A Pyroptosis-Related LncRNA Signature for Predicting Prognosis and Treatment in Hepatocellular Carcinoma

Abstract Background: Hepatocellular carcinoma (HCC), which carries a very bad prognosis, is a common malignant tumor worldwide. This study aim to identify a pyroptosis-related long non-coding RNA(pyLncRNA) prognostic signature in HCC by integrated bioinformatics analysis. Methods: All expression profiles of HCC were obtained from The Cancer Genome Atlas (TCGA) and pyroptosis-related genes were from the GSEA website. After identified differentially expressed pyLncRNAs, univariate Cox regression and Lasso analysis were used to identify a pyroptosis-related LncRNAs prognositic signature(py-LPS). Internal validation was used to validate the prognostic value of the py-LPS via the Kaplan-Meier(K-M) curve and receiver operating characteristic(ROC) curve. Additional, we established the nomogram and analyzed the correlation between the signature and immune immune infiltration as well as clinical treatment. Result: 7 pyLncRNAs were established the signature for HCC prognosis. K-M curves exhibited the low risk group presented a markedly longer OS than the high. Clinical subgroups analysis based age, gender, grade and stage yielded the similar results. The signature had an independent prognostic value for HCC(p<0.001). Nomogram estimated one-, three- and five-year survival were 0.777, 0.741 and 0.709. Then, gene set enrichment analysis(GSEA) demostrated significant pathways. Futhermore, we found immune cell infiltration and immunotherapy targets was associated with the signature,which could provided clinical recommendations for chemotherapy.Conclusion: In this study, a novel pyroptosis-related LncRNAs porgnostic signature of HCC, correlated with immune infiltration, could predict the survival of HCC patients and give suggestions for clinical treatment.

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A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients.

10.21203/rs.3.rs-17783/v1 ◽

2020 ◽

Author(s):

Baohui Zhang ◽

Bufu Tang ◽

Jianyao Gao ◽

Jiatong Li ◽

Lingming Kong ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

Enrichment Analysis ◽

High Risk Group ◽

Cancer Genome ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Diagnostic Model ◽

Potential Biomarker

Abstract Background Hypoxia plays an indispensable role in the development of hepatocellular carcinoma (HCC). However, there are few studies on the application of hypoxia molecules in the prognosis predicting of HCC. We aimed to identify the hypoxia-related genes in HCC and construct reliable models for diagnosis, prognosis and recurrence of HCC patients as well as exploring the potential mechanism.Methods Differentially expressed genes (DEGs) analysis was performed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and four clusters were determined by a consistent clustering analysis. Three DEGs closely related to overall survival（OS）were identified using Cox regression and LASSO analysis and the hypoxia-related signature was developed and validated in TCGA and International Cancer Genome Consortium (ICGC) database. Then the Gene Set Enrichment Analysis (GSEA) was performed to explore signaling pathways regulated by the signature and the CIBERSORT was used for estimating the fractions of immune cell types.Results A total of 397 hypoxia-related DEGs were detected and three genes (PDSS1, CDCA8 and SLC7A11) were selected to construct a prognosis, recurrence and diagnosis model. Then patients were divided into high- and low-risk groups. Our hypoxia-related signature was significantly associated with worse prognosis and higher recurrence rate. The diagnostic model also accurately distinguished HCC from normal samples and nodules. Furthermore, the hypoxia-related signature could positively regulate immune response and the high-risk group had higher fractions of macrophages, B memory cells and follicle-helper T cells, and exhibited higher expression of immunocheckpoints such as PD1and PDL1.Conclusions Altogether, our study showed that hypoxia-related signature is a potential biomarker for diagnosis, prognosis and recurrence of HCC, and it provided an immunological perspective for developing personalized therapies.

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Prognostic value and immune infiltration of novel signatures in colon cancer microenvironment

Cancer Cell International ◽

10.1186/s12935-021-02342-8 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yilin Lin ◽

Xiaoxian Pan ◽

Zhihua Chen ◽

Suyong Lin ◽

Zhanlong Shen ◽

...

Keyword(s):

Colon Cancer ◽

Regression Analysis ◽

Prognostic Value ◽

Immune Cell ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Cell Content ◽

Cox Regression Analysis ◽

Immune Infiltration

Abstract Background Growing evidence has shown that the prognosis for colon cancer depends on changes in microenvironment. The purpose of this study was to elucidate the prognostic value of long noncoding RNAs (lncRNAs) related to immune microenvironment (IM) in colon cancer. Methods Single sample gene set enrichment analysis (ssGSEA) was used to identify the subtypes of colon cancer based on the immune genomes of 29 immune signatures. Cox regression analysis identified a lncRNA signatures associated with immune infiltration. The Tumor Immune Estimation Resource database was used to analyze immune cell content. Results Colon cancer samples were divided into three subtypes by unsupervised cluster analysis. Cox regression analysis identified an immune infiltration-related 5-lncRNA signature. This signature combined with clinical factors can effectively improve the predictive ability for the overall survival (OS) of colon cancer. At the same time, we found that the expression of H19 affects the content of B cells and macrophages in the microenvironment of colon cancer and affects the prognosis of colon cancer. Finally, we constructed the H19 regulatory network and further analyzed the possible mechanisms. We found that knocking down the expression of H19 can significantly inhibit the expression of CCND1 and VEGFA. At the same time, the immunohistochemical assay found that the expression of CCND1 and VEGFA protein was significantly positively correlated with the infiltration of M2 type macrophages. Conclusion The findings may help to formulate clinical strategies and understand the underlying mechanisms of H19 regulation. H19 may be a biomarker for targeted treatment of colon cancer.

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A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients.

10.21203/rs.3.rs-17783/v3 ◽

2020 ◽

Author(s):

Baohui Zhang ◽

Bufu Tang ◽

Jianyao Gao ◽

Jiatong Li ◽

Lingming Kong ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

Enrichment Analysis ◽

High Risk Group ◽

Cancer Genome ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Diagnostic Model ◽

Potential Biomarker

Abstract BackgroundHypoxia plays an indispensable role in the development of hepatocellular carcinoma (HCC). However, there are few studies on the application of hypoxia molecules in the prognosis predicting of HCC. We aim to identify the hypoxia-related genes in HCC and construct reliable models for diagnosis, prognosis and recurrence of HCC patients as well as exploring the potential mechanism.MethodsDifferentially expressed genes (DEGs) analysis was performed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and four clusters were determined by a consistent clustering analysis. Three DEGs closely related to overall survival（OS）were identified using Cox regression and LASSO analysis. Then the hypoxia-related signature was developed and validated in TCGA and International Cancer Genome Consortium (ICGC) database. The Gene Set Enrichment Analysis (GSEA) was performed to explore signaling pathways regulated by the signature. CIBERSORT was used for estimating the fractions of immune cell types.ResultsA total of 397 hypoxia-related DEGs in HCC were detected and three genes (PDSS1, CDCA8 and SLC7A11) among them were selected to construct a prognosis, recurrence and diagnosis model. Then patients were divided into high- and low-risk groups. Our hypoxia-related signature was significantly associated with worse prognosis and higher recurrence rate. The diagnostic model also accurately distinguished HCC from normal samples and nodules. Furthermore, the hypoxia-related signature could positively regulate immune response. Meanwhile, the high-risk group had higher fractions of macrophages, B memory cells and follicle-helper T cells, and exhibited higher expression of immunocheckpoints such as PD1and PDL1.ConclusionsAltogether, our study showed that hypoxia-related signature is a potential biomarker for diagnosis, prognosis and recurrence of HCC, and it provided an immunological perspective for developing personalized therapies.

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A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients.

10.21203/rs.3.rs-17783/v2 ◽

2020 ◽

Author(s):

Baohui Zhang ◽

Bufu Tang ◽

Jianyao Gao ◽

Jiatong Li ◽

Lingming Kong ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

Enrichment Analysis ◽

High Risk Group ◽

Cancer Genome ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Diagnostic Model ◽

Potential Biomarker

Abstract Background Hypoxia plays an indispensable role in the development of hepatocellular carcinoma (HCC). However, there are few studies on the application of hypoxia molecules in the prognosis predicting of HCC. We aimed to identify the hypoxia-related genes in HCC and construct reliable models for diagnosis, prognosis and recurrence of HCC patients as well as exploring the potential mechanism. Methods Differentially expressed genes (DEGs) analysis was performed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and four clusters were determined by a consistent clustering analysis. Three DEGs closely related to overall survival（OS）were identified using Cox regression and LASSO analysis and the hypoxia-related signature was developed and validated in TCGA and International Cancer Genome Consortium (ICGC) database. Then the Gene Set Enrichment Analysis (GSEA) was performed to explore signaling pathways regulated by the signature and the CIBERSORT was used for estimating the fractions of immune cell types. Results A total of 397 hypoxia-related DEGs were detected and three genes (PDSS1, CDCA8 and SLC7A11) were selected to construct a prognosis, recurrence and diagnosis model. Then patients were divided into high- and low-risk groups. Our hypoxia-related signature was significantly associated with worse prognosis and higher recurrence rate. The diagnostic model also accurately distinguished HCC from normal samples and nodules. Furthermore, the hypoxia-related signature could positively regulate immune response and the high-risk group had higher fractions of macrophages, B memory cells and follicle-helper T cells, and exhibited higher expression of immunocheckpoints such as PD1and PDL1. Conclusions Altogether, our study showed that hypoxia-related signature is a potential biomarker for diagnosis, prognosis and recurrence of HCC, and it provided an immunological perspective for developing personalized therapies.

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Hypoxic Characteristic in the Immunosuppressive Microenvironment of Hepatocellular Carcinoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.611058 ◽

2021 ◽

Vol 12 ◽

Author(s):

Zhuomao Mo ◽

Daiyuan Liu ◽

Dade Rong ◽

Shijun Zhang

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

Cancer Genome ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Immune Checkpoints ◽

Immune Cell Infiltration ◽

Immunosuppressive Microenvironment

Background: Generally, hepatocellular carcinoma (HCC) exists in an immunosuppressive microenvironment that promotes tumor evasion. Hypoxia can impact intercellular crosstalk in the tumor microenvironment. This study aimed to explore and elucidate the underlying relationship between hypoxia and immunotherapy in patients with HCC.Methods: HCC genomic and clinicopathological datasets were obtained from The Cancer Genome Atlas (TCGA-LIHC), Gene Expression Omnibus databases (GSE14520) and International Cancer Genome Consortium (ICGC-LIRI). The TCGA-LIHC cases were divided into clusters based on single sample gene set enrichment analysis and hierarchical clustering. After identifying patients with immunosuppressive microenvironment with different hypoxic conditions, correlations between immunological characteristics and hypoxia clusters were investigated. Subsequently, a hypoxia-associated score was established by differential expression, univariable Cox regression, and lasso regression analyses. The score was verified by survival and receiver operating characteristic curve analyses. The GSE14520 cohort was used to validate the findings of immune cell infiltration and immune checkpoints expression, while the ICGC-LIRI cohort was employed to verify the hypoxia-associated score.Results: We identified hypoxic patients with immunosuppressive HCC. This cluster exhibited higher immune cell infiltration and immune checkpoint expression in the TCGA cohort, while similar significant differences were observed in the GEO cohort. The hypoxia-associated score was composed of five genes (ephrin A3, dihydropyrimidinase like 4, solute carrier family 2 member 5, stanniocalcin 2, and lysyl oxidase). In both two cohorts, survival analysis revealed significant differences between the high-risk and low-risk groups. In addition, compared to other clinical parameters, the established score had the highest predictive performance at both 3 and 5 years in two cohorts.Conclusion: This study provides further evidence of the link between hypoxic signals in patients and immunosuppression in HCC. Defining hypoxia-associated HCC subtypes may help reveal potential regulatory mechanisms between hypoxia and the immunosuppressive microenvironment, and our hypoxia-associated score could exhibit potential implications for future predictive models.

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Identification of the HMMR Gene as a Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma Based on Integrated Bioinformatics Analysis

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/5970085 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Honglan Guo ◽

Qinqiao Fan

Keyword(s):

Hepatocellular Carcinoma ◽

Roc Curve ◽

Cox Regression ◽

Enrichment Analysis ◽

Cancer Genome ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Roc Curve Analysis ◽

Cox Regression Analysis ◽

Normal Tissues

Background. We aimed to investigate the expression of the hyaluronan-mediated motility receptor (HMMR) gene in hepatocellular carcinoma (HCC) and nonneoplastic tissues and to investigate the diagnostic and prognostic value of HMMR. Method. With the reuse of the publicly available The Cancer Genome Atlas (TCGA) data, 374 HCC patients and 50 nonneoplastic tissues were used to investigate the diagnostic and prognostic values of HMMR genes by receiver operating characteristic (ROC) curve analysis and survival analysis. All patients were divided into low- and high-expression groups based on the median value of HMMR expression level. Univariate and multivariate Cox regression analysis were used to identify prognostic factors. Gene set enrichment analysis (GSEA) was performed to explore the potential mechanism of the HMMR genes involved in HCC. The diagnostic and prognostic values were further validated in an external cohort from the International Cancer Genome Consortium (ICGC). Results. HMMR mRNA expression was significantly elevated in HCC tissues compared with that in normal tissues from both TCGA and the ICGC cohorts (all P values <0.001). Increased HMMR expression was significantly associated with histologic grade, pathological stage, and survival status (all P values <0.05). The area under the ROC curve for HMMR expression in HCC and normal tissues was 0.969 (95% CI: 0.948–0.983) in the TCGA cohort and 0.956 (95% CI: 0.932–0.973) in the ICGC cohort. Patients with high HMMR expression had a poor prognosis than patients with low expression group in both cohorts (all P < 0.001 ). Univariate and multivariate analysis also showed that HMMR is an independent predictor factor associated with overall survival in both cohorts (all P values <0.001). GSEA showed that genes upregulated in the high-HMMR HCC subgroup were mainly significantly enriched in the cell cycle pathway, pathways in cancer, and P53 signaling pathway. Conclusion. HMMR is expressed at high levels in HCC. HMMR overexpression may be an unfavorable prognostic factor for HCC.

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PVT1 is a prognostic marker associated with immune invasion of bladder urothelial carcinoma

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2022009 ◽

2021 ◽

Vol 19 (1) ◽

pp. 169-190

Author(s):

Peiyuan Li ◽

◽

Gangjie Qiao ◽

Jian Lu ◽

Wenbin Ji ◽

...

Keyword(s):

Urothelial Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Gene Set Enrichment ◽

Cox Regression Analysis ◽

Gene Set ◽

Bladder Urothelial Carcinoma

<abstract> <p>Plasmacytoma variant translocation 1 (PVT1) is involved in multiple signaling pathways and plays an important regulatory role in a variety of malignant tumors. However, its role in the prognosis and immune invasion of bladder urothelial carcinoma (BLCA) remains unclear. This study investigated the expression of PVT1 in tumor tissue and its relationship with immune invasion, and determined its prognostic role in patients with BLCA. Patients were identified from the cancer genome atlas (TCGA). The enrichment pathway and function of PVT1 were explained by gene ontology (GO) term analysis, gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA), and the degree of immune cell infiltration was quantified. Kaplan–Meier analysis and Cox regression were used to analyze the correlation between PVT1 and survival rate. PVT1-high BLCA patients had a lower 10-year disease-specific survival (DSS P < 0.05) and overall survival (OS P < 0.05). Multivariate Cox regression analysis showed that PVT1 (high vs. low) (P = 0.004) was an independent prognostic factor. A nomogram was used to predict the effect of PVT1 on the prognosis. PVT1 plays an important role in the progression and prognosis of BLCA and can be used as a medium biomarker to predict survival after cystectomy.</p> </abstract>

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CXCL5 Has Potential to Be a Marker for Hepatocellular Carcinoma Prognosis and Was Correlating With Immune Infiltrates

Frontiers in Oncology ◽

10.3389/fonc.2021.637023 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yuan Nie ◽

Mei-chun Jiang ◽

Cong Liu ◽

Qi Liu ◽

Xuan Zhu

Keyword(s):

Hepatocellular Carcinoma ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Hospital Data ◽

Gene Set Enrichment ◽

Local Hospital ◽

High Expression Group ◽

Cancer Genome Atlas

BackgroundsTumor microenvironment (TME) plays a crucial role in the initiation and progression of Hepatocellular Carcinoma (HCC), especially immune infiltrates. However, there is still a challenge in understanding the modulation of the immune and stromal components in TME, especially TME related genes.MethodsThe proportion of tumor-infiltrating immune cells (TICs) and the immune and stromal scores in 374 HCC patients from The Cancer Genome Atlas (TCGA) database were determined using CIBERSORT and ESTIMATE computational methods. The final screened genes were confirmed by the PPI network and univariate Cox regression of the differentially expressed genes based on different immune or stromal scores. The correlation between the expression levels of the final gene interactions and the clinical characteristics was based on TCGA database and local hospital data. Gene set enrichment analysis (GSEA) and the effect of CXCL5 expression on TICs were conducted.ResultsThere were correlations between the expression of CXCL5 and survival of HCC patients and TMN classification both in TCGA database and local hospital data. The immune-related activities were enriched in the high-expression group; however, the metabolic pathways were enriched in the low-expression group. The result of CIBERSORT analyzing had indicated that CXCL5 expression were correlated with the proportion of NK cells activated, macrophages M0, Mast cells resting, Neutrophils.ConclusionsCXCL5 was a potential prognostic marker for HCC and provides clues regarding immune infiltrates, which offers extra insight for therapeutics of HCC, however, more independent cohorts and functional experiments of CXCL5 are warranted.

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Prediction of Hepatocellular Carcinoma Prognosis and Immune Cell Infiltration Using Gene Signature Associated with Inflammatory Response

Computational and Mathematical Methods in Medicine ◽

10.1155/2022/2415129 ◽

2022 ◽

Vol 2022 ◽

pp. 1-24

Author(s):

Bin-Bin Da ◽

Shuai Luo ◽

Ming Huang ◽

Fei Song ◽

Rong Ding ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Inflammatory Response ◽

Immune Cell ◽

Cox Regression ◽

Inflammatory Responses ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Differential Analysis

It has been demonstrated that the inflammatory response influences cancer development and can be used as a prognostic biomarker in various tumors. However, the relevance of genes associated with inflammatory responses in hepatocellular carcinoma (HCC) remains unknown. The Cancer Genome Atlas (TCGA) database was analyzed using weighted gene coexpression network analysis (WGCNA) and differential analysis to discover essential inflammatory response-related genes (IFRGs). Cox regression studies, both univariate and multivariate, were employed to develop a prognostic IFRGs signature. Additionally, Gene Set Enrichment Analysis (GSEA) was used to deduce the biological function of the IFRGs signature. Finally, we estimated immune cell infiltration using a single sample GSEA (ssGSEA) and x-cell. Our results revealed that, among the major HCC IFRGs, two (DNASE1L3 and KLKB1) were employed to create a predictive IFRG signature. The IFRG signature could correctly predict overall survival (O.S) as per Kaplan-Meier time-dependent roc curves analysis. It was also linked to pathological tumor stage and T stage and might be used as a prognostic predictor in HCC. GSEA analysis concluded that the IFRG signature might influence the immune response in HCC. Immunological cell infiltration and immune checkpoint molecule expression differed in the high-risk and low-risk groups. As a result of our findings, DNASILE may play a role in the tumor microenvironment. However, more research is necessary to confirm the role of DNASE1L3 and KLKB1.

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Bioinformatics Analysis of Autophagy-related LncRNAs in Esophageal Carcinoma

10.21203/rs.3.rs-60567/v1 ◽

2020 ◽

Author(s):

junbai fan ◽

Dan Wu ◽

Yi Ding

Keyword(s):

High Risk ◽

Esophageal Carcinoma ◽

Cox Regression ◽

Expression Profiles ◽

Enrichment Analysis ◽

Diagnostic Value ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Risk Patients ◽

Risk Patients

Abstract Background: Esophageal carcinoma (ESCA) is a malignant tumor with high invasiveness and mortality. Autophagy has multiple roles in the development of cancer; however, there are limited data on autophagy genes associated with long non-coding RNAs (lncRNAs) in ESCA. The purpose of this study was to screen potential diagnostic and prognostic molecules, and to identify gene co-expression networks associated with autophagy in ESCA. Methods: We downloaded transcriptome expression profiles from The Cancer Genome Atlas and autophagy-related gene data from the Human Autophagy Database, and analyzed the co-expression of mRNAs and lncRNAs. In addition, the diagnostic and prognostic value of autophagy-related lncRNAs was analyzed by multivariate Cox regression. Furthermore, Kyoto Encyclopedia of Genes and Genomes analysis was carried out for high-risk patients, and enriched pathways were analyzed by gene set enrichment analysis. Results: The results showed that genes of high-risk patients were enriched in protein export and spliceosome. Based on Cox stepwise regression and survival analysis, we identified seven autophagy-related lncRNAs with prognostic and diagnostic value, with the potential to be used as a combination to predict the prognosis of patients with ESCA. Finally, a co-expression network related to autophagy was constructed. Conclusion: These results suggest that autophagy-related lncRNAs and the spliceosome play important parts in the pathogenesis of ESCA. Our findings provide new insight into the molecular mechanism of ESCA and suggest a new method for improving its treatment.

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