Longitudinal Detection of Tumor-Specific Peptides in Cerebrospinal Fluid for Pediatric Brain Tumor Surveillance.

Overview

Authors: Kelsi M. Chesney¹, Jeffrey R. Whiteaker², Brian Hood³, Ming Zhou⁴, Huizen Zhang¹, Samuel Rivero-Hinojosa¹, Amanda G. Paulovich², Thomas P. Conrads⁴, Brian R. Rood¹

ORCID iDs: Jeffrey R. Whiteaker, Ming Zhou, Samuel Rivero-Hinojosa, Amanda G. Paulovich

Brain Tumor Institute, Center for Cancer and Immunology Research, Children’s National Research Institute, Washington, DC 20010, USA; (K.M.C.)
Fred Hutchinson Cancer Center, University of Washington, Seattle, WA 98109, USA
Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20817, USA
Women’s Health Integrated Research Center, Women’s Service Line, Inova Health System, Annandale, VA 22003, USA

Institutions: Children's National (United States); University of Washington (United States); Fred Hutch Cancer Center (United States); Henry M. Jackson Foundation (United States); Inova Health System (United States)

Journal: Cells, volume 15, issue 5, article 474

Dates: received 14 January 2026; accepted 25 February 2026; published online 5 March 2026

Type: Research article · Language: English

License: CC BY

Identifiers: DOI 10.3390/cells15050474 · PMID 41827907 · PMCID PMC12984984 · OpenAlex W7133893679

Open access: gold, a free copy (OpenAlex)

Status: data only

Categories: genetics / omics (modality), other (modality), human (organism), other condition (population), clinical / translational (subfield)

Methods: Statistics

Keywords: cerebrospinal fluid, pediatric brain tumors, proteomics, mass spectrometry, tumor-specific peptides, liquid biopsy, longitudinal disease monitoring, neuro-oncology

MeSH: Biomarkers, Tumor*, Brain Neoplasms*, Peptides*, Child, Child, Preschool, Female, Humans, Longitudinal Studies, Male, Medulloblastoma, Proteomics (* major topic)

Topic: Advanced Proteomics Techniques and Applications (Spectroscopy, Chemistry), according to OpenAlex

Funding: U.S. National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) (R50 CA211499, U01 CA271407); Lilabean Foundation (44844); Jeff Gordon Children’s Foundation (44568); Aven Foundation

Citations: cited by 1 paper (Europe PMC); 57 references in the paper

Abstract

Pediatric brain tumor survivors remain at high risk of recurrence, yet current surveillance strategies relying on neuroimaging and cerebrospinal fluid (CSF) cytology have limited sensitivity for early or minimal disease. Tumor-specific peptides (TSPs) derived from individual tumors represent a promising class of highly specific biomarkers for longitudinal disease monitoring through CSF-based proteomic analysis. In this study, tumor tissue and serial CSF samples from six pediatric brain tumor patients (five medulloblastomas and one atypical teratoid/rhabdoid tumor (ATRT)) were analyzed using an integrated proteogenomic workflow combining discovery and targeted mass spectrometry. TSPs were identified from resected tumor tissue and matched against shotgun CSF proteomic datasets to nominate candidate biomarkers. High-confidence peptides were synthesized as isotopically labeled standards and quantified longitudinally using targeted multiple reaction monitoring. Two TSP biomarkers derived from individualized pediatric brain tumors (one medulloblastoma and one ATRT) demonstrated robust detection in serial CSF samples and exhibited temporal concordance with radiographic disease course, declining with treatment response and increasing during disease progression. These findings establish the feasibility of detecting and longitudinally quantifying TSPs in CSF and support further investigation of individualized proteomic biomarkers for treatment response monitoring and disease surveillance in pediatric brain tumors.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

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Data

Datasets cited

uniprot.org/uniprot, at UniProt; found in the text, “2.2. Discovery Liquid Chromatography–Tandem…”

Data Availability Statement

The data presented in this study are not publicly available due to ethical and privacy restrictions related to patient confidentiality. De-identified data may be made available from the corresponding author upon reasonable request and with appropriate institutional approvals.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 9 authors, 8 keywords, 11 MeSH terms, 4 funders, 57 references.

Cite

This paper

Chesney, K. M., Whiteaker, J. R., Hood, B., Zhou, M., Zhang, H., Rivero-Hinojosa, S., Paulovich, A. G., Conrads, T. P., & Rood, B. R. (2026). Longitudinal Detection of Tumor-Specific Peptides in Cerebrospinal Fluid for Pediatric Brain Tumor Surveillance. Cells, 15(5), 474. https://doi.org/10.3390/cells15050474

BibTeX

@article{chesney2026longitudinal, author = {Chesney, Kelsi M. and Whiteaker, Jeffrey R. and Hood, Brian and Zhou, Ming and Zhang, Huizen and Rivero-Hinojosa, Samuel and Paulovich, Amanda G. and Conrads, Thomas P. and Rood, Brian R.}, title = {{Longitudinal Detection of Tumor-Specific Peptides in Cerebrospinal Fluid for Pediatric Brain Tumor Surveillance}}, journal = {Cells}, year = {2026}, month = mar, volume = {15}, number = {5}, pages = {474}, publisher = {Multidisciplinary Digital Publishing Institute (MDPI)}, issn = {2073-4409}, doi = {10.3390/cells15050474}, url = {https://doi.org/10.3390/cells15050474}, pmid = {41827907}, pmcid = {PMC12984984} }

RIS

TY - JOUR AU - Chesney, Kelsi M. AU - Whiteaker, Jeffrey R. AU - Hood, Brian AU - Zhou, Ming AU - Zhang, Huizen AU - Rivero-Hinojosa, Samuel AU - Paulovich, Amanda G. AU - Conrads, Thomas P. AU - Rood, Brian R. TI - Longitudinal Detection of Tumor-Specific Peptides in Cerebrospinal Fluid for Pediatric Brain Tumor Surveillance T2 - Cells J2 - Cells PY - 2026 DA - 2026/03/05 VL - 15 IS - 5 SP - 474 SN - 2073-4409 PB - Multidisciplinary Digital Publishing Institute (MDPI) DO - 10.3390/cells15050474 UR - https://doi.org/10.3390/cells15050474 LA - en ER -

CSL-JSON

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