Prognostic Impact of Intratumoral Heterogeneity Based on Fractal Geometry Analysis in Operated NSCLC Patients

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The Complexity and Fractal Geometry of Nuclear Medicine Images

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Correlation of metabolic information on FDG-PET with tissue expression of immune markers in patients with non-small cell lung cancer (NSCLC) who are candidates for upfront surgery

Purpose

Eliciting antitumor T-cell response by targeting the PD-1/PD-L1 axis with checkpoint inhibitors has emerged as a novel therapeutic strategy in non-small cell lung cancer (NSCLC). The identification of predictors for sensitivity or resistance to these agents is, therefore, needed. Herein, we investigate the correlation of metabolic information on FDG-PET with tissue expression of immune-checkpoints and other markers of tumor-related immunity in resected NSCLC patients.

Materials and methods

All patients referred to our institution for upfront surgical resection of NSCLC, who were investigated with FDG-PET prior to surgery, were consecutively included in the study. From January 2010 to May 2014, 55 patients (stage IA-IIIB; M:F?=?42:13; mean age 68.9 years) were investigated. Sampled surgical tumor specimens were analyzed by immunohistochemistry (IHC) for CD68-TAMs (tumor-associated macrophages), CD8-TILs (tumor infiltrating lymphocytes), PD-1-TILs, and PD-L1 tumor expression. Immunoreactivity was evaluated, and scores were compared with imaging findings. FDG-PET images were analyzed to define semi-quantitative parameters: SUVmax and SUVmean. Metabolic information on FDG-PET was correlated with tissue markers expression and disease-free survival (DFS) considering a median follow-up of 16.2 months.

Results

Thirty-six adenocarcinomas (ADC), 18 squamous cell carcinomas (SCC), and one sarcomatoid carcinoma were analyzed. All tumors resulted positive at FDG-PET: median SUVmax 11.3 (range: 2.3–32.5) and SUVmean 6.4 (range: 1.5–13) both resulted significantly higher in SCC compared to other NSCLC histotypes (p?=?0.007 and 0.048, respectively). IHC demonstrated a median immunoreactive surface covered by CD68-TAMs of 5.41 % (range: 0.84–14.01 %), CD8-TILs of 2.9 % (range: 0.11–11.92 %), PD-1 of 0.65 % (range: 0.02–5.87 %), and PD-L1 of 0.7 % (range: 0.03–10.29 %). We found a statistically significant correlation between SUVmax and SUVmean with the expression of CD8 TILs (rho?=?0.31; p?=?0.027) and PD-1 (rho?=?0.33; p?=?0.017 and rho?=?0.36; p?=?0.009, respectively). The other tissue markers correlated as follows: CD8 TILs and PD-1 (rho?=?0.45; p?=?0.001), CD8 TILs and PD-L1 (rho?=?0.41; p?=?0.003), CD68-TAMs and PD-L1 (rho?=?0.30; p?=?0.027), PD-1 and PD-L1 (rho?=?0.26; p?=?0.059). With respect to patients’ outcome, SUVmax, SUVmean, and disease stage showed a statistically significant correlation with DFS (p?=?0.002, 0.004, and <0.001, respectively).

Conclusions

The present study shows a direct association between metabolic parameters on FDG-PET and the expression of tumor-related immunity markers, suggesting a potential role for FDG-PET to characterize the tumor microenvironment and select NSCLC patients candidate to checkpoint inhibitors.