Prognostic role of multiple abnormal genes in non-small-cell lung cancer

Abstract

Background: Non-small-cell lung cancer (NSCLC) has the highest morbidity and mortality rates among all malignant tumor types. Although therapies targeting the mutated genes such as KRAS have been used in the clinic for many years, the prognosis remains poor. Therefore, it is necessary to further study the aberrant expression or mutation of non-target genes affecting the survival and prognosis.

Aim: To explore the impact of simultaneous abnormalities of multiple genes on the prognosis and survival of patients.

Methods: We used R packages to analyze gene expression data and clinical data downloaded from The Cancer Genome Atlas (TCGA) database. We also collected samples from 85 NSCLC patients from the First People's Hospital of Jingzhou City and retrospectively followed the patients. Multivariate Cox regression analysis and survival analysis were performed.

Results: Analysis of gene expression data from TCGA revealed that the overexpression of the following single genes affected overall survival: TP53 (P = 0.79), PTEN (P = 0.94), RB1 (P = 0.49), CTNNB1 (P = 0.24), STK11 (P = 0.32), and PIK3CA (P = 0.013). However, the probability of multiple genes (TP53, PTEN, RB1, and STK11) affecting survival was 0.025. Retrospective analysis of clinical data revealed that sex (hazard ratio [HR] = 1.29; [95%CI: 0.64-2.62]), age (HR = 1.05; [95%CI: 1.02-1.07]), smoking status (HR = 2.26; [95%CI: 1.16-4.39]), tumor histology (HR = 0.58; [95%CI: 0.30-1.11]), cancer stage (HR = 16.63; [95%CI: 4.8-57.63]), epidermal growth factor receptor (EGFR) mutation (HR = 1.82; [95%CI: 1.05-3.16]), abundance (HR = 4.95; [95%CI: 0.78-31.36]), and treatment with tyrosine kinase inhibitors (TKIs) (HR = 0.58; [95%CI: 0.43-0.78]) affected patient survival. Co-occurring mutations of TP53, PTEN, RB1, and STK11 did not significantly affect the overall survival of patients receiving chemotherapy (P = 0.96) but significantly affected the overall survival of patients receiving TKIs (P = 0.045).

Conclusion: Co-occurring mutation or overexpression of different genes has different effects on the overall survival and prognosis of NSCLC patients. Combined with TKI treatment, the co-occurring mutation of some genes may have a synergistic effect on the survival and prognosis of NSCLC patients.

Keywords: Epidermal growth factor receptor; Gene mutation; KRAS; Next-generation sequencing; Non-small-cell lung cancer; Overexpression; Tyrosine kinase inhibitor.

Figure 1

Volcano map of gene expression data of 533 cancer tissues and 53 normal tissues from The Cancer Genome Atlas database reveals a large number of upregulated (red) and downregulated (green) genes. LUAD: Lung adenocarcinoma.

Figure 2

Two-dimensional heat map of various parameters plotted to intuitively observe patients' basic indicators and gene expression. OS: Overall survival.

Figure 3

Bubble chart and box chart show that RET, KIT, and TERT exhibit significantly different expression levels between the two groups. The samples were grouped based on the epidermal growth factor receptor and KRAS mutation status with more than 20 samples in each group.

Figure 4

Analysis of survival of patients with single-gene mutations. To amplify the single-gene effect, we considered genes with a Z score greater than 1 to be highly expressed and those with a Z score less than -1 to have a low expression level.

Figure 5

We used the Z score of 0 as the critical value and divided the four genes into two groups in which all had a high expression or a low expression level at the same time.

Figure 6

Heat map revealing data regarding gene mutations and basic clinical information collected from patients. LUAD: Lung adenocarcinoma; WT: Wild type; Del 19: Deletion of exon 19; LUSC: Lung squamous cell carcinoma; TKI: Tyrosine kinase inhibitor; OS: Overall survival.

Figure 7

Multivariate Cox regression analysis of impact of basic indicators and gene mutations.

Figure 8

Cox regression analysis revealed a significant effect of all gene mutations except for BRAF (P = 0.02).

Figure 9

According to the number of mutations in the four tumor suppressor genes (TP53, PTEN, Rb1, and STK11), we classified those with more than one mutation into the greater than 1 group. gt1: Greater than 1; TKI: Tyrosine kinase inhibitor; OS: Overall survival.