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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 2

Validation of staining approach.

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Validation of staining approach.
(A) Quantification of phosphoepitopes. ...
(A) Quantification of phosphoepitopes. Nude mice (n = 3 per group) harboring subcutaneous BT-474 human breast cancer xenografts were treated with a single dose of the dual PI3K/mTOR kinase inhibitor NVP-BEZ235 (10 mg/kg or 40 mg/kg) or vehicle. Tumors were collected 3 hours later, routinely processed, and stained with our multiplexed immunofluorescence method. Top: representative immunofluorescence images from one tumor per cohort, p4EBP1 = red; pS6 = green; DAPI = blue. Bottom: quantification of staining results. *P < 0.05, **P < 0.01, t test, comparing each treatment group to the control group. Original magnification: ×20, zoom ×6. (B) Number of field of views (FOVs) examined for each tumor. Only FOVs with more than 90% IDC cells were included. (C) Tissue loss during successive imaging cycles shown for one representative tumor sample (tumor 072). The y axis depicts the fraction of tumor cells that remain attached to the slide in each FOV (FOVs 1–18) during each imaging cycle and can be coregistered through all cycles. Each line graph represents one FOV. (D) Tissue loss during successive imaging cycles shown for all 26 breast cancer samples. The y axis depicts the fraction of remaining cells (solid line) with a 95% confidence interval (between quantile 2.5% and 97.5%). 638,577 IDC cells that could be coregistered throughout all staining cycles were included in the subsequent proteomic analysis. (E) Correlation of multiplexed immunofluorescence staining results with clinical laboratory improvement amendments (CLIA) assays for estrogen receptor (ER) (left) and HER2 (right) from the same tumor. ER was determined by IHC, HER2 was determined by FISH. Green represents samples that were negative in the CLIA assay, and red represents samples that were positive in the CLIA assay. The cut-off for the ER CLIA assay was 1% of cells staining positive for ER. The cut-off used for CLIA HER2 FISH amplification was a HER2/CEP17 gene copy number ratio of 2.0 or greater.

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ISSN 2379-3708

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