Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors.
Nature genetics
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.
10.1038/ng.3818
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
Cell research
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.
10.1038/cr.2016.23
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.
10.1093/annonc/mdx278
Rare Cell Detection by Single-Cell RNA Sequencing as Guided by Single-Molecule RNA FISH.
Torre Eduardo,Dueck Hannah,Shaffer Sydney,Gospocic Janko,Gupte Rohit,Bonasio Roberto,Kim Junhyong,Murray John,Raj Arjun
Cell systems
Although single-cell RNA sequencing can reliably detect large-scale transcriptional programs, it is unclear whether it accurately captures the behavior of individual genes, especially those that express only in rare cells. Here, we use single-molecule RNA fluorescence in situ hybridization as a gold standard to assess trade-offs in single-cell RNA-sequencing data for detecting rare cell expression variability. We quantified the gene expression distribution for 26 genes that range from ubiquitous to rarely expressed and found that the correspondence between estimates across platforms improved with both transcriptome coverage and increased number of cells analyzed. Further, by characterizing the trade-off between transcriptome coverage and number of cells analyzed, we show that when the number of genes required to answer a given biological question is small, then greater transcriptome coverage is more important than analyzing large numbers of cells. More generally, our report provides guidelines for selecting quality thresholds for single-cell RNA-sequencing experiments aimed at rare cell analyses.
10.1016/j.cels.2018.01.014
Association of T-Cell Receptor Repertoire Use With Response to Combined Trastuzumab-Lapatinib Treatment of HER2-Positive Breast Cancer: Secondary Analysis of the NeoALTTO Randomized Clinical Trial.
Powles Ryan L,Redmond David,Sotiriou Christos,Loi Sherene,Fumagalli Debora,Nuciforo Paolo,Harbeck Nadia,de Azambuja Evandro,Sarp Severine,Di Cosimo Serena,Huober Jens,Baselga Jose,Piccart-Gebhart Martine,Elemento Olivier,Pusztai Lajos,Hatzis Christos
JAMA oncology
Importance:Dual anti-HER2 blockade increased the rate of pathologic complete response (pCR) in the Neoadjuvant Lapatinib and/or Trastuzumab Treatment Optimisation (NeoALTTO) trial, and high immune gene expression was associated with pCR in all treatment arms. So far, no marker has been identified that is specifically associated with the benefit from dual HER2 blockade. Objective:To examine if use of the T-cell β chain variable genes adds to the potential association of immune gene signatures with response to dual HER2 blockade. Design, Setting, and Participants:In the NeoALTTO trial, HER2-positive patients recruited between January 5, 2008, and May 27, 2010, were treated with paclitaxel plus either lapatinib or trastuzumab or both as neoadjuvant therapy. In this study, RNA sequencing data from baseline tumor specimens of 245 patients in the NeoALTTO trial were analyzed and reads were aligned to TRBV gene reference sequences using a previously published Basic Local Alignment Search Tool T-cell receptor mapping pipeline. Total TRBV gene use, Shannon entropy, and gene richness were calculated for each tumor, and nonnegative matrix factorization was used to define TRBV co-use metagenes (TMGs). The association between TRBV metrics, tumor genomic metrics, and response was assessed with multivariable logistic regression. Statistical analysis was performed from January 23 to December 2, 2017. Main Outcomes and Measures:The association between TRBV use metrics and pCR. Results:Among the 245 women with available data (mean [SD] age, 49 [11] years), total TRBV use correlated positively with a gene expression signature for immune activity (Spearman ρ = 0.93; P < .001). High use of TRBV11-3 and TMG2, characterized by high use of TRBV4.3, TRBV6.3, and TRBV7.2, was associated with a higher rate of pCR to dual HER2-targeted therapy (TRBV11-3 interaction: odds ratio, 2.63 [95% CI, 1.22-6.47]; P = .02; TMG2 interaction: odds ratio, 3.39 [95% CI, 1.57-8.27]; P = .004). Immune-rich cancers with high TMG2 levels (n = 92) had significantly better response to dual HER2-targeted treatment compared with the single therapy arms (rate of pCR, 68% [95% CI, 52%-83%] vs 21% [95% CI, 10%-31%]; P < .001), whereas those with low TMG2 levels did not benefit from dual therapy. High TMG2 levels were also associated with a higher rate of pCR to the combined therapy in immune-poor tumors (n = 30; pCR, 50% [95% CI, 22%-78%] vs 6% [95% CI, 0%-16%]; P = .009). Conclusions and Relevance:Use patterns of TRBV genes potentially provide information about the association with response to dual HER2 blockade beyond immune gene signatures. High use of TRBV11.3 or TRBV4.3, TRBV6.3, and TRBV7.2 identifies patients who have a better response to dual HER2 targeted therapy. Trial Registration:ClinicalTrials.gov Identifier: NCT00553358.
10.1001/jamaoncol.2018.1564
Early Detection of Cancer in Blood Using Single-Cell Analysis: A Proposal.
Krasnitz Alexander,Kendall Jude,Alexander Joan,Levy Dan,Wigler Michael
Trends in molecular medicine
Here, we explore the potential of single-cell genomic analysis in blood for early detection of cancer; we consider a method that screens the presence of recurrent patterns of copy number (CN) alterations using sparse single-cell sequencing. We argue for feasibility, based on in silico analysis of existing single-cell data and cancer CN profiles. Sampling procedures from existing diploid single cells can render data for a cell with any given profile. Sampling from multiple published tumor profiles can interrogate cancer clonality via an algorithm that tests the multiplicity of close pairwise similarities among single-cell cancer genomes. The majority of common solid cancers would be detectable in this manner. As any early detection method must be verifiable and actionable, we describe how further analysis of suspect cells can aid in determining risk and anatomic origin. Future affordability rests on currently available procedures for tumor cell enrichment and inexpensive methods for single-cell analysis.
10.1016/j.molmed.2017.05.005
International Working Group consensus response evaluation criteria in lymphoma (RECIL 2017).
Annals of oncology : official journal of the European Society for Medical Oncology
In recent years, the number of approved and investigational agents that can be safely administered for the treatment of lymphoma patients for a prolonged period of time has substantially increased. Many of these novel agents are evaluated in early-phase clinical trials in patients with a wide range of malignancies, including solid tumors and lymphoma. Furthermore, with the advances in genome sequencing, new "basket" clinical trial designs have emerged that select patients based on the presence of specific genetic alterations across different types of solid tumors and lymphoma. The standard response criteria currently in use for lymphoma are the Lugano Criteria which are based on [18F]2-fluoro-2-deoxy-D-glucose positron emission tomography or bidimensional tumor measurements on computerized tomography scans. These differ from the RECIST criteria used in solid tumors, which use unidimensional measurements. The RECIL group hypothesized that single-dimension measurement could be used to assess response to therapy in lymphoma patients, producing results similar to the standard criteria. We tested this hypothesis by analyzing 47 828 imaging measurements from 2983 individual adult and pediatric lymphoma patients enrolled on 10 multicenter clinical trials and developed new lymphoma response criteria (RECIL 2017). We demonstrate that assessment of tumor burden in lymphoma clinical trials can use the sum of longest diameters of a maximum of three target lesions. Furthermore, we introduced a new provisional category of a minor response. We also clarified response assessment in patients receiving novel immune therapy and targeted agents that generate unique imaging situations.
10.1093/annonc/mdx097
Tumour heterogeneity and resistance to cancer therapies.
Dagogo-Jack Ibiayi,Shaw Alice T
Nature reviews. Clinical oncology
Cancer is a dynamic disease. During the course of disease, cancers generally become more heterogeneous. As a result of this heterogeneity, the bulk tumour might include a diverse collection of cells harbouring distinct molecular signatures with differential levels of sensitivity to treatment. This heterogeneity might result in a non-uniform distribution of genetically distinct tumour-cell subpopulations across and within disease sites (spatial heterogeneity) or temporal variations in the molecular makeup of cancer cells (temporal heterogeneity). Heterogeneity provides the fuel for resistance; therefore, an accurate assessment of tumour heterogeneity is essential for the development of effective therapies. Multiregion sequencing, single-cell sequencing, analysis of autopsy samples, and longitudinal analysis of liquid biopsy samples are all emerging technologies with considerable potential to dissect the complex clonal architecture of cancers. In this Review, we discuss the driving forces behind intratumoural heterogeneity and the current approaches used to combat this heterogeneity and its consequences. We also explore how clinical assessments of tumour heterogeneity might facilitate the development of more-effective personalized therapies.
10.1038/nrclinonc.2017.166
Tumor Cell Biodiversity Drives Microenvironmental Reprogramming in Liver Cancer.
Cancer cell
Cellular diversity in tumors is a key factor for therapeutic failures and lethal outcomes of solid malignancies. Here, we determined the single-cell transcriptomic landscape of liver cancer biospecimens from 19 patients. We found varying degrees of heterogeneity in malignant cells within and between tumors and diverse landscapes of tumor microenvironment (TME). Strikingly, tumors with higher transcriptomic diversity were associated with patient's worse overall survival. We found a link between hypoxia-dependent vascular endothelial growth factor expression in tumor diversity and TME polarization. Moreover, T cells from higher heterogeneous tumors showed lower cytolytic activities. Consistent results were found using bulk genomic and transcriptomic profiles of 765 liver tumors. Our results offer insight into the diverse ecosystem of liver cancer and its impact on patient prognosis.
10.1016/j.ccell.2019.08.007
New approaches to molecular monitoring in CML (and other diseases).
Blood
Chronic myeloid leukemia (CML) is the model cancer, demonstrating the clinical benefits of targeted therapy and the power of molecular diagnostics and monitoring. In CML, the BCR-ABL1 fusion gene and its companion messenger RNA offers a unique target differentiating cancer from the normal cell, affording the potential for very sensitive and specific assays. Because CML is such an ideal model, new methods are arising that should make testing in CML faster, more reliable, and reach a greater sensitivity. New ultrasensitive sequencing approaches, coupled with single-cell genomic approaches, further the study of measurable residual disease, clonal heterogeneity, and promise to make clinical trials more innovative and informative. These methods should be able to be transferred to other hematological and solid malignancies.
10.1182/blood.2019000838
Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic.
Annals of oncology : official journal of the European Society for Medical Oncology
Background:Treatment with immune checkpoint blockade (ICB) with agents such as anti-programmed cell death protein 1 (PD-1), anti-programmed death-ligand 1 (PD-L1), and/or anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) can result in impressive response rates and durable disease remission but only in a subset of patients with cancer. Expression of PD-L1 has demonstrated utility in selecting patients for response to ICB and has proven to be an important biomarker for patient selection. Tumor mutation burden (TMB) is emerging as a potential biomarker. However, refinement of interpretation and contextualization is required. Materials and methods:In this review, we outline the evolution of TMB as a biomarker in oncology, delineate how TMB can be applied in the clinic, discuss current limitations as a diagnostic test, and highlight mechanistic insights unveiled by the study of TMB. We review available data to date studying TMB as a biomarker for response to ICB by tumor type, focusing on studies proposing a threshold for TMB as a predictive biomarker for ICB activity. Results:High TMB consistently selects for benefit with ICB therapy. In lung, bladder and head and neck cancers, the current predictive TMB thresholds proposed approximate 200 non-synonymous somatic mutations by whole exome sequencing (WES). PD-L1 expression influences response to ICB in high TMB tumors with single agent PD-(L)1 antibodies; however, response may not be dependent on PD-L1 expression in the setting of anti-CTLA4 or anti-PD-1/CTLA-4 combination therapy. Disease-specific TMB thresholds for effective prediction of response in various other malignancies are not well established. Conclusions:TMB, in concert with PD-L1 expression, has been demonstrated to be a useful biomarker for ICB selection across some cancer types; however, further prospective validation studies are required. TMB determination by selected targeted panels has been correlated with WES. Calibration and harmonization will be required for optimal utility and alignment across all platforms currently used internationally. Key challenges will need to be addressed before broader use in different tumor types.
10.1093/annonc/mdy495
Next-generation computational tools for interrogating cancer immunity.
Nature reviews. Genetics
The remarkable success of cancer therapies with immune checkpoint blockers is revolutionizing oncology and has sparked intensive basic and translational research into the mechanisms of cancer-immune cell interactions. In parallel, numerous novel cutting-edge technologies for comprehensive molecular and cellular characterization of cancer immunity have been developed, including single-cell sequencing, mass cytometry and multiplexed spatial cellular phenotyping. In order to process, analyse and visualize multidimensional data sets generated by these technologies, computational methods and software tools are required. Here, we review computational tools for interrogating cancer immunity, discuss advantages and limitations of the various methods and provide guidelines to assist in method selection.
10.1038/s41576-019-0166-7
Mechanisms and Consequences of Cancer Genome Instability: Lessons from Genome Sequencing Studies.
Lee June-Koo,Choi Yoon-La,Kwon Mijung,Park Peter J
Annual review of pathology
During tumor evolution, cancer cells can accumulate numerous genetic alterations, ranging from single nucleotide mutations to whole-chromosomal changes. Although a great deal of progress has been made in the past decades in characterizing genomic alterations, recent cancer genome sequencing studies have provided a wealth of information on the detailed molecular profiles of such alterations in various types of cancers. Here, we review our current understanding of the mechanisms and consequences of cancer genome instability, focusing on the findings uncovered through analysis of exome and whole-genome sequencing data. These analyses have shown that most cancers have evidence of genome instability, and the degree of instability is variable within and between cancer types. Importantly, we describe some recent evidence supporting the idea that chromosomal instability could be a major driving force in tumorigenesis and cancer evolution, actively shaping the genomes of cancer cells to maximize their survival advantage.
10.1146/annurev-pathol-012615-044446
Resolving genetic heterogeneity in cancer.
Nature reviews. Genetics
To a large extent, cancer conforms to evolutionary rules defined by the rates at which clones mutate, adapt and grow. Next-generation sequencing has provided a snapshot of the genetic landscape of most cancer types, and cancer genomics approaches are driving new insights into cancer evolutionary patterns in time and space. In contrast to species evolution, cancer is a particular case owing to the vast size of tumour cell populations, chromosomal instability and its potential for phenotypic plasticity. Nevertheless, an evolutionary framework is a powerful aid to understand cancer progression and therapy failure. Indeed, such a framework could be applied to predict individual tumour behaviour and support treatment strategies.
10.1038/s41576-019-0114-6
Understanding tumor ecosystems by single-cell sequencing: promises and limitations.
Genome biology
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.
10.1186/s13059-018-1593-z
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.
10.1038/s41581-018-0021-7
Single-Cell RNA Sequencing in Cancer: Lessons Learned and Emerging Challenges.
Suvà Mario L,Tirosh Itay
Molecular cell
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.
10.1016/j.molcel.2019.05.003
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.
10.1038/nrc.2017.58
[Application of Single-cell RNA Sequencing in Research on Tumor Immune Microenvironment].
Yang Kai Li,Sun Zhao,Bai Chun Mei,Zhao Lin
Zhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae
Tumors are highly complex systems. Understanding the compositions and functions of the tumor immune microenvironment is a prerequisite for effective tumor immunotherapy. Single-cell RNA sequencing can detect the transcriptome of a cell at the resolution of single-cell level,describe its functional status,and thus deepen the understanding of the composition and function of different cell clusters in tumor immune microenvironment. This article reviews the application of single-cell RNA sequencing in research on tumor immune microenvironment.
10.3881/j.issn.1000-503X.11194
Application of single-cell sequencing in human cancer.
Rantalainen Mattias
Briefings in functional genomics
Precision medicine is emerging as a cornerstone of future cancer care with the objective of providing targeted therapies based on the molecular phenotype of each individual patient. Traditional bulk-level molecular phenotyping of tumours leads to significant information loss, as the molecular profile represents an average phenotype over large numbers of cells, while cancer is a disease with inherent intra-tumour heterogeneity at the cellular level caused by several factors, including clonal evolution, tissue hierarchies, rare cells and dynamic cell states. Single-cell sequencing provides means to characterize heterogeneity in a large population of cells and opens up opportunity to determine key molecular properties that influence clinical outcomes, including prognosis and probability of treatment response. Single-cell sequencing methods are now reliable enough to be used in many research laboratories, and we are starting to see applications of these technologies for characterization of human primary cancer cells. In this review, we provide an overview of studies that have applied single-cell sequencing to characterize human cancers at the single-cell level, and we discuss some of the current challenges in the field.
10.1093/bfgp/elx036
Application of single-cell RNA sequencing methodologies in understanding haematopoiesis and immunology.
Essays in biochemistry
The blood and immune system are characterised by utmost diversity in its cellular components. This heterogeneity can solely be resolved with the application of single-cell technologies that enable precise examination of cell-to-cell variation. Single-cell transcriptomics is continuously pushing forward our understanding of processes driving haematopoiesis and immune responses in physiological settings as well as in disease. Remarkably, in the last five years, a number of studies involving single-cell RNA sequencing (scRNA-seq) allowed the discovery of new immune cell types and revealed that haematopoiesis is a continuous rather than a stepwise process, thus challenging the classical haematopoietic lineage tree model. This review summarises the most recent studies which applied scRNA-seq to answer outstanding questions in the fields of haematology and immunology and discusses the present challenges and future directions.
10.1042/EBC20180072
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
Nature communications
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.
10.1038/s41467-019-10122-2
Multiclonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing.
Cell
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.
10.1016/j.cell.2017.12.007
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
Genome biology
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.
10.1186/s13059-016-1109-7
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
Cell
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.
10.1016/j.cell.2018.03.041
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
Nature medicine
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.
10.1038/s41591-018-0078-7
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
Nature medicine
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.
10.1038/s41591-018-0045-3
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
Nature methods
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.
10.1038/s41592-019-0425-8
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.
10.1126/science.aao3791
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.
10.1038/nrg.2015.16