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In Cancer medicine

BACKGROUND : It is unclear whether clinical factors and immune microenvironment (IME) factors are associated with tumor mutation burden (TMB) in patients with nonsmall cell lung cancer (NSCLC).

MATERIALS AND METHODS : We assessed TMB in surgical tumor specimens by performing whole exome sequencing. IME profiles, including PD-L1 tumor proportion score (TPS), stromal CD8 tumor-infiltrating lymphocyte (TIL) density, and stromal Foxp3 TIL density, were quantified by digital pathology using a machine learning algorithm. To detect factors associated with TMB, clinical data, and IME factors were assessed by means of a multiple regression model.

RESULTS : We analyzed tumors from 200 of the 246 surgically resected NSCLC patients between September 2014 and September 2015. Patient background: median age (range) 70 years (39-87); male 37.5%; smoker 27.5%; pathological stage (p-stage) I/II/III, 63.5/22.5/14.0%; histological type Ad/Sq, 77.0/23.0%; primary tumor location upper/lower, 58.5/41.5%; median PET SUV 7.5 (0.86-29.8); median serum CEA (sCEA) level 3.4 ng/mL (0.5-144.3); median serum CYFRA 21-1 (sCYFRA) level 1.2 ng/mL (1.0-38.0); median TMB 2.19/ Mb (0.12-64.38); median PD-L1 TPS 15.1% (0.09-77.4); median stromal CD8 TIL density 582.1/mm2 (120.0-4967.6);, and median stromal Foxp3 TIL density 183.7/mm2 (6.3-544.0). The multiple regression analysis identified three factors associated with higher TMB: smoking status: smoker, increase PET SUV, and sCEA level: >5 ng/mL (P < .001, P < .001, and P = .006, respectively).

CONCLUSIONS : The IME factors assessed were not associated with TMB, but our findings showed that, in addition to smoking, PET SUV and sCEA levels may be independent predictors of TMB. TMB and IME factors are independent factors in resected NSCLC.

Ono Akira, Terada Yukihiro, Kawata Takuya, Serizawa Masakuni, Isaka Mitsuhiro, Kawabata Takanori, Imai Toru, Mori Keita, Muramatsu Koji, Hayashi Isamu, Kenmotsu Hirotsugu, Ohshima Keiichi, Urakami Kenichi, Nagashima Takeshi, Kusuhara Masatoshi, Akiyama Yasuto, Sugino Takashi, Ohde Yasuhisa, Yamaguchi Ken, Takahashi Toshiaki


CEA, immune microenvironment, machine learning, nonsmall cell lung cancer, tumor mutation burden, whole-slide imaging