Integrative Analysis and Machine Learning based Characterization of Single Circulating Tumor Cells

We collated publicly available single-cell expression profiles of circulating tumor cells (CTCs) and showed that CTCs across cancers lie on a near-perfect continuum of epithelial to mesenchymal (EMT) transition. Integrative analysis of CTC transcriptomes also highlighted the inverse gene expression pattern between PD-L1 and MHC, which is implicated in cancer immunotherapy. We used the CTCs expression profiles in tandem with publicly available peripheral blood mononuclear cell (PBMC) transcriptomes to train a classifier that accurately recognizes CTCs of diverse phenotype. Further, we used this classifier to validate circulating breast tumor cells captured using a newly developed microfluidic system for label-free enrichment of CTCs.

[1]  G. Doyle,et al.  Significance of Circulating Tumor Cells Detected by the CellSearch System in Patients with Metastatic Breast Colorectal and Prostate Cancer , 2009, Journal of oncology.

[2]  Tony J. Pircher,et al.  Detection of EpCAM-Negative and Cytokeratin-Negative Circulating Tumor Cells in Peripheral Blood , 2011, Journal of oncology.

[3]  Sridhar Ramaswamy,et al.  HER2 expression identifies dynamic functional states within circulating breast cancer cells , 2016, Nature.

[4]  Zhi Zhu,et al.  Enrichment and single-cell analysis of circulating tumor cells , 2016, Chemical science.

[5]  Caroline Dive,et al.  SnapShot: Circulating Tumor Cells , 2017, Cell.

[6]  T. Seyfried,et al.  On the origin of cancer metastasis. , 2013, Critical reviews in oncogenesis.

[7]  Thomas J. Watson,et al.  An empirical study of the naive Bayes classifier , 2001 .

[8]  Federico Garrido,et al.  Rejection versus escape: the tumor MHC dilemma , 2017, Cancer Immunology, Immunotherapy.

[9]  Debarka Sengupta,et al.  Improved dropClust R package with integrative analysis support for scRNA-seq data , 2019, Bioinform..

[10]  J. Friedman.  Greedy function approximation: A gradient boosting machine. , 2001 .

[11]  Kamil Slowikowski,et al.  Fast, sensitive, and accurate integration of single cell data with Harmony , 2019, Nature Methods.

[12]  A. Bhagat,et al.  ClearCell® FX, a label‐free microfluidics technology for enrichment of viable circulating tumor cells , 2018, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[13]  V. Valero,et al.  Comparison of assay methods for detection of circulating tumor cells in metastatic breast cancer: AdnaGen AdnaTest BreastCancer Select/Detect™ versus Veridex CellSearch™ system , 2012, International journal of cancer.

[14]  Vibhor Kumar,et al.  CellAtlasSearch: a scalable search engine for single cells , 2018, Nucleic Acids Res..

[15]  Bin Huang,et al.  RACIPE: a computational tool for modeling gene regulatory circuits using randomization , 2017, bioRxiv.

[16]  Yvonne A. Evrard,et al.  Promise and limits of the CellSearch platform for evaluating pharmacodynamics in circulating tumor cells. , 2016, Seminars in oncology.

[17]  Peter C. Y. Chen,et al.  Slanted spiral microfluidics for the ultra-fast, label-free isolation of circulating tumor cells. , 2014, Lab on a chip.

[18]  Sridhar Ramaswamy,et al.  RNA-Seq of single prostate CTCs implicates noncanonical Wnt signaling in antiandrogen resistance , 2015, Science.

[19]  Drew M. Pardoll,et al.  The blockade of immune checkpoints in cancer immunotherapy , 2012, Nature Reviews Cancer.

[20]  Jean Paul Thiery,et al.  EMT: 2016 , 2016, Cell.

[21]  Sridhar Ramaswamy,et al.  Circulating Tumor Cell Clusters Are Oligoclonal Precursors of Breast Cancer Metastasis , 2014, Cell.

[22]  Sridhar Ramaswamy,et al.  Expression of β-globin by cancer cells promotes cell survival during blood-borne dissemination , 2017, Nature Communications.

[23]  D. Planchard,et al.  A direct comparison of CellSearch and ISET for circulating tumour-cell detection in patients with metastatic carcinomas , 2011, British Journal of Cancer.

[24]  Feng Li,et al.  CellMarker: a manually curated resource of cell markers in human and mouse , 2018, Nucleic Acids Res..

[25]  F. Bai,et al.  Single-cell analyses of circulating tumor cells , 2015, Cancer biology & medicine.

[26]  Sridhar Ramaswamy,et al.  A microfluidic device for label-free, physical capture of circulating tumor cell-clusters , 2015, Nature Methods.

[27]  Wenjun Guo,et al.  The Epithelial-Mesenchymal Transition Generates Cells with Properties of Stem Cells , 2008, Cell.

[28]  Jayadeva,et al.  Discovery of rare cells from voluminous single cell expression data , 2018, Nature Communications.

[29]  L. J. K. Wee,et al.  Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors , 2017, Nature Genetics.

[30]  Karl Pearson F.R.S..  LIII. On lines and planes of closest fit to systems of points in space , 1901 .

[31]  John Hines,et al.  Optimization and Evaluation of a Novel Size Based Circulating Tumor Cell Isolation System , 2015, PloS one.

[32]  Eugene J. Lim,et al.  Microfluidic, marker-free isolation of circulating tumor cells from blood samples , 2014, Nature Protocols.

[33]  Ben S. Wittner,et al.  AR Expression in Breast Cancer CTCs Associates with Bone Metastases , 2018, Molecular Cancer Research.

[34]  M. G. van der Wijst,et al.  Single-cell RNA sequencing identifies cell type-specific cis-eQTLs and co-expression QTLs , 2018, Nature Genetics.

[35]  T. Tan,et al.  Epithelial-mesenchymal transition spectrum quantification and its efficacy in deciphering survival and drug responses of cancer patients , 2014, EMBO molecular medicine.

[36]  Woncheol Lee,et al.  Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells , 2019, Nature Communications.

[37]  D. Heymann,et al.  Circulating Tumor Cells: A Review of Non-EpCAM-Based Approaches for Cell Enrichment and Isolation. , 2016, Clinical chemistry.

[38]  Ben S. Wittner,et al.  Single-Cell RNA Sequencing Identifies Extracellular Matrix Gene Expression by Pancreatic Circulating Tumor Cells , 2014, Cell reports.

[39]  A. Nobel,et al.  Supervised risk predictor of breast cancer based on intrinsic subtypes. , 2009, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[40]  P. Kulesa,et al.  Melanoma revives an embryonic migration program to promote plasticity and invasion , 2012, Pigment cell & melanoma research.

[41]  Jongyoon Han,et al.  Ultra-fast, label-free isolation of circulating tumor cells from blood using spiral microfluidics , 2015, Nature Protocols.

[42]  N. Beerenwinkel,et al.  Neutrophils escort circulating tumour cells to enable cell cycle progression , 2019, Nature.

[43]  Kyle W. Hukari,et al.  Fluidic Logic Used in a Systems Approach to Enable Integrated Single-Cell Functional Analysis , 2016, Front. Bioeng. Biotechnol..

[44]  F. Castro-Giner,et al.  Circulating Tumor Cell Clustering Shapes DNA Methylation to Enable Metastasis Seeding , 2019, Cell.

[45]  Stefanie S Jeffrey,et al.  Circulating tumor cell technologies , 2016, Molecular oncology.

[46]  Thong M. Cao,et al.  Circulating Tumor Cells: Diagnostic and Therapeutic Applications. , 2018, Annual review of biomedical engineering.

[47]  R. Salgia,et al.  Development of PD-1 and PD-L1 inhibitors as a form of cancer immunotherapy: a comprehensive review of registration trials and future considerations , 2018, Journal of Immunotherapy for Cancer.