Abstract
Esophageal squamous cell carcinoma (ESCC) is one of the most common and deadly causes of cancer worldwide. However, to date, the mechanisms underlying its pathogenesis remain unclear. The present study investigated the gene expression profile of human esophageal cancer cell line TE-1, a cell model for ESCC, to gain insight to the genetic regulation of this disease. Human esophageal cancer TE-1 cells and normal esophageal HET-1A cells were cultured for isolation of total RNA. Differential expression of RNA transcripts was assessed using the Agilent 4×44 K microarray, combined with real-time PCR (qRT-PCR) for validation. Classification and function of the differential genes were illustrated by bioinformatics processing including hierarchical clustering and gene ontology (GO) analysis. We identified 4,986 transcripts with differential expression (fold-change ≥1.5, P<0.05), including 2,368 up-regulated and 2,618 down-regulated transcripts. GO analysis showed that the dysregulated transcripts were associated with biological process, cellular component, and molecular function. After bioinformatic analysis of significantly regulated signaling pathways, we found these transcripts may target 35 gene pathways, including p53 signaling, glioma, ubiquitin-mediated proteolysis, insulin signaling, cell cycle, inositol phosphate metabolism, mTOR signaling, and MAPK signaling. The differentially expressed transcripts were screened between the esophageal cancer cell line TE-1 and normal esophageal cell line HET-1A, as well as their target gene pathways. Further data mining is related to prevention and treatment of esophageal cancer.
Keywords: Esophageal cancer, cDNA microarray, differential gene expression, cell line
Introduction
Esophageal cancer has a rapidly rising incidence and poor survival rate. Affecting more than 450,000 people worldwide, it has the eighth most common incidence and sixth highest mortality of all cancers globally. Esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) make up more than 90% of diagnosed esophageal cancers [1]. Worldwide, the majority of esophageal cancers are ESCC, which has been the subject of most studies in China [2].
Interaction and imbalance between oncogenes and tumor suppressor genes result in the occurrence and development of cancer. Understanding this interplay requires a more global view of cancer genetics. A global view can be provided through powerful approaches that examine the expression profiles of hundreds to thousands of genes at once in large-scale analyses using gene chip technologies like cDNA microarray. Indeed, gene chip technology has been used to explore the molecular mechanisms in various tumors, including gastrointestinal stromal tumors [3], breast cancer [4], ovarian cancer [5], and thyroid carcinomas [6].
Gene expression changes during the course of esophageal cancer can provide important insight into disease development and progression. Previous studies analyzing gene expression changes have identified hundreds of genes differentially expressed in esophageal cancer, specifically in regards to disease metastasis, treatment sensitivity, and patient survival [7]. However, the mechanism of esophageal tumorigenesis remains incompletely understood, and predictive and diagnostic markers for the disease are still needed.
Human esophageal cancer cell line TE-1, developed by the cell bank at the Chinese Academy of Science, maintains biological characteristics of ESCC [8] and, therefore, is a cell model for ESCC. The present study profiled gene expression of TE-1 cells in comparison with normal esophageal cells to identify genes related to the occurrence and development of ESCC.
Materials and methods
Reagents
Normal esophageal cell line HET-1A and esophageal cancer cell line TE-1 were purchased from the Cell Bank of the Chinese Academy of Science (Beijing, China). Low Input Quick Amp Labeling kit, One-Color RNA Spike-In kit, Gene Expression Hybridization kit, Gene Expression Wash Buffer kit, gasket slide, and hybridization chamber were obtained from Agilent Technologies (Santa Clara, CA, USA. Nuclease-free water and RNeasy mini kits were obtained from Qiagen (Venlo, Limberg).
Chip and equipment
Gene expression was measured with Human Gene Expression 4×44 K v2 Microarray Kit, which targeted 27,958 Entrez Gene RNAs (G4845A, Agilent Technologies). Other equipment used included a L96G PCR Thermal Cycler Dice (Hangzhou Longgene Scientific Instruments Co. Ltd., Zhejiang, China), hybridization oven (G2545A, Agilent Technologies), and Genepix 4000B microarray scanner (Axon Instruments, Union City, CA, USA).
Cell culture
HET-1A and TE-1 cells were inoculated in 25 cm2 culture flasks at a concentration of 105 cells/cm2. Cells were grown in RPMI 1640 (Gibco) containing 10% FBS (HyClone), 2 mmol/L L-glutamine, and 100 U/mL streptomycin/penicillin and were cultured at 37 °C in a humidified atmosphere with 5% CO2. Medium was replaced every 3 days. When cells became confluent, they were trypsinized and sub-cultured at a concentration of 1:4.
mRNA label and chip hybridization
When cell density reached 6×106~107, total RNA was isolated with Trizol reagent (15596-018, Life Technologies, Carlsbad, CA, USA) and purified with a Qiagen RNeasy mini kit. Concentration was determined by ultraviolet absorption and cDNA was synthesized using an MBI Fermentas First Strand cDNA Synthesis kit (Fermentas GmbH, St. Leon-Rot, Germany). cDNA was labeled with aaUTP and Cy3 and fragmented at 60°C for 30 min. Gene expression chip was balanced to room temperature and hybridized with the labeled cDNA in a hybridization oven at 45°C and 10 rpm for 17 hours. The hybridized cDNA microarray was eluted, dyed, and scanned on a Genepix 4000B scanner. Images were analyzed with GenePix Pro 6.0. Fluorescence intensity of each array spot was quantified and the mean value was calculated.
Real-time PCR
Quantitative real-time polymerase chain reaction (qPCR) was used to validate the differential expression of five up-regulated and five down-regulated transcripts in the cDNA microarray using the primers detailed in Table 1. RNA was isolated from HET-1A and TE-1 cells using Trizol reagent and cDNA was synthesized with an MBI Fermentas First Strand cDNA Synthesis kit. PCR was conducted with SYBR Green Real-time PCR Kit (Toyobo Co. Ltd., Osaka, Japan). Each 10 μL reaction included 2×SYBR Real-time PCR buffer (5 μL), forward primers (0.5 μL, 0.5 µM), reverse primers (0.5 μL, 0.5 µM), cDNA template (0.5 μL), and dH2O (3.5 μL). PCR reaction conditions were 50°C for 2 min, 95°C for 10 min, and 40 cycles of 95°C for 15 s and 55°C for 30 s. Standard curves and melting curves were drawn to measure cycle threshold (Ct) values. Data were analyzed with the 2-ΔΔCt method. Fold changes were computed for Ct values of amplified mRNA in comparison to those of housekeeping gene GAPDH.
Table 1.
Primers used for qPCR
| Gene | Forward primer | Reverse primer |
|---|---|---|
| Upregulation | ||
| LOC643650 | GTTTTCTGGAGCGCTGTGTG | TCTTTTTCGTCCAGCCAGGT |
| TUFT1 | GCAACAATGCTGACTGCCAA | GGCGTCCTTTGACTGGATCA |
| HIST1H2BK | TACAACAAGCGCTCGACCAT | TAGCGCTGGTGTACTTGGTG |
| GPR119 | CAGCCCTTCCGCTACTTGAA | ACTGCCCTTTGTAGGCAGTC |
| C10orf35 | AGAGCTTCTTCAACAGGGGC | AGAGCTTCTTCAACAGGGGC |
| Downregulation | ||
| ARID3B | GGCAGAAGACAGAGCAGAGG | CTTCTGGGCAAACAGCACAC |
| THAP10 | ACTGGTACGGAGGCAATGAC | TCCTCTCCCCTCTTAGGTGC |
| PUS7 | CCATCAGTGAAGACGTGCCT | GCCTCAGTGAGTCCATGCTT |
| IKZF4 | GGCAAGGGAAGGATAATCTGGA | GGAGAAGAGTGCTGGCTGTT |
| DISP2 | CCAGTTTTTCCTGCACTGCC | GCTGGGTCTGGTTGTAGTCC |
Statistical analysis
Experiments were performed in triplicate and were compared in a factorial design using an error-weighted one-way analysis of variance (ANOVA). To control for multiple comparisons, we applied a Bonferroni multiple correction. Only gene expression changes with P≤0.05 were considered statistically significant. Gene ontology (GO) and pathway analyses were based on David 6.7 (http://david.abcc.ncifcrf.gov/home.jsp).
Results
Differentially expressed mRNAs
With a cut-off set at 1.5-fold difference between HET-1A and TE-1 cells, we identified 4,986 transcripts with differential expression, including 2,368 up-regulated and 2,618 down-regulated transcripts. For further analysis, we focused initially on transcripts that were up- or down-regulated more than 7-fold, which limited analysis to 55 up-regulated genes (Table 2) and 33 down-regulated genes (Table 3).
Table 2.
Genes upregulated in esophageal cancer cell line TE-1 (fold change >7 and P<0.05)*
| Gene symbol | Gene name | Genbank accession | Probe name | Fold change | P-value |
|---|---|---|---|---|---|
| LOC643650 | uncharacterized LOC643650 | NR_033957 | A_23_P359214 | 16.23 | 8.09E-03 |
| BC101214 | A_24_P229871 | 14.34 | 7.89E-03 | ||
| TUFT1 | tuftelin 1 | NM_020127 | A_23_P371824 | 12.63 | 1.33E-02 |
| HIST1H2BK | histone cluster 1, H2bk | NM_080593 | A_33_P3229083 | 11.86 | 1.39E-02 |
| GPR119 | G protein-coupled receptor 119 | NM_178471 | A_23_P21425 | 11.44 | 2.28E-02 |
| C10orf35 | chromosome 10 open reading frame 35 | NM_145306 | A_23_P369328 | 11.36 | 1.67E-03 |
| DDX42 | DEAD (Asp-Glu-Ala-Asp) box polypeptide 42 | NM_007372 | A_23_P152651 | 11.22 | 2.22E-02 |
| GFM2 | G elongation factor, mitochondrial 2 | NM_170681 | A_24_P137582 | 11.16 | 1.06E-02 |
| MPRIP | myosin phosphatase Rho interacting protein | NM_015134 | A_23_P15348 | 11.1 | 3.72E-02 |
| COPS2 | COP9 constitutive photomorphogenic homolog subunit 2 (Arabidopsis) | NM_004236 | A_23_P26021 | 10.52 | 2.63E-02 |
| LOC728190 | uncharacterized LOC728190 | NR_024397 | A_33_P3357753 | 10.43 | 1.89E-02 |
| PRKRIP1 | PRKR interacting protein 1 (IL11 inducible) | NM_024653 | A_33_P3235925 | 10.35 | 5.44E-04 |
| ADAMTSL4 | ADAMTS-like 4 | NM_019032 | A_23_P115011 | 10.15 | 1.08E-02 |
| NOP2 | NOP2 nucleolar protein homolog (yeast) | NM_001033714 | A_23_P204364 | 9.96 | 2.12E-02 |
| LOC100128361 | uncharacterized LOC100128361 | NR_036505 | A_32_P93996 | 9.87 | 2.35E-02 |
| ZZZ3 | zinc finger, ZZ-type containing 3 | NM_015534 | A_23_P11507 | 9.75 | 2.00E-02 |
| A_33_P3348744 | 9.72 | 1.83E-02 | |||
| CHDH | choline dehydrogenase | NM_018397 | A_23_P69293 | 9.35 | 1.97E-02 |
| SYS1 | SYS1 Golgi-localized integral membrane protein homolog (S. cerevisiae) | NM_001197129 | A_33_P3398107 | 9.2 | 2.50E-02 |
| GTF2F1 | general transcription factor IIF, polypeptide 1, 74kDa | NM_002096 | A_23_P16143 | 8.87 | 2.89E-02 |
| TMUB1 | transmembrane and ubiquitin-like domain containing 1 | NM_031434 | A_33_P3268763 | 8.84 | 2.10E-02 |
| HOXA10 | homeobox A10 | NM_018951 | A_33_P3288649 | 8.83 | 6.05E-03 |
| PCBP4 | Poly (rC) binding protein 4 | NM_033010 | A_23_P166807 | 8.8 | 4.34E-02 |
| PCNX | pecanex homolog (Drosophila) | NM_014982 | A_33_P3249529 | 8.73 | 1.64E-02 |
| CCNB1 | cyclin B1 | NM_031966 | A_33_P3401621 | 8.7 | 5.24E-03 |
| LOC157740 | uncharacterized protein C8orf9 | AJ291676 | A_32_P200237 | 8.65 | 1.69E-03 |
| PPME1 | protein phosphatase methylesterase 1 | NM_016147 | A_23_P64567 | 8.6 | 3.77E-02 |
| DAZAP2 | DAZ associated protein 2 | NM_014764 | A_23_P40025 | 8.37 | 3.90E-02 |
| STAM2 | signal transducing adaptor molecule (SH3 domain and ITAM motif) 2 | NM_005843 | A_24_P62860 | 8.34 | 4.18E-02 |
| EN2 | engrailed homeobox 2 | NM_001427 | A_23_P134433 | 8.26 | 7.68E-04 |
| RAPH1 | Ras association (RalGDS/AF-6) and pleckstrin homology domains 1 | NM_213589 | A_24_P924862 | 8.24 | 2.52E-02 |
| FOXK2 | forkhead box K2 | NM_004514 | A_33_P3310070 | 8.21 | 2.16E-02 |
| RNF126 | ring finger protein 126 | NM_194460 | A_23_P314086 | 8.18 | 4.24E-05 |
| RAB31 | RAB31, member RAS oncogene family | NM_006868 | A_24_P236799 | 8.04 | 2.71E-04 |
| LOC100653296 | uncharacterized LOC100653296 | XR_132982 | A_33_P3394789 | 8 | 2.05E-02 |
| CITED2 | Cbp/p300-interacting transactivator, with Glu/Asp-rich carboxy-terminal domain, 2 | NM_006079 | A_33_P3213374 | 7.88 | 1.28E-02 |
| PCMT1 | protein-L-isoaspartate (D-aspartate) O-methyltransferase | NM_005389 | A_24_P140827 | 7.87 | 3.26E-02 |
| GNAI1 | guanine nucleotide binding protein (G protein), alpha inhibiting activity polypeptide 1 | NM_002069 | A_23_P122976 | 7.81 | 1.76E-05 |
| HBG1 | hemoglobin, gamma A | NM_000559 | A_33_P3329078 | 7.66 | 2.26E-03 |
| RAI14 | retinoic acid induced 14 | NM_015577 | A_23_P92727 | 7.6 | 4.96E-02 |
| HOXC8 | homeobox C8 | NM_022658 | A_24_P124558 | 7.52 | 3.31E-03 |
| STIM1 | stromal interaction molecule 1 | NM_003156 | A_23_P53162 | 7.49 | 2.48E-03 |
| C7orf59 | chromosome 7 open reading frame 59 | NM_001008395 | A_33_P3326772 | 7.42 | 4.34E-02 |
| SH2D4A | SH2 domain containing 4A | NM_022071 | A_23_P169003 | 7.37 | 3.51E-02 |
| KIF21B | kinesin family member 21B | NM_017596 | A_23_P126888 | 7.33 | 1.93E-03 |
| LAMB2 | laminin, beta 2 (laminin S) | NM_002292 | A_33_P3338116 | 7.32 | 1.43E-03 |
| EPAS1 | endothelial PAS domain protein 1 | NM_001430 | A_23_P210210 | 7.27 | 2.71E-03 |
| SIDT2 | SID1 transmembrane family, member 2 | NM_001040455 | A_33_P3411741 | 7.24 | 3.96E-02 |
| A_33_P3411325 | 7.22 | 2.49E-02 | |||
| MYOM2 | myomesin (M-protein) 2, 165kDa | NM_003970 | A_23_P258912 | 7.19 | 1.49E-03 |
| ZC3HC1 | zinc finger, C3HC-type containing 1 | NM_016478 | A_23_P215088 | 7.16 | 2.16E-02 |
| ETFDH | electron-transferring-flavoprotein dehydrogenase | NM_004453 | A_23_P61447 | 7.15 | 6.86E-03 |
| TTC35 | tetratricopeptide repeat domain 35 | NM_014673 | A_23_P60002 | 7.09 | 4.09E-02 |
| SOCS1 | suppressor of cytokine signaling 1 | NM_003745 | A_23_P420196 | 7 | 4.13E-02 |
Compared to expression levels in normal esophageal cell line HET-1A.
Table 3.
Genes downregulated in esophageal cancer cell line TE-1 (fold change >7 and P<0.05)*
| Gene symbol | Gene name | Genbank accession | Probe name | Fold change | P-value |
|---|---|---|---|---|---|
| ARID3B | AT rich interactive domain 3B (BRIGHT-like) | NM_006465 | A_23_P88580 | -10.78 | 4.48E-02 |
| THAP10 | THAP domain containing 10 | NM_020147 | A_23_P106391 | -10.6 | 3.99E-02 |
| PUS7 | pseudouridylate synthase 7 homolog (S. cerevisiae) | NM_019042 | A_23_P82478 | -10.58 | 5.00E-02 |
| IKZF4 | IKAROS family zinc finger 4 (Eos) | NM_022465 | A_23_P378288 | -10.14 | 4.30E-02 |
| DISP2 | dispatched homolog 2 (Drosophila) | NM_033510 | A_23_P324340 | -10.12 | 3.53E-04 |
| SLC6A8 | solute carrier family 6 (neurotransmitter transporter, creatine), member 8 | NM_005629 | A_23_P159937 | -9.57 | 1.56E-03 |
| POGK | pogo transposable element with KRAB domain | NM_017542 | A_23_P137715 | -9.53 | 4.96E-02 |
| CCDC88B | coiled-coil domain containing 88B | NM_032251 | A_23_P24389 | -9.08 | 1.69E-03 |
| HLA-DPB1 | major histocompatibility complex, class II, DP beta 1 | NM_002121 | A_24_P166443 | -9 | 5.18E-05 |
| MOB3B | MOB kinase activator 3B | NM_024761 | A_23_P146551 | -8.92 | 4.94E-05 |
| SLC25A29 | solute carrier family 25, member 29 | NM_001039355 | A_23_P77048 | -8.31 | 2.93E-02 |
| IFFO2 | intermediate filament family orphan 2 | NM_001136265 | A_23_P418031 | -8.27 | 9.23E-04 |
| ANXA7 | annexin A7 | NM_004034 | A_23_P86570 | -8.14 | 2.72E-02 |
| SFT2D3 | SFT2 domain containing 3 | NM_032740 | A_23_P5568 | -8.12 | 1.21E-02 |
| QRFPR | pyroglutamylated RFamide peptide receptor | NM_198179 | A_23_P92467 | -8.03 | 5.84E-03 |
| SETD6 | SET domain containing 6 | NM_001160305 | A_33_P3315355 | -7.98 | 7.66E-04 |
| TBL1X | transducin (beta)-like 1X-linked | NM_005647 | A_33_P3347161 | -7.97 | 2.80E-05 |
| FAM178B | family with sequence similarity 178, member B | NM_001122646 | A_33_P3287119 | -7.95 | 2.84E-02 |
| AKAP7 | A kinase (PRKA) anchor protein 7 | NM_016377 | A_23_P259594 | -7.88 | 3.35E-02 |
| EDN1 | endothelin 1 | NM_001955 | A_23_P214821 | -7.83 | 1.47E-03 |
| NRM | nurim (nuclear envelope membrane protein) | NM_007243 | A_23_P8055 | -7.76 | 1.15E-02 |
| MAGEE1 | melanoma antigen family E, 1 | NM_020932 | A_23_P114445 | -7.75 | 1.18E-02 |
| ETAA1 | Ewing tumor-associated antigen 1 | NM_019002 | A_23_P51117 | -7.59 | 8.25E-03 |
| METTL10 | methyltransferase like 10 | NM_212554 | A_33_P3332066 | -7.42 | 3.05E-02 |
| CD63 | CD63 molecule | NM_001040034 | A_24_P270144 | -7.35 | 1.36E-03 |
| C7orf55 | chromosome 7 open reading frame 55 | NM_197964 | A_23_P82588 | -7.33 | 2.70E-03 |
| RAP1GDS1 | RAP1, GTP-GDP dissociation stimulator 1 | NM_001100426 | A_32_P85813 | -7.3 | 9.52E-03 |
| A_33_P3590279 | -7.28 | 1.89E-02 | |||
| GPCPD1 | glycerophosphocholine phosphodiesterase GDE1 homolog (S. cerevisiae) | NM_019593 | A_23_P91350 | -7.26 | 3.05E-03 |
| PPP1R3E | protein phosphatase 1, regulatory subunit 3E | NR_026862 | A_23_P428640 | -7.14 | 4.02E-02 |
| GTF2A2 | general transcription factor IIA, 2, 12 kDa | NM_004492 | A_24_P270525 | -7.09 | 1.08E-02 |
| HIST1H4B | histone cluster 1, H4b | NM_003544 | A_24_P166407 | -7.09 | 2.26E-05 |
| SSNA1 | Sjogren syndrome nuclear autoantigen 1 | NM_003731 | A_23_P159476 | -7.01 | 1.12E-02 |
Compared to expression levels in normal esophageal cell line HET-1A.
GO and pathway analysis
Inputting differentially expressed transcripts into the online tool David 6.7 (http://david.abcc.ncifcrf.gov/home.jsp) sorted 340 terms belonging to biological processes, 124 terms belonging to cellular components, and 104 terms belonging to molecular functions (Figure 1). Molecular functions included RNA binding, nucleotide binding, enzyme binding, cofactor binding, structural ribosome constituents, and ATP binding, and these functions could be associated with the occurrence and development of ESCC. Pathway analysis revealed 35 different pathways related to differentially expressed genes (Table 4).
Figure 1.
Gene ontology (GO) enrichment analysis (P<0.01). A. GO analysis of genes >5% associated with biological processes. B. GO analysis of genes >5% associated with cell components. C. GO analysis of genes >5% associated with molecular functions.
Table 4.
Target gene-related pathways
| Term | Counts | % | P-value |
|---|---|---|---|
| Ribosome | 40 | 0.90 | 0.0000 |
| p53 signaling pathway | 30 | 0.67 | 0.0003 |
| Glioma | 28 | 0.63 | 0.0004 |
| Spliceosome | 47 | 1.05 | 0.0005 |
| Small cell lung cancer | 34 | 0.76 | 0.0007 |
| Proteasome | 22 | 0.49 | 0.0009 |
| Ubiquitin mediated proteolysis | 49 | 1.10 | 0.0010 |
| Non-small cell lung cancer | 23 | 0.52 | 0.0029 |
| ErbB signaling pathway | 32 | 0.72 | 0.0056 |
| Insulin signaling pathway | 45 | 1.01 | 0.0074 |
| Chronic myeloid leukemia | 28 | 0.63 | 0.0080 |
| Cell cycle | 42 | 0.94 | 0.0084 |
| Neurotrophin signaling pathway | 41 | 0.92 | 0.0124 |
| Huntington disease | 56 | 1.25 | 0.0127 |
| Inositol phosphate metabolism | 21 | 0.47 | 0.0150 |
| Alzheimer’s disease | 51 | 1.14 | 0.0158 |
| Pathways in cancer | 93 | 2.08 | 0.0202 |
| Propanoate metabolism | 14 | 0.31 | 0.0208 |
| Phosphatidylinositol signaling system | 26 | 0.58 | 0.0243 |
| N-glycan biosynthesis | 18 | 0.40 | 0.0244 |
| Limonene and pinene degradation | 8 | 0.18 | 0.0258 |
| Prostate cancer | 30 | 0.67 | 0.0265 |
| Pancreatic cancer | 25 | 0.56 | 0.0316 |
| Parkinson’s disease | 40 | 0.90 | 0.0338 |
| Nicotinate and nicotinamide metabolism | 11 | 0.25 | 0.0339 |
| mTOR signaling pathway | 19 | 0.43 | 0.0406 |
| Beta-alanine metabolism | 10 | 0.22 | 0.0488 |
| Apoptosis | 28 | 0.63 | 0.0563 |
| Pyrimidine metabolism | 30 | 0.67 | 0.0598 |
| NOD-like receptor signaling pathway | 21 | 0.47 | 0.0645 |
| Amino sugar and nucleotide sugar metabolism | 16 | 0.36 | 0.0662 |
| Lysine degradation | 16 | 0.36 | 0.0662 |
| Valine, leucine, and isoleucine degradation | 16 | 0.36 | 0.0662 |
| MAPK signaling pathway | 73 | 1.64 | 0.0793 |
| Folate biosynthesis | 6 | 0.13 | 0.0877 |
qPCR confirmation of mRNA expression
To verify microarray results, five top up-regulated and five top down-regulated mRNAs were amplified using qPCR. Results showed highly significant concordance with microarray results for all 10 transcripts (Figure 2).
Figure 2.
Quantitative real-time PCR (qPCR) confirmed expression of ten selected genes. Five up-regulated genes [LOC643650 (LOC643650); tuftelin 1 (TUFT1); histone cluster 1, H2bk (HIST1H2BK); G protein-coupled receptor 119 (GPR119); and chromosome 10 open reading frame 35 (C10orf35)] and five down-regulated genes [AT rich interactive domain 3B (ARID3B); THAP domain containing 10 (THAP10); pseudouridylate synthase 7 homolog (PUS7); IKAROS family zinc finger 4 (IKZF4); and dispatched homolog 2 (DISP2)] were amplified from esophageal cancer cell line TE-1 and control esophageal cell line HET-1A. mRNA expression was measured in triplicate by qPCR and normalized to expression of housekeeping gene U6 using the two standard curves method. Data are expressed as mean ± SEM.
Discussion
We have presented a detailed analysis of the mRNA profile of esophageal cancer cell line TE-1 in comparison with the normal esophageal cell line HET-1A. These results have implications for our understanding of esophageal tumorigenesis.
The cDNA microarray used in this study has 27,958 Entrez gene RNA targets, of which 4,986 were differentially expressed between TE-1 esophageal cancer cells and HET-1A normal esophageal cells. Some of these genes have already been demonstrated to be relevant in esophageal cancer. For example, HOXC6 and HOXC8 are prognostic markers in patients with ESCC [9]. GPCR56, an orphan G-protein coupled receptor, is detected in 48% of ESCCs, while adjacent non-malignant esophageal tissue does not express this transcript [10]. Expression of Hsp90α and cyclin B1 is associated with tumor malignancy and prognosis for patients with ESCC [11]. Further exploration of differentially expressed genes in the progression of esophageal cancer is warranted to explore potential early diagnostic markers and their functions in esophageal tumorigenesis.
GO has become a major bioinformatics initiative to unify the representation of genes and gene products. Ontology is divided into three domains: (1) cellular components, referring to the parts of a cell or its extracellular environment; (2) molecular functions, describing the elemental activities of a gene product at the molecular level; and (3) biological processes, defining molecular events pertinent to the function of integrated living cells, tissues, organs, and organisms. This study sorted differentially expressed transcripts and identified 340 terms indexed in biological processes, 124 terms indexed in cellular components, and 104 terms indexed in molecular functions. Further, more than ten terms were >5% involved in biological processes: cellular macromolecule catabolic processes (5.49%); macromolecule catabolic processes (5.67%); cell cycle (5.33%); transcription (12.86%); negative regulation of macromolecule metabolic processes (5.02%); regulation of transcription (14.97%); protein localization (5.47%); proteolysis (6.25%); regulation of RNA metabolic processes (10.24%); and DNA-dependence (9.88%).
Further analysis revealed these differentially expressed transcripts were associated with 35 pathways. Among them, p53 signaling [12], glioma [13], ubiquitin-mediated proteolysis [14], insulin signaling [15], cell cycle [16], inositol phosphate metabolism [17], mTOR signaling [18], and MAPK signaling [19] have been demonstrated to be associated with the occurrence and development of human esophageal cancer, but little is known for the other pathways, which should be explored in human esophageal cancer in the future.
Disclosure of conflict of interest
None.
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