New evaluation of the tumor immune microenvironment of non-small cell lung cancer and its association with prognosis

Abstract

BackgroundA better understanding of the tumor immune microenvironment (TIME) will facilitate the development of prognostic biomarkers and more effective therapeutic strategies in patients with lung cancer. However, little has been reported on the comprehensive evaluation of complex interactions among cancer cells, immune cells, and local immunosuppressive elements in the TIME.MethodsWhole-exome sequencing and RNA sequencing were carried out on 113 lung cancers. We performed single sample gene set enrichment analysis on TIME-related gene sets to develop a new scoring system (TIME score), consisting of T-score (tumor proliferation), I-score (antitumor immunity) and S-score (immunosuppression). Lung cancers were classified according to a combination of high or low T-score, I-score, and S-scores (eight groups; G1-8). Clinical and genomic features, and immune landscape were investigated among eight groups. The external data sets of 990 lung cancers from The Cancer Genome Atlas and 76 melanomas treated with immune checkpoint inhibitors (ICI) were utilized to evaluate TIME scoring and explore prognostic and predictive accuracy.ResultsThe representative histological type including adenocarcinoma and squamous cell carcinoma, and driver mutations such as epidermal growth factor receptor and TP53 mutations were different according to the T-score. The numbers of somatic mutations and predicted neoantigens were higher in Thi (G5-8) than Tlo (G1-4) tumors. Immune selection pressure against neoantigen expression occurred only in Thi and was dampened in Thi/Ilo (G5-6), possibly due to a reduced number of T cells with a high proportion of tumor specific but exhausted cells. Thi/Ilo/Shi (G5) displayed the lowest immune responses by additional immune suppressive mechanisms. The T-score, I-score and S-scores were independent prognostic factors, with survival curves well separated into eight groups with G5 displaying the worst overall survival, while the opposite group Tlo/Ihi/Slo (G4) had the best prognosis. Several oncogenic signaling pathways influenced on T-score and I-scores but not S-score, and PI3K pathway alteration correlated with poor prognosis in accordance with higher T-score and lower I-score. Moreover, the TIME score predicted the efficacy of ICI in patients with melanoma.ConclusionThe TIME score capturing complex interactions among tumor proliferation, antitumor immunity and immunosuppression could be useful for prognostic predictions or selection of treatment strategies in patients with lung cancer.

Single-cell sequencing on CD8+TILs revealed the nature of exhausted T cells recognizing neoantigen and cancer/testis antigen in non-small cell lung cancer

“…Patients 1 and 2 both harbored HLA-B15:01, which is known to present the KK-LC-1-derived epitope KK-LC-1 76-84 (RQKRILVNL). 26 Representative immune-related gene expression profiles from bulk RNA sequencing data (online supplemental figure S1), immunohistochemical analysis of immune cells (CD3 + Open access and CD8 + T cells) and immune checkpoint molecules (PD-1 and PD-L1) confirmed our previously reported immune score data 20 (online supplemental figure S2). Flow cytometric analysis of fresh tumor digests confirmed the infiltration of CD8 + T cells expressing PD-1 or CD39 and CD103 16 into the tumor (online supplemental figure S3).…”

Integrated single-cell and bulk RNA-Seq analysis enhances prognostic accuracy of PD-1/PD-L1 immunotherapy response in lung adenocarcinoma through necroptotic anoikis gene signatures

“…The tumor microenvironment (TME) in lung adenocarcinoma constitutes a complex interplay of immune cells, stromal cells, and tumor cells 34 , each crucial in modulating tumor progression and influencing clinical outcomes. Solid tumors with higher ratios of CD163+ macrophages, non-classical monocytes, and intermediate monocytes have poorer survival rates, while solid tumors with an increased proportion of mast cells have a prolonged survival rate 35 . Additionally, a greater number of B cells is significantly associated with better overall survival 36 .…”

Checkpoint inhibitors are a basic science‐based, transformative new treatment for lung cancer

“…The importance of the TME has been shown in analysis of lung cancer samples. In a study examining the characteristics of lung cancer TME by whole exome and RNA‐seq analysis, Shinohara and colleagues classified tumours according to their degree of tumour proliferation, immunosuppression and anti‐tumour immunity 34 . They showed clear associations between level of tumour proliferation and immunosuppression and poor clinical outcome, with immunosuppression perhaps being most important in outcomes, particularly in those tumours with high rates of progression.…”