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Attend this session at the
2019 ASCO Annual Meeting!


Session: Developmental Immunotherapy and Tumor Immunobiology

Type: Poster Session

Time: Saturday June 1, 8:00 AM to 11:00 AM

Location: Hall A

Tumor mutational burden (TMB) and PD-L1 expression as predictors of response to immunotherapy (IO) in NSCLC.

Sub-category:
Tissue-Based Biomarkers

Category:
Developmental Immunotherapy and Tumor Immunobiology

Meeting:
2019 ASCO Annual Meeting

Abstract No:
2630

Poster Board Number:
Poster Session (Board #274)

Citation:
J Clin Oncol 37, 2019 (suppl; abstr 2630)

Author(s): Emily Castellanos, Jeremy Snider, Siraj Mahamed Ali, Daniel Backenroth, Lee A. Albacker, Karthikeyan Murugesan, Gerald Li, Garrett M. Frampton, Brian Michael Alexander, Kenneth Robert Carson; Flatiron Health, New York, NY; Foundation Medicine, Inc., Cambridge, MA

Abstract Disclosures

Abstract:

Background: PD-L1 expression and TMB, as a proxy for neoantigen burden, have been correlated with response to IO in advanced NSCLC (aNSCLC) clinical trials, but their combined utility is unclear. We assessed TMB and PD-L1 as predictors of response in aNSCLC patients (pts) after IO monotherapy in a real-world setting. Methods: Pts had a diagnosis of aNSCLC, comprehensive genomic profiling of 186-315 genes/1.1 megabase (Mb), PD-L1 testing of pre-IO specimens, and were treated in the Flatiron Health network (1/2011 - 6/2018). Clinical characteristics and real-world tumor response (rwTR) were obtained via technology-enabled abstraction of clinician notes and radiology/pathology reports, and linked to genomic data in the Flatiron Health-Foundation Medicine Clinico-Genomic Database. A general additive model examined the predictive value of TMB (as continuous measure) and PD-L1 level on rwTR. A reduced PD-L1-only model was compared to the full model using Akaike Information Criterion (AIC). rwTR predictions at representative TMB and PD-L1 levels were calculated. Results: Of 426 pts, PD-L1 expression was high (≥50%) in 140, low (1-49%) in 123, and negative (<1%) in 163. Median TMB was 9.6 mut/Mb (IQR 4.4 - 14.8) overall, 11.3 in responders and 8.7 in non-responders. TMB did not correlate with PD-L1 level (Kruskal-Wallis p=0.29). The TMB + PD-L1 model had superior prediction of rwTR than the PD-L1 model, as assessed by lower AIC score. In the combined model, higher TMB and PD-L1 levels were each associated with higher rwTR likelihood (Table). Predicted rwTR probability, % (95% CI), by TMB and PD-L1 in line 1. Conclusions: TMB and PD-L1 expression are independent markers that, when combined, have increased predictive power for response to IO. High TMB + low/neg PD-L1 behaved similarly to low TMB + high PD-L1, and high TMB + high PD-L1 predicted the highest rwTR. Investigation of these biomarkers as complementary predictors of progression and overall survival is ongoing.

PD-L1 levelNegativeLowHigh
TMB (mut/Mb)
121 (11 - 38)13 (4 - 39)43 (29 - 59)
525 (15 - 39)22 (10 - 42)47 (35 - 60)
1030 (19 - 44)39 (24 - 56)52 (41 - 62)
1536 (23 - 51)53 (36 - 70)56 (44 - 67)
2041 (25 - 59)58 (38 - 77)60 (46 - 73)
3051 (28 - 73)51 (21 - 81)69 (46 - 85)

 
Other Abstracts in this Sub-Category:

 

1. Phase I trial of the combination of the heat shock protein-90 inhibitor onalespib (AT13387) and the cyclin-dependent kinase inhibitor AT7519M in patients with advanced solid tumors.

Meeting: 2019 ASCO Annual Meeting Abstract No: 2619 First Author: Khanh Tu Do
Category: Developmental Immunotherapy and Tumor Immunobiology - Tissue-Based Biomarkers

 

2. Non-small cell lung cancer (NSCLC) next generation sequencing (NGS) using the Oncomine Comprehensive Assay (OCA) v3: Integrating expanded genomic sequencing into the Canadian publicly funded health care model.

Meeting: 2019 ASCO Annual Meeting Abstract No: 2620 First Author: Kirstin Perdrizet
Category: Developmental Immunotherapy and Tumor Immunobiology - Tissue-Based Biomarkers

 

3. Overestimation of tumor mutational burden (TMB) using algorithms compared to germline subtraction.

Meeting: 2019 ASCO Annual Meeting Abstract No: 2621 First Author: Kaushal Parikh
Category: Developmental Immunotherapy and Tumor Immunobiology - Tissue-Based Biomarkers

 

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