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. 2021 Dec 31;9(4):249-263.
doi: 10.2478/jtim-2021-0046. eCollection 2021 Dec 1.

Lung adenocarcinoma-specific three-integrin signature contributes to poor outcomes by metastasis and immune escape pathways

Yizhe Wang  1 , Kezuo Hou  2   3   4 , Yue Jin  2   3   4 , Bowen Bao  2   3   4 , Shiying Tang  2   3   4 , Jianfei Qi  5 , Yang Yang  1 , Xiaofang Che  2   3   4 , Yunpeng Liu  2   3   4 , Xuejun Hu  1 , Chunlei Zheng  2   3   4
Affiliations

Lung adenocarcinoma-specific three-integrin signature contributes to poor outcomes by metastasis and immune escape pathways

Yizhe Wang et al. J Transl Int Med. .

Abstract

Background: Inhibitors targeting integrins (ITGs) are applied as a novel strategy for cancers including lung cancer; however, the heterogeneity of ITG subunits might explain why ITG-targeted inhibitors only show limited efficacy for a small group of lung cancer patients.

Materials and methods: RNA-Seq data of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients were obtained from the TCGA database. Cox regression analysis was performed to construct the prognostic signature and generate the nomogram combined with pathologic stages (pStage). GEO datasets were used for verification. The related biological functions were analyzed by Gene Set Enrichment Analysis (GSEA) software and the TIMER database.

Results: By Cox regression analysis of 30 ITG subunits, ITG subunit alpha 5 (ITGA5), ITG subunit alpha 6 (ITGA6), and ITG subunit alpha L (ITGAL) were identified as the prognostic factors in LUAD, which were included in the construction of a LUAD-specific 3-ITG signature. Following the calculation of risk score (RS) of each patient based on 3-ITG signature, patients with high RS in LUAD were found to exhibit worse prognosis, especially in early stage. Nomogram combined with RS and pStage could predict the prognosis of LUAD patients accurately. Mechanism exploration by GSEA showed that metastasis-related microenvironmental pathways were significantly enriched in the high-RS group. An elevated expression of ITGA5 was mainly associated with the promotion of cell migration and invasion, while the high expression of ITGAL had a strong positive correlation with the capability of recognizing and killing cancer cells.

Conclusions: Three-ITG signature could improve the prediction ability combined with pStage in LUAD and might contribute to poor prognosis by metastasis and immune escape-related pathways.

Keywords: biomarkers; integrin; lung adenocarcinoma; prognosis; risk factors..

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Conflict of interest statement

The authors have no conflicts of interest to declare.

Figures

Figure 1:
Figure 1:
The expression pattern of integrin family genes of NSCLC patients in TCGA. (A) Heatmap of the differential expression of integrins between NSCLC and adjacent noncancerous tissues. Boxplot of the differential expression of integrins between (B) LUSC or (C) LUAD and adjacent normal tissues.
Figure 2:
Figure 2:
The construction of 3-ITG prognostic signature. (A) Multivariate Cox regression analysis of six robust integrins. (B) The distribution of RS of patients in TCGA. (C) The boxplot of RS between alive and dead patients. (D) Heatmap for the expression of integrins in the 3-ITG signature. Kaplan–Meier (KM) curve of overall survival probability based on the (E) RS or (F) pathologic stages in LUAD.
Figure 3:
Figure 3:
Construction and identification of nomogram model 3-ITG signature combined with pathologic stages. (A) Nomogram for overall survival probability predicting. Calibration plots for (B) 1-year, (C) 3-year and (D) 5-year survival probabilities of the nomograms. Receiver operating characteristic (ROC) curves of nomogram model, 3-ITG signature, or pathologic stage individual for (E) 1-year, (F) 3-year and (G) 5-year survival probabilities by.
Figure 4:
Figure 4:
Kaplan–Meier curves of overall survival probability based on the RS in LUAD with different stages: (A) pStage I, (B) pStage II, (C) pStage III–IV, (D) T1 stage, (E) T2 stage, (F) T3–T4 stage, (G) N0 stage, (H) N1 stage, (I) M0 stage, (J) M1 stage.
Figure 5:
Figure 5:
External validation of nomogram model in GSE68465. (A) The distribution of RS. (B) The boxplot of RS between alive and dead patients. (C) Heatmap for the expression of three integrins. (D) Kaplan–Meier curve for 3-ITG signature (top) and pStage (bottom). The calibration plots of nomogram model for (E) 1-year, (F) 3-year, and (G) 5-year survival probabilities. ROC curves of nomogram model and pathologic stage or RS individually for (H) 1-year, (I) 3-year, and (J) 5-year survival probabilities.
Figure 6:
Figure 6:
Functional enrichment analysis by GSEA and identification of individual gene function. Functional enrichment pathways in patients with high risk score in (A) TCGA and (B) GSE68465. Kaplan–Meier curve for verification of survival by the expression of (C) ITGA5, (D) ITGA6, and (E) ITGAL in LUAD patients in TCGA. Functional enrichment pathways in patients with high expression of (F) ITGA5 in TCGA, (G) ITGA5 in GSE68465, (H) ITGAL in TCGA, and (I) ITGAL in GSE68465.
Figure 7:
Figure 7:
Comprehensive analysis of tumor-infiltrating immune cells in LUAD. Expression levels of (A) ITGA5, (B) ITGA6, and (C) ITGAL in CD4+ T cells, CD8+ T cells, and dendritic cells. (D) Scatterplots of correlations between ITGAL expression and gene markers of T cells.
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