MPC-04 MOLECULAR FEATURES AND CLINICAL OUTCOMES OF ELDERLY GLIOBLASTOMA PATIENTS: ANALYSES OF KANSAI NETWORK AND TCGA COHORTS

Junya Fukai, Hideyuki Arita, Toru Umehara, Ema Yoshioka, Tomoko Shofuda, Yoshinori Kodama, Manabu Kinoshita, Yoshiko Okita, Masahiro Nonaka, Takehiro Uda, Daisuke Sakamoto, Kanji Mori (+1 others)
2019 Neuro-Oncology Advances  
INTRODUCTION Aging is a negative prognostic factor in glioblastoma (GB) and the genetic background in clinical outcome of elderly GB could exist. This study investigates the difference of elderly patients from younger ones regarding molecular characteristics as well as clinical outcomes in IDH-wildtype GB. METHODS We collected adult cases diagnosed with IDH-wildtype GB and enrolled in Kansai Molecular Diagnosis Network for CNS Tumors (Kansai Network) (212 cases) and The Cancer Genome Atlas
more » ... r Genome Atlas (TCGA) project (359 cases). Clinical and pathological characteristics were analyzed retrospectively and compared between elderly cases (≥70 years) and younger ones (≤50 years). Molecular analysis included copy number alterations (CNAs) of eight genes (EGFR, PDGFRA, PTEN, CDKN2A, CDK4, MDM2, TP53, NFKBIA). RESULTS Included in the study were 92 (≥70 years)/33 (≤50 years) cases of Kansai Network and 88 (≥70 years)/69 (≤50 years) cases of TCGA. Median overall survival was 12.8 (≥70 years)/ 21.0 (≤50 years) months in Kansai Network cohort and 8.8 (≥70 years)/ 21.09 (≤50 years) months in TCGA cohort. MGMT promoter was methylated in 50 (54.3%) (≥70 years)/14 (42.4%) (≤50 years) tumors in Kansai Network and 34 (48.6%) (≥70 years)/16 (36.4%) (≤50 years) tumors in TCGA. TERT promoter was mutated in 51 (55.4%) (≥70 years)/13 (39.4%) (≤50 years) tumors in Kansai Network and unknown in TCGA. Significant difference of CNA profiles between ≥70 years and ≤50 years was as follows: PTEN del, 43 (46.7%)/8 (24.2%); CDK4 amp, 17 (18.5%)/1 (3.0%) in Kansai Network and CDKN2A del, 69 (78.4%)/ 42 (60.9%) in TCGA. CONCLUSION Elderly patients have several potential factors for poor prognosis and different molecular profiles might explain the survival differences among generations.
doi:10.1093/noajnl/vdz039.101 fatcat:u5wokwfrl5fplnz4gpncpbiwvi