High Expression of FGF5 Is an Independent Prognostic Factor for Poor Overall Survival and Relapse-Free Survival in Lung Adenocarcinoma

Abstract

Lung cancer is not only a serious disease but also a public problem threatening human health all over the world. Nonsmall cell lung cancer—which accounts for the majority of lung cancer—is mainly composed of lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). FGF5 is a gene located in q21.21. In the past years, research on FGF5 is mainly focused on hair length and hereditary spherocytosis. In our study, bioinformatics analysis of FGF5 was performed through multiple databases. Expression of FGF5 was compared between tumor and normal tissues, association between gene expression and clinical outcomes was investigated in LUAD and LUSC separately, and potential signaling pathways were predicted. FGF5 expression was upregulated in lung cancer tissues compared with normal tissues. What is more, the high FGF5 expression group had significantly lower proportions of lymph node negative (N0) patients (77/144, 53.5%, vs. 253/358, 70.7%, p = 0.000), and is associated with worse overall survival (OS) (p < 0.0001) and relapse-free survival (RFS) (p = 0.024) in LUAD patients, which could not be seen in LUSC. The following analysis confirmed that high FGF5 expression could be an independent prognostic factor for poor OS (HR: 0.431, 95% CI: 0.312–0.597, p = 0.001) and RFS (HR: 0.678, 95% CI: 0.471–0.977, p = 0.037) in LUAD, but not in LUSC. Coexpression genes related to FGF5 were explored and potential pathways were investigated for further research. FGF5 is a tumor-associated gene that upregulated in lung cancer tissues, and could be an independent prognostic factor that have potential value for further research.

1. Introduction

Great improvement has been made in the treatment of lung cancer in recent years, but the survival status is still poor. The 5-year survival rate of lung cancer is just 19% (Siegel et al., 2019). Many scholars believe that lung cancer is a complex disease which can hardly be controlled by single target therapy; it is important to explore new pathological mechanisms and develop new targets for the disease. Nonsmall cell lung cancer (NSCLC) constitutes the main part of lung cancer, and is mainly composed of lung squamous cancer (LUSC) and lung adenocarcinoma (LUAD). With worldwide tobacco uptake and cessation activities, lung squamous cancer incidence declined twice as fast in males compared with females (Ahmedin et al., 2012). But the incidence of LUAD was still stable and had replaced LUSC as the most common pathological type of NSCLC.

Public database provides us with a convenient and fast way to research oncology, such as The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Large pieces of information about cancer patients and compared with normal people could be found in these databases, including gene expression level, clinical features, and outcomes.

FGF5 is an encoded gene belonging to the fibroblast growth factor family, the protein encoded by FGF5 is fibroblast growth factor 5, which is an important component in transducing signals from fibroblast growth factor receptors 1 to 4 (FGFR1–4) (Mckeehan et al., 1998). Past research indicated that FGF5 is associated with hair length and some other disease such as hereditary spherocytosis (Hébert et al., 1994). Intriguingly, in recent years, oncological value of FGF5 has been gradually revealed: overexpression of FGF5 could be seen in some solid tumors such as hepatocellular carcinoma (Feng et al., 2015), colorectal cancer (Mitchell et al., 2014), and breast carcinoma (Huang et al., 2018), and expression of FGF5 was associated with poor survival outcome. In lung cancer, to our best knowledge, seldom research has reported the oncological value of FGF5. In this study, bioinformatics analysis was performed to investigate the prognostic value of FGF5 in LUSC and LUAD, and explore the possible pathways FGF5 might be involved in.

2. Methods

2.1. Expression analysis

The expression level of FGF5 in two kinds of lung cancer (LUSC and LUAD) and normal tissues was obtained from TCGA database through UCSC Xena Browser (Cline et al., 2013) (https://xenabrowser.net). Patients were grouped in different pathological stages and compared with normal tissues separately.

2.2. Survival analysis

Data of clinical features were obtained from TCGA database through UCSC Xena browser, including living status, overall survival (OS), relapse-free survival (RFS), age at initial diagnosis, gender, and smoking history. The survival analysis results were validated by Kaplan–Meier Plotter browser (Gyorffy et al., 2013) (http://kmplot.com/analysis/index.php?p = service&cancer = lung).

2.3. Coexpression gene analysis and protein–protein interaction analysis

Coexpression genes of FGF5 were obtained by Cbioportal (Ethan et al., 2012) (www.cbioportal.org/index.do) and Ualcan (Chandrashekar et al., 2017) browser (http://ualcan.path.uab.edu/analysis.html). Only the genes with the Spearman or Pearson rank >0.4 could be selected for study. These genes were sent to GlueGo (Bindea et al., 2009) in Cytoscape (Shannon et al., 2003) for KEGG pathway analysis. FGF5 and coexpression genes were performed to String browser (Szklarczyk et al., 2019) for protein–protein interaction analysis.

2.4. Statistical analysis

Excel was used to prepare the obtained data, statistical analysis was mainly performed through SPSS23.0. Expression status was compared by T-test, and χ²-test was used to explore the association between FGF5 expression and the clinical data. The FGF5 expression was divided into high and low groups, and the cutoff value was determined by receiver operating characteristic curve through Medcalc V15.0 software. Kaplan–Meier was used to analyze the OS and RFS in two expression groups. Univariate and multivariate analyses were used to identify the prognostic value

3. Results

3.1. Compared with normal tissues, upregulation of FGF5 expression could be seen in lung cancer

With the use of Xena browser, expression data of LUAD, LUSC, and normal tissues were obtained, results showed a significantly upregulated expression of FGF5 in lung cancer tissues, both in LUAD and in LUSC (Fig. 1A, B). Further analysis showed that, compared with normal tissues, FGF5 expression was significantly elevated in almost every independent stage (Fig. 1C–I), except stage IV in LUSC (Fig. 1J).

FIG. 1.

Expression of FGF5 in LUAD (A) and LUSC (B) compared with normal tissues; expression of FGF5 in different stages in LUAD (C, D, E, F) and LUSC (G, H, I, J) compared with normal tissues. LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma.

3.2. High FGF5 expression was associated with poor survival outcome, which had potential prognostic value

Tables 1 and 2 showed the relationship between FGF5 expression and clinical feature, for LUAD patients, compared with low expression group, high FGF5 expression patients had a smaller proportion of early stage (stage I/II) (96/144, 66.7% vs. 300/362, 82.3%, p = 0.000) and lymph node negative (N0) (77/144, 53.5% vs. 253/358, 70.7%, p = 0.000) status. What is more, significantly more patients died in the high-expression group of FGF5 (69/144, 47.9% vs. 114/358, 31.8%, p = 0.001) (Table 1). We could seldom explore a similar phenomenon in LUSC patients (Table 2). Through Kaplan–Meier analysis, high expression of FGF5 in LUAD patients was associated with worse survival outcome, both in OS (p = 0.000) and RFS (p = 0.024) (Fig. 2A, B). However, no statistical difference could be observed in LUSC (OS: p = 0.204, RFS: p = 0.106, Fig. 2C, D). Results were verified by Kaplan–Meier plotter, probe 208378_x_at was selected in our research, and similar results were obtained (Fig. 2E, F): high expression of FGF5 was associated with worse OS in LUAD patients (p < 0.000) but not in LUSC patients (p = 0.18).

FIG. 2.

Survival curve of different FGF5 expression groups. (A, B) Display the survival curve of LUAD patients in different FGF5 expression groups, (C, D) Show the survival curve of LUSC patients in different FGF5 expression groups. (E, F) Show the verification of overall survival in different FGF5 expression groups in LUAD and LUSC.

Table 1.

Association Between FGF5 Expression and Clinical Features of Lung Adenocarcinoma Patients

Parameters	FGF5 expression	FGF5 expression	χ²	p
Parameters	Low, N = 367	High, N = 147	χ²	p
Age
<66	171	79	2.740	0.098
>66	184	61
DIS	12	7
Gender
Male	167	70	0.189	0.664
Female	200	77	0.189	0.664
Clinical stage
I/II	300	96	15.904	0.000
III/IV	62	48
DIS	5	3
Smoking history
Lifelong nonsmoker	51	24	0.500	0.480
Smoker	306	119
DIS	10	4
Status
Living	244	75	11.453	0001
Dead	114	69
DIS	9	3
T stage
T1/T2	324	121	3.217	0.073
T3/T4	41	25
DIS	2	1
N stage
N0	253	77	13.486	0.00
N1/N2/N3	105	67
DIS	9	3
M stage
M0	244	102	0.473	0.492
M1	16	9
DIS	107	36

DIS, discrepancy.

Table 2.

Association Between FGF5 Expression and Clinical Features of Lung Squamous Cell Carcinoma Patients

Parameters	FGF5 expression	FGF5 expression	χ²	p
Parameters	Low, N = 315	High, N = 187	χ²	p
Age
≤68 years	166	89	1.644	0.200
>68 years	141	96
	8	2
Gender
Male	228	144	1.184	0.277
Female	86	43
DIS	1	0
Clinical stage
I/II	252	154	0.243	0.622
III/IV	59	32
DIS	4	1
Smoking
Nonsmoker	10	8	0.495	0.482
Smoker	300	171
DIS	5	8
Status
Living	183	99	1.645	0.200
Dead	125	86
DIS	7	1
T stage
T1/T2	257	150	0.205	0.651
T3/T4	57	37
DIS	1	0
N stage
N0	196	123	0.369	0.544
N1/N2/N3	113	63
DIS	6	1
M stage
M0	254	157	0.016	0.898
M1	5	2
DIS	56	28

Then the following univariate analysis showed an association between high FGF5 expression and poor survival, as well as the association between advantage stage and poor survival. Multivariate analysis confirmed that high FGF5 expression and advantage pathological stage could be an independent prognostic factor for poor OS (HR: 0.431, 95% CI: 0.312–0.597, p = 0.001) and RFS (HR: 0.678, 95% CI: 0.471–0.977, p = 0.037) in LUAD patients (Table 3). However, a similar result was not found in LUSC (Table 4).

Table 3.

Univariate and Multivariate Analyses of Overall Survival/Relapse-Free Survival in Lung Adenocarcinoma Patients

Parameters	Univariate analysis				Multivariate analysis
Parameters	p	HR	95% CI (lower/upper)		p	HR	95% CI (lower/upper)
OS
Age	0.116	0.785	0.580	1.062
>65 years vs. ≤65 years	0.116	0.785	0.580	1.062
Female vs. male	0.397	0.878	0.649	1.187
Smoking history	0.808	1.053	0.693	1.601
2/3/4/5 vs. 1	0.808	1.053	0.693	1.601
Clinical stage III/IV vs. I/II	0.000	0.403	0.292	0.555	0.000	0.431	0.425	0.804
FGF5 expression high vs. low	0.000	0.533	0.388	0.730	0.001	0.431	0.312	0.597
RFS
Age	0.097	0.751	0.535	1.054
>65 years vs. 65 years	0.097	0.751	0.535	1.054
Female vs. male	0.765	1.054	0.748	1.484
Smoking history	0.400	0.812	0.499	1.319
2/3/4/5 vs. 1	0.400	0.812	0.499	1.319
Clinical stage III/IV vs. I/II	0.032	0.644	0.430	0.964	0.055	0.672	0.448	1.008
FGF5 expression high vs. low	0.024	0.658	0.458	0.947	0.037	0.678	0.471	0.977

OS, overall survival; RFS, relapse-free survival. Smoking history: 1, never smoke; 2, current smokers; 3, former smokers >15 years; 4, former smokers ≤15 years; 5, former smokers without specified duration.

Table 4.

Univariate and Multivariate Analyses of Overall Survival/Relapse-Free Survival in Lung Squamous Cell Carcinoma Patients

Parameters	Univariate analysis				Multivariate analysis
Parameters	p	HR	95% CI (lower/upper)		p	HR	95% CI (lower/upper)
OS
Age	0.123	0.805	0.612	1.060
>65 years vs. ≤65 years	0.123	0.805	0.612	1.060
Female vs. male	0.316	0.848	0.615	1.170
Smoking history	0.221	1.666	0.736	3.722
2/3/4/5 vs. 1	0.221	1.666	0.736	3.722
Clinical stage III/IV vs. I/II	0.007	0.642	0.466	0.885	0.007	0.642	0.466	0.885
FGF5 expression high vs. low	0.205	0.835	0.632	1.103
RFS
Age	0.629	1.107	0.733	1.672
>65 years vs. 65 years	0.629	1.107	0.733	1.672
Female vs. male	0.174	0.712	0.436	1.161
Smoking history	0.076	2.497	0.910	6.850
2/3/4/5 vs. 1	0.076	2.497	0.910	6.850
Clinical stage III/IV vs. I/II	0.004	0.490	0.300	0.799	0.004	0.490	0.300	0.799
FGF5 expression High vs. low	0.108	0.698	0.451	1.081

3.3. FGF5 participates in different pathways in lung adenocarcinoma compared with lung squamous cell carcinoma

Coexpression genes were obtained in two different platforms in our study. Results showed that there were 85 genes related to FGF5 in LUAD, and 43 genes in LUSC ( Supplementary Material). The heatmap of the top 25 coexpression genes in LUAD and LUSC is shown in Figure 3.

FIG. 3.

Heatmap for top 25 coexpression genes in LUAD (A) and LUSC (B).

To further explore the possible pathways these genes might be participated in, KEGG pathway analysis was performed through ClueGo in Cytoscape. Results showed that FGF5 and its coexpressed genes were enriched in some pathways such as protein digestion and absorption, phagosome, PI3K-Akt signaling pathway, proteoglycans in cancer, Ras signaling pathway, ECM–receptor interaction, hypertrophic cardiomyopathy (HCM), hematopoietic cell lineage, dilated cardiomyopathy, NF-kappa B signaling pathway, phospholipase D signaling pathway, and melanoma in LUAD (Fig. 4A), whereas they were enriched in cytokine–cytokine receptor interaction, PI3K-Akt signaling pathway, focal adhesion, proteoglycans in cancer, pertussis, regulation of actin cytoskeleton, ECM–receptor interaction, HCM, hematopoietic cell lineage, dilated cardiomyopathy, rheumatoid arthritis, allograft rejection, graft-versus-host disease, type I diabetes mellitus, Rap1 signaling pathway, shigellosis, melanoma, arrhythmogenic right ventricular cardiomyopathy, bacterial invasion of epithelial cells, TGF-beta signaling pathway, protein digestion and absorption, toll-like receptor signaling pathway, toxoplasmosis, vascular smooth muscle contraction, pathways in cancer, Systemic lupus erythematosus, cell adhesion molecules, phagosome, and calcium signaling pathway in LUSC (Fig. 4B).

FIG. 4.

KEGG analysis for FGF5 coexpression genes and PPI network. (A) Shows the KEGG pathway in LUAD patients, 82 coexpression genes were obtained from 2 different platforms. (B) Shows the KEGG pathway in LUSC patients, 42 coexpression genes were obtained from 2 different platforms. (C) Shows PPI network of fibroblast growth factor 5, the filter value of PPI was set at 0.8, and 17 proteins were closely related to fibroblast growth factor 5. PPI, protein–protein interaction.

The gene FGF5 was enriched mainly in melanoma, PI3K-Akt signaling pathway, and Ras signaling pathway in LUAD, and Rap1 signaling pathway, melanoma, regulation of actin cytoskeleton, and PI3K-Akt signaling pathway in LUSC; results showed that FGF5 participated in different pathways between LUAD and LUSC. Then the protein–protein interaction network was analyzed, proteins that were closely related to the FGF5 expression were observed (Fig. 4C).

4. Discussion

FGF5 is a gene located in the q21.21 of human chromosome. The protein expressed by FGF5 gene is fibroblast growth factor-5 (FGF5), which is composed of 18 polypeptides and belongs to fibroblast growth factor family. FGF5 participates in many activities of embryonic development and normal physiological activities of adults, such as stem cell generation, migration, proliferation, and tube formation. Ren et al. (2018) observed the abnormal FGF5 expression in hypertension patients and found the relationship between FGF5 expression and blood pressure. Higgins et al. (2014) explored the important value of FGF5 in hair growth in humans. In the past, the study of FGF5 is mainly limited to non-neoplastic diseases. In recent years, the role of FGF5 in tumorigenesis and development has been discovered. Some scholars believed that FGF5 not only participates in the carcinogenic process of melanoma, but also could promote the growth of melanoma in some subgroups (Ghassemi et al., 2017). FGF5 is an important factor that promotes the malignant progression by autocrine and paracrine effects in astrocytic brain tumors (Allerstorfer et al., 2008). Silencing FGF5 expression could suppress NSCLC cell growth and invasion by regulating the VEGF pathways and cell cycle (Zhou et al., 2018). Fang et al. (2015) observed that FGF5 plays an important role to suppress the proliferation and metastasis of hepatocellular carcinoma. However, the expression of FGF5 and its relationship with oncological outcomes in NSCLC remain unclear.

In our study, FGF5 expression in two different types of lung cancer was compared with normal tissues, and significant upregulation was observed both in LUAD and in LUSC. Next, FGF5 expression of lung cancer at different pathological stages was analyzed. Except stage IV LUSC cases, upregulation expression of FGF5 could be seen at all the other stages. As a carcinogenic gene in other tumors, we speculate that fibroblast growth factor 5 may play a role in promoting the occurrence and development of lung cancer.

Lymph node metastasis is one of the important factors affecting prognosis of lung cancer patients (Dai et al., 2016). Patients with lymph node metastasis had a later pathological stage and a poorer survival compared with lymph node negative (stage N0) patients. Lymph node metastasis can be inferred by imaging examination, but the most accurate diagnostic method is pathological diagnosis by invasive examination (Call et al., 2018). In our study, there was a significant difference in the expression of FGF5 between patients with lymph node negative and lymph node positive status. High FGF5 expression was associated with lymph node metastasis. Therefore, we believe that FGF5 expression can not only be an independent prognostic factor for LUAD patients, but can also act as a potential predictor of lymph node metastasis. High expression of FGF5 suggests poor prognosis and greater likelihood of lymph node metastasis. For this reason, we believe that FGF5 has certain research potential in noninvasive diagnosis of LUAD.

To further investigate the possible signaling pathways in which FGF5 might be involved in, FGF5 coexpressed genes in LUAD and LUSC were subjected to KEGG pathway analysis.

To explore the potential pathways in which FGF5 might participate in, KEGG was analyzed with the FGF5 coexpressed genes in LUAD and LUSC. Some pathophysiological pathways are common in LUAD and LUSC such as PI3K-Akt signaling pathway, proteoglycans in cancer, and Rap1 signaling pathway. FGF5 may promote the development of tumors in these aspects. Through protein–protein interaction analysis, many proteins once closely related to epidermal growth factor (EGF) have been found to be associated with FGF5. As we know, the main mechanism of epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) is MAPK/PI3K pathway (Liu et al., 2018). We speculate that FGF5 might be another potential target for anticancer therapy: designing TKI drugs for this target has similar antineoplastic effects compared with EGFR pathways perhaps, which may provide hope for EGFR-negative patients. Nevertheless, we should also be aware that targeting FGF5 therapy may be cross-resistant with classical EGFR-TKI drugs.

5. Conclusion

As a tumor-associated gene, FGF5 was upregulated in two types of lung cancer in our study, and could be an independent prognostic factor that has potential value for further research; pathways analysis indicated that FGF5 participates in various pathophysiological pathways, the oncological value of which deserves further study verification.

Footnotes

Author Disclosure Statement

The authors declare that no competing financial interests exist.

Funding Information

Clinical Technology Innovation Project of Beijing Municipal Administration of Hospitals provided financial support for this study (Grant No. XMLX201702).

Supplementary Material

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Supplementary Material

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