Characterizing the tumor immune microenvironment of ependymomas using targeted gene expression profiles and RNA sequencing

Background Defining the tumor immune microenvironment (TIME) of patients using transcriptome analysis is gaining more popularity. Here, we examined and discussed the pros and cons of using RNA sequencing for fresh frozen samples and targeted gene expression immune profiles (NanoString) for formalin-...

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Veröffentlicht in:Cancer Immunology, Immunotherapy Immunotherapy, 2023-08, Vol.72 (8), p.2659-2670
Hauptverfasser: de Koning, W., Feenstra, F. F., Calkoen, F. G. J., van der Lugt, J., Kester, L. A., Mustafa, D. A. M.
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container_issue 8
container_start_page 2659
container_title Cancer Immunology, Immunotherapy
container_volume 72
creator de Koning, W.
Feenstra, F. F.
Calkoen, F. G. J.
van der Lugt, J.
Kester, L. A.
Mustafa, D. A. M.
description Background Defining the tumor immune microenvironment (TIME) of patients using transcriptome analysis is gaining more popularity. Here, we examined and discussed the pros and cons of using RNA sequencing for fresh frozen samples and targeted gene expression immune profiles (NanoString) for formalin-fixed, paraffin-embedded (FFPE) samples to characterize the TIME of ependymoma samples. Results Our results showed a stable expression of the 40 housekeeping genes throughout all samples. The Pearson correlation of the endogenous genes was high. To define the TIME, we first checked the expression of the PTPRC gene, known as CD45 , and found it was above the detection limit in all samples by both techniques. T cells were identified consistently using the two types of data. In addition, both techniques showed that the immune landscape was heterogeneous in the 6 ependymoma samples used for this study. Conclusions The low-abundant genes were detected in higher quantities using the NanoString technique, even when FFPE samples were used. RNA sequencing is better suited for biomarker discovery, fusion gene detection, and getting a broader overview of the TIME. The technique that was used to measure the samples had a considerable effect on the type of immune cells that were identified. The limited number of tumor-infiltrating immune cells compared to the high density of tumor cells in ependymoma can limit the sensitivity of RNA expression techniques regarding the identification of the infiltrating immune cells.
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F. ; Calkoen, F. G. J. ; van der Lugt, J. ; Kester, L. A. ; Mustafa, D. A. M.</creator><creatorcontrib>de Koning, W. ; Feenstra, F. F. ; Calkoen, F. G. J. ; van der Lugt, J. ; Kester, L. A. ; Mustafa, D. A. M.</creatorcontrib><description>Background Defining the tumor immune microenvironment (TIME) of patients using transcriptome analysis is gaining more popularity. Here, we examined and discussed the pros and cons of using RNA sequencing for fresh frozen samples and targeted gene expression immune profiles (NanoString) for formalin-fixed, paraffin-embedded (FFPE) samples to characterize the TIME of ependymoma samples. Results Our results showed a stable expression of the 40 housekeeping genes throughout all samples. The Pearson correlation of the endogenous genes was high. To define the TIME, we first checked the expression of the PTPRC gene, known as CD45 , and found it was above the detection limit in all samples by both techniques. T cells were identified consistently using the two types of data. In addition, both techniques showed that the immune landscape was heterogeneous in the 6 ependymoma samples used for this study. Conclusions The low-abundant genes were detected in higher quantities using the NanoString technique, even when FFPE samples were used. RNA sequencing is better suited for biomarker discovery, fusion gene detection, and getting a broader overview of the TIME. The technique that was used to measure the samples had a considerable effect on the type of immune cells that were identified. The limited number of tumor-infiltrating immune cells compared to the high density of tumor cells in ependymoma can limit the sensitivity of RNA expression techniques regarding the identification of the infiltrating immune cells.</description><identifier>ISSN: 0340-7004</identifier><identifier>EISSN: 1432-0851</identifier><identifier>DOI: 10.1007/s00262-023-03450-2</identifier><identifier>PMID: 37072536</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Cancer Research ; CD45 antigen ; Fusion protein ; Gene expression ; Immunology ; Lymphocytes T ; Medicine ; Medicine &amp; Public Health ; Microenvironments ; Oncology ; Paraffin ; Ribonucleic acid ; RNA ; Transcriptomes ; Tumor cells ; Tumor-infiltrating lymphocytes</subject><ispartof>Cancer Immunology, Immunotherapy, 2023-08, Vol.72 (8), p.2659-2670</ispartof><rights>The Author(s) 2023</rights><rights>2023. The Author(s).</rights><rights>The Author(s) 2023. 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F.</creatorcontrib><creatorcontrib>Calkoen, F. G. J.</creatorcontrib><creatorcontrib>van der Lugt, J.</creatorcontrib><creatorcontrib>Kester, L. A.</creatorcontrib><creatorcontrib>Mustafa, D. A. M.</creatorcontrib><title>Characterizing the tumor immune microenvironment of ependymomas using targeted gene expression profiles and RNA sequencing</title><title>Cancer Immunology, Immunotherapy</title><addtitle>Cancer Immunol Immunother</addtitle><addtitle>Cancer Immunol Immunother</addtitle><description>Background Defining the tumor immune microenvironment (TIME) of patients using transcriptome analysis is gaining more popularity. Here, we examined and discussed the pros and cons of using RNA sequencing for fresh frozen samples and targeted gene expression immune profiles (NanoString) for formalin-fixed, paraffin-embedded (FFPE) samples to characterize the TIME of ependymoma samples. Results Our results showed a stable expression of the 40 housekeeping genes throughout all samples. The Pearson correlation of the endogenous genes was high. To define the TIME, we first checked the expression of the PTPRC gene, known as CD45 , and found it was above the detection limit in all samples by both techniques. T cells were identified consistently using the two types of data. In addition, both techniques showed that the immune landscape was heterogeneous in the 6 ependymoma samples used for this study. Conclusions The low-abundant genes were detected in higher quantities using the NanoString technique, even when FFPE samples were used. RNA sequencing is better suited for biomarker discovery, fusion gene detection, and getting a broader overview of the TIME. The technique that was used to measure the samples had a considerable effect on the type of immune cells that were identified. 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RNA sequencing is better suited for biomarker discovery, fusion gene detection, and getting a broader overview of the TIME. The technique that was used to measure the samples had a considerable effect on the type of immune cells that were identified. The limited number of tumor-infiltrating immune cells compared to the high density of tumor cells in ependymoma can limit the sensitivity of RNA expression techniques regarding the identification of the infiltrating immune cells.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>37072536</pmid><doi>10.1007/s00262-023-03450-2</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record>
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subjects Cancer Research
CD45 antigen
Fusion protein
Gene expression
Immunology
Lymphocytes T
Medicine
Medicine & Public Health
Microenvironments
Oncology
Paraffin
Ribonucleic acid
RNA
Transcriptomes
Tumor cells
Tumor-infiltrating lymphocytes
title Characterizing the tumor immune microenvironment of ependymomas using targeted gene expression profiles and RNA sequencing
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