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Multiplexed immunofluorescence delineates proteomic cancer cell states associated with metabolism
Anup Sood, Alexandra M. Miller, Edi Brogi, Yunxia Sui, Joshua Armenia, Elizabeth McDonough, Alberto Santamaria-Pang, Sean Carlin, Aleksandra Stamper, Carl Campos, Zhengyu Pang, Qing Li, Elisa Port, Thomas G. Graeber, Nikolaus Schultz, Fiona Ginty, Steven M. Larson, Ingo K. Mellinghoff
Anup Sood, Alexandra M. Miller, Edi Brogi, Yunxia Sui, Joshua Armenia, Elizabeth McDonough, Alberto Santamaria-Pang, Sean Carlin, Aleksandra Stamper, Carl Campos, Zhengyu Pang, Qing Li, Elisa Port, Thomas G. Graeber, Nikolaus Schultz, Fiona Ginty, Steven M. Larson, Ingo K. Mellinghoff
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Resource and Technical Advance Oncology

Multiplexed immunofluorescence delineates proteomic cancer cell states associated with metabolism

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Abstract

The phenotypic diversity of cancer results from genetic and nongenetic factors. Most studies of cancer heterogeneity have focused on DNA alterations, as technologies for proteomic measurements in clinical specimen are currently less advanced. Here, we used a multiplexed immunofluorescence staining platform to measure the expression of 27 proteins at the single-cell level in formalin-fixed and paraffin-embedded samples from treatment-naive stage II/III human breast cancer. Unsupervised clustering of protein expression data from 638,577 tumor cells in 26 breast cancers identified 8 clusters of protein coexpression. In about one-third of breast cancers, over 95% of all neoplastic cells expressed a single protein coexpression cluster. The remaining tumors harbored tumor cells representing multiple protein coexpression clusters, either in a regional distribution or intermingled throughout the tumor. Tumor uptake of the radiotracer 18F-fluorodeoxyglucose was associated with protein expression clusters characterized by hormone receptor loss, PTEN alteration, and HER2 gene amplification. Our study demonstrates an approach to generate cellular heterogeneity metrics in routinely collected solid tumor specimens and integrate them with in vivo cancer phenotypes.

Authors

Anup Sood, Alexandra M. Miller, Edi Brogi, Yunxia Sui, Joshua Armenia, Elizabeth McDonough, Alberto Santamaria-Pang, Sean Carlin, Aleksandra Stamper, Carl Campos, Zhengyu Pang, Qing Li, Elisa Port, Thomas G. Graeber, Nikolaus Schultz, Fiona Ginty, Steven M. Larson, Ingo K. Mellinghoff

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Figure 4

Distribution of protein coexpression clusters.

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Distribution of protein coexpression clusters.
(A) Relative frequency of...
(A) Relative frequency of tumor cells representing each cluster within the complete data set (638,577 IDC cells from 26 human breast cancers). (B) Intertumoral distribution of cells representing each protein coexpression cluster. Each row in the table represents one tumor sample, and each column represents one protein coexpression cluster. Tumors were sorted by the extent of intratumoral heterogeneity, with the most homogenous tumor on top (99% of tumor cells expressing cluster C6) and the most heterogenous tumor at the bottom (coexistence of cancer cells representing 5 different protein coexpression clusters, with 3 clusters [C1, C2, and C4] contributing about one-third of the tumor cells each). The number in each cell indicates the percentage of neoplastic cells expressing a particular protein coexpression cluster. The percentage of cells expressing the most abundant cluster is shown in the area graph to the right and is 50% or greater (dashed line) in most tumors. (C) Intratumoral distribution of cells representing each protein coexpression cluster. Pie charts show the distribution of protein expression clusters in each field of view. Shown are 3 representative patterns. See Supplemental Figure 5 for a complete view of all breast cancer samples. (D) FDG tumor uptake in 26 patients with invasive ductal breast cancer. FDG uptake was measured by PET and quantified as standardized uptake values (SUVmax).

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