Integrative analysis identifies key mRNA biomarkers for diagnosis, prognosis, and therapeutic targets of HCV-associated hepatocellular carcinoma

Zhang, Yongqiang; Tang, Yuqin; Guo, Chengbin; Li, Gen

doi:10.18632/aging.202957

Cited by 12 publications

(32 citation statements)

References 79 publications

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“…Interestingly, four clusters were highly connected by driver oncogenes of HCC or immunologic genes such as CXCL8, UBE2C, and MMP9. Notably, we observed the most conspicuous cluster that consisted of several hub genes of HCC (CCNB1, CDC20, TOP2A, and UBE2C) ( 23 , 24 ). Thus, the “seed” node of this cluster, KIF2C, was considered as the key target of HGSIS, and its crucial role in the discovery of putative drugs is worth looking into.…”

Section: Resultsmentioning

confidence: 88%

“…The patient population and the clinicopathological characteristics are summarized in Supplementary Table 1 . The normalized RNA sequencing profiles were retrieved and preprocessed as previously reported ( 20 , 23 , 24 ). For the analysis of somatic mutation information, we gathered the available mutation annotation format (MAF) file from the TCGA data portal ( ) using the “maftools” package ( 25 ).…”

Section: Methodsmentioning

confidence: 99%

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Hallmark-guided subtypes of hepatocellular carcinoma for the identification of immune-related gene classifiers in the prediction of prognosis, treatment efficacy, and drug candidates

Guo

Tang²,

Zhao³

et al. 2022

Front. Immunol.

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Hepatocellular carcinoma (HCC), accounting for ~90% of all primary liver cancer, is a prevalent malignancy worldwide. The intratumor heterogeneity of its causative etiology, histology, molecular landscape, and immune phenotype makes it difficult to precisely recognize individuals with high mortality risk or tumor-intrinsic treatment resistance, especially immunotherapy. Herein, we comprehensively evaluated the activities of cancer hallmark gene sets and their correlations with the prognosis of HCC patients using gene set variation analysis (GSVA) and identified two HCC subtypes with distinct prognostic outcomes. Based on these subtypes, seven immune-related genes (TMPRSS6, SPP1, S100A9, EPO, BIRC5, PLXNA1, and CDK4) were used to construct a novel prognostic gene signature [hallmark-guided subtypes-based immunologic signature (HGSIS)] via multiple statistical approaches. The HGSIS-integrated nomogram suggested an enhanced predictive performance. Interestingly, oncogenic hallmark pathways were significantly enriched in the high-risk group and positively associated with the risk score. Distinct mutational landscapes and immune profiles were observed between different risk groups. Moreover, immunophenoscore (IPS) and tumor immune dysfunction and exclusion (TIDE) analysis showed different sensitivities of HGSIS risk groups for immune therapy efficacy, and the pRRophetic algorithm indicated distinguishable responses for targeted/chemotherapies in different groups. KIF2C was picked out as the key target concerning HGSIS, and the top 10 small molecules were predicted to bind to the active site of KIF2C via molecular docking, which might be further used for candidate drug discovery of HCC. Taken together, our study offers novel insights for clinically significant subtype recognition, and the proposed signature may be a helpful guide for clinicians to improve the treatment regimens.

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Section: Resultsmentioning

confidence: 88%

Section: Methodsmentioning

confidence: 99%

Hallmark-guided subtypes of hepatocellular carcinoma for the identification of immune-related gene classifiers in the prediction of prognosis, treatment efficacy, and drug candidates

Guo

Tang²,

Zhao³

et al. 2022

Front. Immunol.

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“…Additionally, the CNV alteration landscapes of the high- and low-risk groups were generated after removing the germline features ( Figure 6F ). Interestingly, the hub genes of HCC ( 32 , 33 ) were widely amplified in the high-risk group in comparison with the low-risk group ( Figure 6G ). NDC80 and RFC4 were two examples demonstrating the positive correlations of gene expression and copy number in the TIPRGPI high-risk group ( Figure 6H ).…”

Section: Resultsmentioning

confidence: 99%

“…For the TCGA-LIHC dataset, the Fragments per Kilobase Million (FPKM) value was used to generate the Transcripts per Kilobase Million (TPM) and further subjected to log2 transformation for normalization. For the ICGC-LIRI-JP and GSE14520 datasets, data were preprocessed as previously reported ( 32 , 33 ). The ESTIMATE algorithm was utilized to calculate the immune score, stromal score, estimate score, and tumor purity for all the patients in the TCGA-LIHC dataset ( 34 , 35 ).…”

Section: Methodsmentioning

confidence: 99%

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Identification of a Tumor Immunological Phenotype-Related Gene Signature for Predicting Prognosis, Immunotherapy Efficacy, and Drug Candidates in Hepatocellular Carcinoma

et al. 2022

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Hepatocellular carcinoma (HCC) is the predominant subtype of primary liver cancer and represents a highly heterogeneous disease, making it hard to predict the prognosis and therapy efficacy. Here, we established a novel tumor immunological phenotype-related gene index (TIPRGPI) consisting of 11 genes by Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) algorithm to predict HCC prognosis and immunotherapy response. TIPRGPI was validated in multiple datasets and exhibited outstanding performance in predicting the overall survival of HCC. Multivariate analysis verified it as an independent predictor and a TIPRGPI-integrated nomogram was constructed to provide a quantitative tool for clinical practice. Distinct mutation profiles, hallmark pathways, and infiltration of immune cells in tumor microenvironment were shown between the TIPRGPI high and low-risk groups. Notably, significant differences in tumor immunogenicity and tumor immune dysfunction and exclusion (TIDE) were observed between the two risk groups, suggesting a better response to immune checkpoint blockade (ICB) therapy of the low-risk group. Besides, six potential drugs binding to the core target of the TIPRGPI signature were predicted via molecular docking. Taken together, our study shows that the proposed TIPRGPI was a reliable signature to predict the risk classification, immunotherapy response, and drugs candidate with potential application in the clinical decision and treatment of HCC. The novel “TIP genes”-guided strategy for predicting the survival and immunotherapy efficacy, we reported here, might be also applied to more cancers other than HCC.

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Hallmark guided identification and characterization of a novel immune-relevant signature for prognostication of recurrence in stage I–III lung adenocarcinoma

et al. 2023

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Integrative analysis identifies key mRNA biomarkers for diagnosis, prognosis, and therapeutic targets of HCV-associated hepatocellular carcinoma

Cited by 12 publications

References 79 publications

Hallmark-guided subtypes of hepatocellular carcinoma for the identification of immune-related gene classifiers in the prediction of prognosis, treatment efficacy, and drug candidates

Hallmark-guided subtypes of hepatocellular carcinoma for the identification of immune-related gene classifiers in the prediction of prognosis, treatment efficacy, and drug candidates

Identification of a Tumor Immunological Phenotype-Related Gene Signature for Predicting Prognosis, Immunotherapy Efficacy, and Drug Candidates in Hepatocellular Carcinoma

Hallmark guided identification and characterization of a novel immune-relevant signature for prognostication of recurrence in stage I–III lung adenocarcinoma

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