A Novel Immune-Related Prognostic Model for Response to Immunotherapy and Survival in Patients With Lung Adenocarcinoma.

Yujia Zheng,Hengchang Liu,Qi Xue,Tao Fan,Bo Zheng,Zheng Zhou,Gengshu Gao,Chu Xiao,Yu Liu,Jie He,Chunxiang Li,He Tian,Fengwei Tan,Liyu Wang

doi:10.3389/fcell.2021.651406

Yujia Zheng, Hengchang Liu + Show 12 more

Open Access

https://doi.org/10.3389/fcell.2021.651406

Copy DOI

Abstract

Lung adenocarcinoma is one of the most malignant diseases worldwide. The immune checkpoint inhibitors targeting programmed cell death protein 1 (PD-1) and programmed cell death-ligand 1 (PD-L1) have changed the paradigm of lung cancer treatment; however, there are still patients who are resistant. Further exploration of the immune infiltration status of lung adenocarcinoma (LUAD) is necessary for better clinical management. In our study, the CIBERSORT method was used to calculate the infiltration status of 22 immune cells in LUAD patients from The Cancer Genome Atlas (TCGA). We clustered LUAD based on immune infiltration status by consensus clustering. The differentially expressed genes (DEGs) between cold and hot tumor group were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed. Last, we constructed a Cox regression model. We found that the infiltration of M0 macrophage cells and follicular helper T cells predicted an unfavorable overall survival of patients. Consensus clustering of 22 immune cells identified 5 clusters with different patterns of immune cells infiltration, stromal cells infiltration, and tumor purity. Based on the immune scores, we classified these five clusters into hot and cold tumors, which are different in transcription profiles. Hot tumors are enriched in cytokine–cytokine receptor interaction, while cold tumors are enriched in metabolic pathways. Based on the hub genes and prognostic-related genes, we developed a Cox regression model to predict the overall survival of patients with LUAD and validated in other three datasets. In conclusion, we developed an immune-related signature that can predict the prognosis of patients, which might facilitate the clinical application of immunotherapy in LUAD.

Highlights

Lung cancer is the most common fatal disease in the world, causing most cancer-related death every year
In terms of progression-free interval (PFI), higher infiltration of dendritic cell, mast cell, monocyte, CD4+ T cell, and regulatory T cell (Tregs) were significantly correlated with longer survival, while follicular helper T cell points to negative prognosis
These results indicate that immune cells status can reflect tumor features, and the infiltration of immune cells has prognosis predicting function (Figure 2)

Summary

Introduction

Lung cancer is the most common fatal disease in the world, causing most cancer-related death every year. Eighty-five percent of lung cancer are non-small cell lung cancer (NSCLC) (Siegel et al, 2020). As the most frequently diagnosed subtype of NSCLC, lung adenocarcinoma (LUAD) has high inter/intratumor heterogeneity, and its carcinogenic mechanisms have not been fully illustrated (Calvayrac et al, 2017). Before the introduction of immunotherapy, the outcomes of LUAD patients were dismal due to its malignant nature and limited effect of chemotherapy. With the rapid development of immune checkpoint inhibitors and target therapy, the prognosis of patients has improved significantly (Herbst et al, 2018). To diagnose and treat patients more precisely and economically, effective and stable models that can predict and stratify the prognosis of LUAD patients is warranted (Tang et al, 2017)

Methods

Results

Conclusion