Nature Communications (Jan 2025)
Multiparametric MRI along with machine learning predicts prognosis and treatment response in pediatric low-grade glioma
- Anahita Fathi Kazerooni,
- Adam Kraya,
- Komal S. Rathi,
- Meen Chul Kim,
- Arastoo Vossough,
- Nastaran Khalili,
- Ariana M. Familiar,
- Deep Gandhi,
- Neda Khalili,
- Varun Kesherwani,
- Debanjan Haldar,
- Hannah Anderson,
- Run Jin,
- Aria Mahtabfar,
- Sina Bagheri,
- Yiran Guo,
- Qi Li,
- Xiaoyan Huang,
- Yuankun Zhu,
- Alex Sickler,
- Matthew R. Lueder,
- Saksham Phul,
- Mateusz Koptyra,
- Phillip B. Storm,
- Jeffrey B. Ware,
- Yuanquan Song,
- Christos Davatzikos,
- Jessica B. Foster,
- Sabine Mueller,
- Michael J. Fisher,
- Adam C. Resnick,
- Ali Nabavizadeh
Affiliations
- Anahita Fathi Kazerooni
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Adam Kraya
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Komal S. Rathi
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Meen Chul Kim
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Arastoo Vossough
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Nastaran Khalili
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Ariana M. Familiar
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Deep Gandhi
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Neda Khalili
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Varun Kesherwani
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Debanjan Haldar
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Hannah Anderson
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Run Jin
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Aria Mahtabfar
- Department of Neurosurgery, Thomas Jefferson University
- Sina Bagheri
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Yiran Guo
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Qi Li
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Xiaoyan Huang
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Yuankun Zhu
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Alex Sickler
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Matthew R. Lueder
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Saksham Phul
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Mateusz Koptyra
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Phillip B. Storm
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Jeffrey B. Ware
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania
- Yuanquan Song
- Department of Pathology and Laboratory Medicine, The Children’s Hospital of Philadelphia
- Christos Davatzikos
- AI2D Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania
- Jessica B. Foster
- Division of Oncology, The Children’s Hospital of Philadelphia
- Sabine Mueller
- Department of Neurology and Pediatrics, University of California San Francisco
- Michael J. Fisher
- Division of Oncology, The Children’s Hospital of Philadelphia
- Adam C. Resnick
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- Ali Nabavizadeh
- Center for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia
- DOI
- https://doi.org/10.1038/s41467-024-55659-z
- Journal volume & issue
-
Vol. 16,
no. 1
pp. 1 – 16
Abstract
Abstract Pediatric low-grade gliomas (pLGGs) exhibit heterogeneous prognoses and variable responses to treatment, leading to tumor progression and adverse outcomes in cases where complete resection is unachievable. Early prediction of treatment responsiveness and suitability for immunotherapy has the potential to improve clinical management and outcomes. Here, we present a radiogenomic analysis of pLGGs, integrating MRI and RNA sequencing data. We identify three immunologically distinct clusters, with one group characterized by increased immune activity and poorer prognosis, indicating potential benefit from immunotherapies. We develop a radiomic signature that predicts these immune profiles with over 80% accuracy. Furthermore, our clinicoradiomic model predicts progression-free survival and correlates with treatment response. We also identify genetic variants and transcriptomic pathways associated with progression risk, highlighting links to tumor growth and immune response. This radiogenomic study in pLGGs provides a framework for the identification of high-risk patients who may benefit from targeted therapies.
