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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

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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 3

T cell infiltrate has prognostic value and distinct states in TN and high-proliferation ER+ breast cancer.

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T cell infiltrate has prognostic value and distinct states in TN and hig...
(A) Kaplan-Meier analysis of abundance of CD3 T cells versus overall survival (OS) in TNBC discovery (left) and validation cohort (right). (B) Kaplan-Meier analysis of abundance of CD20 B cells versus OS in TNBC discovery (left) and validation cohort (right). (C) Multivariable CPH modeling adding patient age, tumor size, and stage to CD3 T cell high variable defined in A. (D) Multivariable CPH modeling adding patient age, tumor size and stage to CD20 B cell high variable defined in B. (E) Kaplan-Meier analysis of abundance of CD3 T cell versus OS in all patients who are ER+ (left) and patients who are ER+ with high (above the median) tumor proliferation (right). (F) CPH modeling of CD3 T cell abundance plus clinical variables in high- and low-proliferation ER+ tumors. (G) Kaplan-Meier analysis of all patients who are ER+ and patients with TNBC stratified into 4 groups by median tumor proliferation and median T cell abundance. (H) CPH modeling of CD3 T cell abundance plus clinical variables in high- and low-proliferation TNBC tumors. (I) Mean number of T cell neighbors (within 25 μm) of T cells in tissues from high- and low-proliferation ER+ or TNBC tumors in IMC cohort. (J) Ki67 intensity indicating proliferation levels of T cells in tissues from high- and low-proliferation ER+ or TNBC tumors in IMC cohort. (K) CD44 intensity in T cells, indicating memory/effector phenotypes in IMC tissues. (A–H) All Kaplan-Meier P values obtained from the log-rank test, validation cohort corrected for testing multiple cell types with Benjamini-Hochberg method. CPH modeling P values for cell type variable given in panel titles; the HR estimates are marked by boxes, and data are shown as 95% CI. (I–K) Significance was found with the Kruskal-Wallis test. Post hoc Tukey’s HSD was used for pairwise comparisons between groups. Box plots show the median and interquartile range (IQR), and whiskers indicate 1.5× the IQR.

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