Single Genomics Research Articles

210 Three-dimensional models of human skin at single-cell resolution in health and disease

The human skin is a complex three-dimensional tissue comprised of an outer layer, the epidermis includes keratinocytes, melanocytes and Langerhans cells, with an underlying connective tissue layer, the dermis which contains numerous cell types such as fibroblasts, endothelial cells and immune populations. As for many human tissues, the structure and function is determined by complex interactions between these diverse cell types. In recent years, advances in single cell genomics and computational methods have facilitated a revolution in the ability to analyse transcriptional profiles at the single cell level. However dissecting to what extent observed transcriptional identify is specified intrinsically rather than dictated by the local cellular and extracellular matrix environment remains a significant challenge for the field. As part of the Human Cell Atlas project – an international collaborative effort to map all cell types within the human body – single cell RNA sequencing has been performed on in excess of a hundred thousand cells from the epidermis and dermis from human skin derived from healthy individuals using the chromium 10X platform. This has enabled the identification of novel cellular subtypes. In order to understand the factors governing cellular identity in healthy and diseased skin, we are integrating computational and ex vivo strategies with in vivo dynamic optical computed tomography skin imaging to probe the relative importance of intrinsic and extrinsic factors in in three-dimensional human tissues. In future work, we will apply these methods to skin diseases including psoriasis, eczema and lichen planus with the goal of understanding the changes in cellular identity that accompany disease pathogenesis.

Assessing the viral content of uncultured picoeukaryotes in the global-ocean by single cell genomics.

Viruses are the most abundant biological entities on Earth and have fundamental ecological roles in controlling microbial communities. Yet, although their diversity is being increasingly explored, little is known about the extent of viral interactions with their protist hosts as most studies are limited to a few cultivated species. Here, we exploit the potential of single-cell genomics to unveil viral associations in 65 individual cells of 11 essentially uncultured stramenopiles lineages sampled during the Tara Oceans expedition. We identified viral signals in 57% of the cells, covering nearly every lineage and with narrow host specificity signal. Only seven out of the 64 detected viruses displayed homologies to known viral sequences. A search for our viral sequences in global ocean metagenomes showed that they were preferentially found at the DCM and within the 0.2-3µm size fraction. Some of the viral signals were widely distributed, while others geographically constrained. Among the viral signals we detected an endogenous mavirus virophage potentially integrated within the nuclear genome of two distant uncultured stramenopiles. Virophages have been previously reported as a cell's defence mechanism against other viruses, and may therefore play an important ecological role in regulating protist populations. Our results point to single-cell genomics as a powerful tool to investigate viral associations in uncultured protists, suggesting a wide distribution of these relationships, and providing new insights into the global viral diversity.

Single Cell Genomics: Whole Genome Sequencing of Single Circulating Tumor Cells Isolated by Applying a Pulsed Laser to Cell‐Capturing Microstructures (Small 37/2019)

Single Cell Genomics: Whole Genome Sequencing of Single Circulating Tumor Cells Isolated by Applying a Pulsed Laser to Cell‐Capturing Microstructures (Small 37/2019)

Abstract 1443: Sensitive detection and quantification of CAR-T cells in the treated patients

Abstract Background. Cell therapy for cancers has gained great momentum as a promising new cancer treatment approach. In particular, autologous T cells modified with a chimeric antigen receptor (CAR-T) has recently been regulatory-approved for the treatment of the patients of CD19+ acute B-cell leukemia [1][2]. However effective monitoring and characterizing the CAR-T cells after administration, vital to understand the treatment effect and its underneath mechanism, remain to be an urgent unmet need for CAR-T therapy in the clinics. There have been two major methods to monitor the presence of CAR-T in patients at present: a) flow cytometry (a single cell based assay recognizing the tag engineered in CAR molecule), but with extremely poor sensitivity ~1%); and b) Real-Time PCR (amplifying the engineered tag sequences), being more sensitive, but without the ability to identify and characterizing the individual CAR-T cells [3][4]. Thus, a method with high sensitivity and also the ability to characterize individual CAR-T is in high demand. Methods. We are attempting to establish a novel platform, based on rare cell detection in pathology format, to detect and character rare CAR-T cells in patients treated by CAR-T using Rarecyte technology. First, 1x106 white blood cells (PBMC from C57BL/6 mice), spiked with the serial dilution of 0-250 human breast cancer MCF-7 cells, were smeared on a pathology slide and subjected to the staining by antibodies against human Cytokeratin 18 (Abcam, ab181597) and mouse CD45 (R&D, AF114), followed by either flow cytometry or Rarecyte system, in order to test the detection sensitivity and quantification dynamic ranges. Second, PBMC obtained from the DLBCL patient treated with CD19 CAR-T cells were (100 μL) were subjected to the same two analysis as above with the CAR-T specific staining (CD3-FITC, CD19-CAR-PE, DAPI (nucleus)), as controlled by the PBMC from healthy donors. Results. Our preliminary data from the spiked study indicated that our method has high sensitivity down to 2 cells (>90% recovery), and good linear range of quantification. The sensitivity (< 1/1-million) is at least 3-orders of magnitude above that of flow cytometry (~1%). Our CAR-T treated clinical data demonstrated the detection and quantification of CAR-T in patients that flow cytometry cannot. In addition, the single CAR-T can be picked up for further characterization, e.g. single cell genomics. Conclusions. Our method detection, monitoring and characterization of CAR-T offers an great opportunity in the clinical setting to monitor patient treatment and to understand the treatment mechanisms, that otherwise is unavailable. This could become an useful diagnostics to provide guidance on the treatment and prognosis of patients. Citation Format: Xiaoyu An, Xiaolong Tu, Xinhe Feng, Jianjian Zhang, Dandan Song, Haijuan Yu, Henry Li. Sensitive detection and quantification of CAR-T cells in the treated patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1443.

Concepts and limitations for learning developmental trajectories from single cell genomics.

Single cell genomics has become a popular approach to uncover the cellular heterogeneity of progenitor and terminally differentiated cell types with great precision. This approach can also delineate lineage hierarchies and identify molecular programmes of cell-fate acquisition and segregation. Nowadays, tens of thousands of cells are routinely sequenced in single cell-based methods and even more are expected to be analysed in the future. However, interpretation of the resulting data is challenging and requires computational models at multiple levels of abstraction. In contrast to other applications of single cell sequencing, where clustering approaches dominate, developmental systems are generally modelled using continuous structures, trajectories and trees. These trajectory models carry the promise of elucidating mechanisms of development, disease and stimulation response at very high molecular resolution. However, their reliable analysis and biological interpretation requires an understanding of their underlying assumptions and limitations. Here, we review the basic concepts of such computational approaches and discuss the characteristics of developmental processes that can be learnt from trajectory models.

Single Cell Genomics-Based Analysis of Gene Content and Expression of Prophages in a Diffuse-Flow Deep-Sea Hydrothermal System.

Phage–host interactions likely play a major role in the composition and functioning of many microbiomes, yet remain poorly understood. Here, we employed single cell genomics to investigate phage–host interactions in a diffuse-flow, low-temperature hydrothermal vent that may be reflective of a broadly distributed biosphere in the subseafloor. We identified putative prophages in 13 of 126 sequenced single amplified genomes (SAGs), with no evidence for lytic infections, which is in stark contrast to findings in the surface ocean. Most were distantly related to known prophages, while their hosts included bacterial phyla Campylobacterota, Bacteroidetes, Chlorobi, Proteobacteria, Lentisphaerae, Spirochaetes, and Thermotogae. Our results suggest the predominance of lysogeny over lytic interaction in diffuse-flow, deep-sea hydrothermal vents, despite the high activity of the dominant Campylobacteria that would favor lytic infections. We show that some of the identified lysogens have co-evolved with their host over geological time scales and that their genes are transcribed in the environment. Functional annotations of lysogeny-related genes suggest involvement in horizontal gene transfer enabling host’s protection against toxic metals and antibacterial compounds.

Using single cell genomics to change the treatment of lung cancer.

e20563 Background: Lung cancer (LC) is common with a dismal prognosis. Although treatment with immunotherapy (IO) has improved survival outcomes, these therapies remain expensive. Even using biomarker selection, response rates still fall short of 50%. The majority of immune cell profiling done previously uses samples taken from early stage patients focusing on a single immune cell subtype. Here we use single cell RNA sequencing (scRNA-seq) and Cellular Indexing of Transcriptome and Epitopes by sequencing (CITE-seq) to characterise the innate and adaptive immune cell activation state and assess the response to exposure to IO in vitro from patients with advanced LC. Methods: Patients with locally advanced or metastatic LC having an Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) have biopsies collected for analysis. Cells are grown in culture +/- nivolumab for 48 hours. scRNA-seq and CITE-seq is conducted using established protocols. Transcriptomic and proteomic data on the innate and adaptive immune cell subsets assess markers of immune activation and/or suppression and the changes after nivolumab are quantified. Results are correlated with clinical outcomes. Results: In a locally advanced/metastatic population, EBUS-TBNA biopsies yield highly cellular samples with a heterogeneous population of immune cells able to be cultured +/- IO using novel, inclusive techniques. Transcriptomic clustering reveals distinct sub-populations within the T-cell, B-cell and innate immune cell compartments. Within these clusters, CITE-seq shows protein expression on individual cells can determine states of exhaustion, cytolytic ability, migratory potential and innate immune activation. Conclusions: Single cell genomics is feasible and informative in patients with advanced LC. This work will form the basis of a functional, real-time assay to assess individualised responses to IO therapy that has the potential to predict IO response.

Circulating tumor cell (CTC) enumeration in patients (pts) with metastatic genitourinary (mGU) tumors treated in a phase I study of cabozantinib and nivolumab (CaboNivo) +/- ipilimumab (CaboNivoIpi).

4555 Background: CTCs may serve as biomarkers for clinical outcomes in GU tumor pts. We examined the association between baseline CTC enumeration, CTC heterogeneity, CTC morphologic subtypes, and progression-free-survival, overall survival and response to therapy with combination CaboNivo or CaboNivoIpi. Methods: 123 samples from 52 pts with mGU tumors treated with CaboNivo (38 pts) or CaboNivoIpi (14 pts) drawn at Baseline, Cycle (C) 2 Day (D) 1, and C3D1 were processed using the Epic Sciences platform. CTCs were defined as cytokeratin (CK)+, CD45-, distinct morphology, intact nucleus. PD-L1 expression was also assessed. Results: From 07/20/2016-09/01/2018, 52 pts [urothelial carcinoma (UC) N = 33; plasmacytoid N = 1; Clear cell renal cell carcinoma N = 4; bladder adenocarcinoma N = 8; bladder squamous cell carcinoma N = 2; bladder small cell N = 2; renal medullary N = 2] were treated. Median age was 61.5 years (range 20-82); 35 (67%) were male. N = 37 (71%) had visceral involvement, N = 15 (29%) with liver involvement, N = 11 (21%) with bone involvement. CTCs were found in the peripheral blood of 26/40 (65%) pts at baseline. 1/40 pts (bladder adenocarcinoma) had PDL1+ CTCs at Baseline. Median CTC/mL at Baseline, C2D1, C3D1, were not significantly different. CTC counts of > 2 and > 4 at C2D1 were potentially associated with shorter OS (p = 0.071 and p = 0.045 without adjustment for multiple cutoffs for evaluation). PFS results exhibited similar trends. Unsupervised clustering of CTC images identified 5 main CTC subtypes, of which the presence of one was significantly associated with shorter OS (p = 0.0014, not adjusted for multiple testing). Additionally, we observed a trend towards patients with higher CTC heterogeneity at C2D1 having longer OS, when adjusting for the risk associated with CTC enumeration (p = 0.084). Conclusions: CTC were detected in pts with mGU tumors treated with CaboNivo and CaboNivoIpi. CTC values were somewhat but not statistically lower in responders vs. non-responders. On treatment lower CTCs and the absence of aggressive CTC subtypes were associated with better clinical outcomes. Ongoing analyses include single cell genomics, and analysis of T-cell populations. Clinical trial information: NCT02496208.

Single Cell Transcriptomic Analysis of Pancreatic β Cell Development and Differentiation from Pluripotent Stem Cells

Single cell genomics is a powerful tool to study cellular heterogeneity and discover novel cell types. Recent studies used single cell RNA sequencing (scRNA-seq) to analyze the transcriptomes of individual pancreatic islet cells. Islets are a complex mixture of endocrine cells and therefore represent an ideal tissue for single cell transcriptomic analysis. Adult human islets consist of five known endocrine cell types (α, β, δ, γ, ε) and multiple less well defined non-endocrine cells. In this review, we discuss the scRNA-seq studies performed on human fetal, adult, diseased and stem cell-derive islets in recent years. Since 2015, ~30,000 adult human islet cells have been analyzed using several scRNA-seq technologies. Studies provide a complete catalogue of all islet cell types (up to 14) and subtypes found throughout human development from fetus to adulthood. Islets from patients with Type 2 diabetes have also been analyzed with scRNA-seq unraveling multiple mechanisms of islet dysfunction. Advances in stem cell differentiation protocols and cell therapy manufacturing are bring stem cell-derived islets (SC-Islets) closer to clinical trials. In 2018, more than 60,000 SC-Islet cells were analyzed using scRNA-seq technologies. Lessons learned include SC-Islet cell populations, lineage trajectories and comparative analyses to adult human islet cell transcriptomes. Studies have also identified and characterized the non-islet, off-target cell populations revealing potential strategies for their elimination.

An advancement in single cell genomics allows for T cell population analysis at high resolution

Abstract Progress in our understanding of immunology and cancer immunotherapies requires a comprehensive view of immune cell behavior and the interactions of these cells with their environment. Recent technological innovations have facilitated the combination of cell-surface protein, transcriptome, immune repertoire, and antigen specificity measurements from the same single cells, providing thorough and high-throughput lymphocyte characterization. Using the 10x Genomics Single Cell Immune Profiling Solution with Feature Barcoding technology along with oligo-conjugated antibodies and peptide-MHC (pMHC) Dextramers®, we performed multi-omic characterization of PBMCs from cytomegalovirus (CMV) seronegative and seropositive patients. Next generation sequencing libraries were made following the 10x Genomics workflows, where transcriptome and immune repertoire libraries are generated alongside libraries from DNA barcodes conjugated to antibodies or pMHC. Full length, paired TCRα/β sequences with specificity to known CMV antigens were identified in the seropositive donor, but not in the seronegative donor. Interestingly, a large Epstein Barr Virus (EBV) pMHC specific T cell expansion was identified in the CMV seronegative donor, suggesting an active EBV response. Moreover, the combination of transcriptomic and cell surface protein information resulted in an increase in resolution of cell type identification. This multi-omic workflow allowed the identification of enriched amino acid motifs within the TCR sequences that contained novel and known CDR3 amino acid sequences specific to CMV. These technological advancements provide new biological insights that are critical for progress in the field.

Single cell genomics yields a wide diversity of small planktonic protists across major ocean ecosystems

Marine planktonic protists are critical components of ocean ecosystems and are highly diverse. Molecular sequencing methods are being used to describe this diversity and reveal new associations and metabolisms that are important to how these ecosystems function. We describe here the use of the single cell genomics approach to sample and interrogate the diversity of the smaller (pico- and nano-sized) protists from a range of oceanic samples. We created over 900 single amplified genomes (SAGs) from 8 Tara Ocean samples across the Indian Ocean and the Mediterranean Sea. We show that flow cytometric sorting of single cells effectively distinguishes plastidic and aplastidic cell types that agree with our understanding of protist phylogeny. Yields of genomic DNA with PCR-identifiable 18S rRNA gene sequence from single cells was low (15% of aplastidic cell sorts, and 7% of plastidic sorts) and tests with alternate primers and comparisons to metabarcoding did not reveal phylogenetic bias in the major protist groups. There was little evidence of significant bias against or in favor of any phylogenetic group expected or known to be present. The four open ocean stations in the Indian Ocean had similar communities, despite ranging from 14°N to 20°S latitude, and they differed from the Mediterranean station. Single cell genomics of protists suggests that the taxonomic diversity of the dominant taxa found in only several hundreds of microliters of surface seawater is similar to that found in molecular surveys where liters of sample are filtered.

Carbon Fixation by Marine Ultrasmall Prokaryotes.

Autotrophic carbon fixation is a crucial process for sustaining life on Earth. To date, six pathways, the Calvin–Benson–Bassham cycle, the reductive tricarboxylic acid cycle, the 3-hydroxypropionate bi-cycle, the Wood–Ljungdahl pathway, the dicarboxylate/4-hydroxybutyrate cycle, and the 4-hydroxybutyrate cycle, have been described. Nano-organisms such as members of the Candidate Phyla Radiation (CPR) bacterial superphylum and the Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohalorchaeota (DPANN) archaeal superphylum could deeply impact carbon cycling and carbon fixation in ways that are still to be determined. CPR and DPANN are ubiquitous in the environment but understudied; their gene contents are not exhaustively described; and their metabolisms are not yet fully understood. Here, the completeness of each of the above pathways was quantified and tested for the presence of all key enzymes in nano-organisms from across the World Ocean. The novel marine ultrasmall prokaryotes were demonstrated to collectively harbor the genes required for carbon fixation, in particular the “energetically efficient” dicarboxylate/4-hydroxybutyrate pathway and the 4-hydroxybutyrate pathway. This contrasted with the known carbon metabolic pathways associated with CPR members in aquifers, where they are described as degraders (Castelle CJ, et al. 2015. Genomic expansion of domain archaea highlights roles for organisms from new phyla in anaerobic carbon cycling. Curr Biol. 25(6):690–701; Castelle CJ, et al. 2018. Biosynthetic capacity, metabolic variety and unusual biology in the CPR and DPANN radiations. Nat Rev Microbiol. 16(10):629–645; Anantharaman K, et al. 2016. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat Commun. 7:13219.). Our findings suggest that nano-organisms have a broader contribution to carbon fixation and cycling than currently assumed. Furthermore, CPR and DPANN superphyla are possibly not the only nanosized prokaryotes; therefore, the discovery of new autotrophic marine nano-organisms by future single cell genomics is anticipated.

Acute leukemias harboring KMT2A/MLLT10 fusion: a 10-year experience from a single genomics laboratory.

The MLLT10 (formerly AF10) gene is the fourth most common KMT2A fusion partner across all acute leukemias and requires at least 3 breaks to form an in-frame KMT2A/MLLT10 fusion due to the opposite orientation of each gene. A 10-year retrospective review was performed to identify individuals from all age groups that harbor KMT2A/MLLT10 fusion obtained by our KMT2A/MLLT10 dual-color dual-fusion fluorescence in situ hybridization (D-FISH) assay. Of the 60 unique individuals identified, 31 were male and 29 were female (M:F ratio, 1.1:1) with ages ranging from 3 days to 86 years (mean 21.5 years, median 5.5 years). The diagnoses included acute myeloid leukemia (AML) (49 patients, 82%), B- or T-lymphoblastic leukemia/lymphoma (7 patients, 12%), myeloid sarcoma (3 patients, 5%), and a single case (2%) of undifferentiated leukemia. Twenty-seven of 49 patients (55%) with AML were in the infant or pediatric age group. Fifty-three of 60 patients (88%) had KMT2A/MLLT10 D-FISH signal patterns mostly consisting of single fusions. In addition, 10 (26%) of 38 patients with conventional chromosome studies had "normal" (5 patients) or abnormal (5 patients) chromosome studies that lacked structural or numeric abnormalities involving chromosomes 10 or 11, implying cryptic cytogenetic mechanisms for KMT2A/MLLT10 fusion. Lastly, mate-pair sequencing was performed on 4 AML cases, 2 of which had "normal" chromosome studies and cryptic KMT2A/MLLT10 fusion as detected by KMT2A/MLLT10 D-FISH studies, and verified the multiple breaks required to generate KMT2A/MLLT10 fusion.

Circulating tumor cell (CTC) enumeration in patients (pts) with metastatic genitourinary (mGU) tumors treated in a phase I study of cabozantinib and nivolumab (CaboNivo) +/- ipilimumab (CaboNivoIpi).

379 Background: CTCs may serve as biomarkers for clinical outcomes in GU tumor pts. We examined the association between baseline CTC enumeration, change in CTC enumeration post treatment, progression-free-survival, overall survival and response to therapy with combination CaboNivo or CaboNivoIpi. Methods: 128 samples from 52 pts with mGU tumors treated with CaboNivo (38 pts) or CaboNivoIpi (14 pts) were drawn at baseline, cycle (C) 2 Day (D) 1, and C3D1 and processed with Epic Sciences platform. CTCs were defined as cytokeratin (CK)+, CD45-, distinct morphology, intact nucleus. PD-L1 expression was assessed. Results: From 07/20/2016-09/01/2018, 52 pts were treated for metastatic [urothelial carcinoma (UC) N = 33; UC plasmacytoid N = 1; clear cell renal cell carcinoma N = 4; bladder adenocarcinoma (BAC) N = 8; bladder squamous cell carcinoma N = 2; bladder small cell carcinoma N = 2; renal medullary carcinoma N = 2]. Median age was 61.5 years (range 20-82); 35 (67%) were male; N = 37(71%) had visceral involvement, N = 15(29%) had liver involvement, N = 11(21%) had bone involvement. CTCs were found in the peripheral blood of 39 (75%) pts, 1 pt (BAC) had PDL1+ CTCs at baseline. Median CTC/mL at C1D1, C2D1, C3D1, were 0.5 (0-357.1), 0.4 (0-71.8), and 0.75 (0-18), respectively. Median (lower and upper quartile) CTCs in pts with complete or partial responses (responders) vs stable or progressive disease (non-responders) were: 0.0 (0 to 5.40) vs 0.7 (0 to 2.5) at baseline; -0.35 (-3.65 to 0) vs 0 (-2 to 1.7) change from baseline to C2D1; and 0 (-5.4 to 0.5) vs 0 (-0.9 to 0.65) change from baseline to C3D1 (all p > 0.15). CTC counts of > 2 and > 4 at C2D1 were potentially associated with shorter OS (p = 0.071 and p = 0.045 without adjustment for multiple cutoffs for evaluation). PFS results exhibited similar trends. Conclusions: CTC were detected in pts with mGU tumors treated with CaboNivo and CaboNivoIpi. CTC values were lower in responders than in non-responders. On treatment lower CTCs were associated with better clinical outcomes. Ongoing analyses with the CTCs include cell morphology and heterogeneity, single cell genomics, and T-cell populations.

Live Single-Cell Metabolomics With Matrix-Free Laser/Desorption Ionization Mass Spectrometry to Address Microalgal Physiology.

Unicellular phototrophic algae can form massive blooms with up to millions of individual cells per milliliter in freshwater and marine ecosystems. Despite the temporal dominance of bloom formers many algal species can co-exist and compete for nutrients and space, creating a complex and diverse community. While microscopy and single cell genomics can address the taxonomic inventory, the cellular metabolome has yet to be thoroughly explored to determine the physiological status of microalgae. This might, however, provide a key to understand the observed species diversity in the homogeneous environment. Here, we introduce an effective, rapid and versatile method to analyze living single cells from aqueous substrata with laser-desorption/ionization mass spectrometry (LDI-MS) using a simple and inexpensive matrix-free support. The cells deposited on a cultivation-medium wetted support are analyzed with minimal disturbance as they remain in their natural viable state until their disruption during LDI-MS. Metabolites desorbed from single cells are analyzed on High-Resolution Mass Spectrometry (HR-MS) using the Orbitrap FT-MS technology to fingerprint cellular chemistry. This live single-cell mass spectrometry (LSC-MS) allows assessing the physiological status and strain-specifics of different microalgae, including marine diatoms and freshwater chlorophytes, at the single-cell level. We further report a reliable and robust data treatment pipeline to perform multivariate statistics on the replicated LSC-MS data. Comparing single cell MS spectra from natural phytoplankton samples and from laboratory strains allows the identification and discrimination of inter and intra-specific metabolic variability and thereby has promising applications in addressing highly complex phytoplankton communities. Notably, the herein described matrix-free live-single-cell LDI-HR-MS approach enables monitoring dynamics of the plankton and might explain why key-players survive, thrive, avoid selective feeding or pathogenic virus and bacteria, while others are overcome and die.

Abstract P5-07-03: Small molecule inhibition of smoothened in triple negative breast cancer-associated fibroblasts depletes cancer stem cells and sensitizes to cytotoxic chemotherapy in mice and humans

Abstract The cellular and molecular basis of stromal cell recruitment, activation and crosstalk in carcinomas is poorly understood, limiting the development of targeted anti-stromal therapies. In mouse models of triple negative breast cancer (TNBC), we use single cell genomics to show that Hh ligand produced by neoplastic cells reprograms cancer-associated fibroblast (CAF) gene expression, driving tumor growth and metastasis. Hh-activated CAFs upregulated expression of FGF5 and deposition of fibrillar collagen, leading to FGFR and FAK activation in adjacent neoplastic cells and the acquisition of a stem-like, drug-resistant phenotype. Treatment with smoothened inhibitors (SMOi) reversed these phenotypes. Stromal treatment of TNBC patient-derived xenograft (PDX) models with SMOi downregulated the expression of cancer stem cell markers and sensitized tumors to docetaxel, leading to markedly improved survival and reduced metastatic burden. In the phase I clinical trial EDALINE, 3 patients with metastatic TNBC derived clinical benefit from combination therapy with the SMOi Sonedigib and docetaxel chemotherapy, with one patient experiencing a complete radiological response. Responders also exhibited high baseline FGFR activation and ECM deposition, suggesting a mechanism of action consistent with findings from the animal models. These studies identify Hh signaling to CAFs as a novel mediator of cancer stem cell plasticity and drug resistance and an exciting new therapeutic target in TNBC. Citation Format: Swarbrick A, Cazet A, Hui M, O'Toole S, Lim E, Martin M. Small molecule inhibition of smoothened in triple negative breast cancer-associated fibroblasts depletes cancer stem cells and sensitizes to cytotoxic chemotherapy in mice and humans [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-07-03.

Abstract PL1: Breast Tumor Evolution and Intratumor Heterogeneity - Insights from Single Cell Genomics

Abstract Breast tumors evolve from single cells in the ducts and acquire mutations leading to divergent lineages and intratumor heterogeneity in invasive cancers. To understand the genomic evolution of breast cancers during complex evolutionary processes including initiation, invasion and therapeutic resistance we have developed single cell sequencing (SCS) methods. I will discuss our efforts in applying SCS methods to study invasion in 10 premalignant breast cancer patients with ductal-carcinoma-in-situ (DCIS), which led to a discovery of early punctuated copy number evolution in the ducts and multi-clonal invasion. I will also discuss our work in applying both single cell DNA and RNA sequencing methods to study chemoresistance evolution in 20 triple-negative breast cancer patients using longitudinal samples, which identified an adaptive genomic evolution and acquired transcriptional reprogramming during resistance. Finally I will present unpublished work on our efforts to develop a 'Human Breast Cell Atlas' of cell types and cell states (transcriptional programs) of normal cell types, and recent work on delineating copy number evolution in BRCA-positive breast cancer patients. Citation Format: Navin N. Breast Tumor Evolution and Intratumor Heterogeneity - Insights from Single Cell Genomics [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PL1.

Abstract GS1-01: Landscape of the breast tumour microenvironment at single-cell resolution

Abstract Breast cancers are a complex 'ecosystem' of diverse cell types, whose heterotypic interactions play central roles in defining the aetiology of disease and its response to therapy. The next generation of therapies will likely be based upon an integrated understanding of the malignant, microenvironmental and immune states that define the tumour and inform treatment response. However, our poor understanding of the tumour microenvironment (TME) of breast cancers has limited the development and implementation of new drugs that target stromal and immune cells. Single cell genomics (SCG) is a remarkable new platform to examine the compositional, gene expression and other parameters of thousands of cells, rapidly and at scale. We have used a multi-dimensional SCG approach to characterise the TME in a unique cohort of early and metastatic breast cancers with rich clinico-pathological annotation. We have conducted single cell RNA-Sequencing on more than 125,000 cells collected from 22 patients. Malignant cells showed remarkable intra-tumoural heterogeneity for canonical breast cancer features, such as intrinsic subtype, hormone receptor expression and activity, drug targets, drug resistance signatures and transcriptional drivers. Cancer Associated Fibroblasts (CAFs), which are classically studied as a single cell type, were heterogeneous across primary and metastatic sites. Interestingly we identified a myofibroblast-like subset and an inflammatory-mediator subset and propose multi-faceted roles in regulating malignancy and tumour immunity. Distinct transcription factor networks regulated these polarised states. We applied a new method known as CITE-Seq to measure cell surface immune markers and checkpoint proteins simultaneous to RNA-Sequencing. We resolve the tumour-immune milieu with high precision and generate new transcriptional signatures of breast tumour-infiltrating leukocytes. To track lymphocyte clonal dynamics through space and time, we developed a novel method known as RAGE-Seq to permit simultaneous full length lymphocyte receptor- and RNA-sequencing at single cell resolution. We observe clonal expansion and trafficking of CD4+ and CD8+ T lymphocytes between the lymph nodes, blood and tumor of patients. In comparison, B cells were polyclonal, suggesting an absence of antigen-dependent clonal expansion. This data provides by far the most extensive insights into the cellular landscape of breast cancer and will reveal new biomarkers and opportunities for stromal- and immune-based therapy. Citation Format: Swarbrick A, Wu SZ, Roden D, Al-Eryani G, O'Toole S, Lim E. Landscape of the breast tumour microenvironment at single-cell resolution [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr GS1-01.

Barcode identification for single cell genomics

BackgroundSingle-cell sequencing experiments use short DNA barcode ‘tags’ to identify reads that originate from the same cell. In order to recover single-cell information from such experiments, reads must be grouped based on their barcode tag, a crucial processing step that precedes other computations. However, this step can be difficult due to high rates of mismatch and deletion errors that can afflict barcodes.ResultsHere we present an approach to identify and error-correct barcodes by traversing the de Bruijn graph of circularized barcode k-mers. Our approach is based on the observation that circularizing a barcode sequence can yield error-free k-mers even when the size of k is large relative to the length of the barcode sequence, a regime which is typical single-cell barcoding applications. This allows for assignment of reads to consensus fingerprints constructed from k-mers.ConclusionWe show that for single-cell RNA-Seq circularization improves the recovery of accurate single-cell transcriptome estimates, especially when there are a high number of errors per read. This approach is robust to the type of error (mismatch, insertion, deletion), as well as to the relative abundances of the cells. Sircel, a software package that implements this approach is described and publically available.

Single cell functional genomics reveals the importance of mitochondria in cell-to-cell phenotypic variation.

Mutations frequently have outcomes that differ across individuals, even when these individuals are genetically identical and share a common environment. Moreover, individual microbial and mammalian cells can vary substantially in their proliferation rates, stress tolerance, and drug resistance, with important implications for the treatment of infections and cancer. To investigate the causes of cell-to-cell variation in proliferation, we used a high-throughput automated microscopy assay to quantify the impact of deleting >1500 genes in yeast. Mutations affecting mitochondria were particularly variable in their outcome. In both mutant and wild-type cells mitochondrial membrane potential - but not amount - varied substantially across individual cells and predicted cell-to-cell variation in proliferation, mutation outcome, stress tolerance, and resistance to a clinically used anti-fungal drug. These results suggest an important role for cell-to-cell variation in the state of an organelle in single cell phenotypic variation.