Polyploidy and chromosomal instability correlates with proliferative traits and lack of immune-related gene signatures in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) remains the third leader cancer-associated cause of death globally, but the etiological basis for this complex disease remains poorly clarified. The present study was thus conceptualized to define a prognostic immune-related gene (IRG) signature capable of predicting immunotherapy responsiveness and overall survival (OS) in patients with HCC. Methods: Five differentially expressed IRG associated with HCC were established the immune-related risk model through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Patients were separated at random into training and testing cohorts, after which the association between the identified IRG signature and OS was evaluated using the “survival” R package. In addition, maftools was leveraged to assess mutational data, with tumor mutation burden (TMB) scores being calculated as follows: (total mutations/total bases) × 106. Immune-related risk term abundance was quantified via “ssGSEA” algorithm using the “gsva” R package. Results: HCC patients were successfully stratified into low-risk and high-risk groups based upon a signature composed of 5 differentially expressed IRGs, with overall survival being significantly different between these 2 groups in training cohort, testing cohort and overall patient cohort ( P = 1.745e-06, P = 1.888e-02, P = 4.281e-07). No association was observed between TMB and this IRG risk score in the overall patient cohort ( P = 0.461). Notably, 19 out of 29 immune-related risk terms differed substantially in the overall patient dataset. These risk terms mainly included checkpoints, human leukocyte antigens, natural killer cells, dendritic cells, and major histocompatibility complex class I. Conclusion: In summary, an immune-related prognostic gene signature was successfully developed and used to predict survival outcomes and immune system status in patients with HCC. This signature has the potential to help guide immunotherapeutic treatment planning for patients affected by this deadly cancer.

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An Immune-Related Gene Signature for Predicting Survival and Immunotherapy Efficacy in Hepatocellular Carcinoma

10.21203/rs.3.rs-36927/v1 ◽

2020 ◽

Author(s):

Yifei Dai ◽

Weijie Qiang ◽

Kequan Lin ◽

Yu Gui ◽

Xun Lan ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cell ◽

Prognostic Index ◽

Gene Signature ◽

The Cancer Genome Atlas ◽

Lasso Regression ◽

Related Gene ◽

Immune Related Gene ◽

Clinicopathologic Factors ◽

Immune Related Genes

Abstract Background: Hepatocellular carcinoma (HCC) ranks the fourth in terms of cancer-related mortality globally. Herein, in this research, we attempted to develop a novel immune-related gene signature that could predict survival and efficacy of immunotherapy for HCC patients.Methods: The transcriptomic and clinical data of HCC samples were downloaded from The Cancer Genome Atlas (TCGA) and GSE14520 datasets, followed by acquisition of immune-related genes from the ImmPort database. Afterwards, an immune-related gene-based prognostic index (IRGPI) was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. Kaplan-Meier survival curves as well as time-dependent receiver operating characteristic (ROC) curve were performed to evaluate its predictive capability. Besides, both univariate and multivariate analysis on overall survival for the IRGPI and multiple clinicopathologic factors were carried out, followed by the construction of nomogram. Finally, we explored the possible correlation of IRGPI with immune cell infiltration or immunotherapy efficacy. Results: Analysis of 365 HCC samples identified 11 differentially expressed genes, which were selected to establish the IRGPI. Notably, it can predict survival of HCC patients more accurately than published biomarkers. Furthermore, IRGPI can predict the infiltration of immune cells in the tumor microenvironment of HCC, as well as the response of immunotherapy.Conclusion: Collectively, the currently established IRGPI can accurately predict survival, reflect the immune microenvironment, and predict the efficacy of immunotherapy among HCC patients.

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