Highly multiplexed imaging reveals prognostic immune and stromal spatial biomarkers in breast cancer
Jennifer R. Eng, Elmar Bucher, Zhi Hu, Cameron R. Walker, Tyler Risom, Michael Angelo, Paula Gonzalez-Ericsson, Melinda E. Sanders, A. Bapsi Chakravarthy, Jennifer A. Pietenpol, Summer L. Gibbs, Rosalie C. Sears, Koei Chin
Jennifer R. Eng, Elmar Bucher, Zhi Hu, Cameron R. Walker, Tyler Risom, Michael Angelo, Paula Gonzalez-Ericsson, Melinda E. Sanders, A. Bapsi Chakravarthy, Jennifer A. Pietenpol, Summer L. Gibbs, Rosalie C. Sears, Koei Chin
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Research Article Immunology Oncology

Highly multiplexed imaging reveals prognostic immune and stromal spatial biomarkers in breast cancer

Abstract

Spatial profiling of tissues promises to elucidate tumor-microenvironment interactions and generate prognostic and predictive biomarkers. We analyzed single-cell spatial data from 3 multiplex imaging technologies: cyclic immunofluorescence (CycIF) data we generated from 102 patients with breast cancer with clinical follow-up as well as publicly available mass cytometry and multiplex ion-beam imaging datasets. Similar single-cell phenotyping results across imaging platforms enabled combined analysis of epithelial phenotypes to delineate prognostic subtypes among patients who are estrogen-receptor+ (ER+). We utilized discovery and validation cohorts to identify biomarkers with prognostic value. Increased lymphocyte infiltration was independently associated with longer survival in triple-negative (TN) and high-proliferation ER+ breast tumors. An assessment of 10 spatial analysis methods revealed robust spatial biomarkers. In ER+ disease, quiescent stromal cells close to tumor were abundant in tumors with good prognoses, while tumor cell neighborhoods containing mixed fibroblast phenotypes were enriched in poor-prognosis tumors. In TN disease, macrophage/tumor and B/T lymphocyte neighbors were enriched, and lymphocytes were dispersed in good-prognosis tumors, while tumor cell neighborhoods containing vimentin+ fibroblasts were enriched in poor-prognosis tumors. In conclusion, we generated comparable single-cell spatial proteomic data from several clinical cohorts to enable prognostic spatial biomarker identification and validation.

Authors

Jennifer R. Eng, Elmar Bucher, Zhi Hu, Cameron R. Walker, Tyler Risom, Michael Angelo, Paula Gonzalez-Ericsson, Melinda E. Sanders, A. Bapsi Chakravarthy, Jennifer A. Pietenpol, Summer L. Gibbs, Rosalie C. Sears, Koei Chin

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Figure 5

Prognostic multicellular neighborhoods surrounding tumor cells modeled with spatial latent Dirichlet allocation.

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Prognostic multicellular neighborhoods surrounding tumor cells modeled w...
(A) Top: CycIF staining of TNBC tissue showing tumor (panCK), T cell (CD4 and CD8), macrophage (CD68), fibroblast (vimentin), and endothelial (CD31) markers. Middle: Tumor cells colored by topic weights of select topics. Bottom: Tumor cells colored by their spatial latent Dirichlet allocation (LDA) neighborhood cluster. Tumor cells colored by the following neighborhoods: T cell (blue), macrophage (purple), mixed fibroblast (brown) and vimentin+ fibroblast (green). n = 308 patients analyzed with spatial LDA. (B and D) Heatmap of stromal cell enrichment in spatial LDA topics in a 100 μm radius of tumor cells in CycIF TNBC tissues (B) (n = 59) and ER+ tissues (D) (n = 30). Cyan arrowhead indicates cell type enrichment in topic-0 in TNBC tissues; magenta arrowhead indicates CD4 T cell enrichment in TNBC spatial LDA topics. (C and E) Heatmap of fraction of each topic in each neighborhood cluster resulting from K-means clustering (k =8) of spatial LDA topics from TNBC (C) and ER+ tissues (E). (F) Kaplan-Meier (K-M) estimate of overall survival (OS) for high and low vimentin+ fibroblast tumor neighborhoods in TNBC tissues in discovery (left) and validation cohorts (right). (G) CPH modeling of OS and recurrence-free survival (RFS) with clinical variables plus spatial LDA neighborhood from F. (H) K-M analysis of OS for high and low mixed fibroblast tumor neighborhoods in ER+ tissues in the discovery (left) and validation cohorts (right). (I) CPH modeling of OS and RFS for mixed fibroblast neighborhoods in ER+ tumors. (J and K) Pearson correlation of cell types within ER+ (J) and TNBC tissues (K) from all cohorts, colored by cohort (legend in L). Pearson correlation of neighborhood/cell type abundances, subtype in panel title, colored by cohort. (F and H) P values were calculated from the log-rank test. (G and I) CPH modeling P values for spatial variable are shown in panel titles; the HR estimates are marked by boxes, and data are shown as 95% CI. (J–L) Cell types, cohort, 2-sided Pearson correlation (r), and P values given in panel titles.