ArticleGenome medicine2023
A novel transcriptional signature identifies T-cell infiltration in high-risk paediatric cancer.
Article in Genome medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- MYCN-driven metabolic remodelling of the tumour microenvironment in neuroblastoma: implications for stromal biology and CAF heterogeneity.Cancer metastasis reviews · 2026Review
- From Sequencing to Survival: The Growing Role of Precision Medicine in Paediatric Oncology.Targeted oncology · 2025Article
- Expansion of tumor-infiltrating and marrow-infiltrating lymphocytes from pediatric malignant solid tumors.Cytotherapy · 2025Article
- Immune Microenvironment in Childhood Cancers: Characteristics and Therapeutic Challenges.Cancers · 2024Review
- Immune-related signature identifies IL1R2 as an immunological and prognostic biomarker in pancreatic cancer.Journal of pancreatology · 2024Article
- Management of locally advanced non-small cell lung cancer: State of the art and future directions.Cancer communications (London, England) · 2024Review
- A novel transcriptional signature identifies T-cell infiltration in high-risk paediatric cancer.Genome medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
44 authors at 11 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMolecular profiling of the tumour immune microenvironment (TIME) has enabled the rational choice of immunotherapies in some adult cancers. In contrast, the TIME of paediatric cancers is relatively unexplored. We speculated that a more refined appreciation of the TIME in childhood cancers, rather than a reliance on commonly used biomarkers such as tumour mutation burden (TMB), neoantigen load and PD-L1 expression, is an essential prerequisite for improved immunotherapies in childhood solid cancers.
methodsWe combined immunohistochemistry (IHC) with RNA sequencing and whole-genome sequencing across a diverse spectrum of high-risk paediatric cancers to develop an alternative, expression-based signature associated with CD8
resultsA novel 15-gene immune signature, Immune Paediatric Signature Score (IPASS), was identified. Using this signature, we estimate up to 31% of high-risk cancers harbour infiltrating T-cells. In addition, we showed that PD-L1 protein expression is poorly correlated with PD-L1 RNA expression and TMB and neoantigen load are not predictive of T-cell infiltration in paediatrics. Furthermore, deconvolution algorithms are only weakly correlated with IHC measurements of T-cells.
conclusionsOur data provides new insights into the variable immune-suppressive mechanisms dampening responses in paediatric solid cancers. Effective immune-based interventions in high-risk paediatric cancer will require individualised analysis of the TIME.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.