Subtype Of Primary Liver Cancer Research Articles

DDX39B protects against sorafenib-induced ferroptosis by facilitating the splicing and cytoplasmic export of GPX4 pre-mRNA in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the main histological subtype of primary liver cancer and remains one of the most common solid malignancies globally. Ferroptosis was recently defined as an iron-catalyzed form of regulated necrosis. Because cancer cells exhibit higher iron requirements than noncancer cells, treatment with ferroptosis-inducing compounds may be a feasible strategy for cancer therapy. However, cancer cells develop acquired resistance to evade ferroptosis, and the mechanisms responsible for ferroptosis resistance are not fully clarified. In the current study, we reported that DDX39B was downregulated during sorafenib-induced ferroptosis in a dose- and time-dependent manner. Exogenous introduction of DDX39B ensured the survival of HCC cells upon exposure to sorafenib, while the opposite phenomenon was observed in DDX39B-silenced HCC cells. Mechanistically, we demonstrated that DDX39B increased GPX4 levels by promoting the splicing and cytoplasmic translocation of GPX4 pre-mRNA, which was sufficient to detoxify sorafenib-triggered excess lipid ROS production, lipid peroxidation accumulation, ferrous iron levels, and mitochondrial damage. Inhibition of DDX39B ATPase activity by CCT018159 repressed the splicing and cytoplasmic export of GPX4 pre-mRNA and synergistically assisted sorafenib-induced ferroptotic cell death in HCC cells. Taken together, our data uncover a novel role for DDX39B in ferroptosis resistance by modulating the maturation of GPX4 mRNA via a posttranscriptional approach and suggest that DDX39B inhibition may be a promising therapeutic strategy to enhance the sensitivity and vulnerability of HCC cells to sorafenib.

Research on multi-model imaging machine learning for distinguishing early hepatocellular carcinoma

ObjectiveTo investigate the value of differential diagnosis of hepatocellular carcinoma (HCC) and non-hepatocellular carcinoma (non-HCC) based on CT and MR multiphase radiomics combined with different machine learning models and compare the diagnostic efficacy between different radiomics models.BackgroundPrimary liver cancer is one of the most common clinical malignancies, hepatocellular carcinoma (HCC) is the most common subtype of primary liver cancer, accounting for approximately 90% of cases. A clear diagnosis of HCC is important for the individualized treatment of patients with HCC. However, more sophisticated diagnostic modalities need to be explored.MethodsThis retrospective study included 211 patients with liver lesions: 97 HCC and 124 non-hepatocellular carcinoma (non-HCC) who underwent CT and MRI. Imaging data were used to obtain imaging features of lesions and radiomics regions of interest (ROI). The extracted imaging features were combined to construct different radiomics models. The clinical data and imaging features were then combined with radiomics features to construct the combined models. Support Vector Machine (SVM), K-nearest Neighbor (KNN), RandomForest (RF), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Multilayer Perceptron (MLP) six machine learning models were used for training. Five-fold cross-validation was used to train the models, and ROC curves were used to analyze the diagnostic efficacy of each model and calculate the accuracy rate. Model training and efficacy test were performed as before.ResultsStatistical analysis showed that some clinical data (gender and concomitant cirrhosis) and imaging features (presence of envelope, marked enhancement in the arterial phase, rapid contouring in the portal phase, uniform density/signal and concomitant steatosis) were statistical differences (P < 0.001). The results of machine learning models showed that KNN had the best diagnostic efficacy. The results of the combined model showed that SVM had the best diagnostic efficacy, indicating that the combined model (accuracy 0.824) had better diagnostic efficacy than the radiomics-only model.ConclusionsOur results demonstrate that the radiomic features of CT and MRI combined with machine learning models enable differential diagnosis of HCC and non-HCC (malignant, benign). The diagnostic model with dual radiomic had better diagnostic efficacy. The combined model was superior to the radiomic model alone.

Treatment and prognostic implications of strong PD-L1 expression in primary hepatic sarcomatoid carcinoma.

Primary hepatic sarcomatoid carcinoma (HSC) is an extremely rare and aggressive subtype of primary liver cancer. HSC has uncertain pathogenesis and dismal prognosis with overall survival of only 8.3months. The molecular alterations of HSC are also not well understood. In this study, the authors describe a patient who presented with a large liver mass. The patient underwent complete surgical resection and histological examination demonstrated HSC, infiltrating the stomach. PD-L1 was strongly positive in the tumor cells. The patient was started on anti-PD-L1 immunotherapy postsurgery and is doing well 15 months after surgical resection. Tumor whole exome sequencing revealed genetic alterations in TP53, NF2 and MAGEC3 genes, indicating their potential role in tumor development.

Hepatocellular carcinoma and intrahepatic cholangiocarcinoma incidence between 2006 and 2015 in China: estimates based on data from 188 population-based cancer registries.

Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the most common subtypes of primary liver cancer, but nationwide incidence of both liver cancer subtypes have never been reported in China. We aimed to estimate the most recent incidence of HCC and ICC and temporal trends in China based on the most updated data from high qualified population-based cancer registries (covering 13.1% of the national population), in comparison to those in the United States at the same period. We used data from 188 Chinese population-based cancer registries covering 180.6 million population of China to estimate the nationwide incidence of HCC and ICC in 2015. And 22 population-based cancer registries' data were used to estimate the trends of HCC and ICC incidence from 2006 to 2015. Multiple imputation by chained equations method was used to impute liver cancer cases with unknown subtype (50.8%). We used data from 18 population-based registries from the Surveillance, Epidemiology, and End Results program to analyze incidence of HCC and ICC in the United States. In China, an estimated 301,500 and 61,900 newly diagnosed HCC and ICC occurred in 2015. The overall age-standardized rates (ASRs) of HCC incidence decreased by 3.9% per year. For ICC incidence, the overall ASR was relatively stable, but increased in the population of over 65 years old. Subgroup analysis by age showed that the ASR of HCC incidence had the sharpest decline in population who were less than 14 years old and received neonatally hepatitis B virus (HBV) vaccination. In the United States, though the incidence of HCC and ICC were lower than those in China, the overall HCC and ICC incidence increased by 3.3% and 9.2% per year. China still faces with a heavy burden of liver cancer incidence. Our results may further support the beneficial effect of Hepatitis B vaccination on reduction of HCC incidence. Both healthy lifestyle promotion and infection control are needed for future liver cancer control and prevention for China and the United States.

Integrative analysis identified two subtypes and a taurine-related signature to predict the prognosis and efficacy of immunotherapy in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent subtypes of primary liver cancer, with high mortality and poor prognosis. Immunotherapy has revolutionized treatment strategies for many cancers. However, only a subset of patients with HCC achieve satisfactory benefits from immunotherapy. Therefore, a reliable biomarker that could predict the prognosis and immunotherapy response in patients with HCC is urgently needed. Taurine plays an important role in many physiological processes. However, its participation in the occurrence and progression of liver cancer and regulation of the composition and function of various components of the immune microenvironment remains elusive. In this study, we identified and validated two heterogeneous subtypes of HCC with different taurine metabolic profiles, presenting distinct genomic features, clinicopathological characteristics, and immune landscapes, using multiple bulk transcriptome datasets. Subsequently, we constructed a risk model based on genes related to taurine metabolism to assess the prognosis, immune cell infiltration, immunotherapy response, and drug sensitivity of patients with HCC. The risk model was validated using several independent external cohorts and showed a robust predictive performance. In addition, we evaluated the expression patterns of taurine metabolism-related genes in the tumor microenvironment and the heterogeneity of taurine metabolism among cancer cells using a single-cell transcriptome. In conclusion, our study provides insights into the important role played by taurine metabolism in tumor progression and immune regulation. Furthermore, the risk model can serve as a biomarker to assess patient prognosis and immunotherapy response, potentially helping clinicians make more precise and personalized clinical decisions.

Nestin as a diagnostic and prognostic marker for combined hepatocellular-cholangiocarcinoma.

Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a rare primary liver cancer (PLC) associated with a poor prognosis. Given the challenges in its identification and its clinical implications, biomarkers are critically needed. We aimed to investigate the diagnostic and prognostic value of the immunohistochemical expression of Nestin, a progenitor cell marker, in a large multicentric series of PLCs. We collected 461 cHCC-CCA samples from 32 different clinical centers. Control cases included 368 hepatocellular carcinomas (HCCs) and 221 intrahepatic cholangiocarcinomas (iCCAs). Nestin immunohistochemistry was performed on whole tumor sections. Diagnostic and prognostic performances of Nestin expression were determined using receiver-operating characteristic curves and Cox regression modeling. Nestin was able to distinguish cHCC-CCA from HCC with AUCs of 0.85 and 0.86 on surgical and biopsy samples, respectively. Performance was lower for the distinction of cHCC-CCA from iCCA (AUCs of 0.59 and 0.60). Nestin, however, showed a high prognostic value, allowing identification of the subset of cHCC-CCA ("Nestin High", >30% neoplastic cells with positive staining) associated with the worst clinical outcome (shorter disease-free and overall survival) after surgical resection and liver transplantation, as well as when assessment was performed on biopsies. We show in different clinical settings that Nestin has diagnostic value and that it is a useful biomarker to identify the subset of cHCC-CCA associated with the worst clinical outcome. Nestin immunohistochemistry may be used to refine risk stratification and improve treatment allocation for patients with this highly aggressive malignancy. There are different types of primary liver cancers (i.e. cancers that originate in the liver). Accurately identifying a specific subtype of primary liver cancer (and determining its associated prognosis) is important as it can have a major impact on treatment allocation. Herein, we show that a protein called Nestin could be used to refine risk stratification and improve treatment allocation for patients with combined hepatocellular carcinoma, a rare but highly aggressive subtype of primary liver cancer.

Mallotucin D, a Clerodane Diterpenoid from Croton crassifolius, Suppresses HepG2 Cell Growth via Inducing Autophagic Cell Death and Pyroptosis.

Hepatocellular carcinoma (HCC) is a major subtype of primary liver cancer with a high mortality rate. Pyroptosis and autophagy are crucial processes in the pathophysiology of HCC. Searching for efficient drugs targeting pyroptosis and autophagy with lower toxicity is useful for HCC treatment. Mallotucin D (MLD), a clerodane diterpenoid from Croton crassifolius, has not been previously reported for its anticancer effects in HCC. This study aims to evaluate the inhibitory effects of MLD in HCC and explore the underlying mechanism. We found that the cell proliferation, DNA synthesis, and colony formation of HepG2 cells and the angiogenesis of HUVECs were all greatly inhibited by MLD. MLD caused mitochondrial damage and decreased the TOM20 expression and mitochondrial membrane potential, inducing ROS overproduction. Moreover, MLD promoted the cytochrome C from mitochondria into cytoplasm, leading to cleavage of caspase-9 and caspase-3 inducing GSDMD-related pyroptosis. In addition, we revealed that MLD activated mitophagy by inhibiting the PI3K/AKT/mTOR pathway. Using the ROS-scavenging reagent NAC, the activation effects of MLD on pyroptosis- and autophagy-related pathways were all inhibited. In the HepG2 xenograft model, MLD effectively inhibited tumor growth without detectable toxicities in normal tissue. In conclusion, MLD could be developed as a candidate drug for HCC treatment by inducing mitophagy and pyroptosis via promoting mitochondrial-related ROS production.

Glycoproteomic analysis reveals the effects of bisecting GlcNAc in intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (ICC) is the second major subtype of primary liver cancer and has caused more and more attention with increasing incidence and mortality worldwide. Our previous study found that bisecting N-glycans are commonly increased in ICC, while the effects and potential functions of bisecting GlcNAc in ICC are still largely unclear. In this study, we further confirmed that the structures of bisecting GlcNAc were significantly up-regulated in ICC compared with paracancer tissues by glycoproteomic data and lectin histochemistry. The expression of its glycosyltransferase MGAT3 was also up-regulated in ICC tissues at both mRNA and protein levels, and expression of MGAT3 is negatively correlated with overall survival explored by bioinformatic analyses and published datasets from 255 patients. Next, the silencing of MGAT3 could inhibit the growth and invasion of ICC cells, and overexpressing of MGAT3 only promoted ICC cell invasion. Further glycoproteomic analysis showed that the commonly glycoproteins modified by bisecting GlcNAc after MGAT3-overexpression in two ICC cell lines were mainly involved in cell movement-related biological processes, such as cell adhesion, integrin-related and ECM-receptor interaction. This study sheds light on the potential effects of bisecting GlcNAc in ICC cells and suggests that MGAT3 might be used as a potential target in the therapy of ICC.

Lymphoepithelioma-like hepatocellular carcinoma, case report of a rare indolent subtype of hepatic cancer

Background: Lymphoepithelioma - Like Carcinomas (LELC) of the liver are tumors of poorly differentiated epithelial cells with prominent lymphoid cell infiltration of the stroma. Unlike common primary liver cancers, LELC is a rare subtype of primary liver cancer with notably better prognosis. Unfortunately, available data and understanding of this unique cancer type is limited. Case report: A 72-year-old Hispanic female with compensated cirrhosis due to treatment-naïve hepatitis C and Primary Biliary Cirrhosis (PBC) presented with chronic abdominal pain. Computed Tomography scan (CT) of her abdomen at that time showed nodular liver with a mass measuring 4.6 x 3.7 cm in the right hepatic lobe with heterogeneous enhancement on arterial phase associated with mild venous washout, concerning for Hepatocellular Carcinoma (HCC). She was lost to follow up but re-presented 4 years later with an interval increase in the liver mass to 6.4 x 4.8 cm. Staging work up was unremarkable and patient underwent resection of the mass. Histopathologic examination showed moderately differentiated HCC with massive lymphocytic infiltration within the tumor with lymphocyte outnumbering tumor cells and diagnosed as lymphoepithelial-like carcinoma-HCC. The patient remained asymptomatic with no tumor recurrence at 16 months post resection. Conclusion: This report of an indolent course of untreated EBV positive LELC-hepatocellular carcinoma provides valuable insight about this rare tumor type

Clinical and Prognostic Value of PPIA, SQSTM1, and CCL20 in Hepatocellular Carcinoma Patients by Single-Cell Transcriptome Analysis.

Hepatocellular carcinoma (HCC) is the most malignant and poor-prognosis subtype of primary liver cancer. The scRNA-seq approach provides unique insight into tumor cell behavior at the single-cell level. Cytokine signaling in the immune system plays an important role in tumorigenesis and has both pro-tumorigenic and anti-tumorigenic functions. A biomarker of cytokine signaling in immune-related genes (CSIRG) is urgently required to assess HCC patient diagnosis and treatment. By analyzing the expression profiles of HCC single cells, TCGA, and ICGC data, we discovered that three important CSIRG (PPIA, SQSTM1, and CCL20) were linked to the overall survival of HCC patients. Cancer status and three hub CSIRG were taken into account while creating a risk nomogram. The nomogram had a high level of predictability and accuracy. Based on the CSIRG risk score, a distinct pattern of somatic tumor mutational burden (TMB) was detected between the two groups. The enrichment of the pyrimidine metabolism pathway, purine metabolism pathway, and lysosome pathway in HCC was linked to the CSIRG high-risk scores. Overall, scRNA-seq and bulk RNA-seq were used to create a strong CSIRG signature for HCC diagnosis.

Patient-derived tumor organoids for personalized medicine in a patient with rare hepatocellular carcinoma with neuroendocrine differentiation: a case report

BackgroundHepatocellular carcinoma with neuroendocrine differentiation (HCC-NED) is a very rare subtype of primary liver cancer. Treatment allocation in these patients therefore remains a challenge.MethodsWe report the case of a 74-year-old man with a HCC-NED. The tumor was surgically removed in curative intent. Histopathological work-up revealed poorly differentiated hepatocellular carcinoma (Edmondson-Steiner grade IV) with diffuse expression of neuroendocrine markers synaptophysin and chromogranin. Three months after resection, multifocal recurrence of the HCC-NED was observed. In the meantime, tumor organoids have been generated from the resected HCC-NED and extensively characterized. Sensitivity to a number of drugs approved for the treatment of HCC or neuroendocrine carcinomas was tested in vitro.ResultsBased on the results of the in vitro drug screening, etoposide and carboplatin are used as first line palliative combination treatment. With genomic analysis revealing a NTRK1-mutation of unknown significance (kinase domain) and tumor organoids found to be sensitive to entrectinib, a pan-TRK inhibitor, the patient was treated with entrectinib as second line therapy. After only two weeks, treatment is discontinued due to deterioration of the patient’s general condition.ConclusionThe rapid establishment of patient-derived tumor organoids allows in vitro drug testing and thereby personalized treatment choices, however clinical translation remains a challenge. To the best of our knowledge, this report provides a first proof-of-principle for using organoids for personalized medicine in this rare subtype of primary liver cancer.

Mitochondrial-Related Transcriptome Feature Correlates with Prognosis, Vascular Invasion, Tumor Microenvironment, and Treatment Response in Hepatocellular Carcinoma.

Background Hepatocellular carcinoma (HCC) is the most common subtype of primary liver cancer, which was highly correlated with metabolic dysfunction. Nevertheless, the association between nuclear mitochondrial-related transcriptome and HCC remained unclear. Materials and Methods A total of 147 nuclear mitochondrial-related genes (NMRGs) were downloaded from the MITOMAP: A Human Mitochondrial Genome Database. The training dataset was downloaded from The Cancer Genome Atlas (TCGA), while validation datasets were retrieved from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). The univariate and multivariate, and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were applied to construct a NMRG signature, and the value of area under receiver operating characteristic curve (AUC) was utilized to assess the signature and nomogram. Then, data from the Genomics of Drug Sensitivity in Cancer (GDSC) were used for the evaluation of chemotherapy response in HCC. Results Functional enrichment of differentially expressed genes (DEGs) between HCC and paired normal tissue samples demonstrated that mitochondrial dysfunction was significantly associated with HCC development. Survival analysis showed a total of 35 NMRGs were significantly correlated with overall survival (OS) of HCC, and the LASSO Cox regression analysis further identified a 25-NMRG signature and corresponding prognosis score based on their transcriptional profiling. HCC patients were divided into high- and low-risk groups according to the median prognosis score, and high-risk patients had significantly worse OS (median OS: 27.50 vs. 83.18 months, P < 0.0001). The AUC values for OS at 1, 3, and 5 years were 0.79, 0.77, and 0.77, respectively. The prognostic capacity of NMRG signature was verified in the GSE14520 dataset and ICGC-HCC cohort. Besides, the NMRG signature outperformed each NMRG and clinical features in prognosis prediction and could also differentiate whether patients presented with vascular invasions (VIs) or not. Subsequently, a prognostic nomogram (C-index: 0.753, 95% CI: 0.703~0.804) by the integration of age, tumor metastasis, and NMRG prognosis score was constructed with the AUC values for OS at 1, 3, and 5 years were 0.82, 0.81, and 0.82, respectively. Notably, significant enrichment of regulatory and follicular helper T cells in high-risk group indicated the potential treatment of immune checkpoint inhibitors for these patients. Interestingly, the NMRG signature could also identify the potential responders of sorafenib or transcatheter arterial chemoembolization (TACE) treatment. Additionally, HCC patients in high-risk group appeared to be more sensitive to cisplatin, vorinostat, and methotrexate, reversely, patients in low-risk group had significantly higher sensitivity to paclitaxel and bleomycin instead. Conclusions In summary, the development of NMRG signature provided a more comprehensive understanding of mitochondrial dysfunction in HCC, helped predict prognosis and tumor microenvironment, and provided potential targeted therapies for HCC patients with different NMRG prognosis scores.

Identification of a Tumor Immunological Phenotype-Related Gene Signature for Predicting Prognosis, Immunotherapy Efficacy, and Drug Candidates in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the predominant subtype of primary liver cancer and represents a highly heterogeneous disease, making it hard to predict the prognosis and therapy efficacy. Here, we established a novel tumor immunological phenotype-related gene index (TIPRGPI) consisting of 11 genes by Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) algorithm to predict HCC prognosis and immunotherapy response. TIPRGPI was validated in multiple datasets and exhibited outstanding performance in predicting the overall survival of HCC. Multivariate analysis verified it as an independent predictor and a TIPRGPI-integrated nomogram was constructed to provide a quantitative tool for clinical practice. Distinct mutation profiles, hallmark pathways, and infiltration of immune cells in tumor microenvironment were shown between the TIPRGPI high and low-risk groups. Notably, significant differences in tumor immunogenicity and tumor immune dysfunction and exclusion (TIDE) were observed between the two risk groups, suggesting a better response to immune checkpoint blockade (ICB) therapy of the low-risk group. Besides, six potential drugs binding to the core target of the TIPRGPI signature were predicted via molecular docking. Taken together, our study shows that the proposed TIPRGPI was a reliable signature to predict the risk classification, immunotherapy response, and drugs candidate with potential application in the clinical decision and treatment of HCC. The novel “TIP genes”-guided strategy for predicting the survival and immunotherapy efficacy, we reported here, might be also applied to more cancers other than HCC.

Promising role of liver transplantation in patients with combined hepatocellular-cholangiocarcinoma: a propensity score matching analysis.

BackgroundCombined hepatocellular-cholangiocarcinoma (CHC) is a rare but vital heterogeneous histological subtype of primary liver cancer (PLC) with no standardized treatment strategy. This study aimed to preliminarily investigate the role of liver transplantation (LT) in CHC and develop a novel risk scoring model (RSM) to evaluate the benefits of transplantation.MethodsThe study cohort was taken from the Surveillance, Epidemiology, and End Results database. The annual percent change (APC) in incidence or ratio was calculated utilizing the Joinpoint regression. Propensity score matching (PSM) was introduced to reduce the selection bias between groups. A novel RSM was developed based on the independent prognostic factors identified by the Cox regression model. The predictive performance of the RSM was compared with the Milan Criteria and the University of California, San Francisco (UCSF) Criteria, respectively.ResultsA total of 223 CHC patients were enrolled, and 60 (26.9%) of them received LT. The incidence-based mortality did not decrease between 2004 and 2015 (APC =1.7%, P=0.195). Although LT was considered an independent protective predictor for CHC, it showed a declining ratio from 33.3% in 2004 to 15.4% in 2015 (APC =−8.9%, P=0.012). The LT recipients had better outcomes than others who underwent hepatectomy or local destruction (P<0.05). Compared with other subtypes of PLC, the post-transplantation prognoses of CHC patients were similar to those with hepatocellular carcinoma (P>0.05) but significantly better than those with intrahepatic cholangiocarcinoma (ICC) (P<0.05). Based on the RSM (vascular invasion: 1 point; tumor size >2 cm: 1 point; multiple tumors: 2 points), patients were stratified into two prognostic subgroups: the low-risk (scoring ≤2) and the high-risk (scoring >2 or extrahepatic metastasis) groups. Patients in the low-risk group were more likely to benefit from LT. The predictive performance of the RSM outperformed the Milan and UCSF Criteria in both the training and validation sets.ConclusionsTherapeutic strategies for CHC should be further improved. Patients with CHC should also be considered potential LT candidates. The novel RSM could be helpful to stratify patients and assist clinical decision-making.

A Novel Lactate Metabolism-Related Gene Signature for Predicting Clinical Outcome and Tumor Microenvironment in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the main subtype of primary liver cancer with high malignancy and poor prognosis. Metabolic reprogramming is a hallmark of cancer and has great importance on the tumor microenvironment (TME). As an abundant metabolite, lactate plays a crucial role in cancer progression and the immunosuppressive TME. Nonetheless, the potential roles of lactate in HCC remain unclear. In this study, we downloaded transcriptomic data of HCC patients with corresponding clinical information from the TCGA and ICGC portals. The TCGA-HCC dataset used as the training cohort, while the ICGC-LIRI-JP dataset was served as an external validation cohort. Cox regression analysis and the LASSO regression model were combined to construct the lactate metabolism-related gene signature (LMRGS). Then, we assessed the clinical significance of LMRGS in HCC. Besides, enriched molecular functions, tumor mutation burden (TMB), infiltrating immune cells, and immune checkpoint were comprehensively analyzed in different LMRGS subgroups. In total, 66 differentially expressed lactate metabolism-related genes (LMRGs) were screened. The functions of LMRGs were mainly enriched in mitochondrial activity and metabolic processes. The LMRGS comprised of six key LMRGs (FKTN, PDSS1, PET117, PUS1, RARS1, and RNASEH1) had significant clinical value for independently predicting the prognosis of HCC patients. The overall survival and median survival of patients in the LMRGS-high group were significantly shorter than in the LMRGS-low group. In addition, there were differences in TMB between the two LMRGS subgroups. The probability of genetic mutations was higher in the LMRGS-high group. Most importantly, the LMRGS reflected the TME characteristics. In the LMRGS-high group, the immune microenvironment presented a suppressed state, accompanied by more inhibitory immune cell infiltration, including follicular helper T cells and regulatory T cells. Additionally, the expression of inhibitory checkpoint molecules was much higher in the LMRGS-high group. Our study suggested that the LMRGS was a robust biomarker to predict the clinical outcomes and evaluate the TME of patients with HCC.

Global, regional and national burden of primary liver cancer by subtype

IntroductionHepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA) are the two main histological subtypes of primary liver cancer. Estimates of the burden of liver cancer by subtype are needed to facilitate development and evaluation of liver cancer control globally. We provide worldwide, regional and national estimates of HCC and iCCA incidence using high-quality data. MethodsWe used population-based cancer registry data on liver cancer cases by histological subtype from 95 countries to compute the sex- and country-specific distributions of HCC, iCCA and other specified histology. Subtype distributions were applied to estimates of total liver cancer cases for 2018 from the Global Cancer Observatory. Age-standardised incidence rates (ASRs) were calculated. ResultsThere were an estimated 826,000 cases of liver cancer globally in 2018: 661,000 HCC (ASR 7.3 cases per 100,000); 123,000 iCCA (ASR 1.4) and 42,000 other specified histology (ASR 0.5). HCC contributed 80% of the world total liver cancer burden followed by iCCA (14.9%) and other specified histology (5.1%). HCC rates were highest in Eastern Asia (ASR 14.8), Northern Africa (ASR 13.2) and South-Eastern Asia (ASR 9.5). Rates of iCCA were highest in South-Eastern Asia (ASR 2.9), Eastern Asia (ASR 2.0), Northern Europe, the Caribbean and Central America and Oceania (ASR all 1.8). ConclusionWe have shown the importance of uncovering the distinct patterns of the major subtypes of liver cancer. The use of these estimates is critical to further develop public health policy to reduce the burden of liver cancer and monitor progress in controlling HCC and iCCA globally.

Morbidity, Prognostic Factors, and Competing Risk Nomogram for Combined Hepatocellular-Cholangiocarcinoma.

Background Combined hepatocellular-cholangiocarcinoma (CHC) is a rare and heterogeneous histological subtype of primary liver cancer, which is still poorly understood. This study aimed to describe the epidemiological and clinical features, investigate the prognostic indicators, and develop a competing risk nomogram for CHC. Methods The study cohort was taken from the Surveillance, Epidemiology, and End Results database. The annual percent change (APC) in incidence was calculated using the joinpoint regression. The nomogram was developed based on multivariate competing risk survival analyses and validated by calibration curves. Akaike information criterion, Bayesian information criterion, Harrell's C-index, and area under the receiver operating characteristic curves were obtained to compare prognostic performance. Decision curve analysis was introduced to examine the clinical value of the models. Results The overall incidence of CHC was 0.062 per 100,000 individuals in 2004 and 0.081 per 100,000 individuals in 2018, with an APC of 1.0% (P > 0.05). CHC displayed intermediate clinicopathological features of hepatocellular carcinoma and intrahepatic cholangiocarcinoma. Race, tumor size, vascular invasion, extrahepatic invasion, distant metastasis, grade, surgery, and Metavir stage were confirmed as the independent predictors of cancer-specific survival. The constructed nomogram was well calibrated, which showed better discrimination power and higher net benefits than the current American Joint Committee on Cancer staging system. Patients with liver transplantation had better survival than those with hepatectomy, especially patients within the Milan Criteria (P=0.022 and P=0.015). There was no survival difference between liver transplantation and hepatectomy in patients beyond the Milan Criteria (P=0.340). Conclusion The morbidity of CHC remained stable between 2004 and 2018. The constructed nomogram could predict the prognosis with good performance, which was meaningful to individual treatment strategies optimization. CHC patients should also be considered as potential liver transplantation recipients, especially those within the Milan Criteria, but the finding still needs more evidence to be further confirmed.

Key Candidate Prognostic Biomarkers Correlated with Immune Infiltration in Hepatocellular Carcinoma

BackgroundHepatocellular carcinoma (HCC) is the most common subtype of primary liver cancer, which causes ~800,000 deaths annually world-wide. Immune checkpoint inhibitor (ICI) has reformed cancer therapy and achieved unprecedented results in various malignancies, including HCC. However, the response rate of immunotherapy is very low in HCC. Considereing the complicated and unique immune status in liver, we hypothesize that critical molecules will affect prognosis and correlate with immune context in the tumor microenvironment of HCC.MethodsUsing Kaplan–Meier plotter, GEPIA2 and Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB), survival genes and their prognostic value were estimated in HCC. Based on Tumor Immune Estimation Resource (TIMER), association between survival genes and immune infiltration was examined in HCC. FunRich and STRING were used to analyze gene ontology and protein–protein interaction (PPI) Network, qRT-PCR was used to measure mRNA level of candidates; and a Cell Counting Kit-8 was used to measure proliferation of HCC cell line.ResultsUsing multiple databases, we identified 36 key prognostic genes highly expressed in HCC and associated with poor survival of patients. Meanwhile, the 36 gene signatures correlated with immune infiltration in HCC. Moreover, these genes were significantly associated with exhausted T cells and polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) in HCC. Among the 36 key genes, SKA3, SGOL2, SPINDOC, TEDC2, TMCO3 and NUP205 were highly expressed in tumor samples compared with adjacent normal tissues in our HCC cohort (n=22). Additionally, proliferation of SMMC7721 cell line was inhibited when it interfered with SiRNA of each gene.ConclusionThe 36 genes may serve as potential prognostic biomarkers and molecular targets to ameliorate tumor immune microenvironment (TIME) in HCC and therefore represent a novel avenue for individualized immunotherapy in HCC.

Prediction of Survival and Analysis of Prognostic Factors for Patients With Combined Hepatocellular Carcinoma and Cholangiocarcinoma: A Population-Based Study.

BackgroundCombined hepatocellular carcinoma and cholangiocarcinoma (CHC) is an uncommon subtype of primary liver cancer. Because of limited epidemiological data, prognostic risk factors and therapeutic strategies for patients with CHC tend to be individualized. This study aimed to identify independent prognostic factors and develop a nomogram-based model for predicting the overall survival (OS) of patients with CHC.MethodsWe recruited eligible individuals from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015 and randomly divided them into the training or verification cohort. Univariate and multivariate analyses were performed to identify independent variables associated with OS. Based on multivariate analysis, the nomogram was established, and its prediction performance was evaluated using the consistency index (C-index) and calibration curve.ResultsIn total, 271 patients with CHC were included in our study. The median OS was 14 months, and the 1-, 3-, and 5-year OS rates were 52.3%, 27.1%, and 23.3%, respectively. In the training cohort, multivariate analysis showed that the pathological grade (hazard ratio [HR], 1.26; 95% confidence interval [CI]: 0.96–1.66), TNM stage (HR, 1.21; 95% CI: 1.02 - 1.44), and surgery (HR, 0.26; 95% CI: 0.17 - 0.40) were independent indicators of OS. The nomogram-based model related C-indexes were 0.76 (95% CI: 0.72 - 0.81) and 0.72 (95% CI: 0.66 - 0.79) in the training and validation cohorts, respectively. The calibration of the nomogram showed good consistency of 1-, 3-, and 5-year OS rates between the actual observed survival and predicted survival in both cohorts. The TNM stage (HR, 1.23; 95% CI: 1.01 - 1.49), and M stage (HR, 1.87; 95% CI: 1.14 3.05) were risk factors in the surgical treatment group. Surgical resection and liver transplantation could significantly prolong the survival, with no statistical difference observed.ConclusionsThe pathological grade, TNM stage, and surgery were independent prognostic factors for patients with CHC. We developed a nomogram model, in the form of a static nomogram or an online calculator, for predicting the OS of patients with CHC, with a good predictive performance.

DNA methylation biomarkers for diagnosis of primary liver cancer and distinguishing hepatocellular carcinoma from intrahepatic cholangiocarcinoma.

Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the two most common pathology subtypes of primary liver cancer (PLC). Identifying DNA methylation biomarkers for diagnosis of PLC and further distinguishing HCC from ICC plays a vital role in subsequent treatment options selection. To obtain potential diagnostic DNA methylation sites for PLC, differentially methylated CpG (DMC) sites were first screened by comparing the methylation data between normal liver samples and PLC samples (ICC samples and HCC samples). A random forest algorithm was then used to select specific DMC sites with top Gini value. To avoid overfitting, another cohort was taken as an external validation for evaluating the area under curves (AUCs) of different DMC sites combination. A similar model construction strategy was applied to distinguish HCC from ICC. In addition, we identified DNA Methylation-Driven Genes in HCC and ICC via MethylMix method and performed pathway analysis by utilizing MetaCore. Finally, we not only performed methylator phenotype based on independent prognostic sites but also analyzed the correlations between methylator phenotype and clinical factors in HCC and ICC, respectively. To diagnose PLC, we developed a model based on three PLC-specific methylation sites (cg24035245, cg21072795, and cg00261162), whose sensitivity and specificity achieved 98.8%,94.8% in training set and 97.3%,81% in validation set. Then, to further divide the PLC samples into HCC and ICC, we established another mode through three methylation sites (cg17769836, cg17591574, and cg07823562), HCC accuracy and ICC accuracy achieved 95.8%, 89.8% in the training set and 96.8%,85.4% in the validation set. In HCC, the enrichment pathways were mainly related to protein folding, oxidative stress, and glutathione metabolism. While in ICC, immune response, embryonic hepatocyte maturation were the top pathways. Both in HCC and ICC, methylator phenotype correlated well with overall survival time and clinical factors involved in tumor progression. In summary, our study provides the biomarkers based on methylation sites not only for the diagnosis of PLC but also for distinguishing HCC from ICC.