School of Medicine and Health Sciences

Project 6: “Evaluation of biomarker for response to immune checkpoint Inhibitors in patients with advanced non-small cell lung in tissue and liquid biopsy”

Prof. Dr. Harry J.M. Groen
Department of Pulmonary Diseases
University Medical Center Groningen

Prof. Dr. Frank Griesinger
Department of Medical Oncology
Universität Oldenburg

Summary: Immune-checkpoint-Inhibitors (I/O) have revolutionized NSCLC treatment. The only established predictive marker for I/O is PD-L1 expression. However, this marker is not very reliable, most likely due to heterogeneous expression and most likely PD-L1 independent modes of action of I/O.

Therefore, novel biomarkers are needed to better predict tumour response (positive predictive) as well as poor responders (negative predictive). A novel positive predictive biomarker is tumour mutation burden (TMB). Possible negative predictive markers include CD73 expression, STK11 loss or driver mutations such as EGFR, BRAF or c-MET. Exploring predictive markers in an academic setting is particularly important as this is not a primary focus of pharmaceutical companies.

In this study, we want to explore new tumour DNA and thus potentially blood based biomarkers predictive of response to I/O such as TMB and mutations in STK11, PTEN, c-MET and driver mutations and compare them with purely tumour tissue derived biomarkers, such as CD73 and PDL1 immunohistochemistry. Also, genetic markers for early response prediction of I/O will be assessed.

The study will be performed in two parts. First, in a cohort of clinically well characterised patients from both institutions tumour samples will be retrospectively assessed for their estimated TMB as well as additional positive and negative predictive markers (STK11 mutations, CD73 and PD-L1 expression). In selected very good or very bad responders, whole exome sequencing (WES) will be performed in cooperation with New Oncology. This data of WES will be used in silico to optimize the design of the targeted hybrid capture assay to estimate TMB in tissue and liquid biopsy samples. This data will also be used to explore potential new predictive biomarkers.

Second, we will perform a prospective non-interventional study to validate the retrospective findings. An optimized hybrid capture NGS panel will be used in tissue for the detection of both druggable mutations, STK11 and TMB. CD73 and PD-L1 expression will be examined by IHC.

Since tumour tissue often is limiting we will attempt to estimate TMB in liquid biopsy with the assay optimised for minimal required exonic territory. To this end, an initial liquid biopsy will be taken in order to study the predictive value of the liquid biopsy TMB assay. Further sequential samples will be taken to assess the change in allele frequency of patient specific alterations using ddPCR over time as a marker for early response.