Background TP53 mutation is the most common mutation in hepatocellular carcinoma (HCC), and it affects the progression and prognosis of HCC. We investigated how TP53 mutation regulates the HCC immunophenotype and thus affects the prognosis of HCC. Methods We investigated TP53 mutation status and RNA expression in different populations and platforms and developed an immune prognostic model (IPM) based on immune-related genes that were differentially expressed between TP53 WT and TP53 MUT HCC samples. Then, the influence of the IPM on the immune microenvironment in HCC was comprehensively analysed. Findings TP53 mutation resulted in the downregulation of the immune response in HCC. Thirty-seven of the 312 immune response-related genes were differentially expressed based on TP53 mutation status. An IPM was established and validated based on 865 patients with HCC to differentiate patients with a low or high risk of poor survival. A nomogram was also established for clinical application. Functional enrichment analysis showed that the humoral immune response and immune system diseases pathway represented the major function and pathway, respectively, related to the IPM genes. Moreover, we found that the patients in the high-risk group had higher fractions of T cells follicular helper, T cells regulatory (Tregs) and macrophages M0 and presented higher expression of CTLA-4, PD-1 and TIM-3 than the low-risk group. Interpretation TP53 mutation is strongly related to the immune microenvironment in HCC. Our IPM, which is sensitive to TP53 mutation status, may have important implications for identifying subgroups of HCC patients with low or high risk of unfavourable survival. Fund This work was supported by the International Science and Technology Cooperation Projects (2016YFE0107100), the Capital Special Research Project for Health Development (2014-2-4012), the Beijing Natural Science Foundation (L172055 and 7192158), the National Ten Thousand Talent Program, the Fundamental Research Funds for the Central Universities (3332018032), and the CAMS Innovation Fund for Medical Science (CIFMS) (2017-I2M-4-003 and 2018-I2M-3-001).

With the development of new advances in hepatocellular carcinoma (HCC) management and noninvasive radiological techniques, high‐risk patient groups such as those with hepatitis virus are closely monitored. HCC is increasingly diagnosed early, and treatment may be successful. In spite of this progress, most patients who undergo a hepatectomy will eventually relapse, and the outcomes of HCC patients remain unsatisfactory. In our study, we aimed to identify potential gene biomarkers based on RNA sequencing data to predict and improve HCC patient survival. The gene expression data and clinical information were acquired from The Cancer Genome Atlas (TCGA) database. A total of 339 differentially expressed genes (DEGs) were obtained between the HCC (n = 374) and normal tissues (n = 50). Four genes (CENPA, SPP1, MAGEB6 and HOXD9) were screened by univariate, Lasso and multivariate Cox regression analyses to develop the prognostic model. Further analysis revealed the independent prognostic capacity of the prognostic model in relation to other clinical characteristics. The receiver operating characteristic (ROC) curve analysis confirmed the good performance of the prognostic model. Then, the prognostic model and the expression levels of the four genes were validated using the Gene Expression Omnibus (GEO) dataset. A nomogram comprising the prognostic model to predict the overall survival was established, and internal validation in the TCGA cohort was performed. The predictive model and the nomogram will enable patients with HCC to be more accurately managed in trials testing new drugs and in clinical practice.

BackgroundThe gut microbiome is associated with the response to immunotherapy for different cancers. However, the impact of the gut microbiome on hepatobiliary cancers receiving immunotherapy remains unknown. This study aims to investigate the relationship between the gut microbiome and the clinical response to anti-programmed cell death protein 1 (PD-1) immunotherapy in patients with advanced hepatobiliary cancers.MethodsPatients with unresectable hepatocellular carcinoma or advanced biliary tract cancers who have progressed from first-line chemotherapy (gemcitabine plus cisplatin) were enrolled. Fresh stool samples were collected before and during anti-PD-1 treatment and analyzed with metagenomic sequencing. Significantly differentially enriched taxa and prognosis associated taxa were identified. The Kyoto Encyclopedia of Genes and Genomes database and MetaCyc database were further applied to annotate the differentially enriched taxa to explore the potential mechanism of the gut microbiome influencing cancer immunotherapy.ResultsIn total, 65 patients with advanced hepatobiliary cancers receiving anti-PD-1 treatment were included in this study. Seventy-four taxa were significantly enriched in the clinical benefit response (CBR) group and 40 taxa were significantly enriched in the non-clinical benefit (NCB) group. Among these taxa, patients with higher abundance of Lachnospiraceae bacterium-GAM79 and Alistipes sp Marseille-P5997, which were significantly enriched in the CBR group, achieved longer progression-free survival (PFS) and overall survival (OS) than patients with lower abundance. Higher abundance of Ruminococcus calidus and Erysipelotichaceae bacterium-GAM147 enriched in the CBR group was also observed in patients with better PFS. In contrast, worse PFS and OS were found in patients with higher abundance of Veillonellaceae, which was significantly enriched in the NCB group. Functional annotation indicated that the taxa enriched in the CBR group were associated with energy metabolism while the taxa enriched in the NCB group were associated with amino acid metabolism, which may modulate the clinical response to immunotherapy in hepatobiliary cancers. In addition, immunotherapy-related adverse events were affected by the gut microbiome diversity and relative abundance.ConclusionsWe demonstrate that the gut microbiome is associated with the clinical response to anti-PD-1 immunotherapy in patients with hepatobiliary cancers. Taxonomic signatures enriched in responders are effective biomarkers to predict the clinical response and survival benefit of immunotherapy, which might provide a new therapeutic target to modulate the response to cancer immunotherapy.