Evidence map›Paper›PMID 37072536›Full record

ArticleCancer immunology, immunotherapy : CII2023

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

W de Koning, F F Feenstra, F G J Calkoen, J van der Lugt, L A Kester, D A M Mustafa

Abstract read
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Article in Cancer immunology, immunotherapy : CII, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

W de KoningTumor Immuno-Pathology Laboratory, Department of Pathology and Clinical Bioinformatics, Erasmus University Medical Centre, Rotterdam, The Netherlands.
F F FeenstraPrincess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
F G J CalkoenPrincess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
J van der LugtPrincess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
L A KesterPrincess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
D A M MustafaTumor Immuno-Pathology Laboratory, Department of Pathology and Clinical Bioinformatics, Erasmus University Medical Centre, Rotterdam, The Netherlands. d.mustafa@erasmusmc.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDefining 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.

resultsOur 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.

conclusionsThe 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.

Indexed as

EpendymomaTranscriptomeFormaldehydeGene Expression ProfilingHumansParaffin EmbeddingSequence Analysis, RNATissue FixationTumor MicroenvironmentFormaldehydeEpendymomaNanoStringRNA sequencingTargeted gene expression immune profilesTranscriptome analysisTumor immune microenvironment

Identifiers

PMID37072536
PMCPMC10361846

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.