was extracted from these samples and then subjected to Whole-Exome Sequencing. ResultsA higher number of SNVs was identified in PFs than in solid tissue biopsies (STBs). Most SNVs were detected in PFs samples but not in STBs samples, while only a few SNVs were detected in STBs samples but not in PFs samples. ConclusionThe current findings support the notion that PFs might offer a more robust depiction of cancer's molecular diversity. Nonetheless, the current outcomes challenge the assertion that liquid biopsies can encompass the entirety of intra-patient variations. Indeed, a subset of potential cancer-driver SNVs was exclusively identified in STBs. However, relying solely on STBs would have precluded the detection of significant SNVs that were exclusively present in PFs. This implies that while PFs serve as a valuable complement to STBs, they do not supplant them.

Rapid tumor DNA analysis of cerebrospinal fluid accelerates treatment of central nervous system lymphoma

AbstractDelays and risks associated with neurosurgical biopsies preclude timely diagnosis and treatment of central nervous system (CNS) lymphoma and other CNS neoplasms. We prospectively integrated targeted rapid genotyping of cerebrospinal fluid (CSF) into the evaluation of 70 patients with CNS lesions of unknown cause. Participants underwent genotyping of CSF-derived DNA using a quantitative polymerase chain reaction–based approach for parallel detection of single-nucleotide variants in the MYD88, TERT promoter, IDH1, IDH2, BRAF, and H3F3A genes within 80 minutes of sample acquisition. Canonical mutations were detected in 42% of patients with neoplasms, including cases of primary and secondary CNS lymphoma, glioblastoma, IDH-mutant brainstem glioma, and H3K27M-mutant diffuse midline glioma. Genotyping results eliminated the need for surgical biopsies in 7 of 33 cases (21.2%) of newly diagnosed neoplasms, resulting in significantly accelerated initiation of disease-directed treatment (median, 3 vs 12 days; P = .027). This assay was then implemented in a Clinical Laboratory Improvement Amendments environment, with 2-day median turnaround for diagnosis of CNS lymphoma from 66 patients across 4 clinical sites. Our study prospectively demonstrates that targeted rapid CSF genotyping influences oncologic management for suspected CNS tumors.

Modified Unit-Mediated Strand Displacement Reactions for Direct Detection of Single Nucleotide Variants in Active Double-Stranded DNA.

Accurate identification of single nucleotide variants (SNVs) in key driver genes holds a significant value for disease diagnosis and treatment. Fluorescent probes exhibit tremendous potential in specific, high-resolution, and rapid detection of SNVs. However, additional steps are required in most post-PCR assays to convert double-stranded DNA (dsDNA) products into single-stranded DNA (ssDNA), enabling them to possess hybridization activity to trigger subsequent reactions. This process not only prolongs the complexity of the experiment but also introduces the risk of losing target information. In this study, we proposed two strategies for enriching active double-stranded DNA, involving PCR based on obstructive groups and cleavable units. Building upon this, we explored the impact of modified units on the strand displacement reaction (SDR) and assessed their discriminatory efficacy for mutations. The results showed that detection of low variant allele frequencies (VAF) as low as 0.1% can be achieved. The proposed strategy allowed orthogonal identification of 45 clinical colorectal cancer tissue samples with 100% specificity, and the results were generally consistent with sequencing results. Compared to existing methods for enriching active targets, our approach offers a more diverse set of enrichment strategies, characterized by the advantage of being simple and fast and preserving original information to the maximum extent. The objective of this study is to offer an effective solution for the swift and facile acquisition of active double-stranded DNA. We anticipate that our work will facilitate the practical applications of SDR based on dsDNA.

Abstract PO3-06-05: Association of tumor-derived extracellular vesicles with circulating tumor DNA alterations in metastatic breast cancer patients: exploring differences in inflammatory breast cancer

Abstract Background: Liquid biopsy provides a real-time assessment of metastatic breast cancer (MBC). Recently, the complementary prognostic value of tumor-derived extracellular vesicles (tdEVs) and circulating tumor cells (CTCs) has been reported. We have previously confirmed the strong prognostic significance of CTCs and tdEVs in inflammatory breast cancer (IBC). While previous studies have reported the association of CTCs with circulating tumor DNA (ctDNA) alterations in MBC, no evidence is available for tdEVs. This study aimed to analyze the association of tdEVs with ctDNA alterations, to investigate the molecular pathways underlying their presence. Moreover, we explored potential differences of this association in patients (pts) with IBC to provide a comprehensive liquid biopsy-based portrait of this aggressive subtype of BC. Methods: Blood samples were collected from 355 pts with MBC before starting a new line of therapy at Northwestern University (Chicago, IL) between 2016 and 2021 (NU16B06 trial). For CTCs and tdEVs analysis, 7.5 mL of blood was processed with the CellSearch® system. The ACCEPT software was applied to CellSearch® images to automatically enumerate CTCs and tdEVs. Positivity cutoff was ≥5 for CTCs, while tdEV cutoff points were < 20 (low), 20-79 (intermediate), and ≥80 (high). For ctDNA analysis, matched plasma samples (± 1 month) were analyzed with the Guardant360™ NGS platform for the detection of somatic single nucleotide variants (SNVs) and copy number variations (CNVs), which were classified into oncogenic pathways based on defined profiles generated on the Cancer Genome Atlas database (p53, PI3K, ER, RTK, RAS, RAF, WNT, MYC, cell cycle, notch). Associations between ctDNA pathways alterations and tdEVs were tested in the overall population by multinomial logistic regression and corrected for significant clinical characteristics. Differences in liquid biopsy features between IBC and non-IBC subgroups were analyzed through Fisher's exact test. Results: Of the 355 MBC pts, 210 (62%) had HR+ BC, 61 (17%) had HER2+ BC, and 68 (20%) had triple-negative BC. Eighty-three (23%) had a diagnosis of IBC and had a numerically lower tdEV count. Also, lower tdEVs were detected in HER2+ BC as compared with HR+. Significantly higher tdEVs were observed among pts with lobular histology, liver, and bone metastases. CTC count was significantly associated with tdEV number. A matched plasma sample for ctDNA analysis was available for 175 pts (62 IBC and 113 non-IBC). In the overall population, SNVs in ER pathway were associated with intermediated/high levels of tdEVs (p=0.004 and 0.008). A similar association was observed for CNVs in the cell cycle pathway (p=0.008 and 0.007). Moreover, associations with ≥80 tdEVs were observed for PI3K SNVs and CNVs (p=0.039 and 0.004, respectively), RTK CNVs (p=0.023), and MYC CNVs (p=0.001). In multivariable analysis, clinical characteristics associated with higher tdEVs were lobular histology (p=0.014 for 20-79 and < 0.001 for ≥80) and bone metastases (p=0.019 for 20-79 and 0.002 for ≥80). When considering clinical variables of interest, only ER SNVs and MYC CNVs were significantly associated with intermediate (p=0.031) and high (p=0.022) tdEV counts, respectively. While the association with ER SNVs and cell cycle CNVs was significant both in the IBC and non-IBC subgroups, others were specific for a certain subgroup: higher tdEVs were significantly associated with PI3K SNVs only in non-IBC pts whereas the significant association with CNVs in PI3K and MYC pathways was observed only in pts with IBC. Conclusion: Detection of tdEVs was associated with particular genomic profiles. These alterations seem to be different in IBC further underlying a different biology of this BC subtype. Additional studies are needed to explore how to integrate different liquid-biopsy based biomarkers in the management of pts with MBC. Citation Format: Eleonora Nicolò, Lorenzo Gerratana, Lorenzo Foffano, Laura Munoz Arcos, Mara Serena Serafini, Maroua Manai, Letizia Pontolillo, Nadia Bayou, Elisabetta Molteni, Amanda Kaylan Strickland, Youbin Zhang, Paolo D’Amico, Andrew Davis, Jeannine Donahue, Huiping liu, William Gradishar, Ami Shah, Giuseppe Curigliano, Carolina Reduzzi, Massimo Cristofanilli. Association of tumor-derived extracellular vesicles with circulating tumor DNA alterations in metastatic breast cancer patients: exploring differences in inflammatory breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-06-05.

Clinical Validation of a Targeted Next-Generation Sequencing Panel for Lymphoid Malignancies

Lymphoid malignancies are a heterogeneous group of hematological disorders characterized by a diverse range of morphologic, immunophenotypic, and clinical features. Next-generation sequencing (NGS) is increasingly being applied to delineate the complex nature of these malignancies and identify high-value biomarkers with diagnostic, prognostic, or therapeutic benefit. However, there are various challenges in using NGS routinely to characterize lymphoid malignancies, including pre-analytic issues, such as sequencing DNA from formalin-fixed, paraffin-embedded tissue, and optimizing the bioinformatic workflow for accurate variant calling and filtering. This study reports the clinical validation of a custom capture-based NGS panel to test for molecular markers in a range of lymphoproliferative diseases and histiocytic neoplasms. The fully validated clinical assay represents an accurate and sensitive tool for detection of single-nucleotide variants and small insertion/deletion events to facilitate the characterization and management of patients with hematologic cancers specifically of lymphoid origin.

Abstract 340: Validation of TSO500 NGS panel for comprehensive genomic profiling from FFPE tumor samples

Abstract Comprehensive genomic profiling (CGP) of tumor sample using large targeted NGS panels (e.g. MSK-IMPACT) has been shown to allow the detection of biomarkers from hundreds of cancer relevant genes involved in targeted and immunotherapy. Illumina TruSight Oncology 500 (TSO500), a commercial CGP assay, allows concurrent analysis of DNA and RNA to simultaneously detect multiple types of variants across 523 genes. The assay is intended to detect single nucleotide variants (SNV), insertions and deletions (indel), and multinucleotide variants (MNV), copy number gain (CNV), tumor mutational burden (TMB) and microsatellite instability (MSI) in DNA, and fusions and splicing variants (exon skipping) in RNA. Here we aimed to validate TSO500 assay for its analytical performance on FFPE tumor samples. The validation samples include commercial controls, cell lines, clinical FFPE from NSCLC, CRC, Uterus and GIST (tumor content ≥20%). Library preparation was performed from minimum of 40 ng DNA and 40ng RNA. The data analysis is performed using TruSight Oncology 500 Local App software (LRM v2.2). A custom script (v1.0) was used to add SNP annotation for small variants and combine data output into cumulative format. For SNV and indel detection QC, 61 of 64 DNA libraries (95%) passed the QC for library size (median insert size ≥70bp) and coverage (median exon coverage ≥150). The percentage of DNA libraries passing QC for CNV and MSI are 95% and 88%, respectively. All 64 RNA libraries passed QC. The analytical performance of TSO500 was summarized in the Table below. In summary, the results showed that all the acceptance criteria were met and the TSO500 assay can be utilized for genomic profiling of FFPE tumor samples. The study also identified a few limitations of the Illumina LRM software e.g. potential false positive SNV within a indel background, potential false negative of complex indel, and the challenge of long indel detection. Summary of analytical performance of TSO500 Sensitivity and specificity Assay LoD Accuracy by concordance Inter-run reproducibility SNV/Small indel Sensitivity for SNV and indel detection are 99.24% and 99.36%. The LoD for SNV is 3-5%, for DEL is 5-10% and for INS is 3-5%. PPA for SNV detections is 96.64% (115/119; 95% CI: 91.68%, 98.69%) and for small indel is 92.86% (13/14; 95% CI: 68.53%, 98.73%) between TSO500 and comparator assays. The positive call rate across all SNV and small indel variants is 98.7% (42842/43419). Specificity for SNV and small indel detection are 99.9998% and 100.00%, respectively. MSI Sensitivity and Specificity for MSI detection are both 100%. NA MSI status for all samples were detected with 100% of concordance by three assays; MSI concordance for MSI-H is 100% (95% CI: 60.97%, 100.0%) and for MSS is 100% (87.13%, 100.0%). PPA is 100% (95% CI: 51.01%, 100%) and NPA is 100% (95% CI: 34.24%, 100%). TMB NA NA TSO500 reported TMB is well correlated and comparable to exome determined TMB. The CV values for samples are acceptable. CNV NA NA All positive CNVs detected by the comparator assay were detected by the TSO500 assay with similar fold changes; The overall reproducible call rate is 91.5% (43/47). PPA between TSO500 and OCAV3 assays is 100% (95% CI: 51.01%, 100%). Fusion Sensitivity and specificity for fusion detection is 91.94% and 100%, respectively. NA All TSO500 assay detected fusions were confirmed by other assays;PPA is 100% (95% CI: 60.97%, 100%) and NPA is 100% (95% CI: 75.75%, 100%) The reproducibility of fusion call is 92.59% (25/27; 95% CI: 76.63%, 97.94%). Splicing Sensitivity and Specificity for splicing variant detection are 91.67% and 100.00%, respectively. NA The splicing variant detections were confirmed by OCAV3, OFA and Archer assays; The overall reproducibility of positive call is 100% with 95% CI (43.85%, 100%) and negative call reproducibility is 100% with 95% CI (87.13%, 100%). PPA is 100% (95%% CI: 20.65%, 100%) and NPA is 100% (95% CI: 83.18%, 100%) Citation Format: Jin Li, Zhenyu Yan, Weihua Liu, Lin Shi, Cynthia Spittle, Chad Galderisi. Validation of TSO500 NGS panel for comprehensive genomic profiling from FFPE tumor samples [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 340.

Abstract 5038: Validation of a comprehensive next-generation sequencing liquid biopsy assay for clinical diagnostics and clinical trial applications

Abstract Liquid biopsy next generation sequencing (NGS) provides a powerful non-invasive approach to detect solid tumor derived somatic variants in a massively parallel manner. Liquid biopsy NGS has rapidly become an invaluable choice of testing technologies for clinical utility where invasive tissue biopsy is inaccessible and/or inadequate for molecular characterization. We present here a targeted NGS gene panel assay designed and validated specifically for liquid biopsy characterization. The assay was designed to test cell free DNA and cell free RNA from blood plasma for detection of single nucleotide variants (SNV), insertion/deletion (Indel), copy number variants (CNV), and gene fusions present in 52 most commonly mutated genes in cancers. The validation was performed to assess assay accuracy, specificity, sensitivity, repeatability, and reproducibility, with including pre-characterized reference controls, retrospective plasma samples from cancer patients, and prospectively-collected clinic blood specimen. Triplicates were included and testing was performed at different times and by different operators to assess the assay precision. Over 100 clinic blood specimens were collected in Streck cfDNA tubes from multiple trial centers, including treatment naïve phase III-IV patients with solid tumor (lung cancer, breast cancer, brain cancer, prostate cancer, kidney cancer, melanoma, etc) as well as heathy donors, processed within 7 days for plasma separation and total nucleotide acid (TNA) extraction, and assessed by the NGS assay for mutation detection. The identified mutations and wild-types were verified with orthogonal ddPCR. Assay sensitivity as low as 0.1% for SNV and Indel, 1.3 fold change for CNV, and 10 copies for gene fusion were observed, with near-perfect assay specificity (>99.99%) at these sensitivity levels. In conclusion, a targeted NGS liquid biopsy assay was analytically validated under medical oversight, with a demonstrated rigor of the test by its high sensitivity/specificity and robust reproducibility. The validated assay has been utilized for clinical diagnostics and to support research and development efforts in clinical trials. Citation Format: Xin-Xing Tan, Tricia Peters, Meredith Berry, Kimberly Barber, Kristyn Jeter, Brigitte Lovell, Paula Elizondo, Yanglong Mou, Brad Thomas, Heng Xie, Jiannan Guo. Validation of a comprehensive next-generation sequencing liquid biopsy assay for clinical diagnostics and clinical trial applications [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 5038.

Abstract 7414: Claire: a search engine leveraging deep databases for reliable detection of peptides, with a special focus on proteogenomic applications

Abstract As the field of cancer diagnostics and treatment evolves, the significance of peptides characterized by post-translational modifications and amino acid substitutions is becoming increasingly prominent. These molecular alterations frequently offer critical insights into tumor biology, aiding the development of targeted therapies and methods for personalized medicine. However, despite ongoing advances in shotgun proteomics, the field still faces multiple challenges for the reliable detection of rare peptide forms, for instance, amino acid substitutions when the corresponding DNA or RNA sequencing is unavailable. As a response to these challenges, our group has developed Claire—a probabilistic search engine employing large peptide databases for detection. These databases, often on the terabyte scale, further incorporate the estimates of peptides' prior probabilities to improve detection accuracy and utilize several optimizations to allow fast interpretation of tandem mass spectra. Claire outperformed state-of-the-art software, such as MSFragger and TagGraph when evaluated on the protein-level detection of single nucleotide variants in the public NCI60 proteome dataset. Further, Claire's analysis of a range of NCI60 datasets revealed high protein-level mutational burdens in genomically unstable cancer cell lines and detected mislabeling and contamination across several omics datasets. In a clinical domain, Claire discerned the hypermutation status of colorectal cancer patients' tumors, identifying candidates suitable for immunotherapy. Protein-level variation in peripheral blood mononuclear cells also recognized individuals, monozygotic twins aside, revealing the pseudonymous nature of germline proteome datasets, and raising the need for their protection. From a computational perspective, Claire can be run as a standalone software in the Linux operating system, or its capabilities accessed remotely using an interface on our cloud computing infrastructure. Claire has thus shown remarkable potential in enhancing peptide detection, offers substantial advancements for both clinical and research applications, and allows direct incorporation of its capabilities into various computational workflows. Citation Format: Miroslav Hruska, Petr Dzubak, Marian Hajduch. Claire: a search engine leveraging deep databases for reliable detection of peptides, with a special focus on proteogenomic applications [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 7414.

Abstract 3694: Genomic profiling of single cancer cells using the novel single-cell integrated mutational profiling of actionable cancer targets (scIMPACT) assay

Abstract Liquid biopsy provides opportunities to guide therapy decisions using biomarkers such as circulating tumor cells (CTCs) even years after the primary tumor resection. For this, novel methods permitting the genomic profiling of CTCs are needed to characterize systemic cancer spread and identify clinically targetable genomic alterations. Hence, we developed an assay based on the FDA-approved MSK-IMPACT® assay to analyze the genomes of single-cells. We present a series of benchmarking experiments using well-characterized cell lines to demonstrate the performance of our new Single-Cell Integrated Mutation Profiling of Actionable Cancer Targets (scIMPACT) assay.The scIMPACT assay was developed using Ampli1® WGA products of single-cell and pool samples. The workflow consists of an optimized library preparation protocol followed by targeted sequencing with the scIMPACT panel. A bioinformatics mutation calling workflow facilitates the detection of single nucleotide variations (SNVs), indels, and copy number variations (CNVs). To account for WGA associated bias, we developed an in-house proprietary machine learning based classifier algorithm. Two sample collectives were prepared and used for training and validating the workflow. The first collective, including genomic libraries of MDA-MB-453, BT474, BT549 and ZR-75.1 samples, was used for training of the mutation detection workflow. The second collective, consisting of HCC1395/HCC1395BL cell lines representing matched tumor and normal cells, was used to validate the performance of the assay. The scIMPACT assay identified somatic mutations in all WGA products as predicted from bulk gDNA samples and published literature. Notably, evidence of genetic heterogeneity was reported at the single cell level. Pertaining to the SNV detection, the training collective displayed 91% sensitivity and 96% specificity (AUC=0.98) while the validation collective demonstrated similar performance with 84% sensitivity and 96% specificity (AUC=0.90) proving the applicability of our workflow across different datasets. Furthermore, CNV analysis showed high concordance between matching gDNA and WGA samples. Our workflow enables mutational profiling with high specificity and sensitivity and accurate CNV detection in single cells. The scIMPACT assay has been successfully adapted to analyze samples at the single-cell level. Therefore, our method can be applied for the genomic profiling of patient-derived CTCs. Citation Format: Clara Chaiban, Adithi Ravikumar Varadarajan, Jonas Grote, Thomas Ragg, Isabell Blochberger, Vadim Dechand, Jens Warfsmann, Christoph A. Klein, Zbigniew T. Czyż. Genomic profiling of single cancer cells using the novel single-cell integrated mutational profiling of actionable cancer targets (scIMPACT) assay [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 3694.

Abstract 2283: A targeted mutation calling workflow - end to end - from FASTQ to clinical report for single cells

Abstract Molecular profiling of rare cancer cells derived from liquid biopsy holds promise to monitor systemic cancer progression and guide personalized therapy interventions. However, this necessitates reliable and comprehensive profiling of samples at the single cell level and requires whole genome amplification (WGA), which adds amplification errors and bias to common sequencing errors. Therefore, we established a single-cell mutation calling workflow that can identify clinically actionable somatic mutations in rare single cell DNA with high sensitivity and accuracy. Our workflow is an end-to-end solution which can take FASTQ reads from any Panel Sequencing (PanelSeq) data and gives out single nucleotide variations (SNVs), insertion-deletions (InDels), and copy number variations (CNVs) in single cells alongside with mutation specific information from ClinVar, OncoKB, pathogenicity scores, conservations scores as well as known association to drug response and resistance. We incorporated a Bayesian Neural Network (NN) based Classifier algorithm that assigns a single statistical confidence score to the mutations, enabling prioritization of the mutations in a robust manner. On the training dataset including MDA-MB-453, BT474, BT549 and ZR-75.1 cell lines, the classifier achieved 91% sensitivity and 96% specificity (AUC=0.98), while on the independent test collective including HCC1395/HCC1395BL cell lines it achieved 84% sensitivity and 96% specificity (AUC=0.90). We applied the workflow to patient samples suffering from advanced metastatic Triple Negative Breast Cancer (TNBC) assayed with in-house single-cell Integrated Mutation Profiling of Actionable Cancer Targets (scIMPACT) and single-cell Whole Exome Sequencing (scWES). Using our method, we detected clinically actionable SNVs with pathogenic relevance in primary tumor, metastatic specimens, circulating tumor cells (CTCs) from blood and disseminated cancer cells (DCC) from pleural effusions, as well as the matched CTC-derived in vivo models (CDX). Notably, functional in vitro drug screens performed on CDX models uncovered susceptibility to approved drug treatments conferred by mutations detected in the samples. In summary, we introduce a novel mutation calling workflow facilitating detection of SNVs, Indels and CNVs in rare single cells with high sensitivity and precision. Confident scores assigned by the NN classifier enables identification of functionally actionable mutations. The workflow was executed in GDPR compliant fashion and follows all data protection standards imposed by the European laws. Accordingly, the method is well suited for molecular profiling, therapeutic target selection and longitudinal monitoring of liquid biopsy specimens in diagnostic environments. Citation Format: Adithi Ravikumar Varadarajan, Thomas Ragg, Jonas Grote, Vadim Dechand, Steffi Treitschke, Clara Chaiban, Christoph Klein, Zbigniew Czyz, Jens Warfsmann. A targeted mutation calling workflow - end to end - from FASTQ to clinical report for single cells [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 2283.

MtDNA analysis using Mitopore

Mitochondrial DNA (mtDNA) analysis is crucial for diagnosis of mitochondrial disorders, forensic investigations, and basic research, but existing pipelines are complex, expensive, and require specialized personnel. In many cases, including the diagnosis of detrimental single nucleotide variants (SNVs), mtDNA analysis is still carried out using Sanger sequencing. Here, we developed a simple workflow and a publicly available webserver named Mitopore that allows the detection of mtDNA SNVs, indels and haplogroups. To simplify mtDNA analysis, we tailored our workflow to process noisy long-read sequencing data for mtDNA analysis, focusing on sequence alignment and parameter optimization. We implemented Mitopore with eliBQ (eliminate Bad Quality reads), an innovative quality enhancement that allows to increase per base quality of over 20 % for low-quality data. The whole Mitopore workflow and webserver were validated using patient-derived and induced pluripotent stem cells harboring mtDNA mutations. Mitopore streamlines mtDNA analysis as an easy-to-use fast, reliable, and cost-effective analysis method for both long- and short-read sequencing data. This significantly enhances the accessibility of mtDNA analysis and reduces the cost per sample, contributing to the progress of mtDNA-related research and diagnosis.

Long read sequencing on its way to the routine diagnostics of genetic diseases.

The clinical application of technological progress in the identification of DNA alterations has always led to improvements of diagnostic yields in genetic medicine. At chromosome side, from cytogenetic techniques evaluating number and gross structural defects to genomic microarrays detecting cryptic copy number variants, and at molecular level, from Sanger method studying the nucleotide sequence of single genes to the high-throughput next-generation sequencing (NGS) technologies, resolution and sensitivity progressively increased expanding considerably the range of detectable DNA anomalies and alongside of Mendelian disorders with known genetic causes. However, particular genomic regions (i.e., repetitive and GC-rich sequences) are inefficiently analyzed by standard genetic tests, still relying on laborious, time-consuming and low-sensitive approaches (i.e., southern-blot for repeat expansion or long-PCR for genes with highly homologous pseudogenes), accounting for at least part of the patients with undiagnosed genetic disorders. Third generation sequencing, generating long reads with improved mappability, is more suitable for the detection of structural alterations and defects in hardly accessible genomic regions. Although recently implemented and not yet clinically available, long read sequencing (LRS) technologies have already shown their potential in genetic medicine research that might greatly impact on diagnostic yield and reporting times, through their translation to clinical settings. The main investigated LRS application concerns the identification of structural variants and repeat expansions, probably because techniques for their detection have not evolved as rapidly as those dedicated to single nucleotide variants (SNV) identification: gold standard analyses are karyotyping and microarrays for balanced and unbalanced chromosome rearrangements, respectively, and southern blot and repeat-primed PCR for the amplification and sizing of expanded alleles, impaired by limited resolution and sensitivity that have not been significantly improved by the advent of NGS. Nevertheless, more recently, with the increased accuracy provided by the latest product releases, LRS has been tested also for SNV detection, especially in genes with highly homologous pseudogenes and for haplotype reconstruction to assess the parental origin of alleles with de novo pathogenic variants. We provide a review of relevant recent scientific papers exploring LRS potential in the diagnosis of genetic diseases and its potential future applications in routine genetic testing.

Genetics of inborn errors of immunity: Diagnostic strategies and new approaches to CNV detection.

Genetic diagnosis of inborn errors of immunity (IEI) is complex due to the large number of genes involved and their molecular features. Missense variants have been reported as the most common cause of IEI. However, the frequency of copy number variants (CNVs) may be underestimated since their detection requires specific quantitative techniques. At this point, the use of Next Generation Sequencing (NGS) is acquiring relevance. In this article, we present our experience in the genetic diagnosis of IEI based on three diagnostic algorithms that allowed the detection of single nucleotide variants (SNVs) and CNVs. Following this approximation, 703 index cases were evaluated between 2014 and 2021. Sanger sequencing, MLPA, CGH array, breakpoint spanning PCR or a customized NGS-based multigene-targeted panel were performed. A genetic diagnosis was reached in 142 of the 703 index cases (20%), 19 of them presented deletions as causal variants. Deletions were also detected in 5 affected relatives and 16 healthy carriers during the family studies. Additionally, we compile, characterize and present all the CNVs detected by our diagnostic algorithms, representing the largest cohort of deletions related to IEI to date. Furthermore, three bioinformatic tools (LACONv, XHMM, VarSeq™) based on NGS data were evaluated. VarSeq™ was the most sensitive and specific bioinformatic tool; detecting 21/23 (91%) deletions located in captured regions. Based on our results, we propose a strategy to guide the molecular diagnosis that can be followed by expert and non-expert centres in the field of IEI.