The data of CRC tumor and adjacent normal tissue samples were obtained from The Cancer Genome Atlas (TCGA; www.cancergenome.nih.gov) and the Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/; Access number: GSE17537) databases. The TCGA-CRC dataset contained a total of 512 CRC samples, including 471 tumor samples and 41 adjacent normal samples. The age of the samples is from 41 to 90 with the median age of 68. Numbers of female and male patients is 212 and 235, respectively. The GEO dataset contained 55 CRC tumor samples. The age of those 55 patients is from 23 to 94 with the median age of 61. Numbers of female and male patients is 29 and 26, respectively.

Differential expression analysis was performed on the TCGA-CRC dataset using edgeR package in R v. 3.5.3 software (20). First, genes were excluded with average counts <10. Then the samples were divided into normal tissue group (N) and tumor tissue group (T) according to the sample type. A false discovery rate (FDR) <0.05 and |log2 fold change (FC)| >1 were set as the criteria for screening differentially expressed genes.

GSEA (version 2.2) was conducted for functional enrichment analysis (21). The selected gene set was Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. P<0.05 was set as the threshold for screening significantly enriched KEGG pathways.

The normal colorectal cell line FHC, colon cancer cell line LoVo, CRC cell line SW620, and colon cancer cell line SW1116 were purchased from BeNa Culture Collection. FHC, LoVo, SW620 and SW1116 cells were cultured in DMEM (Gibco; Thermo Fisher Scientific, Inc.), DMEM/F12 (Gibco; Thermo Fisher Scientific, Inc.), DMEM/F-12K (Gibco; Thermo Fisher Scientific, Inc.) and DMEM/L-15 (Gibco; Thermo Fisher Scientific, Inc.) containing 10% fetal bovine serum (FBS; Hyclone; GE Healthcare Life Sciences) and 1% penicillin/streptomycin (Hyclone; GE Healthcare Life Sciences), respectively. The cells were incubated at 37°C with 5% CO₂.

RNA was extracted from LoVo cells using Trizol reagent (Thermo Fisher Scientific, Inc.). cDNA was synthesized by TransScript^® Two-Step RT-PCR SuperMix (TransGen Biotech). ORF sequence of TNNT2 was amplified via RT-PCR according to the manufacturer's instructions of 2×TransTaq^® HiFi PCR SuperMix II (TransGen Biotech). TNNT2 primer sequences were as follows: Forward, 5′-ATGTCTGACATAGAAGAGGTGGTGG-3′ and reverse, 5′-CTATTTCCAGCGCCCGGTGACTTTA-3′. PCR reaction condition was as follows: 94°C 3 min, 1 cycle, 94°C 30 sec, 55°C 30 sec, 72°C 3 min, 35 cycles and 72°C 10 min, 1 cycle. Then PCR products were inserted into the pCMV-Myc vector (Biovector Co., Ltd.) to construct the expression vector pCMV-Myc-TNNT2. LoVo, SW620 and SW1116 cells were transfected with 16 µg/ml pCMV-Myc-TNNT2 using Lipofectamine 2000 (Thermo Fisher Scientific, Inc.) for 48 h according to the manufacturer's instructions.

Total RNA of FHC, LoVo, SW620 and SW1116 cells was extracted using Trizol (Invitrogen; Thermo Fisher Scientific, Inc.). The purity and concentration of RNA were determined via NanoDrop ND-2000 spectrophotometer (NanoDrop Technologies; Thermo Fisher Scientific, Inc.). Then the RNA was reverse transcribed into cDNA using TransScript^® Two-Step RT-PCR SuperMix (TransGen Biotech) according to the manufacturer's instructions. RT-qPCR was performed according to the manufacturer's instructions of the SYBR Premix Ex Taq kit (Roche Diagnostics), with GAPDH used as the internal reference. The thermocycling conditions were as follows: Step 1, 95°C for 5 min; step 2, 95°C for 30 sec; step 3, 58–65°C for 30 sec; step 4, 72°C for 30 sec; step 5, repeat from step 2 for 34 cycles; step 6, 72°C for 10 min. The relative expression of TNNT2 was calculated using the 2^−ΔΔCq method. The primer sequences of RT-qPCR are listed in Table I.

The cells were lysed using RIPA solution and then total proteins were extracted. The proteins were quantified using bovine serum albumin (BSA; Boster Biological Technology Co., Ltd). The protein samples were electrophoresed on 10% SDS-PAGE and transferred onto PVDF membranes. After blocking with 1X Blotto (Thermo Fisher Scientific, Inc.) for 2 h at room temperature, the membranes were incubated with anti-Cardiac Troponin T antibody (cat. no. ab91605; 1:1,000; Abcam) and anti-GAPDH antibody (cat. no. ab8245; 1:1,000; Abcam) at 4°C overnight. After washing with TBST three times at room temperature, the membranes were incubated with horseradish peroxidase (HRP)-labeled goat anti-rabbit IgG as the secondary antibody (cat. no. ab6728; 1:1,000; Abcam) for 1.5 h at room temperature. The proteins were visualized using Western Lightning™ Chemiluminescence reagent (PerkinElmer, Inc.), and densitometric analysis was conducted using LabWorks™ 4.6 (UVP, LLC). GAPDH was used as the internal control.

The CRC and normal tissues were fixed using 4% paraformaldehyde at 4°C overnight, embedded with paraffin, and sliced into 3–5 µm sections, followed by dewaxing. After antigen retrieval by microwave, the sections were blocked with 10% normal goat serum (Beijing Solarbio Science & Technology Co., Ltd.) and incubated at room temperature for 20 min. Then the primary antibody rabbit anti-cardiac troponin T (cat. no. ab91605; Abcam) were added for an incubation at 4°C overnight. The biotin-labeled IgG (cat. no. Sp-9001; 1: 1,000; OriGene Technologies, Inc.) was used as secondary antibody for 30 min at room temperature. After development in DAB and counterstaining with hematoxylin for 5 min at room temperature, the sections were sealed with resinene. Five fields were randomly selected and imaged under an optical microscope (BX51T-PHD-J11, Olympus Corporation). The images were analyzed using Image-Pro Plus (Media Cybernetics, Inc.).

Cox regression analysis was performed by using survival and survminer packages in R software (22). Clinical factors, including age, sex, TNM staging system [American Joint Committee on Cancer (AJCC) (23) and the International Union Against Cancer (UICC) (24)] and gene expression levels, were adjusted in the Cox regression model. P<0.1 was set as the threshold to screen factors significantly associated with CRC survival. Kaplan-Meier analysis was performed by stratifying CRC patients according to median TNNT2 expression. Data were presented as the mean ± SEM, n=3. The significance was assessed via one-way ANOVA (with Tukey's post hoc analysis). Statistical analysis was performed using GraphPad Prism Version 5.0 software (GraphPad Software, Inc.).

A total of 2,703 downregulated genes and 4,001 upregulated genes between CRC tumor samples and paracancerous samples were identified. The volcano blot is presented in Fig. 1A. Analysis of these differentially expressed genes revealed that TNNT2 was significantly upregulated in CRC tumor samples vs. adjacent normal samples, as indicated by Fig. 1B (P=1.6×10⁻⁷). Furthermore, there was a positive association between TNNT2 gene expression with the stages of patients with CRC, especially between stage II and stage III, as indicated in Fig. 1C (P=0.0026). As the association between TNNT2 and CRC has not been investigated in previous studies, TNNT2 was selected as the key candidate gene, and the association of TNNT2 with the progression and prognosis of CRC was investigated.

CRC samples were divided into a high- and low-expression group according to the median level of TNNT2 expression which was 4.82 (log2-based) according to the survival package. The survival curve was plotted using survminer package (Fig. 2A). It was revealed that the expression level of TNNT2 had a significant effect on survival outcome (P=0.012). Moreover, a Cox regression model was constructed adjusting for age, sex, staging and TNNT2 expression level (high or low) (Fig. 2C). It was revealed that compared with the high-TNNT2 expression group, the low-expression group exhibited a more favorable survival outcome. Additionally, patients with CRC with higher stages had a higher risk of mortality.

The same method was utilized for the survival analysis to verify the association of TNNT2 expression with survival in GEO dataset GSE17537. The survival curve suggested that different expression levels of TNNT2 had an effect on survival in patients with CRC, but the difference was not statistically significant (P=0.56). The Cox regression analysis indicated that the TNNT2 low expression group had a lower risk of mortality compared with the high expression group, and patients at higher stages had a higher risk of mortality (Fig. 2B and D).

According to the median expression level of TNNT2, CRC samples were stratified into high and low expression groups, and then differential expression analysis was performed. A total of 784 differentially expressed genes were identified, of which 163 genes were downregulated and 621 genes were upregulated. The top 100 differentially expressed genes within down- and upregulated gene sets were selected, respectively. A heatmap was constructed comprising the 200 selected genes in 10 CRC samples with the highest and lowest TNNT2 expression, respectively (Fig. 3A). According to the functional enrichment analysis, the ‘ErbB signaling pathway’ and ‘glycerophospholipid metabolism pathway’ were significantly activated in the high TNNT2 expression group (Fig. 3B).

In order to further confirm the effect of TNNT2 on the ErbB signaling pathway and glycerophospholipid metabolism pathway, RT-PCR were carried out in CRC cell lines transfected with the expression vector pCMV-Myc-TNNT2. As indicated in Fig. 4A, TNNT2 expression was significantly increased in LoVo, SW620 and SW1116 cells following transfection with pCMV-Myc-TNNT2. Additionally, the expression of EGFR and Fasn were significantly increased (Fig. 4B and C). This result demonstrated that high TNNT2 expression upregulates the ErbB signaling and glycerophospholipid metabolism pathway in CRC cell lines, which was consistent with the present bioinformatics analysis.

The mRNA and protein expression levels of TNNT2 were detected in normal colorectal cell line FHC, colon cancer cell line LoVo, CRC cell line SW620 and colon cancer cell line SW1116. The result revealed that compared with the normal colorectal cells, the mRNA expression level of TNNT2 was significantly increased in the CRC cells (P<0.05; Fig. 5). Moreover, the protein expression level of TNNT2 in CRC cells was higher compared with in normal colorectal cells (P<0.05; Fig. 6). Immunohistochemistry was performed to detect the protein expression of TNNT2 in CRC and normal tissues. The result indicated increased protein expression level of TNNT2 in CRC tissues in comparison to that in normal tissues (P<0.05; Fig. 7).