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Starfysh reveals heterogeneous spatial dynamics in the breast tumor microenvironment

Siyu He, Yinuo Jin, Achille Nazaret, Lingting Shi, Xueer Chen, Sham Rampersaud, Bahawar S. Dhillon, Izabella Valdez, Lauren E Friend, Joy Linyue Fan, Cameron Y Park, Rachel Mintz, Yeh-Hsing Lao, David Carrera, Kaylee W Fang, Kaleem Mehdi, Madeline Rohde, José L. McFaline-Figueroa, David Blei, Kam W. Leong, Alexander Y Rudensky, George Plitas, Elham Azizi
doi: https://doi.org/10.1101/2022.11.21.517420
Siyu He
1Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
2Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10027, USA
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Yinuo Jin
1Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
2Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10027, USA
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Achille Nazaret
2Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10027, USA
3Department of Computer Science, Columbia University, New York, NY 10027, USA
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Lingting Shi
2Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10027, USA
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Xueer Chen
2Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10027, USA
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Sham Rampersaud
4Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, CA 94143, USA
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Bahawar S. Dhillon
5Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
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Izabella Valdez
6Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Lauren E Friend
1Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
2Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10027, USA
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Joy Linyue Fan
1Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
2Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10027, USA
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Cameron Y Park
1Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
2Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10027, USA
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Rachel Mintz
7Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130
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Yeh-Hsing Lao
1Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
8Department of Pharmaceutical Sciences, University at Buffalo, The State University of New York, Buffalo NY 14214
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David Carrera
3Department of Computer Science, Columbia University, New York, NY 10027, USA
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Kaylee W Fang
1Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
3Department of Computer Science, Columbia University, New York, NY 10027, USA
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Kaleem Mehdi
9Department of Biological Sciences, Fordham University, New York, NY 10458, USA
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Madeline Rohde
10Briarcliff High School, Briarcliff Manor, New York, NY 10510, USA
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José L. McFaline-Figueroa
1Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
2Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10027, USA
11Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10032, USA
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David Blei
3Department of Computer Science, Columbia University, New York, NY 10027, USA
12Department of Statistics, Columbia University, New York, NY, USA
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Kam W. Leong
1Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
11Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10032, USA
13Department of Systems Biology, Columbia University Irving Medical Center, New York 10027, NY 10032, USA
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Alexander Y Rudensky
5Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
14Howard Hughes Medical Institute, Memorial Sloan Kettering Cancer Center, New York 10027, NY 10065, USA
15Ludwig Center at Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
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  • For correspondence: rudenska@mskcc.org plitasg@mskcc.org ea2690@columbia.edu
George Plitas
5Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
14Howard Hughes Medical Institute, Memorial Sloan Kettering Cancer Center, New York 10027, NY 10065, USA
15Ludwig Center at Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
16Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
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  • For correspondence: rudenska@mskcc.org plitasg@mskcc.org ea2690@columbia.edu
Elham Azizi
1Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
2Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10027, USA
3Department of Computer Science, Columbia University, New York, NY 10027, USA
11Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10032, USA
17Data Science Institute, Columbia University, New York, NY 10027, USA
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  • For correspondence: rudenska@mskcc.org plitasg@mskcc.org ea2690@columbia.edu
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Abstract

Spatially-resolved gene expression profiling provides valuable insight into tissue organization and cell-cell crosstalk; however, spatial transcriptomics (ST) lacks single-cell resolution. Current ST analysis methods require single-cell RNA sequencing data as a reference for a rigorous interpretation of cell states and do not utilize associated histology images. Significant sample variation further complicates the integration of ST datasets, which is essential for identifying commonalities across tissues or altered cellular wiring in disease. Here, we present Starfysh, the first comprehensive computational toolbox for joint modeling of ST and histology data, dissection of refined cell states, and systematic integration of multiple ST datasets from complex tissues. Starfysh uses an auxiliary deep generative model that incorporates archetypal analysis and any known cell state markers to avoid the need for a single-cell-resolution reference in characterizing known or novel tissue-specific cell states. Additionally, Starfysh improves the characterization of spatial dynamics in complex tissues by leveraging histology images and enables the comparison of niches as spatial “hubs” across tissues. Integrative analysis of primary estrogen receptor-positive (ER+) breast cancer, triple-negative breast cancer (TNBC), and metaplastic breast cancer (MBC) tumors using Starfysh led to the identification of heterogeneous patient- and disease-specific hubs as well as a shared stromal hub with varying spatial orientation. Our results show the ability to delineate the spatial co-evolution of tumor and immune cell states and their crosstalk underlying intratumoral heterogeneity in TNBC and revealed metabolic reprogramming shaping immunosuppressive hubs in aggressive MBC. Starfysh is publicly available (https://github.com/azizilab/starfysh).

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/azizilab/starfysh

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 24, 2022.
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Starfysh reveals heterogeneous spatial dynamics in the breast tumor microenvironment
Siyu He, Yinuo Jin, Achille Nazaret, Lingting Shi, Xueer Chen, Sham Rampersaud, Bahawar S. Dhillon, Izabella Valdez, Lauren E Friend, Joy Linyue Fan, Cameron Y Park, Rachel Mintz, Yeh-Hsing Lao, David Carrera, Kaylee W Fang, Kaleem Mehdi, Madeline Rohde, José L. McFaline-Figueroa, David Blei, Kam W. Leong, Alexander Y Rudensky, George Plitas, Elham Azizi
bioRxiv 2022.11.21.517420; doi: https://doi.org/10.1101/2022.11.21.517420
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Starfysh reveals heterogeneous spatial dynamics in the breast tumor microenvironment
Siyu He, Yinuo Jin, Achille Nazaret, Lingting Shi, Xueer Chen, Sham Rampersaud, Bahawar S. Dhillon, Izabella Valdez, Lauren E Friend, Joy Linyue Fan, Cameron Y Park, Rachel Mintz, Yeh-Hsing Lao, David Carrera, Kaylee W Fang, Kaleem Mehdi, Madeline Rohde, José L. McFaline-Figueroa, David Blei, Kam W. Leong, Alexander Y Rudensky, George Plitas, Elham Azizi
bioRxiv 2022.11.21.517420; doi: https://doi.org/10.1101/2022.11.21.517420

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