Cancer genetic markers according to radiotherapeutic response in patients with primary glioblastoma – Radiogenomic approach for precision medicine
- Authors
- Yang, K.[Yang, K.]; Jung, S.W.[Jung, S.W.]; Shin, H.[Shin, H.]; Lim, D.H.[Lim, D.H.]; Lee, J.-I.[Lee, J.-I.]; Kong, D.-S.[Kong, D.-S.]; Seol, H.J.[Seol, H.J.]; Kim, S.T.[Kim, S.T.]; Nam, D.-H.[Nam, D.-H.]
- Issue Date
- Feb-2019
- Publisher
- Elsevier Ireland Ltd
- Keywords
- Biomarkers; Genome; Glioblastoma; Precision medicine; Radiotherapy; Response assessment
- Citation
- Radiotherapy and Oncology, v.131, pp.66 - 74
- Journal Title
- Radiotherapy and Oncology
- Volume
- 131
- Start Page
- 66
- End Page
- 74
- URI
- https://scholarworks.bwise.kr/skku/handle/2021.sw.skku/15936
- DOI
- 10.1016/j.radonc.2018.11.025
- ISSN
- 0167-8140
- Abstract
- Background and purpose: To find genetic markers associated with response to radiotherapy (RT) in glioblastoma (GB) patients. Materials and methods: From Jan 2009 to Dec 2016, 161 patients with newly diagnosed IDH-wild type GB were treated with surgery and adjuvant concurrent chemoradiotherapy with the Stupp's regimen, and then genomic research proceeded with their surgical specimens. Among the 161 patients, 49 with clinically measurable disease on postoperative MRI were analyzed. The response evaluation to RT was based on Response Assessment in Neuro-Oncology (RANO) criteria. For genomic analyses to compare between patients with progression and non-progression, Fisher test for DNA mutations and copy number alterations and the Gene Set Enrichment Analysis (GSEA) were performed. Results: RT responses were non-progressive and progressive disease (PD) in 22 (44.9%) and 27 patients (55.1%), respectively. After three months, seven of PD exhibited pseudoprogression. For true response adjusting pseudoprogression from PD, 1-year progression-free survival for true Non-Responders (tNR-group) and true Responders (tR-group) were 0% and 45.4% (p < 0.001), and overall survival were 52.5% and 81.1% (p = 0.046), respectively. In genomic analyses, the tNR-group had more CDKN2A deletions (94.4% vs. 55.6%, p = 0.013), EGFR mutations (33.3% vs. 3.7%, p = 0.012) and less TP53 mutations (22.2% vs. 40.7%, p = 0.333) than the tR-group. In GSEA, immune-related gene sets were enriched in the tNR-group, and in contrast, some gene sets related with cell cycle were enriched in tR-groups. Conclusion: The RANO criteria were feasible for the short-term response evaluation from RT despite of pseudoprogression. Genomic differences such as CDKN2A deletion, EGFR mutation, and immune- or inflammation-related related gene sets enrichment were found to be potentially predictive markers of RT. © 2018 Elsevier B.V.
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