Novel MiRNA Markers and Their Mechanism of Esophageal Squamous Cell Carcinoma (ESCC) based on TCGA

doi:10.21203/rs.3.rs-3238969/v1

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Novel MiRNA Markers and Their Mechanism of Esophageal Squamous Cell Carcinoma (ESCC) based on TCGA

https://doi.org/10.21203/rs.3.rs-3238969/v1

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Background

MiRNAs are promising biomarkers for early ESCC detection and prognostic prediction. This study aimed to explore the potential biomarkers and molecular pathogenesis in early diagnosis of esophageal squamous cell carcinoma (ESCC).

Results

48 differentical expressed miRNAs (DEMs) and 1319 differentical expressed genes (DEGs) were identified between 94 ESCC tissues and 13 normal esophageal tissues in TCGA. Among 6558 target genes of the 48 DEMs, 400 are also in 1319 DEGs. Top GO and KEGG enrichment of these 400 DEGs includes cell cycle, proteoglycans in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and oocyte meiosis, where 66 DEGs are in these six biological pathways, called GO-DEGs. In total, 32 DEMs downregulated these 66 GO-DEGs, where 22 DEMs were verified by different types of experiments in ESCC tissues, cells or serum from literature. For the other 10 DEMs, only hsa-miR-34b-3p showed no significant correlation with the overall survival of ESCC patients by single-factor cox regression analysis. Novel nine DEMs related to ESCC were: three down-regulated (hsa-miR-215-5p, hsa-miR-194-3p, hsa-miR-29b-2-5p), and six up-regulated (hsa-miR-944, hsa-miR-205-3p, hsa-miR-4652-5p, hsa-miR-452-3p, hsa-miR-6499-3p, and hsa-miR-767-5p).

Conclusion

This study identified nine novel miRNA markers potentially related to the diagnosis of ESCC (hsa-miR-944, hsa-miR-205-3p, hsa-miR-4652-5p, hsa-miR-452-3p, hsa-miR-6499-3p, hsa-miR-767-5p, hsa-miR-215-5p, hsa-miR-194-3p, hsa-miR-29b-2-5p) and participated in the occurrence and development of ESCC through cell cycle, proteoglycans in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and signaling pathway for oocyte meiosis.

Biological sciences/Genetics/Gene expression

Biological sciences/Genetics/Gene regulation

Esophageal squamous cell carcinoma

miRNA

mRNA

Biomarkers

Esophageal cancer is one of the most common gastrointestinal malignant tumors in the world, with the incidence rate ranked eighth in the world, accounting for the sixth mortality rate of all cancers^[1], and the fourth leading cause of cancer-related deaths in China^[2]. Esophageal cancer mainly has two pathological subtypes of esophageal squamous cell carcinoma and esophageal adenocarcinoma, and esophageal squamous cell carcinoma is the main type in China, accounting for about 90% of esophageal cancer^[3], and about 90% of the pathological stage for advanced stage^[4], the prognosis is very poor, 5-year survival rate is 15–25%^[5]. Esophageal squamous cell carcinoma mainly occurs in the upper and middle esophagus, which is closely related to smoking, alcohol abuse, dietary habits, and genetic factors^[6]. At present, the specific pathogenesis of ESCC is not clear. Previous studies have shown that miRNA may participate in the occurrence, development, invasion and metastasis of ESCC. A large amount of evidence indicates that miRNAs are promising important biomarkers for early cancer detection and prognosis prediction, and also potential therapeutic targets of molecular targeted therapy^{[7, 8]}. MiRNA is a kind of endogenous non-coding small RNA with about 18–25 base sequences in length, which can regulate the expression of target genes through post-transcriptional regulation mechanism to play a role similar to that of oncogene or tumor suppressor gene, thus exerting an important influence on the prognosis of patients.^[9]. Liu et al^[10]A meta-analysis of 27 of the 11 published papers revealed that miRNA could be used as a biomarker for early detection of ESCC. Through literature review, it was found that most of the previous studies used TCGA transcriptome data to explore ESCC miRNA markers, and few searched miRNACancerMap database and PubMed to search for new ESCC miRNA markers ^[11–13]. In this study, we analyzed the miRNA-seq data and RNA-seq data of ESCC in the TCGA database together with clinical case data, in order to explore new key miRNA markers in the occurrence and development of ESCC and provide a theoretical basis for finding potential diagnostic and therapeutic targets of ESCC and exploring its molecular pathogenic mechanism.

2.1 Differentical expressed miRNAs (DEMs) and differentical expressed genes (DEGs)

By deduplication of ESCC tissue samples and normal tissue samples adjacent to cancer in the TCGA database and deletion of relapsed samples, 94 ESCC samples of miRNA-seq and 13 normal samples of RNA-seq were included in the study, and 48 DEMs (28 with up-regulated expression and 20 with down-regulated expression) were screened out through differential expression analysis. There were 1319 DEGs (845 up-regulated genes and 474 down-regulated genes). The Volcano maps and heatmaps are shown in Fig. 1.

2.2 DEMs target genes

Target genes of 48 DEMs were predicted using the miRTarBase database, and 6559 target genes were obtained, which were intersected with 1319 DEGs to obtain 400 differentially expressed genes. The Venn diagram was shown in Fig. 2A.

2.3 GO and KEGG enrichment

The enrichment result of that above 400 common differential gene GO by using R 4.2.3 show that there were 531 biological processes of common enrichment, including mitotic karyopycnosis, karyopycnosis, karyopycnosis, chromosome segregation, organelle fission, mitotic sister chromatid segregation, sister chromatid segregation, mitotic cell cycle phase change, regulation of chromosome segregation, mitotic rule, etc ., and there were 42 cell components of common enrichment, Including condensed chromosomal centromeric regions, chromosomal centromeric regions, chromosomal regions, condensed chromosomes, major axes, centromeres, mitotic spindles, centrosomes, external centromeres, kinesin complexes and the like, and 26 biological functions are jointly participated in, Including microtubule movement activity, CXCR chemokine receptor binding, DNA-binding transcriptional activator activity RNA polymerase ii specificity, DNA-binding transcriptional activator activity, microtubule binding, DNA secondary structure binding, tubulin binding, extracellular matrix structural components imparting tensile strength, cytoskeletal movement activity, catalytic activity on DNA, etc. There were six common biological pathways involved, including cell cycle, proteoglycan in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and oocyte meiosis, and 66 common differential genes were contained in the six pathways.GO and KEGG enrichment results are shown in Fig. 3.

2.4 Compared with ESCC–related genes reported from literature

According to the prediction results of DEMs target genes by the miRTarBase database, the 66 differentially expressed genes collectively correspond to 32 of the upstream DEMs, and the expression of 22 DEMs in ESCC samples has been reported in miRCancerMap and PubMed, and the expression in ESCC tissues, cell lines or serum has been verified by different experiments, as shown in Table 1. Including hsa-miR-133a-3p^[14],hsa-miR-196a-5p^[15],hsa-miR-205-5p^[16],hsa-miR-129-5p^[17],hsa-miR-196b-5p^[18],hsa-miR-30a-5p^[19],hsa-miR-30a-3p^[20],hsa-miR-148a-3p^[21],hsa-miR-149-5p^[22],hsa-miR-139-5p^[23],hsa-miR-224-5p^[24],hsa-miR-204-5p^[25],hsa-miR-455-3p^[26],hsa-miR-338-3p^[27],hsa-miR-153-5p^[28],hsa-miR-192-5p^[29],hsa-miR-1-3p^[30],hsa-miR-29c-3p^[31],hsa-miR-375^{[32, 33]},hsa-miR-338-5p^[34],hsa-miR-194-5p^[35],hsa-miR-675-3p^[36], univariate cox regression analysis showed that hsa-miR-34b-3p^[37].There was no significant correlation with the overall survival of patients with ESCC. The expressions of the other nine DEMs in ESCC have not been reported in the literature and are tentatively defined as new miRNA markers related to ESCC, including six upregulated (hsa-miR-944, hsa-miR-205-3p, hsa-miR-4652-5p, hsa-miR-452-3p, hsa-miR-6499-3p, hsa-miR-767-5p). 3 downregulated (hsa-miR-215-5p, hsa-miR-194-3p, hsa-miR-29b-2-5p).The expression of 9 newly discovered miRNA in ESCC, possible regulated target genes and pathways involved in cancer occurrence are shown in Table 2.

Table 1

ESCC-Related DEMs Reported in miRNACancerMAP and PuBMed
miRNA	Expression	Target Gene	Detection method	Sample	Reference
hsa-miR-133a-3p	↓	COL1A1	qRT-PCR	Tissues and cells	[14]
hsa-miR-196a-5p	↑	-	qPCR	Cell line	[15]
hsa-miR-205-5p	↑	-	miRNA microarrays	Cell line	[16]
hsa-miR-129-5p	↓	CCND1	qRT-PCR	Cells	[17]
hsa-miR-196b-5p	↑	PPP1R12B	qRT-PCR	Tissues and cells	[18]
hsa-miR-30a-5p	↓	FOXD1	RT-qPCR	Tissues	[19]
hsa-miR-30a-3p	↓	Wnt2	Microarray	Tissues	[20]
hsa-miR-148a-3p	↓	TUG1	qRT-PCR	Tissues and cells	[21]
hsa-miR-149-5p	↓	IL-6	RT-PCR	Cells	[22]
hsa-miR-139-5p	↓	TBX1	qRT-PCR	Tissues	[23]
hsa-miR-224-5p	↑	CPEB3	qRT-PCR	Tissues and cells	[24]
hsa-miR-204-5p	↓	Nestin	qPCR	Tissues and cell lines	[25]
hsa-miR-455-3p	↑	FAM83F	qRT-PCR	Tissues and cell lines	[26]
hsa-miR-338-3p	↓	-	RT‑qPCR	Tissues and cell lines	[27]
hsa-miR-153-5p	↓	SNAI1	qRT-PCR	Tissues	[28]
hsa-miR-192-5p	↑	-	qRT-PCR	Tissue and serum	[29]
hsa-miR-1-3p	↓	-	qPCR	Cell line	[30]
hsa-miR-29c-3p	↓	CCNA2	qRT-PCR	Tissues	[31]
hsa-miR-375	↓	PRDX1、XPR1	RT-qPCR	Tissue, cell, serum	[32][33]
hsa-miR-338-5p	↓	FERMT2	RT-PCR	Cells	[34]
hsa-miR-194-5p	↓	JMJD1C	qRT-PCR	Tissues and cells	[35]
hsa-miR-675-3p	↑	-	RT‑qPCR	Tissues	[36]

Table 2

The target genes and pathways involved in the regulation of 9 newly discovered miRNA were identified
miRNA	logFC	PValue	Up/Down	Target gene	Pathway
hsa-miR-215-5p	-4.55384815	1.68E-19	Down	KNL1,BUB1B,TRIP13,MAD2L1,CDC20,ORC1,TICRR,TTK,PLAU,FZD4,WNT3,PLCE1,PERP,PPARG,HOXA10	Cell cycle; Proteoglycans in cancer; p53 signaling pathway; Transcriptional misregulation in cancer; Oocyte meiosis
hsa-miR-194-3p	-4.52886534	2.90E-19	Down	ORC6,MMP9	Cell cycle; Proteoglycans in cancer; Transcriptional misregulation in cancer
hsa-miR-29b-2-5p	-2.34622638	3.62E-17	Down	KCNK5	Protein digestion and absorption
hsa-miR-944	7.06925469	1.12E-16	Up	BCL11B	Transcriptional misregulation in cancer
hsa-miR-205-3p	4.32605455	1.79E-16	Up	AR	Oocyte meiosis
hsa-miR-4652-5p	3.76365882	9.39E-11	Up	SFN	Cell cycle; p53 signaling pathway
hsa-miR-452-3p	3.33894914	4.83E-09	Up	ZBTB16	Transcriptional misregulation in cancer
hsa-miR-6499-3p	2.83288755	3.48E-07	Up	SGO1,CCNB1,ESCO2,KNL1,ORC6,FZD4,PPP1R12B	Cell cycle; Proteoglycans in cancer; p53 signaling pathway; Oocyte meiosis
hsa-miR-767-5p	4.55427294	0.00184551	Up	SGO1,COL3A1,COL10A1	Cell cycle; Protein digestion andabsorption; Oocyte meiosis

2.5 miRNA-mRNA regulatory network

The target genes possibly regulated by the six up-regulated miRNA are as follows, hsa-miR-944(BCL11B), hsa-miR-205-3p (AR),hsa-miR-4652-5p (SFN),hsa-miR-452-3p (ZBTB16),hsa-miR-6499-3p (GO1,CCNB1,ESCO2,KNL1,ORC6,FZD4,PPP1R12B), Hsa-miR-767-5p(SGO1, COL3A1, COL10A1), and the target genes that may be regulated by three down-regulating miRNA are as follows,hsa-miR-215-5p (KNL1, BUB1B, TRIP13, MAD2L1, CDC20, ORC1, TICRR, TTK, PLAU, FZD4, WNT3, PLCE1, PERP, PPARG, HOXA10), hsa-miR-194-3p (ORC6, MMP9), hsa-miR-29b-2-5p(KCNK5). The prepared regulatory network diagram of miRNA-mRNA is shown in Fig. 4.

3.1 data download and preprocessing

The relevant ESCC data were downloaded from the TCGA database website (https://portal.gdc.cancer.gov/), including: (1) Gene expression profile data: RNA-seq was downloaded, and it could be divided into mRNA, lncRNA gene and other types according to gene type. The database included 108 samples, including 95 tumor samples and 13 normal samples. (2)miRNA expression profile data: miRNA-seq is downloaded, and the name of miRNA adopts the naming method of a miRNA base (V21) database. There were a total of 109 samples in the database, including 96 tumor samples and 13 normal samples. (3) Clinical data of cases in RNA-Seq and miRNA-seq data, mainly including information on prognosis, survival state and survival time. The data was downloaded on 11 May 2023. The TCGA database is public and therefore does not require approval by the Ethics Committee.

3.2 Differential expression analysis

The raw data of miRNAs and RNAs were normalized using the "GDCRNATools" package in R language 4.2.2, and > 50% of the specimens expressing miRNAs or RNAs with a value of 0 were deleted. Then, the "limma" package was used to screen the differentially expressed miRNAs and RNAs between the tumor and adjacent normal tissues at the screening threshold of P < 0.05 and logFC > 2 (logFC > 0 indicates up-regulated differentially expressed genes, and logFC < 0 indicates down-regulated differentially expressed genes). MiRNAs or RNAs that meet the above conditions are defined as differentially expressed miRNAs (DEMs) or differentially expressed RNAs (DEGs). The "gdcVolcanoPlot" package was used to draw the volcanic map, while the "gdcHeatmap" package was used to draw the thermal map, thus visualizing the extent of difference between DEMs and DEGs, respectively. The design flow chart of this study is shown in Fig. 5.

3.3 Prediction of differentially expressed miRNA target genes

The miRTarBase (https://mirtarbase.cuhk.edu.cn) database is a database dedicated to collecting experimental evidence supporting miRNA-mRNA targeting (MTI, microRNA-target interactions). The target genes of the differentially expressed miRNAs obtained above were predicted using the miRTarBase database. The "ggplot2" package and "VennDiagram" were used to analyze the intersection part of the target gene of DEMs and DEGs, to obtain common differentially expressed genes, and the results were visualized.

3.4 GO and KEGG analysis

The "org.Hs.eg.db" package, "clusterProfiler" package, "ggplot2" package and "msigdbr" package of R language 4.2.3 were used for GO functional annotation and KEGG pathway enrichment analysis of jointly differentially expressed genes. When the threshold condition was set, a difference of P < 0.05 showed statistical significance. Among them, the functional annotation of GO included biological process (BP), cell component (CC) and molecular function (MF).

3.5 Comparison to disease database and PubMed

Based on the prediction results of DEMs target genes by the miRTarBase database, the upstream DEMs corresponding to genes in the KEGG enrichment pathway could be obtained. miRNACancerMAP (cis.hku.hk/miRNACancerMAP) is an online tool for studying the miRNA regulatory network of cancer. Through the database, we can retrieve the miRNA expression, related pathways, disease prognosis, and regulatory target genes in various cancers reported in PubMed. According to the retrieval results of DEMs in PubMed, the expression of DEMs in ESCC has not been reported in the literature, and no experiment has been conducted to verify DEMs, which are defined as new miRNA markers related to ESCC.

3.6 Construction of miRNA-mRNA regulatory network

The cytoscape3.7.2 software was used to map the miRNA-mRNA regulatory network of new ESCC-related miRNAs and their regulated co-differentially expressed genes contained in the KEGG enrichment pathway.

ESCC is a major subtype of esophageal cancer in Asia, and its early symptoms are hidden. About 90% of patients have reached the advanced stage of the disease when they are diagnosed, and the prognosis is extremely poor. The five-year survival rate is 15–25%. At present, the pathogenic mechanism of ESCC is still unclear, and the early detection and treatment effect are still unsatisfactory. Surgery, chemoradiotherapy are still the main treatment methods, and targeted drug therapy and immunotherapy are recommended as the second-line treatment. More and more studies have shown that miRNA is an important molecular marker for early diagnosis and prognosis prediction of cancer, and is expected to become a key molecule for molecular targeted therapy.

In this study, we obtained 48 DEMSs, 1319 DEGs, and 400 co-differentially expressed genes by jointly analyzing the ESCC RNA-seq and miRNA-seq data in the TCGA database. There were 32 out of 66 common differential genes DEMs participating in the regulation of ESCC-related pathways, and the expression of 23 DEMs in ESCC tissues, cells or serum has been reported in the literature. The expression of the other nine DEMSs (HSA-miR-944, hsa-miR-205-3p, hsa-miR-4652-5p, hsa-miR-452-3p, hsa-miR-6499-3p, hsa-miR-767-5p, hsa-miR-215-5p, hsa-miR-194-3p, and hsa-miR-29b-2-5p) in the ESCC has not been reported.

Previous studies have found that hsa-miR-944 is abnormally expressed in more than 10 cancers, including esophageal adenocarcinoma, gastric cancer, colorectal cancer, breast cancer, oral cancer, lung cancer, cervical cancer, nasopharyngeal cancer, and liver cancer^[38], which plays an important role in the process of tumor proliferation, invasion, migration, epithelial-mesenchymal transition, apoptosis, drug resistance, and provides an important clinical application value for the diagnosis, treatment and prognosis judgment of cancer. Low Expression of miR-944-5p in Tissue and Serum Samples from Patients with Esophageal Adenocarcinoma^[39].However, its expression in ESCC has not been reported yet. The expression of miR-205-3p is up-regulated in non-small cell lung cancer tissues and cell lines, and the progression of the non-small cell lung cancer is promoted by regulating the expression of a target gene APBB2^[40],and is significantly associated with poor prognosis in breast cancer patients^[41]. miR-205-3p play a role in inhibiting canc in ovarian cancer and gastric cancer^{[42, 43]}. MiR-4652-5p regulates cell adhesion by down-regulating RND1 expression and promotes the progression of lung squamous cell carcinoma^[44], has the potential to be one of the key molecular diagnostic biomarkers for laryngeal squamous cell carcinoma and head and neck squamous cell carcinoma^{[45, 46]}. MiR-452-3p is significantly up-regulated in liver cancer tissues and cells and promotes the proliferation and migration of liver cancer cells by targeting CPEB3^[47]. Long-chain noncoding RNA ZFAS1 promotes the development of oral squamous cell carcinoma by regulating the miR-6499-3p/CCL5 axis^[48]. As an oncogene, miR-767-5p promotes the progression of hepatocellular carcinoma by regulating the expression of downstream target gene PMP22^[49], and the weighted gene co-expression network analysis shows that the miR-767-5p is significantly related to the prognosis of patients with liver cancer^[50]. As one of the prognostic model molecules composed of 10 miRNAs, miR-767-5p can accurately predict tumor recurrence in patients with hepatocellular carcinoma after sexual surgery^[51]. MiR-215-5p is reported as a tumor suppressor gene in a variety of human cancers, for example, by targeting RUNX1 to inhibit the proliferation of tumor cells in multiple myeloma^[52], which can inhibit the proliferation and migration of tumor cells by regulating the expression of CRK in nephroblastoma^[53], while inhibiting the progression of cancer in colorectal cancer by regulating the expression of target genes epiregulin and HOXB9^[54], inhibiting tumor progression through the MDM2 -p53 signaling axis in malignant pleural mesothelioma^[55], inhibiting the invasion of cancer cells by down-regulating the expression of the target gene Sox9 in breast cancer^[56], down-regulates the expression of RAD54B and promotes the apoptosis of cancer cells^[57]. The molecular tag consist of miR-215-5p, miR-190b-5p and miR-527 can be used as a serum biomarker of prostate canc^[58]. MiR-194-3p inhibits proliferation, migration, invasion, and docetaxel resistance of colorectal cancer cells via KLK10^{[59, 60]}, and high expression of miR-194-3p is associated with early t-staging of cancer^[61]. MiR-29b-2-5p inhibits the proliferation of pancreatic ductal adenocarcinoma cells by directly targeting Cbl-b^[62], miR-29b-2-5p, as one of the most significant hinge genes of digestive system cancers including esophageal cancer, may be related to cancer prognosis^[63].

In summary, the nine ESCC-related novel miRNA exert various degrees of cancer inhibition or carcinogenic effects in various cancers. It may participate in the occurrence and development of ESCC through cell cycle, proteoglycans in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and signaling pathway of oocyte meiosis. These results require further validation in clinical samples.

This study identified nine novel miRNA markers that might be relevant for the diagnosis and treatment of ESCC (hsa-miR-944, hsa-miR-205-3p, hsa-miR-4652-5p, hsa-miR-452-3p, hsa-miR-6499-3p, hsa-miR-767-5p, hsa-miR-215-5p, hsa-miR-194-3p, Hsa-miR-29b-2-5p) and participates in the occurrence and development of ESCC through cell cycle, proteoglycans in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and signaling pathway of oocyte meiosis.

ESCC Esophageal Squamous Cell Carcinoma

DEMs Differential Expression of miRNAs

DEGs Differentially Expressed RNAs

BP Biological Process

CC Cell Component

MF Molecular Function

Ethical approval and consent to participate

Not applicableto this study.

Consent for publication

Not applicable.

Availability of data and materials

The data (ESCC) used in this research were obtained from The Cancer Genome Atlas(TCGA, https://portal.GDC.cancer. gov/).This study complies with its data use and publication rules.

Competing interests

The authors declare that they have no competing interests.

Funding

This work was supported by Grants from the Natural Science Foundation project of Hubei Province(2021CFB158), Education Research Project of Hubei Province (No.D20222106) and National Natural Science Foudation of China (No.32060150).

Author's contribution

P Y and W L participated in the conception and design of the study. P Y collected data, did statistical analysis and created the table and fgures. P Y wrote the frst draft of the manuscript.W L,X G, J S,Z X,H X,R Y, L Z, J G and X Lparticipated in the revision of the manuscript. All authors read and agreed to the fnal manuscript and authorship arrangement. All authors read and approved the fnal manuscript.

Acknowledgement

Not applicable.

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No competing interests reported.

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Editorial decision: Major revision
15 Sep, 2023
Editor assigned by journal
13 Sep, 2023
Editor invited by journal
08 Aug, 2023
Submission checks completed at journal
08 Aug, 2023
First submitted to journal
06 Aug, 2023

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Novel MiRNA Markers and Their Mechanism of Esophageal Squamous Cell Carcinoma (ESCC) based on TCGA

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Version 1

Abstract

Background

Results

Conclusion

Figures

1 Introduction

2 Results

2.1 Differentical expressed miRNAs (DEMs) and differentical expressed genes (DEGs)

2.2 DEMs target genes

2.3 GO and KEGG enrichment

2.4 Compared with ESCC–related genes reported from literature

2.5 miRNA-mRNA regulatory network

3 Materials and methods

3.1 data download and preprocessing

3.2 Differential expression analysis

3.3 Prediction of differentially expressed miRNA target genes

3.4 GO and KEGG analysis

3.5 Comparison to disease database and PubMed

3.6 Construction of miRNA-mRNA regulatory network

4 Discussion

5 Conclusion

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1