Abstract

   MicroRNAs(miRNAs) are promising biomarkers for early esophageal
   squamous cell carcinoma (ESCC) detection and prognostic prediction.
   This study aimed to explore the potential biomarkers and molecular
   pathogenesis in the early diagnosis of ESCC. Firstly, 48 differentially
   expressed miRNAs (DEMs) and 1319 differentially expressed genes (DEGs)
   were identified between 94 ESCC tissues and 13 normal esophageal
   tissues in TCGA. From miRNA–mRNA regulatory network, there are 6558
   target genes of the 48 DEMs, where 400 target genes are also among 1319
   DEGs. Then, gene ontology (GO) and Kyoto Encyclopedia of Genes and
   Genomes (KEGG) pathway enrichment indicate that the 400 DEGs
   significantly enriched in cell cycle, proteoglycans in cancer, p53
   signaling pathway, protein digestion and absorption, transcriptional
   dysregulation in cancer, and oocyte meiosis. And there are 66 DEGs
   among these six biological pathways, which we called GO-DEGs. From
   miRNA–mRNA regulatory network, 32 DEMs regulated the 66 GO-DEGs, where
   22 DEMs were verified by different types of experiments in ESCC
   tissues, cells, or serum from the literature. For the other novel 10
   DEMs, single-factor Cox regression analysis show that only
   hsa-miR-34b-3p showed no significant correlation with the overall
   survival of ESCC patients. Finally, we obtained the novel 9
   ESCC-related DEMs, where three are down-regulated, and six are
   up-regulated. We analyzed the expression trends of target genes for
   five miRNAs and identified three significantly different miRNAs
   (hsa-miR-205-3p, hsa-miR-452-3p, and hsa-miR-6499-3p) confirmed by
   qPCR. Moreover, the stage-specific miRNAs were also suggested. These
   three qPCR validated miRNAs are also specific to the early stages of
   ESCC: hsa-miR-452-3p is specific to Stage I, II and III; hsa-miR-205-3p
   is specific in Stage II and III; and hsa-miR-6499-3p is Stage II
   specific. They might be the potential biomarkers for ESCC stage
   diagnosis. This study identified three novel miRNA markers potentially
   related to the diagnosis of ESCC 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.

Supplementary Information

   The online version contains supplementary material available at
   10.1038/s41598-024-76321-0.

   Keywords: Esophageal squamous cell carcinoma, miRNA, mRNA, Biomarkers

   Subject terms: Gene expression, Gene regulation, Cancer genomics,
   Tumour biomarkers

Introduction

   Esophageal cancer is one of the most common gastrointestinal malignant
   tumors, the eighth incidence rate, the sixth mortality rate of all
   cancers in the world^[46]1, and the fourth leading cause of
   cancer-related deaths in China^[47]2. Esophageal cancer mainly has two
   pathological subtypes: esophageal adenocarcinoma and esophageal
   squamous cell carcinoma (ESCC). And in China, about 90% of esophageal
   cancer are ESCC^[48]3, and most ESCC pathological stage, around 90%
   were at the severe stage^[49]4. The prognosis of ESCC in China is very
   poor, and 5-year survival rate is only 15–25%^[50]5. The location of
   ESCC were mainly in the upper and middle esophagus. The cause factors
   include smoking, alcohol abuse, dietary habits, and genetic
   factors^[51]6. However, the specific pathogenesis of ESCC remains
   unclear.

   Studies have identified several miRNAs upregulated in ESCC patients,
   including miR-10a, miR-18a, miR-19b, miR-21, miR-22, miR-25, miR-31,
   miR-93, miR-129, miR-1246, miR-1322, miR-451, and miR-365. Conversely,
   miR-155, miR-203, miR-205, miR-375, miR-377, miR-486, and miR-718 are
   downregulated in these patients^[52]7. Recent findings indicate miRNA
   profiles are crucial for ESCC prognosis. High levels of plasma miR-21
   and miR-16 correlate with poor survival, and low miR-375 levels predict
   an especially poor outcome^[53]8. A six-miRNA signature outperforms
   traditional tumour, node and metastasis (TNM) staging in accuracy,
   while miR-129, miR-103, and miR-107 also relate to worse survival
   rates^[54]9. Conversely, miR-377 and miR-15a levels are inversely
   related to survival, suggesting their potential as new prognostic
   markers, along with the rising importance of miR-367 serum levels.
   These results highlight the significant role of miRNA dysregulation in
   diagnosis and treatment of ESCC^[55]10.

   Previous studies show that miRNA may participate in the occurrence,
   development, invasion, and metastasis of ESCC, thus, miRNAs are
   promising diagnosis and prognosis biomarkers of ESCC^[56]11,[57]12.
   MiRNA is small non-coding RNA regulating gene expression through
   post-transcriptional regulation, and roles similarly as oncogene or
   tumor suppressor gene^[58]13. A meta-analysis^[59]14 of 11 studies
   revealed that miRNA could be used as a biomarker for early detection of
   ESCC. Most previous studies on ESCC miRNA markers used The Cancer
   Genome Atlas (TCGA) database, while few searched miRNACancerMap
   database and PubMed^[60]15–[61]17.

   In this study, we used the transcriptomic data of both miRNA and mRNA,
   clinical survival information of ESCC from TCGA to explore novel key
   miRNA markers participating in progression of ESCC, as well as their
   molecular pathogenic mechanism in ESCC.

Results

Differentially expressed miRNAs (DEM) and genes (DEG) between ESCC and normal

   In total, 94 ESCC and 13 normal samples with both miRNA and mRNA
   transcriptome data from TCGA were included in the study. Compared to
   the normal esophageal tissue samples, 1319 differentially expressed
   genes (DEGs) with FDR < 0.05 and 4-FoldChange were obtained, as shown
   in the volcano plot of Fig. [62]1A, where 845 were upregulated and 474
   were downregulated in ESCC samples. And 48 differentially expressed
   miRNAs (DEMs) with FDR < 0.05 and 4-FoldChange were identified as shown
   in the volcano plot of Fig. [63]1B, where 28 were upregulated and 20
   were downregulated in ESCC samples. The heatmaps of these 1319 DEGs and
   48 DEMs are shown in Fig. [64]1C and D, respectively.

Fig. 1.

   [65]Fig. 1
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   DEMs and DEGs between ESCC and normal samples. A Volcano plot of 1319
   DEGs with FDR < 0.05 and 4-FoldChange; B Volcano plot of DEMs with
   FDR < 0.05 and 4-FoldChange; C Heatmap of 1319 DEGs; D Heatmap of 48
   DEMs.

The target genes of 48 DEMs

   There are 6,559 target genes of 48 DEMs according to miRTarBase
   database
   ([67]https://mirtarbase.cuhk.edu.cn/~miRTarBase/miRTarBase_2022/php/ind
   ex.php).

   The comparison of these 6559 target genes with 1319 DEGs was shown in
   Fig. [68]2, where Venn diagram in Fig. [69]2A shows that 400 DEGs are
   also the target genes regulated by the 48 DEMs, i.e., DEM regulated
   DEGs. The heatmap of 400 DEM-regulated DEGs in Fig. [70]2B shows that
   they well separate the ESCC and normal samples.

Fig. 2.

   [71]Fig. 2
   [72]Open in a new tab

   Common genes between 1319 DEGs and 6,559 target genes of 48 DEMs.
   A Venn diagram of 1319 DEGs and the 6559 target genes of 48 DEMs, where
   the 400 common genes are DEM regulated DEGs; B Heatmap of the 400 DEM
   regulated DEGs.

GO and KEGG enrichment

   Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG)
   enrichment analysis of 1319 DEGs, 6559 target genes of the 48 DEMs, and
   400 DEM-regulated DEGs were shown in Fig. [73]3.

Fig. 3.

   [74]Fig. 3
   [75]Open in a new tab

   GO and KEGG enrichment of DEGs and DEMs. A Dot plot of top GO terms
   enriched from 6559 target gene of 48 DEMs; B Dot plot of top GO terms
   enriched from 1319 DEGs; C Dot plot of top GO terms enriched from 400
   DEM-regulated DEGs; D Dot plot of top KEGG pathways enriched from 6559
   target gene of 48 DEMs; E Dot plot of top KEGG pathways enriched from
   1319 DEGs; F Dot plot of top KEGG pathways enriched from 400
   DEM-regulated DEGs; G The occurrence heatmap shows that only 66
   DEM-regulated DEGs participate in the top six KEGG pathways.

   From GO enrichment of 6559 DEMs target genes in Fig. [76]3A, the top
   enriched biological processes include cell growth, mitotic cell cycle
   phase transition, gland development, regulation of apoptotic signaling
   pathway, and regulation of binding; the top cell components include
   cell-substrate junction, focal adhesion, spindle, chromosomal region,
   and cell leading edge; and the top molecular function include
   DNA-binding transcription factor binding, DNA-binding transcription
   activator activity, RNA polymerase II-specific, RNA polymerase
   II-specific DNA-binding transcription factor binding cadherin binding.

   From GO enrichment of 1319 DEGs in Fig. [77]3B, the top enriched
   biological processes include epidermis development, organelle fission,
   nuclear division, skin development, and mitotic nuclear division. The
   top enriched cell components include the collagen-containing
   extracellular matrix, chromosome, chromosomal region, and basal part of
   the cell. The top enriched molecular functions include
   glycosaminoglycan binding, DNA-binding transcription activator
   activity, RNA polymerase II-specific, glycosaminoglycan binding,
   extracellular matrix structural constituent, and heparin binding.

   From GO enrichment of 400 DEM-regulated DEGs in Fig. [78]3C, the top
   enriched biological processes include organelle fission, nuclear
   division, chromosome segregation, mitotic nuclear division, nuclear
   chromosome segregation, mitotic cell cycle phase transition, sister
   chromatid segregation, mitotic sister chromatid segregation,
   microtubule cytoskeleton organization involved in mitosis, and
   regulation of chromosome segregation; the top cell components include
   the spindle, chromosomal region, condensed chromosome, chromosome
   centromeric region, condensed chromosome centromeric region,
   kinetochore, mitotic spindle, midbody, kinesin complex, and outer
   kinetochore; and the top molecular functions include DNA-binding
   transcription activator activity RNA polymerase II-specific,
   DNA-binding transcription activator activity, tubulin binding,
   microtubule binding, catalytic activity acting on DNA, microtubule
   motor activity, cytoskeletal motor activity, DNA secondary structure
   binding, extracellular matrix structural constituent conferring tensile
   strength, and single-stranded DNA helicase activity.

   From KEGG enrichment of 6559 DEMs target genes in Fig. [79]3D, the top
   enriched KEGG pathways include Human papillomavirus infection,
   Proteoglycans in cancer, Cellular senescence, and Cell cycle.

   From KEGG enrichment of 1319 DEGs in Fig. [80]3E, the top enriched KEGG
   pathways include Cell Cycle, Oocyte meiosis, Hippo signaling pathway,
   Melanogenesis, IL-17 signaling pathway, and p53 signaling pathway.

   Furthermore, KEGG enrichment of 400 DEM-regulated DEGs in Fig. [81]3F
   shows that the top enriched KEGG pathways include cell cycle,
   proteoglycan in cancer, p53 signaling pathway, protein digestion and
   absorption, transcriptional dysregulation in cancer, and oocyte
   meiosis.

   Both GO and KEGG enrichment indicates that these six pathways were the
   main mechanisms of both DEM target genes and regulated DEGs, which
   related to ESCC. We thus filtered the DEM-regulated DEGs in these six
   ESCC-related pathways, and there are 66 DEM-regulated DEGs among them
   as shown in their occurrence heatmap of Fig. [82]3G.

   The heatmaps of these 66 DEM-regulated DEGs in the six ESCC-related
   pathways are shown in Fig. [83]4A–F, respectively. They show that these
   66 DEMs regulated DEGs well separate ESCC and normal samples. We thus
   looked for the DEMs regulating these 66 DEGs. From the miRNA–mRNA
   regulatory network in miRTarBase database, there are 32 DEMs in total
   regulating these 66 DEGs, called as ESCC-related DEMs.

Fig. 4.

   [84]Fig. 4
   [85]Open in a new tab

   The heatmaps of the DEM-regulated DEGs in six ESCC-related pathways.
   A Heatmap of DEM-regulated DEGs in cell cycle pathway; B Heatmap of
   DEM-regulated DEGs in proteoglycans in cancer pathway; C Heatmap of
   DEM-regulated DEGs in p53 signaling pathway; D Heatmap of DEM-regulated
   DEGs in protein digestion and absorption pathway; E Heatmap of
   DEM-regulated DEGs in transcriptional misregulation in cancer pathway;
   F Heatmap of DEM-regulated DEGs in oocyte meiosis pathway.

Comparison with ESCC-related DEMs reported in the literature

   Among the 32 ESCC-related DEMs identified from our analysis in “[86]GO
   and KEGG enrichment” section, 22 DEMs (hsa-miR-133a-3p,
   hsa-miR-196a-5p, hsa-miR-205-5p, hsa-miR-129-5p, hsa-miR-196b-5p,
   hsa-miR-30a-5p, hsa-miR-30a-3p, hsa-miR-148a-3p, hsa-miR-149-5p,
   hsa-miR-139-5p, hsa-miR-224-5p, hsa-miR-204-5p, hsa-miR-455-3p,
   hsa-miR-338-3p, hsa-miR-153-5p, hsa-miR-192-5p, hsa-miR-1-3p,
   hsa-miR-29c-3p, hsa-miR-375, hsa-miR-338-5p, hsa-miR-194-5p,
   hsa-miR-675-3p) were previously reported in miRCancerMap and PubMed, as
   verified by different experiments in ESCC tissues, cell lines, or
   serum, as shown in Table [87]1.

Table 1.

   ESCC-related DEMs reported in miRNACancerMAP and PuBMed.
   miRNA Expression Target gene Detection method Sample References