Impact of Region-of-Interest Size on Immune Profiling Using Multiplex Immunofluorescence Tyramide Signal Amplification for Paraffin-Embedded Tumor Tissues

Sun, Baohua; Fernández, Caddie Laberiano; Salazar, Ruth; Zhang, Jiexin; Rendon, Jose Luis Solorzano; Lee, John; Soto, Luisa M. Solis; Wistuba, Ignacio I.; Parra, Edwin R.

doi:10.1159/000523751

Cited by 6 publications

(4 citation statements)

References 25 publications

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“…We annotated a total of 1,076 ROIs from the mIF slides. The average ROIs per patient is 13.8, which is higher than the number of ROIs needed to achieve stable correlation compared to analyzing the entire slide demonstrated in prior work [23]. After cell segmentation, 3,229,582 cells were identified.…”

Section: Resultsmentioning

confidence: 97%

Radiomics Correlation to CD68+ Tumor-Associated Macrophages in Clear Cell Renal Cell Carcinoma

Shieh,

Cen,

Varghese

et al. 2023

Oncology

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Introduction: Renal cell carcinoma (RCC) is the ninth most common cancer worldwide, with clear cell RCC (ccRCC) being the most frequent histological subtype. The tumor immune microenvironment (TIME) of ccRCC is an important factor to guide treatment, but current assessments are tissue-based, which can be time-consuming and resource-intensive. In this study, we used radiomics extracted from clinically performed computed tomography (CT) as a noninvasive surrogate for CD68 tumor-associated macrophages (TAMs), a significant component of ccRCC TIME. Methods: TAM population was measured by CD68+/PanCK+ ratio and tumor-TAM clustering was measured by normalized K function calculated from multiplex immunofluorescence (mIF). A total of 1,076 regions on mIF slides from 78 patients were included. Radiomic features were extracted from multiphase CT of the ccRCC tumor. Statistical machine learning models, including random forest, Adaptive Boosting, and ElasticNet, were used to predict TAM population and tumor-TAM clustering. Results: The best models achieved an area under the ROC curve of 0.81 (95% CI: [0.69, 0.92]) for TAM population and 0.77 (95% CI: [0.66, 0.88]) for tumor-TAM clustering, respectively. Conclusion: Our study demonstrates the potential of using CT radiomics-derived imaging markers as a surrogate for assessment of TAM in ccRCC for real-time treatment response monitoring and patient selection for targeted therapies and immunotherapies.

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Section: Resultsmentioning

confidence: 97%

Radiomics Correlation to CD68+ Tumor-Associated Macrophages in Clear Cell Renal Cell Carcinoma

Shieh,

Cen,

Varghese

et al. 2023

Oncology

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“…In this study, we originally selected 10 ROIs for analysis with the intent of expanding our understanding of the heterogeneity of the TME ( 53 ). Recent work from Sun et al., has shown that selection of 5 ROIs is able to reasonably recapitulate the TME in non-small cell lung cancer whole slide sections ( 60 ). The dependence on tissue availability and fluorescent probes that deviate from pathology standards are other technical limitations with mIF.…”

Section: Discussionmentioning

confidence: 99%

Spatial modelling of the tumor microenvironment from multiplex immunofluorescence images: methods and applications

Kumar,

Pandurengan,

Parra

et al. 2023

Front. Immunol.

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Spatial modelling methods have gained prominence with developments in high throughput imaging platforms. Multiplex immunofluorescence (mIF) provides the scope to examine interactions between tumor and immune compartment at single cell resolution using a panel of antibodies that can be chosen based on the cancer type or the clinical interest of the study. The markers can be used to identify the phenotypes and to examine cellular interactions at global and local scales. Several translational studies rely on key understanding of the tumor microenvironment (TME) to identify drivers of immune response in immunotherapy based clinical trials. To improve the success of ongoing trials, a number of retrospective approaches can be adopted to understand differences in response, recurrence and progression by examining the patient’s TME from tissue samples obtained at baseline and at various time points along the treatment. The multiplex immunofluorescence (mIF) technique provides insight on patient specific cell populations and their relative spatial distribution as qualitative measures of a favorable treatment outcome. Spatial analysis of these images provides an understanding of the intratumoral heterogeneity and clustering among cell populations in the TME. A number of mathematical models, which establish clustering as a measure of deviation from complete spatial randomness, can be applied to the mIF images represented as spatial point patterns. These mathematical models, developed for landscape ecology and geographic information studies, can be applied to the TME after careful consideration of the tumor type (cold vs. hot) and the tumor immune landscape. The spatial modelling of mIF images can show observable engagement of T cells expressing immune checkpoint molecules and this can then be correlated with single-cell RNA sequencing data.

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“…This approach uses TSA reagents, significantly increasing sensitivity while maintaining specificity and resolution, allowing detection in lowexpression targets [38,[40][41][42][43]. However, it is essential to select the areas that can represent the whole tumor section [44]. In the optimization process, cross-talking reactions or umbrella effects should be minimized or eliminated [34,37].…”

Section: Discussionmentioning

confidence: 99%

Exploring the Expression of Adenosine Pathway-Related Markers CD73 and CD39 in Colorectal and Pancreatic Carcinomas Characterized by Multiplex Immunofluorescence: A Pilot Study

Lima,

Tamegnon,

Rodriguez

et al. 2023

Pathobiology

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Introduction: Generating high levels of immunosuppressive adenosine in the tumor microenvironment contributes to cancer immune evasion. CD39 and CD73 hydrolyze adenosine triphosphate into adenosine; thus, efforts have been made to target this pathway for cancer immunotherapy. Our objective was optimizing a multiplex immunofluorescence (mIF) panel to explore the role of CD39 and CD73 within the tumor microenvironment. Materials and methods: In three-time points, a small cohort (n=8 ) of colorectal and pancreatic adenocarcinomas were automated staining using an mIF panel against CK, CD3, CD8, CD20, CD39, CD73 and CD68 to compare them with individual markers immunohistochemistry (IHC) for internal panel validation. Densities of immune cells and distances from different tumor-associated immune cells to tumor cells were exploratory assessment and compared with clinicopathologic variables and outcomes. Results: Comparing the three-time points and individual IHC staining results, we demonstrated high reproducibility of the mIF panel. CD39 and CD73 expression was low in malignant cells; the exploratory analysis showed higher densities of CD39 expression by various cells, predominantly stromal cells, followed by T cells, macrophages, and B cells. No expression of CD73 by B cells or macrophages was detected. Distance analysis revealed proximity of cytotoxic T cells, macrophages, and T cells expressing CD39 to malignant cells, suggesting a close regulatory signal driven by this adenosine marker. Conclusions: We optimized an mIF panel for detection of markers in the adenosine pathway, an emerging clinically relevant pathway. The densities and spatial distribution demonstrated that this pathway may modulate aspects of the tumor immune microenvironment.

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Impact of Region-of-Interest Size on Immune Profiling Using Multiplex Immunofluorescence Tyramide Signal Amplification for Paraffin-Embedded Tumor Tissues

Cited by 6 publications

References 25 publications

Radiomics Correlation to CD68+ Tumor-Associated Macrophages in Clear Cell Renal Cell Carcinoma

Radiomics Correlation to CD68+ Tumor-Associated Macrophages in Clear Cell Renal Cell Carcinoma

Spatial modelling of the tumor microenvironment from multiplex immunofluorescence images: methods and applications

Exploring the Expression of Adenosine Pathway-Related Markers CD73 and CD39 in Colorectal and Pancreatic Carcinomas Characterized by Multiplex Immunofluorescence: A Pilot Study

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