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

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/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