Gene expression profiling, pathway analysis and subtype classification reveal molecular heterogeneity in hepatocellular carcinoma and suggest subtype specific therapeutic targets

Rahul Agarwal, Jitendra Narayan, Amitava Bhattacharyya, Mayank Saraswat, Anil Kumar Tomar

Résultats de recherche: Contribution à un journal/une revueArticle

Résumé

A very low 5-year survival rate among hepatocellular carcinoma (HCC) patients is mainly due to lack of early stage diagnosis, distant metastasis and high risk of postoperative recurrence. Hence ascertaining novel biomarkers for early diagnosis and patient specific therapeutics is crucial and urgent. Here, we have performed a comprehensive analysis of the expression data of 423 HCC patients (373 tumors and 50 controls) downloaded from The Cancer Genome Atlas (TCGA) followed by pathway enrichment by gene ontology annotations, subtype classification and overall survival analysis. The differential gene expression analysis using non-parametric Wilcoxon test revealed a total of 479 up-regulated and 91 down-regulated genes in HCC compared to controls. The list of top differentially expressed genes mainly consists of tumor/cancer associated genes, such as AFP, THBS4, LCN2, GPC3, NUF2, etc. The genes over-expressed in HCC were mainly associated with cell cycle pathways. In total, 59 kinases associated genes were found over-expressed in HCC, including TTK, MELK, BUB1, NEK2, BUB1B, AURKB, PLK1, CDK1, PKMYT1, PBK, etc. Overall four distinct HCC subtypes were predicted using consensus clustering method. Each subtype was unique in terms of gene expression, pathway enrichment and median survival. Conclusively, this study has exposed a number of interesting genes which can be exploited in future as potential markers of HCC, diagnostic as well as prognostic and subtype classification may guide for improved and specific therapy.

langueAnglais
Pages37-51
Nombre de pages15
journalCancer Genetics
Volume216-217
Les DOIs
étatPublié - 1 oct. 2017

Empreinte digitale

Gene Expression Profiling
Hepatocellular Carcinoma
Genes
Therapeutics
Early Diagnosis
Molecular Sequence Annotation
Gene Expression
Neoplasms
Gene Ontology
Atlases
Neoplasm Genes
Survival Analysis
Cluster Analysis
Cell Cycle
Phosphotransferases
Survival Rate
Biomarkers
Genome
Neoplasm Metastasis
Recurrence

mots-clés

    Citer ceci

    @article{319fd115fb1d4a70854d89c26bc3ae83,
    title = "Gene expression profiling, pathway analysis and subtype classification reveal molecular heterogeneity in hepatocellular carcinoma and suggest subtype specific therapeutic targets",
    abstract = "A very low 5-year survival rate among hepatocellular carcinoma (HCC) patients is mainly due to lack of early stage diagnosis, distant metastasis and high risk of postoperative recurrence. Hence ascertaining novel biomarkers for early diagnosis and patient specific therapeutics is crucial and urgent. Here, we have performed a comprehensive analysis of the expression data of 423 HCC patients (373 tumors and 50 controls) downloaded from The Cancer Genome Atlas (TCGA) followed by pathway enrichment by gene ontology annotations, subtype classification and overall survival analysis. The differential gene expression analysis using non-parametric Wilcoxon test revealed a total of 479 up-regulated and 91 down-regulated genes in HCC compared to controls. The list of top differentially expressed genes mainly consists of tumor/cancer associated genes, such as AFP, THBS4, LCN2, GPC3, NUF2, etc. The genes over-expressed in HCC were mainly associated with cell cycle pathways. In total, 59 kinases associated genes were found over-expressed in HCC, including TTK, MELK, BUB1, NEK2, BUB1B, AURKB, PLK1, CDK1, PKMYT1, PBK, etc. Overall four distinct HCC subtypes were predicted using consensus clustering method. Each subtype was unique in terms of gene expression, pathway enrichment and median survival. Conclusively, this study has exposed a number of interesting genes which can be exploited in future as potential markers of HCC, diagnostic as well as prognostic and subtype classification may guide for improved and specific therapy.",
    keywords = "Hepatocellular carcinoma, kinases, mRNA expression, subtype classification, survival analysis",
    author = "Rahul Agarwal and Jitendra Narayan and Amitava Bhattacharyya and Mayank Saraswat and Tomar, {Anil Kumar}",
    year = "2017",
    month = "10",
    day = "1",
    doi = "10.1016/j.cancergen.2017.06.002",
    language = "English",
    volume = "216-217",
    pages = "37--51",
    journal = "Cancer Genetics",
    issn = "2210-7762",
    publisher = "Elsevier Inc.",

    }

    Gene expression profiling, pathway analysis and subtype classification reveal molecular heterogeneity in hepatocellular carcinoma and suggest subtype specific therapeutic targets. / Agarwal, Rahul; Narayan, Jitendra; Bhattacharyya, Amitava; Saraswat, Mayank; Tomar, Anil Kumar.

    Dans: Cancer Genetics, Vol 216-217, 01.10.2017, p. 37-51.

    Résultats de recherche: Contribution à un journal/une revueArticle

    TY - JOUR

    T1 - Gene expression profiling, pathway analysis and subtype classification reveal molecular heterogeneity in hepatocellular carcinoma and suggest subtype specific therapeutic targets

    AU - Agarwal,Rahul

    AU - Narayan,Jitendra

    AU - Bhattacharyya,Amitava

    AU - Saraswat,Mayank

    AU - Tomar,Anil Kumar

    PY - 2017/10/1

    Y1 - 2017/10/1

    N2 - A very low 5-year survival rate among hepatocellular carcinoma (HCC) patients is mainly due to lack of early stage diagnosis, distant metastasis and high risk of postoperative recurrence. Hence ascertaining novel biomarkers for early diagnosis and patient specific therapeutics is crucial and urgent. Here, we have performed a comprehensive analysis of the expression data of 423 HCC patients (373 tumors and 50 controls) downloaded from The Cancer Genome Atlas (TCGA) followed by pathway enrichment by gene ontology annotations, subtype classification and overall survival analysis. The differential gene expression analysis using non-parametric Wilcoxon test revealed a total of 479 up-regulated and 91 down-regulated genes in HCC compared to controls. The list of top differentially expressed genes mainly consists of tumor/cancer associated genes, such as AFP, THBS4, LCN2, GPC3, NUF2, etc. The genes over-expressed in HCC were mainly associated with cell cycle pathways. In total, 59 kinases associated genes were found over-expressed in HCC, including TTK, MELK, BUB1, NEK2, BUB1B, AURKB, PLK1, CDK1, PKMYT1, PBK, etc. Overall four distinct HCC subtypes were predicted using consensus clustering method. Each subtype was unique in terms of gene expression, pathway enrichment and median survival. Conclusively, this study has exposed a number of interesting genes which can be exploited in future as potential markers of HCC, diagnostic as well as prognostic and subtype classification may guide for improved and specific therapy.

    AB - A very low 5-year survival rate among hepatocellular carcinoma (HCC) patients is mainly due to lack of early stage diagnosis, distant metastasis and high risk of postoperative recurrence. Hence ascertaining novel biomarkers for early diagnosis and patient specific therapeutics is crucial and urgent. Here, we have performed a comprehensive analysis of the expression data of 423 HCC patients (373 tumors and 50 controls) downloaded from The Cancer Genome Atlas (TCGA) followed by pathway enrichment by gene ontology annotations, subtype classification and overall survival analysis. The differential gene expression analysis using non-parametric Wilcoxon test revealed a total of 479 up-regulated and 91 down-regulated genes in HCC compared to controls. The list of top differentially expressed genes mainly consists of tumor/cancer associated genes, such as AFP, THBS4, LCN2, GPC3, NUF2, etc. The genes over-expressed in HCC were mainly associated with cell cycle pathways. In total, 59 kinases associated genes were found over-expressed in HCC, including TTK, MELK, BUB1, NEK2, BUB1B, AURKB, PLK1, CDK1, PKMYT1, PBK, etc. Overall four distinct HCC subtypes were predicted using consensus clustering method. Each subtype was unique in terms of gene expression, pathway enrichment and median survival. Conclusively, this study has exposed a number of interesting genes which can be exploited in future as potential markers of HCC, diagnostic as well as prognostic and subtype classification may guide for improved and specific therapy.

    KW - Hepatocellular carcinoma

    KW - kinases

    KW - mRNA expression

    KW - subtype classification

    KW - survival analysis

    UR - http://www.scopus.com/inward/record.url?scp=85026213896&partnerID=8YFLogxK

    U2 - 10.1016/j.cancergen.2017.06.002

    DO - 10.1016/j.cancergen.2017.06.002

    M3 - Article

    VL - 216-217

    SP - 37

    EP - 51

    JO - Cancer Genetics

    T2 - Cancer Genetics

    JF - Cancer Genetics

    SN - 2210-7762

    ER -