Single-cell Genetic Analysis Research Articles

Massively parallel single-cell sequencing of diverse microbial populations.

Single-cell genetic heterogeneity is ubiquitous in microbial populations and an important aspect of microbial biology; however, we lack a broadly applicable and accessible method to study this heterogeneity in microbial populations. Here, we show a simple, robust and generalizable method for high-throughput single-cell sequencing of target genetic loci in diverse microbes using simple droplet microfluidics devices (droplet targeted amplicon sequencing; DoTA-seq). DoTA-seq serves as a platform to perform diverse assays for single-cell genetic analysis of microbial populations. Using DoTA-seq, we demonstrate the ability to simultaneously track the prevalence and taxonomic associations of >10 antibiotic-resistance genes and plasmids within human and mouse gut microbial communities. This workflow is a powerful and accessible platform for high-throughput single-cell sequencing of diverse microbial populations.

Molecular Markers of Blood Cell Populations Can Help Estimate Aging of the Immune System.

Aging of the immune system involves functional changes in individual cell populations, in hematopoietic tissues and at the systemic level. They are mediated by factors produced by circulating cells, niche cells, and at the systemic level. Age-related alterations in the microenvironment of the bone marrow and thymus cause a decrease in the production of naive immune cells and functional immunodeficiencies. Another result of aging and reduced tissue immune surveillance is the accumulation of senescent cells. Some viral infections deplete adaptive immune cells, increasing the risk of autoimmune and immunodeficiency conditions, leading to a general degradation in the specificity and effectiveness of the immune system in old age. During the COVID-19 pandemic, the state-of-the-art application of mass spectrometry, multichannel flow cytometry, and single-cell genetic analysis have provided vast data on the mechanisms of aging of the immune system. These data require systematic analysis and functional verification. In addition, the prediction of age-related complications is a priority task of modern medicine in the context of the increase in the aged population and the risk of premature death during epidemics. In this review, based on the latest data, we discuss the mechanisms of immune aging and highlight some cellular markers as indicators of age-related immune disbalance that increase the risk of senile diseases and infectious complications.

Clonal Hematopoiesis Evolves into Dendritic Cell Neoplasm through the Acquisition of UV Mutations in the Skin

Background Expansion of blood cells derived from a single mutated blood stem cell - clonal hematopoiesis - often precedes leukemic transformation. However, the circumstances that promote or prevent transformation are poorly understood. Here, we investigate the evolution of clonal hematopoiesis into blastic plasmacytoid dendritic cell neoplasm (BPDCN), an aggressive blood cancer that often presents with malignant cells isolated to the skin (referred to as skin-only disease). We gain a better understanding of the influence of site-specific selective pressures and the role of TET2 mutations, which may inform interventions to prevent disease progression. Methods We analyzed bone marrow and skin from 13 BPDCN patients using targeted, exome, and whole-genome sequencing, with germline controls. We performed multimodal single-cell sequencing (10x 3' v3.1 single-cell RNA-seq with genotyping of expressed variants) on bone marrow from 6 healthy donors (20,411 cells), 5 skin-only BPDCN patients with malignant cells in the skin but not conventionally detectable in marrow (36,018 cells), and 6 BPDCN patients with overt bone marrow involvement (30,582 cells). For functional studies, we targeted Tet2 using CRISPR/Cas9 in mouse blood progenitor cells immortalized by an estrogen receptor hormone binding domain fused to HoxB8, which undergo synchronized differentiation to myeloid and dendritic cells upon estrogen withdrawal. We used CellRanger, Seurat, RandomForest machine learning, and the R tidyverse package collection for bioinformatics. Results Genetics allowed us to reconstruct the evolution of BPDCN across bone marrow and skin (representative patient, panel a). Invariably, we detected founder mutations in marrow, including TET2 inactivation in 9/13 patients (two mutations, likely bi-allelic, in 5/9). Single-cell sequencing of marrow from 5 skin-only patients showed that pre-malignant mutant stem cells contributed to multiple lineages, and that TET2 mutated clones were myeloerythroid-biased. We generated a gene expression signature to identify rare malignant BPDCN cells in marrow of skin-only patients. In 3/5 patients, we identified rare cells (0.03-0.19%) with the transcriptional profile of fully transformed cells, and concurrent single-cell genetic analysis suggested that these cells originated from the skin tumor (panel b). To assess whether disseminated skin tumor cells establish bone marrow disease, we quantified mutational signatures: skin tumors and malignant BPDCN marrow cells in 5/5 patients harbored UV-induced mutations, likely acquired in a single skin-resident plasmacytoid dendritic cell (pDC) during malignant transformation. Finally, we edited Tet2 in mouse myelo-dendritic progenitors and tested the response to UV irradiation in vitro. In addition to observing that Tet2 inactivation increases dendritic cell commitment, the more striking result was a survival advantage of Tet2-mutated cells in the presence of UV (n = 6, fold change 1.803, P = 0.0012). These results highlight an unexpected function of TET2 that may predispose mutated pDCs to survive UV-induced DNA damage in the skin, leading to disease progression. Conclusion The complex evolution of BPDCN traverses multiple anatomic sites prior to full transformation. This allows for accurate sequencing of oncogenic events. Disease evolution frequently starts with acquisition of a leukemia-associated mutation in a multipotent blood stem cell, leading to clonal expansion. In the most frequently observed scenario, bi-allelic TET2 inactivation promotes myeloerythroid bias, increases dendritic cell commitment, and confers resistance to UV-mediated cell death. Subsequent evolution of skin-resident mutant pDCs leads to a high burden of UV-induced mutations and ultimate transformation. Dissemination of malignant cells, which can be detected by integrating single-cell gene expression and mutation profiles, initiates "retrograde" bone marrow disease. Our discovery that multiple anatomic sites - and local selective pressures - play a role in disease progression provides a template to study multi-site evolution of clonal hematopoiesis. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

A genome-wide library of MADM mice for single-cell genetic mosaic analysis.

Mosaic analysis with double markers (MADM) offers one approach to visualize and concomitantly manipulate genetically defined cells in mice with single-cell resolution. MADM applications include the analysis of lineage, single-cell morphology and physiology, genomic imprinting phenotypes, and dissection of cell-autonomous gene functions invivo in health and disease. Yet, MADM can only be applied to <25% of all mouse genes on select chromosomes to date. To overcome this limitation, we generate transgenic mice with knocked-in MADM cassettes near the centromeres of all 19 autosomes and validate their use across organs. With this resource, >96% of the entire mouse genome can now be subjected to single-cell genetic mosaic analysis. Beyond a proof of principle, we apply our MADM library to systematically trace sister chromatid segregation in distinct mitotic cell lineages. We find striking chromosome-specific biases in segregation patterns, reflecting a putative mechanism for the asymmetric segregation of genetic determinants in somatic stem cell division.

Single-cell genetic analysis of lung tumor cells based on self-driving micro-cavity array chip

Lung cancer is one of the common malignant tumors with a high incidence and mortality rate. Targeted therapies are efficient on lung cancer patients with specific gene mutations. Circulating tumor cells (CTCs) are used for liquid biopsy, providing genetic information for lung cancer treatment selection and prognosis. We developed a less costly self-driving micro-cavity array for simple molecular analysis at a single cell level to examine the genetic make-up of CTCs. This chip integrated sample detection structure and vacuum driving system to achieve cell loading, lysing, isothermal amplification (LAMP), and signal read-out on one chip. We used the “film-polydimethylsiloxane (PDMS) chip-film” structure and oil sealing method during amplification reaction to minimize water loss. We then conducted a LAMP assay using the self-driving device to detect epidermal growth factor receptor (EGFR) L858R mutation and identified an excellent linear in the range between 101-104 copies/μL (R2 = 0.997). We finally assessed the EGFR L858R gene expression of lung tumor cells (H1975 cells) as putative CTCs using the proposed detection platform. We discovered its ability to perform genetic analysis at the single-cell level. The EGFR L858R mutational gene expression levels were different in H1975 cells. In conclusion, the self-driving micro-cavity array is a less costly and simple tool for mutational gene profiling of single lung CTC. Besides, it can be used in personalized therapy and efficacy monitoring.

Development of High Throughput Single-Cell Analysis System for Circulating Tumor Cells Based on Digital Micromirror Device

Circulating tumor cells (CTCs) are widely known as useful biomarkers in the liquid biopsies of cancer patients. Recently, in addition to counting the number of CTCs, genetic analysis of CTCs provides critical insights into cancer metastases and add detailed clinical information that enhances patient care. It is widely known that CTCs are genetically heterogeneous, the molecular characterization of CTCs should be performed at the single-cell level. In fact, several studies have identified inter- and intra-patient heterogeneity in the mutational status of CTCs in metastatic breast and lung cancers. These studies also reported that CTCs related to drug resistance are novel therapeutic targets. Thus, genetic analysis of single CTCs has the potential to be widely applicable in personalized medicine and drug discovery. However, CTCs are extremely rare cells that only 1-100 cells are contained in 1 ml of blood, so the recovery of such extremely rare CTCs from the peripheral blood is technically challenging. So far, we have developed a CTC recovery system using a microcavity array (MCA), which demonstrates highly efficient recovery of cancer cells based on differences in cell size and deformability. Furthermore, we have proposed a novel cell manipulation method through the visualization of single cells through hydrogel encapsulation for subsequent genetic analysis of single CTCs. Subsequently, recovered CTCs can be subjected to a hydrogel-encapsulation for the following genetic analysis of single cells. Clinical studies indicated that the genetic analysis of CTCs from lung, pancreatic and gastric cancer patients was successfully achieved. However, this hydrogel encapsulation has limitations in throughput. In this study, we demonstrate a high-throughput single-cell analysis for CTCs using a multiple single-cell encapsulation system with a digital micromirror device (DMD). The novel multiple single-cell encapsulation systemwas composed of two optical systems: the wide-field fluorescence imaging system and the photopolymerization system equipped with DMD. The wide-field fluorescence imaging system using a CMOS sensor was designed to visualize 2D fluorescence imaging of the entire MCA (6.0 × 6.0 mm2). We evaluated the sensitivity of fluorescence detection of the wide-field fluorescence imaging system using the calibration slide. The limit of detection of the wide-field fluorescence imaging system was 2.1 × 102 molecules-Cy3/μm2, which is comparable to conventional fluorescence microscopy (1.0 × 102 molecules-Cy3/μm2). Generally, the expression of cellular marker protein, such as cytokeratin, was estimated to be 1.3 × 103 molecules/μm2. Therefore, our proposed system had enough sensitivity for the detection of antibody-stained CTCs. Furthermore, this wide-field fluorescence imaging system for CTC detection enables the rapid visualization of all stained cells within the field of the MCA via one-shot imaging. This rapid detection method also allows for the rapid completion of single-CTC manipulation. The photopolymerization system for single-cell encapsulation was controlled by the DMD. The curing light (λmax = 365 nm) modulated by the DMD was projected onto an MCA for hydrogel generation, and single-cell isolation by hydrogel-photopolymerization was examined at the optimized conditions. After recovery of cancer cells from whole blood onto MCA and staining by the fluorescent-labeled antibodies, cancer cells were identified by the wide-field imaging system. Then light irradiation (3 sec) was performed by the photopolymerization system. To minimize the area of the hydrogel reserved for a single cell, we newly designed the convex-type hydrogel. In the spike-in experiment, single-cell isolation rates were 97.6% (41/42) for NCI-H1975 cells (non-small cell lung cancer cell) and 94.4% (51/54) for NCI-N87 (gastric cancer cell) that were comparable with our previous study using fluorescence microscopy. With this proposed system, more than 50 single cells were encapsulated simultaneously within 1 min and isolated with an efficiency. Furthermore, single cells were successfully isolated from adjacent cells on the same microcavity without any contamination. Single cancer cell was partially encapsulated on the hydrogel, and the partial encapsulation allows us to subject them to whole genome amplification (WGA). Light irradiation and photopolymerizaion did not affect the quality of the amplified WGA products for single-cell genomic analyses. We are currently investigating single cell genetic analysis of metastatic cancer patients, and this developed multiple single-cell encapsulation system will improve the high throughput single-cell genetic analysis of CTCs in clinical samples. Our system provides an attractive application for other targets such as adherent cells, tissue samples, and microorganisms, in addition to widespread use in the isolation of CTCs for liquid biopsy.

Genetic Heterogeneity of Single Circulating Tumour Cells in Colorectal Carcinoma.

The aim of the present study was to isolate and investigate the genetic heterogeneities in single circulating tumour cells (CTCs) from patients with colorectal carcinoma (CRC). Twenty-eight single CTCs were collected from eight patients with CRC using a negative immunomagnetic enrichment method. After validation with glyceraldehyde 3-phosphate dehydrogenase (GAPDH) gene expression in 3 colon cancer cell lines, a panel of 19 genes were used to analyse the single CTCs (n = 28), primary colorectal carcinoma tissues (n = 8) and colon carcinoma cells (n = 6) using real-time qPCR. Genetic heterogeneities were assessed by comparing gene expression profiles of single CTCs from the different patients and in the same patient, respectively. Genetic profiling of the single CTCs showed extensive heterogeneities of the selected genes among the CTCs. Hierarchical clustering analyses exhibited two clusters of CTCs with differentially expressed genes, which highlighted different modifications from the primary carcinomas. Further, the genetic heterogeneities were observed between different patients or in the same patient. Finally, AKT1 expression was significantly (p = 0.0129) higher in single CTCs from CRC of advanced pathological stages (III or IV) CRC than in CTCs from CRC of early stages (I or II). Our findings suggest that single-cell genetic analysis can monitor the genetic heterogeneities and guide the personalised therapeutic targets in clinical sectors.

Single-Cell-Derived Primary Rectal Carcinoma Cell Lines Reflect Intratumor Heterogeneity Associated with Treatment Response.

The standard treatment of patients with locally advanced rectal cancer consists of preoperative chemoradiotherapy (CRT) followed by surgery. However, the response of individual tumors to CRT is extremely diverse, presenting a clinical dilemma. This broad variability in treatment response is likely attributable to intratumor heterogeneity (ITH). We addressed the impact of ITH on response to CRT by establishing single-cell-derived cell lines (SCDCL) from a treatment-naïve rectal cancer biopsy after xenografting. Individual SCDCLs derived from the same tumor responded profoundly different to CRT in vitro. Clonal reconstruction of the tumor and derived cell lines based on whole-exome sequencing revealed nine separate clusters with distinct proportions in the SCDCLs. Missense mutations in SV2A and ZWINT were clonal in the resistant SCDCL, but not detected in the sensitive SCDCL. Single-cell genetic analysis by multiplex FISH revealed the expansion of a clone with a loss of PIK3CA in the resistant SCDCL. Gene expression profiling by tRNA-sequencing identified the activation of the Wnt, Akt, and Hedgehog signaling pathways in the resistant SCDCLs. Wnt pathway activation in the resistant SCDCLs was confirmed using a reporter assay. Our model system of patient-derived SCDCLs provides evidence for the critical role of ITH for treatment response in patients with rectal cancer and shows that distinct genetic aberration profiles are associated with treatment response. We identified specific pathways as the molecular basis of treatment response of individual clones, which could be targeted in resistant subclones of a heterogenous tumor.

A Genome-Wide Library of MADM Mice for Single-Cell Genetic Mosaic Analysis

Mosaic Analysis with Double Markers (MADM) offers a unique approach to visualize and concomitantly manipulate genetically-defined cells in mice with single-cell resolution. MADM applications include the analysis of lineage; single-cell morphology and physiology; genomic imprinting phenotypes; and dissection of cell-autonomous gene functions in vivo in health and disease. Yet, MADM could only be applied to 96% of the entire mouse genome can now be subjected to single-cell genetic mosaic analysis. Beyond proof-of-principle, we applied our MADM library to systematically trace sister chromatid segregation in distinct mitotic cell lineages. We found striking chromosome-specific biases in segregation patterns, reflecting a putative mechanism for the asymmetric segregation of genetic determinants in somatic stem cell division.

Abstract 3426: Combining cell barcoding and CRISPR sgRNA libraries with targeted gene expression for single-cell genetic analysis of tumor metastasis

Abstract Pooled lentiviral libraries of CRISPR sgRNAs to mediate genome-wide gene knockout have become an invaluable tool for uncovering the functional genetic drivers required for a biological response. Another type of pooled lentiviral library designed with unique DNA sequence tags have also been used to label large populations of cells with unique cell-specific barcodes which allows monitoring changes in sub-populations of cells with distinct phenotypes over time. We have combined cell barcodes with CRISPR sgRNA to construct libraries that enable the identification of multiple occurrences of a common phenotypic response from independent transductions of the same sgRNA effector. Specifically, we demonstrate how this sort of library can be used to identify genes whose activation promotes metastasis of tumors derived from MDA-MB-231 cells engrafted into mice after transduction with a barcoded CRISPR-activation (CRISPRa) sgRNA library. By incorporating multiple barcodes with each sgRNA effector, it is possible to see that, not only are cells in metastatic tumors more likely to have a particular sgRNA targeted to a certain gene, but also that independent transductions of that sgRNA sequence lead to multiple independent metastatic events. With multiple independent clones producing the same phenotype, it is possible to confidently isolate the sgRNA, and by implication, the increased activation of its gene target, as the primary cause of the metastatic phenotype. Citation Format: Alex Chenchik, Paul Diehl, Mikhail Makhanov. Combining cell barcoding and CRISPR sgRNA libraries with targeted gene expression for single-cell genetic analysis of tumor metastasis [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 3426.

Understanding mitochondrial DNA maintenance disorders at the single muscle fibre level.

Clonal expansion of mitochondrial DNA (mtDNA) deletions is an important pathological mechanism in adults with mtDNA maintenance disorders, leading to a mosaic mitochondrial respiratory chain deficiency in skeletal muscle. This study had two aims: (i) to determine if different Mendelian mtDNA maintenance disorders showed similar pattern of mtDNA deletions and respiratory chain deficiency and (ii) to investigate the correlation between the mitochondrial genetic defect and corresponding respiratory chain deficiency. We performed a quantitative analysis of respiratory chain deficiency, at a single cell level, in a cohort of patients with mutations in mtDNA maintenance genes. Using the same tissue section, we performed laser microdissection and single cell genetic analysis to investigate the relationship between mtDNA deletion characteristics and the respiratory chain deficiency. The pattern of respiratory chain deficiency is similar with different genetic defects. We demonstrate a clear correlation between the level of mtDNA deletion and extent of respiratory chain deficiency within a single cell. Long-range and single molecule PCR shows the presence of multiple mtDNA deletions in approximately one-third of all muscle fibres. We did not detect evidence of a replicative advantage for smaller mtDNA molecules in the majority of fibres, but further analysis is needed to provide conclusive evidence.

EGFR point mutation detection of single circulating tumor cells for lung cancer using a micro-well array

In view of their critical function in metastasis, characterization of single circulating tumor cells (CTCs) can provide important clinical information to monitor tumor progression and guide personal therapy. Single-cell genetic analysis methods based on microfluidics have some inherent shortcomings such as complicated operation, low throughput, and expensive equipment requirements. To overcome these barriers, we developed a simple and open micro-well array containing 26,208 units for either nuclear acids or single-cell genetic analysis. Through modification of the polydimethylsiloxane surface and optimization of chip packaging, we addressed protein adsorption and solution evaporation for PCR amplification on a chip. In the detection of epidermal growth factor receptor (EGFR) exon gene 21, this micro-well array demonstrated good linear correlation at a DNA concentration from 1 × 101 to 1 × 105 copies/μL (R2 = 0.9877). We then successfully integrated cell capture, lysis, PCR amplification, and signal read-out on the micro-well array, enabling the rapid and simple genetic analysis of single cells. This device was used to detect duplex EGFR mutation genes of lung cancer cell lines (H1975 and A549 cells) and normal leukocytes, demonstrating the ability to perform high-throughput, massively parallel duplex gene analysis at the single-cell level. Different types of point mutations (EGFR-L858R mutation or EGFR-T790M mutation) were detected in single H1975 cells, further validating the significance of single-cell level gene detection. In addition, this method showed a good performance in the heterogeneity detection of individual CTCs from lung cancer patients, required for micro-invasive cancer monitoring and treatment selection.

Discovery of a Vascular Endothelial Stem Cell (VESC) Population Required for Vascular Regeneration and Tissue Maintenance

The roles that blood vessels play in the maintenance of organs and tissues in addition to the delivery of oxygen and nutrients are being gradually clarified. The maintenance of tissue-specific organ stem cells, such as hematopoietic and neuronal stem cells, is supported by endothelial cells (ECs), which represent an important component of the stem cell niche. The maintenance of organogenesis, for example, osteogenesis and liver generation/regeneration, is supported by molecules referred to as "angiocrine signals" secreted by EC. The mechanisms responsible for the well-known functions of blood vessels, such as thermoregulation and metabolism, especially removal of local metabolites, have now been determined at the molecular level. Following the development of single-cell genetic analysis, blood cell heterogeneity, especially of mural cell populations, has been established and tissue-specific blood vessel formation and function are now also understood at the molecular level. Among the heterogeneous populations of ECs, it seems that a stem cell population with the ability to maintain the production of ECs long-term is present in pre-existing blood vessels. Neovascularization by therapeutic angiogenesis yields benefits in many diseases, not only ischemic disease but also metabolic disease and other vascular diseases. Therefore, vascular endothelial stem cells should be considered to use in vascular regeneration therapy.

Single-cell genetic analysis of clonal dynamics in colorectal adenomas indicates CDX2 gain as a predictor of recurrence.

Colorectal adenomas are common precancerous lesions with the potential for malignant transformation to colorectal adenocarcinoma. Endoscopic polypectomy provides an opportunity for cancer prevention; however, recurrence rates are high. We collected formalin-fixed paraffin-embedded tissue of 15 primary adenomas with recurrence, 15 adenomas without recurrence, and 14 matched pair samples (primary adenoma and the corresponding recurrent adenoma). The samples were analysed by array-comparative genomic hybridisation (aCGH) and single-cell multiplex interphase fluorescence in situ hybridisation (miFISH) to understand clonal evolution, to examine the dynamics of copy number alterations (CNAs) and to identify molecular markers for recurrence prediction. The miFISH probe panel consisted of 14 colorectal carcinogenesis-relevant genes (COX2, PIK3CA, APC, CLIC1, EGFR, MYC, CCND1, CDX2, CDH1, TP53, HER2, SMAD7, SMAD4 and ZNF217), and a centromere probe (CEP10). The aCGH analysis confirmed the genetic landscape typical for colorectal tumorigenesis, that is, CNAs of chromosomes 7, 13q, 18 and 20q. Focal aberrations (≤10 Mbp) were mapped to chromosome bands 6p22.1-p21.33 (33.3%), 7q22.1 (31.4%) and 16q21 (29.4%). MiFISH detected gains of EGFR (23.6%), CDX2 (21.8%) and ZNF217 (18.2%). Most adenomas exhibited a major clone population which was accompanied by multiple smaller clone populations. Gains of CDX2 were exclusively seen in primary adenomas with recurrence (25%) compared to primary adenomas without recurrence (0%). Generation of phylogenetic trees for matched pair samples revealed four distinct patterns of clonal dynamics. In conclusion, adenoma development and recurrence are complex genetic processes driven by multiple CNAs whose evaluations by miFISH, with emphasis on CDX2, might serve as a predictor of recurrence.

An integrated microfluidic platform for size-selective single-cell trapping of monocytes from blood.

Reliable separation and isolation of target single cells from bodily fluids with high purity is of great significance for an accurate and quantitative understanding of the cellular heterogeneity. Here, we describe a fully integrated single-blood-cell analysis platform capable of size-selective cell separation from a population containing a wide distribution of sizes such as diluted blood sample and highly efficient entrapment of single monocytes. The spiked single U937 cells (human monocyte cell line) are separated in sequence by two different-sized microfilters for removing large cell clumps, white blood cells, and red blood cells and then discriminated by dielectrophoretic force and isolated individually by downstream single-cell trapping arrays. When 2% hematocrit blood cells with a final ratio of 1:1000 U937 cells were introduced under the flow rate of 0.2 ml/h, 400 U937 cells were trapped sequentially and deterministically within 40 s with single-cell occupancy of up to 85%. As a proof-of-concept, we also demonstrated single monocyte isolation from diluted blood using the integrated microfluidic device. This size-selective, label-free, and live-cell enrichment microfluidic single blood-cell isolation platform for the processing of cancer and blood cells has a myriad of applications in areas such as single-cell genetic analysis, stem cell biology, point-of-care diagnostics, and cancer diagnostics.

Single-cell genetic analysis validates cytopathological identification of circulating cancer cells in patients with clear cell renal cell carcinoma.

ContextCirculating Rare Cells (CRC) are non-haematological cells circulating in blood. They include Circulating Cancer Cells (CCC) and cells with uncertain malignant features (CRC-UMF) according to cytomorphology. Clear cell renal cell carcinomas frequently bear a mutated Von Hippel-Lindau (VHL) gene.AimTo match blind genetic analysis of CRC and tumor samples with CRC cytopathological diagnosis.Results29/30 patients harboured CRC (20 harboured CCC, 29 CRC-UMF) and 25/29 patients carried VHL mutations in their tumour. 205 single CRC (64 CCC, 141 CRC-UMF) provided genetic data. 57/57 CCC and 104/125 CRC-UMF from the 25 patients with VHL-mutated tumor carried the same VHL mutation detected in the tumor. Seven CCC and 16 CRC-UMF did not carry VHL mutations but were found in patients with wild-type VHL tumor tissue.ConclusionsAll the CCC and 83,2% (104/125) of the CRC-UMF were found to carry the same VHL mutation identified in the corresponding tumorous tissue, validating cytopathological identification of CCC in patients with clear cell renal cell carcinoma.MethodsThe blood of 30 patients with clear cell renal cell carcinoma was treated by ISET® for CRC isolation, cytopathology and single-cell VHL mutations analysis, performed blindly and compared to VHL mutations of corresponding tumor tissues and leukocytes.

Intelligent image-based in situ single-cell isolation

Quantifying heterogeneities within cell populations is important for many fields including cancer research and neurobiology; however, techniques to isolate individual cells are limited. Here, we describe a high-throughput, non-disruptive, and cost-effective isolation method that is capable of capturing individually targeted cells using widely available techniques. Using high-resolution microscopy, laser microcapture microscopy, image analysis, and machine learning, our technology enables scalable molecular genetic analysis of single cells, targetable by morphology or location within the sample.

Heterogeneity of Metazoan Cells and Beyond: To Integrative Analysis of Cellular Populations at Single-Cell Level.

In this paper, we review some of the recent advances in cellular heterogeneity and single-cell analysis methods. In modern research of cellular heterogeneity, there are four major approaches: analysis of pooled samples, single-cell analysis, high-throughput single-cell analysis, and lately integrated analysis of cellular population at a single-cell level. Recently developed high-throughput single-cell genetic analysis methods such as RNA-Seq require purification step and destruction of an analyzed cell often are providing a snapshot of the investigated cell without spatiotemporal context. Correlative analysis of multiparameter morphological, functional, and molecular information is important for differentiation of more uniform groups in the spectrum of different cell types. Simplified distributions (histograms and 2D plots) can underrepresent biologically significant subpopulations. Future directions may include the development of nondestructive methods for dissecting molecular events in intact cells, simultaneous correlative cellular analysis of phenotypic and molecular features by hybrid technologies such as imaging flow cytometry, and further progress in supervised and non-supervised statistical analysis algorithms.

Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia.

Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype–phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy.

Abstract 4030: Celsee™ SingleCell Chip can retrieve rare single cells with 100% efficiency for genetic analysis

Abstract Tumors are comprised of heterogeneous cells. Only a specific or rare population of tumor cells is capable of metastasizing through blood. While mapping out the genome of cancer cells, gene expression variations indicative of more aggressive cancer cells might be missed among the noise. Therefore, single cell gene expression and mutation analysis provide a more comprehensive and most precise information about the heterogeneity of cancer progression and metastasis. Although there has been a surge in technologies used for selection and analysis of single cells, single cell analysis of rare cells such as circulating tumor cells (CTCs) is fraught with technical challenges. Among many used techniques to isolate single cells, the most common cell separation method is cell sorting by flow cytometry, which requires cell labeling. The numerous steps involved in cell labelling and centrifugation result in significant cell loss and changes in gene expression. In addition, centrifugation may also cause shear-induced gene expression changes in viable cells. For other single cell analysis platforms, there is a minimum input of cells ranging from 200 - 1000 cells. Rare cells like CTCs are found in the range of 1-10 per mL of blood. Another challenge is that the input volume required for these systems is very low usually in microliters. Here, we introduce a novel microfluidic chip with 250,000 microwells which captures cells at 100% efficiency down to one cell with a dynamic range over 5 logs. The underlying principle of this technology is that the geometric pattern of the microfluidic chip captures a single cell from an initial volume of up to 1 mL of fluid due to cell settling. The unique microwell structure promotes easy fluid exchange without perturbing the cells from their captured locations, thereby eliminating cell loss during multistep downstream processing. Preliminary tests have shown that single or cluster of spiked cancer cells in blood can be immunostained, both live or fixed and can also be retrieved very efficiently from this chip using a micro capillary. The retrieved single cells can further be used for several single cell genetic analysis. We will present data describing cancer gene expression and gene mutation analysis in isolated single cells. Citation Format: Kalyan Handique, Priya Gogoi, William Chow, Kyle Gleason, Auston Payne, Vishal Premdev Sharma, Yixin Wang. Celsee™ SingleCell Chip can retrieve rare single cells with 100% efficiency for genetic analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4030. doi:10.1158/1538-7445.AM2017-4030