A Cancer-Specific Qualitative Method for Estimating the Proportion of Tumor-Infiltrating Immune Cells
Tumor-infiltrating immune cells are important components in the tumor microenvironment (TME) and different types of these cells exert different effects on tumor development and progression; these effects depend upon the type of cancer involved. Several methods have been developed for estimating the...
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doaj-f010831e5385420994a2fe3d86ce208b2021-05-14T08:11:01ZengFrontiers Media S.A.Frontiers in Immunology1664-32242021-05-011210.3389/fimmu.2021.672031672031A Cancer-Specific Qualitative Method for Estimating the Proportion of Tumor-Infiltrating Immune CellsHuiting Xiao0Jiashuai Zhang1Kai Wang2Kai Wang3Kai Song4Hailong Zheng5Jing Yang6Keru Li7Rongqiang Yuan8Wenyuan Zhao9Yang Hui10Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, ChinaTumor-infiltrating immune cells are important components in the tumor microenvironment (TME) and different types of these cells exert different effects on tumor development and progression; these effects depend upon the type of cancer involved. Several methods have been developed for estimating the proportion of immune cells using bulk transcriptome data. However, there is a distinct lack of methods that are capable of predicting the immune contexture in specific types of cancer. Furthermore, the existing methods are based on absolute gene expression and are susceptible to experimental batch effects, thus resulting in incomparability across different datasets. In this study, we considered two common neoplasms as examples (colorectal cancer [CRC] and melanoma) and introduced the Tumor-infiltrating Immune Cell Proportion Estimator (TICPE), a cancer-specific qualitative method for estimating the proportion of tumor-infiltrating immune cells. The TICPE was based on the relative expression orderings (REOs) of gene pairs within a sample and is notably insensitive to batch effects. Performance evaluation using public expression data with mRNA mixtures, single-cell RNA-Seq (scRNA-Seq) data, immunohistochemistry data, and simulated bulk RNA-seq samples, indicated that the TICPE can estimate the proportion of immune cells with levels of accuracy that are clearly superior to other methods. Furthermore, we showed that the TICPE could effectively detect prognostic signals in patients with tumors and changes in the fractions of immune cells during immunotherapy in melanoma. In conclusion, our work presented a unique novel method, TICPE, to estimate the proportion of immune cells in specific cancer types and explore the effect of the infiltration of immune cells on the efficacy of immunotherapy and the prognosis of cancer. The source code for TICPE is available at https://github.com/huitingxiao/TICPE.https://www.frontiersin.org/articles/10.3389/fimmu.2021.672031/fulltumor microenvironmentrelative expression orderingssignature genesprognosisimmunotherapy |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Huiting Xiao Jiashuai Zhang Kai Wang Kai Wang Kai Song Hailong Zheng Jing Yang Keru Li Rongqiang Yuan Wenyuan Zhao Yang Hui |
spellingShingle |
Huiting Xiao Jiashuai Zhang Kai Wang Kai Wang Kai Song Hailong Zheng Jing Yang Keru Li Rongqiang Yuan Wenyuan Zhao Yang Hui A Cancer-Specific Qualitative Method for Estimating the Proportion of Tumor-Infiltrating Immune Cells Frontiers in Immunology tumor microenvironment relative expression orderings signature genes prognosis immunotherapy |
author_facet |
Huiting Xiao Jiashuai Zhang Kai Wang Kai Wang Kai Song Hailong Zheng Jing Yang Keru Li Rongqiang Yuan Wenyuan Zhao Yang Hui |
author_sort |
Huiting Xiao |
title |
A Cancer-Specific Qualitative Method for Estimating the Proportion of Tumor-Infiltrating Immune Cells |
title_short |
A Cancer-Specific Qualitative Method for Estimating the Proportion of Tumor-Infiltrating Immune Cells |
title_full |
A Cancer-Specific Qualitative Method for Estimating the Proportion of Tumor-Infiltrating Immune Cells |
title_fullStr |
A Cancer-Specific Qualitative Method for Estimating the Proportion of Tumor-Infiltrating Immune Cells |
title_full_unstemmed |
A Cancer-Specific Qualitative Method for Estimating the Proportion of Tumor-Infiltrating Immune Cells |
title_sort |
cancer-specific qualitative method for estimating the proportion of tumor-infiltrating immune cells |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Immunology |
issn |
1664-3224 |
publishDate |
2021-05-01 |
description |
Tumor-infiltrating immune cells are important components in the tumor microenvironment (TME) and different types of these cells exert different effects on tumor development and progression; these effects depend upon the type of cancer involved. Several methods have been developed for estimating the proportion of immune cells using bulk transcriptome data. However, there is a distinct lack of methods that are capable of predicting the immune contexture in specific types of cancer. Furthermore, the existing methods are based on absolute gene expression and are susceptible to experimental batch effects, thus resulting in incomparability across different datasets. In this study, we considered two common neoplasms as examples (colorectal cancer [CRC] and melanoma) and introduced the Tumor-infiltrating Immune Cell Proportion Estimator (TICPE), a cancer-specific qualitative method for estimating the proportion of tumor-infiltrating immune cells. The TICPE was based on the relative expression orderings (REOs) of gene pairs within a sample and is notably insensitive to batch effects. Performance evaluation using public expression data with mRNA mixtures, single-cell RNA-Seq (scRNA-Seq) data, immunohistochemistry data, and simulated bulk RNA-seq samples, indicated that the TICPE can estimate the proportion of immune cells with levels of accuracy that are clearly superior to other methods. Furthermore, we showed that the TICPE could effectively detect prognostic signals in patients with tumors and changes in the fractions of immune cells during immunotherapy in melanoma. In conclusion, our work presented a unique novel method, TICPE, to estimate the proportion of immune cells in specific cancer types and explore the effect of the infiltration of immune cells on the efficacy of immunotherapy and the prognosis of cancer. The source code for TICPE is available at https://github.com/huitingxiao/TICPE. |
topic |
tumor microenvironment relative expression orderings signature genes prognosis immunotherapy |
url |
https://www.frontiersin.org/articles/10.3389/fimmu.2021.672031/full |
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