Multiparametric MRI Along with Machine Learning Informs on Molecular Underpinnings, Prognosis, and Treatment Response in Pediatric Low-Grade Glioma

Abstract

In this study, we present a comprehensive radiogenomic analysis of pediatric low-grade gliomas (pLGGs), combining treatment-naive multiparametric MRI and RNA sequencing. We identified three immunological clusters using XCell enrichment scores, highlighting an 'immune-hot' group correlating with poorer prognosis, suggesting potential benefits from immunotherapies. A radiomic signature predicting immunological profiles showed balanced accuracies of 81.5% and 84.4% across discovery and replication cohorts, respectively. Our clinicoradiomic model predicted progression-free survival with concordance indices of 0.71 and 0.77 in these cohorts, and the clinicoradiomic scores correlated with treatment response (p = 0.001). We also explored germline variants and transcriptomic pathways related to clinicoradiomic risk, identifying those involved in tumor growth and immune responses. This is the first radiogenomic analysis in pLGGs that enhances prognostication by prediction of immunological profiles, assessment of patients' risk of progression, prediction of treatment response to standard-of-care therapies, and early stratification of patients to identify potential candidates for novel therapies targeting specific pathways.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This study was funded by National Institute of Health Grant Fundings 75N91019D00024, Supplement 3U2CHL156291-03S2, and 75N91019D00024.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Children's Brain Tumor Network (CBTN)

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Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

Data Availability

All data produced in the present study are available upon reasonable request to the authors

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