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Article summary:

1. A novel 15-gene immune signature, Immune Paediatric Signature Score (IPASS), has been developed to identify T-cell infiltration in high-risk paediatric tumours.

2. Deconvolution algorithms such as CSX, quanTIseq, and MCP-counter poorly distinguish individual cell types in high-risk paediatric solid tumours.

3. The study provides a unique and more accurate identification of T-cell infiltrated paediatric cancers and suggests that effective immune-based interventions in high-risk paediatric cancer will require individualised analysis of the TIME.

Article analysis:

The article presents a novel transcriptional signature that identifies T-cell infiltration in high-risk pediatric cancer. The authors argue that a more refined appreciation of the tumor immune microenvironment (TIME) in childhood cancers is necessary for improved immunotherapies, as commonly used biomarkers such as tumor mutation burden (TMB), neoantigen load, and PD-L1 expression are less relevant in the pediatric setting than in adult cancers.

The authors provide a comprehensive characterization of T-cell infiltration in high-risk pediatric solid tumors using immunohistochemistry (IHC), RNA sequencing (RNA-seq), and whole genome sequencing (WGS). They cross-referenced genomic and RNA-seq data with CD8+ and CD4+ IHC staining on the same tumor specimens to define and validate a novel pediatric-specific gene signature that identifies tumors infiltrated by CD8+ T-cells.

However, the article has some limitations. Firstly, it is important to note that the study has not been formally peer-reviewed yet, which means that its findings should not guide health-related behavior or be reported in the press as conclusive. Secondly, while the authors argue that their novel signature provides a unique and more accurate identification of T-cell infiltrated pediatric cancers, they do not provide evidence comparing their signature to other existing signatures or methods for identifying TILs.

Additionally, while the authors acknowledge that deconvolution algorithms have only weak correlations with IHC-determined measures of T-cell infiltration, they do not explore why this might be the case or discuss potential limitations of these algorithms. Furthermore, while they suggest that effective immune-based interventions in high-risk pediatric cancer will require individualized analysis of TIME, they do not discuss potential challenges or limitations associated with such an approach.

Overall, while the article presents interesting findings regarding T-cell infiltration in high-risk pediatric cancer and highlights the need for improved understanding of TIME in childhood cancers, it would benefit from further exploration of potential limitations and challenges associated with the authors' approach.