The impact of the tumor immune microenvironment on overall survival in non‐small cell lung cancer ( NSCLC ) has been studied, but there is little information on its relevance for risk of relapse after surgery. Understanding more about the immune microenvironment in previously untreated NSCLC could help in identifying high‐risk patients and patients more likely to benefit from neoadjuvant/adjuvant immunotherapy. Here, we examined gene expression in 399 surgically derived NSCLC samples and 47 samples from normal lung, using Agilent microarray and RNA sequencing. In 335 of the tumor samples, programmed death‐ligand 1 ( PD ‐L1) expression was evaluated by immunohistochemistry. Gene expression was used to estimate content of immune cells and to calculate an immune score. Properties of the immune microenvironment, and its impact on prognosis, were compared in histological subgroups and gene expression subtypes. Tumors with an active immune microenvironment were found for both adenocarcinomas ( AD ) and squamous cell carcinomas ( SCC ). In AD , high immune score and high estimates of several immune cell types belonging to the adaptive immune system were associated with better progression‐free survival ( PFS ), while in SCC , no association between immune characteristics and PFS was found. The immune microenvironment, including PD ‐L1 expression, and its impact on prognosis showed clear differences in AD and SCC gene expression subtypes. In conclusion, the NSCLC immune microenvironment is predictive of prognosis after surgery. Lung AD and SCC gene expression subtypes should be investigated as potential prognostic biomarkers in patients treated with immune checkpoint inhibitors.

Previous studies have indicated a synergistic effect between radiotherapy and immunotherapy. A better understanding of how this combination affects the immune system can help to clarify its role in the treatment of metastatic cancer. We performed T cell receptor (TCR) sequencing on 46 sequentially collected samples from 15 patients with stage IV non-small cell lung cancer, receiving stereotactic body radiotherapy combined with a programmed cell death ligand-1 (PD-L1) inhibitor. TCR repertoire diversity was assessed using Rényi diversity curves and the Shannon diversity index. TCR clones were tracked over time. We found decreasing or stable diversity in the best responders, and an increase in diversity at progression in patients with an initial response. Expansion of TCR clones was more often seen in responders. Several patients also developed new clones of high abundance. This seemed to be more related to radiotherapy than to immune checkpoint blockade. In summary, we observed similar dynamics in the TCR repertoire as have been described with immunotherapy alone. In addition, the occurrence of new unique clones of high abundance after radiotherapy may indicate that radiotherapy functions as a personalized cancer vaccine.

Dysregulation of microRNAs is a common mechanism in the development of lung cancer, but the relationship between microRNAs and expression subtypes in non‐small‐cell lung cancer (NSCLC) is poorly explored. Here, we analyzed microRNA expression from 241 NSCLC samples and correlated this with the expression subtypes of adenocarcinomas (AD) and squamous cell carcinomas (SCC) to identify microRNAs specific for each subtype. Gene set variation analysis and the hallmark gene set were utilized to calculate gene set scores specific for each sample, and these were further correlated with the expression of the subtype‐specific microRNAs. In ADs, we identified nine aberrantly regulated microRNAs in the terminal respiratory unit (TRU), three in the proximal inflammatory (PI), and nine in the proximal proliferative subtype (PP). In SCCs, 1, 5, 5, and 9 microRNAs were significantly dysregulated in the basal, primitive, classical, and secretory subtypes, respectively. The subtype‐specific microRNAs were highly correlated to specific gene sets, and a distinct pattern of biological processes with high immune activity for the AD PI and SCC secretory subtypes, and upregulation of cell cycle‐related processes in AD PP, SCC primitive, and SCC classical subtypes were found. Several in silico predicted targets within the gene sets were identified for the subtype‐specific microRNAs, underpinning the findings. The results were significantly validated in the LUAD (n = 492) and LUSC (n = 380) TCGA dataset (False discovery rates‐corrected P‐value < 0.05). Our study provides novel insight into how expression subtypes determined with discrete biological processes may be regulated by subtype‐specific microRNAs. These results may have importance for the development of combinatory therapeutic strategies for lung cancer patients.

IntroductionProtein expression is deregulated in cancer, and the proteomic changes observed in lung cancer may be a consequence of mutations in essential genes. The purpose of this study was to identify protein expression associated with prognosis in lung cancers stratified by smoking status, molecular subtypes, and EGFR-, TP53-, and KRAS-mutations.MethodsWe performed profiling of 295 cancer-relevant phosphorylated and non-phosphorylated proteins, using reverse phase protein arrays. Biopsies from 80 patients with operable lung adenocarcinomas were analyzed for protein expression and association with relapse free survival (RFS) were studied.ResultsSpearman’s rank correlation analysis identified 46 proteins with significant association to RFS (p&lt;0.05). High expression of protein kinase C (PKC)-α and the phosporylated state of PKC-α, PKC-β, and PKC-δ, showed the strongest positive correlation to RFS, especially in the wild type samples. This was confirmed in gene expression data from 172 samples. Based on protein expression, unsupervised hierarchical clustering separated the samples into four subclusters enriched with the molecular subtypes terminal respiratory unit (TRU), proximal proliferative (PP), and proximal inflammatory (PI) (p=0.0001). Subcluster 2 contained a smaller cluster (2a) enriched with samples of the subtype PP, low expression of the PKC isozymes, and associated with poor RFS (p=0.003) compared to the other samples. Low expression of the PKC isozymes in the subtype PP and a reduced relapse free survival was confirmed with The Cancer Genome Atlas (TCGA) lung adenocarcinoma (LUAD) samples.ConclusionThis study identified different proteins associated with RFS depending on molecular subtype, smoking- and mutational-status, with PKC-α, PKC-β, and PKC-δ showing the strongest correlation.