Single-cell genome sequencing: current state of the science.
Gawad Charles,Koh Winston,Quake Stephen R
Nature reviews. Genetics
The field of single-cell genomics is advancing rapidly and is generating many new insights into complex biological systems, ranging from the diversity of microbial ecosystems to the genomics of human cancer. In this Review, we provide an overview of the current state of the field of single-cell genome sequencing. First, we focus on the technical challenges of making measurements that start from a single molecule of DNA, and then explore how some of these recent methodological advancements have enabled the discovery of unexpected new biology. Areas highlighted include the application of single-cell genomics to interrogate microbial dark matter and to evaluate the pathogenic roles of genetic mosaicism in multicellular organisms, with a focus on cancer. We then attempt to predict advances we expect to see in the next few years.
Multiregion whole-exome sequencing of matched primary and metastatic tumors revealed genomic heterogeneity and suggested polyclonal seeding in colorectal cancer metastasis.
Wei Q,Ye Z,Zhong X,Li L,Wang C,Myers R E,Palazzo J P,Fortuna D,Yan A,Waldman S A,Chen X,Posey J A,Basu-Mallick A,Jiang B H,Hou L,Shu J,Sun Y,Xing J,Li B,Yang H
Annals of oncology : official journal of the European Society for Medical Oncology
Background:Distant metastasis accounts for 90% of deaths from colorectal cancer (CRC). Genomic heterogeneity has been reported in various solid malignancies, but remains largely under-explored in metastatic CRC tumors, especially in primary to metastatic tumor evolution. Patients and methods:We conducted high-depth whole-exome sequencing in multiple regions of matched primary and metastatic CRC tumors. Using a total of 28 tumor, normal, and lymph node tissues, we analyzed inter- and intra-individual heterogeneity, inferred the tumor subclonal architectures, and depicted the subclonal evolutionary routes from primary to metastatic tumors. Results:CRC has significant inter-individual but relatively limited intra-individual heterogeneity. Genomic landscapes were more similar within primary, metastatic, or lymph node tumors than across these types. Metastatic tumors exhibited less intratumor heterogeneity than primary tumors, indicating that single-region sequencing may be adequate to identify important metastasis mutations to guide treatment. Remarkably, all metastatic tumors inherited multiple genetically distinct subclones from primary tumors, supporting a possible polyclonal seeding mechanism for metastasis. Analysis of one patient with the trio samples of primary, metastatic, and lymph node tumors supported a mechanism of synchronous parallel dissemination from the primary to metastatic tumors that was not mediated through lymph nodes. Conclusions:In CRC, metastatic tumors have different but less heterogeneous genomic landscapes than primary tumors. It is possible that CRC metastasis is, at least partly, mediated through a polyclonal seeding mechanism. These findings demonstrated the rationale and feasibility for identifying and targeting primary tumor-derived metastasis-potent subclones for the prediction, prevention, and treatment of CRC metastasis.
Spatial Intratumor Genomic Heterogeneity within Localized Prostate Cancer Revealed by Single-nucleus Sequencing.
Su Fei,Zhang Wei,Zhang Dalei,Zhang Yaqun,Pang Cheng,Huang Yingying,Wang Miao,Cui Luwei,He Lei,Zhang Jinsong,Zou Lihui,Zhang Junhua,Li Wenqinq,Li Lin,Shao Jianyong,Ma Jie,Xiao Fei,Liu Ming
BACKGROUND:Prostate adenocarcinoma (PCa) is a complex genetic disease, and the implementation of personalized treatment in PCa faces challenges due to significant inter- and intrapatient tumor heterogeneities. OBJECTIVE:To systematically explore the genomic complexity of tumor cells with different Gleason scores (GSs) in PCa. DESIGN, SETTING, AND PARTICIPANTS:We performed single-cell whole genome sequencing of 17 tumor cells from localized lesions with distinct GS and matched four normal samples from two prostatectomy patients. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS:All classes of genomic alterations were identified, including substitutions, insertions/deletions, copy number alterations, and rearrangements. RESULTS AND LIMITATIONS:Significant spatial, intra- and intertumoral heterogeneities were observed at the cellular level. In the patient 1, all cells shared the same TP53 driver mutation, implying a monoclonal origin of PCa. In the patient 2, only a subpopulation of cells contained the TP53 driver mutation, whereas other cells carried different driver mutations, indicating a typical polyclonal model with separate clonal cell expansions. The tumor cells from different sides of prostate owned various mutation patterns. Considerable neoantigens were predicted among different cells, implying unknown immune editing components helping prostate tumor cells escaping from immune surveillance. CONCLUSIONS:There is a significant spatial genomic heterogeneity even in the same PCa patient. Our study also provides the first genome-wide evidence at single-cell level, supporting that the origin of PCa could be either polyclonal or monoclonal, which has implications for treatment decisions for prostate cancer. PATIENT SUMMARY:We reported the first single-cell whole genomic data of prostate adenocarcinoma (PCa) from different Gleason scores. Identification of these genetic alterations may help understand PCa tumor progression and clonal evolution.
Single-cell profiling of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis.
Savas Peter,Virassamy Balaji,Ye Chengzhong,Salim Agus,Mintoff Christopher P,Caramia Franco,Salgado Roberto,Byrne David J,Teo Zhi L,Dushyanthen Sathana,Byrne Ann,Wein Lironne,Luen Stephen J,Poliness Catherine,Nightingale Sophie S,Skandarajah Anita S,Gyorki David E,Thornton Chantel M,Beavis Paul A,Fox Stephen B, ,Darcy Phillip K,Speed Terence P,Mackay Laura K,Neeson Paul J,Loi Sherene
The quantity of tumor-infiltrating lymphocytes (TILs) in breast cancer (BC) is a robust prognostic factor for improved patient survival, particularly in triple-negative and HER2-overexpressing BC subtypes. Although T cells are the predominant TIL population, the relationship between quantitative and qualitative differences in T cell subpopulations and patient prognosis remains unknown. We performed single-cell RNA sequencing (scRNA-seq) of 6,311 T cells isolated from human BCs and show that significant heterogeneity exists in the infiltrating T cell population. We demonstrate that BCs with a high number of TILs contained CD8 T cells with features of tissue-resident memory T (T) cell differentiation and that these CD8 T cells expressed high levels of immune checkpoint molecules and effector proteins. A CD8 T gene signature developed from the scRNA-seq data was significantly associated with improved patient survival in early-stage triple-negative breast cancer (TNBC) and provided better prognostication than CD8 expression alone. Our data suggest that CD8 T cells contribute to BC immunosurveillance and are the key targets of modulation by immune checkpoint inhibition. Further understanding of the development, maintenance and regulation of T cells will be crucial for successful immunotherapeutic development in BC.
Single-cell sequencing reveals karyotype heterogeneity in murine and human malignancies.
Bakker Bjorn,Taudt Aaron,Belderbos Mirjam E,Porubsky David,Spierings Diana C J,de Jong Tristan V,Halsema Nancy,Kazemier Hinke G,Hoekstra-Wakker Karina,Bradley Allan,de Bont Eveline S J M,van den Berg Anke,Guryev Victor,Lansdorp Peter M,Colomé-Tatché Maria,Foijer Floris
BACKGROUND:Chromosome instability leads to aneuploidy, a state in which cells have abnormal numbers of chromosomes, and is found in two out of three cancers. In a chromosomal instable p53 deficient mouse model with accelerated lymphomagenesis, we previously observed whole chromosome copy number changes affecting all lymphoma cells. This suggests that chromosome instability is somehow suppressed in the aneuploid lymphomas or that selection for frequently lost/gained chromosomes out-competes the CIN-imposed mis-segregation. RESULTS:To distinguish between these explanations and to examine karyotype dynamics in chromosome instable lymphoma, we use a newly developed single-cell whole genome sequencing (scWGS) platform that provides a complete and unbiased overview of copy number variations (CNV) in individual cells. To analyse these scWGS data, we develop AneuFinder, which allows annotation of copy number changes in a fully automated fashion and quantification of CNV heterogeneity between cells. Single-cell sequencing and AneuFinder analysis reveals high levels of copy number heterogeneity in chromosome instability-driven murine T-cell lymphoma samples, indicating ongoing chromosome instability. Application of this technology to human B cell leukaemias reveals different levels of karyotype heterogeneity in these cancers. CONCLUSION:Our data show that even though aneuploid tumours select for particular and recurring chromosome combinations, single-cell analysis using AneuFinder reveals copy number heterogeneity. This suggests ongoing chromosome instability that other platforms fail to detect. As chromosome instability might drive tumour evolution, karyotype analysis using single-cell sequencing technology could become an essential tool for cancer treatment stratification.
Single-cell multiomics sequencing and analyses of human colorectal cancer.
Bian Shuhui,Hou Yu,Zhou Xin,Li Xianlong,Yong Jun,Wang Yicheng,Wang Wendong,Yan Jia,Hu Boqiang,Guo Hongshan,Wang Jilian,Gao Shuai,Mao Yunuo,Dong Ji,Zhu Ping,Xiu Dianrong,Yan Liying,Wen Lu,Qiao Jie,Tang Fuchou,Fu Wei
Science (New York, N.Y.)
Although genomic instability, epigenetic abnormality, and gene expression dysregulation are hallmarks of colorectal cancer, these features have not been simultaneously analyzed at single-cell resolution. Using optimized single-cell multiomics sequencing together with multiregional sampling of the primary tumor and lymphatic and distant metastases, we developed insights beyond intratumoral heterogeneity. Genome-wide DNA methylation levels were relatively consistent within a single genetic sublineage. The genome-wide DNA demethylation patterns of cancer cells were consistent in all 10 patients whose DNA we sequenced. The cancer cells' DNA demethylation degrees clearly correlated with the densities of the heterochromatin-associated histone modification H3K9me3 of normal tissue and those of repetitive element long interspersed nuclear element 1. Our work demonstrates the feasibility of reconstructing genetic lineages and tracing their epigenomic and transcriptomic dynamics with single-cell multiomics sequencing.
Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas.
Hou Yu,Guo Huahu,Cao Chen,Li Xianlong,Hu Boqiang,Zhu Ping,Wu Xinglong,Wen Lu,Tang Fuchou,Huang Yanyi,Peng Jirun
Single-cell genome, DNA methylome, and transcriptome sequencing methods have been separately developed. However, to accurately analyze the mechanism by which transcriptome, genome and DNA methylome regulate each other, these omic methods need to be performed in the same single cell. Here we demonstrate a single-cell triple omics sequencing technique, scTrio-seq, that can be used to simultaneously analyze the genomic copy-number variations (CNVs), DNA methylome, and transcriptome of an individual mammalian cell. We show that large-scale CNVs cause proportional changes in RNA expression of genes within the gained or lost genomic regions, whereas these CNVs generally do not affect DNA methylation in these regions. Furthermore, we applied scTrio-seq to 25 single cancer cells derived from a human hepatocellular carcinoma tissue sample. We identified two subpopulations within these cells based on CNVs, DNA methylome, or transcriptome of individual cells. Our work offers a new avenue of dissecting the complex contribution of genomic and epigenomic heterogeneities to the transcriptomic heterogeneity within a population of cells.
Application of single-cell RNA sequencing in optimizing a combinatorial therapeutic strategy in metastatic renal cell carcinoma.
Kim Kyu-Tae,Lee Hye Won,Lee Hae-Ock,Song Hye Jin,Jeong Da Eun,Shin Sang,Kim Hyunho,Shin Yoojin,Nam Do-Hyun,Jeong Byong Chang,Kirsch David G,Joo Kyeung Min,Park Woong-Yang
BACKGROUND:Intratumoral heterogeneity hampers the success of marker-based anticancer treatment because the targeted therapy may eliminate a specific subpopulation of tumor cells while leaving others unharmed. Accordingly, a rational strategy minimizing survival of the drug-resistant subpopulation is essential to achieve long-term therapeutic efficacy. RESULTS:Using single-cell RNA sequencing (RNA-seq), we examine the intratumoral heterogeneity of a pair of primary renal cell carcinoma and its lung metastasis. Activation of drug target pathways demonstrates considerable variability between the primary and metastatic sites, as well as among individual cancer cells within each site. Based on the prediction of multiple drug target pathway activation, we derive a combinatorial regimen co-targeting two mutually exclusive pathways for the metastatic cancer cells. This combinatorial strategy shows significant increase in the treatment efficacy over monotherapy in the experimental validation using patient-derived xenograft platforms in vitro and in vivo. CONCLUSIONS:Our findings demonstrate the investigational application of single-cell RNA-seq in the design of an anticancer regimen. The approach may overcome intratumoral heterogeneity which hampers the success of precision medicine.
Single-cell transcriptome conservation in cryopreserved cells and tissues.
Guillaumet-Adkins Amy,Rodríguez-Esteban Gustavo,Mereu Elisabetta,Mendez-Lago Maria,Jaitin Diego A,Villanueva Alberto,Vidal August,Martinez-Marti Alex,Felip Enriqueta,Vivancos Ana,Keren-Shaul Hadas,Heath Simon,Gut Marta,Amit Ido,Gut Ivo,Heyn Holger
A variety of single-cell RNA preparation procedures have been described. So far, protocols require fresh material, which hinders complex study designs. We describe a sample preservation method that maintains transcripts in viable single cells, allowing one to disconnect time and place of sampling from subsequent processing steps. We sequence single-cell transcriptomes from >1000 fresh and cryopreserved cells using 3'-end and full-length RNA preparation methods. Our results confirm that the conservation process did not alter transcriptional profiles. This substantially broadens the scope of applications in single-cell transcriptomics and could lead to a paradigm shift in future study designs.
Spatially and functionally distinct subclasses of breast cancer-associated fibroblasts revealed by single cell RNA sequencing.
Bartoschek Michael,Oskolkov Nikolay,Bocci Matteo,Lövrot John,Larsson Christer,Sommarin Mikael,Madsen Chris D,Lindgren David,Pekar Gyula,Karlsson Göran,Ringnér Markus,Bergh Jonas,Björklund Åsa,Pietras Kristian
Cancer-associated fibroblasts (CAFs) are a major constituent of the tumor microenvironment, although their origin and roles in shaping disease initiation, progression and treatment response remain unclear due to significant heterogeneity. Here, following a negative selection strategy combined with single-cell RNA sequencing of 768 transcriptomes of mesenchymal cells from a genetically engineered mouse model of breast cancer, we define three distinct subpopulations of CAFs. Validation at the transcriptional and protein level in several experimental models of cancer and human tumors reveal spatial separation of the CAF subclasses attributable to different origins, including the peri-vascular niche, the mammary fat pad and the transformed epithelium. Gene profiles for each CAF subtype correlate to distinctive functional programs and hold independent prognostic capability in clinical cohorts by association to metastatic disease. In conclusion, the improved resolution of the widely defined CAF population opens the possibility for biomarker-driven development of drugs for precision targeting of CAFs.
Diverse modes of clonal evolution in HBV-related hepatocellular carcinoma revealed by single-cell genome sequencing.
Duan Meng,Hao Junfeng,Cui Sijia,Worthley Daniel L,Zhang Shu,Wang Zhichao,Shi Jieyi,Liu Longzi,Wang Xiaoying,Ke Aiwu,Cao Ya,Xi Ruibin,Zhang Xiaoming,Zhou Jian,Fan Jia,Li Chong,Gao Qiang
Hepatocellular carcinoma (HCC) is a cancer of substantial morphologic, genetic and phenotypic diversity. Yet we do not understand the relationship between intratumor heterogeneity and the associated morphologic/histological characteristics of the tumor. Using single-cell whole-genome sequencing to profile 96 tumor cells (30-36 each) and 15 normal liver cells (5 each), collected from three male patients with HBV-associated HCC, we confirmed that copy number variations occur early in hepatocarcinogenesis but thereafter remain relatively stable throughout tumor progression. Importantly, we showed that specific HCCs can be of monoclonal or polyclonal origins. Tumors with confluent multinodular morphology are the typical polyclonal tumors and display the highest intratumor heterogeneity. In addition to mutational and copy number profiles, we dissected the clonal origins of HCC using HBV-derived foreign genomic markers. In monoclonal HCC, all the tumor single cells exhibit the same HBV integrations, indicating that HBV integration is an early driver event and remains extremely stable during tumor progression. In addition, our results indicated that both models of metastasis, late dissemination and early seeding, have a role in HCC progression. Notably, early intrahepatic spreading of the initiating clone leads to the formation of synchronous multifocal tumors. Meanwhile, we identified a potential driver gene ZNF717 in HCC, which exhibits a high frequency of mutation at both single-cell and population levels, as a tumor suppressor acting through regulating the IL-6/STAT3 pathway. These findings highlight multiple distinct tumor evolutionary mechanisms in HCC, which suggests the need for specific treatment strategies.
SiFit: inferring tumor trees from single-cell sequencing data under finite-sites models.
Zafar Hamim,Tzen Anthony,Navin Nicholas,Chen Ken,Nakhleh Luay
Single-cell sequencing enables the inference of tumor phylogenies that provide insights on intra-tumor heterogeneity and evolutionary trajectories. Recently introduced methods perform this task under the infinite-sites assumption, violations of which, due to chromosomal deletions and loss of heterozygosity, necessitate the development of inference methods that utilize finite-sites models. We propose a statistical inference method for tumor phylogenies from noisy single-cell sequencing data under a finite-sites model. The performance of our method on synthetic and experimental data sets from two colorectal cancer patients to trace evolutionary lineages in primary and metastatic tumors suggests that employing a finite-sites model leads to improved inference of tumor phylogenies.
Nanogrid single-nucleus RNA sequencing reveals phenotypic diversity in breast cancer.
Gao Ruli,Kim Charissa,Sei Emi,Foukakis Theodoros,Crosetto Nicola,Chan Leong-Keat,Srinivasan Maithreyan,Zhang Hong,Meric-Bernstam Funda,Navin Nicholas
Single cell RNA sequencing has emerged as a powerful tool for resolving transcriptional diversity in tumors, but is limited by throughput, cost and the ability to process archival frozen tissue samples. Here we develop a high-throughput 3' single-nucleus RNA sequencing approach that combines nanogrid technology, automated imaging, and cell selection to sequence up to ~1800 single nuclei in parallel. We compare the transcriptomes of 485 single nuclei to 424 single cells in a breast cancer cell line, which shows a high concordance (93.34%) in gene levels and abundance. We also analyze 416 nuclei from a frozen breast tumor sample and 380 nuclei from normal breast tissue. These data reveal heterogeneity in cancer cell phenotypes, including angiogenesis, proliferation, and stemness, and a minor subpopulation (19%) with many overexpressed cancer genes. Our studies demonstrate the utility of nanogrid single-nucleus RNA sequencing for studying the transcriptional programs of tumor nuclei in frozen archival tissue samples.Single cell RNA sequencing is a powerful tool for understanding cellular diversity but is limited by cost, throughput and sample preparation. Here the authors use nanogrid technology with integrated imaging to sequence thousands of cancer nuclei in parallel from fresh or frozen tissue.
Single-Cell RNA Sequencing in Cancer: Lessons Learned and Emerging Challenges.
Suvà Mario L,Tirosh Itay
Bulk genomic analyses and expression profiling of clinical specimens have shaped much of our understanding of cancer in patients. However, human tumors are intricate ecosystems composed of diverse cells, including malignant, immune, and stromal subsets, whose precise characterization is masked by bulk genomic methods. Single-cell genomic techniques have emerged as powerful approaches to dissect human tumors at the resolution of individual cells, providing a compelling approach to deciphering cancer biology. Here, we discuss some of the common themes emerging from initial studies of single-cell RNA sequencing in cancer and then highlight challenges in cancer biology for which emerging single-cell genomics methods may provide a compelling approach.
Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments.
Tian Luyi,Dong Xueyi,Freytag Saskia,Lê Cao Kim-Anh,Su Shian,JalalAbadi Abolfazl,Amann-Zalcenstein Daniela,Weber Tom S,Seidi Azadeh,Jabbari Jafar S,Naik Shalin H,Ritchie Matthew E
Single cell RNA-sequencing (scRNA-seq) technology has undergone rapid development in recent years, leading to an explosion in the number of tailored data analysis methods. However, the current lack of gold-standard benchmark datasets makes it difficult for researchers to systematically compare the performance of the many methods available. Here, we generated a realistic benchmark experiment that included single cells and admixtures of cells or RNA to create 'pseudo cells' from up to five distinct cancer cell lines. In total, 14 datasets were generated using both droplet and plate-based scRNA-seq protocols. We compared 3,913 combinations of data analysis methods for tasks ranging from normalization and imputation to clustering, trajectory analysis and data integration. Evaluation revealed pipelines suited to different types of data for different tasks. Our data and analysis provide a comprehensive framework for benchmarking most common scRNA-seq analysis steps.
Profiling human breast epithelial cells using single cell RNA sequencing identifies cell diversity.
Nguyen Quy H,Pervolarakis Nicholas,Blake Kerrigan,Ma Dennis,Davis Ryan Tevia,James Nathan,Phung Anh T,Willey Elizabeth,Kumar Raj,Jabart Eric,Driver Ian,Rock Jason,Goga Andrei,Khan Seema A,Lawson Devon A,Werb Zena,Kessenbrock Kai
Breast cancer arises from breast epithelial cells that acquire genetic alterations leading to subsequent loss of tissue homeostasis. Several distinct epithelial subpopulations have been proposed, but complete understanding of the spectrum of heterogeneity and differentiation hierarchy in the human breast remains elusive. Here, we use single-cell mRNA sequencing (scRNAseq) to profile the transcriptomes of 25,790 primary human breast epithelial cells isolated from reduction mammoplasties of seven individuals. Unbiased clustering analysis reveals the existence of three distinct epithelial cell populations, one basal and two luminal cell types, which we identify as secretory L1- and hormone-responsive L2-type cells. Pseudotemporal reconstruction of differentiation trajectories produces one continuous lineage hierarchy that closely connects the basal lineage to the two differentiated luminal branches. Our comprehensive cell atlas provides insights into the cellular blueprint of the human breast epithelium and will form the foundation to understand how the system goes awry during breast cancer.
Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors.
Li Huipeng,Courtois Elise T,Sengupta Debarka,Tan Yuliana,Chen Kok Hao,Goh Jolene Jie Lin,Kong Say Li,Chua Clarinda,Hon Lim Kiat,Tan Wah Siew,Wong Mark,Choi Paul Jongjoon,Wee Lawrence J K,Hillmer Axel M,Tan Iain Beehuat,Robson Paul,Prabhakar Shyam
Intratumoral heterogeneity is a major obstacle to cancer treatment and a significant confounding factor in bulk-tumor profiling. We performed an unbiased analysis of transcriptional heterogeneity in colorectal tumors and their microenvironments using single-cell RNA-seq from 11 primary colorectal tumors and matched normal mucosa. To robustly cluster single-cell transcriptomes, we developed reference component analysis (RCA), an algorithm that substantially improves clustering accuracy. Using RCA, we identified two distinct subtypes of cancer-associated fibroblasts (CAFs). Additionally, epithelial-mesenchymal transition (EMT)-related genes were found to be upregulated only in the CAF subpopulation of tumor samples. Notably, colorectal tumors previously assigned to a single subtype on the basis of bulk transcriptomics could be divided into subgroups with divergent survival probability by using single-cell signatures, thus underscoring the prognostic value of our approach. Overall, our results demonstrate that unbiased single-cell RNA-seq profiling of tumor and matched normal samples provides a unique opportunity to characterize aberrant cell states within a tumor.
Single-cell RNA sequencing for the study of development, physiology and disease.
Potter S Steven
Nature reviews. Nephrology
An ongoing technological revolution is continually improving our ability to carry out very high-resolution studies of gene expression patterns. Current technology enables the global gene expression profiles of single cells to be defined, facilitating dissection of heterogeneity in cell populations that was previously hidden. In contrast to gene expression studies that use bulk RNA samples and provide only a virtual average of the diverse constituent cells, single-cell studies enable the molecular distinction of all cell types within a complex population mix, such as a tumour or developing organ. For instance, single-cell gene expression profiling has contributed to improved understanding of how histologically identical, adjacent cells make different differentiation decisions during development. Beyond development, single-cell gene expression studies have enabled the characteristics of previously known cell types to be more fully defined and facilitated the identification of novel categories of cells, contributing to improvements in our understanding of both normal and disease-related physiological processes and leading to the identification of new treatment approaches. Although limitations remain to be overcome, technology for the analysis of single-cell gene expression patterns is improving rapidly and beginning to provide a detailed atlas of the gene expression patterns of all cell types in the human body.
Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing.
Guo Xinyi,Zhang Yuanyuan,Zheng Liangtao,Zheng Chunhong,Song Jintao,Zhang Qiming,Kang Boxi,Liu Zhouzerui,Jin Liang,Xing Rui,Gao Ranran,Zhang Lei,Dong Minghui,Hu Xueda,Ren Xianwen,Kirchhoff Dennis,Roider Helge Gottfried,Yan Tiansheng,Zhang Zemin
Cancer immunotherapies have shown sustained clinical responses in treating non-small-cell lung cancer, but efficacy varies and depends in part on the amount and properties of tumor infiltrating lymphocytes. To depict the baseline landscape of the composition, lineage and functional states of tumor infiltrating lymphocytes, here we performed deep single-cell RNA sequencing for 12,346 T cells from 14 treatment-naïve non-small-cell lung cancer patients. Combined expression and T cell antigen receptor based lineage tracking revealed a significant proportion of inter-tissue effector T cells with a highly migratory nature. As well as tumor-infiltrating CD8 T cells undergoing exhaustion, we observed two clusters of cells exhibiting states preceding exhaustion, and a high ratio of "pre-exhausted" to exhausted T cells was associated with better prognosis of lung adenocarcinoma. Additionally, we observed further heterogeneity within the tumor regulatory T cells (Tregs), characterized by the bimodal distribution of TNFRSF9, an activation marker for antigen-specific Tregs. The gene signature of those activated tumor Tregs, which included IL1R2, correlated with poor prognosis in lung adenocarcinoma. Our study provides a new approach for patient stratification and will help further understand the functional states and dynamics of T cells in lung cancer.
Unravelling biology and shifting paradigms in cancer with single-cell sequencing.
Baslan Timour,Hicks James
Nature reviews. Cancer
The fundamental operative unit of a cancer is the genetically and epigenetically innovative single cell. Whether proliferating or quiescent, in the primary tumour mass or disseminated elsewhere, single cells govern the parameters that dictate all facets of the biology of cancer. Thus, single-cell analyses provide the ultimate level of resolution in our quest for a fundamental understanding of this disease. Historically, this quest has been hampered by technological shortcomings. In this Opinion article, we argue that the rapidly evolving field of single-cell sequencing has unshackled the cancer research community of these shortcomings. From furthering an elemental understanding of intra-tumoural genetic heterogeneity and cancer genome evolution to illuminating the governing principles of disease relapse and metastasis, we posit that single-cell sequencing promises to unravel the biology of all facets of this disease.
Understanding tumor ecosystems by single-cell sequencing: promises and limitations.
Ren Xianwen,Kang Boxi,Zhang Zemin
Cellular heterogeneity within and across tumors has been a major obstacle in understanding and treating cancer, and the complex heterogeneity is masked if bulk tumor tissues are used for analysis. The advent of rapidly developing single-cell sequencing technologies, which include methods related to single-cell genome, epigenome, transcriptome, and multi-omics sequencing, have been applied to cancer research and led to exciting new findings in the fields of cancer evolution, metastasis, resistance to therapy, and tumor microenvironment. In this review, we discuss recent advances and limitations of these new technologies and their potential applications in cancer studies.
Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells.
Cheng Yu-Heng,Chen Yu-Chih,Lin Eric,Brien Riley,Jung Seungwon,Chen Yu-Ting,Lee Woncheol,Hao Zhijian,Sahoo Saswat,Min Kang Hyun,Cong Jason,Burness Monika,Nagrath Sunitha,S Wicha Max,Yoon Euisik
Molecular analysis of circulating tumor cells (CTCs) at single-cell resolution offers great promise for cancer diagnostics and therapeutics from simple liquid biopsy. Recent development of massively parallel single-cell RNA-sequencing (scRNA-seq) provides a powerful method to resolve the cellular heterogeneity from gene expression and pathway regulation analysis. However, the scarcity of CTCs and the massive contamination of blood cells limit the utility of currently available technologies. Here, we present Hydro-Seq, a scalable hydrodynamic scRNA-seq barcoding technique, for high-throughput CTC analysis. High cell-capture efficiency and contamination removal capability of Hydro-Seq enables successful scRNA-seq of 666 CTCs from 21 breast cancer patient samples at high throughput. We identify breast cancer drug targets for hormone and targeted therapies and tracked individual cells that express markers of cancer stem cells (CSCs) as well as of epithelial/mesenchymal cell state transitions. Transcriptome analysis of these cells provides insights into monitoring target therapeutics and processes underlying tumor metastasis.
Chemoresistance Evolution in Triple-Negative Breast Cancer Delineated by Single-Cell Sequencing.
Kim Charissa,Gao Ruli,Sei Emi,Brandt Rachel,Hartman Johan,Hatschek Thomas,Crosetto Nicola,Foukakis Theodoros,Navin Nicholas E
Triple-negative breast cancer (TNBC) is an aggressive subtype that frequently develops resistance to chemotherapy. An unresolved question is whether resistance is caused by the selection of rare pre-existing clones or alternatively through the acquisition of new genomic aberrations. To investigate this question, we applied single-cell DNA and RNA sequencing in addition to bulk exome sequencing to profile longitudinal samples from 20 TNBC patients during neoadjuvant chemotherapy (NAC). Deep-exome sequencing identified 10 patients in which NAC led to clonal extinction and 10 patients in which clones persisted after treatment. In 8 patients, we performed a more detailed study using single-cell DNA sequencing to analyze 900 cells and single-cell RNA sequencing to analyze 6,862 cells. Our data showed that resistant genotypes were pre-existing and adaptively selected by NAC, while transcriptional profiles were acquired by reprogramming in response to chemotherapy in TNBC patients.
Tracing the origin of disseminated tumor cells in breast cancer using single-cell sequencing.
Demeulemeester Jonas,Kumar Parveen,Møller Elen K,Nord Silje,Wedge David C,Peterson April,Mathiesen Randi R,Fjelldal Renathe,Zamani Esteki Masoud,Theunis Koen,Fernandez Gallardo Elia,Grundstad A Jason,Borgen Elin,Baumbusch Lars O,Børresen-Dale Anne-Lise,White Kevin P,Kristensen Vessela N,Van Loo Peter,Voet Thierry,Naume Bjørn
BACKGROUND:Single-cell micro-metastases of solid tumors often occur in the bone marrow. These disseminated tumor cells (DTCs) may resist therapy and lay dormant or progress to cause overt bone and visceral metastases. The molecular nature of DTCs remains elusive, as well as when and from where in the tumor they originate. Here, we apply single-cell sequencing to identify and trace the origin of DTCs in breast cancer. RESULTS:We sequence the genomes of 63 single cells isolated from six non-metastatic breast cancer patients. By comparing the cells' DNA copy number aberration (CNA) landscapes with those of the primary tumors and lymph node metastasis, we establish that 53% of the single cells morphologically classified as tumor cells are DTCs disseminating from the observed tumor. The remaining cells represent either non-aberrant "normal" cells or "aberrant cells of unknown origin" that have CNA landscapes discordant from the tumor. Further analyses suggest that the prevalence of aberrant cells of unknown origin is age-dependent and that at least a subset is hematopoietic in origin. Evolutionary reconstruction analysis of bulk tumor and DTC genomes enables ordering of CNA events in molecular pseudo-time and traced the origin of the DTCs to either the main tumor clone, primary tumor subclones, or subclones in an axillary lymph node metastasis. CONCLUSIONS:Single-cell sequencing of bone marrow epithelial-like cells, in parallel with intra-tumor genetic heterogeneity profiling from bulk DNA, is a powerful approach to identify and study DTCs, yielding insight into metastatic processes. A heterogeneous population of CNA-positive cells is present in the bone marrow of non-metastatic breast cancer patients, only part of which are derived from the observed tumor lineages.
BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single-cell analysis.
Uzbas Fatma,Opperer Florian,Sönmezer Can,Shaposhnikov Dmitry,Sass Steffen,Krendl Christian,Angerer Philipp,Theis Fabian J,Mueller Nikola S,Drukker Micha
We describe a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts or genomic regions from thousands of bulk samples or single cells in parallel. Multiplexing is based on a simple method that produces extensive matrices of diverse DNA barcodes attached to invariant primer sets, which are all pre-selected and optimized in silico. By applying the matrices in a novel workflow named Barcode Assembly foR Targeted Sequencing (BART-Seq), we analyze developmental states of thousands of single human pluripotent stem cells, either in different maintenance media or upon Wnt/β-catenin pathway activation, which identifies the mechanisms of differentiation induction. Moreover, we apply BART-Seq to the genetic screening of breast cancer patients and identify BRCA mutations with very high precision. The processing of thousands of samples and dynamic range measurements that outperform global transcriptomics techniques makes BART-Seq first targeted sequencing technique suitable for numerous research applications.
Multiclonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing.
Casasent Anna K,Schalck Aislyn,Gao Ruli,Sei Emi,Long Annalyssa,Pangburn William,Casasent Tod,Meric-Bernstam Funda,Edgerton Mary E,Navin Nicholas E
Ductal carcinoma in situ (DCIS) is an early-stage breast cancer that infrequently progresses to invasive ductal carcinoma (IDC). Genomic evolution has been difficult to delineate during invasion due to intratumor heterogeneity and the low number of tumor cells in the ducts. To overcome these challenges, we developed Topographic Single Cell Sequencing (TSCS) to measure genomic copy number profiles of single tumor cells while preserving their spatial context in tissue sections. We applied TSCS to 1,293 single cells from 10 synchronous patients with both DCIS and IDC regions in addition to exome sequencing. Our data reveal a direct genomic lineage between in situ and invasive tumor subpopulations and further show that most mutations and copy number aberrations evolved within the ducts prior to invasion. These results support a multiclonal invasion model, in which one or more clones escape the ducts and migrate into the adjacent tissues to establish the invasive carcinomas.