Dataset Information

Immunological inflammatory biomarkers as prognostic predictors for advanced hepatocellular carcinoma.

ABSTRACT:

Background

The immunological inflammatory biomarkers for advanced hepatocellular carcinoma are unclear. We aimed to investigate the association of immunity and inflammatory status with treatment outcomes in patients with advanced hepatocellular carcinoma who received molecular-targeted agents as primary treatment.

Patients and methods

We enrolled 728 consecutive patients with advanced hepatocellular carcinoma who received sorafenib (n = 554) or lenvatinib (n = 174) as primary treatment in Japan between May 2009 and June 2020. Changes in the neutrophil-to-lymphocyte ratio before and 1 month after treatment and their impact on survival were evaluated. The cut-off values of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio for predicting overall and progression-free survival were calculated using receiver operating characteristic curves.

Results

The neutrophil-to-lymphocyte ratio, but not the platelet-to-lymphocyte ratio, was an independent prognostic factor. Patients with decreased neutrophil-to-lymphocyte ratio survived significantly longer than patients with increased neutrophil-to-lymphocyte ratio (median overall survival: 14.7 versus 10.4 months, P = 0.0110). Among patients with a low pre-treatment neutrophil-to-lymphocyte ratio, the overall survival did not differ significantly between those with decreased and those with increased neutrophil-to-lymphocyte ratio after 1 month (median: 19.0 versus 14.8 months, P = 0.1498). However, among patients with high pre-treatment neutrophil-to-lymphocyte ratio, those whose neutrophil-to-lymphocyte ratio decreased after 1 month showed significantly longer survival than those whose neutrophil-to-lymphocyte ratio increased (median: 12.7 versus 5.5 months, P < 0.0001). The therapeutic effect was not correlated with pre-treatment neutrophil-to-lymphocyte ratio or platelet-to-lymphocyte ratio.

Conclusions

The neutrophil-to-lymphocyte ratio is a prognostic factor, along with liver function and tumor markers, in patients with advanced hepatocellular carcinoma who received molecular-targeted agents as primary treatment. Thus, the neutrophil-to-lymphocyte ratio could be a prognostic biomarker for advanced hepatocellular carcinoma primarily treated with immunotherapy.

SUBMITTER: Nakano M

PROVIDER: S-EPMC7807940 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Immunological inflammatory biomarkers as prognostic predictors for advanced hepatocellular carcinoma.

Nakano M M Kuromatsu R R Niizeki T T Okamura S S Iwamoto H H Shimose S S Shirono T T Noda Y Y Kamachi N N Koga H H Torimura T T

ESMO open 20210104 1

<h4>Background</h4>The immunological inflammatory biomarkers for advanced hepatocellular carcinoma are unclear. We aimed to investigate the association of immunity and inflammatory status with treatment outcomes in patients with advanced hepatocellular carcinoma who received molecular-targeted agents as primary treatment.<h4>Patients and methods</h4>We enrolled 728 consecutive patients with advanced hepatocellular carcinoma who received sorafenib (n = 554) or lenvatinib (n = 174) as primary trea ...[more]

PMID: 33399083

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Project description:Background: Hepatocellular carcinoma (HCC) is a tumor with high morbidity and high mortality worldwide. DNA methylation, one of the most common epigenetic changes, might serve a vital regulatory role in cancer. Methods: To identify categories based on DNA methylation data, consensus clustering was employed. The risk signature was yielded by systematic bioinformatics analyses based on the remarkably methylated CpG sites of cluster 1. Kaplan-Meier analysis, variable regression analysis, and ROC curve analysis were further conducted to validate the prognosis predictive ability of risk signature. Gene set enrichment analysis (GSEA) was performed for functional annotation. To uncover the context of tumor immune microenvironment (TIME) of HCC, we employed the ssGSEA algorithm and CIBERSORT method and performed TIMER database exploration and single-cell RNA sequencing analysis. Additionally, quantitative real-time polymerase chain reaction was employed to determine the LRRC41 expression and preliminarily explore the latent role of LRRC41 in prognostic prediction. Finally, mutation data were analyzed by employing the "maftools" package to delineate the tumor mutation burden (TMB). Results: HCC samples were assigned into seven subtypes with different overall survival and methylation levels based on 5'-cytosine-phosphate-guanine-3' (CpG) sites. The risk prognostic signature including two candidate genes (LRRC41 and KIAA1429) exhibited robust prognostic predictive accuracy, which was validated in the external testing cohort. Then, the risk score was significantly correlated with the TIME and immune checkpoint blockade (ICB)-related genes. Besides, a prognostic nomogram based on the risk score and clinical stage presented powerful prognostic ability. Additionally, LRRC41 with prognostic value was corroborated to be closely associated with TIME characterization in both expression and methylation levels. Subsequently, the correlation regulatory network uncovered the potential targets of LRRC41 and KIAA1429. Finally, the methylation level of KIAA1429 was correlated with gene mutation status. Conclusion: In summary, this is the first to identify HCC samples into distinct clusters according to DNA methylation and yield the CpG-based prognostic signature and quantitative nomogram to precisely predict prognosis. And the pivotal player of DNA methylation of genes in the TIME and TMB status was explored, contributing to clinical decision-making and personalized prognosis monitoring of HCC.

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Dataset Information

Immunological inflammatory biomarkers as prognostic predictors for advanced hepatocellular carcinoma.

Background

Patients and methods

Results

Conclusions

Publications

Immunological inflammatory biomarkers as prognostic predictors for advanced hepatocellular carcinoma.

Similar Datasets

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