MAIT Lung Tumour Tissue
The aim of this study is to perform whole genomic and transcriptomic sequencing on non-small cell lung cancer specimens that have undergone immune profiling examining mucosal-associated invariant T cells and other immune populations. The study will utilize cohorts from two prospective tumor tissue collections studies which have been stored as FFPE, fresh frozen and viably cryopreserved tissue (tumor and adjacent normal where possible). We will ultimately seek to correlate the presence of specific immune populations including MAIT cells with specific tumor genomic and transcriptomic states. We will also seek to interrogate potential intratumoral microbiome correlations using KRAKEN and similar algorithms.
Immune checkpoint inhibitors have emerged as an effective and potentially transformative treatment strategy for thoracic malignancies including non-small cell lung cancer (NSCLC). Immunotherapeutic strategies utilizing PD-1 inhibitors have demonstrated improved efficacy compared to standard chemotherapy in most forms of metastatic NSCLC. The potential for durable clinical benefit observed with PD-1 pathway blockade in lung cancer patients has led to an explosion of clinical trials to study immunotherapy in chemotherapy naïve NSCLC as well as locally advanced and early stage lung cancer. However, only a subset of patients with metastatic NSCLC will achieve a durable clinical response following treatment with an immune checkpoint inhibitor. These agents also carry the risk of generating unpredictable and potentially serious immune-related adverse events. Definitive clinical and tissue biomarkers that can identify patients likely to experience durable clinical benefit without significant toxicity remain elusive.
Multiple potential predictors of response to immunotherapy in metastatic NSCLC have been previously investigated. Tumor PDL1 expression, mutational burden and genotype have been associated with the likelihood of response to immunotherapy. Tumor histology and smoking status have similarly been associated with response to immunotherapy. Multiple other potential clinical and biological predictors such as tumor clonality and microbiome composition are presently being investigated as potential predictors of response to immunotherapy. However, the individual contribution of individual factors to the likelihood of response to immunotherapy in metastatic NSCLC remains unclear. Furthermore, the impact of previous treatment on both likelihood of subsequent response to immunotherapy as well as immune-related toxicity remains murky at best.