Adjuvant Treatment of Hepatocellular Carcinoma: Prospect of Immunotherapy

Unveiling the cytotoxicity of a new gold(I) complex towards hepatocellular carcinoma by inhibiting TrxR activity

Hepatocellular carcinoma (HCC), the predominant type of liver cancer, is an aggressive malignancy with limited therapeutic options. In this study, we assess a collection of newly designed gold(I) phosphine complexes. Remarkably, the compound GC002 exhibits the greatest toxicity to HCC cells and outperforms established medications, such as sorafenib and auranofin, in terms of antitumor efficacy. GC002 triggers irreversible necroptosis in HCC cells by increasing the intracellular accumulation of reactive oxygen species (ROS). Mechanistically, GC002 significantly suppresses the activity of thioredoxin reductase (TrxR), which plays a crucial role in regulating redox homeostasis and is often overexpressed in HCC by binding directly to the enzyme. Our in vivo xenograft study confirms that GC002 possesses remarkable antitumor activity against HCC without severe side effects. These findings not only highlight the novel mechanism of controlling necroptosis via TrxR and ROS but also identify GC002 as a promising candidate for the further development of antitumor agents targeting HCC.

CT radiomics-based biomarkers can predict response to immunotherapy in hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) remains a leading cause of cancer deaths. Despite the rise of immunotherapies, many HCC patients don't benefit. There's a clear need for biomarkers to guide treatment decisions. This research aims to identify such biomarkers by combining radiological data and machine learning. We analyzed clinical and CT imaging data of 54 HCC patients undergoing immunotherapy. Radiologic features were examined to develop a model predicting short-term immunotherapy effects. We utilized 9 machine learning and 2 ensemble learning techniques using RapidMiner for model construction. We conducted the validation of the above feature combination using 29 HCC patients who received immunotherapy from another hospital, and tested and validated it using XGBoost combined with a genetic algorithm. In 54 HCC patients, radiomics features varied significantly between those with partial response (PR) and stable disease (SD). Key features in Gray Level Run Length Matrix (GLRLM) and in adjacent tissues' Intensity Direct, Neighborhood Gray Tone Difference Matrix (NGTDM), and Shape correlated with short-term immunotherapy efficacy. Selected feature combinations of 15, 19, and 8/15 features yielded better outcomes. Deep learning, random forest, and naive bayes outperformed other methods, with Bagging being more reliable than Adaboost. In the validation set of 29 HCC patients, the mentioned feature combination also demonstrated favorable performance. Furthermore, we achieved improved results when employing XGBoost in conjunction with a genetic algorithm for testing and validation. The machine learning model built with CT image features derived from GLCM, GLRLM, IntensityDirect, NGTDM, and Shape can accurately forecast the short-term efficacy of immunotherapy for HCC.

Current advance of nanotechnology in diagnosis and treatment for malignant tumors

Cancer remains a significant risk to human health. Nanomedicine is a new multidisciplinary field that is garnering a lot of interest and investigation. Nanomedicine shows great potential for cancer diagnosis and treatment. Specifically engineered nanoparticles can be employed as contrast agents in cancer diagnostics to enable high sensitivity and high-resolution tumor detection by imaging examinations. Novel approaches for tumor labeling and detection are also made possible by the use of nanoprobes and nanobiosensors. The achievement of targeted medication delivery in cancer therapy can be accomplished through the rational design and manufacture of nanodrug carriers. Nanoparticles have the capability to effectively transport medications or gene fragments to tumor tissues via passive or active targeting processes, thus enhancing treatment outcomes while minimizing harm to healthy tissues. Simultaneously, nanoparticles can be employed in the context of radiation sensitization and photothermal therapy to enhance the therapeutic efficacy of malignant tumors. This review presents a literature overview and summary of how nanotechnology is used in the diagnosis and treatment of malignant tumors. According to oncological diseases originating from different systems of the body and combining the pathophysiological features of cancers at different sites, we review the most recent developments in nanotechnology applications. Finally, we briefly discuss the prospects and challenges of nanotechnology in cancer.

Construction of CDKN2A-related competitive endogenous RNA network and identification of GAS5 as a prognostic indicator for hepatocellular carcinoma

BACKGROUND

Competitive endogenous RNA (ceRNA) is an innovative way of gene expression modulation, which plays a crucial part in neoplasia. However, the intricacy and behavioral characteristics of the ceRNA network in hepatocellular carcinoma (HCC) remain dismal.

AIM

To establish a cyclin dependent kinase inhibitor 2A (CDKN2A)-related ceRNA network and recognize potential prognostic indicators for HCC.

METHODS

The mutation landscape of CDKN2A in HCC was first explored using the cBioPortal database. Differential expression analysis was implemented between CDKN2Ahigh and CDKN2Alow expression HCC samples. The targeted microRNAs were predicted by lncBasev3.0, and the targeted mRNAs were predicted by miRDB, and Targetscan database. The univariate and multivariate analysis were utilized to identify independent prognostic indicators.

RESULTS

CDKN2A was frequently mutated and deleted in HCC. The single-cell RNA-sequencing analysis revealed that CDKN2A participated in cell cycle pathways. The CDKN2A-related ceRNA network-growth arrest specific 5 (GAS5)/miR-25-3p/SRY-box transcription factor 11 (SOX11) was successfully established. GAS5 was recognized as an independent prognostic biomarker, whose overexpression was correlated with a poor prognosis in HCC patients. The association between GAS5 expression and methylation, immune infiltration was explored. Besides, traditional Chinese medicine effective components targeting GAS5 were obtained.

CONCLUSION

This CDKN2A-related ceRNA network provides innovative insights into the molecular mechanism of HCC formation and progression. Moreover, GAS5 might be a significant prognostic biomarker and therapeutic target in HCC.

A nomogram based on 4-lncRNAs signature for improving prognostic prediction of hepatocellular carcinoma

PURPOSE

Long noncoding RNAs (lncRNAs) with abnormal expression are frequently seen in hepatocellular cancer patients (HCC). Previous studies have reported the correlation between lncRNA and prognosis processes of HCC patients. In this research, a graphical nomogram with lncRNAs signatures, T, M phases was developed using the rms R package to estimate the survival rates of HCC patients in year 1, 3, and 5.

METHODS

To find the prognostic lncRNA and create the lncRNA signatures, univariate Cox survival analysis and multivariate Cox regression analysis were chosen. The rms R software package was used to build a graphical nomogram based on lncRNAs signatures to predict the survival rates in of HCC patients in 1, 3, and 5 years. Using "edgeR", "DEseq" R packages to find the differentially expressed genes (DEGs).

RESULTS

Firstly, a total of 5581 DEGs including 1526 lncRNAs and 3109 mRNAs were identified through bioinformatic analysis, of which 4 lncRNAs (LINC00578, RP11-298O21.2, RP11-383H13.1, RP11-440G9.1) were identified to be strongly related to the prognosis of liver cancer (P < 0.05). Moreover, we constructed a 4-lncRNAs signature by using the calculated regression coefficient. 4-lncRNAs signature is identified to significantly correlated with clinical and pathological characteristics (such as T stage, and death status of HCC patients).

CONCLUSIONS

A prognostic nomogram on the base of 4-lncRNAs markers was built, which is capable to accurately predict the 1-year, 3-year, and 5-year survival of HCC patients after the construction of the 4-lncRNAs signature linked with prognosis of HCC.

C-reactive protein to albumin ratio predict responses to programmed cell death-1 inhibitors in hepatocellular carcinoma patients

BACKGROUND

Over the years, programmed cell death-1 (PD-1) inhibitors have been routinely used for hepatocellular carcinoma (HCC) treatment and yielded improved survival outcomes. Nonetheless, significant heterogeneity surrounds the outcomes of most studies. Therefore, it is critical to search for biomarkers that predict the efficacy of PD-1 inhibitors in patients with HCC.

AIM

To investigate the role of the C-reactive protein to albumin ratio (CAR) in evaluating the efficacy of PD-1 inhibitors for HCC.

METHODS

The clinical data of 160 patients with HCC treated with PD-1 inhibitors from January 2018 to November 2022 at the First Affiliated Hospital of Guangxi Medical University were retrospectively analyzed.

RESULTS

The optimal cut-off value for CAR based on progression-free survival (PFS) was determined to be 1.20 using x-tile software. Cox proportional risk model was used to determine the factors affecting prognosis. Eastern Cooperative Oncology Group performance status [hazard ratio (HR) = 1.754, 95% confidence interval (95%CI) = 1.045-2.944, P = 0.033], CAR (HR = 2.118, 95%CI = 1.057-4.243, P = 0.034) and tumor number (HR = 2.932, 95%CI = 1.246-6.897, P = 0.014) were independent prognostic factors for overall survival. CAR (HR = 2.730, 95%CI = 1.502-4.961, P = 0.001), tumor number (HR = 1.584, 95%CI = 1.003-2.500, P = 0.048) and neutrophil to lymphocyte ratio (HR = 1.120, 95%CI = 1.022-1.228, P = 0.015) were independent prognostic factors for PFS. Two nomograms were constructed based on independent prognostic factors. The C-index index and calibration plots confirmed that the nomogram is a reliable risk prediction tool. The ROC curve and decision curve analysis confirmed that the nomogram has a good predictive effect as well as a net clinical benefit.

CONCLUSION

Overall, we reveal that the CAR is a potential predictor of short- and long-term prognosis in patients with HCC treated with PD-1 inhibitors. If further verified, CAR-based nomogram may increase the number of markers that predict individualized prognosis.

An Engineered Influenza a Virus Expressing the Co-Stimulator OX40L as an Oncolytic Agent Against Hepatocellular Carcinoma

Background

Oncolytic virus (OV) therapy has emerged as a promising novel form of immunotherapy. Moreover, an increasing number of studies have shown that the therapeutic efficacy of OV can be further improved by arming OVs with immune-stimulating molecules.

Methods

In this study, we used reverse genetics to produce a novel influenza A virus, termed IAV-OX40L, which contained the immune-stimulating molecule OX40L gene in the influenza virus nonstructural (NS1) protein gene. The oncolytic effect of IAV-OX40L was explored on hepatocellular carcinoma (HCC)HCC cells in vitro and in vivo.

Results

Hemagglutination titers of the IAV-OX40L virus were stably 27-28 in specific-pathogen-free chicken embryos. The morphology and size distribution of IAV-OX40L are similar to those of the wild-type influenza. Expression of OX40L protein was confirmed by Western blot and immunofluorescence. MTS assays showed that the cytotoxicity of IAV-OX40L was higher in HCC cells (HepG2 and Huh7) than in normal liver cells (MIHA) in a time- and dose-dependent manner in vitro. We found that intratumoral injection of IAV-OX40L reduced tumor growth and increased the survival rate of mice compared with PR8-treated controls in vivo. In addition, the pathological results showed that IAV-OX40L selectively destroyed tumor tissues without harming liver and lung tissues. CD4+ and CD8+ T cells of the IAV-OX40L group were significantly increased in the splenic lymphocytes of mice. Further validation confirmed that IAV-OX40L enhanced the immune response mainly by activating Th1-dominant immune cells, releasing interferon-γ and interleukin-2.

Conclusion

Taken together, our findings demonstrate the novel chimeric influenza OV could provide a potential therapeutic strategy for combating HCC and improve the effectiveness of virotherapy for cancer therapy.

Oxoaporphine Pr(III) complex inhibits hepatocellular carcinoma progression and metastasis by disrupting tumor cell-macrophage crosstalk

Tumor cells and macrophages communicate through the secretion of various cytokines to jointly promote the malignant development of cancers. We synthesized and characterized an oxoaporphine Pr(III) complex (PrL3(NO3)3) and found that it inhibits hepatocellular carcinoma (HCC) progression and metastasis by disrupting HCC cell-macrophage crosstalk. PrL3(NO3)3 treatment upregulated CD86, TNF-α, and IL-1β and downregulated CD163, CD206, CCL2, and VEGFA in macrophages. Our mRNA-Seq results demonstrated that PrL3(NO3)3 inhibited macrophage M2-like polarization by inhibiting the AMPK pathway and activating the NF-κB pathway by upregulating RelA/p65 Ser536 phosphorylation. This kind of macrophage polarization significantly inhibited HCC cell proliferation, migration, and invasion. In addition, PrL3(NO3)3 inhibited the migration, invasion, and chemotaxis of HCC cells by downregulating the expression of EMT-related markers and CCL2. hTFtarget database analysis revealed that PrL3(NO3)3 inhibited NF-κB nuclear translocation by upregulating RelA/p65 Ser536 phosphorylation in HCC cells, thereby downregulating the expression of Snail and CCL2. HCC tissue microarray analysis revealed that downregulation of RelA/p65 Ser536 phosphorylation is a driving event in HCC malignant progression. In conclusion, PrL3(NO3)3 effectively inhibits HCC cell-macrophage crosstalk by upregulating RelA/p65 Ser536 phosphorylation. This is the first report of a lanthanide complex exerting regulatory effects on both tumors and tumor-associated macrophages, providing a new strategy for the development of effective antitumor drugs.

Adjuvant and neoadjuvant therapies for hepatocellular carcinoma

Immune-oncology-based regimens have shown efficacy in advanced HCC and have been implemented as standard of care as first-line therapy. Their efficacy, including high response rates, and safety justify their evaluation in earlier disease stages. Following negative results for adjuvant sorafenib in the global STORM trial in 2015, 4 global phase 3 trials, featuring different immune checkpoint inhibitor combinations, entered in parallel the race in the adjuvant setting. The IMbrave050 trial, comparing adjuvant atezolizumab in combination with bevacizumab to active surveillance following curative-intent resection or ablation, was the first to report, fast-tracking the results of the first interim analysis and demonstrating an improvement in recurrence-free survival. The trial has provoked a discussion on the horizon of expectations from adjuvant treatment and the clinical relevance of efficacy endpoints. Moreover, major pathological responses reported from early phase 2 data in the neoadjuvant setting provide a strong rationale for the evaluation of these concepts in phase 3 trials. In this review, we summarize current evidence and outline future directions for systemic therapies in early-stage HCC.

Atezolizumab plus bevacizumab versus active surveillance in patients with resected or ablated high-risk hepatocellular carcinoma (IMbrave050): a randomised, open-label, multicentre, phase 3 trial

BACKGROUND

No adjuvant treatment has been established for patients who remain at high risk for hepatocellular carcinoma recurrence after curative-intent resection or ablation. We aimed to assess the efficacy of adjuvant atezolizumab plus bevacizumab versus active surveillance in patients with high-risk hepatocellular carcinoma.

METHODS

In the global, open-label, phase 3 IMbrave050 study, adult patients with high-risk surgically resected or ablated hepatocellular carcinoma were recruited from 134 hospitals and medical centres in 26 countries in four WHO regions (European region, region of the Americas, South-East Asia region, and Western Pacific region). Patients were randomly assigned in a 1:1 ratio via an interactive voice-web response system using permuted blocks, using a block size of 4, to receive intravenous 1200 mg atezolizumab plus 15 mg/kg bevacizumab every 3 weeks for 17 cycles (12 months) or to active surveillance. The primary endpoint was recurrence-free survival by independent review facility assessment in the intention-to-treat population. This trial is registered with ClinicalTrials.gov, NCT04102098.

FINDINGS

The intention-to-treat population included 668 patients randomly assigned between Dec 31, 2019, and Nov 25, 2021, to either atezolizumab plus bevacizumab (n=334) or to active surveillance (n=334). At the prespecified interim analysis (Oct 21, 2022), median duration of follow-up was 17·4 months (IQR 13·9-22·1). Adjuvant atezolizumab plus bevacizumab was associated with significantly improved recurrence-free survival (median, not evaluable [NE]; [95% CI 22·1-NE]) compared with active surveillance (median, NE [21·4-NE]; hazard ratio, 0·72 [adjusted 95% CI 0·53-0·98]; p=0·012). Grade 3 or 4 adverse events occurred in 136 (41%) of 332 patients who received atezolizumab plus bevacizumab and 44 (13%) of 330 patients in the active surveillance group. Grade 5 adverse events occurred in six patients (2%, two of which were treatment related) in the atezolizumab plus bevacizumab group, and one patient (<1%) in the active surveillance group. Both atezolizumab and bevacizumab were discontinued because of adverse events in 29 patients (9%) who received atezolizumab plus bevacizumab.

INTERPRETATION

Among patients at high risk of hepatocellular carcinoma recurrence following curative-intent resection or ablation, recurrence-free survival was improved in those who received atezolizumab plus bevacizumab versus active surveillance. To our knowledge, IMbrave050 is the first phase 3 study of adjuvant treatment for hepatocellular carcinoma to report positive results. However, longer follow-up for both recurrence-free and overall survival is needed to assess the benefit-risk profile more fully.

FUNDING

F Hoffmann-La Roche/Genentech.

The effect of liver disease on hepatic microenvironment and implications for immune therapy

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and the fourth leading cause of cancer-related death worldwide. HCC often occurs in the setting of chronic liver disease or cirrhosis. Recent evidence has highlighted the importance of the immune microenvironment in the development and progression of HCC, as well as its role in the potential response to therapy. Liver disease such as viral hepatitis, alcohol induced liver disease, and non-alcoholic fatty liver disease is a major risk factor for the development of HCC and has been demonstrated to alter the immune microenvironment. Alterations in the immune microenvironment may markedly influence the response to different therapeutic strategies. As such, research has focused on understanding the complex relationship among tumor cells, immune cells, and the surrounding liver parenchyma to treat HCC more effectively. We herein review the immune microenvironment, as well as the relative effect of liver disease on the immune microenvironment. In addition, we review how changes in the immune microenvironment can lead to therapeutic resistance, as well as highlight future strategies aimed at developing the next-generation of therapies for HCC.

Treatment and Prognosis of Fibrolamellar Hepatocellular Carcinoma: a Systematic Review of the Recent Literature and Meta-analysis

BACKGROUND

Fibrolamellar hepatocellular carcinoma (FL-HCC) is a rare disease and current efforts are focused on the prognosis and on the development of efficient and specific treatments. This study aimed to review the latest evidence regarding FL-HCC treatment and prognosis.

METHODS

A systematic review of the literature over the past 10 years regarding FL-HCC, and meta-analysis of 1-, 3-, and 5-year overall survival (OS) comparing FL-HCC and conventional HCC were performed.

RESULTS

Overall, 1567 articles were screened, of them 21 were selected for the systematic review, and 6 for meta-analysis. Twenty-one studies included a total of 2168 patients with FL-HCC, with a median age ranging from 11 to 56 years. The majority of patients underwent surgical resection or liver transplantation. After a median follow-up ranging from 24 to 58 months, 1-year OS was 67-100% and 5-year OS was 28-65%. A total of 743 patients with FL-HCC and 163,472 with conventional HCC were included in the meta-analysis. There was a significantly improved 1-, 3-, and 5-years OS in the FL-HCC group compared to the conventional HCC group, although high heterogeneity was found. When excluding population-based studies, and including 96 FL-HCC and 221 conventional HCC patients, the heterogeneity was low, and the meta-analysis showed a significantly longer 1-year OS in patients with FL-HCC than conventional HCC; however, there were no differences at 3- and 5-years OS.

CONCLUSIONS

Surgical resection for FL-HCC is currently the only curative treatment available. FL-HCC is plagued by high-recurrence rates and poor long-term outcomes which may be related to the absence of specific treatment for advanced and recurrent disease.

Interval dynamics of transplantability for hepatocellular carcinoma after primary curative resection: risk factors for nontransplantable recurrence

BACKGROUND

To investigate the changes in transplantability between primary and recurrent Hepatocellular carcinoma (HCC) after hepatic resection (HR) and the risk factors for nontransplantable recurrence (NTR).

METHODS

Consecutive 3122 patients who received HR for primary HCC between 2001 and 2019 were analyzed for changes in transplantability. Predictors of survival and NTR were evaluated using a competing risk analysis.

RESULTS

After a median follow-up of 78.3 months, the 5-year overall survival rate was 82.6%. Also, 58.2% of them developed recurrence after a median of 45.6 months. Recurrence occurred in 1205 and 611 patients with primary transplantable and nontransplantable HCC, respectively, of whom 26.1% and 63.2%, respectively, had NTR. Tumor diameter >3 cm [subdistribution hazard ratios (95% CI), 2.00 (1.62-2.48)], major resection [1.20 (1.00-1.43)], pathological grade >2 [1.28 (1.07-1.52)], microvascular invasion [1.74 (1.45-2.08)], and early recurrence (<1 year) [9.22 (7.83-10.87)] were associated with NTR. The overall transplantable pool increased from 72.3% to 77.5%.

CONCLUSION

Microvascular invasion and early recurrence were risk factors for NTR. Nonetheless, the transplantable pool increased after HR, 41.8% of the patients had no recurrence and may not require liver transplantation. If the patient's liver function is acceptable, HR should be considered the treatment of choice for HCC.

Development of preoperative prognostic models including radiological features for survival of singular nodular HCC patients

BACKGROUND

Early singular nodular hepatocellular carcinoma (HCC) is an ideal surgical indication in clinical practice. However, almost half of the patients have tumor recurrence, and there is no reliable prognostic prediction tool. Besides, it is unclear whether preoperative neoadjuvant therapy is necessary for patients with early singular nodular HCC and which patient needs it. It is critical to identify the patients with high risk of recurrence and to treat these patients preoperatively with neoadjuvant therapy and thus, to improve the outcomes of these patients. The present study aimed to develop two prognostic models to preoperatively predict the recurrence-free survival (RFS) and overall survival (OS) in patients with singular nodular HCC by integrating the clinical data and radiological features.

METHODS

We retrospective recruited 211 patients with singular nodular HCC from December 2009 to January 2019 at Eastern Hepatobiliary Surgery Hospital (EHBH). They all met the surgical indications and underwent radical resection. We randomly divided the patients into the training cohort (n =132) and the validation cohort (n = 79). We established and validated multivariate Cox proportional hazard models by the preoperative clinicopathologic factors and radiological features for association with RFS and OS. By analyzing the receiver operating characteristic (ROC) curve, the discrimination accuracy of the models was compared with that of the traditional predictive models.

RESULTS

Our RFS model was based on HBV-DNA score, cirrhosis, tumor diameter and tumor capsule in imaging. RFS nomogram had fine calibration and discrimination capabilities, with a C-index of 0.74 (95% CI: 0.68-0.80). The OS nomogram, based on cirrhosis, tumor diameter and tumor capsule in imaging, had fine calibration and discrimination capabilities, with a C-index of 0.81 (95% CI: 0.74-0.87). The area under the receiver operating characteristic curve (AUC) of our model was larger than that of traditional liver cancer staging system, Korea model and Nomograms in Hepatectomy Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma, indicating better discrimination capability. According to the models, we fitted the linear prediction equations. These results were validated in the validation cohort.

CONCLUSIONS

Compared with previous radiography model, the new-developed predictive model was concise and applicable to predict the postoperative survival of patients with singular nodular HCC. Our models may preoperatively identify patients with high risk of recurrence. These patients may benefit from neoadjuvant therapy which may improve the patients' outcomes.

Combined iodine-125 seed strand, portal vein stent, transarterial chemoembolization, lenvatinib and anti-PD-1 antibodies therapy for hepatocellular carcinoma and Vp4 portal vein tumor thrombus: A propensity-score analysis

Objective

To evaluate the safety and efficacy of interventional therapy (iodine-125[¹²⁵I] seed strand and portal vein stent [PVS] implantation plus transarterial chemoembolization [TACE]) combined with systemic therapy (lenvatinib plus anti-PD-1 antibody) as first-line treatment for hepatocellular carcinoma (HCC) patients with Vp4 portal vein tumor thrombus (PVTT).

Patients and methods

From December 2018 to October 2021, 87 HCC patients with Vp4 PVTT were included in this single-center retrospective study. Forty-seven patients underwent interventional therapy combined with lenvatinib and anti-PD-1 antibody (group A), while 40 cases underwent interventional therapy combined with lenvatinib only (group B). Overall response rate (ORR), stent occlusion rates (SOR), median overall survival (OS), median progression-free survival (PFS) and median stent patency time (SPT) were compared between the 2 groups.

Results

The mean intended dose (r = 10 mm; z = 0; 240 days) was 64.9 ± 1.0 Gy and 64.5 ± 1.1 Gy in group A and B, respectively (p = 0.133). ORR and SOR were significantly different between group A and B (ORR, 55.3% vs 17.5%, p < 0.001; SOR, 12.8% vs 35.0%, p = 0.014). In the propensity-score matching (PSM) cohort, the median OS, median PFS and median SPT were significantly longer in group A compared with group B (32 PSM pairs; OS, 17.7 ± 1.7 vs 12.0 ± 0.8 months, p = 0.010; PFS, 17.0 ± 4.3 vs 8.0 ± 0.7 months, p < 0.001; SPT, not-reached vs 12.5 ± 1.1 months, p = 0.028).

Conclusion

This interventional therapy combined with lenvatinib and anti-PD-1 antibody is safe and effective for HCC patients with Vp4 PVTT.

Prospective validation of the Eastern Staging in predicting survival after surgical resection for patients with hepatocellular carcinoma: a multicenter study from China

BACKGROUND

The Eastern Staging System, which was specially developed for patients undergoing surgical resection for hepatocellular carcinoma (HCC), has been proposed for more than ten years. To prospectively validate the predictive accuracy of the Eastern staging on long-term survival after HCC resection.

METHODS

Patients who underwent hepatectomy for HCC from 2011 to 2020 at 10 Chinese hospitals were identified from a prospectively collected database. The survival predictive accuracy was evaluated and compared between the Eastern Staging with six other staging systems, including the JIS, BCLC, Okuda, CLIP, 8th AJCC TNM, and HKLC staging.

RESULTS

Among 2365 patients, the 1-, 3-, and 5-year overall survival rates were 84.2%, 64.5%, and 52.6%, respectively. Among these seven staging systems, the Eastern staging was associated with the best monotonicity of gradients (linear trend χ²: 408.5) and homogeneity (likelihood ratio χ²: 447.3), and the highest discriminatory ability (the areas under curves for 1-, 3-, and 5-year mortality: 0.776, 0.787, and 0.768, respectively). In addition, the Eastern staging was the most informative staging system in predicting survival (Akaike information criterion: 2982.33).

CONCLUSION

Using a large multicenter prospectively collected database, the Eastern Staging was found to show the best predictive accuracy on long-term overall survival in patients with resectable HCC than the other 6 commonly-used staging systems.

Adjuvant therapy following curative treatments for hepatocellular carcinoma: current dilemmas and prospects

Curative surgical treatments, mainly liver resection, are still one of the optimal options for patients with early-, mid-, and even progression-stage hepatocellular carcinoma (HCC). However, the recurrence rate within 5 years after surgery is as high as 70%, especially in patients with high risk factors for recurrence, most of whom experience early recurrence within 2 years. Effective adjuvant therapy may improve prognosis, previous studies found that adjuvant transarterial chemoembolization, antiviral, and traditional Chinese medicine et al. were helpful in preventing HCC recurrence. Nevertheless, due to controversial results or lack of high-level evidence, there is no standardized postoperative management protocol worldwide at present. Continued exploration of effective postoperative adjuvant treatments to improve surgical prognosis is necessary.

Immunological function and prognostic value of lymphoid-specific helicase in liver hepatocellular carcinoma

BACKGROUND

Lymphoid-specific helicase (HELLS), a SNF2-like chromatin-remodeling enzyme, plays a key role in tumor progression via its DNA methylation function. However, the effects of HELLS on immune infiltration and prognosis in liver hepatocellular carcinoma (LIHC) remain uncertain.

METHODS

The Tumor Immune Estimation Resource (TIMER) database was employed to explore the pan-cancer mRNA expression of HELLS and its correlation with immunity. GEPIA2 was used to verify the correlation between HELLS expression and survival. The role of HELLS in cancer was explored via gene set enrichment analysis (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes) and the construction of gene-gene and protein-protein interaction networks (PPI). Additionally, correlations between DNA methylation, HELLS expression, and immune-related genes were explored in LIHC. HELLS expression in LIHC clinical samples was determined using qRT-PCR and western blotting. The effects of downregulated HELLS expression in hepatocellular carcinoma cells was explored via transfection experiments in vitro.

RESULTS

High HELLS mRNA expression was identified in several cancers and was significantly associated with poorer prognosis in LIHC. Furthermore, HELLS expression was positively correlated with tumor-infiltrating lymphocytes and immune checkpoint genes in LIHC. Bioinformatics analysis suggested that DNA methylation of HELLS may be associated with the immune response. Results from the TCGA-LIHC dataset, clinical samples, and functional analysis indicated that HELLS contributed to tumor progression in LIHC.

CONCLUSION

The study findings demonstrate that HELLS is an important factor in promoting LIHC malignancy and might serve as a potential biomarker for LIHC.

Systemic T-cell and humoral responses against cancer testis antigens in hepatocellular carcinoma patients

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related deaths worldwide due to high recurrence rates after curative treatment and being frequently diagnosed at an advanced stage. Immune-checkpoint inhibition (ICPI) has yielded impressive clinical successes in a variety of solid cancers, however results in treatment of HCC have been modest. Vaccination could be a promising treatment to synergize with ICPI and enhance response rates. Cancer testis antigens (CTAs) were recently discovered to be widely expressed in HCC and expression in macroscopically tumor-free tissues correlated with recurrence, implying the presence of micro-satellites. To determine whether CTAs are immunogenic in HCC patients, we analyzed systemic T-cell and humoral responses against seven CTAs in 38 HCC patients using a multitude of techniques; flowcytometry, ELISA and whole antigen and peptide stimulation assays. CTA-specific T-cells were detected in all (25/25) analyzed patients, of which most had a memory phenotype but did not exhibit unequivocal signs of chronic stimulation or recent antigen encounter. Proliferative CD4⁺ and CD8⁺ T-cell responses against these CTAs were found in 14/16 analyzed HCC patients. CTA-peptide stimulation-induced granzyme B, IL2, and TNFa in 8/8 analyzed patients, including two MAGEA1 peptides included based on in silico prediction. Finally, IgG responses were observed in 13/32 patients, albeit with low titers. The presence of CD4⁺ and CD8⁺ T-cells and IgG responses shows the immunogenicity of these CTAs in HCC-patients. We hypothesize that vaccines based on these tumor-specific antigens may boost preexisting CTA-specific immunity and could enhance therapeutic efficacy of ICPI in advanced HCC.

The Role of Radiomics and AI Technologies in the Segmentation, Detection, and Management of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common primary hepatic neoplasm. Thanks to recent advances in computed tomography (CT) and magnetic resonance imaging (MRI), there is potential to improve detection, segmentation, discrimination from HCC mimics, and monitoring of therapeutic response. Radiomics, artificial intelligence (AI), and derived tools have already been applied in other areas of diagnostic imaging with promising results. In this review, we briefly discuss the current clinical applications of radiomics and AI in the detection, segmentation, and management of HCC. Moreover, we investigate their potential to reach a more accurate diagnosis of HCC and to guide proper treatment planning.

Identification of an Oxidative Stress-Related LncRNA Signature for Predicting Prognosis and Chemotherapy in Patients With Hepatocellular Carcinoma

Background: Oxidative stress plays a critical role in oncogenesis and tumor progression. However, the prognostic role of oxidative stress-related lncRNA in hepatocellular carcinomas (HCC) has not been fully explored. Methods: We used the gene expression data and clinical data from The Cancer Genome Atlas (TCGA) database to identify oxidative stress-related differentially expressed lncRNAs (DElncRNAs) by pearson correlation analysis. A four-oxidative stress-related DElncRNA signature was constructed by LASSO regression and Cox regression analyses. The predictive signature was further validated by Kaplan-Meier (K-M) survival analysis, receiver operating characteristic (ROC) curves, nomogram and calibration plots, and principal component analysis (PCA). Single-sample gene set enrichment analysis (ssGSEA) was used to explore the relationship between the signature and immune status. Finally, the correlation between the signature and chemotherapeutic response of HCC patients was analyzed. Results: In our study, the four-DElncRNA signature was not only proved to be a robust independent prognostic factor for overall survival (OS) prediction, but also played a crucial role in the regulation of progression and chemotherapeutic response of HCC. ssGSEA showed that the signature was correlated with the infiltration level of immune cells. HCC patients in high-risk group were more sensitive to the conventional chemotherapeutic drugs including Sorafenib, lapatinib, Nilotinib, Gefitinib, Erlotinib and Dasatinib, which pave the way for targeting DElncRNA-associated treatments for HCC patients. Conclusion: Our study has originated a prognostic signature for HCC based on oxidative stress-related DElncRNAs, deepened the understanding of the biological role of four key DElncRNAs in HCC and laid a theoretical foundation for the choice of chemotherapy.

Prior Knowledge-Aware Fusion Network for Prediction of Macrovascular Invasion in Hepatocellular Carcinoma

Macrovascular invasion (MaVI) is a major threat to survival in hepatocellular carcinoma (HCC), which should be treated as early as possible to ensure safety and efficacy. In this aspect, MaVI prediction can be helpful. However, MaVI prediction is difficult because of the inter-class similarity and intra-class variation of HCC in computed tomography (CT) images. Moreover, existing methods fail to include clinical priori knowledge associated with HCC, leading to incomprehensive information extraction. In this paper, we proposed a prior knowledge-aware fusion network (PKAFnet) to accurately achieve MaVI prediction in CT images. First, a perception module was presented to extract features related to tumor marginal heterogeneity in the graph domain, which contributed to rotation invariance and captured intensity variations of tumor margin. Second, a tumor segmentation network was built to obtain global information of a 3D tumor image and information associated with tumor internal heterogeneity in the image domain. Finally, multi-domain features associated with the tumor margin and tumor region were combined by using a multi-domain attentional feature fusion module. Thus, by incorporating MaVI-related prior knowledge, our PKAFnet can alleviate overfitting, which can improve the discriminative ability. The proposed PKAFnet was validated on a multi-center dataset, and remarkable performance was achieved in an independent testing set. Moreover, the interpretability of perception module and segmentation network were presented in our paper, which illustrated the effectiveness and credibility of PKAFnet. Therefore, the proposed method showed great application potential for MaVI prediction.

Feasibility of hepatocellular carcinoma treatment based on the tumor microenvironment

The incidence of liver cancer is extremely high worldwide and poses a serious threat to human life and health. But at present, apart from radiotherapy, chemotherapy, liver transplantation, and early resection, sorafenib was the main systemic therapy proven to have clinical efficacy for unresectable liver cancer (HCC) until 2017. Despite the emerging immunotherapy in the past decade with immune inhibitors such as PD - 1 being approved and applied to clinical treatment, there are still some patients with no response. This review aims to elucidate the mechanisms underlying the tumor microenvironment of hepatocellular carcinoma and thus analyze the effectiveness of targeting the tumor microenvironment to improve the therapeutic efficacy of hepatocellular carcinoma, including the effectiveness and feasibility of immunotherapy, tumor oncolytic viruses and anti-vascular proliferation therapy.

M6A Modifier-Mediated Methylation Characterized by Diverse Prognosis, Tumor Microenvironment, and Immunotherapy Response in Hepatocellular Carcinoma

Objective. Emerging evidence highlights the clinical implications of N6-methyladenosine (m6A) modification in HCC. Yet, the roles of m6A modification in modulating cancer immunity and shaping tumor microenvironment (TME) are undefined in hepatocellular carcinoma (HCC). Methods. Here, m6A modification classification was determined for HCC through 23 m6A modifier levels by employing consensus clustering approach. Prognosis analysis was presented for comparing the differences in survival outcomes. The ssGSEA and ESTIMATE approaches were adopted for evaluating the abundances of tumor-infiltrating immune cell populations. The m6A scoring system was computed for reflecting m6A modification classification via PCA algorithm. Results. Three m6A modifier-mediated modification patterns were established among HCC specimens, which were characterized by different prognosis, signaling pathways, and TME features. After extracting m6A phenotype-associated DEGs, we determined m6A scores in individual HCC and stratified patients into high- and low-score groups. Patients with low m6A score displayed the survival advantage and higher sensitivity to gemcitabine. Moreover, those with low m6A score possessed the better anti-PD-1/PD-L1 therapeutic response in the IMvigor210 immunotherapy cohort. Conclusion. Our findings highlighted that m6A modification exerted a nonnegligible role in remodeling diverse and complex TME. Quantification of the m6A modification patterns of individual HCC may enhance the comprehension of TME features and facilitate immunotherapeutic plans.

Experimental drug treatments for hepatocellular carcinoma: Clinical trial failures 2015 to 2021

INTRODUCTION

Hepatocellular carcinoma (HCC) is a major health problem worldwide with limited systemic therapy options. Since the approval of sorafenib in 2008, no systemic therapy has provided a sustained/robust/survival benefit for patients with advanced HCC until recently. Many initially promising therapies have been trialed, but survival outcomes remained stagnant. As such, knowledge concerning previous treatment failures may help guide further areas of study, as well inform future therapeutic approaches.

AREA COVERED

This article reviews recent advances in the treatment of HCC. Despite some recent success, many systemic and locoregional therapies have failed to produce significant improvements in outcome. These treatment failures are examined and insight into pathways for future success are discussed.

EXPERT OPINION

Combination atezolizumab and bevacizumab has changed the landscape of systemic treatment for patients with HCC when it became the first therapy after demonstrating improve outcomes over sorafenib. Clinical trials in patients with advanced HCC have inherent difficulty with challenges to determine if a patient's declining liver function is secondary to disease progression, worsening cirrhosis, or drug toxicity, which may skew results. As we gain more knowledge of underlying genetic alterations behind the pathophysiology of the development of HCC, molecular markers may be identified to assist in predicting which patients would respond to a specific therapy.

ALYREF associated with immune infiltration is a prognostic biomarker in hepatocellular carcinoma

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ALYREF is a potential prognostic marker for hepatocellular carcinoma.

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ALYREF affects the biological function of hepatocellular carcinoma cells.

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ALYREF is associated with immune infiltration in hepatocellular carcinoma.

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The model constructed based on ALYREF-related immune genes provides a reference for the evaluation of immunotherapy.

Background

Although ALYREF has been demonstrated to have a role in a number of malignancies, its role in hepatocellular carcinoma (HCC) has received little attention. Our objective was to research at the prognostic value, biological role and relevance of ALYREF to the immune system in HCC.

Methods

The expression of ALYREF and its relationship with clinical parameters of HCC patients were analyzed by liver cancer cohort (LIHC) of The Cancer Genome Atlas. The expression and prognosis were verified by immunohistochemistry experiments. Gene transfection, CCK-8, scratch healing, transwell invasion and flow cytometry were used to assess the molecular function of ALYREF in vitro. The TIMER and TISIDB online data portals were used to assess the relevance of ALYREF to immunization. Stepwise regression analysis of ALYREF-related immune genes in the LIHC training set was used to construct a prognostic risk prediction model. Also, construct a nomogram to predict patient survival. The testing set for internal verification.

Results

Knockdown of ALYREF changed the biological phenotypes of HCC cells, such as proliferation, apoptosis, and invasion. In addition, the expression of ALYREF in HCC affected the level of immune cell infiltration and correlated with the overall survival time of patients. The constructed immune prognostic model allows for a valid assessment of patients.

Conclusion

ALYREF is increased in HCC, has an impact on cellular function and the immune system, and might be used as a prognostic marker.

Characteristics and Clinical Significance of T-Cell Receptor Repertoire in Hepatocellular Carcinoma

Several studies have demonstrated that the T-cell receptor (TCR) repertoire is associated with prognosis and immune therapy response in several types of cancer. However, the comprehensive features of TCR repertoire in tumor-infiltrating and circulating T cells, as well as its clinical significance of diagnosis in hepatocellular carcinoma (HCC) patients, are still unknown. In this study, we perform paired tumor/peritumoral tissues and peripheral blood samples from 58 patients with HCC and sequenced them with high-throughput TCR to comprehensively analyze the characteristics of TCR and the clinical significance of peripheral TCR sequence. By exploring the abundance and diversity of TCR repertoires, we observe that there was a significantly higher TCR diversity in peripheral blood than in tumoral and peritumoral tissues, while tumoral and peritumoral tissues showed similar TCR diversity. A substantial difference in the usage frequencies of several Vβ, Jβ genes, and TCRβ VJ pairings was found among three types of tissues. Moreover, we reveal that HCC patients have a unique profile of TCR repertoire in peripheral blood in contrast to healthy individuals. We further establish an HCC diagnostic model based on TCRβ VJ pairing usage in peripheral blood, which yields a best-fit area under the curve (AUC) of 0.9746 ± 0.0481 (sensitivity = 0.9675 ± 0.0603, specificity = 0.9998 ± 0.0007, average of 100 repeats) in the test set. Our study describes the characteristics of tissue infiltration and circulating T-cell bank in patients with HCC and shows the potential of using circulating TCR sequence as a biomarker for the non-invasive diagnosis of patients with HCC.

An Integrated Fibrosis Signature for Predicting Survival and Immunotherapy Efficacy of Patients With Hepatocellular Carcinoma

Introduction: Fibrosis, a primary cause of hepatocellular carcinoma (HCC), is intimately associated with inflammation, the tumor microenvironment (TME), and multiple carcinogenic pathways. Currently, due to widespread inter- and intra-tumoral heterogeneity of HCC, the efficacy of immunotherapy is limited. Seeking a stable and novel tool to predict prognosis and immunotherapy response is imperative. Methods: Using stepwise Cox regression, least absolute shrinkage and selection operator (LASSO), and random survival forest algorithms, the fibrosis-associated signature (FAIS) was developed and further validated. Subsequently, comprehensive exploration was conducted to identify distinct genomic alterations, clinical features, biological functions, and immune landscapes of HCC patients. Results: The FAIS was an independent prognostic predictor of overall survival and recurrence-free survival in HCC. In parallel, the FAIS exhibited stable and accurate performance at predicting prognosis based on the evaluation of Kaplan-Meier survival curves, receiver operator characteristic curves, decision curve analysis, and Harrell's C-index. Further investigation elucidated that the high-risk group presented an inferior prognosis with advanced clinical traits and a high mutation frequency of TP53, whereas the low-risk group was characterized by superior CD8⁺ T cell infiltration, a higher TIS score, and a lower TIDE score. Additionally, patients in the low-risk group might yield more benefits from immunotherapy. Conclusion: The FAIS was an excellent scoring system that could stratify HCC patients and might serve as a promising tool to guide surveillance, improve prognosis, and facilitate clinical management.

Survival Outcomes and Safety of Programmed Cell Death/Programmed Cell Death Ligand 1 Inhibitors for Unresectable Hepatocellular Carcinoma: Result From Phase III Trials

Programmed cell death (PD-1) and programmed cell death ligand 1 (PD-L1) inhibitors have been increasingly used in cancer therapy. The aim of this study was conducted a meta-analysis to assess the efficacy and safety of PD-1/PD-L1 inhibitors in patients with unresectable hepatocellular carcinoma (uHCC). A total of 1657 patients were included. The completed phase III trials with details data, such as overall survival (OS), progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR), and adverse effects (AEs) were included. The pooled hazard ratio (HR) of OS and PFS were .75 (95% CI: .61–.92) and .74 (95% CI: .56–.97) with heterogeneity between PD-1/PD-L1 inhibitors groups and control groups. Sensitivity analysis revealed IMbrave-150 could be the most important factor of heterogeneity for OS, while CheckMate-459 was the main fact of heterogeneity for PFS. In addition, the relative risk (RR) of ORR and DCR were 2.43 (95% CI: 1.80–3.26) and 1.26 (95% CI: 1.11–1.43) with low heterogeneity in PD-1/PD-L1 inhibitors groups. The therapeutic effect of PD-1/PD-L1 inhibitors was better in females, Asia without Japan, BCLC status C and infected hepatitis groups. The RR of AEs from any cause and serious adverse events (SAEs) for patients receiving PD-1/PD-L1 inhibitors were 1.03 (95% CI: .93–1.13) and 1.13 (95% CI: .89–1.44), respectively. Pruritus was the most common AEs reported in 10% of patients or more (RR = 1.69, 95% CI: 1.33–2.15). In conclusion, PD-L1 inhibitor combined with anti-VEGF antibody could improve the prognosis of patients with uHCC. However, caution should be taken for AEs during patients receiving PD-1/PD-L1 inhibitors.

Liquid biopsy to identify biomarkers for immunotherapy in hepatocellular carcinoma

The past years have witnessed the vigorous development of immunotherapy, mainly immune checkpoint inhibitors (ICIs) targeting the programmed cell death-1 (PD-1) protein and its ligand, PD-L1, and cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4). Indeed, ICIs have largely revolutionized the management and improved the prognosis of patients with intermediate and advanced hepatocellular carcinoma (HCC). However, biomarker-based stratification of HCC patients for optimal response to ICI treatment is still of unmet need and again, there exists the necessity to dynamically monitor treatment effect in real-time manner. The role of conventional biomarkers in immunotherapy surveillance is largely limited by spatial and temporal tumor heterogeneity whereas liquid biopsy seems to be promising to circumvent tumor heterogeneity to identify candidate patients who may response to immunotherapy, to dynamically monitor treatment effect and to unveil resistance mechanism. Herein, we provide a thorough review about the potential utility of liquid biopsy in immunotherapy for HCC and discuss its future perspectives.

Identification of the Immune Cell Infiltration Landscape in Hepatocellular Carcinoma to Predict Prognosis and Guide Immunotherapy

Background: Globally, hepatocellular carcinoma (HCC) is the sixth most frequent malignancy with a high incidence and a poor prognosis. Immune cell infiltration (ICI) underlies both the carcinogenesis and immunogenicity of tumors. However, a comprehensive classification system based on the immune features for HCC remains unknown.

Methods: The HCC dataset from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) cohorts was used in this study. The ICI patterns of 571 patients were characterized using two algorithms: the patterns were determined based on the ICI using the ConsensusClusterPlus package, and principal component analysis (PCA) established the ICI scores. Differences in the immune landscape, biological function, and somatic mutations across ICI scores were evaluated and compared, followed by a predictive efficacy evaluation of ICI scores for immunotherapy by the two algorithms and validation using an external immunotherapy cohort.

Results: Based on the ICI profile of the HCC patients, three ICI patterns were identified, including three subtypes having different immunological features. Individual ICI scores were determined; the high ICI score subtype was characterized by enhanced activation of immune-related signaling pathways and a significantly high tumor mutation burden (TMB); concomitantly, diminished immunocompetence and enrichment of pathways associated with cell cycle and RNA degradation were found in the low ICI score subtype. Taken together, our results contribute to a better understanding of an active tumor and plausible reasons for its poor prognosis.

Conclusion: The present study reveals that ICI scores may serve as valid prognostic biomarkers for immunotherapy in HCC.

Multi-task deep learning network to predict future macrovascular invasion in hepatocellular carcinoma

BACKGROUND

Models predicting future macrovascular invasion in hepatocellular carcinoma are constructed to assist timely interventions.

METHODS

A total of 366 HCC cases were retrospectively collected from five Chinese hospitals between April 2007 and November 2016: the training dataset comprised 281 patients from four hospitals; the external validation dataset comprised 85 patients from another hospital. Multi-task deep learning network-based models were constructed to predict future macrovascular invasion. The discrimination, calibration, and decision curves were compared to identify the best model. We compared the time to macrovascular invasion and overall survival using the best model and related image heterogeneity scores (H-score). Then, we determined the need for a segmentation subnet or the replacement deep learning algorithm by logistic regression in screening clinical/radiological factors. Finally, an applet was constructed for future application.

FINDINGS

The best model combined clinical/radiological factors and radiomic features. It achieved best discrimination (areas under the curve: 0·877 in the training dataset and 0·836 in the validation dataset), calibration, and decision curve. Its performance was not affected by the treatments and disease stages. The subgroups had statistical significance for time to macrovascular invasion (training: hazard ratio [HR] = 0·073, 95% confidence interval [CI]: 0·032-0·167, p < 0·001 and validation: HR = 0·090, 95%CI: 0·022-0·366, p < 0·001) and overall survival (training: HR = 0·344, 95%CI: 0·246-0·547, p < 0·001 and validation: HR = 0·489, 95%CI: 0·279 - 0·859, p = 0·003). Similar results were achieved when the patients were subdivided by the H-score. The subnet for segmentation and end-to-end deep learning algorithms improved the performance of the model.

INTERPRETATION

Our multi-task deep learning network-based model successfully predicted future macrovascular invasion. In high-risk populations, besides the current first-line treatments, more therapies may be explored for macrovascular invasion.

Atezolizumab plus bevacizumab versus sorafenib or atezolizumab alone for unresectable hepatocellular carcinoma: A systematic review

BACKGROUND

Despite the use of current standard therapy, the prognosis of patients with unresectable hepatocellular carcinoma (HCC) is poor, with median survival times of 40 mo for intermediate HCC (Barcelona Clinic Liver Cancer [BCLC] stage B) and 6–8 mo for advanced HCC (BCLC stage C). Although patients with early-stage HCC are usually suitable for therapies with curative intention, up to 70% of patients experience relapse within 5 years. In the past decade, the United States Food and Drug Administration has approved different immunogenic treatment options for advanced HCC, the most common type of liver cancer among adults. Nevertheless, no treatment is useful in the adjuvant setting. Since 2007, the multi-kinase inhibitor sorafenib has been used as a first-line targeted drug to address the increased mortality and incidence rates of HCC. However, in 2020, the IMbrave150 trial demonstrated that combination therapy of atezolizumab (anti-programmed death-ligand 1 [PD-L1]) and bevacizumab (anti-vascular endothelial growth factor [VEGF]) is superior to sorafenib, a single anti-programmed death 1/PD-L1 antibody inhibitor used as an anti-cancer monotherapy for HCC treatment.

AIM

To conduct a systematic literature review to evaluate the evidence supporting the efficacy and safety of atezolizumab/bevacizumab as preferred first-line drug therapy over the conventional sorafenib or atezolizumab monotherapies, which are used to improve survival outcomes and reduce disease progression in patients with unresectable HCC and non-decompensated liver disease.

METHODS

A comprehensive literature review was conducted using the PubMed, Scopus, ScienceDirect, clinicaltrials.gov, PubMed Central, Embase, EuropePMC, and CINAHL databases to identify studies that met the inclusion criteria using relevant MeSH terms. This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and risk of bias (RoB) were assessed using the Cochrane RoB 2 tool and Sevis.

RESULTS

In the atezolizumab/bevacizumab group, an improvement in overall tumor response, reduction of disease progression, and longer progression-free survival were observed compared to monotherapy with either sorafenib or atezolizumab. Hypertension and proteinuria were the most common adverse events, and the rates of adverse events were comparable to those with the monotherapy. Of the studies, there were two completed trials and two ongoing trials analyzed using high quality and low bias. A more thorough analysis was only performed on the completed trials.

CONCLUSION

Treatment of HCC with atezolizumab/bevacizumab combination therapy was confirmed to be an effective first-line treatment to improve survival in patients with unresectable HCC and non-decompensated liver disease compared to monotherapy with either sorafenib or atezolizumab.

Identification of Gene-Set Signature in Early-Stage Hepatocellular Carcinoma and Relevant Immune Characteristics

Background

The incidence of hepatocellular carcinoma (HCC) is rising worldwide, and there is limited therapeutic efficacy due to tumor microenvironment heterogeneity and difficulty in early-stage screening. This study aimed to develop and validate a gene set-based signature for early-stage HCC (eHCC) patients and further explored specific marker dysregulation mechanisms as well as immune characteristics.

Methods

We performed an integrated bioinformatics analysis of genomic, transcriptomic, and clinical data with three independent cohorts. We systematically reviewed the crosstalk between specific genes, tumor prognosis, immune characteristics, and biological function in the different pathological stage samples. Univariate and multivariate survival analyses were performed in The Cancer Genome Atlas (TCGA) patients with survival data. Diethylnitrosamine (DEN)-induced HCC in Wistar rats was employed to verify the reliability of the predictions.

Results

We identified a Cluster gene that potentially segregates patients with eHCC from non-tumor, through integrated analysis of expression, overall survival, immune cell characteristics, and biology function landscapes. Immune infiltration analysis showed that lower infiltration of specific immune cells may be responsible for significantly worse prognosis in HCC (hazard ratio, 1.691; 95% CI: 1.171–2.441; p = 0.012), such as CD8 Tem and cytotoxic T cells (CTLs) in eHCC. Our results identified that Cluster C1 signature presented a high accuracy in predicting CD8 Tem and CTL immune cells (receiver operating characteristic (ROC) = 0.647) and cancerization (ROC = 0.946) in liver. As a central member of Cluster C1, overexpressed PRKDC was associated with the higher genetic alteration in eHCC than advanced-stage HCC (aHCC), which was also connected to immune cell-related poor prognosis. Finally, the predictive outcome of Cluster C1 and PRKDC alteration in DEN-induced eHCC rats was also confirmed.

Conclusions

As a tumor prognosis-relevant gene set-based signature, Cluster C1 showed an effective approach to predict cancerization of eHCC and its related immune characteristics with considerable clinical value.

Interaction between hepatitis B virus infection and the efficacy of camrelizumab in combination with apatinib therapy in patients with hepatocellular carcinoma: a multicenter retrospective cohort study

Background

The interaction between hepatitis B virus (HBV) load and anti-programmed cell death (PD)-1 in combination with (+) antiangiogenic therapy remains controversial, especially for hepatocellular carcinoma (HCC) patients. This study sought to explore the effects of HBV load and antiviral therapy on anti-PD-1+ antiangiogenic therapy, and the rate of HBV reactivation during anti-PD-1+ antiangiogenic treatment.

Methods

We performed a multicenter retrospective cohort study of camrelizumab combined with apatinib (C+A) therapy between January 1, 2019 and January 1, 2021 in patients with unresectable HCC who were seropositive for hepatitis B surface antigen (HBsAg) and received antiviral therapy before C+A involvement. The effects of HBV load and antiviral therapy on C+A and the rate of HBV reactivation during C+A treatment were examined.

Results

Eighty-six patients were included in the analysis. The patients had a mean age of 55 years, and 72 (83.7%) were male. The objective response rates (ORRs) in patients with low (<2,000 IU/mL) and high (≥2,000 IU/mL) baseline HBV deoxyribonucleic acid (DNA) levels were 34.5% and 32.2%, respectively (χ²=0.046; P=0.829), while the disease control rates (DCRs) were 67.3% and 80.6%, respectively (χ²=1.762; P=0.184). The results of the univariate and multivariate analyses showed that the baseline HBV DNA level did not affect PD. Additionally, none of the 86 patients suffered from HBV reactivation or HBV-related hepatic impairment with continuous antiviral treatment, regardless of nucleos(t)ide analogue (NA) type (F=1.473; P=0.228).

Conclusions

Baseline HBV loads did not affect the tumor responses of HCC patients receiving anti-PD-1+ antiangiogenic therapy. Thus, HBV reactivation should not be a contradiction for anti-PD-1+ antiangiogenic therapy among patients undergoing continuous and effective antiviral treatment.

Thermal ablation and immunotherapy for hepatocellular carcinoma: Recent advances and future directions

Hepatocellular carcinoma (HCC) is one of most common cancers that cause death in the world. Thermal ablation (TA) is an important alternative treatment method for HCC patients who are not appropriate for surgery or liver transplantation. Particularly for small and early HCCs, TA can be considered as the first-line curative treatment. However, local and distant recurrence rates are still high even though the TA equipment and technology develop rapidly. Immunotherapy is a novel systemic treatment method to enhance the anti-tumor immune response of HCC patients, which has the potential to reduce the tumor recurrence and metastasis. The combination of local TA and systemic immunotherapy for HCCs may be an ideal treatment for enhancing the efficacy of TA and controlling the recurrence. Herein we summarize the latest progress in TA, immunotherapy, and their combination for the treatment of patients with HCC and discuss the limitations and future research directions of the combined therapy.

E2F1-Induced lncRNA BAIAP2-AS1 Overexpression Contributes to the Malignant Progression of Hepatocellular Carcinoma via miR-361-3p/SOX4 Axis

Currently, plenty of researches have revealed that long noncoding RNAs (lncRNAs) can act as crucial roles during the progression of various tumors, including hepatocellular carcinoma (HCC). Here, we measured the expression of lncRNA BAIAP2 antisense RNA 1(BAIAP2-AS1) as well as its contribution to the developments of HCC. In this study, the expressions of BAIAP2-AS1 and SOX4 were distinctly upregulated in HCC cells and tissues, and high BAIAP2-AS1 may be a novel biomarker for HCC. E2F1 activated BAIAP2-AS1 expression. The silence of BAIAP2-AS1 inhibited the proliferation and metastasis of HepG2 and PLC5 cells. Assays for relationship verification showed that BAIAP2-AS1 regulated the expression of SOX4 and miR-361-3p. Rescue experiments further confirmed the positive interaction between miR-361-3p and BAIAP2-AS1 as well as between miR-361-3p and SOX4. Overall, BAIAP2-AS1 modulated the miR-361-3p/SOX4 axis to promote the development of HCC. Thus, our study offers a potential therapeutic target for treating HCC.

Progress of MRI Radiomics in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is the sixth most common cancer in the world and the third leading cause of cancer-related death. Although the diagnostic scheme of HCC is currently undergoing refinement, the prognosis of HCC is still not satisfactory. In addition to certain factors, such as tumor size and number and vascular invasion displayed on traditional imaging, some histopathological features and gene expression parameters are also important for the prognosis of HCC patients. However, most parameters are based on postoperative pathological examinations, which cannot help with preoperative decision-making. As a new field, radiomics extracts high-throughput imaging data from different types of images to build models and predict clinical outcomes noninvasively before surgery, rendering it a powerful aid for making personalized treatment decisions preoperatively.

Objective

This study reviewed the workflow of radiomics and the research progress on magnetic resonance imaging (MRI) radiomics in the diagnosis and treatment of HCC.

Methods

A literature review was conducted by searching PubMed for search of relevant peer-reviewed articles published from May 2017 to June 2021.The search keywords included HCC, MRI, radiomics, deep learning, artificial intelligence, machine learning, neural network, texture analysis, diagnosis, histopathology, microvascular invasion, surgical resection, radiofrequency, recurrence, relapse, transarterial chemoembolization, targeted therapy, immunotherapy, therapeutic response, and prognosis.

Results

Radiomics features on MRI can be used as biomarkers to determine the differential diagnosis, histological grade, microvascular invasion status, gene expression status, local and systemic therapeutic responses, and prognosis of HCC patients.

Conclusion

Radiomics is a promising new imaging method. MRI radiomics has high application value in the diagnosis and treatment of HCC.

Atezolizumab and bevacizumab as first line therapy in advanced hepatocellular carcinoma: Practical considerations in routine clinical practice

Hepatocellular carcinoma (HCC) is the most common primary liver cancer. For advanced HCC, sorafenib was considered the standard of care for more than ten years. Recently the atezolizumab and bevacizumab combination has become standard of care for these patients without contraindications to either immune checkpoint inhibitors or antiangiogenic therapy. We now review the practical aspects of the atezolizumab and bevacizumab combination, including current evidence, indications, contraindications, management of adverse events, sequencing of this combination, areas of current knowledge gaps and future areas of active clinical research of this combination for busy clinicians in clinical practice.

Immunological Markers, Prognostic Factors and Challenges Following Curative Treatments for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortalities worldwide. Patients with early-stage HCC are eligible for curative treatments, such as surgical resection, liver transplantation (LT) and percutaneous ablation. Although curative treatments provide excellent long-term survival, almost 70–80% of patients experience HCC recurrence after curative treatments. Tumor-related factors, including tumor size, number and differentiation, and underlying liver disease, are well-known risk factors for recurrence following curative therapies. Moreover, the tumor microenvironment (TME) also plays a key role in the recurrence of HCC. Many immunosuppressive mechanisms, such as an increase in regulatory T cells and myeloid-derived suppressor cells with a decrease in cytotoxic T cells, are implicated in HCC recurrence. These suppressive TMEs are also modulated by several factors and pathways, including mammalian target of rapamycin signaling, vascular endothelial growth factor, programmed cell death protein 1 and its ligand 1. Based on these mechanisms and the promising results of immune checkpoint blockers (ICBs) in advanced HCC, there have been several ongoing adjuvant studies using a single or combination of ICB following curative treatments in HCC. In this review, we strive to provide biologic and immunological markers, prognostic factors, and challenges associated with clinical outcomes after curative treatments, including resection, LT and ablation.

Identification of FABP5 as an immunometabolic marker in human hepatocellular carcinoma

Background

Regulating T-cell metabolism is crucial for their anticancer activity. Therefore, understanding the function and metabolism of human tumor-infiltrating T cells is of broad interest and clinical importance.

Methods

CD3⁺CD45⁺ T cells were sorted from adjacent area or tumor core of human hepatocellular carcinoma (HCC), then the clusters and heterogeneity of T cells were further interrogated by single-cell transcriptomic profiling. 118 surgical samples from patients with HCC were histologically examined for infiltration of CD8⁺ T cells in tumor and adjacent tissue.

Results

Single-cell transcriptomic profiling indicated that several exhausted T-cell (Tex) populations differentially coexisted in the tumor and adjacent tissue. CD137 identifies and enriches Tex with superior effector functions and proliferation capacity. Furthermore, enhanced fatty acid-binding protein 5 (FABP5) expression along with increased mitochondrial oxidative metabolism were evident in these CD137-enriched Tex. Inhibiting FABP5 expression and mitochondrial fatty acid oxidation impaired the anti-apoptosis and proliferation of CD137-enriched Tex. These observations have been verified by generating CD137 CART. Immunohistochemistry staining on the tissue microarray of 118 patients with HCC showed intra-tumoral FABP5 ^high CD8⁺ T-cell infiltration was linked to overall and recurrence-free survival.

Conclusions

The tumor microenvironment can impose metabolic restrictions on T-cell function. CD137, a costimulatory molecule highly expressed on some Tex, uses exogenous fatty acids and oxidative metabolism to mediate antitumor immunity. The immunometabolic marker FABP5 should be investigated in larger, longitudinal studies to determine their potential as prognostic biomarkers for HCC.

A Co-Expression Network Reveals the Potential Regulatory Mechanism of lncRNAs in Relapsed Hepatocellular Carcinoma

Background

The mechanistic basis for relapsed hepatocellular carcinoma (HCC) remains poorly understood. Recent research has highlighted the important roles of long non-coding RNAs (lncRNAs) in HCC. However, there are only a few studies on the association between lncRNAs and HCC relapse.

Methods

Differentially expressed lncRNAs and mRNAs between a primary HCC group and relapsed HCC group were identified using the edge R package to analyze the GSE101432 dataset. The differentially expressed lncRNAs and mRNAs were used to construct a lncRNA–mRNA co-expression network. Weighted gene co-expression network analysis followed by Gene Ontology (GO) enrichment analyses were conducted on the database. Furthermore, correlation and survival analyses were performed using The Cancer Genome Atlas database, and expression in the clinical samples was verified by qRT-PCR. Thereafter, we inputted the genes from the two groups into the HCC TNM stage and tumor grade database from TCGA. Finally, we performed Kaplan–Meier survival analysis on the lncRNAs related to relapsed HCC.

Results

In this study, lncRNAs and mRNAs associated with HCC relapse were identified. Two gene modules were found to be closely linked to this. The GO terms in the yellow and black modules were related to cell proliferation, differentiation, and survival, as well as some transcription-related biological processes. Through qRT-PCR, we found that the expression levels of LINC00941 and LINC00668 in relapsed HCC were higher than those in primary HCC. Further, mRNA levels of LOX, OTX1, MICB, NDUFA4L2, BAIAP2L2, and KCTD17 were changed in relapsed HCC compared to levels in primary HCC. In addition, we verified that these genes could predict the overall survival and recurrence-free survival of HCC. Moreover, we found that LINC00668 and LINC00941 could affect tumor grade and TNM stages. In total, we identified and validated two lncRNAs (LINC00941 and LINC00668) and six mRNAs (LOX, MICB, OTX1, BAIAP2L2, KCTD17, NDUFA4L2) associated with HCC relapse.

Conclusion

In summary, we identified the key gene modules and central genes associated with relapsed HCC and constructed lncRNA–mRNA networks related to this. These genes are likely to have potential prognostic value for relapsed HCC and might shed new light on novel biomarkers or diagnostic targets for relapsed HCC.

Deep Learning-Based Prediction of Future Extrahepatic Metastasis and Macrovascular Invasion in Hepatocellular Carcinoma

Purpose

For timely treatment of extrahepatic metastasis and macrovascular invasion (aggressive progressive disease [PD]) in hepatocellular carcinoma, models aimed at stratifying the risks of subsequent aggressive PD should be constructed.

Patients and Methods

After dividing 332 patients from five hospitals into training (n = 236) and validation (n = 96) datasets, non-invasive models, including clinical/semantic factors (Model^CS), deep learning radiomics (Model^D), and both (Model^CSD), were constructed to stratify patients according to the risk of aggressive PD. We examined the discrimination and calibration; similarly, we plotted a decision curve and devised a nomogram. Furthermore, we performed analyses of subgroups who received different treatments or those in different disease stages and compared time to aggressive PD and overall survival in the high- and low-risk subgroups.

Results

Among the constructed models, Model^CSD, combining clinical/semantic factors and deep learning radiomics, outperformed Model^CS and Model^D (areas under the curve [AUCs] for the training dataset: 0.741, 0.815, and 0.856; validation dataset: 0.780, 0.836, and 0.862), with statistical difference per the net reclassification improvement, the integrated discrimination improvement, and/or the DeLong test in both datasets. Besides, Model^CSD had the best calibration and decision curves. The performance of Model^CSD was not affected by treatment types (AUC: resection = 0.839; transarterial chemoembolization = 0.895; p = 0.183) or disease stages (AUC: BCLC [Barcelona Clinic Liver Cancer] stage 0 and A = 0.827; BCLC stage AB &B = 0.861; p = 0.537). Moreover, the high-risk group had a significantly shorter median time to aggressive PD than the low-risk group (training dataset hazard ratio [HR] = 0.108, p < 0.001; validation dataset HR = 0.058, p < 0.001) and poorer overall survival (training dataset HR = 0.357, p < 0.001; validation dataset HR = 0.204, p < 0.001).

Conclusion

Our deep learning-based model successfully stratified the risks of aggressive PD. In the high-risk population, current guideline indicates that first-line treatments are insufficient to prevent extrahepatic metastasis and macrovascular invasion and ensure survival benefits, so more therapies may be explored for these patients.

Immune classifier-based signatures provide good prognostic stratification and predict the clinical benefits of immune-based therapies for hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is an aggressive cancer with a high rate of death globally. The use of bioinformatics may help to identify immune cell-related genes both as targets for potential immunotherapies and for their value associated with predicting therapy responses.

METHODS

In this study, mRNA expression profiles of HCC samples from The Cancer Genome Atlas (TCGA) database were subjected to gene enrichment, cell type abundance, immune cell infiltration, and pathway enrichment analyses to determine immune cell gene features, cell type abundance, and functional annotation characteristics. We also evaluated their prognostic values using Cox regression and Kaplan-Meier analyses and assessed potential responses to chemotherapy. Four subgroups (Groups 1-4) were identified. Group 4 was associated with advanced clinical characteristics, high immune cell enrichment scores, and the poorest outcomes.

RESULTS

Differentially expressed genes (DEGs) in the HCC samples were enriched in the following pathways: antigen binding, cell surface receptor signal transduction of the immune response, and cell surface activated receptor signal transduction of the immune response. Highly expressed genes in Group 4 were enriched in elements of the WNT signalling pathway. We identified five immune-related genes (SEMA3A, TNFRSF11B, GUCA2A, SAA1, and CALCR) that were significantly related to HCC prognosis. A prognostic model based on these five genes exhibited good predictive value, with 1-year and 5-year area under the curve (AUC) values of  >  0.66. Group 4 was also potentially more sensitive to EHT 1864, FH535, and lapatinib chemotherapies than the other groups.

CONCLUSIONS

We identified and validated four HCC subgroups based on immune system-related genes and identified five genes that may be used for an immune-based prognostic model for HCC treatment.

The Prognostic Impact of Tumor Differentiation on Recurrence and Survival after Resection of Hepatocellular Carcinoma Is Dependent on Tumor Size

INTRODUCTION

The present study aimed to evaluate the effect of poor differentiation and tumor size on survival outcome after hepatic resection of hepatocellular carcinoma (HCC).

METHODS

A total of 1,107 patients who underwent initial and curative hepatic resection for HCC without macroscopic vascular invasion participated in the study. Using the multivariable Cox proportional hazards regression model, we evaluated changes in hazard ratios (HRs) for the association between tumor differentiation and survival based on tumor size.

RESULTS

In patients with poorly (Por) differentiated HCCs, the adjusted HRs of reduced overall survival (OS), recurrence-free survival (RFS), early RFS, and early extrahepatic RFS were 1.31 (95% confidence interval [CI]; 1.07-1.59), 1.07 (95% CI 0.89-1.28), 1.31 (95% CI 1.06-1.62), and 1.81 (95% CI 1.03-3.17), respectively. Moreover, based on an analysis of the effect modification of tumor differentiation according to tumor size, Por HCC was found to be associated with a reduced OS (p = 0.033). The HRs of Por HCCs sharply increased in patients with tumors measuring up to 5 cm. The adjusted HRs of reduced OS in patients with Por HCCs measuring <2, ≥2 and <5, and ≥5 cm were 1.22 (95% CI 0.69-2.14), 1.33 (95% CI 1.02-1.73), and 1.58 (95% CI 1.04-2.42), respectively. The corresponding adjusted HRs of reduced early RFS were 0.85 (95% CI 0.46-1.57), 1.34 (95% CI 1.01-1.8), and 1.57 (95% CI 1.03-2.39), respectively. The adjusted HRs of reduced early extrahepatic RFS were 1.89 (95% CI 0.83-4.3) in patients with tumors measuring ≥2 and <5 cm and 2.33 (95% CI 0.98-5.54) in those with tumors measuring ≥5 cm.

CONCLUSIONS

Por HCC measuring ≥2 cm was associated with early recurrence. Hence, it had negative effects on OS. After surgery, patients with Por HCC measuring ≥5 cm should be cautiously monitored for early extrahepatic recurrence. These findings will help physicians devise treatment strategies for patients with HCC.

Metabolic reprogramming of immune cells: Shaping the tumor microenvironment in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a typical inflammation‐induced cancer and displays a complex interaction between the tumor microenvironment and tumor development. Immune cells in the HCC microenvironment play both pro‐ and anti‐tumoral roles in HCC progression. An increasing number of findings indicate that metabolic reprogramming is essential for immune cell differentiation and function. In this review, we discuss the metabolic changes of different immune cells and correlate these findings to HCC progression.

PD-1 Blockade for Hepatocellular Carcinoma: Current Research and Future Prospects

The treatment of hepatocellular carcinoma (HCC) has witnessed radical changes over the last few years, with the introduction of immune checkpoint inhibitors (ICI) in clinical practice, namely the combination of atezolizumab plus bevacizumab as the standard of care for first-line treatment of advanced HCC. The immunosuppressive microenvironment of the chronically inflamed liver makes HCC a fertile ground for the use of ICI. This review focuses on anti-programmed cell death-1 (PD-1) monoclonal antibodies (mAb), which have been extensively studied, as monotherapy, in combination with other ICI or with antiangiogenic agents. Currently, anti-PD-1 agents are approved by the United States Food and Drug Administration for second-line treatment in advanced HCC: nivolumab, alone or in combination with ipilimumab, and pembrolizumab. Lack of demonstration of survival benefit in first and second line led to the investigation of PD-1 agents in combination with multi-kinase inhibitors, with a number of first-line treatment regimens being actively investigated. Mounting evidence suggests a potential role of PD-1 blockade as adjuvant or neoadjuvant therapies. A key challenge remains the identification of biomarkers of response, since only a minority of patients appear to benefit from ICI.

Immune signature-based hepatocellular carcinoma subtypes may provide novel insights into therapy and prognosis predictions

Background

Hepatocellular carcinoma (HCC) has a poor prognosis and has become the sixth most common malignancy worldwide due to its high incidence. Advanced approaches to therapy, including immunotherapeutic strategies, have played crucial roles in decreasing recurrence rates and improving clinical outcomes. The HCC microenvironment is important for both tumour carcinogenesis and immunogenicity, but a classification system based on immune signatures has not yet been comprehensively described.

Methods

HCC datasets from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the International Cancer Genome Consortium (ICGC) were used in this study. Gene set enrichment analysis (GSEA) and the ConsensusClusterPlus algorithm were used for clustering assessments. We scored immune cell infiltration and used linear discriminant analysis (LDA) to improve HCC classification accuracy. Pearson's correlation analyses were performed to assess relationships between immune signature indices and immunotherapies. In addition, weighted gene co-expression network analysis (WGCNA) was applied to identify candidate modules closely associated with immune signature indices.

Results

Based on 152 immune signatures from HCC samples, we identified four distinct immune subtypes (IS1, IS2, IS3, and IS4). Subtypes IS1 and IS4 had more favourable prognoses than subtypes IS2 and IS3. These four subtypes also had different immune system characteristics. The IS1 subtype had the highest scores for IFNγ, cytolysis, angiogenesis, and immune cell infiltration among all subtypes. We also identified 11 potential genes, namely, TSPAN15, TSPO, METTL9, CD276, TP53I11, SPINT1, TSPO, TRABD2B, WARS2, C9ORF116, and LBH, that may represent potential immunological biomarkers for HCC. Furthermore, real-time PCR revealed that SPINT1, CD276, TSPO, TSPAN15, METTL9, and WARS2 expression was increased in HCC cells.

Conclusions

The present gene-based immune signature classification and indexing may provide novel perspectives for both HCC immunotherapy management and prognosis prediction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02033-4.

Effects of hypoxia-inducible factor-1α and hypoxia-inducible factor-2α overexpression on hepatocellular carcinoma survival: A systematic review with meta-analysis

BACKGROUND AND AIM

The role of hypoxia-inducible factor-1α (HIF-1α) and hypoxia-inducible factor-2α (HIF-2α) has been implicated in the clinical prognosis of hepatocellular carcinoma (HCC), but the results remain controversial. We aim to investigate the association of HIF-1α and HIF-2α overexpression with the prognosis and clinicopathological features of HCC.

METHODS

A systematic search was conducted in PubMed, Embase, Scopus, Web of Science, and Cochrane Library until June 20, 2020. Meta-analysis was conducted to generate combined HRs with 95% confidence intervals (CI) for overall survival (OS) and disease-free survival (DFS). Odds ratios (ORs) with 95% CI were also derived by fixed or random effect model.

RESULTS

Twenty-two studies involving 3238 patients were included. Combined data suggested that overexpression of HIF-1α in HCC was not only correlated with poorer OS [HR = 1.75 (95% CI: 1.53-2.00)] and DFS [HR = 1.64 (95% CI: 1.34-2.00)] but was also positively associated with vascular invasion [OR = 1.83 (95% CI: 1.36-2.48)], tumor size [OR = 1.36 (95% CI: 1.12-1.66)], and tumor number [1.74 (95% CI: 1.34-2.25)]. In contrast, HIF-2α overexpression was not associated with the prognosis and clinicopathological features of HCC.

CONCLUSION

Our data provided compelling evidence of a worse prognosis of HCC in HIF-1α overexpression patients but not HIF-2α overexpression ones.