Abstract

e16174 Background: The combination of immune checkpoint inhibitors and anti-angiogenic drugs has been approved as the preferred first-line treatment for advanced hepatocellular carcinoma (HCC). However, only a small subset of HCC patients could benefit from this combination treatment. Methods: The m6A clusters were identified by consistent cluster analysis via R package “consense-cluster plus” based on the expression of 26 m6A regulators. The immune cells infiltration was estimation of by ssGSEA, MCPCOUNT and TIMER 2.0 algorithm. The m6A-related prognosis significant genes were screened by univariate Cox, lasso-Cox and multivariate Cox regression, and the prognosis signature was constructed by multivariate Cox regression. The IC50s of anti-angiogenic drugs in GDSC (Genomics of Drug Sensitivity in Cancer) database were calculated by “pRRophetic” package. The packages “Celldex” and “SingleR” were used to annotate cell types, and to present the expression landscapes of 5 hub genes in different sites and immune cell subpopulations of HCC patients. Results: We identified three m6A clusters with distinct immune and angiogenesis microenvironments. We further constructed a 5-gene prognosis signature (termed as m6Asig-Score) which could predict both immune and anti-angiogenic responses. We illustrated that high m6Asig-Score is associated with poor prognosis, advanced TNM stage, and high TP53 mutation frequency. Besides, the m6Asig-Score was negatively associated with immune checkpoint inhibitors and anti-angiogenic drugs response. We further found that two of the five m6Asig-Score inner genes, B2M and SMOX, were associated with immune cell infiltration, immune response and the sensitivity to sorafenib, which were validated in two independent immunotherapy cohorts and the GDSC database. Conclusions: The m6Asig-Score, B2M and SMOX might have a significant impact on guiding the combined strategy of immunotherapy and anti-angiogenic therapy in HCC.

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