Bioinformatic analysis reveals an exosomal miRNA-mRNA network in colorectal cancer

Abstract Background Exosomes play important roles in angiogenesis, drug resistance, and metastasis of colorectal cancer (CRC), but the underlying mechanism has seldom been reported. Herein, our study aimed to reveal an exosomal miRNA-mRNA network involved in CRC by performing bioinformatical analysis. Methods The mRNA and miRNA data of colon adenocarcinoma and rectal adenocarcinoma were downloaded from The Cancer Genome Atlas (TCGA) database, and exosomal miRNAs data were downloaded from the GEO dataset GSE39833. The differential expression analysis was performed using “limma” and “edgeR”. Target mRNAs of miRNAs were predicted using FunRich 3.1.3, miRNAtap and multiMiR. The candidate mRNAs and exosomal miRNAs were obtained by intersecting two groups of differentially expressed miRNAs and intersection of the differential expressed mRNAs and the target mRNAs, respectively. Key mRNAs and exosomal miRNAs were identified by the least absolute shrinkage and selection operator regression analysis, and used to construct the exosomal miRNA-mRNA network. The network verified was by receiver operating characteristic curve, GEPIA and LinkedOmics. Functional enrichment analysis was also performed for studied miRNAs and mRNAs. Results A total of 6568 differentially expressed mRNAs and 531 differentially expressed miRNAs from TCGA data, and 166 differentially expressed exosomal miRNAs in GSE39833 dataset were identified. Next, 16 key mRNAs and five key exosomal miRNAs were identified from the 5284 candidate mRNAs and 61 candidate exosomal miRNAs, respectively. The exosomal miRNA-mRNA network with high connectivity contained 13 hub mRNAs (CBFB, CDH3, ETV4, FOXQ1, FUT1, GCNT2, GRIN2D, KIAA1549, KRT80, LZTS1, SLC39A10, SPTBN2, and ZSWIM4) and five hub exosomal miRNAs (hsa-miR-126, hsa-miR-139, hsa-miR-141, hsa-miR-29c, and hsa-miR-423). The functional annotation revealed that these hub mRNAs were mainly involved in the regulation of B cell receptor signaling pathway and glycosphingolipid biosynthesis related pathways. All hub mRNAs and hub exosomal miRNAs exhibited high diagnosis value for CRC. Furthermore, the association of the hub mRNAs with overall survival, stages, and MSI phenotype of CRC revealed their important roles in CRC progression. Conclusion This study constructed an exosomal miRNA-mRNA network which may play crucial roles in the carcinogenesis and progression of CRC, thus providing potential diagnostic biomarkers and therapeutic targets for CRC.

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Competitive Endogenous RNA Network Construction and Comparison of Lung Squamous Cell Carcinoma in Smokers and Nonsmokers

Disease Markers ◽

10.1155/2019/5292787 ◽

2019 ◽

Vol 2019 ◽

pp. 1-14 ◽

Cited By ~ 1

Author(s):

Yan Yao ◽

Tingting Zhang ◽

Lingyu Qi ◽

Ruijuan Liu ◽

Gongxi Liu ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Molecular Mechanisms ◽

Differential Expression Analysis ◽

Lung Squamous Cell Carcinoma ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Cerna Network

Background. Lung squamous cell carcinoma (LUSC) is a subtype of highly malignant lung cancer with poor prognosis, for which smoking is the main risk factor. However, the underlying genetic and molecular mechanisms of smoking-related LUSC remain largely unknown. Methods. We mined existing LUSC-related mRNA, miRNA, and lncRNA transcriptome data and corresponding clinical data from The Cancer Genome Atlas (TCGA) database and divided them into smoking and nonsmoking groups, followed by differential expression analysis. Functional enrichment analysis of the unique differentially expressed mRNAs of the two groups was performed using the DAVID database. Subsequently, the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network of LUSC in smoking and nonsmoking groups was constructed. Finally, survival analyses were performed to determine the effects of differentially expressed lncRNAs/mRNAs/miRNAs that were involved in the ceRNA network on overall survival and to discover the hub genes. Results. A total of 1696 lncRNAs, 125 miRNAs, and 3246 mRNAs and 1784 lncRNAs, 96 miRNAs, and 3229 mRNAs with differentially expressed profiles were identified in the smoking and nonsmoking groups, respectively. The ceRNA network and survival analysis revealed four lncRNAs (LINC00466, DLX6-AS1, LINC00261, and AGBL1), one miRNA (hsa-mir-210), and two mRNAs (CITED2 and ENPP4), with the potential as biomarkers for smoking-related LUSC diagnosis and prognosis. Conclusion. Taken together, our research has identified the differences in the ceRNA regulatory networks between smoking and nonsmoking LUSC, which could lay the foundation for future clinical research.

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Serum-Derived Neuronal Exosomal miRNAs as Biomarkers of Acute Severe Stress

International Journal of Molecular Sciences ◽

10.3390/ijms22189960 ◽

2021 ◽

Vol 22 (18) ◽

pp. 9960

Author(s):

Minkyoung Sung ◽

Soo-Eun Sung ◽

Kyung-Ku Kang ◽

Joo-Hee Choi ◽

Sijoon Lee ◽

...

Keyword(s):

Acute Stress ◽

Stress Hormones ◽

Differentially Expressed ◽

Control Group ◽

Severe Stress ◽

Sprague Dawley ◽

Sprague Dawley Rats ◽

Exosomal Mirnas ◽

Differentially Expressed Mirnas ◽

Exosomal Mirna

Stress is the physical and psychological tension felt by an individual while adapting to difficult situations. Stress is known to alter the expression of stress hormones and cause neuroinflammation in the brain. In this study, miRNAs in serum-derived neuronal exosomes (nEVs) were analyzed to determine whether differentially expressed miRNAs could be used as biomarkers of acute stress. Specifically, acute severe stress was induced in Sprague-Dawley rats via electric foot-shock treatment. In this acute severe-stress model, time-dependent changes in the expression levels of stress hormones and neuroinflammation-related markers were analyzed. In addition, nEVs were isolated from the serum of control mice and stressed mice at various time points to determine when brain damage was most prominent; this was found to be 7 days after foot shock. Next-generation sequencing was performed to compare neuronal exosomal miRNA at day 7 with the neuronal exosomal miRNA of the control group. From this analysis, 13 upregulated and 11 downregulated miRNAs were detected. These results show that specific miRNAs are differentially expressed in nEVs from an acute severe-stress animal model. Thus, this study provides novel insights into potential stress-related biomarkers.

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Analysis of core genes for colorectal cancer prognosis based on immune and stromal scores

PeerJ ◽

10.7717/peerj.12452 ◽

2021 ◽

Vol 9 ◽

pp. e12452

Author(s):

Yi Zhu ◽

Yuan Zhou ◽

HongGang Jiang ◽

ZhiHeng Chen ◽

BoHao Lu

Keyword(s):

Colorectal Cancer ◽

Tumor Microenvironment ◽

Differentially Expressed Genes ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Ppi Network ◽

The Core ◽

Regulatory Effects ◽

Core Genes

Background Colorectal cancer (CRC) is one of the most common malignancies.An early diagnosis and an accurate prognosis are major focuses of CRC research. Tumor microenvironment cells and the extent of infiltrating immune and stromal cells contribute significantly to the tumor prognosis. Methods Immune and stromal scores were calculated based on the ESTIMATE algorithm using the sample expression profile of the The Cancer Genome Atlas (TCGA) database. GSE102479 was used as the validation database. Differentially expressed genes whose expression was significantly associated with the prognosis of CRC patients were identified based on the immune matrix score. Survival analysis was conducted on the union of the differentially expressed genes. A protein–protein interaction (PPI) network was constructed using the STRING database to identify the closely connected modules. To conduct functional enrichment analysis of the relevant genes, GO and KEGG pathway analyses were performed with Cluster Profiler. Pivot analysis of the ncRNAs and TFs was performed by using the RAID2.0 database and TRRUST v2 database. TF-mRNA regulatory relationships were analyzed in the TRRUST V2 database. Hubgene targeting relationships were screened in the TargetScan, miRTarBase and miRDB databases. The SNV data of the hub genes were analyzed by using the R maftools package. A ROC curve was drawn based on the TCGA database. The proportion of immune cells was estimated using CIBERSORT and the LM22 feature matrix. Results The results showed that the matrix score was significantly correlated with colorectal cancer stage T. A total of 789 differentially expressed genes and 121 survival-related prognostic genes were identified. The PPI network showed that 22 core genes were related to the CRC prognosis. Furthermore, four ncRNAs that regulated the core prognosis genes, 11 TFs with regulatory effects on the core prognosis genes, and two drugs, quercetin and pseudoephedrine, that have regulatory effects on colorectal cancer were also identified. Conclusions We obtained a list of tumor microenvironment-related genes for CRC patients. These genes could be useful for determining the prognosis of CRC patients. To confirm the function of these genes, additional experiments are necessary.

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Comprehensive Analysis of Potential miRNA-Target mRNA-Immunocyte Subtype Network in Cerebral Infarction

European Neurology ◽

10.1159/000518893 ◽

2021 ◽

pp. 1-14

Author(s):

Xiuyan Qi ◽

Huiqian Lin ◽

Yongge Hou ◽

Xiaohui Su ◽

Yanfang Gao

Keyword(s):

Cerebral Infarction ◽

Mirna Target ◽

Differential Expression Analysis ◽

Diagnostic Value ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Target Mrna ◽

Target Mrnas ◽

Differentially Expressed Mirnas

Introduction: Cerebral infarction (CI) is one of the leading causes of serious long-term disability and mortality. Objective: We aimed to identify potential miRNAs and target mRNAs and assess the involvement of immunocyte infiltration in the process of CI. Methods: First, miRNA and mRNA data were downloaded from the Gene Expression Omnibus database, followed by differential expression analysis. Second, correlation analysis between differentially expressed mRNAs and differential immunocyte subtypes was performed through the CIBERSORT algorithm. Third, the regulatory network between miRNAs and immunocyte subtype-related mRNAs was constructed followed by the functional analysis of these target mRNAs. Fourth, correlation validation between differentially expressed mRNAs and differential immunocyte subtypes was performed in the GSE37587 dataset. Finally, the diagnostic ability of immunocyte subtype-related mRNAs was tested. Results: Up to 17 differentially expressed miRNAs and 3,267 differentially expressed mRNAs were identified, among which 310 differentially expressed mRNAs were significantly associated with immunocyte subtypes. Several miRNA-target mRNA-immunocyte subtype networks including hsa-miR-671-3p-ZC3HC1-neutrophils, hsa-miR-625-CD5-monocytes, hsa-miR-122-ACOX1/DUSP1/NEDD9-neutrophils, hsa-miR-455-5p-SLC24A4-monocytes, and hsa-miR-455-5p-SORL1-neutrophils were identified. LAT, ACOX1, DUSP1, NEDD9, ZC3HC1, BIN1, AKT1, DNMT1, SLC24A4, and SORL1 had a potential diagnostic value for CI. Conclusions: The network including miRNA, target mRNA, and immunocyte subtype may be novel regulators and diagnostic and therapeutic targets in CI.

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Distinct Exosomal miRNA Profiles from BALF and Lung Tissue from COPD and IPF Patients

10.20944/preprints202108.0520.v1 ◽

2021 ◽

Author(s):

Gagandeep Kaur ◽

Krishna Maremanda ◽

Michael Campos ◽

Hitendra Singh Chand ◽

Feng Li ◽

...

Keyword(s):

Lung Tissue ◽

Cell Communication ◽

Differentially Expressed ◽

Chronic Obstructive ◽

Obstructive Pulmonary Disease ◽

Chronic Lung Diseases ◽

Copd Patients ◽

Exosomal Mirnas ◽

Differentially Expressed Mirnas ◽

Exosomal Mirna

Background: Chronic Obstructive Pulmonary Disease (COPD) and Idiopathic Pulmonary Fibrosis (IPF) are chronic, progressive lung ailments which are characterized by distinct pathologies. Early detection biomarkers and disease mechanisms for these debilitating diseases are lacking. Exosomes are small extracellular vesicles attributed to carry proteins, mRNA, miRNA and sncRNA to facilitate cell-to-cell communication under normal and diseased conditions. Exosomal miRNAs have been studied in relation to many diseases. However, there is little to no knowledge regarding the miRNA population of BALF or the lung tissue derived exosomes in COPD and IPF. Here, we determined and compared the miRNA profiles of BALF and lung tissue-derived exosomes from healthy non-smokers, healthy smokers, and patients with COPD and IPF in independent cohorts. Results: Exosome characterization using NanoSight particle tracking and TEM demonstrated that the BALF-derived exosomes were approximately 89.85 nm in size and ~2.95 X 1010 particles/mL. Lung-derived exosomes were ~146.04 nm in size and ~2.38 X 1011 particles/mL. NGS results identified three differentially expressed miRNAs in the BALF, while one in the lung-derived exosomes from COPD patients as compared to healthy non-smokers. Of these, three- and five-fold downregulation of miR-122-5p amongst the lung tissue-derived exosomes from COPD patients as compared to healthy non-smokers and smokers, respectively. Interestingly, there were key 55 differentially expressed miRNAs in the lung tissue-derived exosomes of IPF patients compared to non-smoking controls. Conclusions: Overall, we identified specific miRNAs to develop as biomarkers or targets for pathogenesis of these chronic lung diseases.

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Distinct exosomal miRNA profiles from BALF and lung tissue from COPD and IPF patients

10.1101/2021.08.24.21262557 ◽

2021 ◽

Author(s):

Gagandeep Kaur ◽

Krishna P Maremanda ◽

Michael Campos ◽

Hitendra S Chand ◽

Feng Li ◽

...

Keyword(s):

Lung Tissue ◽

Cell Communication ◽

Differentially Expressed ◽

Chronic Obstructive ◽

Obstructive Pulmonary Disease ◽

Chronic Lung Diseases ◽

Copd Patients ◽

Exosomal Mirnas ◽

Differentially Expressed Mirnas ◽

Exosomal Mirna

AbstractBackgroundChronic Obstructive Pulmonary Disease (COPD) and Idiopathic Pulmonary Fibrosis (IPF) are chronic, progressive lung ailments which are characterized by distinct pathologies. Early detection biomarkers and disease mechanisms for these debilitating diseases are lacking. Exosomes are small extracellular vesicles attributed to carry proteins, mRNA, miRNA and sncRNA to facilitate cell-to-cell communication under normal and diseased conditions. Exosomal miRNAs have been studied in relation to many diseases. However, there is little to no knowledge regarding the miRNA population of BALF or the lung tissue derived exosomes in COPD and IPF. Here, we determined and compared the miRNA profiles of BALF and lung tissue-derived exosomes from healthy non-smokers, healthy smokers, and patients with COPD and IPF in independent cohorts.ResultsExosome characterization using NanoSight particle tracking and TEM demonstrated that the BALF-derived exosomes were approximately 89.85 nm in size and ∼2.95 × 1010 particles/mL. Lung-derived exosomes were ∼146.04 nm in size and ∼2.38 × 1011 particles/mL. NGS results identified three differentially expressed miRNAs in the BALF, while one in the lung-derived exosomes from COPD patients as compared to healthy non-smokers. Of these, three- and five-fold downregulation of miR-122-5p amongst the lung tissue-derived exosomes from COPD patients as compared to healthy non-smokers and smokers, respectively. Interestingly, there were key 55 differentially expressed miRNAs in the lung tissue-derived exosomes of IPF patients compared to non-smoking controls.ConclusionsOverall, we identified specific miRNAs to develop as biomarkers or targets for pathogenesis of these chronic lung diseases.

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Genomic Expression Profiling of Colorectal Cancer in Silico

10.21203/rs.3.rs-310514/v1 ◽

2021 ◽

Author(s):

Feifei Liu ◽

Yu Wang ◽

Wenxue Li ◽

Diancheng Li ◽

Yuwei Xin ◽

...

Keyword(s):

Colorectal Cancer ◽

Survival Analysis ◽

Mrna Expression ◽

Differentially Expressed Genes ◽

Expression Profiles ◽

Functional Enrichment ◽

Differentially Expressed ◽

Analysis Tool ◽

Hub Genes ◽

Normal Tissues

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies of the digestive system; the progression and prognosis of which are affected by a complicated network of genes and pathways. The aim of this study was to identify potential hub genes associated with the progression and prognosis of colorectal cancer (CRC).Methods: We obtained gene expression profiles from GEO database to search differentially expressed genes (DEGs) between CRC tissues and normal tissue. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network to identify the hub genes, and analyzed the expression validation of the hub genes. Kaplan–Meier plotter survival analysis tool was performed to evaluate the prognostic value of hub genes expression in CRC patients.Results: A total of 370 samples, involving CRC and normal tissues were enrolled in this article. 283 differentially expressed genes (DEGs), including 62 upregulated genes and 221 downregulated genes between CRC and normal tissues were selected. We finally filtered out 6 hub genes, including INSL5, MTIM, GCG, SPP1, HSD11B2, and MAOB. In the database of TCGA-COAD, the mRNA expression of INSL5, MT1M, HSD11B2, MAOB in tumor is lower than that in normal; the mRNA expression of SPP1 in tumor is higher than that in normal. In the HPA database, the expression of INSL5, GCG, HSD11B2, MAOB in tumor is lower than that in normal tissues; the expression of SPP1 in the tumor is higher than that in normal tissues. Survival analysis revealed that INSL5, GCG, SPP1 and MT1M may serve as prognostic biomarkers in CRC. Conclusions: We screened out six hub genes to predict the occurrence and prognosis of patients with CRC using bioinformatics methods, which may provide new targets and ideas for diagnosis, prognosis and individualized treatment for CRC.

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Integrative transcriptome data mining for identification of core lncRNAs in breast cancer

PeerJ ◽

10.7717/peerj.7821 ◽

2019 ◽

Vol 7 ◽

pp. e7821 ◽

Cited By ~ 7

Author(s):

Xiaoming Zhang ◽

Jing Zhuang ◽

Lijuan Liu ◽

Zhengguo He ◽

Cun Liu ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Prognostic Value ◽

Early Stage ◽

Expression Profiles ◽

Diagnostic Value ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Data Set

Background Cumulative evidence suggests that long non-coding RNAs (lncRNAs) play an important role in tumorigenesis. This study aims to identify lncRNAs that can serve as new biomarkers for breast cancer diagnosis or screening. Methods First, the linear fitting method was used to identify differentially expressed genes from the breast cancer RNA expression profiles in The Cancer Genome Atlas (TCGA). Next, the diagnostic value of all differentially expressed lncRNAs was evaluated using a receiver operating characteristic (ROC) curve. Then, the top ten lncRNAs with the highest diagnostic value were selected as core genes for clinical characteristics and prognosis analysis. Furthermore, core lncRNA-mRNA co-expression networks based on weighted gene co-expression network analysis (WGCNA) were constructed, and functional enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The differential expression level and diagnostic value of core lncRNAs were further evaluated by using independent data set from Gene Expression Omnibus (GEO). Finally, the expression status and prognostic value of core lncRNAs in various tumors were analyzed based on Gene Expression Profiling Interactive Analysis (GEPIA). Results Seven core lncRNAs (LINC00478, PGM5-AS1, AL035610.1, MIR143HG, RP11-175K6.1, AC005550.4, and MIR497HG) have good single-factor diagnostic value for breast cancer. AC093850.2 has a prognostic value for breast cancer. AC005550.4 and MIR497HG can better distinguish breast cancer patients in early-stage from the advanced-stage. Low expression of MAGI2-AS3, LINC00478, AL035610.1, MIR143HG, and MIR145 may be associated with lymph node metastasis in breast cancer. Conclusion Our study provides candidate biomarkers for the diagnosis and prognosis of breast cancer, as well as a bioinformatics basis for the further elucidation of the molecular pathological mechanism of breast cancer.

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Identification of a prognostic long non-coding RNA signature in breast cancer

10.21203/rs.3.rs-27286/v1 ◽

2020 ◽

Author(s):

Gaochen Lan ◽

Xiaoling Yu ◽

Yanna Zhao ◽

Jinjian Lan ◽

Wan Li ◽

...

Keyword(s):

Breast Cancer ◽

Cox Regression ◽

Prognostic Biomarker ◽

Expression Profiles ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

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Identification of Hypoxia-Related Differentially Expressed Genes and Construction of the Clinical Prognostic Predictor in Hepatocellular Carcinoma by Bioinformatic Analysis

BioMed Research International ◽

10.1155/2021/7928051 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Hao Guo ◽

Jing Zhou ◽

Yanjun Zhang ◽

Zhi Wang ◽

Likun Liu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Regression Model ◽

Molecular Mechanisms ◽

Cox Regression ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Clinical Prognosis ◽

Prognostic Predictor ◽

Key Genes

Background. Hypoxia closely relates to malignant progression and appears to be prognostic for outcome in hepatocellular carcinoma (HCC). Our research is aimed at mining the hypoxic-related genes (HRGs) and constructing a prognostic predictor (PP) model on clinical prognosis in HCC patients. Methods. RNA-sequencing data about HRGs and clinical data of patients with HCC were obtained from The Cancer Genome Atlas (TCGA) database portal. Differentially expressed HRGs between HCC and para-carcinoma tissue samples were obtained by applying the Wilcox analysis in R statistical software. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for gene functional enrichment analyses. Then, the patients who were asked to follow up for at least one month were enrolled in the following study. Cox proportional risk regression model was applied to obtain key HRGs which related to overall survival (OS) in HCC. PP was constructed and defined, and the accuracy of PP was validated by constructing the signature in a training set and validation set. Connectivity map (CMap) was used to find potential drugs, and gene set cancer analysis (GSCA) was also performed to explore the underlying molecular mechanisms. Results. Thirty-seven differentially expressed HRGs were obtained. It contained 28 upregulated and 9 downregulated genes. After the univariate Cox regression model analysis, we obtained 27 prognosis-related HRGs. Of these, 25 genes were risk factors for cancer, and 2 genes were protective factors. The PP was composed by 12 key genes (HDLBP, SAP30, PFKP, DPYSL4, SLC2A1, HMOX1, PGK1, ERO1A, LDHA, ENO2, SLC6A6, and TPI1). GSCA results showed the overall activity of these 12 key genes in 10 cancer-related pathways. Besides, CMap identified deferoxamine, crotamiton, talampicillin, and lycorine might have effects with HCC. Conclusions. This study firstly reported 12 prognostic HRGs and constructed the model of the PP. This comprehensive research of multiple databases helps us gain insight into the biological properties of HCC and provides deferoxamine, crotamiton, talampicillin, and lycorine as potential drugs to fight against HCC.

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