Single-cell Next-generation Sequencing Research Articles

Next-Generation Sequencing: An Advanced Diagnostic Tool for Detection of Pancreatic Disease/Disorder.

The pancreas is involved in digestion and glucose regulation in the human body. Given the recognized link between chronic pancreatitis and pancreatic cancer, addressing pancreatic disorders and pancreatic cancer is particularly challenging. This review aims to highlight the limitations of traditional methods in diagnosing pancreatic disorders and cancer and explore several next-generation sequencing (NGS) approaches as a promising alternative. There are distinct clinical symptoms that are shared by a number of clinical phenotypes of pancreatic illness induced by particular genetic mutations. Traditional diagnostic methods encompass computed tomography, magnetic resonance imaging, contrast-enhanced Doppler ultrasound, endoscopic ultrasound, endoscopic retrograde cholangiopancreatography, transabdominal ultrasound, laparoscopy, and positron emission tomography have a prognostic ability of only 5% or less and a 5-year survival rate. Genetic sequencing can be employed as an alternative to conventional diagnostic techniques. Sanger sequencing and NGS are currently largely operated genome analysis, with no exception for pancreatic disease diagnosis. The NGS methods can sequence millions to billions of short DNA fragments, enabling enormous sample screening in a short amount of time with low-abundance detection, like in 0.1%-1% mutation prevalence declining approximate cost. Whole-genome sequencing, whole-exome sequencing, RNA sequencing, and single-cell NGS are a few NGS methods utilized to diagnose pancreatic disease. For both research and clinical applications, the NGS techniques can provide a precise diagnosis of pancreatic disorders in a short amount of time at a reasonable expenditure.

Variant load of mitochondrial DNA in single human mesenchymal stem cells

Heteroplasmic mitochondrial DNA (mtDNA) variants accumulate as humans age, particularly in the stem-cell compartments, and are an important contributor to age-related disease. Mitochondrial dysfunction has been observed in osteoporosis and somatic mtDNA pathogenic variants have been observed in animal models of osteoporosis. However, this has never been assessed in the relevant human tissue. Mesenchymal stem cells (MSCs) are the progenitors to many cells of the musculoskeletal system and are critical to skeletal tissues and bone vitality. Investigating mtDNA in MSCs could provide novel insights into the role of mitochondrial dysfunction in osteoporosis. To determine if this is possible, we investigated the landscape of somatic mtDNA variation in MSCs through a combination of fluorescence-activated cell sorting and single-cell next-generation sequencing. Our data show that somatic heteroplasmic variants are present in individual patient-derived MSCs, can reach high heteroplasmic fractions and have the potential to be pathogenic. The identification of somatic heteroplasmic variants in MSCs of patients highlights the potential for mitochondrial dysfunction to contribute to the pathogenesis of osteoporosis.

Exploiting a living biobank to delineate mechanisms underlying disease-specific chromosome instability.

Chromosome instability (CIN) is a cancer hallmark that drives tumour heterogeneity, phenotypic adaptation, drug resistance and poor prognosis. High-grade serous ovarian cancer (HGSOC), one of the most chromosomally unstable tumour types, has a 5-year survival rate of only ~30% - largely due to late diagnosis and rapid development of drug resistance, e.g., via CIN-driven ABCB1 translocations. However, CIN is also a cell cycle vulnerability that can be exploited to specifically target tumour cells, illustrated by the success of PARP inhibitors to target homologous recombination deficiency (HRD). However, a lack of appropriate models with ongoing CIN has been a barrier to fully exploiting disease-specific CIN mechanisms. This barrier is now being overcome with the development of patient-derived cell cultures and organoids. In this review, we describe our progress building a Living Biobank of over 120 patient-derived ovarian cancer models (OCMs), predominantly from HGSOC. OCMs are highly purified tumour fractions with extensive proliferative potential that can be analysed at early passage. OCMs have diverse karyotypes, display intra- and inter-patient heterogeneity and mitotic abnormality rates far higher than established cell lines. OCMs encompass a broad-spectrum of HGSOC hallmarks, including a range of p53 alterations and BRCA1/2 mutations, and display drug resistance mechanisms seen in the clinic, e.g., ABCB1 translocations and BRCA2 reversion. OCMs are amenable to functional analysis, drug-sensitivity profiling, and multi-omics, including single-cell next-generation sequencing, and thus represent a platform for delineating HGSOC-specific CIN mechanisms. In turn, our vision is that this understanding will inform the design of new therapeutic strategies.

Single-Cell Next-Generation Sequencing to Monitor Hematopoietic Stem-Cell Transplantation: Current Applications and Future Perspectives.

Acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) are genetically complex and diverse diseases. Such complexity makes challenging the monitoring of response to treatment. Measurable residual disease (MRD) assessment is a powerful tool for monitoring response and guiding therapeutic interventions. This is accomplished through targeted next-generation sequencing (NGS), as well as polymerase chain reaction and multiparameter flow cytometry, to detect genomic aberrations at a previously challenging leukemic cell concentration. A major shortcoming of NGS techniques is the inability to discriminate nonleukemic clonal hematopoiesis. In addition, risk assessment and prognostication become more complicated after hematopoietic stem-cell transplantation (HSCT) due to genotypic drift. To address this, newer sequencing techniques have been developed, leading to more prospective and randomized clinical trials aiming to demonstrate the prognostic utility of single-cell next-generation sequencing in predicting patient outcomes following HSCT. This review discusses the use of single-cell DNA genomics in MRD assessment for AML/MDS, with an emphasis on the HSCT time period, including the challenges with current technologies. We also touch on the potential benefits of single-cell RNA sequencing and analysis of accessible chromatin, which generate high-dimensional data at the cellular resolution for investigational purposes, but not currently used in the clinical setting.

Single-cell next-generation sequencing of circulating tumor cells in patients with neuroblastoma.

Circulating tumor cells (CTCs) derived from any tumor tissue could contribute to metastasis and resistance to cancer treatments. In this study, we performed single-cell next-generation sequencing of CTCs and evaluated their usefulness for characterizing tumor biology and the mechanisms of metastasis in neuroblastomas (NB). We aimed to isolate CTCs from10 patients with NB at diagnosis before any treatments and four patients at relapse. GD2+ CD90+ CD45- CD235a- DAPI- cells were isolated as neuroblastoma CTCs using fluorescence-activated cell sorting. In five patients with advanced stages (M stage), DNA and RNA sequencing of CTCs at single-cell level were performed. NB CTCs were isolated from eight of the 10 patients at diagnosis and three of the four patients at relapse. More CTCs could be isolated from patients with advanced stages. In one patient, ALK mutation (p.F1174L), was identified in both tumor tissue and a CTC. In patients with MYCN amplification, this gene was amplified in 12 of 13 CTCs. Using single-cell RNA sequencing, angiogenesis-related and cell cycle-related genes together with CCND1 and TUBA1A genes were found to be upregulated in CTCs. In one patient, CTCs were divided into two subgroups showing different gene expression profiles. In one subgroup, cell cycle-related and proliferation-related genes were differentially upregulated compared with the other group. In conclusion, next-generation sequencing of CTCs at single-cell level might help to characterize the tumor biology and the mechanisms of metastasis in NB.

Abstract 2008: The oncogenic fusion protein DNAJB1-PRKACA can be actively targeted by peptide-based immunotherapy in fibrolamellar hepatocellular carcinoma

Abstract Fibrolamellar hepatocellular carcinoma (FL-HCC) is a rare tumor disease, which affects children and adolescents without history of primary liver disease. Beside surgical resection established treatment options are lacking for FL-HCC. Recently, the DNAJB1-PRKACA fusion transcript was identified as the oncogenic driver of tumor pathogenesis in 100% of FL-HCC patients. Here, we investigated the role of the DNAJB1-PRKACA fusion protein as a source for immunogenic neoepitopes and showed first immunotherapeutic application of these antigens in a FL-HCC patient.HLA class I- and class II-presented neoantigens derived from the DNAJB1-PRKACA fusion protein were predicted in silico using NetMHCpan 4.1 and SYFPEITHI 1.0, or NetMHCIIpan 4.0, respectively. With this workflow nine binding cores of nine amino acid length for a total of 1290 different HLA class II alleles, as well as 13 HLA class I ligands for the 20 most frequent HLA class I allotypes (European population, iedb.org) were identified. Cellular processing and HLA presentation of DNAJB1-PRKACA-derived peptides was proven by liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) of DNAJB1-PRKACA-transduced HCC cell lines. Immunogenicity of DNAJB1-PRKACA-derived peptides was assessed for the HLA class II peptide (PII-1) and the HLA-A*24 peptide (PA*24) by in vitro priming experiments which showed an induction of multifunctional peptide-specific CD4+ and CD8+ T cells, respectively, with expression of CD107a, IFNγ, and TNF upon peptide-pulsing. Furthermore, PA*24-specific T cells showed antigen-specific lysis of autologous peptide-loaded target cells and single-cell next-generation sequencing (10x Genomics) of PA*24-specific CD8+ T cells further enabled the identification of DNAJB1-PRKACA-reactive T cell receptors. Based on these preclinical data we applied a peptide vaccine, consisting of three HLA class I ligands (PA*02, PB*44, and PC*05) and PII-1 spanning the DNAJB1-PRKACA fusion region, to a 15-year old patient with histologically confirmed FL-HCC, who experienced multiple tumor relapses after early liver transplant due to unresectable FL-HCC not responsive to chemotherapy. After two vaccinations in vivo induction of multifunctional CD4+ T cells targeting PII-1 and PB*44 was observed by IFNγ ELISPOT. Single-cell RNA sequencing of vaccine-induced CD4+ T cells revealed distinct gene expression clusters of T cell activation and high TCR clonality. DNAJB1-PRKACA-specific T cells persisted in peripheral blood and were accompanied by relapse free survival of the patient until now, more than one year post vaccination. These findings identified the DNAJB1-PRKACA fusion transcript as novel prime source for broadly applicable neoepitopes and corresponding TCRs and provide first evidence for their application in cancer immunotherapy of FL-HCC. Citation Format: Jens Bauer, Natalie Köhler, Yacine Maringer, Philip Bucher, Tatjana Bilich, Melissa Zwick, Severin Dicks, Annika Nelde, Marissa Dubbelaar, Jonas Scheid, Marcel Wacker, Jonas J. Heitmann, Sarah Schroeder, Jonas Rieth, Monika Denk, Marion Richter, Reinhild Klein, Irina Bonzheim, Julia Luibrand, Ursula Holzer, Martin Ebinger, Ines B. Brecht, Michael Bitzer, Melanie Boerries, Helmut R. Salih, Hans-Georg Rammensee, Stephan Hailfinger, Juliane S. Walz. The oncogenic fusion protein DNAJB1-PRKACA can be actively targeted by peptide-based immunotherapy in fibrolamellar hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2008.

Enhancer-Promoter Communication: It's Not Just About Contact.

Cis-regulatory elements such as enhancers can be located even a million base pairs away from their cognate promoter and yet modulate gene transcription. Indeed, the 3D organisation of chromatin enables the establishment of long-range enhancer-promoter communication. The observation of long-range enhancer-promoter chromatin loops at active genes originally led to a model in which enhancers and promoters form physical contacts between each other to control transcription. Yet, recent microscopy data has challenged this prevailing activity-by-contact model of enhancer-promoter communication in transcriptional activation. Live single-cell imaging approaches do not systematically reveal a correlation between enhancer-proximity and transcriptional activation. We therefore discuss the need to move from a static to a dynamic view of enhancer-promoter relationships. We highlight recent studies that not only reveal considerable chromatin movement in specific cell types, but suggest links between chromatin compaction, chromatin movement and transcription. We describe the interplay between enhancer-promoter proximity within the context of biomolecular condensates and the need to understand how condensate microenvironments influence the chromatin binding kinetics of proteins that bind at cis-regulatory elements to activate transcription. Finally, given the complex multi-scale interplay between regulatory proteins, enhancer-promoter proximity and movement, we propose the need to integrate information from complementary single-cell next-generation sequencing and live-cell imaging approaches to derive unified 3D theoretical models of enhancer-promoter communication that are ultimately predictive of transcriptional output and cell fate. In time, improved models will shed light on how tissues grow and diseases emerge.

Single-cell DNA-seq depicts clonal evolution of multiple driver alterations in osimertinib-resistant patients

The development of targeted agents, such as osimertinib for EGFR-mutated non-small-cell lung cancer (NSCLC), has drastically improved patient outcome, but tumor resistance eventually always occurs. In osimertinib-resistant NSCLC, the emergence of a second molecular driver alteration (such as ALK, RET, FGFR3 fusions or BRAF, KRAS mutations) has been described. Whether those alterations and the activating EGFR mutations occur within a single cancer cell or in distinct cell populations is largely debated. Tumor sequencing was used to identify the acquired resistance mechanisms to osimertinib in the MATCH-R trial (NCT0251782). We implemented single-cell next-generation sequencing to investigate tumor heterogeneity on patient's frozen tissues in which multiple alterations have been identified. Patient-derived models, cell lines, and patient-derived xenografts were exposed to specific inhibitors to investigate combination treatment strategies. Among the 45 patients included in MATCH-R who progressed on osimertinib, 9 developed a second targetable alteration (n= 2 FGFR3-TACC3, n= 1 KIF5B-RET, n= 1 STRN-ALK fusions; n= 2 BRAFV600E, n= 1 KRASG12V, n= 1 KRASG12R, n= 1 KRASG12D mutations). Single-cell analysis revealed that the two driver alterations coexist within one single cancer cell in the four patients whose frozen samples were fully contributive. A high degree of heterogeneity within samples and sequential acquisitions of molecular events were highlighted. A combination treatment concomitantly targeting the two driver alterations was required on the corresponding patient-derived models to restore cell sensitivity, which was consistent with clinical data showing efficacy of brigatinib in the patient with ALK fusion after progression to osimertinib and crizotinib administered sequentially. Distinct molecular driver alterations at osimertinib resistance coexist with initial EGFR mutations in single cancer cells. The clonal evolution of cancer cell populations emphasized their heterogeneity leading to osimertinib relapse. Combining two targeted treatments is effective to achieve clinical benefit.

T-Cell Repertoire Characterization.

T-cell repertoire characterization is a methodology that enables the identification of T-cell receptor (TCR) gene sequences in a T-cell population. TCR genes are composed of modular gene segments V (D) J that undergo somatic recombination, resulting in unique and unpredictable sequences that can be utilized to identify each T-cell clone. The analysis of the TCR composition in a T-cell population can give information on the biological phenomenon such as antigen-driven expansion and heterogeneity of T-cell responses. Bulk TCR analysis can give useful information on the clonality and can help track a specific clonotype over time or in different compartments, although the information about pairing cannot be provided. Single-cell TCR sequencing, on the other hand, can provide pairing information that are necessary to reconstruct the TCR and confirm antigen specificity.Here we describe common methods to characterize T-cell repertoires based on both bulk and single-cell next-generation sequencing.

A Portrait of Intratumoral Genomic and Transcriptomic Heterogeneity at Single-Cell Level in Colorectal Cancer.

In the study of cancer, omics technologies are supporting the transition from traditional clinical approaches to precision medicine. Intra-tumoral heterogeneity (ITH) is detectable within a single tumor in which cancer cell subpopulations with different genome features coexist in a patient in different tumor areas or may evolve/differ over time. Colorectal carcinoma (CRC) is characterized by heterogeneous features involving genomic, epigenomic, and transcriptomic alterations. The study of ITH is a promising new frontier to lay the foundation towards successful CRC diagnosis and treatment. Genome and transcriptome sequencing together with editing technologies are revolutionizing biomedical research, representing the most promising tools for overcoming unmet clinical and research challenges. Rapid advances in both bulk and single-cell next-generation sequencing (NGS) are identifying primary and metastatic intratumoral genomic and transcriptional heterogeneity. They provide critical insight in the origin and spatiotemporal evolution of genomic clones responsible for early and late therapeutic resistance and relapse. Single-cell technologies can be used to define subpopulations within a known cell type by searching for differential gene expression within the cell population of interest and/or effectively isolating signal from rare cell populations that would not be detectable by other methods. Each single-cell sequencing analysis is driven by clustering of cells based on their differentially expressed genes. Genes that drive clustering can be used as unique markers for a specific cell population. In this review we analyzed, starting from published data, the possible achievement of a transition from clinical CRC research to precision medicine with an emphasis on new single-cell based techniques; at the same time, we focused on all approaches and issues related to this promising technology. This transition might enable noninvasive screening for early diagnosis, individualized prediction of therapeutic response, and discovery of additional novel drug targets.

Novel application of single-cell next-generation sequencing for determination of intratumoral heterogeneity of canine osteosarcoma cell lines.

Osteosarcoma (OSA) is a highly aggressive and metastatic neoplasm of both the canine and human patient and is the leading form of osseous neoplasia in both species worldwide. To gain deeper insight into the heterogeneous and genetically chaotic nature of OSA, we applied single-cell transcriptome (scRNA-seq) analysis to 4 canine OSA cell lines. This novel application of scRNA-seq technology to the canine genome required uploading the CanFam3.1 reference genome into an analysis pipeline (10X Genomics Cell Ranger); this methodology has not been reported previously in the canine species, to our knowledge. The scRNA-seq outputs were validated by comparing them to cDNA expression from reverse-transcription PCR (RT-PCR) and Sanger sequencing bulk analysis of 4 canine OSA cell lines (COS31, DOUG, POS, and HMPOS) for 11 genes implicated in the pathogenesis of canine OSA. The scRNA-seq outputs revealed the significant heterogeneity of gene transcription expression patterns within the cell lines investigated (COS31 and DOUG). The scRNA-seq data showed 10 distinct clusters of similarly shared transcriptomic expression patterns in COS31; 12 clusters were identified in DOUG. In addition, cRNA-seq analysis provided data for integration into the Qiagen Ingenuity Pathway Analysis software for canonical pathway analysis. Of the 81 distinct pathways identified within the clusters, 33 had been implicated in the pathogenesis of OSA, of which 18 had not been reported previously in canine OSA.

Pancreatic circulating tumor cell detection by targeted single-cell next-generation sequencing.

Single-cell next-generation sequencing (scNGS) technology has been widely used in genomic profiling, which relies on whole-genome amplification (WGA). However, WGA introduces errors and is especially less accurate when applied to single nucleotide variant (SNV) analysis. Targeted scNGS for SNV without WGA has not been described. We aimed to develop a method to detect circulating tumor cells (CTCs) with DNA SNVs. We tested this targeted scNGS method with three driver mutant genes (KRAS/TP53/SMAD4) on one pancreatic cancer cell line AsPC-1 and then applied it to patients with metastatic PDAC for the validation. All single-cell of AsPC-1 and spiked-in AsPC-1cells in healthy donor blood, which were isolated by the filtration with size or by flow cytometry, were detected by targeted scNGS method. All blood samples from six patients with metastatic PDAC, for the validation of target scNGS method, showed CTCs with SNVs of KRAS/TP53/SMAD4 and the positive confirmation of immunofluorescent stainings with Pan-CK/Vimentin/CD45. Four patients with early stage disease, one patient with benign pancreatic cyst and a healthy control sample all showed concordant results between targeted scNGS and CTC enumeration. The novel technique of targeted scNGS for SNV analysis, without pre-amplification, is a promising method for identifying and characterizing circulating tumor cells.

Comparing Phylogenetic Approaches to Reconstructing Cell Lineage From Microsatellites With Missing Data.

Due to the imperfect fidelity of DNA replication, somatic cells acquire DNA mutations at each division which record their lineage history. Microsatellites, tandem repeats of DNA nucleotide motifs, mutate more frequently than other genomic regions and by observing microsatellite lengths in single cells and implementing suitable inference procedures, the cell lineage tree of an organism can be reconstructed. Due to recent advances in single cell Next Generation Sequencing (NGS) and the phylogenetic methods used to infer lineage trees, this work investigates which computational approaches best exploit the lineage information found in single cell NGS data. We simulated trees representing cell division with mutating microsatellites, and tested a range of available phylogenetic algorithms to reconstruct cell lineage. We found that distance-based approaches are fast and accurate with fully observed data. However, Maximum Parsimony and the computationally intensive probabilistic methods are more robust to missing data and therefore better suited to reconstructing cell lineage from NGS datasets. We also investigated how robust reconstruction algorithms are to different tree topologies and mutation generation models. Our results show that the flexibility of Maximum Parsimony and the probabilistic approaches mean they can be adapted to allow good reconstruction across a range of biologically relevant scenarios.

High-Throughput Mapping of B Cell Receptor Sequences to Antigen Specificity

B cell receptor (BCR) sequencing is a powerful tool for interrogating immune responses to infection and vaccination, but it provides limited information about the antigen specificity of the sequenced BCRs. Here, we present LIBRA-seq (linking B cell receptor to antigen specificity through sequencing), a technology for high-throughput mapping of paired heavy- and light-chain BCR sequences to their cognate antigen specificities. B cells are mixed with a panel of DNA-barcoded antigens so that both the antigen barcode(s) and BCR sequence are recovered via single-cell next-generation sequencing. Using LIBRA-seq, we mapped the antigen specificity of thousands of B cells from two HIV-infected subjects. The predicted specificities were confirmed for a number of HIV- and influenza-specific antibodies, including known and novel broadly neutralizing antibodies. LIBRA-seq will be an integral tool for antibody discovery and vaccine development efforts against a wide range of antigen targets.

Bulk and Single-Cell Next-Generation Sequencing: Individualizing Treatment for Colorectal Cancer.

The increasing incidence combined with constant rates of early diagnosis and mortality of colorectal cancer (CRC) over the past decade worldwide, as well as minor overall survival improvements in the industrialized world, suggest the need to shift from conventional research and clinical practice to the innovative development of screening, predictive and therapeutic tools. Explosive integration of next-generation sequencing (NGS) systems into basic, translational and, more recently, basket trials is transforming biomedical and cancer research, aiming for substantial clinical implementation as well. Shifting from inter-patient tumor variability to the precise characterization of intra-tumor genetic, genomic and transcriptional heterogeneity (ITH) via multi-regional bulk tissue NGS and emerging single-cell transcriptomics, coupled with NGS of circulating cell-free DNA (cfDNA), unravels novel strategies for therapeutic response prediction and drug development. Remarkably, underway and future genomic/transcriptomic studies and trials exploring spatiotemporal clonal evolution represent most rational expectations to discover novel prognostic, predictive and therapeutic tools. This review describes latest advancements and future perspectives of integrated sequencing systems for genome and transcriptome exploration to overcome unmet research and clinical challenges towards Precision Oncology.

Single-cell analysis to understand the diversity of immune cell types that drive disease pathogenesis

Single-cell next-generation sequencing assays are powerful tools to understand the nature of the immune cells that drive disease pathogenesis. In this brief review we explain the value of performing assays at single-cell resolution to better understand the pathogenesis of allergy, asthma, and other lung diseases. We explain the challenges in performing single-cell studies of airways and lung samples from patients with lung diseases. Amajor limitation comes from the amount of diseased tissue that can be used for research purposes. Finally, we discuss which sequencing strategies can be used to successfully investigate airway and lung diseases at single-cell resolution.

7. GENETIC TESTING FOR COPY NUMBER VARIATIONS IN FIRST POLAR BODIES AND OOCYTES BY SINGLE-CELL NEXT-GENERATION SEQUENCING

Introduction Female meiotic errors are the main cause of whole chromosomal aneuploidy in human embryos and significantly contribute to early embryo loss. Meiotic chromosomal malsegregation occurs during divisions of the maturing oocyte in oogenesis concurrently with extrusion of two polar bodies: polar body first (PB1) and polar body second (PB2). Based on meiosis mechanism, genome of a single oocyte can be deduced by analyzing its sibling polar bodies. PB genetic testing can identify abnormalities of maternal meiotic origin and may be the only form of preimplantation genetic testing for aneuploidies (PGT-A) accepted by patients who object embryo biopsy for ideological reasons. In the majority of previous studies, array comparative genomic hybridization (aCGH) was a method of choice for comprehensive chromosome testing in polar bodies. Here, we test the use of single-cell next-generation sequencing (NGS) method in polar body testing for detecting copy number variations (CNVs) in PB1 genome and validate methods for whole genome amplification (WGA) of PB1. Material and methods In this study, single-cell NGS technology was used to asses ploidy status of oocytes and their sibling PB1. A total of 120 single cells (60 first polar bodies and 60 oocytes) were collected from in vitro fertilization (IVF) couples and subjected for WGA using four different kits based on three distinct amplification systems: (i) polymerase chain reaction (PCR-based WGA), (ii) multiple displacement amplification (MDA) or (iii) multiple annealing and looping-based amplification cycles (MALBAC). WGA products were processed and analyzed with VeriSeq PGS MiSeq kit on MiSeq sequencing platform (Illumina) and random samples were validated with the aCGH method. Amplification uniformity and accuracy for CNV detection of the four tested kits were evaluated. Results Ploidy status was determined for 112 of 120 (93,3%) samples (84/112 based on direct analysis and 28/112 based on indirect analysis of the well-amplified sibling PB1 or oocyte). Estimated aneuploidy rate for the studied group which resembles the total oocyte abnormality resulting from meiosis I errors rate was 33% (37/112 samples). In the group of well-amplified PB1-oocyte pairs (33/60) a 97% concordance between the chromosomal status of PB1 and the corresponding oocyte was observed. Both whole chromosome nondisjunction (6 of 37 aneuploid samples) and abnormal chromatid pre-division and segregation were detected (31 of 37 aneuploid samples). The result is concordant with previous studies - abnormal chromatid segregation was the dominant aneuploidy-causing mechanism. Differences in WGA kits performance including amplification uniformity, aneuploidy calling potential and a number of interpretable NGS results were evaluated and the most optimal kit for PB1 genome WGA was pre-selected. Results from aCGH validation of the randomly selected samples showed full consistency with the NGS results. Conclusions The NGS-based method used for PB1 genome analysis showed a high predictive potential of PB1 in deducing ploidy status of the corresponding oocyte and is a promising method for PGT-A of oocytes. The study also contributes to a better understanding of the chromosome segregation patterns and maternal meiosis errors. Supported by: POIR.02.03.02-14- 0092/17

The Impact of Heterogeneity on Single-Cell Sequencing.

The importance of diversity and cellular specialization is clear for many reasons, from population-level diversification, to improved resiliency to unforeseen stresses, to unique functions within metazoan organisms during development and differentiation. However, the level of cellular heterogeneity is just now becoming clear through the integration of genome-wide analyses and more cost effective Next Generation Sequencing (NGS). With easy access to single-cell NGS (scNGS), new opportunities exist to examine different levels of gene expression and somatic mutational heterogeneity, but these assays can generate yottabyte scale data. Here, we model the importance of heterogeneity for large-scale analysis of scNGS data, with a focus on the utilization in oncology and other diseases, providing a guide to aid in sample size and experimental design.

PO-336 ThruPLEX® and PicoPLEX® technologies for rare alleles and copy number variation detection from cell-free DNA and single human cancer cells

IntroductionLiquid biopsies provide a non-invasive method to acquire the genetic information provided in cell-free DNA (cfDNA) as well as in single circulating tumour cells. Access to this genetic information through next-generation sequencing (NGS) identifies mutations and alterations such as Copy Number Variation (CNV) that play a role in cancer and other diseases.Material and methodsThe key to identifying rare mutations is improved sequencing accuracy and the ability to distinguish between biological and PCR duplicates. ThruPLEX Tag-seq was developed with the addition of unique molecular tags (UMTs) to improve sequencing accuracy by accounting for polymerase and sequencing errors and to increase confidence in rare allele identification. Whole Genome Amplification (WGA) for CNV detection was achieved by the thermal cycling quasi-random primed library chemistry of the PicoPLEX DNA-seq single-cell NGS library prep kit.Results and discussionsThruPLEX Tag-seq libraries were prepared using 10–30 ng of Horizon Discovery’s Multiplex I cfDNA Reference Standard Set containing six single nucleotide variants (SNV) for 4 different genes (EGFR, KRAS, NRAS, PIK3CA) present at 0.5%–5% allele frequency. The libraries were enriched with either a 110 kb or 240 kb custom panel or the Agilent ClearSeq Comprehensive Cancer Panel. Enriched libraries were sequenced witan average total read coverage of approximately 5,000X and analysed with and without the UMTs.For CNV analysis in single cells, a bar-coded PicoPLEX DNA-seq library was synthesised and amplified from 6 single cells from either PBMCs and clonally-expanded PC3 prostate cancer cells. Sequencing was performed on a MiSeq v2 and reads were mapped using BWA-MEM, processed in Picard_Mark_Duplicates, and further characterised in DNA nexus.classic. All PC3 cells showed reproducible CNV calling, however none of the lymphocyte samples showed any CNVs. Accurate CNV calls for PC3 cells were achieved even at when fastq files were randomly downsampled to 1 50 000 read pairs.ConclusionTherefore, use of UMTs in the preparation of NGS libraries from cfDNA enhances sequencing accuracy: by distinguishing between biological duplicates and PCR duplicates, increasing read coverage and decreasing background noise, reducing false positives, and in more confident mutation calls. PicoPLEX DNA-seq NGS libraries have a very simple and fast workflow that is suitable reproducible CNV detection in single cells even at low 0.002X average coverage.

Catch and Release: rare cell analysis from a functionalised medical wire

Enumeration and especially molecular characterization of circulating tumour cells (CTCs) holds great promise for cancer management. We tested a modified type of an in vivo enrichment device (Catch&Release) for its ability to bind and detach cancer cells for the purpose of single-cell molecular downstream analysis in vitro. The evaluation showed that single–cell analysis using array comparative genome hybridization (array-CGH) and next generation sequencing (NGS) is feasible. We found array-CGH to be less noisy when whole genome amplification (WGA) was performed with Ampli1 as compared to GenomePlex (DLRS values 0.65 vs. 1.39). Moreover, Ampli1-processed cells allowed detection of smaller aberrations (median 14.0 vs. 49.9 Mb). Single-cell NGS data obtained from Ampli1-processed samples showed the expected non-synonymous mutations (deletion/SNP) according to bulk DNA. We conclude that clinical application of this refined in vivo enrichment device allows CTC enumeration and characterization, thus, representing a promising tool for personalized medicine.