A total of 60 matched pairs of GC tissues and adjacent normal tissues were obtained from patients who underwent surgical resection without any neoadjuvant treatment between May 2016 and July 2018 at the First Affiliated Hospital of Wannan Medical College, China. Tumor–node–metastasis (TNM) staging of GC samples was performed by two senior pathologists. All tissue specimens after surgery were immediately frozen in liquid nitrogen for subsequent RNA isolation. Written informed consent was obtained from all GC patients, and the study was performed with the approval of the Medical Ethical Committee of Wannan Medical College.

The human GC cell lines SGC-7901, BGC-823, AGS, MKN-45, MGC-803, HGC-27 and the immortalized human gastric epithelial mucosa cell line GES-1 were purchased from the Institute of Biochemistry and Cell Biology of the Chinese Academy of Sciences (Shanghai, China) and the Cell Resource Center of Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College (Beijing, China). Cells were maintained in RPMI 1640 medium supplemented with 10% fetal bovine serum (FBS, Wisent, St-Bruno, PQ, Canada), 100 U/ml penicillin and 100 mg/ml streptomycin (Invitrogen, Carlsbad, CA, United States) in a 37°C incubator supplied with humidified air containing 5% CO₂. SiRNA and antisense oligodeoxy nucleotides (ASO) sequences were designed and synthesized by GenePharma (GenePharma, Shanghai, China) and RiboBio (RiboBio, Ltd., Guangzhou, China), all the sequences for siRNAs and ASO were listed in Supplementary Table S1. GC cells were transfected with the siRNA at a final concentration of 25 nmol/L using Lipofectamine 2000 (Invitrogen, CA, United States) and ASOs at the final concentration of 100 nM using Oligofectamine transfection reagent (Invitrogen) according to the manufacturer’s instructions.

DNA extraction of GC cells was performed with the Genomic DNA Mini Preparation Kit (Beyotime Biotechnology, China) following the manufacturer’s instructions. Total RNA from GC cell lines and tissues was extracted using the TRIzol reagent (Invitrogen, Carlsbad, CA, United States), and reverse transcription was performed with the PrimeScript^TM RT reagent Kit with gDNA Eraser (Takara, Dalian, China) with random hexamers on 1 μg of RNA. Relative expression levels of FALEC and ECM1 were determined by qRT-PCR using the YBR^® Premix Ex Taq^TM II kit (Takara, Dalian, China) according to the manufacturer’s instructions. Primers used for qRT-PCR analyses were synthesized by GENEWIZ (Suzhou, China) and are listed in Supplementary Tables S2, S3. The relative expressions of interested genes were normalized to the expression of β-actin. Gene expression was analyzed using the 2^-ΔΔCt method, and all experiments were performed in triplicate.

Wound healing and transwell invasion and migration assays were performed as described previously (Cui et al., 2015). Briefly, a scratch was generated across confluent cell monolayers using a 10 μl sterile pipette tip followed by supplemented with serum-free medium after washed with phosphate buffered solution (PBS) to remove floating cells. In vitro cell migration and matrigel (BD Biosciences, San Jose, CA, United States) invasion assays were performed using the transwell system (8-μm pore size with polycarbonate membrane; Corning Costar, MA, United States). Cells were seeded into the top chamber in serum-free medium, and medium containing 10% fetal bovine serum was placed in the bottom chamber as an attractant. Cells migrating through the pores or invading through the matrigel were fixed with methanol and stained with 0.5% crystal violet after 36 h of incubation. Images were obtained at 20x magnification by using a microscope (Olympus, Tokyo, Japan).

pGL3-Promoter was digested with BamHI and SalI, and FALEC coding sequence was synthesized by General Biosystems (General Biosystems, Inc., Chuzhou, China) was cloned into the restriction enzyme sites sites 5′ upstream to the luciferase gene. Luciferase assays were performed in 96-well plates using the Dual-Luciferase^® Reporter (DLR^TM) Assay (Promega, Madison, WI, United States) according to the manufacturer’s protocol, and the relative luciferase activity was normalized to the Renilla luciferase activity.

Whole-cell lysates were separated by 10% sodium dodecyl sulfate–polyacrylamide gel electrophoresis and transferred to 0.22 μm polyvinylidene fluoride membranes (Millipore). After blocking the membrane with 5% skimmed milk for 2 h at room temperature, it was incubated with specific anti-ECM1 (Bioworld Technology, Inc.) and anti-β-actin (Sigma-Aldrich) antibodies overnight at 4°C. Protein detection was performed with the enhanced chemiluminescence (ECL) system (SuperSignal; Pierce, United States).

Comparative analysis of FALEC and ECM1 expression levels and correlation analysis were obtained from Gene Expression Profiling Interactive Analysis (GEPIA¹, a web server for cancer and normal gene expression profiling and interactive analyses) (Tang et al., 2017). The expression of ECM1 in GC and its correlation with clinical information such as GC grade and subtype was evaluated using online analysis tool UALCAN (Chandrashekar et al., 2017). Kaplan-Meier survival analysis² was used to determine the influence of ECM1 expression on GC prognosis, and the log-rank test was utilized to compare survival curves between high and low ECM1 expression groups (Szasz et al., 2016).

All data are presented as means ± SD and all statistical analyses were performed using SPSS 20.0 software (IBM Corp., Armonk, NY, United States) or GraphPad Prism 5 software (GraphPad Software, Inc., La Jolla, CA, United States). Differences in the expression levels of FALEC and ECM1 between tumor and non-tumor tissues were analyzed using the chi-squared test (χ2 test). The difference in ECM1 expression regulated by FALEC was estimated using the Student’s t-test. The association between FALEC expression and pathological features of GC was analyzed with the chi-squared (χ2) test. The correlation between FALEC and ECM1 expression levels was analyzed using Pearson’s correlation coefficient test. Survival curves were conducted using the Kaplan-Meier method and the difference was analyzed by log-rank test. All p-values presented were two-sided and the difference was considered to be statistically significant at ^∗p < 0.05 and ^∗∗p < 0.01.

To investigate the possible role of FALEC in the progression of GC, we first detected the expression of FALEC in six human GC cell lines and 60 pairs of GC tissues and paired non-tumorous tissues. As shown by qRT-PCR analysis, FALEC expression was higher in GC cell lines and tumor tissues than controls and non-tumorous tissues (Figure 1A,B). The highest and lowest levels of FALEC were detected in HGC-27 (cell line established from lymph node with metastasis from GC) and AGS (established from human primary GC) cells indicated that FALEC may be a putative driver of metastasis (Figure 1A). Further statistical analysis found that FALEC expression was remarkably higher in tumor tissues compared with adjacent non-tumor tissues (Figure 1C). Next, we divided the samples into high (≥2-fold increase in GC tissues compared with adjacent non-tumor tissues) and low (less than 2-fold) FALEC expression groups to explore correlations between FALEC expression and clinicopathological characteristics in GC patients. As shown in Table 1, although no significant associations between FALEC expression and gender, age, Lauren’s classification, or histological type were detected, the expression of FALEC was significantly correlated with TNM and lymph node metastasis stage. An in-depth analysis found that FALEC expression significantly higher in GC tissues with lymph node metastasis than in non-lymph node metastasis (Figure 1D).

The amplification of a gene can lead to its overexpression such as EGFR and MYC are contained in frequently-amplified regions (Beroukhim et al., 2010). Hu et al. found that FALEC exhibited copy-number gains and losses in cancer (Athie and Huarte, 2014). But, we did not detect significant amplification of FALEC DNA (Supplementary Table S3), therefore, the overexpression of FALEC may not due to the DNA amplification in GC cells.

To explore the potential role of FALEC in GC progression, three siRNA pairs and two ASO targeting FALEC were synthesized to screen for the most effective sequence in HGC-27 and MGC-803 cells. The most efficient siRNA 2 and ASO 1 were chosen for subsequent functional analysis (Figure 2A,B). Because the over-expression of FALEC is significantly associated with lymph node metastasis in GC patients, we first explored its effect on the migration and invasion of GC cells. After transiently transfecting with siRNA or negative control into the GC cell lines, qRT-PCR was used to detect the interference efficiency before cell scratch and transwell assays were performed (Figure 2C). As shown in Figure 2D, the FALEC knockdown resulted in a slower recovery after wounding in HGC-27 (left) and MGC-803 (right) cells compared with the control. Also as expected, FALEC knockdown produced a significant reduction in migration and invasive ability in HGC-27 (Figure 2E) and MGC-803 (Figure 2F) cell lines compared with control by transwell assays. Taken together, these results indicate that knockdown of FALEC expression attenuates migration and invasion in GC cell lines, thereby suppressing the malignant progression of GC.

Previous studies demonstrated that a subset of enhancers was transcribed into a class of eRNAs, and that eRNA knockdown would decrease expression of nearby or target genes by cis-regulation (Kim et al., 2010; Li et al., 2013; Hsieh et al., 2014). To test this hypothesis, we interrogated the FALEC locus and found that protein-coding genes TARS2, RPRD2, ECM1, ADAMTSL4, MCL1 and ENSA were within this genomic region (Figure 3A). To determine whether FALEC has an enhancer-like function, we explored the effect of FALEC on the transcription of nearby genes in HGC-27 and MGC-803 cell lines. As shown in Figure 3B, the depletion of FALEC led to a significantly reduced the expression of its adjacent protein-coding gene ECM1, but did not affect the other genes surrounding FALEC in mRNA level in HGC-27 and MGC-803 cells. These results implied that FALEC may functions as an enhancer element in specifically regulating the expression of ECM1 by cis, and this effect was specific to the ECM1, as we did not detect any changes in the other genes surrounding FALEC. Moreover, ECM1 knockdown did not affect the expression level of FALEC or any of the other adjacent genes further supporting the fact that FALEC is an independent regulator of ECM1 (Figure 3C). Together, these results implied that FALEC might functions as an eRNA to activate ECM1 expression in GC cell lines.

Previous studies showed that an important property of enhancers that stimulates transcriptional activity is independent of the orientation of the DNA sequence (Khoury and Gruss, 1983). To dissect the regulatory mechanisms of the FALEC-activation on the expression of ECM1, we constructed a vector in which the FALEC sequence is reversed (pGL3-Promoter-FALEC-Reverse) (Figure 3D) and cloned down-stream of Firefly luciferase in the pGL3-Promoter vector to assess its orientation independence and enhancement of transcription. As shown in Figure 3E, FALEC inserts result in a significant enhancement of transcription in HGC-27 and MGC-803 cells compared with control. To further demonstrate that the observed potentiation of gene expression is mediated through the action of FALEC, we knocked down the FALEC using siRNAs, depletion of FALEC resulted in a significant decrease of in transcriptional enhancement compared with control in HGC-27 and MGC-803 cells (Figure 3E). Taken together, these experiments demonstrated that FALEC modulated ECM1 expression by exerting its enhancer-like function although the underlying nature of FALEC in the regulation of ECM1 needs further investigation.

Previous research suggested that ECM1 plays pivotal roles in cancer cell migration and invasion (Xiong et al., 2012; Gomez-Contreras et al., 2017), so we examined whether ECM1 affected the migration and invasion ability of the GC cells. SiRNA was used to knockdown the expression of ECM1, and the silencing efficiency was assessed by qRT-PCR (Figure 4A) and western blotting (Figure 4B) in HGC-27 and MGC-803 cells. As shown in Figure 4C,D, ECM1 knockdown significantly impaired the migration and invasion ability of GC cells compared with control. To further investigate whether FALEC affected cell migration and invasion by down-regulating ECM1, we used siRNA and transwell assays to evaluate the cell migration and invasion abilities of the two genes. Compared with the control group, simultaneous silencing of ECM1 and FALEC significantly inhibited the migration and invasion ability of GC cells more than ECM1 alone or the control group in GC cells (Figure 4C,D). These results indicated that FALEC knockdown inhibits cell migration and invasion partly by down-regulating ECM1 in GC cells.

To clarify that ECM1 was the functional target of FALEC, a rescue experiment was conducted in GC cells. We ectopically expressed ECM1 by transfecting of pcDNA3.1(+) containing the ECM1-coding sequence together with siRNA for FALEC into MGC-803 cells. The transwell assay clearly demonstrated that ECM1 overexpression markedly restored the abrogated migration and invasion of GC cells inhabited by FALEC (Figure 4E). This result further confirmed that FALEC-targeted ECM1 is involved in GC cell migration and invasion.

To explore the relationship between ECM1 and FALEC mRNA expression and their clinical significance, we investigated ECM1 expression levels in GC specimens using the GEPIA online database. As shown in Figure 5A, ECM1 was significantly upregulated in tumor tissues compared with non-tumorous tissues. A remarkable positive correlation was found between ECM1 and FALEC mRNA expression in GC (Figure 5B), further indicating that FALEC exerts enhancer effects to promote ECM1 expression, thereby promoting migration and invasion in GC cells. Next, we employed the UALCAN online database to analyze the expression of ECM1 in different stages and histological subtypes of GC patients. Box plot showing that the expression of ECM1 in subtypes of GC samples were significantly higher than normal except for intestinal adenocarcinoma (Mucinous) (Figure 5C), and the expression level of ECM1 was relatively high compared to the normal gastric tissues for GC patients (Figure 5D). Finally, we performed a correlation analysis of ECM1 expression and clinical outcome of GC patients using a Kaplan–Meier plotter. Kaplan-Meier survival plots showed that high ECM1 expression in GC patients was associated with shorter overall survival (OS) (Figure 5E) and progression-free survival rates (PFS) (Figure 5F) compared with patients with low ECM1 expression. These results above suggested that FALEC exerts enhancer activity to promote the ECM1 expression and participate in the development of GC.