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The promise of Imaging Mass Cytometry

Gain unprecedented insights and answer important clinical research questions

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Biomarkers are currently used in basic and clinical research and in clinical practice, yet few biomarkers are used to predict a clinical therapeutic outcome consistently and accurately. Particularly for cancer and other diseases with high tumor heterogeneity and broad cellular signatures, the challenge to classify at an individual level confounds scientists and clinicians. Technological advances that improve how we define cellular phenotypes, expose spatial and temporal factors and improve stratification into smaller and more meaningful classifications can influence treatment decisions. Researchers are now using Imaging Mass Cytometry™ (IMC)™ to highlight novel phenotypes and identify therapeutic targets that may be relevant to developing treatment strategies or biomarkers for use in immuno-oncology or cellular therapies to increase the number of people who respond to current cancer drug treatments.
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Indicative immunotherapy biomarker in melanoma

An April 2021 publication from Martinez-Morilla et al., “Biomarker discovery in patients with immunotherapy-treated melanoma with Imaging Mass Cytometry,” demonstrated the use of IMC to quantitively measure 25 markers simultaneously to generate data from tumor, stroma, T cells, B cells and macrophages. Data were validated using other multiplexing technologies. Biopsy samples from metastatic melanoma patients who received immunotherapy were used to identify markers that were found to be associated with response and survival. This work shows how IMC helped discover a compelling biomarker potentially indicative of treatment response in melanoma.

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Novel signaling networks identified through IMC and transcriptomics data integration

The use of IMC enabled researchers to uncover the heterogeneity of cellular phenotypes and cell-to-cell interactions in the tumor microenvironment of high-grade serous ovarian cancer to understand which interactions might influence patient survival. In the publication “SIO: A spatioimageomics pipeline to identify prognostic biomarkers associated with the ovarian tumor microenvironment,” learn about the pipeline used to generate phenograph clusters for cell density and neighborhood analysis. These clusters were further used to correlate the IMC phenotype with a gene expression profile.

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Unique expression signatures in Hodgkin lymphoma aid in the development of novel biomarkers

Scientists aim to unravel the very complex tumor microenvironment (TME) of Hodgkin lymphoma by deciphering the unique immune cell architecture of the TME and for the first time unveil its phenotype. They pair IMC with single-cell transcriptome analysis and suggest implications for novel therapies, including rational combinations and predictive biomarker development, in “Single-cell transcriptome analysis reveals disease-defining T-cell subsets in the tumor microenvironment of classic Hodgkin lymphoma.”

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Answering key questions about the role of CAF’s in lung cancer

Handan Xiang, PhD

Dr. Handan Xiang, PhD
Senior Scientist at Merck

In her webinar Understanding the immunosuppressive functions of cancer-associated fibroblasts (CAFs) in lung cancer, Handan Xiang, PhD, describes how IMC was used in studies to understand cancer-associated fibroblasts in tumor stroma. Learn how this illuminated a possible therapeutic path that could potentially reverse a CAF-mediated immunosuppressive microenvironment. The work is from Xiang and team at Merck.

» Watch Handan Xiang's webinar

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For Research Use Only. Not for use in diagnostic procedures.