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

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 WuKohei 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

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Pages (from-to)	285-301.e4
Journal	Cell Systems
Volume	14
Issue number	4
DOIs	https://doi.org/10.1016/j.cels.2023.03.004
State	Published - Apr 19 2023

Keywords

cell-cell interactions
latent space factorization
single-cell transcriptomics
spatial analysis
spatial transcriptomics
transfer learning
tumor microenvironment

ASJC Scopus subject areas

Pathology and Forensic Medicine
Histology
Cell Biology

Access to Document

10.1016/j.cels.2023.03.004

Cite this

Deshpande, A., Loth, M., Sidiropoulos, D. N., Zhang, S., Yuan, L., Bell, A. T. F., Zhu, Q., Ho, W. J., Santa-Maria, C., Gilkes, D. M., Williams, S. R., Uytingco, C. R., Chew, J., Hartnett, A., Bent, Z. W., Favorov, A. V., Popel, A. S., Yarchoan, M., Kiemen, A., ... Fertig, E. J. (2023). Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces. Cell Systems, 14(4), 285-301.e4. https://doi.org/10.1016/j.cels.2023.03.004

Deshpande, A, Loth, M, Sidiropoulos, DN, Zhang, S, Yuan, L, Bell, ATF, Zhu, Q , Ho, WJ , Santa-Maria, C , Gilkes, DM, Williams, SR, Uytingco, CR, Chew, J, Hartnett, A, Bent, ZW, Favorov, AV , Popel, AS , Yarchoan, M , Kiemen, A, Wu, PH, Fujikura, K, Wirtz, D , Wood, LD , Zheng, L , Jaffee, EM , Anders, RA , Danilova, L , Stein-O'Brien, G , Kagohara, LT & Fertig, EJ 2023, 'Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces', Cell Systems, vol. 14, no. 4, pp. 285-301.e4. https://doi.org/10.1016/j.cels.2023.03.004

@article{82da83981d16486aab40a27c686e9d87,

title = "Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces",

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",

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

note = "Publisher Copyright: {\textcopyright} 2023 Elsevier Inc.",

year = "2023",

month = apr,

day = "19",

doi = "10.1016/j.cels.2023.03.004",

language = "English (US)",

volume = "14",

pages = "285--301.e4",

journal = "Cell Systems",

issn = "2405-4712",

publisher = "Cell Press",

number = "4",

}

TY - JOUR

T1 - Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces

AU - Deshpande, Atul

AU - Loth, Melanie

AU - Sidiropoulos, Dimitrios N.

AU - Zhang, Shuming

AU - Yuan, Long

AU - Bell, Alexander T.F.

AU - Zhu, Qingfeng

AU - Ho, Won Jin

AU - Santa-Maria, Cesar

AU - Gilkes, Daniele M.

AU - Williams, Stephen R.

AU - Uytingco, Cedric R.

AU - Chew, Jennifer

AU - Hartnett, Andrej

AU - Bent, Zachary W.

AU - Favorov, Alexander V.

AU - Popel, Aleksander S.

AU - Yarchoan, Mark

AU - Kiemen, Ashley

AU - Wu, Pei Hsun

AU - Fujikura, Kohei

AU - Wirtz, Denis

AU - Wood, Laura D.

AU - Zheng, Lei

AU - Jaffee, Elizabeth M.

AU - Anders, Robert A.

AU - Danilova, Ludmila

AU - Stein-O'Brien, Genevieve

AU - Kagohara, Luciane T.

AU - Fertig, Elana J.

PY - 2023/4/19

Y1 - 2023/4/19

N2 - 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.

AB - 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.

KW - cell-cell interactions

KW - latent space factorization

KW - single-cell transcriptomics

KW - spatial analysis

KW - spatial transcriptomics

KW - transfer learning

KW - tumor microenvironment

UR - http://www.scopus.com/inward/record.url?scp=85153139918&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85153139918&partnerID=8YFLogxK

U2 - 10.1016/j.cels.2023.03.004

DO - 10.1016/j.cels.2023.03.004

M3 - Article

C2 - 37080163

AN - SCOPUS:85153139918

SN - 2405-4712

VL - 14

SP - 285-301.e4

JO - Cell Systems

JF - Cell Systems

IS - 4

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this