Integrating genetic and non-genetic determinants of cancer evolution by single-cell multi-omics

Nam, Anna S.; Chaligné, Ronan; Landau, Dan A.

doi:10.1038/s41576-020-0265-5

Cited by 255 publications

(209 citation statements)

References 189 publications

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“…Strikingly, we observed that the basal and classical programs were not mutually exclusive; rather, we identified a large population of cells that co-expressed features of both programs to varying degrees (Figure 2A; Supplemental Figure S3A,B). In developmental contexts, cell state commitment is often a continuous process where mixing/co-expression of state markers indicates state transitions (Nam et al, 2021). Similarly, the large fraction of intermediate co-expressing cells identified in our single-cell snapshots suggests state transitions may be an ongoing and frequent process in human PDAC tumors.…”

Section: Tumor Cell Transcriptional Subtypes In Metastatic Pdac Include An Intermediate Transitional Statementioning

confidence: 64%

“…Specific mutations can program cancer cell states and, in some cases, serve as biomarkers for treatment (Filbin et al, 2018;Hovestadt et al, 2019;van Galen et al, 2019;Venteicher et al, 2017). Yet, in other instances, transcriptional phenotypes are not strongly associated with specific mutational patterns (Nam et al, 2021). In these tumors, cell-extrinsic TME interactions may influence malignant cellular attributes, but our understanding of reciprocal signaling between malignant cells and the TME is rudimentary.…”

Section: Introductionmentioning

confidence: 99%

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The tumor microenvironment drives transcriptional phenotypes and their plasticity in metastatic pancreatic cancer

Raghavan

Winter

Navia

et al. 2020

Preprint

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In pancreatic ductal adenocarcinoma (PDAC), the basal-like and classical transcriptional subtypes are associated with differential chemotherapy sensitivity and patient survival. These phenotypes have been defined using bulk transcriptional profiling, which can mask underlying cellular heterogeneity and the biologic mechanisms that distinguish these subtypes. Furthermore, few studies have interrogated metastases, which are the cause of mortality in most patients with this highly lethal disease. Using single-cell RNA-sequencing of metastatic needle biopsies and matched organoid models, we demonstrate intra-tumoral subtype heterogeneity at the single-cell level and define a continuum for the basal-like and classical phenotypes that includes hybrid cells that co-express features of both states. Basal-like tumors show enrichment of mesenchymal and stem-like programs, and demonstrate immune exclusion and tumor cell crosstalk with specific macrophage subsets. Conversely, classical tumors harbor greater immune infiltration and a relatively pro-angiogenic microenvironment. Matched organoid models exhibit a strong bias against the growth of basal-like cells in standard organoid media, but modification of culture conditions can rescue the basal-like phenotype. This study reframes the transcriptional taxonomy of PDAC, demonstrates how divergent transcriptional subtypes associate with unique tumor microenvironments, and highlights the importance of evaluating both genotype and transcriptional phenotype to establish high-fidelity patient-derived cancer models.

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Section: Tumor Cell Transcriptional Subtypes In Metastatic Pdac Include An Intermediate Transitional Statementioning

confidence: 64%

Section: Introductionmentioning

confidence: 99%

The tumor microenvironment drives transcriptional phenotypes and their plasticity in metastatic pancreatic cancer

Raghavan

Winter

Navia

et al. 2020

Preprint

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“…Despite of its great potential, the current single-cell technologies suffer from their limited scalability, sparse coverage, allelic dropouts, PCR errors, and most importantly, lack of spatial information (Nam et al, 2020). For instance, the current scRNAseq technologies typically generate hundreds to thousands of cells per biological sample, and thousands to hundred thousands of cells per study.…”

Section: Current Limitations and Challenges Of Single-cell Multiomic mentioning

confidence: 99%

“…Last but most importantly, the current single-cell technologies often require front-end tissue dissociation, which inevitably destroys the spatial architecture of the biological specimens, eliminating a critical layer of information that contributes to the biological identity of a cell. To address this limitation, spatial sequencing techniques, such as Slide-Seq (Rodriques et al, 2019), have been developed; and the data integration of spatial transcriptomics is hopeful to help dissect important cell interactions at single-cell resolution in the near future (Adey, 2019;Welch et al, 2019;Nam et al, 2020).…”

Section: Current Limitations and Challenges Of Single-cell Multiomic mentioning

confidence: 99%

Applications of Single-Cell Omics to Dissect Tumor Microenvironment

Guo

Cai

2020

Front. Genet.

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The recent technical and computational advances in single-cell sequencing technologies have significantly broaden our toolkit to study tumor microenvironment (TME) directly from human specimens. The TME is the complex and dynamic ecosystem composed of multiple cell types, including tumor cells, immune cells, stromal cells, endothelial cells, and other non-cellular components such as the extracellular matrix and secreted signaling molecules. The great success on immune checkpoint blockade therapy has highlighted the importance of TME on anti-tumor immunity and has made it a prime target for further immunotherapy strategies. Applications of single-cell transcriptomics on studying TME has yielded unprecedented resolution of the cellular and molecular complexity of the TME, accelerating our understanding of the heterogeneity, plasticity, and complex cross-interaction between different cell types within the TME. In this review, we discuss the recent advances by single-cell sequencing on understanding the diversity of TME and its functional impact on tumor progression and immunotherapy response driven by single-cell sequencing. We primarily focus on the major immune cell types infiltrated in the human TME, including T cells, dendritic cells, and macrophages. We further discuss the limitations of the existing methodologies and the prospects on future studies utilizing single-cell multi-omics technologies. Since immune cells undergo continuous activation and differentiation within the TME in response to various environmental cues, we highlight the importance of integrating multimodal datasets to enable retrospective lineage tracing and epigenetic profiling of the tumor infiltrating immune cells. These novel technologies enable better characterization of the developmental lineages and differentiation states that are critical for the understanding of the underlying mechanisms driving the functional diversity of immune cells within the TME. We envision that with the continued accumulation of single-cell omics datasets, single-cell sequencing will become an indispensable aspect of the immune-oncology experimental toolkit. It will continue to drive the scientific innovations in precision immunotherapy and will be ultimately adopted by routine clinical practice in the foreseeable future.

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“…The recent explosion of technologies allowing detailed phenotypic measurements of single cells in high-throughput has made the dissection of cell types and states in complex tissues accessible to most researchers. While measurement of single modalities has been highly informative for phenotyping, new techniques that allow detection of multiple modalities of information from single cells continue to be developed 1–4 .…”

Section: Introductionmentioning

confidence: 99%

Scalable, multimodal profiling of chromatin accessibility and protein levels in single cells

Mimitou

Lareau

Chen

et al. 2020

Preprint

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Recent technological advances have enabled massively parallel chromatin profiling with single-cell Assay for Transposase Accessible Chromatin by sequencing (scATAC-seq) in thousands of individual cells. Here, we extend these approaches and present ATAC with Select Antigen Profiling by sequencing, ASAP-seq, a tool to simultaneously profile accessible chromatin and protein levels in thousands of single cells. Our approach pairs sparse scATAC-seq data with robust detection of hundreds of cell surface and intracellular protein markers and optional capture of mitochondrial DNA (mtDNA) for clonal tracking, thus concomitantly capturing three distinct modalities in single cells. Importantly, ASAP-seq uses a novel bridging approach that repurposes antibody:oligo conjugates designed for existing technologies that pair protein measurements with single cell RNA-seq. We demonstrate the utility of ASAP-seq by revealing coordinated and distinct changes in chromatin, RNA, and surface proteins during native hematopoietic differentiation, peripheral blood mononuclear cell stimulation, and as a combinatorial decoder and reporter of multiplexed perturbations in primary T cells.

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Integrating genetic and non-genetic determinants of cancer evolution by single-cell multi-omics

Cited by 255 publications

References 189 publications

The tumor microenvironment drives transcriptional phenotypes and their plasticity in metastatic pancreatic cancer

The tumor microenvironment drives transcriptional phenotypes and their plasticity in metastatic pancreatic cancer

Applications of Single-Cell Omics to Dissect Tumor Microenvironment

Scalable, multimodal profiling of chromatin accessibility and protein levels in single cells

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