Prediagnostic biomarkers for early detection of glioma: using case-control studies from cohorts as study approach Show others and affiliations
2022 (English) In: Neuro-Oncology Advances, E-ISSN 2632-2498, Vol. 4, p. II73-II80Article in journal (Refereed) Published
Abstract [en]
Background: Understanding the trajectory and development of disease is important and the knowledge can be used to find novel targets for therapy and new diagnostic tools for early diagnosis.
Methods: Large cohorts from different parts of the world are unique assets for research as they have systematically collected plasma and DNA over long-time periods in healthy individuals, sometimes even with repeated samples. Over time, the population in the cohort are diagnosed with many different diseases, including brain tumors.
Results: Recent studies have detected genetic variants that are associated with increased risk of glioblastoma and lower grade gliomas specifically. The impact for genetic markers to predict disease in a healthy population has been deemed low, and a relevant question is if the genetic variants for glioma are associated with risk of disease or partly consist of genes associated to survival. Both metabolite and protein spectra are currently being explored for early detection of cancer.
Conclusions: We here present a focused review of studies of genetic variants, metabolomics, and proteomics studied in prediagnostic glioma samples and discuss their potential in early diagnostics.
Place, publisher, year, edition, pages Oxford University Press, 2022. Vol. 4, p. II73-II80
Keywords [en]
genetic variants, glioblastoma, metabolites, prediagnositic sample, proteins
National Category
Cancer and Oncology
Identifiers URN: urn:nbn:se:umu:diva-209135 DOI: 10.1093/noajnl/vdac036 ISI: 000890147900012 PubMedID: 36380862 Scopus ID: 2-s2.0-85159173442 OAI: oai:DiVA.org:umu-209135 DiVA, id: diva2:1763401
Funder Swedish Research Council Swedish Cancer Society Sjöberg Foundation 2023-06-072023-06-072023-06-07 Bibliographically approved