DOI: 10.5061/dryad.d7wm37qd2
title: Esculetin inhibited PI3K/Akt/mTOR pathway and enhances anti-colorectal cancer activity via binding to ENO1

description: Colorectal cancer (CRC) is the third most common malignant tumor globally
 and the second leading cause of cancer-related deaths. Currently, although
 the standard treatment for CRC is a combination of surgery and
 chemotherapy, metastasis and recurrence are often associated with a poor
 prognosis. In our preliminary research, we found that Esc has anti-colon
 cancer effects both in vivo and in vitro. However, its specific target
 sites and molecular mechanisms still lack in-depth exploration and remain
 unclear. Therefore, we employed transcriptomics technology to analyze the
 complex interactions between the drug and its targets, thereby conducting
 a comprehensive evaluation. To elucidate the molecular mechanisms
 underlying the anti-tumor properties of Esc in colorectal cancer, we
 performed RNA sequencing for whole-genome expression analysis on HCT116
 cell samples treated with Esc. Through enrichment analysis of
 differentially expressed genes, we revealed that Esc is likely to
 intervene in the development of colorectal cancer by regulating these
 signaling pathway processes. This finding provides a more solid evidence
 base for the development of new anti-tumor drugs with enhanced efficacy
 and reduced toxicity.
description: # Esculetin inhibited PI3K/Akt/mTOR pathway and enhances anti-colorectal
 cancer activity via binding to ENO1 Dataset DOI: [10.5061/dryad.d7wm37qd2
 ](10.5061/dryad.d7wm37qd2) ## Description of the data and file structure
 Illumina, Library preparation, PubChem, Transcriptome Sequencing data ####
 Files and variables **File: Data_4B.xlsx** Description: Differential gene
 expression heatmap This table presents the similarities and differences in
 gene expression patterns between the Esc and Ctrl groups. The data are
 standardized using Z-score normalization, where positive Z-scores
 (indicated in red) represent high expression levels, and negative Z-scores
 (indicated in blue) represent low expression levels. **File:
 Data_4A.xlsx** Description: Principal Component Analysis (PCA) Data among
 Samples This table describes the similarity among samples in the Esc and
 Ctrl groups. **Variables** geneID: A unique identifier assigned to a gene
 in the database. gene_name: The commonly used symbol for the gene. Ctrl-1,
 Ctrl-2, trl-3_fpkm: The FPKM expression levels of genes in each sample of
 the three Ctrl groups. FPKM (Fragments Per Kilobase of transcript per
 Million fragments mapped) is used as an indicator to measure the
 expression levels of transcripts or genes. Esc-1, Esc-2, Esc-3_fpkm: The
 FPKM expression levels of genes in each sample of the three Esc groups.
 Ctrl-1, Ctrl-2, Ctrl-3_count: The raw read counts of genes in the samples
 of the three Ctrl groups. Esc-1, Esc-2, Esc-3_count: The raw read counts
 of genes in the samples of the three Esc groups. chr: The chromosome
 number where the gene is located. start: The start coordinate of the gene.
 end: The end coordinate of the gene. strand: Information indicating
 whether the sequence is on the positive or negative strand. gene_biotype:
 The biological type of the gene. gene_description: A brief description of
 the gene's function, typically including known functions of the gene,
 biological processes it is involved in, and associated diseases. The data
 in this table indicate that the samples within the Ctrl and Esc groups
 show high similarity and good reproducibility, which is suitable for the
 analysis of differentially expressed genes between the groups. **File:
 Data_4D.xlsx** Description: Enrichment Analysis of Differentially
 Expressed Genes in Disease Ontology Disease Ontology (DO) is a database
 that describes the relationships between human gene functions and
 diseases. This table presents the results of mapping differentially
 expressed genes to disease entries in DO and assessing the significance of
 these genes in specific disease categories, thereby revealing potential
 biological significance and disease associations. **Variables** ID:
 Disease ID, from the Disease Ontology (DO) database, used to uniquely
 identify diseases. Description: Disease name. DiffRatio: Proportion of
 differentially expressed genes, for example: 114/1781 (6.4%). This value
 indicates that among the differentially expressed genes, 114 genes are
 associated with a specific disease, accounting for 6.4% of all
 differentially expressed genes. BgRatio: Proportion of background genes,
 for example: 441/10312 (4.28%). This value indicates that within the
 entire genomic background, 441 genes are associated with a specific
 disease, accounting for 4.28% of all genes. P-value: Indicates the
 significance of enrichment of the disease among differentially expressed
 genes. Adjusted P-value: Corrected p-value used to control the false
 discovery rate in multiple hypothesis testing. All_index: List of Ensembl
 IDs for all associated genes, including both upregulated and downregulated
 genes. All_GeneName: List of names for all associated genes. Count_all:
 Total number of all associated genes. Up_index: List of Ensembl IDs for
 upregulated genes. Up_GeneName: List of names for upregulated genes.
 Count_up: Number of upregulated genes. Down_index: List of Ensembl IDs for
 downregulated genes. Down_GeneName: List of names for downregulated genes.
 Count_down: Number of downregulated genes. **File: Data_4E.xlsx**
 Description: Reactome Enrichment Analysis of Differentially Expressed
 Genes Reactome enrichment analysis is a statistical method used to
 evaluate the enrichment of differentially expressed genes in specific
 signaling pathways. The data in this table are intended to identify the
 key signaling pathways involved in differentially expressed genes, thereby
 providing important clues for subsequent mechanistic studies.
 **Variables** ID: Pathway ID, indicating a specific pathway in the
 Reactome database (e.g., R-HSA-190840). Description: Description of
 various cellular biological processes. DiffRatio: Proportion of
 differentially expressed genes. For example, 114/1781 (6.4%) indicates
 that among the differentially expressed genes, 114 genes belong to this
 pathway, accounting for 6.4% of all differentially expressed genes.
 BgRatio: Proportion of background genes. For example, 18/10899 (0.17%)
 indicates that within the entire genomic background, 18 genes belong to
 this pathway, accounting for 0.17% of all genes. P-value: Indicates the
 significance of enrichment of this pathway among differentially expressed
 genes. Adjusted P-value: Corrected p-value used to control the false
 discovery rate in multiple hypothesis testing. All_index: List of Ensembl
 IDs for all associated genes, including both upregulated and downregulated
 genes. All_GeneName: List of names for all associated genes. Count_all:
 Total number of all associated genes. Up_index: List of Ensembl IDs for
 upregulated genes. Up_GeneName: List of names for upregulated genes.
 Count_up: Number of upregulated genes. Down_index: List of Ensembl IDs for
 downregulated genes. Down_GeneName: List of names for downregulated genes.
 Count_down: Number of downregulated genes. **File: Data_4C.xlsx**
 Description: Volcano plot showing differential genes This table is used to
 compare the significance levels of differentially expressed genes between
 the Esc and Ctrl groups. **Variables** Ctrl-1, Ctrl-2, Ctrl-3_fpkm: The
 FPKM expression levels of genes in each sample of the three Ctrl groups.
 Esc-1, Esc-2, Esc-3_fpkm: The FPKM expression levels of genes in each
 sample of the three Esc groups. Ctrl-1, Ctrl-2, Ctrl-3_count: The raw read
 counts of genes in the samples of the three Ctrl groups. Esc-1, Esc-2,
 Esc-3_count: The raw read counts of genes in the samples of the three Esc
 groups. log2FoldChange: The log2-transformed fold change value of gene
 expression, indicating the expression change ratio of the Esc group
 relative to the Ctrl group. pvalue: The significance p-value for
 differential expression, used to determine whether there is a
 statistically significant difference in gene expression between the two
 groups. padj: The adjusted p-value, used to control the false discovery
 rate. regulated: Indicates whether the gene is up-regulated or
 down-regulated, typically determined based on the sign of log2FoldChange.
 chr: The chromosome number where the gene is located. start: The start
 position of the gene on the chromosome. end: The end position of the gene
 on the chromosome. strand: The orientation of the gene on the DNA strand,
 typically indicated as “+” (positive strand) or “–” (negative strand).
 gene_biotype: The biological type of the gene. gene_description: A brief
 description of the gene's function KEGG: The identifier of the gene
 in the KEGG database, used for linking to metabolic pathways and other
 related information. KEGG_pathway: The name of the KEGG pathway in which
 the gene is involved. GO: Gene Ontology (GO) annotations, including
 Molecular Function (MF), Biological Process (BP), and Cellular Component
 (CC). TF_Family: If the gene is a transcription factor (TF), this field
 indicates the transcription factor family to which it belongs. All missing
 data or data not available is represented as NA. ## Code/software
 Microsoft excel can be used to view these files. ## Access information
 Other publicly accessible locations of the data: * NA Data was derived
 from the following sources: * NA