A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer

Shuai Han; Dongjie Jiang; Feng Zhang; Kun Li; Kun Jiao; Jingyun Hu; Haihan Song; Qin-Yun Ma; Jian Wang

doi:10.3389/fonc.2023.1095313

A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer

Front Oncol. 2023 Jan 30:13:1095313. doi: 10.3389/fonc.2023.1095313. eCollection 2023.

Authors

Shuai Han¹, Dongjie Jiang², Feng Zhang¹, Kun Li¹, Kun Jiao¹, Jingyun Hu³, Haihan Song³, Qin-Yun Ma⁴, Jian Wang¹

Affiliations

¹ Department of Orthopedics, Shanghai Pudong New Area People's Hospital, Shanghai, China.
² Department of Orthopedic Oncology, Shanghai Changzheng Hospital, Shanghai, China.
³ Central Lab, Shanghai Key Laboratory of Pathogenic Fungi Medical Testing, Shanghai Pudong New Area People's Hospital, Shanghai, China.
⁴ Department of Thoracic Surgery, North Branch of Huashan Hospital, Fudan University, Shanghai, China.

Abstract

Background: Immune checkpoint blockade (ICB) therapy has brought remarkable clinical benefits to patients with advanced non-small cell lung carcinoma (NSCLC). However, the prognosis remains largely variable.

Methods: The profiles of immune-related genes for patients with NSCLC were extracted from TCGA database, ImmPort dataset, and IMGT/GENE-DB database. Coexpression modules were constructed using WGCNA and 4 modules were identified. The hub genes of the module with the highest correlations with tumor samples were identified. Then integrative bioinformatics analyses were performed to unveil the hub genes participating in tumor progression and cancer-associated immunology of NSCLC. Cox regression and Lasso regression analyses were conducted to screen prognostic signature and to develop a risk model.

Results: Functional analysis showed that immune-related hub genes were involved in the migration, activation, response, and cytokine-cytokine receptor interaction of immune cells. Most of the hub genes had a high frequency of gene amplifications. MASP1 and SEMA5A presented the highest mutation rate. The ratio of M2 macrophages and naïve B cells revealed a strong negative association while the ratio of CD8 T cells and activated CD4 memory T cells showed a strong positive association. Resting mast cells predicted superior overall survival. Interactions including protein-protein, lncRNA and transcription factor interactions were analyzed and 9 genes were selected by LASSO regression analysis to construct and verify a prognostic signature. Unsupervised hub genes clustering resulted in 2 distinct NSCLC subgroups. The TIDE score and the drug sensitivity of gemcitabine, cisplatin, docetaxel, erlotinib and paclitaxel were significantly different between the 2 immune-related hub gene subgroups.

Conclusions: These findings suggested that our immune-related genes can provide clinical guidance for the diagnosis and prognosis of different immunophenotypes and facilitate the management of immunotherapy in NSCLC.

Keywords: immune checkpoint molecules; non-small cell lung cancer; prediction; prognosis; signature.

Grants and funding

This study was supported by Key Sub-specialty of Pudong New Area Health Commission (PWZy2020-04), Natural Science Fund of Shanghai (21ZR1411200; 22ZR1455700), National Natural Science Youth Fund of China (82003132), Excellent Young Medical Talents Training Program in Pudong New Area Health System (PWRq2021–33), Key Specialty of Pudong New Area Health Commission (PWZxk2022-16), and Leading Talent Training Program of Pudong New Area Health Commission (PWRl2022-07), Project of Clinical Outstanding Clinical Discipline Construction in Shanghai Pudong New Area (No. PWYgy2021-08), and Minsheng Research Project of Pudong New Area Science and Technology Development Fund (PKJ2022-Y37).