Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces

Atul Deshpande; Melanie Loth; Dimitrios N Sidiropoulos; Shuming Zhang; Long Yuan; Alexander T F Bell; Qingfeng Zhu; Won Jin Ho; Cesar Santa-Maria; Daniele M Gilkes; Stephen R Williams; Cedric R Uytingco; Jennifer Chew; Andrej Hartnett; Zachary W Bent; Alexander V Favorov; Aleksander S Popel; Mark Yarchoan; Ashley Kiemen; Pei-Hsun Wu; Kohei Fujikura; Denis Wirtz; Laura D Wood; Lei Zheng; Elizabeth M Jaffee; Robert A Anders; Ludmila Danilova; Genevieve Stein-O'Brien; Luciane T Kagohara; Elana J Fertig

doi:10.1016/j.cels.2023.03.004

Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces

Cell Syst. 2023 Apr 19;14(4):285-301.e4. doi: 10.1016/j.cels.2023.03.004.

Authors

Atul Deshpande¹, Melanie Loth¹, Dimitrios N Sidiropoulos², Shuming Zhang³, Long Yuan⁴, Alexander T F Bell¹, Qingfeng Zhu¹, Won Jin Ho¹, Cesar Santa-Maria⁵, Daniele M Gilkes⁵, Stephen R Williams⁶, Cedric R Uytingco⁶, Jennifer Chew⁶, Andrej Hartnett⁶, Zachary W Bent⁶, Alexander V Favorov¹, Aleksander S Popel⁷, Mark Yarchoan¹, Ashley Kiemen⁸, Pei-Hsun Wu⁹, Kohei Fujikura¹⁰, Denis Wirtz¹¹, Laura D Wood¹², Lei Zheng¹, Elizabeth M Jaffee¹, Robert A Anders¹³, Ludmila Danilova¹, Genevieve Stein-O'Brien¹, Luciane T Kagohara¹, Elana J Fertig¹⁴

Affiliations

¹ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Convergence Institute, Johns Hopkins University, Baltimore, MD, USA; Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
² Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Convergence Institute, Johns Hopkins University, Baltimore, MD, USA; Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Cellular and Molecular Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
³ Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
⁴ Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Immunology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
⁵ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
⁶ 10x Genomics, Inc., Pleasanton, CA, USA.
⁷ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
⁸ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
⁹ Department of Chemical and Biomolecular Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USA.
¹⁰ Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
¹¹ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Convergence Institute, Johns Hopkins University, Baltimore, MD, USA; Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Chemical and Biomolecular Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USA; Johns Hopkins Physical Sciences - Oncology Center and Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA.
¹² Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
¹³ Convergence Institute, Johns Hopkins University, Baltimore, MD, USA; Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
¹⁴ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Convergence Institute, Johns Hopkins University, Baltimore, MD, USA; Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Applied Mathematics and Statistics, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USA. Electronic address: ejfertig@jhmi.edu.

Abstract

Recent advances in spatial transcriptomics (STs) enable gene expression measurements from a tissue sample while retaining its spatial context. This technology enables unprecedented in situ resolution of the regulatory pathways that underlie the heterogeneity in the tumor as well as the tumor microenvironment (TME). The direct characterization of cellular co-localization with spatial technologies facilities quantification of the molecular changes resulting from direct cell-cell interaction, as it occurs in tumor-immune interactions. We present SpaceMarkers, a bioinformatics algorithm to infer molecular changes from cell-cell interactions from latent space analysis of ST data. We apply this approach to infer the molecular changes from tumor-immune interactions in Visium spatial transcriptomics data of metastasis, invasive and precursor lesions, and immunotherapy treatment. Further transfer learning in matched scRNA-seq data enabled further quantification of the specific cell types in which SpaceMarkers are enriched. Altogether, SpaceMarkers can identify the location and context-specific molecular interactions within the TME from ST data.

Keywords: cell-cell interactions; latent space factorization; single-cell transcriptomics; spatial analysis; spatial transcriptomics; transfer learning; tumor microenvironment.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Cell Communication
Computational Biology
Gene Expression Profiling
Tumor Microenvironment*

Abstract

Publication types

MeSH terms

Grants and funding