Spatial epitope barcoding reveals subclonal tumor patch behaviors

Intratumoral variability is a seminal feature of human tumors contributing to tumor progression and response to treatment. Current technologies are unsuitable to accurately track phenotypes and subclonal evolution within tumors, especially in response to genetic manipulations. Here, we developed epitope combinatorial tags (EpicTags), which we coupled to multiplexed ion beam imaging (EpicMIBI) for in situ tracking of barcodes within tissue microenvironments. Using this platform, we dissected the spatial component of cell lineages and phenotypes in a xenograft model of small-cell lung cancer. We observed emergent properties from mixed clones leading to the preferential expansion of subclonal patches for both neuroendocrine and non-neuroendocrine cancer cell states in this model. In tumors harboring a fraction of PTEN-deficient cancer cells, we uncovered a non-autonomous increase of subclonal patch size in PTEN wildtype cancer cells. EpicMIBI can facilitate in situ interrogation of cell-intrinsic and cell-extrinsic processes involved in intratumoral heterogeneity.

[1]  Gabor T. Marth,et al.  Archetype tasks link intratumoral heterogeneity to plasticity and cancer hallmarks in small cell lung cancer. , 2022, Cell systems.

[2]  J. Sage,et al.  A conserved YAP/Notch/REST network controls the neuroendocrine cell fate in the lungs , 2022, Nature Communications.

[3]  Keara M. Lane,et al.  A multiplexed epitope barcoding strategy that enables dynamic cellular phenotypic screens. , 2022, Cell systems.

[4]  Eun Sug Park,et al.  Spatial CRISPR genomics identifies regulators of the tumor microenvironment , 2022, Cell.

[5]  Fabian J Theis,et al.  Squidpy: a scalable framework for spatial omics analysis , 2022, Nature Methods.

[6]  Evan Z. Macosko,et al.  Spatial genomics enables multi-modal study of clonal heterogeneity in tissues , 2021, Nature.

[7]  Garry P. Nolan,et al.  Robust Single-cell Matching and Multi-modal Analysis Using Shared and Distinct Features Reveals Orchestrated Immune Responses , 2021, bioRxiv.

[8]  Huanming Yang,et al.  Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays , 2021, Cell.

[9]  G. Nolan,et al.  Adjacent Cell Marker Lateral Spillover Compensation and Reinforcement for Multiplexed Images , 2021, Frontiers in Immunology.

[10]  G. Kollias,et al.  Fibroblasts as immune regulators in infection, inflammation and cancer , 2021, Nature Reviews Immunology.

[11]  Leeat Keren,et al.  MAUI (MBI Analysis User Interface)—An image processing pipeline for Multiplexed Mass Based Imaging , 2021, PLoS Comput. Biol..

[12]  Tyler T. Risom,et al.  Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning , 2021, Nature Biotechnology.

[13]  I. Varela,et al.  Tumor Functional Heterogeneity Unraveled by scRNA-seq Technologies: (Trends in Cancer 6, 13-19, 2020). , 2021, Trends in cancer.

[14]  V. Quaranta,et al.  Cancer Hallmarks Define a Continuum of Plastic Cell States between Small Cell Lung Cancer Archetypes , 2021, bioRxiv.

[15]  P. Robson,et al.  Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities. , 2021, Cancer cell.

[16]  Cindy C. Guo,et al.  High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue , 2020, Cell.

[17]  P. Meltzer,et al.  SCLC-CellMiner: A Resource for Small Cell Lung Cancer Cell Line Genomics and Pharmacology Based on Genomic Signatures , 2020, Cell reports.

[18]  Sean C. Bendall,et al.  Single-cell metabolic profiling of human cytotoxic T cells , 2020, Nature biotechnology.

[19]  R. Gatenby,et al.  Characterizing the ecological and evolutionary dynamics of cancer , 2020, Nature Genetics.

[20]  Adam J. Rubin,et al.  Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma , 2020, Cell.

[21]  Gabor Marth,et al.  MYC Drives Temporal Evolution of Small Cell Lung Cancer Subtypes by Reprogramming Neuroendocrine Fate. , 2020, Cancer cell.

[22]  H. Moch,et al.  Highly multiplexed molecular and cellular mapping of breast cancer tissue in three dimensions using mass tomography , 2020, bioRxiv.

[23]  S. Orkin,et al.  An Engineered CRISPR-Cas9 Mouse Line for Simultaneous Readout of Lineage Histories and Gene Expression Profiles in Single Cells , 2020, Cell.

[24]  Jeffrey J. Quinn,et al.  Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts , 2020, Science.

[25]  L. Girard,et al.  A biobank of small cell lung cancer CDX models elucidates inter- and intratumoral phenotypic heterogeneity , 2020, Nature Cancer.

[26]  Allon M. Klein,et al.  Lineage tracing meets single-cell omics: opportunities and challenges , 2020, Nature Reviews Genetics.

[27]  Scott W. Simpkins,et al.  CRISPR screens in cancer spheroids identify 3D growth specific vulnerabilities , 2020, Nature.

[28]  Kirsten L. Frieda,et al.  Imaging cell lineage with a synthetic digital recording system , 2020, Science.

[29]  P. Robson,et al.  Single-cell analyses reveal increased intratumoral heterogeneity after the onset of therapy resistance in small-cell lung cancer , 2020, Nature Cancer.

[30]  R. Muschel,et al.  A lineage-tracing tool to map the fate of hypoxic tumour cells , 2020, Disease Models & Mechanisms.

[31]  I. Varela,et al.  Tumor Functional Heterogeneity Unraveled by scRNA-seq Technologies. , 2020, Trends in cancer.

[32]  R. Cardiff,et al.  A cancer rainbow mouse for visualizing the functional genomics of oncogenic clonal expansion , 2019, Nature Communications.

[33]  Jian Li,et al.  Immune cells within the tumor microenvironment: biological functions and roles in cancer immunotherapy. , 2019, Cancer letters.

[34]  Mark W. Budde,et al.  In situ readout of DNA barcodes and single base edits facilitated by in vitro transcription , 2019, Nature Biotechnology.

[35]  Garry Nolan,et al.  MIBI-TOF: A multiplexed imaging platform relates cellular phenotypes and tissue structure , 2019, Science Advances.

[36]  Salil S. Bhate,et al.  Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front , 2019, Cell.

[37]  L. Shevde,et al.  The Tumor Microenvironment Innately Modulates Cancer Progression. , 2019, Cancer research.

[38]  Yu Wang,et al.  Immuno-SABER enables highly multiplexed and amplified protein imaging in tissues , 2019, Nature Biotechnology.

[39]  William Graf,et al.  Deep learning for cellular image analysis , 2019, Nature Methods.

[40]  R. Weinberg,et al.  EMT and Cancer: More Than Meets the Eye. , 2019, Developmental cell.

[41]  Peng Yin,et al.  SABER enables amplified and multiplexed imaging of RNA and DNA in cells and tissues , 2019, Nature Methods.

[42]  C. Rudin,et al.  Molecular subtypes of small cell lung cancer: a synthesis of human and mouse model data , 2019, Nature Reviews Cancer.

[43]  Guo-Cheng Yuan,et al.  Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+ , 2019, Nature.

[44]  S. Richon,et al.  Cancer cells in the tumor core exhibit spatially coordinated migration patterns , 2019, Journal of Cell Science.

[45]  Evan Z. Macosko,et al.  Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution , 2019, Science.

[46]  Lai Guan Ng,et al.  Dimensionality reduction for visualizing single-cell data using UMAP , 2018, Nature Biotechnology.

[47]  Thalia E. Chan,et al.  Single-cell transcriptomics reveals multi-step adaptations to endocrine therapy , 2018, Nature Communications.

[48]  Richi Sakaguchi,et al.  Bright multicolor labeling of neuronal circuits with fluorescent proteins and chemical tags , 2018, eLife.

[49]  Eun Sug Park,et al.  Protein Barcodes Enable High-Dimensional Single-Cell CRISPR Screens , 2018, Cell.

[50]  R. Weinberg,et al.  New insights into the mechanisms of epithelial–mesenchymal transition and implications for cancer , 2018, Nature reviews. Molecular cell biology.

[51]  G. Nolan,et al.  Metal-isotope-tagged monoclonal antibodies for high-dimensional mass cytometry , 2018, Nature Protocols.

[52]  Leland McInnes,et al.  UMAP: Uniform Manifold Approximation and Projection , 2018, J. Open Source Softw..

[53]  Sean C. Bendall,et al.  A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging , 2018, Cell.

[54]  George M. Church,et al.  Developmental barcoding of whole mouse via homing CRISPR , 2018, Science.

[55]  Peng Yin,et al.  SABER enables highly multiplexed and amplified detection of DNA and RNA in cells and tissues , 2018, bioRxiv.

[56]  William E. Allen,et al.  Three-dimensional intact-tissue sequencing of single-cell transcriptional states , 2018, Science.

[57]  S. Spencer,et al.  Ki67 is a Graded Rather than a Binary Marker of Proliferation versus Quiescence. , 2018, Cell reports.

[58]  P. Sorger,et al.  Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes , 2018, eLife.

[59]  Li Ding,et al.  Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics , 2018, Cell.

[60]  G. Church,et al.  A homing CRISPR mouse resource for barcoding and lineage tracing , 2018, bioRxiv.

[61]  J. Sage,et al.  Tumor heterogeneity in small cell lung cancer defined and investigated in pre-clinical mouse models. , 2018, Translational lung cancer research.

[62]  Salil S. Bhate,et al.  Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging , 2017, Cell.

[63]  Ronald N. Germain,et al.  Multiplex, quantitative cellular analysis in large tissue volumes with clearing-enhanced 3D microscopy (Ce3D) , 2017, Proceedings of the National Academy of Sciences.

[64]  K. Garcia,et al.  Intratumoral heterogeneity generated by Notch signaling promotes small cell lung cancer , 2017, Nature.

[65]  Kirsten L. Frieda,et al.  Synthetic recording and in situ readout of lineage information in single cells , 2016, Nature.

[66]  Euan A. Ashley,et al.  Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments , 2016, PLoS Comput. Biol..

[67]  Martin Vingron,et al.  Comprehensive genomic profiles of small cell lung cancer , 2015, Nature.

[68]  Piet Demeester,et al.  FlowSOM: Using self‐organizing maps for visualization and interpretation of cytometry data , 2015, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[69]  Faraz Hach,et al.  Spatial genomic heterogeneity within localized, multifocal prostate cancer , 2015, Nature Genetics.

[70]  Evan Z. Macosko,et al.  Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets , 2015, Cell.

[71]  X. Zhuang,et al.  Spatially resolved, highly multiplexed RNA profiling in single cells , 2015, Science.

[72]  Charles Swanton,et al.  Translational Implications of Tumor Heterogeneity , 2015, Clinical Cancer Research.

[73]  P. Pandolfi,et al.  Enhancing chemotherapy efficacy in Pten-deficient prostate tumors by activating the senescence-associated antitumor immunity. , 2014, Cell reports.

[74]  George M. Church,et al.  Highly Multiplexed Subcellular RNA Sequencing in Situ , 2014, Science.

[75]  Sean C. Bendall,et al.  Multiplexed ion beam imaging of human breast tumors , 2014, Nature Medicine.

[76]  J. Buhmann,et al.  Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry , 2014, Nature Methods.

[77]  A. McKenna,et al.  Genetic and Clonal Dissection of Murine Small Cell Lung Carcinoma Progression by Genome Sequencing , 2014, Cell.

[78]  Yann Le Franc,et al.  Multiplex Cell and Lineage Tracking with Combinatorial Labels , 2014, Neuron.

[79]  Nicholas T. Ingolia,et al.  PTEN Is a Potent Suppressor of Small Cell Lung Cancer , 2014, Molecular Cancer Research.

[80]  A. Butte,et al.  A drug repositioning approach identifies tricyclic antidepressants as inhibitors of small cell lung cancer and other neuroendocrine tumors. , 2013, Cancer discovery.

[81]  P. A. Futreal,et al.  Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. , 2012, The New England journal of medicine.

[82]  Michael C. Ostrowski,et al.  Reprogramming of the Tumor Microenvironment by Stromal Pten-regulated miR-320 , 2011, Nature Cell Biology.

[83]  Leland Wilkinson,et al.  ggplot2: Elegant Graphics for Data Analysis by WICKHAM, H. , 2011 .

[84]  D. Hanahan,et al.  Hallmarks of Cancer: The Next Generation , 2011, Cell.

[85]  Hans Clevers,et al.  Intestinal Crypt Homeostasis Results from Neutral Competition between Symmetrically Dividing Lgr5 Stem Cells , 2010, Cell.

[86]  Metin N. Gurcan,et al.  Pten in Stromal Fibroblasts Suppresses Mammary Epithelial Tumors , 2009, Nature.

[87]  G. Nolan,et al.  Mapping normal and cancer cell signalling networks: towards single-cell proteomics , 2006, Nature Reviews Cancer.

[88]  J. Joyce,et al.  Therapeutic Targeting of the Tumor Microenvironment. , 2021, Cancer discovery.

[89]  Z. Medarova RNA Imaging , 2016, Methods in Molecular Biology.

[90]  M. Cronauer,et al.  Re: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing , 2013 .