Spatial composition of the tumor microenvironment as predictive biomarker for immunotherapy response in PD-L1-high non-small cell lung cancer

• Applicant: Dr. Philip Bischoff
• Subject Area: Pathology
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 554596062

Non-small cell lung cancer is the most common cause of cancer-related death. Most patients are diagnosed in advanced stages where curative surgical therapy is no longer possible, and instead, palliative systemic therapies are employed. Like many other cancers, non-small cell lung cancers often exhibit mechanisms that protect tumor cells from the body's immune response. Modern immunotherapy, which is a crucial component of systemic therapy of advanced non-small cell lung cancers, disrupts these protective mechanisms and enables an effective immune response against the tumor cells. Currently, immunotherapy primarily comprises checkpoint inhibitors, which block the immunosuppressive function of the surface molecule PD-L1 on tumor cells. The amount of tumor cells expressing PD-L1 on their surface has been established as a predictive biomarker in histopathological routine diagnostics to predict whether lung cancer patients will respond to immunotherapy with checkpoint inhibitors. However, this approach is too imprecise in clinical practice. Therefore, a significant proportion of patients are inadequately treated and/or exposed to unnecessary adverse effects. Many other potential predictive biomarkers, such as tumor mutational burden or tumor-infiltrating lymphocytes, are subjects of research but have not yet been implemented in clinical practice. Additionally, it is increasingly recognized that the composition of the tumor microenvironment significantly influences the response to immunotherapies. Novel spatially resolved gene expression analyses at the single-cell level allow for comprehensive analysis of the complexity of the tumor microenvironment. In the proposed project, we aim to utilize this technology to investigate, firstly, the steps involved in the development of an immunosuppressive tumor microenvironment that enables tumor growth by analyzing very early and later stages of non-small cell lung cancer. Secondly, we aim to analyze in pre-therapeutic tumor biopsies from lung cancer patients whether the spatial composition of the tumor microenvironment allows prediction of therapy response. Lastly, spatial analysis of the tumor microenvironment in tumor re-biopsies after immunotherapy and subsequent tumor progression will uncover potential resistance mechanisms. In addition, we will perform tumor mutational profiling to determine the extent to which the genetic profile of tumor cells and the composition of the tumor microenvironment affect each other. I am convinced that the application of spatially resolved single-cell gene expression analyses will identify novel predictive biomarkers that will improve the personalized treatment of lung cancer patients.

• DFG Programme: Research Grants