We collected 60 pairs of CRC tumor and para-cancer tissues from the Yunnan Cancer Hospital/The Third Affiliated Hospital of Kunming Medical University. The age of the CRC patients ranged from 46 to 69 years, including 31 males and 29 females. Baseline demographic and clinical characteristics of all 60 CRC patients were collected. All tumors and adjacent tissues removed from the patient were immediately placed in liquid nitrogen and transported to the laboratory within 2 hours for storage in a –80 °C degree refrigerator. Written informed consent was obtained from all participants prior to their enrollment in the study. The protocols for the present study were approved by the Medical Institutional and Clinical Research Ethics Committee of the Yunnan Cancer Hospital, the Third Affiliated Hospital of Kunming Medical University (refers to the same entity) in accordance with the “Declaration of Helsinki” on the ethical principles for medical research involving human subjects.

Previous studies have demonstrated that HNF1A-AS1 is a potential long noncoding RNA which regulates tumor progression. Using the TCGA database, we analyzed the expression of HNF1A-AS1 in 33 different tumors and adjacent tissues. In addition, we analyzed the expression of HNF1A-AS1 in colon cancer and rectal cancer tissues and corresponding para-cancer tissues and its association with overall survival (OS). We further verified differences in HNF1A-AS1 expression in colon cancer and rectal cancer in relative para-cancer tissues in the two databases.

First, we used the “limma 2.11” R package to analyze the differences in HNF1A-AS1 expression in 477 tumors and 41 neighboring tissues in the TCGA database. Then, we analyzed HNF1A-AS1 in 125 immune related genes related to the distribution in the tumor and nearby tissue. Differential screening was set at a threshold for $|$log2 fold change (FC)$|$ $>$1 and a p value 0.05, using a screening of the volcano map. Finally, to determine the correlation between HNF1A-AS1 and differentially expressed miRNAs, TargetScan was used to predict and construct the correlation.

To explore the potential functions of 125 immune-related genes associated with HNF1A-AS1, GO (is an internationally standardized classification system of gene functions that provides a dynamically updated and controlled vocabulary to comprehensively describe the properties of genes and gene products in an organism) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the R package ‘clusterprofiler’ R package. In the analysis results, pathways or functions with a p value 0.05 were considered to be significantly enriched.

The human normal colon epithelial cell lines (NCM460) and the human colon cancer cell lines (HCT116, HT29, SW480, SW620, and LOVO) were purchased from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). The NCM460 and HCT116 cells were cultured in the Roswell Park Memorial Institute-1640 (RPMI-1640; MeilunBio, Dalian, China) and Dulbecco’s modified Eagle’s medium (DMEM; Procell, Wuhan, China). The HT29 and SW480 cells were cultured in L15 media (Leibovitz’s L-15; Procell), the SW620 and LOVO cells were cultured in F12K media (Ham’s F-12K; Procell). Media were supplemented with 10% fetal bovine serum (FBS; Procell) and 100 µg/mL penicillin-streptomycin solution (Procell). Cells were grown at 37 °C incubator with 5% CO${}_2$/95% air. This procedure was also used for the preparation and transfection of HNF1A-AS1 shRNA and INHBA shRNA.

Using Lenti-Pac™ HIV Expression Packaging Kit (GeneCopoeia, Guangzhou, China), the interference plasmid and over-expression plasmid were transfected into 293T cells with DNA-lipofectamine 2000 reagent (Invitrogen; Carlsbad, CA, USA) The complete medium was changed 8 h after transfection. After 48 h of incubation, the culture supernatant rich in lentivirus particles was collected and stored at –80 °C. Following polybrene™ (Merck KGaA, Darmstadt, Germany)-assisted HNF1A-AS1 interference of lentivirus for 72 h, 1 µg/mL puromycin was used to screen the transfected positive cells. The medium was changed every 2 days and screening with complete medium was continued for 2 weeks to expand the cell culture. All cell lines were genotyped for identity by Shanghai Biowing Applied Biotechnology Co., Ltd. Mycoplasma Removal Agent (0.02ug /ml,C0288M, Biyuntian, Shanghai, China) was added during the experiment. The cell morphology was observed under the microscope, which was similar to that of the ATCC cell bank. STR identification was performed on the experimental cells.

Cell viability was demonstrated by a MTT kit (Solarbio, Beijing, China). After performing various treatments, HT29 and SW-480 cells and their transfection with HNF1A-AS1 shRNA and INHBA shRNA were cultured in 96-well plates for 24, 48, 72 and 96 h, respectively. Fresh media were mixed with MTT solution and serially added into culture plates. 4 h later, dimethyl sulfoxide (Sigma, St. Louis, MO, USA) was added into wells to dissolve formazan. Samples were assessed by microplate reader (Thermo Fisher, New York, NY, USA), and results were obtained by analyzing the output of the wavelength at 490 nm.

Cell apoptosis was determined by an Annexin V-fluorescein isothiocyanate (Annexin V-PE; Procell) detection kit (Solarbio). Briefly, cultured cells were digested with trypsin (Thermo Fisher), and suspended in binding buffer (Solarbio). Annexin V-PE (Solarbio) and 7-aminoactinomycin D (7-AAD; Solarbio) were then serially incubated with cells in the dark. Finally, samples were analyzed with a flow cytometer (Thermo Fisher).

In preparation of cell suspension, the cells were digested with 0.25% trypsin and collected, and the cells were resuspended and counted with culture supernatant. The cells were seeded into 96-well plates by 4 $\times$ 10${}^4$ cells, with 5 replicates in each group. A total of four 96-well plates were seeded and returned to the incubator for further culture (measured once at 0 h, 24 h, 48 h, 72 h and 96 h, respectively). CCK8 reagent was diluted with basal medium at 10:1. The 96-well plate was removed to remove the cell supernatant in the culture plate, and 100 µL of diluted CCK8 solution was added to each well, and care was taken not to form bubbles in the wells. A blank control well was set, and 100 µL of diluted CCK8 solution was added to the other 3 wells. The samples were returned to the incubator and incubated for 2 h in darkness. The OD value of each well in the 96-well plate was detected at 450 nm with a microplate reader.

The invasion of HT29 and SW480 cells and their transfection with HNF1A-AS1 shRNA and INHBA shRNA, respectively, was investigated with transwell chambers with Matrigel (Corning, Madison, NY, USA). Cells were seeded in the upper chambers with FBS-free DMEM or L15 media (Procell). DMEM or L15 media containing 15% FBS (Procell) were added into the lower chambers. After 24 h of culture, the cell supernatant was discarded and cells were singly incubated with methanol (Sigma) as well as crystal violet (Sigma). Results were analyzed by counting the cell numbers in the lower chambers under a microscope (Nikon, Tokyo, Japan) at a 100$\times$ magnification.

The relative expression of miRNAs, which is tightly linked with HNF1A-AS1, was detected by RT-qPCR in clinical CRC and para-cancer tissues. Subsequently, the association between differentially expressed miRNAs and HNF1A-AS1 was analyzed.

The miRDB, miRWalk, and TargetScan databases were utilized to predict the target genes of hsa-miR-214. RT-qPCR was used to detect the relative expression level of target genes located in the overlapping region. The relative expression levels of INHBA in CRC and para-cancer tissues were analyzed from the TCGA database. In addition, the expression of INHBA at different stages of CRC and its association with disease-free survival (DFS) and OS were analyzed.

Samples were homogenized with Trizol reagent (Takara, Kyoto, Japan), and total RNA was extracted according to the Trizol kit (Takara) instructions. After quantification by NanoDrop 2000 (Takara), 200 ng total RNA was utilized by the ReverTra Ace qPCR RT Kit (Takara) for reverse transcription according to the instructions. THUNDERBIRD SYBR® qPCR Mix (Takara) was used for quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) analysis. CFX96 Touch Real-Time PCR Detection System (Bio-RAD, Hercules, CA, USA) was used for RT-qPCR. GAPDH was used as an internal reference when determining the contents. Corresponding primer sequences are listed in Table 1.

Cell lysis buffer solution was added to the sample, and total protein extract was obtained after repeated suspension and centrifugation at 4 degrees. Protein concentration in the extract was detected by the Bradford method. Sodium dodecyl sulfate polyacrylamide gel electropheresis (SDS-PAGE) was used for protein electrophoresis, followed by 300 mA constant current for 1 h to transfer the protein onto the PVDF membrane. After sealing, the primary antibody was added and shaken overnight at 4 °C. After washing the membrane, a secondary antibody was added and incubated at 37 °C for 2 h. Then luminous solution was and tablet pressing, exposure and fixing were performed. ImageJ (version 1.8.0, LOCI, University of Wisconsin, Madison, WI, USA) analysis was used to obtain the images and determine the integral optical density of protein bands. GAPDH protein was selected as the internal reference.

IHC assay was performed according to the previous process. Briefly, paraffin sections were placed at 60 °C for 2 h, then washed with dimethylbenzene solution, ethanol, and TBS in sequence. After the antigen was retrieved with citrate buffer solution, endogenous peroxidase was blocked by 1% hydrogen peroxide. Tissues were incubated with primary antibody overnight at 4 °C. Subsequently, the sections were incubated with HRP-labeled goat anti-rabbit immunoglobulin G (1:100; Abcam). Sections were visualized by diaminobenzidine. The sections were then counterstained with hematoxylin and washed by dimethylbenzene solution and ethanol. Finally, the sections were sealed with neutral balsam. The results of the immunohistochemical staining were analyzed with an optical microscope.

SPSS 23.0 software (IBM Corp., Armonk, NY, USA) was used for data analysis, and graph pad prism 8.0 software (GraphPad Software, Inc., San Diego, CA, USA) was used for statistical mapping. The measured data was represented by mean $\pm$ standard deviation ($\pm$ s). If the data presented normal distribution, a paired sample t-test was used for comparison between two groups, and one-way analysis of variance was used for comparison between multiple groups. If the data was not normal, non-parametric testing was used. Counting data were tested by χ${}^2$ test. p 0.05 was considered statistically significant.

GEPIA production plot analysis of LncRNA HNF1A-AS1 gene expression in multiple cancer types and paired normal samples was performed, with each dot representing a different tumor or normal sample (Fig. 1A). It can be seen from the TCGA database that HNF1A-AS1 is highly expressed in Colon adenocarcinoma (COAD) and Rectum adenocarcinoma (READ) Fig. 1). The expression level of HNF1A-AS1 in colon and rectal cancer is correlated with OS (Fig. 1C,D). In addition, we found that in the database of colon cancer and rectal cancer, HNF1A-AS1 was highly expressed in cancer tissues compared with para-cancer tissues, and the difference was statistically significant (p 0.05) (Fig. 1E,F).

Fig. 1.

LncRNA HNF1A-AS1 is up-regulated and associated with OS. (A,B) The expression of HNF1A-AS1 in disparate types of cancers were exhibited with red dots and in para-cancer is shown with green dots. Data derived from TCGA database portal in GEPIA. (B) The horizontal axis shows the type of tumor and the height of the bar represents the median expression of certain tumor types or normal tissue. (C) Kaplan-Meier analysis of colon cancer patients with high (n = 134) or low (n = 135) HNF1A-AS1 levels. Statistical analysis was performed by log-rank test. (D) Kaplan-Meier analysis of rectal cancer patients with high (n = 45) or low (n = 45) HNF1A-AS1 levels. Statistical analysis was performed by log-rank test. (E) The expression of HNF1A-AS1 is up-regulated in colon cancer compared with para-cancer tissues (*p 0.05). (F) The expression of HNF1A-AS1 is up-regulated in rectal cancer compared with the para-cancer tissues (*p 0.05). The triangle symbol highlights the two genes. The triangle symbol highlights the two tumor; OS,overall survival; COAD, colon adenocarcinoma; READ, rectum adenocarcinoma; HNF1A-AS1, LncRNA HNF1A antisense RNA 1.

The hierarchical cluster analysis showed that the expression of hnf1a-as1 target genes was different in 477 tumors and 41 neighboring tissues (Fig. 2A). Similarly, there were differences in the expression of 125 immune-related genes associated with HNF1A-AS1 (Fig. 2B). With the cut-off $|$log2 (FoldChange)$|$ $\ge$1 and p value 0.05, compared with the control, we obtained 2027 up-regulated genes and 1404 down-regulated genes (Fig. 2C); In addition, based on TargetScan data, we found 65 miRNAs that may bind to HNF1A-AS1 (Fig. 2D). GO and KEGG analysis of 125 genes are shown related to immunity including CD4-positive, alpha-beta T cell differentiation involved in immune response, T-helper 17 type immune response, T-helper 1 type immune response, the intestinal immune network for IgA production (Fig. 3A,B).

Fig. 2.

The differential expression of HNF1A-AS1 in tumor and adjacent tissues and its correlation with differential expression of miRNAs. (A) Hierarchical cluster analysis of HNF1A-AS1 expression in 477 CRC and 41 adjacent tissues; The horizontal axis represents groups, and a black line represents a sample; The vertical axis represents the target gene of HNF1A-AS1. (B) Hierarchical cluster of 125 immune related gene expression differences associated with HNF1A-AS1; The e horizontal axis represents the grouping, and a black line represents a sample; The vertical axis shows 125 immune-related genes associated with HNF1A-AS1. (C) Volcano plot of differentially expressed miRNAs (DEMs). (D) Combined with TargetScan data, HNF1A-AS1 potential associated with DEMs. CRC, colorectal cancer; DEMs, differentially expressed miRNAs

Fig. 3.

GO annotation and KEGG pathway enrichment analysis. (A) A biological process rich in 125 genes related to immunity. (B) KEGG pathway enriched by 125 immune-related genes. GO, gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.

RT-qPCR results demonstrated that compared with para-cancer tissues, hsa-miR-1252-3p, hsa-miR-214, hsa-miR-3907, hsa-miR-4688-5p, hsa-miR-10527-5p were less expressed (p 0.05), while HNF1A-AS1 was highly expressed in the CRC tissues (p 0.05) (Fig. 4A). In addition, correlation analysis was conducted between HNF1A-AS1 and the expression of hsa-miR-1252-3p, hsa-miR-214, hsa-miR-3907, hsa-miR-4688-5p, and hsa-miR-10527-5p. The results showed that HNF1A-AS1 was negatively correlated with the expression of hsa-miR-1252-3p, hsa-miR-214, hsa-miR-3907, hsa-miR-4688-5p and hsa-miR-10527-5p. The expression of HNF1A-AS1 was negatively correlated with that of hsa-miR-214, hsa-miR-4688-5p and hsa-miR-1252-3p (p 0.05) (Fig. 4B,C,D,E,F).

Fig. 4.

Expression and correlation of HNF1A-AS1 and related miRNAs. (A) mRNA expression of HNF1A-AS1 and related miRNAs in tumor and normal tissues. (B) The correlation analysis between hsa-miR-1252-3p and HNF1A-AS1 expression in CRC tissues. (C) The correlation analysis between hsa-miR-214 and HNF1A-AS1 expression in CRC tissues. (D) The correlation analysis between hsa-miR-3907 and HNF1A-AS1 expression in CRC tissues. (E) The correlation analysis between hsa-miR-4668-5p and HNF1A-AS1 expression in CRC tissues. (F) The correlation analysis between hsa-miR-10527-5p and HNF1A-AS1 expression in CRC tissues (*p 0.05, **p 0.01, ***p 0.001). R 0.3, uncorrelated; p 0.05, significant correlation.

The miRDB, miRWalk, and TargetScan databases predicted four overlapping genes of miR-214 target genes, namely CXCR5, GFRA1, SNAP25 and INHBA (Fig. 5A). RT-qPCR results showed that compared with adjacent tissues, CXCR5, GFRA1, and SNAP25 genes were less expressed in CRC, while INHBA gene was highly expressed in CRC (p 0.001) (Fig. 5B–E).

Fig. 5.

Expression levels of target genes of hsa-miR-214 in CRC (n = 10) and normal tissues (n = 10). (A) The miRDB, miRWalk, and TargetScan databases were utilized to predict the target genes of hsa-miR-214. (B) Expression of CXCR5 gene in CRC and normal tissues. (C) Expression of GFRA1 gene in CRC and normal tissues. (D) Expression of SNAP25 gene in CRC and normal tissues. (E) Expression of INHBA gene in CRC and normal tissues. CXCR5, CXC ligand 5; GFRA1,GDNF family receptor α1; SNAP25 , synaptosome associated protein 25; INHBA, inhibin βA; p 0.05, significant difference.

The specific binding sites of INHBA-3’UTR and miR-214-5p were identified by starBase. The results indicated that INHBA might be the target gene of miR-214-5p, that is, miR-214-5p might regulate the expression of the INHBA gene through a post-transcriptional mode (Fig. 6A). Through enrichment analysis of the INHBA gene, it was found that miR-214-5p may be one of the key miRNAs regulated upstream from INHBA (Fig. 6B). Analysis of 450 colon cancer samples by TCGA database indicated that miR-214-5p is positively correlated with INHBA (Fig. 6C). The TCGA database was used to analyze the miRNAs data of 261 CRC tissues and normal control tissues. The results demonstrated that miR-214-5p was less expressed in tumor tissues compared with the adjacent tissues (p 0.01) (Fig. 6D).

Fig. 6.

Bioinformatics analysis of the upstream and downstream regulatory relationship between miR-214-5p and INHBA and their expression in CRC. (A) The binding site of miRNA-214-5p in INHBA was identified in the starBase. (B) The upstream and downstream regulatory relationship between miRNA-214-5p and INHBA was analyzed by enrichment. (C) miRNA-214-5p is positively correlated with INHBA in colon cancer patients based on TCGA database. (D) The expression of miRNA-214-5p in CRC and adjacent tissues was analyzed by TCGA database. p 0.05, significant difference.

According to the transcriptome data of 473 CRC and 41 adjacent tissues gathered in the TCGA database, it was found that INHBA was highly expressed in cancer tissues (Fig. 7A,B), and the expression level of INHBA was positively correlated with the T stage of tumor, that is, the higher the expression level of INHBA, the later the T stage of patients (p 0.05) (Fig. 7C). However, there was no correlation between the expression level of INHBA and the N stage, or M stage of the tumor (p $>$ 0.05) (Fig. 7D,E). The survival curve analysis of the GEPIA database demonstrated that there was a negative correlation between the expression level of INHBA and the survival rate of CRC patients, that is, the higher the expression level of INHBA, the lower the OS and DFS of CRC patients (p 0.05) (Fig. 7F,G). A prognostic risk score model of CRC was constructed based on the INHBA gene, and the area under the curve (AUC) was: 0.996 (95% CI: 0.993–1.000, p 0.05), indicating that the INHBA gene has high accuracy in predicting the prognosis of CRC (Fig. 7H).

Fig. 7.

Bioinformatics analysis of the expression of INHBA in CRC and its correlation with the prognosis. (A,B) The expression of INHBA in CRC and adjacent tissues was analyzed by TCGA database. (C) The expression of INHBA in different T stages of CRC was analyzed by TCGA database. (D) The expression of INHBA in different N stages of CRC was analyzed by TCGA database. (E) The expression of INHBA in different M stages of CRC was analyzed by TCGA database. (F) OS analysis corresponding to INHBA expression in CRC patients in GEPIA database. (G) DFS analysis corresponding to INHBA expression in CRC patients in GEPIA database. (H) Prognostic risk scoring model of CRC based on INHBA gene (***p 0.001). DFS, Disease-free survival.

The expression level of INHBA was detected by the immunohistochemical method in 60 pairs of CRC tissues and adjacent tissues, and the positive rate was analyzed by Image-Pro Plus scanning software. Compared with para-cancer tissues, the expression level of INHBA in CRC tissues was significantly up-regulated, with statistical significance (p 0.0001) (Fig. 8A,D). RT-qPCR and Western Blot results indicated that the transcription and protein level of INHBA in CRC tissues were higher than those in adjacent tissues (p 0.05) (Fig. 8B,C,E,F). In addition, INHBA was highly expressed in CRC cell lines (HT29, SW480 and SW620) compared with normal intestinal epithelial cells (NCM460) (Fig. 8G).

Fig. 8.

Expression of INHBA in CRC tissues and cell lines. (A,B) Positive rate in normal and tumor tissues detection by IHC. (C,D) Expression levels in normal and tumor tissues detected by western blot. (E,F) Expression levels in CRC cell lines NCM460, HCT116, HT29, SW480, SW620 and LOVO detected by western blot. (G) mRNA expression levels in CRC cell lines NCM460, HCT116, HT29, SW480, SW620 and LOVO detected by qRT-PCR.The protein expression was normalized against β-actin, and mRNA expression was normalized for GAPDH. Expressed as relative expression ratio. (*p 0.05, **p 0.01, ***p 0.001, ****p 0.0001). IHC, immunohistochemical.

The proliferation and invasion abilities of HT29 cells in HNF1A-AS1 shRNA (p 0.01) and INHBA shRNA (p 0.01) were both attenuated compared with those in the NC group (Fig. 9A,C), but the apoptosis was the opposite (Fig. 9E). The proliferation, invasion and apoptosis of SW480 cells in HNF1A-AS1 shRNA (p 0.01) and INHBA shRNA (p 0.01) were similar to those of HT29 (Fig. 9B,D,F). This indicates that HNF1A-AS1 and INHBA may be key target genes in CRC cell lines.

Fig. 9.

Biological function of HNF1A-AS1 and INHBA in human CRC cell lines. (A,B) HT29 and SW480 cells and their transfection with HNF1A-AS1 shRNA and INHBA shRNA, respectively HT29 and SW480 cells and their transfection with HNF1A-AS1 shRNA and INHBA shRNA, respectively proliferation at 24, 48, 72 and 96 h. (C,D) Apoptosis detection by flow cytometry. (E,F) Transwell invasion assay detects cell invasion ability (**p 0.01, ***p 0.001, ****p 0.0001).

A total of 60 pairs of tumor tissue samples from CRC patients meeting the inclusion and exclusion criteria were collected. The general baseline demographic and clinical data of patients are demonstrated in Table 2.

$\chi$${}^2$ test was used to analyze the correlation between the expression of INHBA protein and the clinicopathologic characteristics of 60 CRC patients, such as age, gender, tumor size, degree of differentiation, depth of invasion (T stage), lymph node metastasis (N stage), distant metastasis (M stage), TNM stage, vascular invasion, nerve invasion, expression status of mismatch repair protein (MMR), and tumor location. The results showed that the expression of INHBA was significantly correlated with the degree of differentiation, depth of invasion, lymph node metastasis, distant metastasis, TNM stage, MMR status, and vascular invasion (p 0.05), but was not significantly correlated with gender, age, tumor size, tumor location and nerve invasion (p $>$ 0.05), as shown in Table 3.