Kohei Hamada, Junzo Hamanishi, Akihiko Ueda, Shiro Takamatsu, Kosuke Yoshihara, Takayuki Nagasawa, T. Seki, Akira Kikuchi, Etsuko Fujimoto, Mana Taki, Koji Yamanoi, Ryusuke Murakami, Kazuki Kumada, K. Oda, Muneaki Shimada, Aikou Okamoto, Masaki Mandai, Noriomi Matsumura
Transcriptomic classification methods have been proposed for ovarian clear cell carcinoma. However, their clinical significance and association with pathologically evaluated tumor-infiltrating lymphocytes (TILs) remain unclear. We established two large transcriptomic datasets and analyzed RNA-sequencing data from 189 (JGOG3025-TR1 cohort) and 38 (Kyoto cohort) ovarian clear cell carcinomas. Representative histopathological slides were also digitized (102 and 38, respectively). Cell types were classified by two state-of-the-art artificial-intelligence models, and TILs were quantified. The transcriptomically defined immune subtype was associated with significantly poor prognosis (hazard ratio, 2.54; 95% CI, 1.42-4.54; p = 0.002 for OS). However, this group also contained significantly higher proportion of advanced-stage cases (p = 0.003), and multivariate analyses showed no independent prognostic effect (hazard ratio, 1.32; 95% CI, 0.68-2.58; p = 0.42 for OS). In contrast, the pathologically defined inflamed group demonstrated a trend toward improved survival, and the inflamed phenotype emerged as a statistically significant favorable prognostic factor for both OS and PFS in multivariate analyses (hazard ratio, 0.32; 95% CI, 0.13-0.78; p = 0.013 for OS. hazard ratio, 0.32; 95% CI, 0.15-0.67; p = 0.0026 for PFS). These findings indicate a discordance between transcriptome- and pathology-based immune classifications and suggest greater prognostic relevance of pathology-derived immune status.