Abstract 1381P
Background
IMpower150 study in NSCLC (NCT02366143) found no significant overall survival (OS) benefit between the Atezolizumab+Carboplatin+Paclitaxel (ACP, treatment) arm and Carboplatin+Paclitaxel+Bevacizumab (BCP, control) arm, with hazard ratio (HR): 0.85, 95% confidence interval (CI): 0.71-1.03. We applied spatial statistics algorithms to characterize the spatial interaction between tumor cells and lymphocytes in the tumor microenvironment and improved the prediction of response of ACP therapy using the generated spatial features.
Methods
A proprietary image analysis algorithm was applied on H&E pathology images of baseline tissue samples from IMpower150 patients to detect the coordinates of tumor cells and lymphocytes. To systematically extract features that capture the spatial heterogeneity of the tumor microenvironment from these cell coordinates as input, we implemented spatial statistics algorithms based on spatial point, spatial lattice and geostatistical process methods. To investigate the association between the derived spatial features and OS, Cox proportional hazard model with L2 regularization was fitted for the Atezolizumab-treated patients. The high and low response group were further identified using nested Monte Carlo Cross Validation to prevent over-fitting.
Results
284 ACP patients and 271 BCP patients with H&E pathology images and OS in the IMpower150 study were used in this analysis. 41 spatial features including Ripley’s K-function, Morista-Horn index, etc. were derived to capture the cell-cell interaction. In the identified high responder group, the HR between ACP patients and BCP patients is 0·64 (95% CI 0·45–0.91), and the p-value of the log-rank test is 0.012.
Conclusions
We developed the spatial statistics algorithms to identify biologically relevant features in the tumor microenvironment such as immune-cancer cell interactions from the H&E pathology images. Our results indicate the method can better stratify patients who benefit from the Atezolizumab treatment in comparison with standard of care therapy.
Clinical trial identification
NCT02366143.
Editorial acknowledgement
Legal entity responsible for the study
F. Hoffmann–La Roche/Genentech, a member of the Roche Group.
Funding
F. Hoffmann–La Roche/Genentech, a member of the Roche Group.
Disclosure
X. Li, R. Copping, T. Bengtsson, J. Dai: Full/Part-time employment: Genentech, Inc. F. Gaire G. Jansen: Full/Part-time employment: F. Hoffmann-La Roche AG.