Prognostic significance of tumor microenvironment assessed by machine learning algorithm in surgically resected non-small cell lung cancer.

Yukihiro Terada,Mitsuhiro Isaka,Akira Ono,Takuya Kawata,Masakuni Serizawa,Keita Mori,Koji Muramatsu,Kiyoshi Tone,Hirotsugu Kenmotsu,Keiichi Ohshima,Kenichi Urakami,Takeshi Nagashima,Masatoshi Kusuhara,Yasuto Akiyama,Takashi Sugino,Toshiaki Takahashi,Yasuhisa Ohde

Cancer reports (Hoboken, N.J.)（2023）

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摘要

Our approach demonstrated that the IME factors are related to survival in patients with NSCLC. The quantitative assessment of IME factors enables to discriminate patients with high risk of recurrence, who can be the candidates for adjuvant therapy. Assessing the CD8 TIL density in the combination of epithelium and stroma might be more useful than their individual assessment because it is a simple and time-saving analysis of TILs in WSI.

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关键词

immune microenvironment, machine learning, non-small cell lung cancer, prognosis, whole-slide imaging

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