Abstract 645: Heterogeneity of immunotherapy biomarkers in the TRACERx non-small cell lung cancer multi-region lung cancer cohort study

Abstract

Abstract Immunotherapy containing regimens have become the standard of care first-line therapy for non-small cell lung cancer (NSCLC) in the metastatic setting and are being explored in the adjuvant and neo-adjuvant setting. However, as intratumor heterogeneity (ITH) is pervasive in cancer we investigated the impact of ITH on established and putative biomarkers predictive of immunotherapy response. We have used whole exome sequencing, RNA sequencing and PDL1 immunohistochemistry (IHC) derived from the multiregion treatment naïve TRACERx cohort to investigate this. Whole exome sequencing data was available for 432 primary tumours from 421 patients with greater than 1500 unique tumour regions. Tumour mutational burden (TMB) was calculated using best practice guidelines from the TMB harmonisation project. Using the FDA approved threshold of ≥ 10 mutations per megabase to define high TMB we found that 41% of patients with high TMB had at least one region with <10 mutation per megabase. This could result in misclassification of patients so we modelled increased sampling in this cohort and found that at least 5 spatially separated samples would be required to ensure no patients are misclassified. Contrary to the published literature we did not find TMB was confounded by tumour purity. Multi-region PDL1 IHC data using the FDA approved companion diagnostic assay (22c3) was available for 132 spatially separated tumour regions from 36 patients. Tumour regions were scored according to the established tumour proportion scoring system (≥50%, 49-1%, <1%). Using only a single sample 31% of patients would have been misclassified. Finally, we investigated several putative transcriptomic biomarkers including 10 single genes (e.g. CXCL9), 15 expression signatures (e.g cytolytic score, TIDE) and 2 tumour microenvironment classification systems. We found that 20-45% of these putative biomarkers were discordant when applied to multi-region data and this increased with the number of tumour regions per patients but was not impacted by tumour purity or sequencing depth. To investigate this further we compared the mean geneset RNA-ITH score between a geneset of all the immune biomarker genes with 100 randomly selected non-immune, but expressed, genesets. The immune biomarker gene set was subject to significantly more intra tumour heterogeneity of expression (Mean RNA-ITH Score 0.50 vs 0.31 p=6.4e-12). In conclusion we demonstrate significant heterogeneity of immune biomarkers in NSCLC and in particular a lack of robustness of expression-based predictors of response to immunotherapy. This highlights the need for biomarkers that are robust to intra-tumour heterogeneity and sampling bias or the need for more representative tumour sampling techniques. Citation Format: Crispin T. Hiley, Kevin Litchfield, Oriol Pich, David Moore, Cristina Naceur-Lombardelli, Selvaraju Veeriah, Maise Al Bakir, Simranpreet Summan, Kristiana Grigoriadis, Carlos Martinez Ruiz, Clare Puttick, Katey Enfield, Sophia Ward, Alexander Frankell, Dhruva Biswas, Rachel Rosenthal, Nicolai J. Birkbak, Mariam Jamal-Hanjani, Nicholas McGranahan, Charles Swanton, TRACERx Consortium. Heterogeneity of immunotherapy biomarkers in the TRACERx non-small cell lung cancer multi-region lung cancer cohort study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 645.