Neoantigens in non small cell lung cancer

Efficient antitumor immunity in humans is to a large extent attributable to T-cells directed against neoantigens, present on tumor cells. Neoantigens are a group of HLA bound proteins, which are formed because of tumor specific mutations. Since they bypass central thymic tolerance they have high immunogenic potenitial. Therefore, they represent an attractive target for anti-tumor immunity. Pulmonary (lung) cancer is among the most frequent and by far the most deadly cancer type. Since smoking is a major risk factor for developing lung cancer it is, together with other cancers subjected to high carcinogen burden, also among the most somatic mutation (and probably also neoantigen) loaded tumor types. The concept of neoantigens has successfully been used in routine clinical management of pulmonary and other cancers, mainly when treating those patients with immune checkpoint inhibitors (ICIs). Recently, FDA has approved treatment with ICI pembrolizumab in individuals with advanced tumors that have high tumor mutational burden (TMB; ≥10 mutations/megabase). TMB represents a proxy for evaluating neoantigen burden, however it is much less specific, since evaluation of TMB does not take into account all the biological steps needed for the presentation of the mutated DNA sequence as a neoantigen to the immune system. ICIs work only on a subset of patients; in an unselected non small cell lung cancer (NSCLC) cohort, only around 20% of individuals are treatment responders. Since ICI have high burden of side effects (according to some estimations up to 60% of patients taking them experience side effects) and are also expensive medications it is therefore of paramount importance that only treatment responders get the treatment. However, biomarkers of treatment response are lacking. To date, solely the above mentioned TMB and immunohistochemical (IHC) expression of PD-L1 in the tumor tissue have been approved as clinical markers for guiding ICI therapy. Different multiparametric prediction models (taking into account multiple tumor and host variables) have regularly shown improved prediction of ICI treatment response compared to only-TMB/only-PD-L1 IHC. Consistently, in these models, the most important prediction feature was TMB. In accordance with biological reasoning, a recent study has shown that solely neoantigen load (mutations presented and recognized by the immune system) is a better predictor of ICI treatment response than solely TMB. However, to our knowledge, no group has used a neoantigen load (neoantigenes defined as mutations ""presented to"" and ""recognized by"" the immune system) as a predictor in a mutiparameter ICI treatment response prediction model. We hypothesize that using neoantigen load in such a context will significantly improve prediction accuracy of such a model; this will be a central hypothesis of the current project. Therefore, in the project, we plan to set up neoantigen prediction pipelines, vi-vitro validate the result of those pipelines and use these results (neoantigen load) to refine ICI treatment response prediction models. Furthermore, we will evaluate the placement of the whole concept of using neoantigen refined ICI treatment response prediction procedure into local routine clinical practice - to see if patients and local health care system can benefit from it. We believe that collaboration of University Clinic of Respiratory and Allergic Diseases Golnik, the main institution in Slovenia and a major facility in South East Europe for diagnosis and treatment of lung cancer and of the Immunology and Cellular Immunotherapy group at the National Institute of Biology, co-led by Dr. Anže Smole and Dr. Jelka Pohar is a perfect fit for executing such a complex project with vast and far reaching basic and clinical research implications.