Assessment of associations between clinical and immune microenvironmental factors and tumor mutation burden in resected nonsmall cell lung cancer by applying machine learning to whole‐slide images. (12th May 2020)

• Record Type: Journal Article
• Authors: 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
• Is Part Of: Cancer medicine. Volume 9:Number 13(2020)
• Page Start: 4864
• Page End: 4875
• Publication Date: 2020-05-12
• Subjects: CEA -- immune microenvironment -- machine learning -- nonsmall cell lung cancer -- tumor mutation burden -- whole‐slide imaging; 616.994005
• DOI: 10.1002/cam4.3107
• Languages: English
• ISSNs: 2045-7634

Abstract

Abstract: 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/mm 2 (120.0‐4967.6);, and median stromal Foxp3 TIL density 183.7/mm 2 (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. Abstract : We were able to quantitatively evaluate the local presence of IME factors that are difficult to evaluate visually, by using a digital pathology platform. The results showed no associations between IME factors and TMB, but significant associations were found with some clinical factors. It is possible that TMB based on whole exome sequencing was not correlated with neoantigen load.