The role of FOXD2-AS1 in cancer: a comprehensive study based on data mining and published articles

Abstract Background and aims: Long non-coding RNA (lncRNA) FOXD2 adjacent opposite strand RNA 1 (FOXD2-AS1) is aberrantly expressed in various cancers and associated with cancer progression. A comprehensive meta-analysis was performed based on published literature and data in the Gene Expression Omnibus database, and then the Cancer Genome Atlas (TCGA) dataset was used to assess the clinicopathological and prognostic value of FOXD2-AS1 in cancer patients. Methods: Gene Expression Omnibus databases of microarray data and published articles were used for meta-analysis, and TCGA dataset was also explored using the GEPIA analysis program. Hazard ratios (HRs) and pooled odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the role of FOXD2-AS1 in cancers. Results: This meta-analysis included 21 studies with 2391 patients and 25 GEO datasets with 3311 patients. The pooled HRs suggested that highly expressed FOXD2-AS1 expression was correlated with poor overall survival (OS) and disease-free survival (DFS). Similar results were obtained by analysis of TCGA data for 9502 patients. The pooled results also indicated that FOXD2-AS1 expression was associated with bigger tumor size and advanced TNM stage, but was not related to age, gender, differentiation and lymph node metastasis. Conclusion: The present study demonstrated that FOXD2-AS1 is closely related to tumor size and TNM stage. Additionally, increased FOXD2-AS1 was a risk factor of OS and DFS in cancer patients, suggesting FOXD2-AS1 may be a potential biomarker in human cancers.


Introduction
Malignant tumors pose a great threat to human health [1]. Each year, there are approximately 14 million new cases of malignant tumors worldwide and more than 8.2 million deaths [2,3]. The prognosis for cancers is still poor, the difficulties of early cancer diagnosis and the lack of tumor-specific targeted drugs is the main reason [4]. Therefore, there is an urgent need for the identification of tumor-specific diagnostic biomarkers.
Long non-coding RNA (lncRNA) was originally discovered during large-scale sequencing of mouse full-length complementary DNA (cDNA) libraries [5], are RNA molecules over 200 nt in length that cannot be translated into proteins [6]. LncRNA was initially considered as noise, but the development of high-throughput sequencing and gene chip technology has revealed that many lncRNAs are abnormally expressed in tumor tissues. These lncRNAs are closely related to tumor resistance, cancer development, invasion and metastasis, suggesting that lncRNAs may be a new class of predictors or therapeutic targets for cancers [7,8]. Some lncRNAs have been identified as prognostic biomarkers for cancer patients, including HOTAIR [9], CRNDE [10], ZEB1-AS1 [11], and PCAT-1 [12].
LncRNA FOXD2 adjacent opposite strand RNA 1 (FOXD2-AS1) is located at chromosome 1p33, and has been linked to deterioration and progression of cancers. FOXD2-AS1 is elevated in several cancers, such as nasopharyngeal carcinoma (NC) [13], hepatocellular carcinoma (HCC) [14][15][16][17], gastric cancer (GC) [18], colorectal cancer (CRC) [19,20], non-small cell lung cancer (NSCLC) [21,22] and esophageal squamous cell carcinoma (ESCC) [22][23][24][25], breast cancer [26], glioma [27][28][29][30] and so on. The overexpression of FOXD2-AS1 has also been associated with clinicopathological characteristics and prognosis of cancers. However, the association between FOXD2-AS1 expression and clinicopathological characteristics in cancers remains controversial, and most studies have been limited by small sample size. Su et al. [31] reported that high FOXD2-AS1 expression was associated with T stage and recurrence, but not with lymph node metastasis and differentiation, and overexpression of FOXD2-AS1 was related to poor overall survival (OS) and disease-free survival (DFS) in bladder cancer. Xu et al. [18] found that FOXD2-AS1 expression was related to tumor size, TNM stage, and lymphatic metastasis, but not to gender, age and differentiation, and overexpression of FOXD2-AS1 was correlated with a high risk of DFS in GC. Bao et al. [32] found no relationship between FOXD2-AS1 and clinicopathological characteristics, but observed that elevated FOXD2-AS1 expression was associated with a poor OS and DFS in ESCC. Interestingly, Ren et al. [33] reported that FOXD2-AS1 was related to Clark level and distant metastasis, however, FOXD2-AS1 was not related to OS or DFS. To date, there has been a meta-analysis about the FOXD2-AS1, however, the studies included were limited [34], so we performed a comprehensive meta-analysis based on GEO datasets and published articles, and assessed the the Cancer Genome Atlas (TCGA) dataset to analysis the clinicopathological and prognostic value of FOXD2-AS1 in patients in pan-cancers.
We set the inclusion criteria for articles in this meta-analysis as follows: (1) use of qRT-PCR or RNA-seq data to measure the expression of FOXD2-AS1 in tumor tissues; (2) reported association between FOXD2-AS1 expression and clinicopathological characteristics and prognosis; and (3) reported specific hazard ratios (HRs) with 95% confidence interval (CI) or inclusion of sufficient data so that these parameters can be calculated by survival curves.
The exclusion criteria were: (1) conference reports, case reports, reviews, letters, and editorials; (2) studies that only reported the molecular function of FOXD2-AS1; (3) non-human studies in articles; and (4) duplicate articles.

Data extraction and quality assessment
Two investigators (Chaojie Liang and Yongping Zhang) performed the search independently and the identified articles were assessed based on the criteria. The extracted data included clinicopathologcial characteristics, OS, and DFS. Newcastle-Ottawa Scale (NOS) criteria [35] were used to assess the quality of studies. NOS score ≥ 6 was considered high-quality studies, otherwise, the studies were considered as low-quality.

Public data and tools
A web program named GEPIA was used to analyze the relationship between FOXD2-AS1 and prognosis. In GEPIA, one-way ANOVA was used to analyze the expression of FOXD2-AS1, and the Kaplan-Meier method and the log-rank test were used to calculate survival analysis, and the cut-off values were analyzed by GEPIA.

Statistical analyses
Statistical data were analyzed by STATA14.2 software. We extracted the HR value with 95% CI from survival curve data by Engauge Digitizer 10.0. Pooled ORs with 95% CIs were calculated for the association of FOXD2-AS1 expression and clinicopathological features. HRs with 95% CIs were calculated to assess the correlation between FOXD2-AS1 expression and prognosis. Heterogeneity was assessed by I 2 test and Q test, and the random effect was performed if the I 2 > 50%, and when the I 2 < 50%, fixed effect was used. We considered the results significant when the pooled OR or HR values with 95% CI did not overlap 1. Sensitivity analysis or subgroup analysis was performed to analyze the presence of heterogeneity and stability of results, and publication bias was assessed by Begg's funnel.

Study identification and characteristics
The screening process employed is shown in Figure 1. Twenty-one studies [13,14,[16][17][18]20,21,23,29,31,33,[36][37][38][39][40][41][42][43][44][45] with a total of 2391 patients were selected. The selected studies included four HCC study, two colorectal cancer (CRC) study, one ESCC study, one tongue squamous cell carcinoma study, one GC study, one NC study, one bladder cancer (BC) study, two glioma studies, one NSCLC study, two cutaneous melanoma (CM) study, and two papillary thyroid carcinoma (PTC) study, one cervical carcinoma (CC) study, one head and neck carcinoma study (HNSC) and one osteosarcoma study (OSC). The studies were selected for inclusion in this meta-analysis based on the inclusion and exclusion criteria. These articles were published from 2017 to 2020, the sample size ranged from 50 to 481 patients, and all studies were from China and published in English or Chinese. All studies scored >6 on the NOS, which indicated that all the studies were of high quality. The details of articles are summarized in Table 1.
As shown in Tables 2 and 3, 19 GEO databases with 2265 patients were included in this meta-analysis for OS.   There were 11 studies from the United States, 14 studies from Western countries, and 6 studies from Asia. Studies of nine different types of tumors were included in the meta-analysis including lung cancer (n=6), colon cancer (n=3), breast cancer (n=3), ovarian cancer (n=2), diffuse large B-cell lymphoma (DLBCL, n=1), chronic lymphocytic leukemia (CLL, n=1), glioblastoma (GBM, n=1), meningioma (n=1), and melanoma (n=1). We also analyzed ten GEO datasets containing records for 1568 patients to calculate DFS. This analysis included three kind of cancers: colon cancer (n=5), breast cancer (n=3), and lung cancer (n=2).

Prognostic value of FOXD2-AS1 for OS
This meta-analysis included data for a total of 4241 patients. The pooled HR indicated that FOXD2-AS1 expression was closely related to a poor OS (HR = 1.34, 95% CI = [1.20, 1.48], P<0.001, Figure 2), and there was no significant heterogeneity (I 2 = 0). In addition, we performed subgroup analysis according to source, region, tumor type and tumor size, as shown in Table 4 Figure 4B). Abbreviation: n, number of sample size.

Prognostic value of FOXD2-AS1 for DFS
The prognostic value of FOXD2-AS1 for DFS of cancer patients was assayed using data that included 13 studies and 2007 patients; and we found a significant relationship between FOXD2-AS1 and DFS (HR = 1.49, 95% CI = [1.22, 1.76], P<0.05, Figure 5). We performed Begg's funnel plot analysis to assess potential publication bias. As shown in Figure 6, no significant publication bias was identified for OS (P=0.159, Figure 6A) or DFS (P=0.669, Figure 6C). Sensitivity analysis can  assess the stability and reliability of meta-analysis results, and can also assess whether the combined results are affected by a single study by calculating the results when individual studies are omitted and determining if the result is within the CI. Sensitivity analysis was performed and the results are shown in Figure 6B,D, indicating the results were robust and reliable.

Validation of TCGA dataset results
Next, we explored FOXD2-AS1 expression in all cancer types using data from the TCGA dataset. As shown in Figure 7A, FOXD2-AS1 was overexpressed in cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), lymphoid neoplasm diffuse large B-cell lymphoma (DLBC), esophageal carcinoma (ESCA), pancreatic adenocarcinoma (PAAD), rectum adenocarcinoma (READ), skin cutaneous melanoma (SKCM), stomach adenocarcinoma (STAD), and thymoma (THYM), determining using a |log2FC| cutoff > 1 and a q-value < 0.01. A total of 9502 patients with digestive, respiratory, urinary, female reproductive, blood, and urinary systems cancers were included in the analysis. According to FOXD2-AS1 expression, the patients were divided into two groups according to mean expression by GEPIA. The results indicated that FOXD2-AS1 expression was correlated with a high risk of poor OS ( Figure 7B) and DFS ( Figure 7C). We also explored the prognostic role of FOXD2-AS1 in different tumor types, such as gastrointestinal (GI; Figure 8A,B), hepatobiliary, and pancreatic cancers ( Figure 8C,D). As shown in Figure 8, FOXD2-AS1 expression was related to poor OS in hepatobiliary and pancreatic cancer ( Figure 8C), urinary cancer ( Figure 8G), and head and neck cancers ( Figure 8K). However, no significant association was found between FOXD2-AS1 expression and OS in cancers of the respiratory system ( Figure 8E). FOXD2-AS1 expression indicated poor DFS in urinary ( Figure 8H), respiratory ( Figure 8F), and head and neck tumors ( Figure 8L), but FOXD2-AS1 expression was not related to DFS in hepatobiliary and pancreatic cancers ( Figure 8D). Interestingly, the high expression of FOXD2-AS1 was related to favorable prognosis in GI ( Figure 8A,B) and female reproductive cancers ( Figure 8I,J).