Tumor mutation burden (TMB)-associated signature constructed to predict survival of lung squamous cell carcinoma patients

Significance of NKX2-1 as a biomarker for clinical prognosis, immune infiltration, and drug therapy in lung squamous cell carcinoma

Background

This study was performed to determine the biological processes in which NKX2-1 is involved and thus its role in the development of lung squamous cell carcinoma (LUSC) toward improving the prognosis and treatment of LUSC.

Methods

Raw RNA sequencing (RNA-seq) data of LUSC from The Cancer Genome Atlas (TCGA) were used in bioinformatics analysis to characterize NKX2-1 expression levels in tumor and normal tissues. Survival analysis of Kaplan-Meier curve, the time-dependent receiver operating characteristic (ROC) curve, and a nomogram were used to analyze the prognosis value of NKX2-1 for LUSC in terms of overall survival (OS) and progression-free survival (PFS). Then, differentially expressed genes (DEGs) were identified, and Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Enrichment Analysis (GSEA) were used to clarify the biological mechanisms potentially involved in the development of LUSC. Moreover, the correlation between the NKX2-1 expression level and tumor mutation burden (TMB), tumor microenvironment (TME), and immune cell infiltration revealed that NKX2-1 participates in the development of LUSC. Finally, we studied the effects of NKX2-1 on drug therapy. To validate the protein and gene expression levels of NKX2-1 in LUSC, we employed immunohistochemistry(IHC) datasets, The Gene Expression Omnibus (GEO) database, and qRT-PCR analysis.

Results

NKX2-1 expression levels were significantly lower in LUSC than in normal lung tissue. It significantly differed in gender, stage and N classification. The survival analysis revealed that high expression of NKX2-1 had shorter OS and PFS in LUSC. The multivariate Cox regression hazard model showed the NKX2-1 expression as an independent prognostic factor. Then, the nomogram predicted LUSC prognosis. There are 51 upregulated DEGs and 49 downregulated DEGs in the NKX2-1 high-level groups. GO, KEGG and GSEA analysis revealed that DEGs were enriched in cell cycle and DNA replication.The TME results show that NKX2-1 expression was positively associated with mast cells resting, neutrophils, monocytes, T cells CD4 memory resting, and M2 macrophages but negatively associated with M1 macrophages. The TMB correlated negatively with NKX2-1 expression. The pharmacotherapy had great sensitivity in the NKX2-1 low-level group, the immunotherapy is no significant difference in the NKX2-1 low-level and high-level groups. The analysis of GEO data demonstrated concurrence with TCGA results. IHC revealed NKX2-1 protein expression in tumor tissues of both LUAD and LUSC. Meanwhile qRT-PCR analysis indicated a significantly lower NKX2-1 expression level in LUSC compared to LUAD. These qRT-PCR findings were consistent with co-expression analysis of NKX2-1.

Conclusion

We conclude that NKX2-1 is a potential biomarker for prognosis and treatment LUSC. A new insights of NKX2-1 in LUSC is still needed further research.

Apoptin Inhibits Glycolysis and Regulates Autophagy by Targeting Pyruvate Kinase M2 (PKM2) in Lung Cancer A549 Cells

BACKGROUND

Pyruvate kinase M2 (PKM2) is a key enzyme in aerobic glycolysis and plays an important role in tumor energy metabolism and tumor growth. Ad-apoptin, a recombinant oncolytic adenovirus, can stably express apoptin in tumor cells and selectively causes cell death in tumor cells.

OBJECTIVE

The relationship between the anti-tumor function of apoptin, including apoptosis and autophagy activation, and the energy metabolism of tumor cells has not been clarified.

METHODS

In this study, we used the A549 lung cancer cell line to analyze the mechanism of PKM2 involvement in apoptin-mediated cell death in tumor cells. PKM2 expression in lung cancer cells was detected by Western blot and qRT-PCR. In the PKM2 knockdown and over-expression experiments, A549 lung cancer cells were treated with Ad-apoptin, and cell viability was determined by the CCK-8 assay and crystal violet staining. Glycolysis was investigated using glucose consumption and lactate production experiments. Moreover, the effects of Ad-apoptin on autophagy and apoptosis were analyzed by immunofluorescence using the Annexin v-mCherry staining and by western blot for c-PARP, p62, and LC3-II proteins. Immunoprecipitation analysis was used to investigate the interaction between apoptin and PKM2. In addition, following PKM2 knockdown and overexpression, the expression levels of p-AMPK, p-mTOR, p-ULK1, and p-4E-BP1 proteins in Ad-apoptin treated tumor cells were analyzed by western blot to investigate the mechanism of apoptin effect on the energy metabolism of tumor cells. The in vivo antitumor mechanism of apoptin was analyzed by xenograft tumor inhibition experiment in nude mice and immunohistochemistry of tumors' tissue.

RESULTS

As a result, apoptin could target PKM2, inhibit glycolysis and cell proliferation in A549 cells, and promote autophagy and apoptosis in A549 cells by regulating the PKM2/AMPK/mTOR pathway.

CONCLUSION

This study confirmed the necessary role of Ad-apoptin in the energy metabolism of A549 cells.

A four-gene-based methylation signature associated with lymph node metastasis predicts overall survival in lung squamous cell carcinoma

We aimed to identify prognostic methylation genes associated with lymph node metastasis (LNM) in lung squamous cell carcinoma (LUSC). Bioinformatics methods were used to obtain optimal prognostic genes for risk model construction using data from the Cancer Genome Atlas database. ROC curves were adopted to predict the prognostic value of the risk model. Multivariate regression was carried out to identify independent prognostic factors and construct a prognostic nomogram. The differences in overall survival, gene mutation and pathways between high- and low-risk groups were analyzed. Finally, the expression and methylation level of the optimal prognostic genes among different LNM stages were analyzed. FGA, GPR39, RRAD and TINAGL1 were identified as the optimal prognostic genes and were applied to establish a prognostic risk model. Significant differences were found among the different LNM stages. The risk model could predict overall survival, showing a moderate performance with AUC of 0.64-0.68. The model possessed independent prognostic value, and could accurately predict 1-, 3- and 5-year survival. Patients with a high risk score showed poorer survival. Lower gene mutation frequencies and enrichment of leukocyte transendothelial migration and the VEGF signaling pathway in the high-risk group may lead to the poor prognosis. This study identified several specific methylation markers associated with LNM in LUSC and generated a prognostic model to predict overall survival for LUSC patients.

Spatial Positioning of Immune Hotspots Reflects the Interplay between B and T Cells in Lung Squamous Cell Carcinoma

Beyond tertiary lymphoid structures, a significant number of immune-rich areas without germinal center-like structures are observed in non-small cell lung cancer. Here, we integrated transcriptomic data and digital pathology images to study the prognostic implications, spatial locations, and constitution of immune rich areas (immune hotspots) in a cohort of 935 patients with lung cancer from The Cancer Genome Atlas. A high intratumoral immune hotspot score, which measures the proportion of immune hotspots interfacing with tumor islands, was correlated with poor overall survival in lung squamous cell carcinoma but not in lung adenocarcinoma. Lung squamous cell carcinomas with high intratumoral immune hotspot scores were characterized by consistent upregulation of B-cell signatures. Spatial statistical analyses conducted on serial multiplex IHC slides further revealed that only 4.87% of peritumoral immune hotspots and 0.26% of intratumoral immune hotspots were tertiary lymphoid structures. Significantly lower densities of CD20+CXCR5+ and CD79b+ B cells and less diverse immune cell interactions were found in intratumoral immune hotspots compared with peritumoral immune hotspots. Furthermore, there was a negative correlation between the percentages of CD8+ T cells and T regulatory cells in intratumoral but not in peritumoral immune hotspots, with tertiary lymphoid structures excluded. These findings suggest that the intratumoral immune hotspots reflect an immunosuppressive niche compared with peritumoral immune hotspots, independent of the distribution of tertiary lymphoid structures. A balance toward increased intratumoral immune hotspots is indicative of a compromised antitumor immune response and poor outcome in lung squamous cell carcinoma.

SIGNIFICANCE

Intratumoral immune hotspots beyond tertiary lymphoid structures reflect an immunosuppressive microenvironment, different from peritumoral immune hotspots, warranting further study in the context of immunotherapies.

Mutational and Transcriptional Characterization Establishes Prognostic Models for Resectable Lung Squamous Cell Carcinoma

Background

The prognosis of non-small cell lung cancer (NSCLC) patients has been comprehensively studied. However, the prognosis of resectable (stage I-IIIA) lung squamous cell carcinoma (LUSC) has not been thoroughly investigated at genomic and transcriptional levels.

Methods

Data of genomic alterations and transcriptional-level changes of 355 stage I-IIIA LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database, together with the clinicopathological information (training cohort). A validation cohort of 91 patients was retrospectively recruited. Data were analyzed and figures were plotted using the R software.

Results

Training cohort was established with 355 patients. TP53 (78%), TTN (68%), CSMD3 (39%), MUT16 (36%) and RYR2 (36%) were genes with the highest mutational frequency. BRINP3, COL11A1, GRIN2B, MUC5B, NLRP3 and TENM3 exhibited significant higher mutational frequency in stage III (P < 0.05). Patients with stage III also exhibited significantly higher tumor mutational burden (TMB) than those with stage I (P < 0.01). The mutational status of 10 genes were found to have significant stratification on patient prognosis. TMB at threshold of 25 percentile (TMB = 2.39 muts/Mb) also significantly stratified the patient prognosis (P = 0.0003). Univariate and multivariate analyses revealed TTN, ADGRB3, MYH7 and MYH15 mutational status and TMB as independent risk factors. Further analysis of transcriptional profile revealed many significantly up- and down-regulated genes, and multivariate analysis found the transcriptional levels of seven genes as independent risk factors. Significant factors from the multivariate analyses were used to establish a Nomogram model to quantify the risk in prognosis of individual LUSC patients. The model was validated with a cohort containing 91 patients, which showed good predicting efficacy and consistency.

Conclusion

The influencing factors of prognosis of stage I-III LUSC patients have been revealed. Risk factors including gender, T stage, cancer location, and the mutational and transcriptional status of several genes were used to establish a Nomogram model to assess the patient prognosis. Subsequent validation proved its effectiveness.

PSMA1, a Poor Prognostic Factor, Promotes Tumor Growth in Lung Squamous Cell Carcinoma

Lung squamous cell carcinoma (LUSC) has a poor clinical prognosis and lacks effective targeted therapy. This study is aimed at investigating the role of PSMA1 (proteasome subunit alpha type-1) in LUSC. The differential expression genes (DEGs) in LUSC were retrieved from The Cancer Genome Atlas (TCGA) by "edgR" algorithm and by "limma" R package. Then, the relationship between genes and overall survival (OS) was explored by the least absolute shrinkage and selection operator (LASSO) and multivariate Cox (multi-Cox) regression. Next, the PSMA1 expression in tissues of LUSC was detected by IHC, qRT-PCR, and western blot (WB). Moreover, the effects of PSMA1 on the proliferation and viability of LUSC cell were explored by cell counting kit 8 (CCK-8) assays, colony formation assays, and flow cytometry (FCM) analysis. All 4421 DEGs were screened by TCGA database, and 26 genes associated with OS were selected by multi-Cox. Based on TCGA database, PSMA1 was highly expressed in tissues of LUSC patients, and OS and FP of patients with PSMA1 overexpression were significantly lower than those of patients with low PSMA1 expression. Furthermore, PSMA1 knockdown significantly decreased the proliferation of LUSC cells and promoted the apoptosis of LUSC cells, and these effects were reversed by PSMA1 overexpression. The results of this project supported that PSMA1 might be a critical gene regulating the development of LUSC and has the potential to be explored as a prognostic biomarker of LUSC.

Prognostic impact of tumour mutational burden in resected stage I and II lung adenocarcinomas from a European Thoracic Oncology Platform Lungscape cohort

BACKGROUND

The primary objective of this study is to evaluate tumor mutational burden (TMB), its associations with selected clinicopathological and molecular characteristics as well as its clinical significance, in a retrospective cohort of surgically resected stage I-II lung adenocarcinomas, subset of the ETOP Lungscape cohort.

METHODS

TMB was evaluated on tumor DNA extracted from resected primary lung adenocarcinomas, based on FoundationOne®CDx (F1CDx) genomic profiling, centrally performed at the University Hospital Zurich. The F1CDx test sequences the complete exons of 324 cancer-related genes and detects substitutions, insertions and deletions (indels), copy number alterations and gene rearrangements. In addition, the genomic biomarkers TMB and microsatellite instability (MSI) are analyzed.

RESULTS

In the Lungscape cohort, TMB was assessed in 78 surgically resected lung adenocarcinomas from two Swiss centers (62 % males, 55 %/45 % stage I/II). Median TMB was 7.6 Muts/Mb, with TMB high (≥10 Muts/Mb) in 40 % of cases (95 %CI:29 %-52 %). The most frequently mutated genes were TP53/KRAS/EGFR/MLL2 detected in 58 %/38 %/33 %/30 % of samples, respectively. TMB was significantly higher among males (TMB high: 50 % vs 23 % in females, p = 0.032), as well as among current/former smokers (TMB high: 44 % vs 8 % in never smokers, p = 0.023). Furthermore, TMB was significantly higher in TP53 mutated than in non-mutated patients (TMB high: 60 % vs 12 %, p < 0.001), while it was higher in EGFR non-mutated patients compared to EGFR mutated (TMB high: 48 % vs 23 %, p = 0.049). At a median follow-up time of 56.1 months (IQR:38.8-72.0), none of the three outcome variables (OS, RFS, TTR) differed significantly by TMB status (all p-values > 5 %). This was also true when adjusting for clinicopathological characteristics.

CONCLUSIONS

While presence of TP53 mutations and absence of EGFR mutations are associated with high TMB, increased TMB had no significant prognostic impact in patients with resected stage I/II lung adenocarcinoma beyond T and N classification, in both unadjusted and adjusted analyses.

A Novel Prognosis Signature Based on Ferroptosis-Related Gene DNA Methylation Data for Lung Squamous Cell Carcinoma

Ferroptosis-related genes regulating an iron- and lipid reactive oxygen species (ROS)-dependent form of programmed cell death suggest critical roles for ferroptosis in cancers. However, the prognostic value of ferroptosis-related epigenetic features such as DNA methylation in lung squamous cell carcinoma (LUSC) needs to be studied. Ferroptosis-related genes are collected from the FerrDb database, and the methylation data of these related genes in LUSC methylation data downloaded from the TCGA are retrieved. The DNA methylation data (362 LUSC samples) were analyzed to screen prognostic ferroptosis-related methylation sites. After patients with complete overall survival (OS) information were randomly separated into training cohort (n = 200) and validation cohort (n = 162), the least absolute shrinkage and selection operator (LASSO) and the Cox regression were used to establish and validate the prognostic signature. The time-dependent receiver operating characteristic (ROC) and Kaplan–Meier survival curve analyses, Harrell's concordance index (C-index), calibration analysis, and decision curve analysis (DCA) were performed to evaluate the risk signature and related nomogram. A series of other bioinformatics approaches such as mexpress, cbioportal, maftools, string, metascape, TIMER, and Kaplan–Meier survival curve analysis were also used to determine the methylation, mutation status, protein interaction network or functional enrichment, effects on immune cell infiltration, or expression level prognosis of those signature-related genes. A total of 137 DNA methylation sites were identified as prognostic predictors corresponding to 109 ferroptosis-related genes (FRGs). The methylation signature containing 31 methylation sites proved to be superior predictive efficiency in predicting the 1-, 3-, 5-, and 10-year OS. 8 out of 28 signature-related genes were significantly related to OS time or OS state in patients with LUSC. In addition, DUSP1, ZFN36, and ALOX5 methylation status also correlated with pathological M and ALOX5 methylation correlated with pathological N. The prognostic prediction efficiency of T, N, M, and the stage was inferior to that of the DNA methylation signature. LUSC patients in the high-risk group own a significantly larger number of variants of FRGs than those in the low-risk group. In addition, negative or positive correlation patterns were presented among the different infiltrating immune cells with risk scores or signature-related genes in patients with LUSC. The expression level of 15 signature-related genes showed a significant relationship with OS of LUSC patients. A novel prognostic nomogram survival model containing 4 factors including age, pathologic T, stage, and risk group was constructed and validated, AndC-index, decision curve analysis (DCA), and calibration analysis demonstrated its excellent predictive performance. The FRG DNA methylation data-based prognostic model acts as a powerful prognostic prediction indicator in LUSC patients and is advantageous over the traditional model based on T, N, M, and stage.

Serine Protease Inhibitor Kazal Type 1, A Potential Biomarker for the Early Detection, Targeting, and Prediction of Response to Immune Checkpoint Blockade Therapies in Hepatocellular Carcinoma

Background

We aimed to characterize serine protease inhibitor Kazal type 1 (SPINK1) as a gene signature for the early diagnosis, molecular targeting, and prediction of immune checkpoint blockade (ICB) treatment response of hepatocellular carcinoma (HCC).

Methods

The transcriptomics, proteomics, and phenotypic analyses were performed separately or in combination.

Results

We obtained the following findings on SPINK1. Firstly, in the transcriptomic training dataset, which included 279 stage I and II tumor samples (out of 1,884 stage I–IV HCC specimens) and 259 normal samples, significantly higher area under curve (AUC) values and increased integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were demonstrated for HCC discrimination in SPINK1-associated models compared with those of alpha-fetoprotein (AFP). The calibration of both SPINK1-related curves fitted significantly better than that of AFP. In the two independent transcriptomic validation datasets, which included 201, 103 stage I-II tumor and 192, 169 paired non-tumor specimens, respectively, the obtained results were consistent with the above-described findings. In the proteomic training dataset, which included 98 stage I and II tumor and 165 normal tissue samples, the analyses also revealed better AUCs and increased IDI and NRI in the aforementioned SPINK1-associated settings. A moderate calibration was shown for both SPINK1-associated models relative to the poor results of AFP. Secondly, in the in vitro and/or in vivo murine models, the wet-lab experiments demonstrated that SPINK1 promoted the proliferation, clonal formation, migration, chemoresistance, anti-apoptosis, tumorigenesis, and metastasis of HCC cells, while the anti-SPINK1 antibody inhibited the growth of the cells, suggesting that SPINK1 has “tumor marker” and “targetable” characteristics in the management of HCC. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that SPINK1 was engaged in immunity-related pathways, including T-cell activation. Thirdly, in the transcriptomic analyses of the 368 HCC specimens from The Cancer Genome Atlas (TCGA) cohort, the high abundance of SPINK1 was positively correlated with the high levels of activated tumor-infiltrating CD4⁺ and CD8⁺ T lymphocytes and dendritic and natural killer cells, while there were also positive correlations between SPINK1 and immune checkpoints, including PD-1, LAG-3, TIM-3, TIGIT, HAVCR2, and CTLA-4. The ESTIMATE algorithm calculated positive correlations between SPINK1 and the immune and ESTIMATE scores, suggesting a close correlation between SPINK1 and the immunogenic microenvironment within HCC tissues, which may possibly help in predicting the response of patients to ICB therapy.

Conclusions

SPINK1 could be a potential biomarker for the early detection, targeted therapy, and prediction of ICB treatment response in the management of HCC.

Immune Infiltration Characteristics and a Gene Prognostic Signature Associated With the Immune Infiltration in Head and Neck Squamous Cell Carcinoma

Background: Immunotherapy has become the new standard of care for recurrent and metastatic head and neck squamous cell carcinoma (HNSCC), and PD-L1 is a widely used biomarker for immunotherapeutic response. However, PD-L1 expression in most cancer patients is low, and alternative biomarkers used to screen the population benefiting from immunotherapy are still being explored. Tumor microenvironment (TME), especially tumor immune-infiltrating cells, regulates the body’s immunity, affects the tumor growth, and is expected to be a promising biomarker for immunotherapy.

Purpose: This article mainly discussed how the immune-infiltrating cell patterns impacted immunity, thereby affecting HNSCC patients’ prognosis.

Method: The immune-infiltrating cell profile was generated by the CIBERSORT algorithm based on the transcriptomic data of HNSCC. Consensus clustering was used to divide groups with different immune cell infiltration patterns. Differentially expressed genes (DEGs) obtained from the high and low immune cell infiltration (ICI) groups were subjected to Kaplan–Meier and univariate Cox analysis. Significant prognosis-related DEGs were involved in the construction of a prognostic signature using multivariate Cox analysis.

Results: In our study, 408 DEGs were obtained from high- and low-ICI groups, and 59 of them were significantly associated with overall survival (OS). Stepwise multivariate Cox analysis developed a 16-gene prognostic signature, which could distinguish favorable and poor prognosis of HNSCC patients. An ROC curve and nomogram verified the sensitivity and accuracy of the prognostic signature. The AUC values for 1 year, 2 years, and 3 years were 0.712, 0.703, and 0.700, respectively. TCGA-HNSCC cohort, GSE65858 cohort, and an independent GSE41613 cohort proved a similar prognostic significance. Notably, the prognostic signature distinguished the expression of promising immune inhibitory receptors (IRs) well and could predict the response to immunotherapy.

Conclusion: We established a tumor immune cell infiltration (TICI)-based 16-gene signature, which could distinguish patients with different prognosis and help predict the response to immunotherapy.

Updated Prognostic Factors in Localized NSCLC

Lung cancer is the most common cause of cancer mortality worldwide, and non-small cell lung cancer (NSCLC) represents 80% of lung cancer subtypes. Patients with localized non-small cell lung cancer may be considered for upfront surgical treatment. However, the overall 5-year survival rate is 59%. To improve survival, adjuvant chemotherapy (ACT) was largely explored and showed an overall benefit of survival at 5 years < 7%. The evaluation of recurrence risk and subsequent need for ACT is only based on tumor stage (TNM classification); however, more than 25% of patients with stage IA/B tumors will relapse. Recently, adjuvant targeted therapy has been approved for EGFR-mutated resected NSCLC and trials are evaluating other targeted therapies and immunotherapies in adjuvant settings. Costs, treatment duration, emergence of resistant clones and side effects stress the need for a better selection of patients. The identification and validation of prognostic and theranostic markers to better stratify patients who could benefit from adjuvant therapies are needed. In this review, we report current validated clinical, pathological and molecular prognosis biomarkers that influence outcome in resected NSCLC, and we also describe molecular biomarkers under evaluation that could be available in daily practice to drive ACT in resected NSCLC.

Clinicopathologic Features and Molecular Biomarkers as Predictors of Epidermal Growth Factor Receptor Gene Mutation in Non-Small Cell Lung Cancer Patients

Lung cancer ranks first in the incidence and mortality of cancer in the world, of which more than 80% are non-small cell lung cancer (NSCLC). The majority of NSCLC patients are in stage IIIB~IV when they are admitted to hospital and have no opportunity for surgery. Compared with traditional chemotherapy, specific targeted therapy has a higher selectivity and fewer adverse reactions, providing a new treatment direction for advanced NSCLC patients. Tyrosine kinase inhibitors of epidermal growth factor receptor (EGFR-TKIs) are the widely used targeted therapy for NSCLC patients. Their efficacy and prognosis are closely related to the mutation status of the EGFR gene. Clinically, detecting EGFR gene mutation is often limited by difficulty obtaining tissue specimens, limited detecting technology, and economic conditions, so it is of great clinical significance to find indicators to predict EGFR gene mutation status. Clinicopathological characteristics, tumor markers, liquid biopsy, and other predictors are less invasive, economical, and easier to obtain. They can be monitored in real-time, which is supposed to predict EGFR mutation status and provide guidance for the accurate, individualized diagnosis and therapy of NSCLC patients. This article reviewed the correlation between the clinical indicators and EGFR gene mutation status in NSCLC patients.

Transcutaneous Vagal Nerve Stimulation Alone or in Combination With Radiotherapy Stimulates Lung Tumor Infiltrating Lymphocytes But Fails to Suppress Tumor Growth

The combination of radiotherapy (RT) with immunotherapy represents a promising treatment modality for non-small cell lung cancer (NSCLC) patients. As only a minority of patients shows a persistent response today, a spacious optimization window remains to be explored. Previously we showed that fractionated RT can induce a local immunosuppressive profile. Based on the evolving concept of an immunomodulatory role for vagal nerve stimulation (VNS), we tested its therapeutic and immunological effects alone and in combination with fractionated RT in a preclinical-translational study. Lewis lung carcinoma-bearing C57Bl/6 mice were treated with VNS, fractionated RT or the combination while a patient cohort with locally advanced NSCLC receiving concurrent radiochemotherapy (ccRTCT) was enrolled in a clinical trial to receive either sham or effective VNS daily during their 6 weeks of ccRTCT treatment. Preclinically, VNS alone or with RT showed no therapeutic effect yet VNS alone significantly enhanced the activation profile of intratumoral CD8+ T cells by upregulating their IFN-γ and CD137 expression. In the periphery, VNS reduced the RT-mediated rise of splenic, but not blood-derived, regulatory T cells (Treg) and monocytes. In accordance, the serological levels of protumoral CXCL5 next to two Treg-attracting chemokines CCL1 and CCL22 were reduced upon VNS monotherapy. In line with our preclinical findings on the lack of immunological changes in blood circulating immune cells upon VNS, immune monitoring of the peripheral blood of VNS treated NSCLC patients (n=7) did not show any significant changes compared to ccRTCT alone. As our preclinical data do suggest that VNS intensifies the stimulatory profile of the tumor infiltrated CD8+ T cells, this favors further research into non-invasive VNS to optimize current response rates to RT-immunotherapy in lung cancer patients.