Dataset Information

Multiplexed (18-Plex) Measurement of Signaling Targets and Cytotoxic T Cells in Trastuzumab-Treated Patients using Imaging Mass Cytometry.

ABSTRACT: PURPOSE:Imaging mass cytometry (IMC) uses metal-conjugated antibodies to provide multidimensional, objective measurement of protein targets. We used this high-throughput platform to perform an 18-plex assessment of HER2 ICD/ECD, cytotoxic T-cell infiltration and other structural and signaling proteins in a cohort of patients treated with trastuzumab to discover associations with trastuzumab benefit. EXPERIMENTAL DESIGN:An antibody panel for detection of 18 targets (pan-cytokeratin, HER2 ICD, HER2 ECD, CD8, vimentin, cytokeratin 7, ?-catenin, HER3, MET, EGFR, ERK 1-2, MEK 1-2, PTEN, PI3K p110 ?, Akt, mTOR, Ki67, and Histone H3) was used with a selection of trastuzumab-treated patients from the Hellenic Cooperative Oncology Group 10/05 trial (n = 180), and identified a case-control series. RESULTS:Patients that recurred after adjuvant treatment with trastuzumab trended toward a decreased fraction of HER2 ECD pixels over threshold compared with cases without recurrence (P = 0.057). After exclusion of the lowest HER2 expressers, 5-year recurrence events were associated with reduced total extracellular domain (ECD)/intracellular domain (ICD) ratio intensity in tumor (P = 0.044). These observations are consistent with our previous work using quantitative immunofluorescence, but represent the proof on identical cell content. We also describe the association of the ECD of HER2 with CD8 T-cell infiltration on the same slide. CONCLUSIONS:The proximity of CD8 cells as a function of the expression of the ECD of HER2 provides further evidence for the role of the immune system in the mechanism of action of trastuzumab.

SUBMITTER: Carvajal-Hausdorf DE

PROVIDER: S-EPMC6522272 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Multiplexed (18-Plex) Measurement of Signaling Targets and Cytotoxic T Cells in Trastuzumab-Treated Patients using Imaging Mass Cytometry.

Carvajal-Hausdorf Daniel E DE Patsenker Jonathan J Stanton Kelly P KP Villarroel-Espindola Franz F Esch Amanda A Montgomery Ruth R RR Psyrri Amanda A Kalogeras Konstantine T KT Kotoula Vassiliki V Foutzilas George G Schalper Kurt A KA Kluger Yuval Y Rimm David L DL

Clinical cancer research : an official journal of the American Association for Cancer Research 20190222 10

<h4>Purpose</h4>Imaging mass cytometry (IMC) uses metal-conjugated antibodies to provide multidimensional, objective measurement of protein targets. We used this high-throughput platform to perform an 18-plex assessment of HER2 ICD/ECD, cytotoxic T-cell infiltration and other structural and signaling proteins in a cohort of patients treated with trastuzumab to discover associations with trastuzumab benefit.<h4>Experimental design</h4>An antibody panel for detection of 18 targets (pan-cytokeratin ...[more]

PMID: 30796036

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Project description:Imaging Mass Cytometry (IMC) combines laser ablation and mass spectrometry to quantitate metal-conjugated primary antibodies incubated in intact tumor tissue slides. This strategy allows spatially-resolved multiplexing of dozens of simultaneous protein targets with 1μm resolution. Each slide is a spatial assay consisting of high-dimensional multivariate observations (m-dimensional feature space) collected at different spatial positions and capturing data from a single biological sample or even representative spots from multiple samples when using tissue microarrays. Often, each of these spatial assays could be characterized by several regions of interest (ROIs). To extract meaningful information from the multi-dimensional observations recorded at different ROIs across different assays, we propose to analyze such datasets using a two-step graph-based approach. We first construct for each ROI a graph representing the interactions between the m covariates and compute an m dimensional vector characterizing the steady state distribution among features. We then use all these m-dimensional vectors to construct a graph between the ROIs from all assays. This second graph is subjected to a nonlinear dimension reduction analysis, retrieving the intrinsic geometric representation of the ROIs. Such a representation provides the foundation for efficient and accurate organization of the different ROIs that correlates with their phenotypes. Theoretically, we show that when the ROIs have a particular bi-modal distribution, the new representation gives rise to a better distinction between the two modalities compared to the maximum a posteriori (MAP) estimator. We applied our method to predict the sensitivity to PD-1 axis blockers treatment of lung cancer subjects based on IMC data, achieving 97.3% average accuracy on two IMC datasets. This serves as empirical evidence that the graph of graphs approach enables us to integrate multiple ROIs and the intra-relationships between the features at each ROI, giving rise to an informative representation that is strongly associated with the phenotypic state of the entire image.

Dataset Information

Multiplexed (18-Plex) Measurement of Signaling Targets and Cytotoxic T Cells in Trastuzumab-Treated Patients using Imaging Mass Cytometry.

Publications

Multiplexed (18-Plex) Measurement of Signaling Targets and Cytotoxic T Cells in Trastuzumab-Treated Patients using Imaging Mass Cytometry.

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