Open Access

Transcriptome analysis of tongue cancer based on high‑throughput sequencing

  • Authors:
    • Mingming Tang
    • Wencheng Dai
    • Hao Wu
    • Xinjiang Xu
    • Bin Jiang
    • Yingze Wei
    • Hongyan Qian
    • Liang Han
  • View Affiliations

  • Published online on: March 23, 2020     https://doi.org/10.3892/or.2020.7560
  • Pages: 2004-2016
  • Copyright: © Tang et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY_NC 4.0].

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Tongue cancer is one of the most common types of cancer, but its molecular etiology and pathogenesis remain unclear. The aim of the present study was to elucidate the pathogenesis of tongue cancer and investigate novel potential diagnostic and therapeutic targets. Four matched pairs of tongue cancer and paracancerous tissues were collected for RNA sequencing (RNA‑Seq), and the differentially expressed genes were analyzed. The RNA‑Seq data of tongue cancer tissues were further analyzed using bioinformatics and reverse transcription‑quantitative PCR analysis. The sequenced reads were quantified and qualified in accordance with the analysis demands. The transcriptomes of the tongue cancer tissues and paired paracancerous tissues were analyzed, and 1,700 upregulated and 2,249 downregulated genes were identified. Gene Ontology analysis uncovered a significant enrichment in the terms associated with extracellular matrix (ECM) organization, cell adhesion and collagen catabolic processes. Kyoto Encyclopedia of Genes and Genomes analysis demonstrated that these differentially expressed genes were mainly enriched in the focal adhesion pathway, ECM‑receptor interaction pathway, phosphoinositide 3‑kinase (PI3K)‑Akt pathway, and cell adhesion molecules. Comprehensive analyses of the gene tree and pathway network revealed that the majority of cell cycle genes were upregulated, while the majority of the genes associated with intracellular response, cell adhesion and cell differentiation were downregulated. The ECM‑receptor interaction, focal adhesion kinase (FAK) and PI3K‑Akt pathways were closely associated with one another and held key positions in differential signaling pathways. The ECM‑receptor, FAK and PI3K‑Akt signaling pathways were found to synergistically promote tongue cancer occurrence and progression, and may serve as potential diagnostic and therapeutic targets for this type of cancer.

Introduction

Oral cancer is a prevalent malignant tumor. Owing to the frequent mechanical stimulation, the incidence of tongue squamous cell carcinoma ranks first among oral cancer cases, and its incidence continues to increase (1,2). The incidence of tongue cancer is obviously higher among older patients, as the majority of the patients are aged ~60 years (3). Oral cancer is characterized as highly malignant, with high rates of local recurrence and cervical lymph node metastasis (4,5). Currently, surgery combined with postoperative radiotherapy and chemotherapy is the preferred treatment for tongue cancer (6). Due to the short-term recurrence and poor therapeutic efficacy, oral cancer has a dismal prognosis and severely affects the life quality of the affected patients (7). The 5 year survival rate of oral cancer is reported to be ~50% (8). The symptoms of early-stage oral cancer are atypical and they are often mistaken for a bite or a mild stabbing pain. Consequently, several patients with oral cancer already have intermediate- or advanced-stage disease at initial diagnosis and, thus, have missed the optimal window for treatment. Tongue cancer must be predicted and diagnosed as early as possible; thus, it is crucial to elucidate the molecular mechanisms underlying its etiology and pathogenesis.

Bioinformatics analyses of gene expression profiles have been extensively performed in recent years. As an assemblage of RNAs, the transcriptome is mainly transcribed from specific tissues or cells at a certain phase or functional state. Analyzing transcriptome data enables assessing overall gene function and structure, thereby elucidating the potential molecular mechanisms underlying pathological conditions, and has previously been applied extensively in cancer research (9). Non-coding RNAs (ncRNAs) are a type of RNA transcribed from DNA that lacks protein-encoding ability. Critical functions of ncRNAs have been highlighted in almost all aspects of cancer progression (10,11).

Transcriptome analyses have been well documented in cancer research; however, few transcriptome analyses have been reported for tongue cancer, and traditional in vivo experiments or single-gene studies are currently preferred. To the best of our knowledge, this is the first study to date to investigate differentially expressed mRNAs and ncRNAs in tongue cancer and paracancerous tissues via transcriptome analysis, in the hope that the findings may help identify potential targets for the diagnosis and clinical treatment of early-stage tongue cancer.

Materials and methods

Subjects

The present study was approved by the Medical Ethics Committee of Nantong Municipal Tumor Hospital (approval no. 2018037). Tongue cancer tissues and matched paracancerous tissues (located ~3 cm from the cancerous tissues) were surgically extracted from 4 patients with tongue cancer (cases 1–4, Table I). A total of 3 men and 1 woman were enrolled, with a mean age of 67 years. Pathologically, 3 of the patients had well-differentiated squamous cell carcinoma (n=2 with T3N2bM0, stage IVb and n=1 with T2N2cM0, stage IVb), and 1 patient had moderately differentiated squamous cell carcinoma (T2N0M0, stage II). Based on the tongue cancer subtypes, 3 patients had ulcerative infiltrating tongue cancer, and 1 had exophytic tongue cancer. Samples used for reverse transcription-quantitative PCR (RT-qPCR) were extracted from 20 patients, whose data are shown in supplementary Table SI. The mean age of these patients was 61.6 years (range, 51–73 years).

Table I.

Basic patient information.

Table I.

Basic patient information.

Case no.Age, yearsSexStage DifferentiationType
166MaleT3N2bM0, IVb Well-differentiatedUlcerative infiltrating
273MaleT2N0M0, II Well-differentiatedExogenous
357MaleT3N2bM0, IVbModerately differentiatedUlcerative infiltrating
473FemaleT2N2cM0, IVb Well-differentiatedUlcerative infiltrating
Hematoxylin and eosin (H&E) staining

Tongue cancer and paracancerous tissues were used for morphological observation with H&E staining as previously described (12). All the following steps are performed at room temperature. In brief, the tissues were fixed in paraformaldehyde for 4 h, dehydrated in graded concentrations of ethanol (70 to 100%, 1 min each), permeabilized in xylene for 5 min, and embedded in paraffin. After embedding, the tissues were cut into 4 µm sections, washed in descending concentrations of ethanol to remove the xylene (100 to 75%, 1 min each, with a final wash in water), stained with hematoxylin for 5 min followed by washing in water, and then stained with eosin for 2 min. The sections were observed and images were captured at a magnification of ×100 using the Olympus IX71 inverted microscope (Olympus Corporation).

cDNA library construction and sequencing

Total RNA was extracted from the tongue cancer and paracancerous tissues using TRIzol reagent (Thermo Fisher Scientific, Inc.). The RNA concentration and purity were determined using an ultraviolet spectrophotometer (RAY-757CRT; Raylabel Instrument Co., Ltd.). The cDNA library was constructed and sequenced as previously described (13). In brief, as much rRNA as possible was removed to obtain the purified RNA. Subsequently, mRNA and ncRNA were separated by poly (A) splicing. The RNA was randomly sliced into short fragments that were used as templates. The first-strand cDNA was synthesized alongside 6-bp random primers. The second-strand cDNA was synthesized using a commercial kit (Takara Biotechnology Co., Ltd.) following the manufacturer's instructions. After purification, end-repair, A-tailing and addition of adaptor sequences, the cDNA was fragmentated using uracil glycosylase.

cDNA fragments were subjected to PCR amplification, and the complementary cDNA library was constructed. ncRNAs and mRNAs were sequenced using the high-throughput and high-sensitivity HiSeq 2500 sequencing platform (Illumina, Inc.). Sequenced data were analyzed and processed to dynamically remove the sequence fragments at the 3′-end and low-quality fragments using Trim Galore −0.6.5 software (Babraham Institute). Finally, Fast-QC version 0.11.8 (Babraham Institute) was used to evaluate the quality of the preprocessed data.

Comparison with reference sequences

RNA-Seq data were compared with the reference database (GRCh, version 38) using Hisat2 software version 2.1.0 (Johns Hopkins University). Data were mapped with a 56-kb index by genetic fate mapping. Reads were quickly and accurately located on the genome to obtain the genomic structure of the sequencing data.

Analysis of differentially expressed genes

Gene expression was quantified via reads per kilobase per million mapped reads (RPKM), which was calculated using Htseq software version 0.9.0 (GitHuB, Fabio Zanini, University of New South Wales, Sydney) as follows: RPKM = total exon reads/[mapped reads × exon length (kb)]. Fold changes (FCs) of the differentially expressed genes in the tongue cancer and paracancerous tissues were calculated. Genes with log2 FC >1 or <-1 and a false discovery rate ≤0.05 were selected.

Gene Ontology (GO) analysis

GO analysis revealed significant enrichment of the terms associated with biological processes, molecular functions and cellular components. GO terms were assigned based on differentially expressed mRNAs and host genes with significantly different circRNAs. The P-value of each GO term was calculated using Fisher's exact test, and P<0.05 was considered to indicate statistically significant differences.

Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis

Pathway annotation of differentially expressed genes was performed using the KEGG database. The P-value of each pathway involved was analyzed using Fisher's exact test based on hypergeometric distribution. P<0.05 was considered to indicate statistically significant differences.

RT-qPCR

Tongue cancer and paracancerous tissues from each patient were considered as a group of samples to verify the changes of cancer-related genes by RT-qPCR. The total sample size was 20, and basic patient information is provided in Table SI.

According to the results of gene expression and signaling pathway analysis, 10 genes that were significantly different and were associated with cancer were selected for RT-qPCR. Their primers are listed in Table II (Sangon Biotech, Co., Ltd.). The reverse transcription kit used was PrimeScript™ RT reagent Kit with gDNA Eraser (Takara Biotechnology Co., Ltd.), first at 42°C for 2 min with gDNA eraser and buffer 1, and then at 37°C for 15 min and 85°C for 5 sec with enzyme mix, RT primer and buffer 2. qPCR (Takara Biotechnology Co., Ltd.) was performed at 95°C for 10 min, then at 95°C for 15 sec, 60°C for 30 sec and 72°C for 40 sec for 40 cycles, with a final step at 72°C for 5 min. The reactions were set up in 96-well format Microseal PCR plates (Bio-Rad Laboratories, Inc.) in triplicates.

Table II.

Primers used in reverse transcription-quantitative PCR.

Table II.

Primers used in reverse transcription-quantitative PCR.

GenePrimers (5′-3′)
COL4A6F: CTAACTATCTAAGGGGCTGTGC
R: ATTGGCTGATGGTGAGATTTGTATC
SPP1F: AGAAGTTTCGCAGACCTGAC
R: TTTCAGCACTCTGGTCATCC
FN1F: TACCATCAGAGAACAAACACTAATG
R: AAGAACTCTAAGCTGGGTCTGC
MMP13F: TCTGGACAGACTGGCTGTTG
R: TTGAAGGGATGTGATGGTCA
CXCL13F: CTCTGCTTCTCATGCTGCTG
R: CAGCTTGAGGGTCCACACAC
MMP9F: TTCAGGAGACGCCCATTTC
R: GTCGTCGGTGTCGTAGTTGG
COL10A1F: CATGCCTGATGGCTTCATAAA
R: AAGCAGACACGGGCATACCT
COL27a1F: GGAACGGACAGGTCTTTGAA
R: GGGTCCGGAAGGTGAATAGT
COL4A1F: GAACGGGCCCATGGACAGGACTTG
R: AGGTGGACGGCGTAGGCTTCTTG
CXCL10F: GTACGCTGTACCTGCATCAGCATTAG
R: CTGGATTCAGACATCTCTTCTCACCC

[i] F, forward; R, reverse; COL, collagen; FN1, fibronectin; SPP1, secreted phosphoprotein 1; matrix metalloproteinase.

Signaling pathway network

The signaling pathway networks were depicted using Cytoscape 3.4.0 software (Institute for Systems Biology). Each pathway network was depicted based on the pathway terms, and those with P<0.05 were analyzed by KEGG.

Statistical analysis

The data are presented as mean ± standard error of the mean. RNA-sequencing data were obtained from 4 independent experiments, while RT-qPCR data were obtained from 20. These data were mainly compared by log2FC to explain the upregulation of gene expression in cancer tissues.

Results

Tissue characteristics and morphology

Representative pathological images are shown in Fig. 1. The normal tongue mucosa is composed of stratified squamous epithelium, while the tongue cancer tissues were mostly highly differentiated, accompanied by large amounts of extracellular keratinization and intercellular bridges.

Mass analysis of the RNA-Seq data

Transcriptome sequencing and data filtering were performed on 4 matched pairs of tongue cancer and paracancerous tissues. After removing adaptor sequences, the acquired data were compared with the reference genome. Large data sequences and high unique mapping rates of the samples indicated that the quantity and quality of the sequenced data were in accordance with the requirements. The raw data have been uploaded to the NCBI online database, and the accession number is GSE143950.

Genome composition of the sequenced samples

Principal component analysis (Fig. 2A) revealed a good clustering effect for both the cancerous and adjacent tissues. The genetic composition of the samples in the exons, introns and intergenic regions is shown in Fig. 2B. Abundant RNA transcripts were detected in both exons and introns, suggesting the presence of numerous ncRNAs. The gene composition and distribution on the chromosomes is shown in Fig. 2C. Compared with the paracancerous tissues, Chr.14 was upregulated, while Chr.MT was downregulated in tongue cancer tissues. The gene expression in each patient's cancerous and paracancerous tissues is shown in Fig. 2D.

Analyses of differentially expressed genes

Gene expressions were quantified via RPKM. Expression abundances were calculated and depicted as volcano plots. In total, 24,582 genes were examined, of which 1,700 were upregulated and 2,249 were downregulated (Fig. 3). The top 20 differentially expressed mRNAs and ncRNAs are listed in Table III. The top 4 genes were MMP13 (log2FC=11.35), KRTAP13-2 (log2FC=−10.52), KRT36 (log2FC=−10.07) and S100A7A (log2FC=10.00). The heatmap revealed that the trend in gene expression change was consistent in all 4 patients, and the differences between the cancerous and paracancerous tissues were statistically significant.

Table III.

Top 10 differentially expressed genes among mRNAs and non-coding (nc)RNAs.

Table III.

Top 10 differentially expressed genes among mRNAs and non-coding (nc)RNAs.

A, mRNAs

Gene ID log2FC Up/downregulation
KRTAP13-2−10.52Down
KRT36−10.07Down
KRTAP13-1−9.95Down
MYOC−9.26Down
KRT84−8.96Down
CA99.07Up
IL249.27Up
MMP109.85Up
S100A7A10.00Up
MMP1311.35Up

B, ncRNAs

Gene ID log2FC Up/downregulation

RMST−8.62Down
LOC105375180−7.20Down
DIO2-AS1−6.83Down
LOC105372641−6.82Down
TATDN2P3−6.78Down
LINC005206.83Up
LOC1019282727.26Up
AFAP1-AS17.33Up
RFTN1P17.47Up
LINC013228.86Up

[i] FC, fold-change.

GO analysis

The genes that were differentially expressed in tongue cancer and paracancerous tissues were analyzed. GO analysis uncovered significantly enriched terms associated with three items: i) Biological processes: Extracellular matrix (ECM) organization, cell adhesion, collagen catabolic processes, ECM disassembly and the integrin-mediated signaling pathway; ii) molecular functions: Calcium ion binding, integrin binding, growth factor activity and ECM structural constituents; and iii) cellular components: Proteinaceous ECM, extracellular region and ECM. The most significantly enriched terms were analyzed as the ECM organization and cell adhesion (Figs. 4 and 5).

KEGG analysis

Of the pathways identified by KEGG pathway annotation and analysis, 61 were significantly downregulated and 43 were upregulated (Fig. 6). The most differentially activated pathways were focal adhesion, ECM-receptor interaction, pathways in cancer, small-cell lung cancer, phosphoinositide 3-kinase (PI3K)-Akt signaling and cell adhesion molecules (CAMs).

RT-qPCR

The differences of fold changes were compared between RNA-seq and RT-qPCR. The results are shown as Fig. 7. These 10 genes were all upregulated in cancer tissues, and there was no significant biological difference between RT-qPCR and RNA-seq, indicating that the RNA-seq results were consistent with those of RT-qPCR.

Signaling pathway network

Potential interactions among the differentially expressed pathways were depicted in the pathway network, including mitogen-activated protein kinase signaling, PI3K-Akt signaling, cancer, calcium signaling and focal adhesion pathways (Fig. 8).

Discussion

Tongue cancer is a prevalent malignant disease that is difficult to diagnose in its early stages and is characterized by high rates of metastasis and postoperative recurrence (4). Hence, the molecular mechanisms implicated in tongue cancer must be elucidated to improve the clinical outcomes of affected patients. In the complicated pathological network of tumorigenesis, abnormal upregulation or downregulation of a single gene cannot adequately illustrate complex transcriptome changes during tumor development. Consequently, GO and KEGG pathway annotations were used in the present study to analyze the transcriptome data of tongue cancer.

GO analysis uncovered significantly enriched terms associated with ECM organization (upregulated), cell adhesion (downregulated) and collagen catabolic processes (upregulated). KEGG analysis demonstrated that these differentially expressed genes were mainly enriched in the focal adhesion pathway (upregulated), ECM-receptor interaction pathway (upregulated), PI3K-Akt pathway (upregulated) and CAMs (downregulated). RT-qPCR was used to verify the sequencing results.

The occurrence, progression and metastasis of tongue cancer are closely linked to the ECM (14). Proliferation and fibrosis of connective tissues have been reported to accompany tumorigenesis and progression of solid tumors (15,16). Upregulated type I collagen, fibronectin (FN1) and other ECM proteins in breast cancer (17,18) and upregulated collagens, non-collagen glycoproteins and proteoglycans in hepatocellular carcinoma (19) suggest that the expression and component changes in the ECM are crucial indicators of tumor progression. Our RNA-Seq results revealed decreased elastin assembly and increased collagen degradation in tongue cancer tissues. Current evidence has demonstrated that fibrous tissue hyperplasia is a protective response of the body, which may be used as a prognostic indicator (20). Abnormal deposition and increased ECM rigidity are apparent in fibrotic and malignant cancer tissues (21). Neovascularization is a hallmark of cancer. The collagen (COL) gene family encodes collagen in the ECM, which can participate in inducing angiogenesis in cancer (2224). Sequencing and qPCR results demonstrated that COL4A1 and COL4A6 were significantly upregulated in tongue cancer, suggesting that these genes may play important roles in the occurrence and development of tongue cancer. Matrix metalloproteinases (MMPs) are important enzymes in the ECM, which can degrade the basement membrane and ECM and promote tumor cell invasion and metastasis (2527). MMP-9 and MMP-13 were found to be significantly upregulated in tongue cancer, further confirmed this function.

The mammalian ECM consists of ~300 proteins (28). The ECM acts as a structural support and infiltration mediator for tissues and organs, and as a cellular signal mediator that regulates cell phenotypes by transmitting signals via membrane surface receptors. A relevant study on hepatocellular carcinoma demonstrated that prostaglandin E2 (PGE2) activates prostaglandin EP3 receptor (PTGER3) in the mesenchymal cells surrounding tumor cells, thereby promoting the activation and release of vascular endothelial growth factor, MMP-2 and MMP-9; in this manner, PGE2 ultimately promotes angiogenesis and tumor cell growth (29). In addition, PTGER3 was found to regulate prostate cancer cell growth by targeting androgen receptors (30). KEGG analysis revealed that several ECM-receptor interactions were significantly upregulated and enriched. As depicted in the KEGG network, the ECM-receptor interaction pathway was directly linked to pathways in cancer, namely the small-cell lung cancer pathway, the PI3K-Akt pathway and CAMs in tongue cancer tissues. The interaction between the ECM and cell membrane receptors is considered to play a key role in tongue cancer development, suggesting that blocking such an interaction may suppress tongue cancer development and metastasis. Chemokines are cytokines that mobilize cells via chemotaxis. It was previously demonstrated that CXCL10, CXCL13 and other chemokines are closely associated with the occurrence and development of cancer (31,32). The sequencing and PCR results in the present study confirmed that the expression levels of CXCL10, CXCL13 and other chemokines in tongue cancer tissues were significantly increased, suggesting their importance in tongue cancer.

The PI3K-Akt pathway is widely distributed in various cells and is known to regulate cellular behavior, protein synthesis and angiogenesis (33). Under pathological conditions, dysregulation of the PI3K-Akt pathway may trigger cancer occurrence and progression (34). Three mechanisms are considered to be responsible for the biological functions of the PI3K-Akt pathway in cancer. First, the PI3K-Akt pathway suppresses apoptosis and stimulates cell proliferation. p-Akt can suppress the mitochondrial apoptotic pathway by downregulating caspase-9 (35). p-Akt can also inhibit cell apoptosis and promote proliferation by activating glycogen synthase kinase 3β, FOX proteins, the MDM2 protooncogene and the transcription factor NF-κB (36). Second, the PI3K-Akt pathway regulates cell cycle progression. By transmitting the mitotic signal to p70s6k, the PI3K-Akt pathway upregulates the expression of cell cycle-related proteins and CDK4. Subsequently, the upregulated CDK4 inhibits downregulation of p21Cip1/WAF1 and p27Kip1, thus triggering the progression from the G1 to the S phase (37). Finally, the PI3K-Akt pathway stimulates tumor angiogenesis and tumor cell migration by upregulating the hypoxia-inducible factors, nitric oxide and cyclooxygenase 2. After activating the PI3K-Akt pathway, downregulated E-cadherin, which is regulated by phosphorylated glycogen synthase, inactivates intercellular adhesion molecules and enhances the metastatic ability of tumor cells (38).

CAMs are functional molecules that mediate the contact and binding between cells, or between cells and the ECM. CAMs exert their biological effects via receptor-ligand binding, and participate in physiological and pathological processes, including cell proliferation, differentiation, movement, immune and inflammatory responses, coagulation, and cancer cell metastasis. Generally, CAMs comprise the integrin family, the immunoglobulin superfamily, the selectin family, the cadherin family, and other adhesion molecules. Epithelial-to-mesenchymal transition (EMT) usually occurs during tumor progression and embryonic development, leading to transformation of cells from an epithelial phenotype with strong adhesions to a mesenchymal phenotype with invasive ability and increased motility (39). EMT causes weakening of intercellular connections in cadherin-based isotypes and attenuates the ability of cells to anchor to the cytoskeleton via cadherin-catenin. Subsequently, activated CAMs with weak adhesion or heterotypic CAMs induce detachment of in situ tumor cells and entry into the blood or lymphatic circulation. CAMs regulate cell-cell adhesion and interactions between cells and the surrounding microenvironment. Moreover, CAMs and their relevant pathways play important roles during different stages of tumor progression (40).

Focal adhesions (FAs) are the main mediators of the connection between cells and the ECM. FAs induce enhanced tumor cell motility and EMT through integrin-based signaling transition and mechanical structural support. Upregulation of genes in the FA pathway is closely associated with tongue cancer progression. During malignant progression from atypical dysplasia of the oral mucosal epithelium into oral squamous cell carcinoma, focal adhesion kinase (FAK) is gradually upregulated. Thus, FAK may be used as a diagnostic marker for precancerous oral epithelial lesions (41). In FAK−/− mice, the rate of papilloma formation decreased by 50%; once benign tumors had formed, loss of FAK inhibited malignant progression (42). Blocking the FAK pathway was shown to markedly decrease cell adhesion ability and cell invasion and motility in head and neck squamous cell carcinoma (43). FAK is upregulated in most tumors, and its level is associated with the malignant behavior of the tumors. FAK levels are markedly higher in malignant metastatic tumor tissues compared with those in normal tissues or invasive tumor tissues (44). A relevant clinical trial reported that FAK expression levels are inversely correlated with the survival of patients with tumors (45). Therefore, FAK may be a potential diagnostic marker for early-stage tongue cancer, and FAK receptors may represent promising therapeutic targets. In the present study, FN1 was found to be highly expressed in tongue cancer tissues. In addition, secreted phosphoprotein 1 (SPP1; also referred to as osteopontin), is a secreted phosphorylated glycoprotein involved in cell adhesion, proliferation, migration, inflammation, immune response and signal transduction, and can induce new angiogenesis (46,47). The present study demonstrated that SPP1 was significantly upregulated in tongue cancer, suggesting that FN1 and SPP1 play important roles in the development of tongue cancer.

Collectively, the activity of the FAK, ECM-receptor, PI3K-Akt and CAM pathways varies greatly during tongue cancer occurrence and progression. The activated PI3K-Akt pathway stimulates cell proliferation, alters the cell cycle, inhibits apoptosis and induces angiogenesis. Phosphorylated glycogen synthases further downregulate E-cadherin and, thus, block the CAM pathway. Impaired CAMs result in compositional changes in the signaling molecules in the ECM, which, in turn, cause alterations in the relevant pathways. In addition, a unique microenvironment affected by component and rigidity alterations of the ECM further affect tumor cell metastasis. In summary, the progression, invasion and metastasis of malignant tumors is a dynamic process. The interaction between the PI3K-Akt pathway and CAMs was shown to trigger changes in the ECM, thus further aggravating an unfavorable microenvironment in tongue cancer.

In the present study, potential molecular mechanisms and tumor-related pathways during tongue cancer progression were analyzed through RNA-Seq. However, certain limitations should be addressed. First, the small sample size may have led to individual bias. Since transcriptome sequencing is a sensitive detection method, our sequencing data only provided referential information. Second, differentially expressed pathways were abundant, and some were significant during tongue cancer progression. The critical pathways and underlying mechanisms of tongue cancer require further investigation.

In conclusion, transcriptomes from four tongue cancer tissues and four paired paracancerous tissues were analyzed, and 1,700 upregulated and 2,249 downregulated genes were identified. These differentially expressed genes were mainly enriched in the FA, ECM-receptor interaction, PI3K-Akt and CAM pathways. These pathways synergistically promoted tongue cancer occurrence and progression, and may be potential biological markers and therapeutic targets for early-stage tongue cancer. However, due to the small sample size and sensitivity of RNA-Seq, further molecular biology research is required to elucidate the roles of differentially expressed pathways in tongue cancer progression, in order to provide a wider theoretical and experimental basis for the clinical diagnosis, treatment and prognosis of patients with tongue cancer.

Supplementary Material

Supporting Data

Acknowledgements

Not applicable.

Funding

The present study was supported by Nantong Science and Technology Projects (grant nos. MS22018011, GJZ17103, MS12018059 and MS32017004).

Availability of materials and data

All data generated or analyzed during the present study are included in this published article.

Authors' contributions

MMT and LH designed the study and drafted the manuscript. MMT, HW, WCD, XJX and BJ conducted the experiments, and contributed to data collection and analysis. YZW, HYQ and LH contributed to and reviewed the data analysis. All authors have read and approved the final version of the manuscript.

Ethics approval and consent to participate

The present study was approved by the Medical Ethics Committee of Nantong Municipal Tumor Hospital (no. 2018037).

Patient consent for publication

Not applicable.

Competing interests

All authors declare that they have no competing interests.

References

1 

Wade J, Smith H, Hankins M and Llewellyn C: Conducting oral examinations for cancer in general practice: What are the barriers? Fam Pract. 27:77–84. 2010. View Article : Google Scholar

2 

Nemeth Z, Somogyi A, Takacsi-Nagy Z, Barabas J, Nemeth G and Szabo G: Possibilities of preventing osteoradionecrosis during complex therapy of tumors of the oral cavity. Pathol Oncol Res. 6:53–58. 2000. View Article : Google Scholar

3 

Mann J, Julie D, Mahase SS, D'Angelo D, Potters L, Wernicke AG and Parashar B: Elective neck dissection, but not adjuvant radiation therapy, improves survival in stage I and II oral tongue cancer with depth of invasion >4 mm. Cureus. 11:e62882019.

4 

Warnakulasuriya S: Global epidemiology of oral and oropharyngeal cancer. Oral Oncol. 45:309–316. 2009. View Article : Google Scholar

5 

Hao SP and Tsang NM: The role of supraomohyoid neck dissection in patients of oral cavity carcinoma. Oral Οncol. 38:309–312. 2002. View Article : Google Scholar

6 

St John MA, Abemayor E and Wong DT: Recent new approaches to the treatment of head and neck cancer. Anti-cancer Drugs. 17:365–375. 2006. View Article : Google Scholar

7 

Calabrese L, Bruschini R, Giugliano G, Ostuni A, Maffini F, Massaro MA, Santoro L, Navach V, Preda L, Alterio D, et al: Compartmental tongue surgery: Long term oncologic results in the treatment of tongue cancer. Oral Oncol. 47:174–179. 2011. View Article : Google Scholar

8 

Uma RS, Naresh KN, D'Cruz AK, Mulherkar R and Borges AM: Metastasis of squamous cell carcinoma of the oral tongue is associated with down-regulation of epidermal fatty acid binding protein (E-FABP). Oral Oncol. 43:27–32. 2007. View Article : Google Scholar

9 

Sun QL, Zhao CP, Wang TY, Hao XB, Wang XY, Zhang X and Li YC: Expression profile analysis of long non-coding RNA associated with vincristine resistance in colon cancer cells by next-generation sequencing. Gene. 572:79–86. 2015. View Article : Google Scholar

10 

Iorio MV and Croce CM: Causes and consequences of microRNA dysregulation. Cancer J. 18:215–222. 2012. View Article : Google Scholar :

11 

Wang F, Ren X and Zhang X: Role of microRNA-150 in solid tumors. Oncol Lett. 10:11–16. 2015. View Article : Google Scholar :

12 

Zhang HL, Yu LX, Yang W, Tang L, Lin Y, Wu H, Zhai B, Tan YX, Shan L, Liu Q, et al: Profound impact of gut homeostasis on chemically-induced pro-tumorigenic inflammation and hepatocarcinogenesis in rats. J Hepatol. 57:803–812. 2012. View Article : Google Scholar

13 

Iyer MK, Niknafs YS, Malik R, Singhal U, Sahu A, Hosono Y, Barrette TR, Prensner JR, Evans JR, Zhao S, et al: The landscape of long noncoding RNAs in the human transcriptome. Nat Genet. 47:199–208. 2015. View Article : Google Scholar :

14 

Rucklidge GJ, Dean V, Robins SP, Mella O and Bjerkvig R: Immunolocalization of extracellular matrix proteins during brain tumor invasion in BD IX rats. Cancer Res. 49:5419–5423. 1989.

15 

Ohlund D, Elyada E and Tuveson D: Fibroblast heterogeneity in the cancer wound. J Exp Med. 211:1503–1523. 2014. View Article : Google Scholar :

16 

Schafer M and Werner S: Cancer as an overhealing wound: An old hypothesis revisited. Nat Rev Mol Cell Biol. 9:628–638. 2008. View Article : Google Scholar

17 

Bergamaschi A, Tagliabue E, Sorlie T, Naume B, Triulzi T, Orlandi R, Russnes HG, Nesland JM, Tammi R, Auvinen P, et al: Extracellular matrix signature identifies breast cancer subgroups with different clinical outcome. J Pathol. 214:357–367. 2008. View Article : Google Scholar

18 

Emery LA, Tripathi A, King C, Kavanah M, Mendez J, Stone MD, de las Morenas A, Sebastiani P and Rosenberg CL: Early dysregulation of cell adhesion and extracellular matrix pathways in breast cancer progression. Am J Pathol. 175:1292–1302. 2009. View Article : Google Scholar :

19 

Lai KK, Shang S, Lohia N, Booth GC, Masse DJ, Fausto N, Campbell JS and Beretta L: Extracellular matrix dynamics in hepatocarcinogenesis: A comparative proteomics study of PDGFC transgenic and pten null mouse models. PLoS Genet. 7:e10021472011. View Article : Google Scholar :

20 

Rasmussen BB, Pedersen BV, Thorpe SM and Rose C: Elastosis in relation to prognosis in primary breast carcinoma. Cancer Res. 45:1428–1430. 1985.

21 

Frantz C, Stewart KM and Weaver VM: The extracellular matrix at a glance. J Cell Sci. 123:4195–4200. 2010. View Article : Google Scholar :

22 

Liu Y, Carson-Walter EB, Cooper A, Winans BN, Johnson MD and Walter KA: Vascular gene expression patterns are conserved in primary and metastatic brain tumors. J NeuroOncol. 99:13–24. 2010. View Article : Google Scholar :

23 

Ameur N, Lacroix L, Roucan S, Roux V, Broutin S, Talbot M, Dupuy C, Caillou B, Schlumberger M and Bidart JM: Aggressive inherited and sporadic medullary thyroid carcinomas display similar oncogenic pathways. Endocr Relat Cancer. 16:1261–1272. 2009. View Article : Google Scholar

24 

Bianchini G, Qi Y, Alvarez RH, Iwamoto T, Coutant C, Ibrahim NK, Valero V, Cristofanilli M, Green MC, Radvanyi L, et al: Molecular anatomy of breast cancer stroma and its prognostic value in estrogen receptor-positive and -negative cancers. J Clin Oncol. 28:4316–4323. 2010. View Article : Google Scholar

25 

Lahmann C, Young AR, Wittern KP and Bergemann J: Induction of mRNA for matrix metalloproteinase 1 and tissue inhibitor of metalloproteinases 1 in human skin in vivo by solar simulated radiation. Photochem Photobiol. 73:657–663. 2001. View Article : Google Scholar

26 

Gomes JR, Omar NF, dos Santos Neves J, Narvaes EA and Novaes PD: Immunolocalization and activity of the MMP-9 and MMP-2 in odontogenic region of the rat incisor tooth after post shortening procedure. J Mol Histol. 42:153–159. 2011. View Article : Google Scholar

27 

Brummer O, Bohmer G, Hollwitz B, Flemming P, Petry KU and Kuhnle H: MMP-1 and MMP-2 in the cervix uteri in different steps of malignant transformation-an immunohistochemical study. Gynecol Oncol. 84:222–227. 2002. View Article : Google Scholar

28 

Hynes RO and Naba A: Overview of the matrisome-an inventory of extracellular matrix constituents and functions. Cold Spring Harb Perspect Biol. 4:a0049032012. View Article : Google Scholar :

29 

Fang T, Hou J, He M, Wang L, Zheng M, Wang X and Xia J: Actinidia chinensis planch root extract (acRoots) inhibits hepatocellular carcinoma progression by inhibiting EP3 expression. Cell Biol Toxicol. 32:499–511. 2016. View Article : Google Scholar

30 

Kashiwagi E, Shiota M, Yokomizo A, Itsumi M, Inokuchi J, Uchiumi T and Naito S: Prostaglandin receptor EP3 mediates growth inhibitory effect of aspirin through androgen receptor and contributes to castration resistance in prostate cancer cells. Endocr Relat Cancer. 20:431–441. 2013. View Article : Google Scholar

31 

Kawada K, Hosogi H, Sonoshita M, Sakashita H, Manabe T, Shimahara Y, Sakai Y, Takabayashi A, Oshima M and Taketo MM: Chemokine receptor CXCR3 promotes colon cancer metastasis to lymph nodes. Oncogene. 26:4679–4688. 2007. View Article : Google Scholar

32 

Zipin-Roitman A, Meshel T, Sagi-Assif O, Shalmon B, Avivi C, Pfeffer RM, Witz IP and Ben-Baruch A: CXCL10 promotes invasion-related properties in human colorectal carcinoma cells. Cancer Res. 67:3396–3405. 2007. View Article : Google Scholar

33 

Osaki M, Oshimura M and Ito H: PI3K-Akt pathway: Its functions and alterations in human cancer. Apoptosis. 9:667–676. 2004. View Article : Google Scholar

34 

Juric D, Krop I, Ramanathan RK, Wilson TR, Ware JA, Sanabria Bohorquez SM, Savage HM, Sampath D, Salphati L, Lin RS, et al: Phase I dose-escalation study of taselisib, an oral PI3K inhibitor, in patients with advanced solid tumors. Cancer Discov. 7:704–715. 2017. View Article : Google Scholar :

35 

Shultz JC, Goehe RW, Wijesinghe DS, Murudkar C, Hawkins AJ, Shay JW, Minna JD and Chalfant CE: Alternative splicing of caspase 9 is modulated by the phosphoinositide 3-kinase/Akt pathway via phosphorylation of SRp30a. Cancer Res. 70:9185–9196. 2010. View Article : Google Scholar :

36 

Jin G, Kim MJ, Jeon HS, Choi JE, Kim DS, Lee EB, Cha SI, Yoon GS, Kim CH, Jung TH and Park JY: PTEN mutations and relationship to EGFR, ERBB2, KRAS, and TP53 mutations in non-small cell lung cancers. Lung Cancer. 69:279–283. 2010. View Article : Google Scholar

37 

Yoon MK, Mitrea DM, Ou L and Kriwacki RW: Cell cycle regulation by the intrinsically disordered proteins p21 and p27. Biochem Soc Trans. 40:981–988. 2012. View Article : Google Scholar :

38 

Cheng JC and Leung PC: Type I collagen down-regulates E-cadherin expression by increasing PI3KCA in cancer cells. Cancer Lett. 304:107–116. 2011. View Article : Google Scholar

39 

Nieto MA, Huang RY, Jackson RA and Thiery JP: Emt: 2016. Cell. 166:21–45. 2016. View Article : Google Scholar

40 

Cavallaro U and Christofori G: Cell adhesion and signalling by cadherins and Ig-CAMs in cancer. Nat Rev Cancer. 4:118–132. 2004. View Article : Google Scholar

41 

Min A, Zhu C, Wang J, Peng S, Shuai C, Gao S, Tang Z and Su T: Focal adhesion kinase knockdown in carcinoma-associated fibroblasts inhibits oral squamous cell carcinoma metastasis via downregulating MCP-1/CCL2 expression. J Biochem Mol Toxicol. 29:70–76. 2015. View Article : Google Scholar

42 

McLean GW, Komiyama NH, Serrels B, Asano H, Reynolds L, Conti F, Hodivala-Dilke K, Metzger D, Chambon P, Grant SG and Frame MC: Specific deletion of focal adhesion kinase suppresses tumor formation and blocks malignant progression. Genes Dev. 18:2998–3003. 2004. View Article : Google Scholar :

43 

Canel M, Secades P, Garzon-Arango M, Allonca E, Suarez C, Serrels A, Frame M, Brunton V and Chiara MD: Involvement of focal adhesion kinase in cellular invasion of head and neck squamous cell carcinomas via regulation of MMP-2 expression. Br J Cancer. 98:1274–1284. 2008. View Article : Google Scholar :

44 

Gabriel B, zur Hausen A, Stickeler E, Dietz C, Gitsch G, Fischer DC, Bouda J, Tempfer C and Hasenburg A: Weak expression of focal adhesion kinase (pp125FAK) in patients with cervical cancer is associated with poor disease outcome. Clin Cancer Res. 12:2476–2483. 2006. View Article : Google Scholar

45 

Yuan Z, Zheng Q, Fan J, Ai KX, Chen J and Huang XY: Expression and prognostic significance of focal adhesion kinase in hepatocellular carcinoma. J Cancer Res Clin Oncol. 136:1489–1496. 2010. View Article : Google Scholar

46 

Ramaiah SK and Rittling S: Pathophysiological role of osteopontin in hepatic inflammation, toxicity, and cancer. Toxicol Sci. 103:4–13. 2008. View Article : Google Scholar

47 

Wai PY and Kuo PC: Osteopontin: Regulation in tumor metastasis. Cancer Metastasis Rev. 27:103–118. 2008. View Article : Google Scholar

Related Articles

Journal Cover

June-2020
Volume 43 Issue 6

Print ISSN: 1021-335X
Online ISSN:1791-2431

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Tang M, Dai W, Wu H, Xu X, Jiang B, Wei Y, Qian H and Han L: Transcriptome analysis of tongue cancer based on high‑throughput sequencing. Oncol Rep 43: 2004-2016, 2020
APA
Tang, M., Dai, W., Wu, H., Xu, X., Jiang, B., Wei, Y. ... Han, L. (2020). Transcriptome analysis of tongue cancer based on high‑throughput sequencing. Oncology Reports, 43, 2004-2016. https://doi.org/10.3892/or.2020.7560
MLA
Tang, M., Dai, W., Wu, H., Xu, X., Jiang, B., Wei, Y., Qian, H., Han, L."Transcriptome analysis of tongue cancer based on high‑throughput sequencing". Oncology Reports 43.6 (2020): 2004-2016.
Chicago
Tang, M., Dai, W., Wu, H., Xu, X., Jiang, B., Wei, Y., Qian, H., Han, L."Transcriptome analysis of tongue cancer based on high‑throughput sequencing". Oncology Reports 43, no. 6 (2020): 2004-2016. https://doi.org/10.3892/or.2020.7560