FAM83A: A Prognostic Biomarker and Its Correlation with Immune Infiltration in Lung Adenocarcinoma

doi:10.21203/rs.3.rs-1526469/v1

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FAM83A: A Prognostic Biomarker and Its Correlation with Immune Infiltration in Lung Adenocarcinoma

https://doi.org/10.21203/rs.3.rs-1526469/v1

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Background: FAM83A (Family with sequence similarity 83, member A) has been found to promote tumor cell proliferation and accelerate the progression of several cancer types. However, integrated studies on the prognostic value of FAM83A and its function as an immunotherapy target in pan-cancers remain limited.

Methods: Multiple online databases, including ONCOMINE, PrognoScan, Kaplan-Meier plotter, GEPIA, Lung Cancer Explorer, and TIMER, were accessed to evaluate the clinical prognostic value of FAM83A and its association with tumor-infiltrating immune cells across different cancer types.

Results: Compared with normal tissues, the expression of FAM83A was higher in breast, colorectal, gastric, head and neck, and lung cancers. High FAM83A expression significantly correlated with inferior overall survival (OS) in lung cancer including lung adenocarcinoma (LUAD). In patients with LUAD, overexpressed FAM83A was negatively associated with infiltration levels of B cells and dendritic cells. In addition, the FAM83A expression level was positively associated with PD-L1, STAT1, STAT3, and JAK1 in LUAD.

Conclusions: The high expression level of FAM83A was significantly correlated with a worse prognosis, which was also associated with a decreased level of infiltration of B cells and dendritic cells. FAM83A might increase the expression of PD-L1 through JAK / STAT pathway in the tumor microenvironment of lung adenocarcinoma.

FAM83A

prognosis

tumor-infiltration

PD-L1

Lung adenocarcinoma.

Lung cancer is one of the leading causes of cancer-associated morbidity and mortality in humans worldwide [1, 2]. Non-small cell lung cancer (NSCLC) accounts for about 80–85% of lung cancers, nearly half of which are lung adenocarcinoma (LUAD), and about 20–30% are lung squamous cell carcinoma (LUSC) [3].

In recent years, with the in-depth research and understanding of the genome, molecular pathology and microenvironment of tumor, immunotherapy has paved an entirely new avenue for cancer treatment [3]. Immune-related mechanisms play an important role in lung cancer [4, 5]. For example, several immune checkpoint inhibitors, which attack tumor cells expressing programmed death-ligand 1 (PD-L1) by blocking the programmed cell death 1 (PD-1)/ PD-L1 signaling pathway, have shown promising antitumor activities in malignant melanoma and NSCLC [6–8]. However, the response to immune checkpoint inhibitors is very heterogeneous among the cancer population, and there is a lack of effective markers to screen for those who really benefit. Therefore, the relevant mechanisms and predictive markers need to be explored urgently.

Family with sequence similarity 83, member A (FAM83A), also known as tumor-specific antigen-9 (BJ-TSA-9), was first reported as a potential cancer biomarker in 2005 [9]. It is located on chromosome 8, locus q24.13, and spans 27,566 base pairs [10]. Some studies have recognized that dysregulated FAM83A affected the occurrence and development of multiple human tumor types, including lung cancer, pancreatic cancer, breast cancer, ovarian and bladder cancer [11–15]. Lee et al. identified that FAM83A could regulate transformation (cell proliferation and metastasis) and activate RAS/RAF/MEK/ERK pathways in breast cancer [16]. Furthermore, Zhou et al. reported that FAM83A drove PD-L1 expression via ERK signaling and correlated with poor outcomes in patients with LUAD [17]. These findings indicated that FAM83A may play a significant role in the occurrence, development, and metastasis of tumors. In addition, FAM83A expressed in immune microenvironment may confer the poor prognosis [18, 19]. Nevertheless, the potential functions, and mechanisms of FAM83A in cancer progression and immunology remain ambiguous.

There are still rarely integrated studies on the prognostic value and the role of FAM83A in immune microenvironment in lung cancer. In this study, we conducted a comprehensive analysis of FAM83A expression and correlation with prognosis of cancer patients, especially in lung adenocarcinoma and lung squamous cell carcinoma. We further explored the correlation of FAM83A with immune infiltrating cells in the different tumor microenvironments. We also investigated the potential mechanism underlying the interplay between FAM83A and PD-L1 (CD274) in lung adenocarcinoma.

Study Design

Online databases were accessed to evaluate and verify the clinical prognostic value of FAM83A and its association with tumor-infiltrating immune cells across different cancer types, especially in lung adenocarcinoma (Fig. 1).

Differential expression: ONCOMINE [20] and Tumor Immune Estimation Resource (TIMER) [21] databases were used to explore and compare the expression of FAM83A in various cancer types. Lung Cancer Explorer (LCE) database were used to validate the expression difference of lung adenocarcinoma [22].

Prognostic value: PrognoScan [23] and Gene Expression Profiling Interactive Analysis (GEPIA) [24] were devoted to assess the prognostic value of FAM83A expression in different human tumors. Survival analysis for FAM83A gene expression was performed using the Kaplan-Meier Plotter [25] with RNA microarray data for lung cancer and LUAD patients.

Immune infiltration: The association between FAM83A and immune infiltration could be explored in the TIMER database. GEPIA database further evaluated the relationship between immune gene sets and FAM83A in lung adenocarcinoma, which was verified with the results in TIMER.

Data Sources

ONCOMINE

ONCOMINE (https://www.oncomine.org/resource/login.html) database [26] was applied to identify the mRNA expression of FAM83A in various human tumors. The thresholds were determined according to the following values: p-value of 0.001, fold change of 1.5 and gene rank in the top 10%.

PrognoScan

PrognoScan (http://www.abren.net/PrognoScan/) database [27] was used to perform the correlation between FAM83A levels and survival in different tumor types. PrognoScan analyzes the relationship between gene expression and patient prognostic indicators such as overall survival (OS), relapse free survival (RFS) and distant metastasis free survival (DMFS), across an enormous number of public cancer microarray datasets. The threshold was set as a Cox p-value < 0.05.

Kaplan-Meier Plotter

Kaplan-Meier plotter (https://kmplot.com/analysis/) [28] can assess the effect of 54k genes (mRNA, miRNA, protein) on survival in 21 cancer types. In this study, Kaplan-Meier plotter was be used to analyze the relationship between FAM83A expression and survival with OS, RFS, progression-free survival (PFS) or post- progression survival (PPS) in breast, ovarian, lung and gastric cancers. Hazard ratio (HR) with 95% confidence intervals (CI) and log-rank p-value were calculated (p-values < 0.05 is considered as significant). In addition, we explored the correlation of FAM83A mRNA expression and clinicopathological factors in lung cancer by Kaplan-Meier plotter.

GEPIA

Gene Expression Profiling Interactive Analysis (http://gepia.cancer-pku.cn/index.html) can be used for differential gene expression analysis, correlation analysis and patient survival analysis etc. based on The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression data (GTEx) [29]. GEPIA was applied for survival curves of FAM83A based on the log-rank test in 33 cancer types. We also used GEPIA to analyze the correlation between FAM83A and immune marker genes in LUAD and LUSC. The correlation coefficient was determined by the Spearman method.

LCE

Lung Cancer Explorer (http://lce.biohpc.swmed.edu/) is a relatively large database that collects lung cancer expression data and clinical data from more than 6,700 patients in 56 studies [30]. In this study, LCE was applied to meta-analysis of FAM83A expression by tumor vs. adjacent non-malignant tissue in LUAD and LUSC through R package.

TIMER

Tumor Immune Estimation Resource (https://cistrome.shinyapps.io/timer/) is a comprehensive resource for systematic analysis of tumor-infiltrating immune cells [31]. We explored the correlation between FAM83A expression in different types of cancer and abundance of six immune infiltrates, including B cells, CD4⁺ T cells, CD8⁺ T cells, Neutrophils, Macrophages, and Dendritic cells, via the “Gene module”. FAM83A expression levels against tumor purity were also determined. Moreover, relationships between FAM83A expression and gene markers of innate immunity cells as well as adaptive immunity cells were evaluated with the “Correlation module”.

Statistical Analysis

The results generated in ONCOMINE were performed with the number of analyses, p-values determined in t-tests, fold changes, and gene ranking. Survival curves were described by the Kaplan-Meier plots, PrognoScan and GEPIA, and the data was evaluated with HR and p-values from log-rank tests. Gene correlation coefficient and p-values were calculated with Spearman method.

The mRNA Expression Levels of FAM83A in Various Human Tumors

The FAM83A mRNA expression level was compared between human tumors and paired normal tissues across various cancer types based on the data from ONCOMINE. The results revealed that the FAM83A expression was higher in bladder, colorectal, head and neck, lung, pancreatic cancers, as well as myeloma tumors, compared with normal tissues; while a lower expression of FAM83A was only found in the esophageal cancer dataset (Fig. 2A). No significant difference in the FAM83A expression was observed in brain and central nervous system, cervical, kidney, liver, ovarian, prostate cancers, as well as leukemia, lymphoma, myeloma, sarcoma. The detailed results of FAM83A expression in different cancer datasets were summarized in Additional Table 1.

We also examined FAM83A expression with RNA-sequencing data from the Cancer Genome Atlas (TCGA) using TIMER. The expression levels of FAM83A across 39 tumor samples and matched normal tissues are displayed in Fig. 2B. The FAM83A expressed significantly lower in PRAD (prostate adenocarcinoma) than in the corresponding normal tissue (P < 0.001). On the contrary, BLCA (bladder urothelial carcinoma), BRCA (breast invasive carcinoma), COAD (colon adenocarcinoma), HNSC (head and neck squamous cell carcinoma), ESCA (esophageal carcinoma), KIRP (kidney renal papillary cell carcinoma), LUAD, LUSC, READ (rectum adenocarcinoma), STAD (stomach adenocarcinoma), and UCEC (uterine corpus endometrial carcinoma) revealed significantly higher expression of FAM83A compared with their adjacent normal tissues (P < 0.05). The meta-analysis from LCE database endorsed that FAM83A expression was significant difference both in LUAD (standard mean difference, SMD = 2.16, 95%CI 1.37 to 2.95) and LUSC (SMD = 1.53, 95%CI 1.05 to 2.01) across several studies (Fig. 3A, B).

Prognostic Value of FAM83A Expression in Cancers

The impact of FAM83A expression on survival was evaluated via PrognoScan. The results were summarized in Additional Table 2. FAM83A expression was significantly associated with prognosis in lung, breast, brain, and colorectal cancers (Fig. 4). Notably, compared with low FAM83A expression (The cut-off value of FAM83A mRNA expression was set as 50%.), high expression of FAM83A predicted worse RFS (GSE31210 HR = 1.79, Cox P < 0.001; GSE8894 HR = 1.17 Cox P = 0.020) and OS (GSE31210 HR = 1.99, Cox P < 0.001; GSE3141 HR = 1.30 Cox P = 0.004) in lung cancer (Fig. 4A-4D). Meanwhile, FAM83A also played a detrimental role in other three cancer types (Cox P < 0.05) (Fig. 4E-4H).

To further assess the prognostic value of FAM83A in different cancers, we analyzed the association between FAM83A mRNA expression and prognosis via Kaplan-Meier plotter, which is based on Affymetrix microarray information. Consistent with the above-mentioned results, the poor PPS and OS in lung cancer (PPS: HR = 1.89, 95%CI 1.22 to 2.91, log-rank p < 0.01; OS: HR = 1.27, 95%CI 1.08 to 1.50, log-rank p < 0.01) and gastric cancer (PPS: HR = 1.36, 95%CI 1.04 to 1.79, log-rank p < 0.05; OS: HR = 1.27, 95%CI 1.00 to 1.60, log-rank p < 0.05) correlated with higher FAM83A expression (Fig. 5A, B, E, F). However, in breast cancer, high mRNA expression of FAM83A was significantly associated with a better RFS (HR = 0.85, 95%CI 0.73 to 0.99, log-rank p < 0.05) but a worse OS (HR = 1.53, 95%CI 1.11 to 2.11, log-rank p < 0.01) (Fig. 5C, D). While high FAM83A expression significantly shortened the OS (HR = 1.43, 95%CI 1.18 to 1.73, log-rank p < 0.001) but not PFS in ovarian cancer (Fig. 5G, H).

In addition, we explored the relationship between FAM83A expression and clinical outcomes in 33 cancer types via GEPIA. We found that high expression of FAM83A was associated with both poor OS and DFS in KIRP, LUAD, PAAD. In CESC, KIRC, and PCPG, the higher FAM83A expression level yielded poorer OS but not associated with DFS. The prognostic value of FAM83A expression was not analyzed in KICH, LGG, and UVM due to the limited sample size. In the remaining cancer types, the expression level of FAM83A had no impact on OS and DFS, including ACC, BLCA, LUSC, etc. (Additional Fig. 1). Taken together, these results confirmed the prognostic value of FAM83A expression in several specific types of cancers, including LUAD.

FAM83A Expression with Poor Prognosis in Lung Cancer

We explored the correlation between the FAM83A expression level and clinical variables of lung cancer patients via Kaplan-Meier plotter databases (Table 1). The high level of FAM83A expression was associated with shorter OS and PPS in LUAD patients compared with the low expression level (OS: HR = 2.22, P < 0.001; PFS: HR = 2.01, P < 0.01) and female lung patients (OS: HR = 1.55, P < 0.05; PFS: HR = 2.70, P < 0.01). High expression of FAM83A was related to worse OS with stage I (HR = 1.48, P < 0.05), stage T₁ (HR = 2.07, P < 0.001), stage N₀ patients (HR = 1.61, P < 0.01). Moreover, FAM83A high expression was associated with worse PFS in stage 2 lung cancer cohorts (HR = 2.03, P < 0.05). FAM83A played a crucial role in the prognosis of LUAD, but not in LUSC, which was in line with the results of GEPIA analysis.

Table 1

Correlation of *FAM83A* mRNA expression and clinical prognosis with clinicopathological factors in lung cancer by Kaplan-Meier plotter.
Clinicopathological characteristics	Overall survival (n = 1927)			Post- progression survival (n = 344)
	N	Hazard ratio	P-value	N	Hazard ratio	P-value
Gender
Female	714	1.55(1.10–2.18)	0.012	165	2.70(1.27–5.70)	0.0071
Male	1100	1.08(0.88–1.32)	0.45	179	1.14(0.66–1.95)	0.64
Smoking history
Smoked	820	1.91(1.26–2.89)	0.002	254	1.39(0.84–2.30)	0.2
Never smoked	205	4.99(1.70-14.63)	0.0012	67	1.37(0.57–3.32)	0.48
Histology
Adenocarcinoma	719	2.22(1.72–2.86)	3.30E-10	125	2.01(1.23–3.29)	0.0046
Squamous cell carcinoma	524	1.07(0.78–1.46)	0.67	20	0.30(0.08–1.09)	0.055
Stage
I	577	1.48(1.08–2.02)	0.014	78	1.71(0.93–3.14)	0.079
II	244	1.34(0.85–2.11)	0.2	58	2.03(1.01–4.07)	0.042
III	70	0.75(0.38–1.49)	0.41	10	*	*
IV	4	*	*	0	*	*
Stage T
1	437	2.07(1.38–3.11)	3.20E-04	61	1.25(0.21–7.53)	0.81
2	589	0.93(0.64–1.36)	0.71	169	1.63(0.78–3.40)	0.19
3	81	0.68(0.30–1.56)	0.36	17	*	*
4	46	0.99(0.42–2.31)	0.98	5	*	*
Stage N
0	781	1.61(1.18–2.21)	0.0028	146	1.81(0.80–4.09)	0.15
1	252	1.02(0.62–1.67)	0.95	71	2.43(0.70–8.37)	0.15
2	111	0.73(0.35–1.55)	0.42	0	*	*
Stage M
0	681	1.07(0.84–1.36)	0.59	59	1.82(0.93–3.56)	0.078
1	10	*	*	0	*	*
Chemotherapy
Yes	176	0.78(0.25–2.49)	0.68	88	1.85(0.46–7.41)	0.38
No	310	33.87(0.45–33.17)	0.18	97	0.29(0.02–4.65)	0.35
* Sample number too low for meaningful analysis. Bold values indicate P < 0.05.

Multivariate Cox survival analyses of FAM83A mRNA expression with several clinicopathological factors in lung cancer and LUAD were shown in Additional Table 3, adjusting for gender, stage, American Joint Committee on Cancer (AJCC) stage T, AJCC stage N, and smoking history. FAM83A differential expression level and AJCC stage T were the independent prognostic factors for OS in lung cancer and LUAD patients.

Immune Cell Infiltration of FAM83A Level in Patients with Lung Cancer

To better understand the underlying mechanisms, we investigated the relationship between immune infiltration and FAM83A expression in 39 cancer types using data from TIMER. The results showed that the FAM83A expression level was significantly associated with tumor purity in 13 types of cancers and there were significant correlations with infiltrating levels of immune cells, including B cells, CD4⁺ T cells, CD8⁺ T cells, macrophages, neutrophils, and dendritic cells, in various types of tumors (Additional Fig. 2).

Furthermore, based on the differences of FAM83A mRNA expression levels and the prognostic value of FAM83A expression in tumors, we ultimately selected lung cancer and for further research on immune infiltration via TIMER (Fig. 6). FAM83A expression had a significantly negative correlation with infiltrating levels of B cell (r = -0.276, P < 0.001) and dendritic cell (r = -0.107, P < 0.05), but not with tumor purity and infiltrating levels of CD8⁺ T cell, CD4⁺ T cell, macrophage, and neutrophil in LUAD. While in LUSC, the FAM83A expression showed significantly negative correlations with tumor purity (r = -0.215, P < 0.001) and infiltrating levels of B cell (r = -0.287, P < 0.001) and CD8⁺ T cell (r = -0.141, P < 0.01), but it did not correlate with infiltrating levels of CD4⁺ T cell, macrophage, neutrophil, or dendritic cell.

Correlations Between FAM83A Expression and Immune Marker Sets

The potential correlations between FAM83A and immune cell markers of various infiltrating FAM83A expression and immune marker genes of innate and adaptive immune cells, included monocytes, TAMs, M1 and M2 macrophages, neutrophils, NK cells, DCs, CD8⁺ T cells, general T cells, B cells, as well as the different functional T cells were studied. FAM83A expression level significantly correlated with most of the immune marker sets in both LUSC and LUAD, after adjustment for purity (Table 2 and Table 3).

Table 2

Correlation analysis between *FAM83A* and relate genes and markers of innate immunity cells in TIMER.
Cell type	Gene marker	LUAD				LUSC
		Purity		None		Purity		None
		Cor	P	Cor	P	Cor	P	Cor	P
Monocyte	CD14	0.052	2.46E-01	0.085	5.48E-02	0.104	*	0.017	7.10E-01
	CD115 (CSF1R)	-0.056	2.12E-01	-0.018	6.79E-01	-0.131	**	-0.015	7.44E-01
TAM	CCL2	-0.052	2.46E-01	-0.028	5.28E-01	-0.158	*******	-0.072	1.10E-01
M1 Macrophage	INOS (NOS2)	0.082	6.83E-02	0.097	*	-0.158	*******	-0.152	*******
	IRF5	0.08	7.59E-02	0.099	*	-0.137	**	-0.116	**
M2 Macrophage	CD206 (MRC1)	-0.139	**	-0.106	*	-0.061	1.86E-01	0.044	3.28E-01
	CD163	0.064	1.59E-01	0.091	*	-0.117	*	-0.018	6.90E-01
	VSIG4	-0.038	4.02E-01	-0.009	8.38E-01	-0.111	*	-0.017	7.04E-01
	MS4A4A	-0.076	9.39E-02	-0.031	4.81E-01	-0.138	**	-0.034	4.47E-01
Neutrophils	CD11b (ITGAM)	-0.07	1.23E-01	-0.036	4.16E-01	-0.152	*******	-0.043	3.41E-01
	CD15 (FUT4)	0.039	3.88E-01	0.042	3.42E-01	-0.145	**	-0.101	*
Natural killer cell	KIR2DL1	0.036	4.29E-01	0.044	3.16E-01	-0.037	4.14E-01	0.009	8.33E-01
	KIR2DL3	0.083	6.70E-02	0.093	*	-0.059	2.01E-01	-0.035	4.36E-01
	KIR3DL1	0.093	*	0.103	*	-0.128	**	-0.084	6.10E-02
	KIR3DL2	0.056	2.13E-01	0.069	1.19E-01	-0.083	6.96E-02	-0.041	3.60E-01
Dendritic cell	BDCA-1 (CD1C)	-0.285	*******	-0.252	*******	-0.048	2.95E-01	0.067	1.32E-01
	BDCA-4 (NRP1)	0.225	*******	0.228	*******	0.079	8.41E-02	0.142	**
	HLA-DPB1	-0.334	*******	-0.264	*******	-0.184	*******	-0.059	1.87E-01
	HLA-DPA1	-0.3	*******	-0.241	*******	-0.191	*******	-0.079	7.82E-02
LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; TAM, tumor associated macrophage; Cor, R value of Spearman’s correlation; None, correlation without adjustment. Purity, correlation adjusted by purity. P < 0.05, P < 0.01, ******P < 0.001.

Table 3

Correlation analysis between *FAM83A* and related genes and markers of adaptive immunity cells in TIMER.
Cell type	Gene marker	LUAD				LUSC
		Purity		None		Purity		None
		Cor	P	Cor	P	Cor	P	Cor	P
CD8⁺T cell	CD8A	0.007	8.80E-01	0.045	3.09E-01	-0.225	*******	-0.166	*******
	CD8B	-0.044	3.30E-01	-0.012	7.94E-01	-0.266	*******	-0.218	*******
	CD45 (PTPRC)	-0.148	*******	-0.092	8.68E-02	-0.246	*******	-0.109	*
T cell (general)	CD3D	-0.057	2.07E-01	-0.002	9.66E-01	-0.221	*******	-0.097	*
	CD3E	-0.112	*	-0.043	3.31E-01	-0.228	*******	-0.101	*
	CD2	-0.14	**	-0.072	1.03E-01	-0.254	*******	-0.132	**
B cell	CD19	-0.156	*******	-0.097	*	-0.229	*******	-0.088	5.00E-02
	CD20 (MS4A1)	-0.22	*******	-0.154	*******	-0.26	*******	-0.119	**
	CD79A	-0.095	*	-0.046	2.94E-01	-0.235	*******	-0.088	5.00E-02
Th1	T-bet (TBX21)	-0.051	2.60E-01	-0.005	9.02E-01	-0.222	*******	-0.112	*
	STAT4	-0.064	1.57E-01	-0.013	7.64E-01	-0.066	1.51E-01	0.042	3.49E-01
	STAT1	0.196	*******	0.213	*******	-0.117	*	-0.057	2.00E-01
Th2	GATA3	-0.083	6.49E-02	-0.041	3.58E-01	0.043	3.43E-01	0.091	*
	STAT6	-0.037	4.14E-01	-0.04	3.70E-01	0.075	1.04E-01	0.081	6.96E-02
	IL13	-0.102	*	-0.085	5.43E-02	-0.125	**	-0.182	*******
Tfh	BCL6	0.11	*	0.117	**	-0.016	7.17E-01	0.016	7.21E-01
	IL21	0.086	5.56E-02	0.101	2.18E-02	-0.169	*******	-0.099	*
Th17	STAT3	0.102	*	0.094	*	-0.02	6.66E-01	0.013	7.71E-01
	IL17A	0.044	3.27E-01	0.067	1.30E-01	-0.058	2.09E-01	-0.008	8.55E-01
Treg	FOXP3	-0.007	8.77E-01	0.035	4.23E-01	-0.18	*******	-0.062	1.67E-01
	CCR8	-0.005	9.18E-01	0.023	6.05E-01	-0.162	*******	-0.061	1.71E-01
	STAT5B	-0.057	2.07E-01	-0.059	1.81E-01	-0.289	*******	-0.278	*******
	CD25 (IL2RA)	0.099	*	0.12	**	-0.187	*******	-0.077	8.40E-02
T cell exhaustion	PD-1 (PDCD1)	0.058	1.97E-01	0.095	*	-0.231	*******	-0.12	**
	CTLA4	-0.034	4.57E-01	0.014	7.52E-01	-0.229	*******	-0.105	*
	LAG3	0.031	4.97E-01	0.055	2.12E-01	-0.233	*******	-0.152	*******
	TIM-3 (HAVCR2)	-0.023	6.18E-01	0.022	6.18E-01	-0.172	*******	-0.062	1.69E-01
	GZMB	0.221	*******	0.234	*******	-0.172	*******	-0.08	7.48E-02
LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; Th, T helper cell; Tfh, Follicular helper T cell; Treg, regulatory T cell; Cor, R value of Spearman’s correlation; None, correlation without adjustment. Purity, correlation adjusted by purity. P < 0.05, P < 0.01, ******P < 0.001.

We found that the FAM83A expression level significantly correlated to markers of B cells (CD19, CD20, CD79A), DCs (BDCA-1, BDCA-4, HLA-DPB1, HLA-DPA1), Th1 (STAT1), and Th17 (STAT3) in LUAD. The associations between FAM83A expression and the above markers of B cells and DCs in LUAD and LUSC were validated via GEPIA database (Additional Table 4). The FAM83A expression level positively correlated with CD274 (R = 0.18, P-value < 0.001), STAT1 (R = 0.18, P-value < 0.001), STAT3 (R = 0.1, P-value < 0.05), and JAK1 (R = 0.11, P-value < 0.05) (Fig. 7).

FAM83A was showed to promote tumor cell proliferation and accelerate the progression of several cancer types [11–15] as well as drove PD-L1 expression in some malignant tumors [16, 17, 32]. So far, there were few studies exploring the prognostic value of FAM83A, along with the correlation between the FAM83A expression and immune infiltration in pan-cancer analysis. In this study, we performed a comprehensive and systematic analysis of FAM83A in different cancers employing the data from different databases. We found that the expression level of FAM83A was significantly associated with survival outcomes and correlated with various tumor-infiltrating immune cells in LUAD. The potential mechanism underlying the correlation between FAM83A and the expression of PD-L1 might be mediated by JAK/STAT pathway. FAM83A could therefore be applied as a prognostic biomarker, which may also play a crucial role in immune suppression by affecting tumor-infiltrating immune cells.

The discrepancy of FAM83A expressions in esophageal, renal, prostate cancer samples (versus normal tissues) between ONCOMINE and TIMER databases may be due to the confounding bias, including the different collection, and processing of data. While in LUAD and LUSC, FAM83A were upregulated molecule across several databases. Cai, et al. and Richtmann, et al. showed that the association of FAM83A with a worse prognosis in both LUAD and LUSC [33, 34]. However, in GEPIA and Kaplan-Meier Plotter database, we found that the expression level of FAM83A was only significantly associated with the prognosis in LUAD, but not in LUSC. Meanwhile, previous clinical studies have also reported the association of high FAM83A expression with a poor prognosis in LUAD[10, 35]. Similarly, our multivariate survival analysis displayed that FAM83A differential expression level was the significant indictor affecting the prognosis of LUAD patients. The different effects of FAM83A on the prognosis of patients with LUSC may be attributed to different races, regions, and insufficient sample size. More clinical data are needed for subgroup analysis in LUSC.

Immune cells play essential roles in tumor progression and metastasis [36, 37], but few studies have investigated the expression of FAM83 family members and its correlated immune infiltration with poor prognosis[17–19]. We found that overexpressed FAM83A downregulated the expression of B cells and dendritic cells in LUAD, including the smoking-related LUAD patients that reported by Zhang, et al[19]. These changes of immune infiltrating cells reduced the production of anti-tumor antibodies and the activation of T cells, and therefore promote tumor progression and metastasis[38–41]. Imbalance of immune infiltrating cells in tumor microenvironment might be a possible underlying mechanism for the poor prognosis of LUAD with high FAM83A expression.

Additionally, FAM83A was involved in a variety of tumor-related signal transduction pathways, including EGFR, RAS/Raf/MEK/ERK and PI3K/Akt /mTOR [9, 16]. Recently, some studies have shown that FAM83A can drive the expression of PD-L1 through ERK pathway in LUAD [17] and PD-L1 expression was regulated by JAK-STAT pathway in several cancers [42–44]. Regulation of PD-L1 expression via JAK/STAT pathway in cancer was illustrated in a published review [45] and a KEGG (The Kyoto Encyclopedia of Genes and Genomes) map[46] (Additional Fig. 3). In our research, the FAM83A expression level was found to be associated with PD-L1 and positively correlated with STAT1, STAT3, and JAK1 in GEPIA. As a result, we speculated that FAM83A could drive PD-L1 expression through JAK/STAT pathway, which may also be a potential mechanism for the correlation of FAM83A expression with immune infiltration and poor prognosis in LUAD.

To sum up, through the multi-database comprehensive analysis, we found that the high expression level of FAM83A was significantly correlated with a worse prognosis in LUAD. Besides, FAM83A could reduce the infiltration of B cells and dendritic cells and also increased the expression of PD-L1 in tumor microenvironment of LUAD. The expression level of FAM83A was positively correlated with the expression of PD-L1, STAT1, STAT3 and JAK1 and FAM83A therefore may affect PD-L1 expression through JAK/STAT pathway in LUAD. Our results suggested that FAM83A could be a prognostic biomarker and new target for immunotherapy in lung adenocarcinoma patients. Experimental studies are warranted to further verify.

Acknowledgments

We sincerely thank the online public databases, including ONCOMINE, PrognoScan, K-M Plotter, GEPIA, LCE, Timer, and KEGG, for providing open access.

Authors’ contributions

X.S., L.H.B., P.H.X., K.J.T.: designed the project and wrote the manuscript. X.S., L.H.B., Y.K.K., Z.M.L., R.J.G.: analyzed and interpreted the data. P.H.X., Y.F.Z., J.Y.W.: participated in discussion and language editing. K.J.T.: Acquisition of funding. All authors reviewed the manuscript. The authors read and approved the final manuscript.

Funding

This work and the open access were supported by a grant from Guangzhou Science and Technology Planning Program (202002030023) and Natural Science Foundation of Guangdong Province (18zxxt17).

Availability of data and materials

Publicly online accessible datasets were examined in this study. The details can be found here: ONCOMINE (https://www.oncomine.org/resource/login.html), PrognoScan (http://www.abren.net/PrognoScan/), Kaplan-Meier plotter (https://kmplot.com/analysis/),GEPIA (http://gepia.cancer-pku.cn/index.html), LCE (http://lce.biohpc.swmed.edu/), TIMER (https://cistrome.shinyapps.io/timer/), KEGG (http://www.genome.jp/kegg/)or http://www.kegg.jp/.

Ethics approval and consent to participate

There was no need for ethical approval as all data in this study were retrieved from public and open-source databases. Ethical review and approval were not required for the study on human participants in accordance with the local legislation and institutional requirements.

Consent for publication

Not applicable.

Competing interests

The authors declare no conflict of interest.

Author details

1 Division of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China

2 Institute of Pulmonary Diseases, Sun Yat-sen University, Guangzhou, China

3 Department of Pharmacy, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China

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No competing interests reported.

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FAM83A: A Prognostic Biomarker and Its Correlation with Immune Infiltration in Lung Adenocarcinoma

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