Single-cell Genomic Analysis Research Articles

Exome Sequencing Starting from Single Cells.

Single-cell genomic analysis enables researchers to gain novel insights across diverse research areas, including developmental biology, tumor heterogeneity, and disease pathogenesis. Conducting single-cell genomic analysis using next-generation sequencing (NGS) methods has traditionally been challenging as the amount of genomic DNA present in a single cell is limited. Advancements in multiple displacement amplification (MDA) technologies allow the unbiased amplification of limited quantities of DNA under conditions that maintain its integrity. This method of amplification results in high yield and facilitates the generation of high-complexity NGS libraries that ensure the highest coverage to effectively allow variant calling. With the introduction of new sequencing platforms and chemistry, whole genome sequencing became a more cost-effective application, but enrichment of specific regions of interest further reduces the amount of required sequencing output and associated costs. There are two enrichment methods, polymerase chain reaction (PCR)-based and hybrid-capture-based methods. PCR-based methods are very flexible and highly effective but focus on specific loci, typically known to be associated with disease. Inherited diseases of unknown genetic origin require a more comprehensive approach to capture the genetic variation that is not yet associated with a specific disease. Hybrid capture enrichment methods require considerable amounts of DNA such that exome enrichment from single cells is only possible after preamplification of this limited material. This article describes the complete workflow from single cells and small quantities of DNA to exome-NGS libraries for Illumina sequencing instruments and includes the following protocols: © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Whole genome amplification from single cells or small amounts of gDNA Basic Protocol 2: NGS library generation of MDA-amplified material Basic Protocol 3: Exome enrichment.

Integrated analysis of single-cell RNA sequencing and bulk RNA data reveals gene regulatory networks and targets in dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is a common cause of heart failure, thromboembolism, arrhythmias, and sudden cardiac death. The quality of life and long-term survival rates of patients with dilated DCM have greatly improved in recent decades. Nevertheless, the clinical prognosis for DCM patients remains unfavorable. The primary driving factors underlying the pathogenesis of DCM remain incompletely understood. The present study aimed to identify driving factors underlying the pathogenesis of DCM from the perspective of gene regulatory networks. Single-cell RNA sequencing data and bulk RNA data were obtained from the Gene Expression Omnibus (GEO) database. Differential gene analysis, single-cell genomics analysis, and functional enrichment analysis were conducted using R software. The construction of Gene Regulatory Networks was performed using Python. We used the pySCENIC method to analyze the single-cell data and identified 401 regulons. Through variance decomposition, we selected 19 regulons that showed significant responsiveness to DCM. Next, we employed the ssGSEA method to assess regulons in two bulk RNA datasets. Significant statistical differences were observed in 9 and 13 regulons in each dataset. By intersecting these differentiated regulons and identifying shared targets that appeared at least twice, we successfully pinpointed three differentially expressed targets across both datasets. In this study, we assessed and identified 19 gene regulatory networks that were responsive to the disease. Furthermore, we validated these networks using two bulk RNA datasets of DCM. The elucidation of dysregulated regulons and targets (CDKN1A, SAT1, ZFP36) enhances the molecular understanding of DCM, aiding in the development of tailored therapies for patients.

Abstract PO5-04-04: Development of a method to detect very low levels of HER2 expression in Circulating Tumor Cells (CTCs) by liquid biopsy in patients with metastatic breast cancer

Abstract Introduction Blood-based liquid biopsies are a non-invasive diagnostic approach for detecting circulating tumor cells (CTCs) or circulating tumor DNA (ctDNA) that may provide clinically actionable information for treatment decisions for metastatic breast cancer (MBC) patients when a conventional tissue biopsy is not feasible. Recently, the novel anti-HER2 antibody-drug conjugate, Trastuzumab Deruxtecan (T-DXd), has shown effectiveness against MBC with low HER2 expression detected by tissue biopsy characterized as HER2-low (immunohistochemically 1+ or 2+ and ERBB2 amplification-negative via in situ hybridization) and is being explored in an ultra-low population. Here we report on the application of a liquid biopsy platform designed to sensitively detect low levels of HER2 protein expression in CTCs from MBC patients. Methods Blood samples from 704 metastatic breast cancer patients as well as control cells lines were collected for cell-based and cell-free DNA analysis. After plasma isolation, nucleated cells deposited on glass slides went through immunofluorescent staining and imaging. CTCs were identified using Epic Sciences’ digital imaging and machine learning algorithms, and a subset of CTCs were isolated and sequenced for genomic quantification of large scale-state transitions (LSTs) as well as copy number variants (CNVs). The HER2 status was based upon on ASCO-CAP guidelines and the previous tissue biopsy results from the ordering healthcare provider, as documented on the DefineMBC™ test requisition form. Results Within a DefineMBC early-access program (EAP), 93% of patients with MBC had detectable CTCs. Among ERBB2-non-amp patients tested with the DefineMBC assay, 25% of patients with MBC had findings that were reported as consistent with HER2-low in the CAP-CLIA setting. To explore the lower boundaries of HER2 protein expression, we created and validated an MCF-7 HER2-negative ERBB2 knock-out cell line and utilized its 95% confidence level threshold (271 MFI) as a negative fluorescence cutoff for very low HER2 expression. Based upon publicly available CCLE datasets, MDA-MB-453, MCF7, and MCF7 ERBB2 KO breast cancer cell lines were selected for their high and low HER2 RNA expression levels and were corroborated via observed HER2 immunofluorescence median levels of 15740, 381, and 188 MFI respectively. In an exploratory analysis, among ERBB2-non-amp patients, we retrospectively applied the 271 MFI HER2 cutoff to the EAP cohort and identified 38% of patients with very low HER2 expression. We examined the impact of the HER2 ultra-low cutoff in patients not eligible for T-DXd treatment. Among patients reported as IHC=0 or with unknown IHC status from the most recent tissue biopsy, 44% and 42%, respectively, may qualify for treatment with T-DXd. Conclusion Using our higher sensitivity assay that combines CTC immunofluorescence and single-cell genomic analysis, we examined the lower boundary of HER2 protein expression. Feasibility data support further characterization of a very low HER2 expression phenotype, for the eventual inclusion into our comprehensive cancer profiling solution. To date, studies with biomarker expression have been limited to tissue biopsy, which may not always yield contemporaneous sampling in the metastatic setting. These results offer a liquid biopsy test that might identify patients potentially responsive to HER2-directed therapies. Citation Format: Giuseppe Di Caro, David Bourdon, Andrew Kunihiro, Alessandra Cunsolo, Ernest Lam, Megan Slade, Martin Blankfard, Lee Schwartzberg. Development of a method to detect very low levels of HER2 expression in Circulating Tumor Cells (CTCs) by liquid biopsy in patients with metastatic 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 PO5-04-04.

Abstract PO4-06-12: Distinction of basal-like and triple-negative basal-like breast cancers utilizing a novel comprehensive single-cell liquid biopsy-based test

Abstract Introduction: Breast cancer is a highly heterogeneous disease and is a leading cause of death for women worldwide. Triple-negative breast cancer (TNBC), the most aggressive form of the disease, is clinically defined by the lack of expression of estrogen receptor (ER) and progesterone receptor (PR), as well as lack of over-expression of human epidermal growth factor receptor-2 (HER2). Approximately 70% of all TNBC cases exhibit basal-like cells, characterized by high basal expression of keratins as well as extensive genomic instability with copy number gains and losses across most chromosomes. In this study we show that novel single cell genomic evaluation coupled with immunofluorescence (IF) protein analysis of CTCs can detect TNBC with basal-like genomic features as well as basal-like tumors with expression of ER and HER2. Materials and Methods: Epic Sciences’ DefineMBC™ liquid biopsy test characterizes CTC proteomics and genomics as well as ctDNA for the treatment of metastatic breast cancer. Blood samples from 813 metastatic breast cancer patients, with either newly diagnosed or progressing disease, with historical tissue subtype [HR(+)HER2(-), HR(+/-)HER2(+), and TNBC] supplied by the referring physician were collected and tested. Up to 5 CTCs were selected and isolated from each sample based on morphology and IF signal. DNA was extracted from individual cells, and whole genome amplified and sequenced at low coverage. Copy number analysis was performed to determine copy number gains and losses across chromosomes, as well as large scale-state transitions (LSTs) and ERBB2 amplification. CTCs characterized with high chromosomal instability (e.g., exhibiting >30 LSTs; 1Q firestorm and 8Q stair step) and high levels of cytokeratin expression (mean fluorescence intensity signal >10K) were categorized as basal-like. Results: By previous metastatic tissue biopsy, 77% were HR(+), 8% were HER2(+), and 12% were TNBC. CTCs categorized in DefineMBC as basal-like subtype (9.8 % of all samples tested) showed to be highly present in patients called as TNBC (79% basal-like). Additionally, 54% of HR(+) and 23% of HER2(+) had basal-like CTCS. Patients characterized with TNBC by metastatic tissue biopsy and by DefineMBC exhibited basal-like cells in 88% of the cases. Conclusion: The results show a novel clinical assay which utilizes CTC protein detection as well as single-cell genomic analysis to identify tumors driven by basal-like cells. Generally, TNBC is classified with negative biomarker expression. We show that CTCs in TNBC display genomically basal-like cells. CTCs from HR(+) and HER2(+) tumors may express basal-like features with preserved ER and HER2 expression. The comprehensive nature of DefineMBC™ utilizing genomic analysis of detected CTCs has provided a new tool to diagnose both basal-like TNBC and basal-like hormone receptor positive and HER2 over-expressing tumors. Citation Format: Alessandra Cunsolo, David Bourdon, Ernest Lam, Giuseppe Di Caro, Nilesh Dharajiya, Timothy Pluard, Lee Schwartzberg. Distinction of basal-like and triple-negative basal-like breast cancers utilizing a novel comprehensive single-cell liquid biopsy-based test [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 PO4-06-12.

Abstract LB094: Assessment of minimal residual disease in lung cancer patients treated with osimertinib using liquid biopsy

Abstract Purpose: Drug tolerance has emerged as one of the major mechanisms driving resistance to targeted therapies (TT), but a comprehensive understanding of the dynamics and molecular heterogeneity underlying the adaptive drug response in patients is still lacking. Here, we used iterative liquid biopsies from osimertinib-treated lung cancer patients to monitor and characterize minimal residual disease (MRD) using both circulating tumor DNA (ctDNA) and circulating tumor cells (CTC). Experimental design: LUNG-RESIST (NCT04222335) is a prospective research study enrolling EGFR-mutant adenocarcinoma patients treated by osimertinib frontline. We collected blood samples at baseline, 1 month and every 3 months until progression. CtDNA was used to monitor the initial EGFR mutation (EGFRm) by digital PCR, and to identify new potential biomarkers of resistance by next-generation sequencing (NGS). CTC were enriched and isolated based on their size, absence of leucocyte staining and viability, to perform single-cell transcriptomic and genomic analyses. Results: 40 patients have been enrolled with a median progression-free survival (mPFS) of 14.5 months (95%CI, 8.5-24.5 months). 28/40 (70%) patients had detectable EGFRm in ctDNA at baseline, and decreased ctDNA level could be measured in 25/26 (96%) patients after 1 month of treatment, with a complete clearance in 15/26 (58%) patients. 7/11 (64%) patients without clearance at 1 month relapsed within 9 months. Clinical relapse could be anticipated 3 months ahead based on ctDNA increase for 9/20 (45%) patients. CTC-like cells have been collected at baseline and MRD (between 1 and 3 months) from respectively 31/40 (78%) and 29/40 (73%) patients, and at clinical progression for 12/22 (54%) patients who relapsed, for a total number of 1,510 cells. The number of CTC-like cells decreased after 1 month of treatment in 18/29 (62%) patients, and increased again in 7/12 (58%) patients at the time of clinical relapse. The results of NGS analyses on ctDNA and single-cell transcriptomic and genomic analyses on CTC will be presented at the congress, and should provide a better insight into the dynamics of molecular events occurring throughout the adaptive response in patients. Conclusion: We report the first molecular profiling of both ctDNA and CTC during the adaptive response to osimertinib in lung cancer patients. Monitoring the response and predicting the clinical outcome for EGFR-mutant lung cancer patients undergoing TT treatment can be done using ctDNA level as a biomarker. The isolation of CTC-like cells represents a non-invasive approach to study drug tolerance and ultimately develop new combinatory treatments to prevent relapse. Citation Format: Celia Delahaye, Anne Casanova, Estelle Clermont-Tarenchon, Aurelia Doussine, Juan-Pablo Cerapio, Anaïs Anton, Emma Devienne, Vincent Dongay, Julie Milia, Gilles Favre, Olivier Calvayrac, Anne Pradines, Julien Mazieres. Assessment of minimal residual disease in lung cancer patients treated with osimertinib using liquid biopsy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB094.

High-Throughput Single-Cell, Single-Mitochondrial DNA Assay Using Hydrogel Droplet Microfluidics.

There is growing interest in understanding the biological implications of single cell heterogeneity and heteroplasmy of mitochondrial DNA (mtDNA), but current methodologies for single-cell mtDNA analysis limit the scale of analysis to small cell populations. Although droplet microfluidics have increased the throughput of single-cell genomic, RNA, and protein analysis, their application to sub-cellular organelle analysis has remained a largely unsolved challenge. Here, we introduce an agarose-based droplet microfluidic approach for single-cell, single-mtDNA analysis, which allows simultaneous processing of hundreds of individual mtDNA molecules within >10,000 individual cells. Our microfluidic chip encapsulates individual cells in agarose beads, designed to have a sufficiently dense hydrogel network to retain mtDNA after lysis and provide a robust scaffold for subsequent multi-step processing and analysis. To mitigate the impact of the high viscosity of agarose required for mtDNA retention on the throughput of microfluidics, we developed a parallelized device, successfully achieving ~95 % mtDNA retention from single cells within our microbeads at >700,000 drops/minute. To demonstrate utility, we analyzed specific regions of the single-mtDNA using a multiplexed rolling circle amplification (RCA) assay. We demonstrated compatibility with both microscopy, for digital counting of individual RCA products, and flow cytometry for higher throughput analysis.

Abstract 5557: Stem-like T cells maintain latent anticancer activity and underly therapy resistance

Abstract Pre-cancerous cells are normally recognized and eliminated by immune cells. Cancer progresses only when this immunosurveillance system fails. Although immunotherapy has driven the most significant and exciting advances in cancer treatment in modern times, current approaches are running into barriers. An emerging area of interest includes evidence for rare but highly potent stem cell-like T cells. Stem-like T cells combine long-term persistence and high potency with immunological memory. Our recent findings reveal insights into the nature and regulation of stem-like T cells and their potential anticancer activity. Minimal residual disease (MRD) underlies therapeutic resistance, dictates treatment escalation, and predicts patient outcomes. We have shown that the Wnt and PI3K pathways promote the transformation of hematopoietic stem cells (HSCs) into chemoresistant leukemia stem cells (LSCs), which form the root of leukemia initiation and post-treatment recurrence. High-throughput screening revealed that LSCs could be targeted by low dose anthracycline treatment. Mechanistically, low dose, but not high dose anthracyclines indirectly target LSCs by inhibiting their unique properties of immune escape, allowing for their elimination by CD8+ T cells. We employed single-cell genomic and proteomic analysis to investigate immunological changes during development of HSCs, LSCs, and their progeny in response to low dose anthracycline treatment. While leukemia progression results in exhaustion of differentiated CD8+ T cells, stem-like T cells accumulate. However, low dose anthracycline treatment reverses this imbalance. Comparing MRD+ and MRD- patient samples, we found that differential proportions of stem-like T cells persist in the bone marrow of leukemia patients. While T cells of MRD- patients recover following chemotherapy induction, T cell recovery is severely attenuated in MRD+ patients. Furthermore, failure of immunological recovery is driven at least partially by a lack of stem-like T cells in MRD+ leukemia patients. Overall, our studies have revealed that low dose anthracyclines, in contrast to high dose, induce opposing, dichotomous effects on LSCs vs. HSCs and stem-like vs. differentiated T cells. Citation Format: Fang Tao, Sara McElroy, Jacqelyn Nemechek, Irina Pushel, John Szarejko, Santosh Khanal, Todd Bradley, Doug Myers, John M. Perry. Stem-like T cells maintain latent anticancer activity and underly therapy resistance [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 5557.

Abstract 322: Ultraplex genome and exome sequencing of rare single cells

Abstract Single-cell genome analysis enables researchers to gain novel insights into tumor heterogeneity. Conducting single-cell genomic analysis using next-generation sequencing (NGS) methods has traditionally been challenging since the amount of genomic DNA present in a single cell is limited. PCR-based amplification methods normally have high error rates, low coverage uniformity, and extensive allelic drop-outs making interpretation of SNVs and CNVs challenging.Here we introduce a new whole-genome amplification method which utilizes an optimized isothermal DNA amplification reaction with a Hi-fidelity, error correcting polymerase and downstream library preparation protocol to allow pooling of amplified DNA. The key DNA amplification steps use multiple displacement amplification (MDA) technology to amplify gDNA directly from single cells, nuclei or previously isolated genomic DNA. During the MDA reaction, sample-barcodes are incorporated into the newly synthetized DNA, allowing the amplified DNA to be pooled and processed in to one ultraplex library. This method saves library preparation time, reduces DNA library costs and limits plastic consumable usage.Our current workflow allows 24 samples to be multiplexed in one library and 24 libraries to be produced for a total of 576 samples per sequencing flow cell. This method can be used to investigate chromosomal instability with low pass sequencing or SNV and CNV analysis following whole genome, exome-capture workflows. Citation Format: Ioanna Andreou, Samuel Rulli, Katja Heitz, Silke Huebner, Christin Meerschiff, Eric Lader. Ultraplex genome and exome sequencing of rare 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 322.

Single-cell genomics analysis reveals complex genetic interactions in an in vivo model of acquired BRAF inhibitor resistance.

The evolution of therapeutic resistance is a major obstacle to the success of targeted oncology drugs. While both inter- and intratumoral heterogeneity limit our ability to detect resistant subpopulations that pre-exist or emerge during treatment, our ability to analyze tumors with single-cell resolution is limited. Here, we utilized a cell-based transposon mutagenesis method to identify mechanisms of BRAF inhibitor resistance in a model of cutaneous melanoma. This screen identified overexpression of NEDD4L and VGLL3 as significant drivers of BRAF inhibitor resistance in vivo. In addition, we describe a novel single-cell genomics profiling method to genotype thousands of individual cells within tumors driven by transposon mutagenesis. This approach revealed a surprising genetic diversity among xenograft tumors and identified recurrent co-occurring mutations that emerge within distinct tumor subclones. Taken together, these observations reveal an unappreciated genetic complexity that drives BRAF inhibitor resistance.

FRI291 Musashi1 And Musashi2 Mark Distinct Pituitary Stem Cell Populations

Abstract Disclosure: Y. Rahmatallah: None. J. Banik: None. K. Bronson: None. M.C. MacNicol: None. The cell plastic state of the pituitary is required to meet the changing demands upon pituitary function and may also result in these cells being more vulnerable to malignant transformation. The mechanisms that control pituitary cell plasticity are unknown. The RNA binding protein Musashi (MSI) is expressed in embryonic stem cells, and in cancer stem cells, where MSI functions to promote stem cell plasticity and to oppose premature cell maturation. MSI is also expressed at high levels in adult gonad and adult pituitary. The function of MSI in adult tissues is not fully understood, and the mechanisms that control the pro-proliferative and pro-malignant aspects of MSI function in adult tissues are not known. The two evolutionarily conserved MSI proteins, Musashi1 (MSI1) and Musashi2 (MSI2), are predicted to function redundantly, however, regulatory distinctions have been reported for MSI1 and MSI2. Towards a characterization of MSI1 and MSI2 in pituitary, we analyzed transcriptomics data from public datasets of single-nucleus and single-cell and bulk-tissue gene expression data from physiological and pathophysiological human pituitary tissue. We performed bioinformatics analysis utilizing the single-cell genomics analysis tool, Seurat in R and the pseudotime trajectory analysis tool Monocle and additional genomics and statistics analyses tools in R. We identify the MSI1-expressing pituitary cell population as immature stem cells and the distinct MSI2-expressing pituitary cell population as more mature, committed progenitor cells. Pituitary from human fetal tissue contains multiple distinct MSI1-expressing cell populations while, in contrast, pituitary from human adult tissue contains multiple distinct MSI2-expressing cell populations. Pituitary from human pediatric tissue demonstrates an intermediate state with both distinct MSI1-expressing and distinct MSI2-expressing cell populations. We identify increased MSI1 expression but not increased MSI2 expression in adult pituitary adenoma, and a high level of variation in the MSI1 to MSI2 expression ratio between distinct pituitary adenomas. Based upon this re-analysis of reposited datasets from other pituitary investigators, we hypothesize that the increase that we observe, in MSI1 to MSI2 expression ratio in adult pituitary tumors is consistent with a reversion of mature cells to an earlier immature state. Adult pituitary may contain the mechanisms that regulate MSI2 function but may not be equipped to properly control high levels of re-expressed MSI1. An understanding of the physiological functions and mechanisms of regulation of the distinct MSI proteins in pituitary may provide insight into potential mechanisms that could be recruited to increase physiological pituitary cell growth and differentiation in regenerative therapy and to oppose pathological cell growth in pituitary tumor. Presentation: Friday, June 16, 2023

Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole-genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole-genome sequencing (WGS) but still generate hundreds of artifacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels), and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrence to distinguish PTA artifacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that hematopoietic stem cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS, have normal somatic single base substitution burdens but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

Plasticity of circulating tumor cells in small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive neuroendocrine tumor with low five-year survival rates. Recently described molecular phenotypes of SCLC exhibit differential vulnerabilities heralding potential for stratified treatment. Whilst tumor biopsy in SCLC is challenging, circulating tumor cells in the liquid biopsy are prevalent and can be repeatedly sampled accommodating the dynamic plasticity of SCLC phenotypes. The aim of this study was to characterize the heterogeneity of rare circulating cells with confirmed tumor origin and to explore a liquid biopsy approach for future clinical trials of targeted therapies. This study applied the 3rd generation of a previously validated direct imaging platform to 14 chemo-naive SCLC patients and 10 non-cancerous normal donor (ND) samples. Phenotypic heterogeneity of circulating rare cells in SCLC was observed and a patient-level classification model was established to stratify SCLC patients from non-cancerous donors. Eight rare cell groups, with combinations of epithelial, endothelial, and mesenchymal biomarker expression patterns, were phenotypically characterized. The single-cell genomic analysis confirmed the cancer cell plasticity in every rare cell group harboring clonal genomic alterations. This study shows rare cell heterogeneity and confirms cellular plasticity in SCLC providing a valuable resource for better opportunities to discover novel therapeutic targets in SCLC.

Multimodal characterization of murine gastruloid development

Gastruloids are 3D structures generated from pluripotent stem cells recapitulating fundamental principles of embryonic pattern formation. Using single-cell genomic analysis, we provide a resource mapping cell states and types during gastruloid development and compare them with the invivo embryo. We developed a high-throughputhandling and imaging pipeline to spatially monitor symmetry breaking during gastruloid development and report an early spatial variability in pluripotency determining a binary response to Wnt activation. Although cells in the gastruloid-core revert to pluripotency, peripheral cells become primitive streak-like. These two populations subsequently break radial symmetry and initiate axial elongation. By performing a compound screen, perturbing thousands of gastruloids, we derive a phenotypic landscape and infer networks of genetic interactions. Finally, using a dual Wnt modulation, we improve the formation of anterior structures in the existing gastruloid model. This work provides a resource to understand how gastruloids develop and generate complex patterns invitro.

PyInfinityFlow: optimized imputation and analysis of high-dimensional flow cytometry data for millions of cells.

While conventional flow cytometry is limited to dozens of markers, new experimental and computational strategies, such as Infinity Flow, allow for the generation and imputation of hundreds of cell surface protein markers in millions of cells. Here, we describe an end-to-end analysis workflow for Infinity Flow data in Python. pyInfinityFlow enables the efficient analysis of millions of cells, without down-sampling, through direct integration with well-established Python packages for single-cell genomics analysis. pyInfinityFlow accurately identifies both common and extremely rare cell populations which are challenging to define from single-cell genomics studies alone. We demonstrate that this workflow can nominate novel markers to design new flow cytometry gating strategies for predicted cell populations. pyInfinityFlow can be extended to diverse cell discovery analyses with flexibility to adapt to diverse Infinity Flow experimental designs. pyInfinityFlow is freely available in GitHub (https://github.com/KyleFerchen/pyInfinityFlow) and on PyPI (https://pypi.org/project/pyInfinityFlow/). Package documentation with tutorials on a test dataset is available by Read the Docs (pyinfinityflow.readthedocs.io). The scripts and data for reproducing the results are available at https://github.com/KyleFerchen/pyInfinityFlow/tree/main/analysis_scripts, along with the raw flow cytometry input data.

Abstract 5581: Single-cell genomic analysis of patient-derived circulating tumor cells in pancreatic cancer

Abstract Metastatic pancreatic cancer suffers from an extremely low five-year survival rate of only 3%. While patients with localized disease show marginally better survival rates, 52% of pancreatic cancers are not diagnosed until metastases have already developed. There is therefore a critically unmet need in the early diagnoses of pancreatic cancer patients. Liquid biopsies have emerged as a promising tool for cancer diagnosis through the analysis of various blood-based biomarkers. Among these, circulating tumor cells (CTCs) stand out as a promising target of interest. Over the past decade, CTCs have been identified as a precursor to metastasis. CTCs have also been shown to harbor mutations matching those of the primary tumor, making them a potential surrogate for biopsied tissue. However, CTCs are an extremely heterogenous population of cells, making bulk analysis challenging. In this study, we demonstrate a workflow for the isolation and genomic characterization of single CTCs from pancreatic cancer patients. CTCs are first enriched using a size-based microfluidic system, the Labyrinth, developed in the Nagrath lab. Single CTCs are subsequently isolated using the DEPArray Nxt system, followed by whole genome amplification (WGA) and low-pass sequencing. The pipeline was optimized using three commercially available pancreatic cancer cells lines (Panc-1, Capan-2, and BxPC-3) and two pancreatic cancer CTC cell lines previously developed in-house (CTC-CL-1 and CTC-CL-2). Finally, the workflow was validated using a blood sample from a stage IV pancreatic ductal adenocarcinoma patient. Following WGA, the average nucleic material concentration of the cell lines was 26.24 ± 16.28 ng/μL and 14.43 ng/μL for cells isolated from the patient sample. The average fragment size was 746 ± 232.79 bp for cell line cells and 507 bp for patient sample cells. This was within the expected range of 100-2000 bp. Both CTC cell lines show gains on parts of chromosome 8q (Myc), 10q (FGFR2) and 17q. Myc is a known oncogene and FGFR2 has been associated with cell growth, migration, and invasion. There are also noticeable differences between the two CTC-CL-1 cells, with one cell showing a 3p12.3-3p26.3 gain (CTNNB1), and the other showing a loss of 6q12-6q15 and gain of 6q16.1-6q27 (Myb, ESR1). A patient sample CTC and patient-matched WBC were isolated and sequenced. The CTC has a noticeable gain of chromosome 1q and loss of chromosome 5q. A gain in chromosome 1q has been seen previously in pancreatic cancer and chromosome 5q is the location of multiple oncogenes including APC, CSF1R and FGFR4. The loss of APC is known to affect Wnt/β-catenin signaling, causing an increase in CD34 expression which is linked to increase in cell invasion and migration. These results demonstrate an efficient workflow for the single cell genomic analysis of pancreatic CTCs. Further studies can be conducted to characterize the heterogenous landscape of CTCs in pancreatic cancer. Citation Format: Harrison Ball, Brittany Rupp, Sarah Owen, Kaylee Smith, Valerie Gunchick, Evan T. Keller, Vaibhav Sahai, Sunitha Nagrath. Single-cell genomic analysis of patient-derived circulating tumor cells in pancreatic cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5581.

Abstract P1-13-10: Deconvoluting dynamics of acquired chemoresistance in Triple Negative Breast Cancer tumors

Abstract Background: BRCA deficient Triple negative breast cancers (TNBC) are effectively treated with platinum agents but, upon relapse, resistance is common. A number of genes have been shown to mediate chemoresistance in vitro, but none have been clinically useful due to the heterogeneous mechanisms of in vivo tumor chemo-resilience. Methods: We attacked this problem by recapitulating the generation of in vivo resistance to cisplatin in 50 mice bearing a platinum sensitive TNBC patient derived xenograft (PDX) TM00099, a BRCA1 deficient type 1 tandem duplicator phenotype tumor. Untreated tumors were compared to residual tumors that were sampled after the first cycle of cisplatin, upon recovery, and after the second cycle of drug which generated platinum resistant and sensitive tumors. Our earlier work on TM00099 suggested the existence of two major subspecies, designated A and B, with shifts observed in their proportions post treatment (1). We deconvoluted the bulk tumors into their clonal components to assess the precise numerical fluxes after each treatment cycle to gain insight into the cellular basis of the emergence of in vivo resistance. Results: 55 single cell derived clones isolated from bulk TM00099 tumors were genomically characterized identifying five subclonal populations: B, CCR, and variations of the original A: A25, A33 and A50. SNP analyses indicated that these five subclones comprised the vast majority (~93%) of all TM00099 tumors. Lineage analysis revealed that all A clones were related but distinct from B. CCR however had both A and B SNP markers and relatively higher ploidy indicating that CCR is a fusion of ancestral A and B clones. We found that A50, A33, and CCR were ~1.9X more resistant to cisplatin (mean IC50=4.4 µM) compared to the sensitive clones A25 and B (mean IC50=2.3 µM; p=0.002) in vitro. Although B clones had similar IC50 to A25s, B had improved in vitro survival at higher concentrations of cisplatin suggesting a dormancy-like phenotype: the persistent B cells did not recover within 50 days after in vitro exposure to cisplatin. Using clonal markers in bulk tumors, we found excellent concordance with their in vitro phenotypic analysis: after the first cycle of cisplatin, there was a proportional decline in A25, an enrichment of B, and stable proportions of A50, A33, and CCR. After the second platinum cycle, the emerging resistant tumors were mostly devoid of A25, and had low proportions of B, but highly enriched for A50, A33, CCR and an uncharacterized resistant A clone. The sensitive tumor residuals after the second platinum dose were predominantly comprised of B. Genomic analysis of the clones did not reveal any genetic drivers of resistance. Transciptionally, the sensitive B clones were characterized as mesenchymal or basal-like 1 TNBC subtypes, while the resistant As were categorized as basal-like 2, which have enhanced growth factor signaling and is associated with poorer response to chemotherapy. Correspondingly, the MAPK and stress assosciated NF-κB signaling pathways were augmented in As which were indeed more sensitive to blockade of MEK, EGFR and NF-κB than the platinum sensitive B clone. A25s which are sensitive revertants of the otherwise resistant A group use a mechanism to bypass resistance likely driven by ZNF350 and ZNF93. Conclusions: Our clonal reconstruction of TM00099 showed that acquired resistance can emerge by enrichment of not one but a composite of multiple preexisting resistant clones. The origins and characteristics of these clones are complex and include epigenetically driven resistance (A50 and A33), cell fusion mediated resistance (CCR), reversion to sensitivity (A25), and dormancy despite initial sensitivity (B). These nuances would not be discerned using bulk tumor assessments pointing to single cell genomic analyses as the most precise way to deconvolute the capacity of TNBC tumors to develop resistance.

Abstract P5-06-02: Circulating tumor cells in metastatic breast cancer highlight potential role of copy number evolution in late-stage cancer mutational profile

Abstract Background: Structural variation is a hallmark of breast cancer. Previous single-cell genomic analysis of 10 untreated early-stage primary TNBC tumors identified only one or two subclones per tumor, found that copy number variation (CNV) occurs early in the evolution of the tumor, and asserted that CNV changes do not contribute to genomic variation at later time points of a tumor’s growth. This PCNE model (punctuated copy number evolution) is analogous to the big-bang theory of colorectal cancer. However, cancer exists in a dynamic environment, and systemic chemotherapy provides evolutionary pressure, making stasis quite unlikely. An investigation of late-stage cancers could shed light on CNV evolution. Methods: We performed a longitudinal, prospective observational study of over 130 patients with metastatic breast cancer, with regular follow-up and detailed treatment histories. CTCs were enumerated by CellSearch, and samples with >20 CTCs in 7.5ml of whole blood were further processed for single CTC isolation via DEPArray, single-cell library construction, and whole-genome sequencing. CNV counts for each cell were obtained using previously published binning methods (Ginkgo). Three mathematical models were used to evaluate the evolution of CNVs: a punctuated model, a gradual model, and a gradual-on-punctuated hybrid model. Results: In total, 150 patient-years of data were collected. Among samples with sufficient CTC counts for study inclusion, a total of nine patients and 376 cells were isolated for sequencing. A mean sequencing depth of 0.8× was achieved from each single cell. The degree of CNV heterogeneity varies from patient to patient. CNV changes occurred over time in a gradual manner on a background of punctuated changes. The adjusted R2 value for the punctuated model was 0.46, the adj R2 value for the gradual model was 0.76, and the hybrid model achieved an adj R2 of 0.99. Patient samples with large CNV heterogeneity across single cells tend to be from patients with longer treatment histories and from the last blood draw (i.e., the blood collection closest to patient’s point of death). We also identified multiple whole-genome duplication (WGD) events from the same patient, in contrast to previous findings that WGD events are usually early clonal events in most instances. Finally, X loss events are among the most frequent chromosomal aberrations identified in CTCs (in up to 80% of CTCs in some patients), which supports previous literature on the loss of the Barr body in hastening metastatic spread. Discussion and Conclusion: In contrast to the previous study, our findings support a gradual-on-punctuated hybrid model, and this model can explain how copy number changes can be a source from which tumors gain resistance to systemic therapies. The model explains how CNV heterogeneities are seen in patients with longer treatment histories, suggesting that CNV continues to be a source of genetic variation at the metastatic stage of the disease course. Citation Format: Weelic Chong, Rui Luo, Zhenchao Zhang, Maysa Abu-Khalaf, Daniel Silver, Frederick Fellin, Rebecca Jaslow, AnaMaria Lopez, Terrence Cescon, Ronald Myers, Mariel Becker, Qiang Wei, Bingshan Li, Chun Wang, Hushan Yang. Circulating tumor cells in metastatic breast cancer highlight potential role of copy number evolution in late-stage cancer mutational profile [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-06-02.

Dissecting endometriosis by single-cell transcriptomic and genomic analysis.

Dissecting endometriosis by single-cell transcriptomic and genomic analysis.

High-throughput single-cell genomic analysis for archival tissue blocks

High-throughput single-cell genomic analysis for archival tissue blocks

A genetic disorder reveals a hematopoietic stem cell regulatory network co-opted in leukemia

The molecular regulation of human hematopoietic stem cell (HSC) maintenance is therapeutically important, but limitations in experimental systems and interspecies variation have constrained our knowledge of this process. Here, we have studied a rare genetic disorder due to MECOM haploinsufficiency, characterized by an early-onset absence of HSCs in vivo. By generating a faithful model of this disorder in primary human HSCs and coupling functional studies with integrative single-cell genomic analyses, we uncover a key transcriptional network involving hundreds of genes that is required for HSC maintenance. Through our analyses, we nominate cooperating transcriptional regulators and identify how MECOM prevents the CTCF-dependent genome reorganization that occurs as HSCs differentiate. We show that this transcriptional network is co-opted in high-risk leukemias, thereby enabling these cancers to acquire stem cell properties. Collectively, we illuminate a regulatory network necessary for HSC self-renewal through the study of a rare experiment of nature.