Prognostic significance of spatial immune profiles in human solid cancers

Tsujikawa, Takahiro; Mitsuda, Junichi; Ogi, Hiroshi; Miyagawa‐Hayashino, Aya; Konishi, Eiichi; Itoh, Kyoko; Hirano, Shigeru

doi:10.1111/cas.14591

Cited by 38 publications

(22 citation statements)

References 71 publications

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“… 32 Further studies evaluating these differential expression profiles of OX40 + lymphocytes in tumor stroma and cancer nest are required. Various spatial relationship analyses using multiplex IHC and image cytometry 35 may further investigate these differences.…”

Section: Discussionmentioning

confidence: 99%

Prognostic significance of OX40 ⁺ lymphocytes in tumor stroma of surgically resected small-cell lung cancer

et al. 2021

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OX40 (CD134) is a co-stimulatory molecule mostly expressed on activated T lymphocytes. Previous reports have shown that OX40 can be an immuno-oncology target and a clinical biomarker for cancers of various organs. In this study, we collected formalin-fixed paraffin-embedded tumor samples from 124 patients with small-cell lung cancer (SCLC) who had undergone surgery. We analyzed the expression profiles of OX40 and other relevant molecules, such as CD4, CD8, and Foxp3, in tumor stroma and cancer nest using immunohistochemistry and investigated their association with survival. High infiltration of OX40 + lymphocytes (OX40 high ) in tumor stroma was positively associated with relapse-free survival (RFS) and overall survival (OS) compared with low infiltration of OX40 + lymphocytes (OX40 low ) (RFS, median, 26.0 months [95% confidence interval (CI), not reached (NR)–NR] vs 13.2 months [9.1–17.2], p = .024; OS, NR [95% CI, NR–NR] vs 29.8 months [21.3–38.2], p = .049). Multivariate analysis revealed that OX40 high in tumor stroma was an independent indicator of prolonged RFS. Moreover, RFS of patients with OX40 high /CD4 high in tumor stroma was significantly longer than that of patients with OX40 low /CD4 low . The RFS of patients with tumor stroma with OX40 high /CD8 high was significantly longer than that of patients with tumor stroma with OX40 low /CD8 high , OX40 high /CD8 low , or OX40 low /CD8 low . These findings suggest that OX40 + lymphocytes in tumor stroma play a complementary role in regulating the relapse of early-stage SCLC. Reinforcing immunity by coordinating the recruitment of OX40 + lymphocytes with CD4 + and CD8 + T cells in tumor stroma may constitute a potential immunotherapeutic strategy for patients with SCLC.

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Section: Discussionmentioning

confidence: 99%

Prognostic significance of OX40 ⁺ lymphocytes in tumor stroma of surgically resected small-cell lung cancer

et al. 2021

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“…Among the determinants of the anti-tumor response of immune cells, counts, phenotypes and the spatial architecture are the three most highlighted. 22,223 Initially, quantified by IHC or flow cytometry, the density of TILs was used to reflect the intensity of the anti-tumor response. 224,225 Substantial studies have proven that the intensity of TILs strongly correlates with the ICB response and clinical outcomes.…”

Section: Applications Of Immunomics In Tumor Immunotherapymentioning

confidence: 99%

Technological advances in cancer immunity: from immunogenomics to single-cell analysis and artificial intelligence

et al. 2021

Sig Transduct Target Ther

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Immunotherapies play critical roles in cancer treatment. However, given that only a few patients respond to immune checkpoint blockades and other immunotherapeutic strategies, more novel technologies are needed to decipher the complicated interplay between tumor cells and the components of the tumor immune microenvironment (TIME). Tumor immunomics refers to the integrated study of the TIME using immunogenomics, immunoproteomics, immune-bioinformatics, and other multi-omics data reflecting the immune states of tumors, which has relied on the rapid development of next-generation sequencing. High-throughput genomic and transcriptomic data may be utilized for calculating the abundance of immune cells and predicting tumor antigens, referring to immunogenomics. However, as bulk sequencing represents the average characteristics of a heterogeneous cell population, it fails to distinguish distinct cell subtypes. Single-cell-based technologies enable better dissection of the TIME through precise immune cell subpopulation and spatial architecture investigations. In addition, radiomics and digital pathology-based deep learning models largely contribute to research on cancer immunity. These artificial intelligence technologies have performed well in predicting response to immunotherapy, with profound significance in cancer therapy. In this review, we briefly summarize conventional and state-of-the-art technologies in the field of immunogenomics, single-cell and artificial intelligence, and present prospects for future research.

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“…Knowing the location of different cell populations in a tumor and the spatial distribution of the cells with other cell groups allows us to characterize a tumor to predict its response to treatment and the potential for progression and relapse. The spatial distribution of different cell phenotypes is known to be important in characterizing the tumor microenvironment, which influences recruitment of immune cells, and the microenvironment can be characterized in different regions within a tumor or studied to determine whether specific cell phenotypes are present (Tsujikawa et al, 2020). Therefore, data obtained from mIFbased digital image analysis are particularly useful for calculating functional spatial distribution metrics.…”

Section: Spatial Cellular Distributionmentioning

confidence: 99%

Methods to Determine and Analyze the Cellular Spatial Distribution Extracted From Multiplex Immunofluorescence Data to Understand the Tumor Microenvironment

Parra

2021

Front. Mol. Biosci.

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Image analysis using multiplex immunofluorescence (mIF) to detect different proteins in a single tissue section has revolutionized immunohistochemical methods in recent years. With mIF, individual cell phenotypes, as well as different cell subpopulations and even rare cell populations, can be identified with extraordinary fidelity according to the expression of antibodies in an mIF panel. This technology therefore has an important role in translational oncology studies and probably will be incorporated in the clinic. The expression of different biomarkers of interest can be examined at the tissue or individual cell level using mIF, providing information about cell phenotypes, distribution of cells, and cell biological processes in tumor samples. At present, the main challenge in spatial analysis is choosing the most appropriate method for extracting meaningful information about cell distribution from mIF images for analysis. Thus, knowing how the spatial interaction between cells in the tumor encodes clinical information is important. Exploratory analysis of the location of the cell phenotypes using point patterns of distribution is used to calculate metrics summarizing the distances at which cells are processed and the interpretation of those distances. Various methods can be used to analyze cellular distribution in an mIF image, and several mathematical functions can be applied to identify the most elemental relationships between the spatial analysis of cells in the image and established patterns of cellular distribution in tumor samples. The aim of this review is to describe the characteristics of mIF image analysis at different levels, including spatial distribution of cell populations and cellular distribution patterns, that can increase understanding of the tumor microenvironment.

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Prognostic significance of spatial immune profiles in human solid cancers

Abstract: This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Cited by 38 publications

References 71 publications

Prognostic significance of OX40 ⁺ lymphocytes in tumor stroma of surgically resected small-cell lung cancer

Prognostic significance of OX40 ⁺ lymphocytes in tumor stroma of surgically resected small-cell lung cancer

Technological advances in cancer immunity: from immunogenomics to single-cell analysis and artificial intelligence

Methods to Determine and Analyze the Cellular Spatial Distribution Extracted From Multiplex Immunofluorescence Data to Understand the Tumor Microenvironment

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Prognostic significance of spatial immune profiles in human solid cancers

Abstract: This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Cited by 38 publications

References 71 publications

Prognostic significance of OX40 + lymphocytes in tumor stroma of surgically resected small-cell lung cancer

Prognostic significance of OX40 + lymphocytes in tumor stroma of surgically resected small-cell lung cancer

Technological advances in cancer immunity: from immunogenomics to single-cell analysis and artificial intelligence

Methods to Determine and Analyze the Cellular Spatial Distribution Extracted From Multiplex Immunofluorescence Data to Understand the Tumor Microenvironment

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Prognostic significance of OX40 ⁺ lymphocytes in tumor stroma of surgically resected small-cell lung cancer

Prognostic significance of OX40 ⁺ lymphocytes in tumor stroma of surgically resected small-cell lung cancer