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Proteomic analysis predicts anti-angiogenic resistance in recurred glioblastoma.
Jeon, Hanwool; Byun, Joonho; Kang, Hayeong; Kim, Kyunggon; Lee, Eunyeup; Kim, Jeong Hoon; Hong, Chang Ki; Song, Sang Woo; Kim, Young-Hoon; Chong, Sangjoon; Kim, Jae Hyun; Nam, Soo Jeong; Park, Ji Eun; Lee, Seungjoo.
Afiliación
  • Jeon H; Translational Biomedical Research Group, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea.
  • Byun J; Department of Neurological Surgery, Brain Tumor Center, Asan Medical Center, University of Ulsan College of Medicine 88, Olympic-ro 43-gil, Songpa-gu, Seoul, Republic of Korea.
  • Kang H; Bio-Medical Institute of Technology, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Kim K; Department of Neurological Surgery, Brain Tumor Center, Asan Medical Center, University of Ulsan College of Medicine 88, Olympic-ro 43-gil, Songpa-gu, Seoul, Republic of Korea.
  • Lee E; Department of Neurological Surgery, Brain Tumor Center, Asan Medical Center, University of Ulsan College of Medicine 88, Olympic-ro 43-gil, Songpa-gu, Seoul, Republic of Korea.
  • Kim JH; Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea.
  • Hong CK; Translational Biomedical Research Group, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea.
  • Song SW; Department of Neurological Surgery, Brain Tumor Center, Asan Medical Center, University of Ulsan College of Medicine 88, Olympic-ro 43-gil, Songpa-gu, Seoul, Republic of Korea.
  • Kim YH; Bio-Medical Institute of Technology, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Chong S; Department of Neurological Surgery, Brain Tumor Center, Asan Medical Center, University of Ulsan College of Medicine 88, Olympic-ro 43-gil, Songpa-gu, Seoul, Republic of Korea.
  • Kim JH; Department of Neurological Surgery, Brain Tumor Center, Asan Medical Center, University of Ulsan College of Medicine 88, Olympic-ro 43-gil, Songpa-gu, Seoul, Republic of Korea.
  • Nam SJ; Department of Neurological Surgery, Brain Tumor Center, Asan Medical Center, University of Ulsan College of Medicine 88, Olympic-ro 43-gil, Songpa-gu, Seoul, Republic of Korea.
  • Park JE; Department of Neurological Surgery, Brain Tumor Center, Asan Medical Center, University of Ulsan College of Medicine 88, Olympic-ro 43-gil, Songpa-gu, Seoul, Republic of Korea.
  • Lee S; Department of Neurological Surgery, Brain Tumor Center, Asan Medical Center, University of Ulsan College of Medicine 88, Olympic-ro 43-gil, Songpa-gu, Seoul, Republic of Korea.
J Transl Med ; 21(1): 69, 2023 02 02.
Article en En | MEDLINE | ID: mdl-36732815
BACKGROUND: Recurrence is common in glioblastoma multiforme (GBM) because of the infiltrative, residual cells in the tumor margin. Standard therapy for GBM consists of surgical resection followed by chemotherapy and radiotherapy, but the median survival of GBM patients remains poor (~ 1.5 years). For recurrent GBM, anti-angiogenic treatment is one of the common treatment approaches. However, current anti-angiogenic treatment modalities are not satisfactory because of the resistance to anti-angiogenic agents in some patients. Therefore, we sought to identify novel prognostic biomarkers that can predict the therapeutic response to anti-angiogenic agents in patients with recurrent glioblastoma. METHODS: We selected patients with recurrent GBM who were treated with anti-angiogenic agents and classified them into responders and non-responders to anti-angiogenic therapy. Then, we performed proteomic analysis using liquid-chromatography mass spectrometry (LC-MS) with formalin-fixed paraffin-embedded (FFPE) tissues obtained from surgical specimens. We conducted a gene-ontology (GO) analysis based on protein abundance in the responder and non-responder groups. Based on the LC-MS and GO analysis results, we identified potential predictive biomarkers for anti-angiogenic therapy and validated them in recurrent glioblastoma patients. RESULTS: In the mass spectrometry-based approach, 4957 unique proteins were quantified with high confidence across clinical parameters. Unsupervised clustering analysis highlighted distinct proteomic patterns (n = 269 proteins) between responders and non-responders. The GO term enrichment analysis revealed a cluster of genes related to immune cell-related pathways (e.g., TMEM173, FADD, CD99) in the responder group, whereas the non-responder group had a high expression of genes related to nuclear replisome (POLD) and damaged DNA binding (ERCC2). Immunohistochemistry of these biomarkers showed that the expression levels of TMEM173 and FADD were significantly associated with the overall survival and progression-free survival of patients with recurrent GBM. CONCLUSIONS: The candidate biomarkers identified in our protein analysis may be useful for predicting the clinical response to anti-angiogenic agents in patients with recurred GBM.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Encefálicas / Glioblastoma Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Transl Med Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Encefálicas / Glioblastoma Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Transl Med Año: 2023 Tipo del documento: Article
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