Unique Molecular Index Research Articles

Cell-Free DNA Variant Sequencing Using CTC-Depleted Blood for Comprehensive Liquid Biopsy Testing in Metastatic Breast Cancer.

Liquid biopsy analytes such as cell-free DNA (cfDNA) and circulating tumor cells (CTCs) exhibit great potential for personalized treatment. Since cfDNA and CTCs are considered to give additive information and blood specimens are limited, isolation of cfDNA and CTC in an “all from one tube” format is desired. We investigated whether cfDNA variant sequencing from CTC-depleted blood (CTC-depl. B; obtained after positive immunomagnetic isolation of CTCs (AdnaTest EMT-2/Stem Cell Select, QIAGEN)) impacts the results compared to cfDNA variant sequencing from matched whole blood (WB). Cell-free DNA was isolated using matched WB and CTC-depl. B from 17 hormone receptor positive/human epidermal growth factor receptor 2 negative (HR+/HER2−) metastatic breast cancer patients (QIAamp MinElute ccfDNA Kit, QIAGEN). Cell-free DNA libraries were constructed (customized QIAseq Targeted DNA Panel for Illumina, QIAGEN) with integrated unique molecular indices. Sequencing (on the NextSeq 550 platform, Illumina) and data analysis (Ingenuity Variant Analysis) were performed. RNA expression in CTCs was analyzed by multimarker quantitative PCR. Cell-free DNA concentration and size distribution in the matched plasma samples were not significantly different. Seventy percent of all variants were identical in matched WB and CTC-depl. B, but 115/125 variants were exclusively found in WB/CTC-depl. B. The number of detected variants per patient and the number of exclusively detected variants per patient in only one cfDNA source did not differ between the two matched cfDNA sources. Even the characteristics of the exclusively detected cfDNA variants in either WB or CTC-depl. B were comparable. Thus, cfDNA variants from matched WB and CTC-depl. B exhibited no relevant differences, and parallel isolation of cfDNA and CTCs from only 10 mL of blood in an “all from one tube” format was feasible. Matched cfDNA mutational and CTC transcriptional analyses might empower a comprehensive liquid biopsy analysis to enhance the identification of actionable targets for individual therapy strategies.

A Universal Analysis Pipeline of Hybrid Capture-Based Targeted Sequencing Data with Unique Molecular Indexes (UMIs).

Hybrid capture-based targeted sequencing is being used increasingly for genomic variant profiling in tumor patients. Unique molecular index (UMI) technology has recently been developed and helps to increase the accuracy of variant calling by minimizing polymerase chain reaction biases and sequencing errors. However, UMI-adopted targeted sequencing data analysis is slightly different from the methods for other types of omics data, and its pipeline for variant calling is still being optimized in various study groups for their own purposes. Due to this provincial usage of tools, our group built an analysis pipeline for global application to many studies of targeted sequencing generated with different methods. First, we generated hybrid capture-based data using genomic DNA extracted from tumor tissues of colorectal cancer patients. Sequencing libraries were prepared and pooled together, and an 8-plexed capture library was processed to the enrichment step before 150-bp paired-end sequencing with Illumina HiSeq series. For the analysis, we evaluated several published tools. We focused mainly on the compatibility of the input and output of each tool. Finally, our laboratory built an analysis pipeline specialized for UMI-adopted data. Through this pipeline, we were able to estimate even on-target rates and filtered consensus reads for more accurate variant calling. These results suggest the potential of our analysis pipeline in the precise examination of the quality and efficiency of conducted experiments.

Detecting Complex Mutations in Myeloid Leukemia Using the GeneReader NGS System and QIAact Myeloid DNA UMI Panel

IntroductionSomatic mutations acquired in key signalling pathway, transcription factor, spliceosome, epigenetic and tumor suppressor genes are of central importance in the development and progression of myeloid malignancies including myeloproliferative neoplasms (MPN), myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). To date, in order to evaluate all relevant genetic alterations, multiple tests are needed, requiring large amounts of DNA. As tests are typically performed sequentially this unnecessarily extends the time between sample acquisition and mutation detection.The QIAact Myeloid DNA UMI Panel in combination with the QIAGEN GeneReader NGS System provides a single solution to simultaneously test for actionable mutations, whilst also saving sample material (only 40ng DNA input required per sample), shortening test time and enabling simplification of lab operations.The QIAact Myeloid DNA UMI Panel is a multi-gene targeted sequencing panel designed to detect complex mutations throughout the most informative genes linked to myeloid disease. This allows reliable and sensitive detection of single nucleotide variants (SNV) and large Insertion/Deletion (InDel) mutations.MethodsThe QIAact Myeloid DNA UMI Panel targets 25 genes known to be important in myeloid leukemia. A key feature of the panel is the addition of a unique molecular index (UMI) to tag each individual original DNA molecule prior to target enrichment by PCR. UMIs enable sequencing and PCR bias corrections, allowing sensitive detection of mutations.To assess the assay performance, reference standards and blood and bone marrow samples were used. Following target enrichment, libraries were sequenced on the GeneReader NGS System and mutations analyzed using the QIAGEN Clinical Insight (QCI) Analyze software suite.ResultsTo confirm DNA mutation detection, Horizon Discovery and SeraCare Reference Standards containing variants typical of myeloid malignancies were used. The anticipated DNA mutations were consistently identified both within and between runs.The samples used, including blood and bone marrow samples, demonstrated the ability of the assay to detect important large indels (52 bp deletion CALR type 1 variant) and key SNVs down to a minor allele fraction (MAF) of 1% for JAK2 (e.g. exon 12, 13, 14 & 15) and KIT (exon 8, 9, 10, 11 & 17). A sensitive variant detection of allele frequency <0.5% for the KIT D816V was also achieved. For the other genes covered by the panel, including ASXL1, RUNX1, NPM1, DNMT3A, IDH1/2, results show sufficiently uniform amplification and sequencing coverage to support mutation detection with a MAF of 5%.ConclusionThe QIAact Myeloid DNA UMI Panel in combination with the QIAGEN GeneReader NGS System offer a fully integrated DNA to variant detection and interpretation solution. The optimized chemistry allows superior analytical sensitivity resulting in accurate and efficient mutation detection of highly relevant genetic alterations for myeloid malignancy research. DisclosuresLaloux:QIAGEN France S.A.S: Employment. Biglia:HalioDx: Employment. Bona:HalioDx: Employment. Lafi:HalioDx: Employment. Charifi:HalioDx: Employment. Larsen:QIAGEN Aarhus: Employment. Lueerssen:QIAGEN Manchester Ltd: Employment. Gupta:QIAGEN Aarhus: Employment. Lauber:QIAGEN GmbH: Employment. Hughes:QIAGEN Manchester Ltd: Employment.

Single Cell RNA Sequencing and V(D)J Profiling of T-Cell Large Granular Lymphocytosis

Introduction. T-cell large granular lymphocytosis (T-LGL) is a low grade lymphoproliferative disorder, often clinically manifest as bone marrow failure. Treatment with immunosuppressive therapies is effective, but the dominant clone may persist even in responding patients. The pathogenesis of T-LGL has not been fully elucidated. In this study, we performed single cell RNA sequencing (sc-RNA seq) and V(D)J profiling to discern clonotypes and gene expression patterns of T lymphocytes from T-LGL patients who were sampled before and after treatment.Methods. Blood was obtained from patients participating in a phase 2 protocol of alemtuzumab as second line therapy (NCT00345345; Dumitriu B et al, Lancet Haematol 2016). Leukapheresis was performed in 13 patients (M/F 7/6; median age 51 years, range 26-85) before and after 3-6 months alemtuzumab administration and in 7 age-matched healthy donors. Cryopreserved blood was enriched for T cells with the EasySep Human T cell Isolation Kit (Stem cell). sc-RNA seq was performed on the 10XGenomics Chromium Single Cell V(D)J + 5' Gene Expression platform, and sequencing obtained on the HiSeq3000 Platform. Barcode assignment, alignment, unique molecular index counting and T cell receptor sequence assembly were performed using Cell Ranger 2.1.1.Results. Four hundred fifty thousand cells from 13 patients and 107,000 cells from 7 healthy donors were profiled. We measured productive TCR chains (which fully span the V and J regions, with a recognizable start codon in the V region and lacking a stop codon in the V-J region, thus potentially generating a protein). We detected at least one productive TCR α-chain in 50%, one productive TCR β-chain in 69% and paired productive αβ-chains in 47% of all cells. There was loss of TCR repertoire diversity in patients which was quantified by Simpson's diversity index; most patients showed oligoclonal or, less frequently, monoclonal expansion of the TCR repertoire (Fig. A). Regardless of clinical response, alemtuzumab treatment did not correct the low TCR repertoire diversity. TCR repertoires can be classified as “public”, when they express identical TCR sequences across multiple individuals, or “private”, when each individual displays distinct TCR clonotypes. No TCRA or TCRB CDR3 homology among patients was observed: most TCR clonotypes appeared to be private. Our data suggests that T-LGL is etiologically heterogenous disease, consistent with T cell expansion in response to a variety antigens, in diverse HLA contexts, or randomly. Despite differences of TCR among patients and healthy donors, and the presence of large clones in patients, distribution of TCR diversity followed the power law distribution in healthy donors and patients (Fig. B, showing the negative linear relationship between logarithmic expression of clone frequency and clone size). The observed distribution is consistent with a somatic evolution model, in which cell fitness depends on cellular receptor response to specific antigens and stimulation of cells by cytokine and other signals from the environment; fitted clones have higher birth-death ratios and thus expand (Desponds J et al, PNAS 2016).CD4 and CD8 T cells can be virtually separated by imputation from their transcriptomes (Fig. C). Comparison of gene expression between patients and healthy donors showed dysregulation of genes involved in pathways related to the immune response and cell apoptosis, consistent with a pathophysiology of T cell clonal expansion. We used diffusion mapping, which localizes datapoints to their eigen components in low-dimesional space, to characterize sources contributing to the gene expression phenotype: the first component was mainly from T cell activation and the second was associated with TCR expression. In LGL the T cell transcriptome appeared to be shaped by both lineage development and TCR rearrangement.Conclusion. We describe at the single cell level T clonal expansion profiles in T-LGL, pre- and post-treatment. Single cell analysis allows accurate recovery of paired α and β chains in the same cell and demonstrates a continuum of cell lineage differentiation. We found a range of differences in transcriptome and TCR repertoires across patients. Transcriptome data, coupled with detailed TCR-based lineage information, provides a rich resource for understanding of the pathology of T-LGL and has implications for prognosis, treatment, and monitoring in the clinic. [Display omitted] DisclosuresYoung:GlaxoSmithKline: Research Funding; CRADA with Novartis: Research Funding; National Institute of Health: Research Funding.

Abstract 2222: Using rare variants to characterize lung cancer risk

Abstract The human genome is exposed to a variety of exogenous and endogenous assaults capable of inducing DNA damage and contributing to diseases like cancer. Multiple DNA repair mechanisms are tasked with identifying and repairing these aberrant nucleotides, but damage is occasionally missed giving rise to somatic mutations. As we age, the relative abundance of somatic mutations increases, which may increase our risk for developing cancer. In addition, inter-individual variation in somatic mutation prevalence suggests an inter-individual variation in (a) inherited DNA repair capacity and/or (b) exposure to environmental mutagens. Therefore, somatic mutation prevalence may serve as an end-point biomarker for cancer risk, as it provides critical information regarding both. While Next Generation Sequencing (NGS) has provided unparalleled access to the human genome and revolutionized the field of cancer genomics, its implementation into the clinical setting has been limited by technical errors introduced during library preparation and on the sequencing platform. This makes identification of rare variants below 10-4 mutations per nucleotide through NGS a challenge, and the use of somatic mutations to characterize cancer risk unfeasible. To address this issue, unique molecular indexes (UMI) were assigned to each genomic copy, enabling reliable identification of rare somatic mutations versus technical errors. We hypothesize that measurement of somatic mutation prevalence in normal bronchial epithelial cells (NBEC) will serve as an end-point biomarker for lung cancer risk by identifying both (a) inherited sub-optimal DNA repair/protection and (b) exposure to inhaled environmental mutagens including components of cigarette smoke, radon, and/or occupational hazards. In our initial pilot study, we used genomic DNA derived from an A549 cell line to optimize an ERCC5 gene-specific, dual-indexed PCR method for UMI assignment, followed by sequencing on the Illumina MiSeq platform. In parallel analyses, UMI correction using 25,000 genomic copies provided over 10-fold greater sensitivity in identifying somatic mutations compared to no UMI correction. Based on this pilot, we obtained three clinical NBEC specimens via cytology brush biopsy of grossly normal (non-cancerous) airway from (a) heavy smoker with lung cancer, (b) heavy smoker without lung cancer, and (c) non-smoking control. UMIs were assigned to 50,000 genomic copies at 16 loci, increasing our theoretical limit of detection to approximately 1 in 4x107 nucleotides. Results thus far support further application of this approach in studies to assess NBEC somatic mutation prevalence as a biomarker for cancer risk. Citation Format: Daniel J. Craig, Mazzin Elsamaloty, Thomas M. Blomquist, Erin L. Crawford, James C. Willey. Using rare variants to characterize lung cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2222.

Abstract 3407: A high performance target-enrichment strategy for liquid biopsy

Abstract For abroad application of liquid biopsy in routine clinical settings, it is essential to use a high performance target-enrichment technique that able to detect all major classes of mutations including single nucleotide variants (SNVs), insertion/deletions (InDels), copy number alternations (CNVs) and rearrangements with affordable costs. The regular enrichment strategies employ unique molecular index (UMI) to suppress sequencing error are limited by several factors for their widespread adoption in clinical application. As an instance for hybridization based methods, Cancer Personalized Profiling by deep Sequencing (CAPP-SEQ) is expensive due to low on target rate. Oncomine, as an example for multiple PCR based technique, is unable to detect DNA rearrangements. Herein, we propose a novel target-enrichment strategy based on the innovated sequencing platform BGISEQ-500. The probes used here are blocked by ddNTPs at 3' end which suit for pyrophosphorolysis-activated polymerization. Modified probes in 3' end consist of complementary sequences targeting SNVs, InDel's hotspots, frequently rearranged intron regions, and a sequencing platform-specific tail in 5' end. In a multi-cycle hybridization and copy procedure with prepared library for enrichment, probes work in two roles: hybridization baits and primers for successively extension; while in Post-PCR, they act as universal PCR sequence to produce sequencing library. Since each molecule containing target locus as well as forward UMI adapters will be captured and copied, we could distinguish the origin of each reads by pull-down probes among huge sequencing data, and select probes with high performance to construct clinical NGS panels. Meanwhile, intermediate and final products from the capture process will be gathered for quality control to evaluate the annealing efficiency and on-target ratio. QPCR primers for EGFR and KRAS are included in the panel to represent areas with normal/low GC content. The collected data were useful to monitor the loss of molecules during hybridization and provide key information for further improvement of the panel. For a customized sequencing panel of non-small-cell lung carcinoma (NSCLC) with sequencing regions about 30k, the sequencing results showed overall very high percentage of reads on target (&amp;gt;95%) and very high data utilization rate (&amp;gt;75%). With 40ng DNA used as input for library generation and 4 Gbyte data size, we can achieve 8000X de-duplicate sequence depth, of which 5000X is error corrected depth, thereby ensure the stable detection of mutation with frequency as low as 0.1%. We believe this novel capture and analysis technique is also applicable to other capture-based sequencing product and will achieve similar performance. Cancer patients, especially NSCLC will benefit from this new sequencing technique. Citation Format: Jilong Liu, Yan Song, Lei Liu, Meihua Tan, Han Liu, Jingjing Wang, Mingzhi Ye. A high performance target-enrichment strategy for liquid biopsy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3407.

Abstract 4582: Capturing T cell receptor clones from circulating free DNA in cancer patients with solid malignancies

Abstract Introduction Understanding the tumor microenvironment is challenging in situations where a tumor biopsy is unavailable. In these situations, liquid biopsies provide a less invasive alternative that can be collected at multiple timepoints throughout treatment. In particular, analyses of circulating free DNA (cfDNA) from plasma samples can distinguish genomic alterations from shed tumor DNA (ctDNA) within the cfDNA population. In this study, we aim to better understand the origin of cfDNA as well as its potential in understanding the intratumoral immune infiltration by developing and validating a strategy for identifying T cell receptor β (TCR β) rearrangements in the cfDNA from patients with solid malignancies. Methods We devised a target enrichment approach for high-throughput DNA sequencing that employs a hybridization capture strategy to bait germline variable (V) and joining (J) gene sequences in the TCR β loci. The target sequences are proximal to rearrangement sites flanking the CDR3, the principal site of contact for recognition specificity with foreign antigens presented by the major histocompatibility complex (MHC). We controlled for amplification bias by tagging DNA fragments with unique molecular indices (UMI). We validated our approach on dilutions of T cell lines in non-T cell lines, compared T cell levels determined from our method to those derived from flow cytometry, and compared data complexity at DNA input levels from 100 ng to 2 ng. Finally, we analyzed 27 pre-treatment plasma samples from cancer patients with solid malignanices, including quantification of total cfDNA concentrations, analyzing somatic genomic alterations using whole exome sequencing (WES), and employing our method for capture of TCR β rearrangements. Results Results indicate we are able to capture T cell rearrangements from cfDNA in cancer patient plasma. T cell rearrangements were identified in more than 25% of samples (7/27). Interestingly, the total cfDNA levels were not correlated to the number of T cell rearrangements detected, but all samples with detectable somatic alterations in the cfDNA (3/27) were also those with T cells identified. These preliminary results suggest a connection between apoptosis of lymphocytes and solid tumors that shed DNA into the bloodstream, and demonstrate potential utility as liquid biopsy for identifying tumor infiltrating lymphocytes. Citation Format: Lara McGrath, Elizabeth Maloney, Daniel Stetson, Tristan J. Lubinski, Rory Kirchner, Brian Dougherty, J. Carl Barrett. Capturing T cell receptor clones from circulating free DNA in cancer patients with solid malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4582.

Oligo-conjugated antibodies (Ab-seq) and massively parallel single cell sequencing reveal the high parameter correlation of protein and mRNA expression in individual immune cells.

Abstract Single-Cell mRNA sequencing has enhanced our knowledge of the cell populations found in individual tissues or disease states. However, low correlation between mRNA and protein expression levels hinders our understanding of biology and disease. Traditional single cell protein assays are limited in the number of parameters that can be achieved within one experiment. Here we use oligo-conjugated antibodies (Ab-seq) in combination with massively parallel single cell mRNA sequencing on the BD Rhapsody™ platform to simultaneously measure the protein and mRNA content of individual human blood cells (PBMCs). To accomplish this, a 30+ parameter Ab-seq panel against immune relevant cell surface markers was paired with the BD Rhapsody™ Immune Response panel (a targeted gene expression panel consisting of 399 targets). The Multi-omics data from this single workflow experiment provides a measurement of both gene expression and protein expression. The digital measurements are rendered free of PCR bias through the use of the unique molecular indices (UMIs). Our results show that protein expression detected with Ab-seq is highly sensitive and specific. Protein expression patterns correlate well with results from flow cytometry data on the same samples. Ab-seq allowed the robust detection of expressed genes even when their cognate mRNA transcripts have low abundance. Certain markers cannot be easily distinguished at the mRNA level (i.e. isoforms CD45RA and CD45RO) but are easily distinguished at the protein level. Our study shows successful analysis of protein and mRNA expression data within a single workflow, and should enable the further elucidation single cells within different tissues, developmental time points, and disease states.

Abstract 21182: Single-Cell Sequencing Analysis Reveals Impaired Adipose Tissue Stem Cell Program in Obesity

The properly programmed “stemness” of tissue specific stem cells, including adipose tissue stem cells (ASCs), is the core feature for their function of tissue regeneration. Although ASCs harbor great potential for clinical application, it is poorly understood how ASCs respond to obesity, an affliction now affect over one third of the national population and health risks of cardiovascular diseases. We recently identified a set of cell surface markers to enrich ASCs from murine visceral adipose tissue. We observed that adipose tissue stromal cells bearing CD45 - CD31 - Sca-1 + CD49f - CD34 + were highly enriched for cells with sphere-initiation and multilineage differentiation capacity. Interestingly, the frequency of ASCs was markedly reduced in obese visceral stroma and their capability to derive multilineage progeny were severely impaired, compared to those in lean mice. Given the heterogeneity of isolated ASCs, we performed single cell sequencing analysis to understand mechanisms underlying the impaired “stemness” of obese ASCs. Freshly isolated ASCs from obese or age matched lean mice were subjected to single cell library generation (10X Genomics), followed by high-throughput sequencing. An average of 5500 UMI (unique molecular index) were detected in each cell and a total of 18,835 genes were detected in each sample (mapped to mm10). Interestingly, ASCs isolated from lean or obese adipose tissue displayed distinct pattern after K-mean clustering. Further, functional analysis revealed that critical networks in ASCs are significantly altered under obese conditions, including suppressed adipogenic program initiation and impaired impaired antioxidative defense. Further, multiple signaling networks triggered by both innate and adaptive immune responses displayed high activation Z-score in obese ASCs than that in lean ASCs. Overall, our results suggested that obesity severely impaired ASCs “stemness”, which may be attributed to multiple factors in obese adipose tissue, including the proinflammatory microenvironment. Further analyses of these profiles will provide critical information on how obesity alters the “stemness” program in ASCs and how to “revive” obese ASCs tissue regenerative ability.

Enrichment allows identification of diverse, rare elements in metagenomic resistome-virulome sequencing

BackgroundShotgun metagenomic sequencing is increasingly utilized as a tool to evaluate ecological-level dynamics of antimicrobial resistance and virulence, in conjunction with microbiome analysis. Interest in use of this method for environmental surveillance of antimicrobial resistance and pathogenic microorganisms is also increasing. In published metagenomic datasets, the total of all resistance- and virulence-related sequences accounts for < 1% of all sequenced DNA, leading to limitations in detection of low-abundance resistome-virulome elements. This study describes the extent and composition of the low-abundance portion of the resistome-virulome, using a bait-capture and enrichment system that incorporates unique molecular indices to count DNA molecules and correct for enrichment bias.ResultsThe use of the bait-capture and enrichment system significantly increased on-target sequencing of the resistome-virulome, enabling detection of an additional 1441 gene accessions and revealing a low-abundance portion of the resistome-virulome that was more diverse and compositionally different than that detected by more traditional metagenomic assays. The low-abundance portion of the resistome-virulome also contained resistance genes with public health importance, such as extended-spectrum betalactamases, that were not detected using traditional shotgun metagenomic sequencing. In addition, the use of the bait-capture and enrichment system enabled identification of rare resistance gene haplotypes that were used to discriminate between sample origins.ConclusionsThese results demonstrate that the rare resistome-virulome contains valuable and unique information that can be utilized for both surveillance and population genetic investigations of resistance. Access to the rare resistome-virulome using the bait-capture and enrichment system validated in this study can greatly advance our understanding of microbiome-resistome dynamics.

Novel Technologies to Detect Minimal Residual Disease

The widespread use of ribonucleic acid (RNA) analysis as a measure of minimal residual disease (MRD) in leukemia has primarily been performed via real-time quantitative polymerase chain reaction (PCR) (RQ-PCR) for common translocations, insertions/deletions and duplications (e.g. FLT3-ITD, MLL-PTD). While RQ-PCR for known rearrangements can offer a limit of detection as low as 1:106, these make up a minority of the total leukemia cases. MLL-rearrangements are generally not amenable to RQ-PCR due to the many fusion partners and breakpoints in these translocations. The ability to use quantitative RNA sequencing (RNA-seq) for MRD assessment would enable detection of allele-specific gene expression, alternative splicing and cryptic splice forms in addition to common rearrangements. While a few institutions are performing reflexive genome, transcription and methylome sequencing for cancer patients, standard RNA-seq library preparation is relatively low efficiency, which causes loss of rare transcripts1 required for meaningful MRD assessment. Three methods currently employed to overcome this inherent bias in RNA-seq are targeted RNA sequencing of cancer-related genes to reduce off target, non-specific sequencing which improves read depth and mutation detection2; single cell transcriptomes to obtain a digital readout of gene expression in single cells rather than a population-based average; and the addition of unique molecular indexes (UMI) to normalize amplification bias and obtain digital quantitation of transcripts in populations of cells. None of these methods have been carefully studied for their applicability to diagnostic testing, but single cell transcriptome profiling has been applied to solid tumor biology3,4. In this presentation, we explore whether digital RNA-seq can serve as a viable modality for MRD either as a stand-alone method or in conjunction with other methods of genomic profiling or immunophenotyping. While single-cell RNA profiling allows for co-localization of mutations within the same cell and is now capable of surveying hundreds to thousands of cells in a single experiment for reasonable costs, this scale remains far below the throughput necessary for MRD detection of cells present at 1:105. One would need to process tens of thousands of cells and analyze the resulting data to confidently identify any residual leukemia cells, which is not currently feasible in timescales amenable to clinical decision making. We present data from the combination of targeted RNA sequencing of a pan-cancer gene expression array with the addition of UMIs to normalize amplification bias and computationally eliminate errors introduced by the sequencing platform while specifically sequencing cancer-associated genes to high read depths. This enables high-throughput detection of allele and isoform-specific transcripts at frequencies below 1:5,000. This method can be coupled with an equivalent DNA sequencing analysis from the same sample to ascertain the relative expression of leukemia-associated mutant alleles. However, one significant drawback to the addition of UMIs compared to single-cell RNA-seq is that the ability to co-localize mutations is lost. As epigenetic modifiers and targeted agents continue to permeate cancer therapy, these evolving technologies should offer more than direct quantification of residual leukemia cells, but a rich series of data on expression differences in healthy and cancer cells before, during and after therapy.

On a semiclassical interpretation of inter‐ and intramolecular interactions

AbstractThe semiclassical models considered here are composed by charge distributions coming from ab initio quantum‐mechanical calculations on actual molecular systems. These charge distributions interact with one another according to the laws of classical electrostatics. This article describes some results of a systematic examination of the performances of this model in a variety of cases, with the aim of putting in evidence the usefulness and the limits of this inherently approximate representation of chemical interactions. Intermolecular interactions are examined first; the test cases are interactions of neutral molecules with H+, Li+, and C1−, and the formation of H‐bonded complexes. Attention is paid mainly to the energetics of the processes; each interacting molecule is considered as a unique entity and classical molecular reactivity indexes (electrostatic potential V, polarization term P) are introduced to compute the interaction energy, to interpret the details of the interaction process, and then to elaborate on less expensive computational procedures. Intramolecular interactions are considered. Attention is paid to the question of defining chemical groups starting from SCF molecular wavefunctions. The transferability and conservation degree of groups derived from localized orbitals of actual molecules is examined in detail, taking as tests their ability to reproduce charge distribution, one‐electron observables, and energy. The effect of classical fields on these groups is then examined, taking into consideration external fields originated either by a point charge or by a solvent, and internal fields deriving from substitution of chemical groups. The intergroup analysis is then extended to the case of bimolecular reaction acts by considering the whole system as a supermolecule. Approximate computational procedures able to reproduce the main features of these interactions are proposed and tested. All through the article the performances of the classical models are compared with ab initio SCF calculations (mainly of low or intermediate quality).