Bluesky Facebook Reddit Email

Classifying pediatric brain tumors by liquid biopsy using artificial intelligence

02.17.26 | St. Jude Children's Research Hospital

Fluke 87V Industrial Digital Multimeter

Fluke 87V Industrial Digital Multimeter is a trusted meter for precise measurements during instrument integration, repairs, and field diagnostics.


(MEMPHIS, Tenn. – February 17, 2026) Liquid biopsies, which test body fluids that contain cancerous material, including circulating tumor DNA (ctDNA), are a noninvasive way to learn about a cancer’s biology. However, technological limitations with the small amount of ctDNA available from pediatric brain tumor liquid biopsies have previously stymied broad use of the approach for those patients. To address this, St. Jude Children’s Research Hospital scientists, in collaboration with scientists at the Hopp Children's Cancer Center Heidelberg (KiTZ), German Cancer Research Center (DKFZ) and other international centers, created Methylation-based Predictive Algorithm for CNS Tumors (M-PACT). M-PACT uses AI to sift through ctDNA in cerebrospinal fluid and molecularly classify tumors based on their DNA methylation pattern. The resource, published today in Nature Cancer , sets a new standard for pediatric brain tumor diagnostics, treatment monitoring and surveillance.

In a compelling demonstration of functionality, M-PACT successfully identified 92% of brain tumors in a benchmarking test; it can also differentiate relapse from secondary tumors and can track if a cancer is getting more aggressive or responding to treatment with no extra input. Beyond brain tumors, M-PACT has the potential to be broadly applicable to many cancer types.

“This is a next-generation assay and computational framework that we’ve optimized and applied across a range of pediatric brain tumor patients,” said corresponding author Paul Northcott, PhD , Center of Excellence in Neuro-Oncology Sciences (CENOS) director and Department of Developmental Neurobiology member. “M-PACT is about taking liquid biopsy to another level in pediatric neuro-oncology and applying the technology across many different clinical scenarios.”

“Taking liquid biopsy to another level”

A key function of tissue-based biopsies is to describe DNA methylation patterns, the chemical modifications to DNA that help regulate gene activity. In cancer, these patterns often become abnormal in ways that act like a fingerprint for specific tumor types, guiding clinicians to the cancer’s identity. While this approach is potent using tissue biopsy samples, the same classifiers fall short in liquid biopsies.

“Traditionally, methylation-based diagnostics for ctDNA use classifiers designed for tumor tissue, which have higher DNA input,” said co-first author Katie Han , a PhD student in the St. Jude Graduate School of Biomedical Sciences and Department of Developmental Neurobiology and MD candidate at University of Tennessee Health Sciences Center. “We reversed the usual flow and designed M-PACT for ctDNA itself with applicability to tissue, instead of the other way around.”

M-PACT utilizes a novel deep neural network training strategy using more than 5,000 DNA methylation profiles across roughly 100 tumor entities. This brings methylation-based ctDNA analysis up to, and beyond, current standards seen from tissue biopsies.

“We developed M-PACT by computationally mixing large reference datasets with normal cell-free DNA datasets,” said co-first author Kyle Smith, PhD , Department of Developmental Neurobiology. “We trained it extensively and showed that even tiny amounts of ctDNA can be accurately classified.”

As proof of concept, the researchers used M-PACT to make diagnoses at the time of surgery using cerebrospinal fluid only and demonstrated its potential use during treatment and follow-up. “If a tumor reoccurs years later, M-PACT can reliably determine whether it’s a true relapse or a second malignancy,” Northcott said.

M-PACT gives unmatched insight into cancer microenvironment

M-PACT's sensitivity enables it to look beyond tumor cells to identify noncancerous cell types contributing to the tumor microenvironment. “Most DNA in cerebrospinal fluid is from something else, the ‘negative space’ of the tumor, which we previously ignored,” Smith said. “Now we can predict what fraction comes from T cells, B cells, or other sources.”

This opens questions about how cancers manipulate normal cells and microenvironments — everything involved in creating the perfect storm. “M-PACT provides us with a new lens to monitor disease evolution, especially during therapy , when tissue sampling isn’t typically done,” said Han. “Now we can start to see how both the tumor and its microenvironment change with therapeutic pressure.”

While M-PACT is immediately applicable to pediatric brain tumors, Northcott is confident its robust framework offers a wide range of potential use cases. “Although we applied this to pediatric brain tumors, it will clearly be useful in other solid tumors and hematological malignancies as well,” he said. “The informatics will need to grow to classify the full scope of cancer types diagnosed in children, but we’ve developed something quite powerful that is likely to be more broadly adopted in the community.”

The power of team science

This body of work relied on tightly knit partnerships between St. Jude investigators, scientists at the KiTZ, DKFZ and several other participating institutions, which were integral to building the large sample cohort of clinically annotated liquid biopsy samples. “Our study is a prime example of what can be accomplished when we approach science as a team and bring together complementary skills and expertise to achieve a common goal,” said Northcott. “The technical and computational innovations that were fundamental to the success of this study would not have been possible without our international network of collaborators.”

Authors and funding

The study’s other co-senior authors are Johannes Gojo, Medical University of Vienna; and Kristian Pajtler and Kendra Maass, Hopp Children’s Cancer Center, Heidelberg University Hospital, German Cancer Consortium and German Cancer Research Center, and Heidelberg University. The study’s other co-first author is Tom Fischer, Hopp Children’s Cancer Center, Heidelberg University Hospital, German Cancer Consortium and German Cancer Research Center, and Heidelberg University. The study’s other authors are Daniel Senfter, Natalia Stepien, Sibylle Madlener, Christine Haberler and Maria Schmook, Medical University of Vienna; Stefanie Volz, Nathalie Schwarz, Tatjana Wedig and Stefan Pfister, Hopp Children’s Cancer Center, Heidelberg University Hospital, German Cancer Consortium and German Cancer Research Center, and Heidelberg University; Judith de Bont and Esther Hulleman, Amsterdam University Medical Centers and Princess Maxima Center for Pediatric Oncology; Hannu Haapasalo, Fimlab Laboratories Ltd.; Justina Dargvainiene and Frank Leypoldt, University Hospital Schleswig-Holstein Kiel/Lübeck; Joonas Haapasalo, Fimlab Laboratories Ltd., Tampere University Hospital and Tampere University; Kristiina Nordfors, Tampere University Hospital and Tampere University; and Anna Kostecka, Hong Lin, Taha Soliman, Sandeep Dhanda, Santosh Upadhyaya, Patrick Blackburn, Brent Orr, Amar Gajjar and Giles Robinson, St. Jude.

The study was supported by the Verein unser_kind, the Forschungsgesellschaft für Cerebrale Tumore, Ein Kiwi gegen Krebs, the Mark Foundation for Cancer Research (Emerging Leader Award), St. Baldrick’s Foundation (Robert J. Arceci Innovation Award), the Brain Tumor Funders’ Collaborative, the National Cancer Institute (P01CA096832; R01CA270785 and R01CA259372), the FWF der Wissenschaftsfonds (#J4353‑B28), the OeNB Jubiläumsfonds (#18535), the Physician Researcher Pathway Scholarships of the Medical University of Vienna, the City of Vienna Fund for Innovative Interdisciplinary Cancer Research (#21080), the CCP Starter Grant 2020, the Oncomine Clinical Research Grant 2020, the Emil Aaltonen Foundation, the Competitive State Research Financing of the Expert Responsibility Area of Tampere University Hospital, the Finnish Ministry of Social Affairs and Health, the Tampere University Foundation Trust, the Väre Foundation for Pediatric Cancer Research, the Foundation for Pediatric Research, the Robert Connor Dawes Scientific Fellowship of the National Brain Tumor Charity and the American Lebanese Syrian Associated Charities (ALSAC), the fundraising and awareness organization of St. Jude.

St. Jude Media Relations Contact

Chelsea Bryant
Desk: (901) 595-0564
Cell: (256) 244-2048
chelsea.bryant@stjude.org
media@stjude.org

St. Jude Children’s Research Hospital

St. Jude Children’s Research Hospital is leading the way the world understands, treats, and cures childhood catastrophic diseases. As the only National Cancer Institute-designated Comprehensive Cancer Center devoted solely to children, St. Jude advances groundbreaking research and shares its discoveries worldwide to accelerate progress in pediatric medicine. Treatments developed at St. Jude have helped increase overall childhood cancer survival rates from 20% to 80% since the hospital opened more than 60 years ago. Through collaboration and innovation, St. Jude is working to ensure that children everywhere have access to the best possible care. To learn more, visit stjude.org , read St. Jude Progress, a digital magazine , and follow St. Jude on social media at @stjuderesearch .

Nature Cancer

10.1038/s43018-026-01115-4

17-Feb-2026

Keywords

Article Information

Contact Information

Chelsea Bryant
St. Jude Children's Research Hospital
chelsea.bryant@stjude.org

How to Cite This Article

APA:
St. Jude Children's Research Hospital. (2026, February 17). Classifying pediatric brain tumors by liquid biopsy using artificial intelligence. Brightsurf News. https://www.brightsurf.com/news/1WRO4QDL/classifying-pediatric-brain-tumors-by-liquid-biopsy-using-artificial-intelligence.html
MLA:
"Classifying pediatric brain tumors by liquid biopsy using artificial intelligence." Brightsurf News, Feb. 17 2026, https://www.brightsurf.com/news/1WRO4QDL/classifying-pediatric-brain-tumors-by-liquid-biopsy-using-artificial-intelligence.html.