Immune- and metabolism-related gene signature analysis uncovers the prognostic and immune microenvironments of hepatocellular carcinoma.

BACKGROUND: Metabolic reprogramming is an emerging hallmark that influences the tumour microenvironment (TME) by regulating the behavior of cancer cells and immune cells. The relationship between metabolism and immunity remains elusive. The purpose of this study was to explore the predictive value of immune- and metabolism-related genes in hepatocellular carcinoma (HCC) and their intricate interplay with TME. METHODS: We established the immune- and metabolism-related signature (IMRPS) based on the LIHC cohort from The Cancer Genome Atlas (TCGA) dataset. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis and Cox regression analysis confirmed the prognostic value of IMRPS. We investigated differences in immune cell infiltration, clinical features, and therapeutic response between risk groups. The quantitative real-time PCR (qPCR) was used to confirm the expression of signature genes. Immunohistochemical staining was performed to evaluate immune infiltration features in HCC tissue samples. We conducted cell experiments including gene knockout, cell counting kit-8 (CCK-8), and flow cytometry to explore the role of the IMRPS key gene UCK2 in HCC. RNA-seq was used to further investigate the potential underlying mechanism involved. RESULTS: The IMRPS, composed of four genes, SMS, UCK2, PFKFB4 and MAPT, exhibited significant correlations with survival, immune cell infiltration, clinical features, immune checkpoints and therapeutic response. The IMRPS was shown to be an excellent predictor of HCC prognosis. It could stratify patients appropriately and characterize the TME accurately. The high-risk HCC group exhibited an immunosuppressive microenvironment with abundant M2-like macrophage infiltration, which was confirmed by the immunohistochemistry results. The results of qPCR revealed that the expression of signature genes in 20 HCC tissues was significantly greater than that in adjacent normal tissues. After the key gene UCK2 was knocked out, the proliferation of the Huh7 cell line was significantly inhibited, and monocyte-derived macrophages polarized towards an M1-like phenotype in the coculture system. RNA-seq and GSEA suggested that the phenotypes were closely related to the negative regulation of growth and regulation of macrophage chemotaxis. CONCLUSIONS: This study established a new IMRS for the accurate prediction of patient prognosis and the TME, which is also helpful for identifying new targets for the treatment of HCC.

A novel nomogram to predict the recurrence of hepatocellular carcinoma after liver transplantation using extended selection criteria.

BACKGROUND: Liver transplantations (LTs) with extended criteria have produced surgical results comparable to those obtained with traditional standards. However, it is not sufficient to predict hepatocellular carcinoma (HCC) recurrence after LT according to morphological criteria alone. The present study aimed to construct a nomogram for predicting HCC recurrence after LT using extended selection criteria. METHODS: Retrospective data on patients with HCC, including pathology, serological markers and follow-up data, were collected from January 2015 to April 2020 at Huashan Hospital, Fudan University, Shanghai, China. Logistic least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses were performed to identify and construct the prognostic nomogram. Receiver operating characteristic (ROC) curves, Kaplan-Meier curves, decision curve analyses (DCAs), calibration diagrams, net reclassification indices (NRIs) and integrated discrimination improvement (IDI) values were used to assess the prognostic capacity of the nomogram. RESULTS: A total of 301 patients with HCC who underwent LT were enrolled in the study. The nomogram was constructed, and the ROC curve showed good performance in predicting survival in both the development set (2/3) and the validation set (1/3) (the area under the curve reached 0.748 and 0.716, respectively). According to the median value of the risk score, the patients were categorized into the high- and low-risk groups, which had significantly different recurrence-free survival (RFS) rates (P < 0.01). Compared with the Milan criteria and University of California San Francisco (UCSF) criteria, DCA revealed that the new nomogram model had the best net benefit in predicting 1-, 3- and 5-year RFS. The nomogram performed well for calibration, NRI and IDI improvement. CONCLUSIONS: The nomogram, based on the Milan criteria and serological markers, showed good accuracy in predicting the recurrence of HCC after LT using extended selection criteria.

The m6A-related gene signature stratifies poor prognosis patients and characterizes immunosuppressive microenvironment in hepatocellular carcinoma.

Background: N6-methyladenosine (m6A) is the most abundant epitranscriptomic modification of RNA, which can affect RNA metabolism and protein translation. The m6A modification plays a critical role in cancer development, including hepatocellular carcinoma (HCC). Despite several m6A-related signatures in HCC, most of them lack the necessary validation and the reliability is still elusive. Methods: Differentially expressed genes (DEGs) in the Cancer Genome Atlas were comprehensively analyzed to identify m6A signature associated with HCC prognosis. Gene set enrichment analysis, tumor mutation burden (TMB), immune infiltration, and therapeutic response were evaluated. Importantly, mass spectrometry proteomics and multiplex immunofluorescence assays were performed for validation. Results: The m6A-related protein-coding gene signature was established, which can divide HCC into high-/low-risk subgroups with markedly different overall survival (OS) and clinical stages. Furthermore, we validated its reliability and robustness in our 101 independent HCC specimens using proteomic detection and confirmed that our signature readily identified high-risk HCC patients with 3-year survival rates of 44.1% vs. 71.8% in the low-risk group. Functional analysis indicated that the high-risk group might stimulate the cell cycle and activate oncogenic pathways such as MAPK, mTOR, and VEGF, whereas the low-risk group mainly regulated amino acid, fatty acid, and drug metabolism. Additionally, the high-risk group had more TMB, upregulated immune checkpoint molecule expression, including PD-1, CTLA4, TIM3, and LAG3, and preferentially formed an immunosuppressive microenvironment. Accordingly, potential therapeutic responses showed that high-risk patients were potentially sensitive to inhibitors targeting the cell cycle and MAPK signaling, with patients possibly benefiting from immunotherapy. Moreover, multiplex immunofluorescence assays indicated that high-risk HCC samples displayed distinct immunosuppressive features, with abundant M2-polarized macrophages and T-regulatory cell infiltration. Conclusion: The m6A signature had a prominent capacity to evaluate OS and characterize the tumor immune microenvironment of HCC, which may serve as a useful approach for risk stratification management and provide a valuable clue to choosing rational therapeutic strategies.

Omicron infections profile and vaccination status among 1881 liver transplant recipients: a multi-centre retrospective cohort.

ABSTRACTA wave of Omicron infections rapidly emerged in China in 2022, but large-scale data concerning the safety profile of vaccines and Coronavirus disease 2019 (COVID-19) infection features in liver transplant (LT) recipients have not been collected. Therefore, the aim of this study was to assess the protectiveness and safety profile of the inactivated vaccines in LT patients against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant infections. A multi-centre retrospective study was conducted in a cohort with a history of liver transplantation. A total of 1881 participants (487 vaccinated and 1394 unvaccinated patients) were enrolled from seven centres in China. Fourteen of the participants were infected by Omicron, and 50% patients had over 14 days of viral shedding duration. The protection rate of COVID-19 vaccinations to Omicron was 2.59%. The three breakthrough infections occurred more than 6 months after fully vaccinated. A total of 96 (19.7%) vaccinated patients had adverse events, including fatigue, myalgia, liver dysfunction, swelling, and scleroma. There were more Grade 3 adverse events in the preoperative vaccination group than those in the postoperative vaccination group. Inactivated whole-virion SARS-CoV-2 vaccines are safe in patients with post-liver transplantation. The efficacy of inactivated vaccines decreases after 6 months of vaccination, it is recommended that liver transplant patients get boosted vaccinations as early as possible even when they are fully vaccinated. Although clinical manifestations of Omicron infections were mild in LT patients, unvaccinated patients might have a higher risk of liver dysfunction during infections.

Itaconic acid facilitates inflammation abatement and alleviates liver ischemia-reperfusion injury by inhibiting NF-κB/NLRP3/caspase-1 inflammasome axis.

Background: Ischemia-reperfusion injury (IRI) severely limits the efficacy and donor source of liver transplantation, and the crucial step in alleviating it is to control inflammation. Itaconic acid is a metabolite produced by intrinsic immune cells (especially macrophages) in the inflammatory state and can promote inflammation subsidence. However, its role in liver ischemia-reperfusion is insufficiently clarified. Methods: A mouse liver ischemia-reperfusion model was constructed, and blood and liver tissue samples were collected by sequential euthanasia of mice at pre-set time points. Liver function and inflammatory factor concentrations were measured, and HE staining was conducted. In the hypoxia-reoxygenation model, proteins were collected at pre-set time points, and the expression of NF-κB pathway-associated protein and its downstream inflammation-associated protein NLRP3 and caspase-1 were detected by Western blot, immunohistochemistry, and immunofluorescence. The level of P-P65 in the nucleus was detected by immunofluorescence. Results: In the liver ischemia-reperfusion model, liver function and inflammatory factors were dynamically varied with reperfusion time in mice, and itaconic acid significantly modified liver function and inflammatory status during this process. NF-κB pathway activity was dynamically varied during hypoxia-reoxygenation, and itaconic acid significantly inhibited the activity of the pathway and significantly suppressed the expression of its downstream inflammation-related proteins. Conclusions: Itaconic acid inhibits NF-κB pathway activation and reduces the accumulation of P-P65 in the nucleus. In turn, this reduces NLRP3 and caspase-1 expression of downstream inflammation-related proteins, promotes inflammation regression, and attenuates liver IRI.

Integrated multi-omics analysis identifies ENY2 as a predictor of recurrence and a regulator of telomere maintenance in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and has a high recurrence rate. Accurate prediction of recurrence risk is urgently required for tailoring personalized treatment programs for individual HCC patients in advance. In this study, we analyzed a gene expression dataset from an HCC cohort with 247 samples and identified five genes including ENY2, GPAA1, NDUFA4L2, NEDD9, and NRP1 as the variables for the prediction of HCC recurrence, especially the early recurrence. The Cox model and risks score were validated in two public HCC cohorts (GSE76427 and The Cancer Genome Atlas (TCGA)) and one cohort from Huashan Hospital, which included a total of 641 samples. Moreover, the multivariate Cox regression analysis revealed that the risk score could serve as an independent prognostic factor in the prediction of HCC recurrence. In addition, we found that ENY2, GPAA1, and NDUFA4L2 were significantly upregulated in HCC of the two validation cohorts, and ENY2 had significantly higher expression levels than another four genes in malignant cells, suggesting that ENY2 might play key roles in malignant cells. The cell line analysis revealed that ENY2 could promote cell cycle progression, cell proliferation, migration, and invasion. The functional analysis of the genes correlated with ENY2 revealed that ENY2 might be involved in telomere maintenance, one of the fundamental hallmarks of cancer. In conclusion, our data indicate that ENY2 may regulate the malignant phenotypes of HCC via activating telomere maintenance.

Immune evasion mechanisms and therapeutic strategies in gastric cancer.

Gastric cancer (GC) is a malignancy with a high incidence and mortality. The tumor immune microenvironment plays an important role in promoting cancer development and supports GC progression. Accumulating evidence shows that GC cells can exert versatile mechanisms to remodel the tumor immune microenvironment and induce immune evasion. In this review, we systematically summarize the intricate crosstalk between GC cells and immune cells, including tumor-associated macrophages, neutrophils, myeloid-derived suppressor cells, natural killer cells, effector T cells, regulatory T cells, and B cells. We focus on how GC cells alter these immune cells to create an immunosuppressive microenvironment that protects GC cells from immune attack. We conclude by compiling the latest progression of immune checkpoint inhibitor-based immunotherapies, both alone and in combination with conventional therapies. Anti-cytotoxic T-lymphocyte-associated protein 4 and anti-programmed cell death protein 1/programmed death-ligand 1 therapy alone does not provide substantial clinical benefit for GC treatment. However, the combination of immune checkpoint inhibitors with chemotherapy or targeted therapy has promising survival advantages in refractory and advanced GC patients. This review provides a comprehensive understanding of the immune evasion mechanisms of GC, and highlights promising immunotherapeutic strategies.

Identification and Validation of an Immune-Related lncRNA Signature to Facilitate Survival Prediction in Gastric Cancer.

BACKGROUND: Long noncoding RNAs (lncRNAs) are versatile in functions and can regulate cancer development, including the modulation of cancer immunity. Immune-related lncRNA signatures predicting prognosis have been reported in multiple cancers, but relevant studies in gastric cancer (GC) are still lacking. METHODS: We performed a comprehensive analysis using TCGA and Immport databases and identified an immune-related lncRNA signature by univariate and multivariate Cox regression analysis. qRT-PCR and immunohistochemistry assays were used for further validation. KEGG and GO analysis and ceRNA network establishment were carried out to explore the regulatory functions. RESULTS: We first identified an immune-related lncRNA signature, which can stratify gastric cancer patients into high- and low-risk subgroups and the high-risk cases frequently suffered from shorter overall survival time. Next, we validated the reliability of the lncRNA signature in an independent 75 gastric cancer samples and demonstrated that the three-year survival rate in high-risk patients was only 30.8% versus 66.5% in low-risk counterparts. Functional exploration indicated that the lncRNA signature might participate in multiple cancer-associated processes including cell adhesion and migration, cytokine-receptor interaction and immune evasion. Additionally, we observed that high-risk samples tended to form an immunosuppressive microenvironment, which had more M2-polarized macrophages and Tregs, but fewer CD8 effector T cells within tumors. Moreover, we found that PD-1 and PD-L1 were dramatically upregulated in a subset of high-risk patients with abundant M2 and Treg infiltration, implying these patients may benefit from anti-PD-1 and PD-L1 immunotherapy. CONCLUSIONS: These results showed that the immune-related lncRNA signature had a prominent capacity to predict overall survival and the immune status of microenvironment in gastric cancer. Our findings may be useful for the risk-stratification management and provide a valuable clue to identify proper patients potentially benefit from immune checkpoint therapy in gastric cancer.

Development of a predictive nomogram for early recurrence of hepatocellular carcinoma in patients undergoing liver transplantation.

BACKGROUND: An individual prognostic model that includes inflammation caused by the delayed recovery of liver function after surgery for the early recurrence of hepatocellular carcinoma (HCC) following liver transplantation (LT) has not been well determined. Our aim was to develop a nomogram model for predicting individual survival and early recurrence following LT for patients. METHODS: Retrospective data, including clinical pathology and follow-up data, on HCC patients were collected between October 2016 and October 2019 at Huashan Hospital Affiliated to Fudan University. A nomogram estimating recurrence post-transplantation was constructed using multivariate Cox regression analysis. RESULTS: A total of 210 patients were included in the present study. The multivariate estimators of recurrence consisted of age, maximum tumor diameter, tumor thrombus, microvascular invasion (MVI), alanine aminotransferase and alpha-fetoprotein on postoperative day 7. Nomogram of recurrence-free survival was developed. The calibration and discrimination of the novel model were assessed with the calibration curves and concordance index (C-index). Its reliability and advantages were evaluated by comparing it with the conventional American Joint Committee on Cancer (AJCC) 8th edition staging system using integrated discrimination improvement (IDI) and net reclassification improvement (NRI). In comparison to the AJCC 8th edition staging system, the C-index (development set: 0.796 vs. 0.643, validation set: 0.741 vs. 0.563), the area under the receiver operating characteristic curve (AUC) of the validation set (1-year AUC: 0.732 vs. 0.586, 2-year AUC: 0.705 vs. 0.504), the development set (1-year AUC: 0.799 vs. 0.551, 2-year AUC: 0.801 vs. 0.512), and this model's calibration plots all showed improved performance. In addition, NRI and IDI verified that the nomogram is an accurate prognostic tool. Subsequently, a web calculator was generated to assess the risk of tumor recurrence post-LT. CONCLUSIONS: The nomogram, based on clinical and pathological factors, showed good accuracy in estimating prognostic recurrence and can be used to guide individual patient follow-up and treatment.