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Michael Feldman
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MA25 - Precision Medicine in Advanced NSCLC (ID 352)
- Event: WCLC 2019
- Type: Mini Oral Session
- Track: Advanced NSCLC
- Presentations: 1
- Now Available
- Moderators:Sebastian Defranchi, Karen Kelly
- Coordinates: 9/10/2019, 14:30 - 16:00, Dublin (1997)
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MA25.02 - Arrangement and Architecture of Tumor-Infiltrating Lymphocyte on H&E Slides Predict OS in Nivolumab Treated Non-Small Cell Lung Cancer (Now Available) (ID 2911)
14:30 - 16:00 | Author(s): Michael Feldman
- Abstract
- Presentation
Background
Immune checkpoint inhibitors (ICI) are a promising and novel approach to treating chemotherapy refractory advanced NSCLC as well as first-line combination therapy in certain NSCLC. Nivolumab, a PD-L1 inhibitor is a promising ICI showing durable benefit with low toxicity in these patients. While PD-L1 positivity is an established tissue based biomarker for response to Nivolumab, studies have shown response rates ranging from 20-50%. Recent research has shown that TILs have been implicated in cancer aggressiveness as well as immune response. In this work, we go beyond simply counting TILs, and apply novel computer-extracted features characterizing the interaction and spatial co-localization of TILs and cancer nuclei (SpaTIL) in stratifying patients based on OS following nivolumab therapy.
Method
H&E tissue slides obtained from pre-treatment biopsies of 96 NSCLC patients treated with nivolumab were digitized and included for this study from 3 different institutions with the tumor region annotated by pathologists. Then 85 SpaTIL features related to TIL density, architecture and co-localization with tumor cells have been extracted to represent each patient. The most discriminative and uncorrelated features were selected by Elastic-Net regularized Cox-regression model to predict OS. The model was trained on D1 (n=25) and independently validated in D2 (n=32) and D3 (n=64). Multivariate analysis with clinico-pathologic factors was also performed.
Result
The top features consisted of the abundance of TILs around tumor cells and the distribution of the TILs. On the validation set, SpaTIL classifier yielded a HR=3.03 (95%CI=1.1 -8.35; p=0.042) on D2 and HR=4.12 (95%CI=1.87-9.09; p=0.02) on D3 by a log-rank test. On multivariate analysis with stage, smoking, histologic type, total lymphocyte count (See Table 1) SpaTIL was independently prognostic of OS (HR=7.88; 95%CI=1.66 – 37.216; p=0.009).
Table 1. Multivariate analysis for overall survival on the validation sets D2 and D3 Variables
HR(95% CI)
p value
Age (>65 vs <=65 yrs)
0.99(0.97-1.03)
0.67
Gender (Male vs Female)
1.05(0.75-2.79)
0.88
Smoking Status
(Former vs Never smoker)
3.19(0.92-11.061)
0.07
Histological Subtypes (Adeno vs Squamous)1
1.06(0.13-8.54)
0.95
EGFR status
1.32(0.49-3.52)
0.58
ALK status
0.63(0.36-1.10)
0.10
Total lymphocyte count
0.99(0.99-1.00)
0.33
SpaTIL Classifier
7.88(1.66-37.216)
0.009
CI = confidence interval; HR = Mantel-Haenszel Hazard ratio. Values in bold are statistically significant, p<=0.05.
Conclusion
Spatial interaction of TILs and cancer are independently prognostic of OS in nivolumab treated NSCLC. Further validation needs to be done to evaluate its utility.
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