Molecular and histological correlations in liver cancer

Preoperative prediction of cytokeratin-19 expression for hepatocellular carcinoma using T1 mapping on gadoxetic acid-enhanced MRI combined with diffusion-weighted imaging and clinical indicators

Objectives

To explore the value of T1 mapping on gadoxetic acid-enhanced magnetic resonance imaging (MRI) in preoperative predicting cytokeratin 19 (CK19) expression for hepatocellular carcinoma (HCC).

Methods

This retrospective study included 158 patients from two institutions with surgically resected treatment-native solitary HCC who underwent preoperative T1 mapping on gadoxetic acid-enhanced MRI. Patients from institution I (n = 102) and institution II (n = 56) were assigned to training and test sets, respectively. univariable and multivariable logistic regression analyses were performed to investigate the association of clinicoradiological variables with CK19. The receiver operating characteristic (ROC) curve and precision-recall (PR) curve were used to evaluate the performance for CK19 prediction. Then, a prediction nomogram was developed for CK19 expression. The performance of the prediction nomogram was evaluated by its discrimination, calibration, and clinical utility.

Results

Multivariable logistic regression analysis showed that AFP>400ng/ml (OR=4.607, 95%CI: 1.098-19.326; p=0.037), relative apparent diffusion coefficient (rADC)≤0.71 (OR=3.450, 95%CI: 1.126-10.567; p=0.030), T1 relaxation time in the 20-minute hepatobiliary phase (T1rt-HBP)>797msec (OR=4.509, 95%CI: 1.301-15.626; p=0.018) were significant independent predictors of CK19 expression. The clinical-quantitative model (CQ-Model) constructed based on these significant variables had the best predictive performance with an area under the ROC curve of 0.844, an area under the PR curve of 0.785 and an F1 score of 0.778. The nomogram constructed based on CQ-Model demonstrated satisfactory performance with C index of 0.844 (95%CI: 0.759-0.908) and 0.818 (95%CI: 0.693-0.902) in the training and test sets, respectively.

Conclusions

T1 mapping on gadoxetic acid-enhanced MRI has good predictive efficacy for preoperative prediction of CK19 expression in HCC, which can promote the individualized risk stratification and further treatment decision of HCC patients.

A High-Throughput Sequencing Data-Based Classifier Reveals the Metabolic Heterogeneity of Hepatocellular Carcinoma

Metabolic heterogeneity plays a key role in poor outcomes in malignant tumors, but its role in hepatocellular carcinoma (HCC) remains largely unknown. In the present study, we aim to disentangle the metabolic heterogeneity features of HCC by developing a classification system based on metabolism pathway activities in high-throughput sequencing datasets. As a result, HCC samples were classified into two distinct clusters: cluster 1 showed high levels of glycolysis and pentose phosphate pathway activity, while cluster 2 exhibited high fatty acid oxidation and glutaminolysis status. This metabolic reprogramming-based classifier was found to be highly correlated with several clinical variables, including overall survival, prognosis, TNM stage, and 𝛼-fetoprotein (AFP) expression. Of note, activated oncogenic pathways, a higher TP53 mutation rate, and increased stemness were also observed in cluster 1, indicating a causal relationship between metabolic reprogramming and carcinogenesis. Subsequently, distinct metabolism-targeted therapeutic strategies were proven in human HCC cell lines, which exhibit the same metabolic properties as corresponding patient samples based on this classification system. Furthermore, the metabolic patterns and effects of different types of cells in the tumor immune microenvironment were explored by referring to both bulk and single-cell data. It was found that malignant cells had the highest overall metabolic activities, which may impair the anti-tumor capacity of CD8+ T cells through metabolic competition, and this provided a potential explanation for why immunosuppressive cells had higher overall metabolic activities than those with anti-tumor functions. Collectively, this study established an HCC classification system based on the gene expression of energy metabolism pathways. Its prognostic and therapeutic value may provide novel insights into personalized clinical practice in patients with metabolic heterogeneity.

Rapid, label-free histopathological diagnosis of liver cancer based on Raman spectroscopy and deep learning

Biopsy is the recommended standard for pathological diagnosis of liver carcinoma. However, this method usually requires sectioning and staining, and well-trained pathologists to interpret tissue images. Here, we utilize Raman spectroscopy to study human hepatic tissue samples, developing and validating a workflow for in vitro and intraoperative pathological diagnosis of liver cancer. We distinguish carcinoma tissues from adjacent non-tumour tissues in a rapid, non-disruptive, and label-free manner by using Raman spectroscopy combined with deep learning, which is validated by tissue metabolomics. This technique allows for detailed pathological identification of the cancer tissues, including subtype, differentiation grade, and tumour stage. 2D/3D Raman images of unprocessed human tissue slices with submicrometric resolution are also acquired based on visualization of molecular composition, which could assist in tumour boundary recognition and clinicopathologic diagnosis. Lastly, the potential for a portable handheld Raman system is illustrated during surgery for real-time intraoperative human liver cancer diagnosis.

Corona enhancement combined with microvascular invasion for prognosis prediction of macrotrabecular-massive hepatocellular carcinoma subtype

Objectives

The macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is aggressive and associated with an unfavorable prognosis. This study aimed to characterize MTM-HCC features based on contrast-enhanced MRI and to evaluate the prognosis of imaging characteristics combined with pathology for predicting early recurrence and overall survival after surgery.

Methods

This retrospective study included 123 patients with HCC that underwent preoperative contrast-enhanced MRI and surgery, between July 2020 and October 2021. Multivariable logistic regression was performed to investigate factors associated with MTM-HCC. Predictors of early recurrence were determined with a Cox proportional hazards model and validated in a separate retrospective cohort.

Results

The primary cohort included 53 patients with MTM-HCC (median age 59 years; 46 male and 7 females; median BMI 23.5 kg/m2) and 70 subjects with non-MTM HCC (median age 61.5 years; 55 male and 15 females; median BMI 22.6 kg/m2) (All P>0.05). The multivariate analysis identified corona enhancement (odds ratio [OR]=2.52, 95% CI: 1.02-6.24; P=0.045) as an independent predictor of the MTM-HCC subtype. The multiple Cox regression analysis identified corona enhancement (hazard ratio [HR]=2.56, 95% CI: 1.08-6.08; P=0.033) and MVI (HR=2.45, 95% CI: 1.40-4.30; P=0.002) as independent predictors of early recurrence (area under the curve=0.790, P<0.001). The prognostic significance of these markers was confirmed by comparing results in the validation cohort to those from the primary cohort. Corona enhancement combined with MVI was significantly associated with poor outcomes after surgery.

Conclusions

A nomogram for predicting early recurrence based on corona enhancement and MVI could be used to characterize patients with MTM-HCC and predict their prognosis for early recurrence and overall survival after surgery.

Vessels That Encapsulate Tumor Clusters (VETC) Predict cTACE Response in Hepatocellular Carcinoma

Background

To investigate the correlation between hepatocellular carcinoma (HCC) pathological types and conventional transarterial chemoembolization (cTACE), and to evaluate the predictive value of the pathological types for efficacy of cTACE.

Methods

We investigated 186 naive HCC patients from 2 hospitals, including 63 patients with recurrence after surgical resection, and 123 unresectable cases, who underwent at least one cTACE procedure as the first treatment. All patients were histologically diagnosed with HCC by surgical resection and/or liver biopsy. Lipiodol deposition rate, ORR (objective response rate), PFS (progression-free survival), OS (overall survival) were compared among different HCC pathological types.

Results

This study evaluated 186 naive HCC patients and 189 tumor nodules. Vessels that encapsulate tumor clusters (VETC), macrotrabecular-massive (MTM), CK19-positive types were identified in 38% (72/189), 40% (76/189), and 28% (53/189) of the whole cohort, respectively. VETC, MTM and CK19-negative HCCs derived significantly better lipiodol deposition rate and ORR. cTACE prolonged the PFS of VETC and CK19-negative HCCs compared with non-VETC and CK19-positive HCCs in the recurrence, liver biopsy and combining whole cohorts, whereas the OSs of different pathological types were not significantly different. Multivariate analysis showed that VETC (OR, 4.671, 95% CI [1.954, 11.166], P<0.001) and CK19-positive type (OR, 0.127, 95% CI [0.044, 0.362], P<0.001) were independent predictive factors for the first cTACE response. However, only VETC type was significantly associated with the second cTACE response in multivariate analysis (OR, 3.31, 95% CI [1.24, 8.83], P=0.017), suggesting that VETC might be a more useful predictor of cTACE response.

Conclusion

Our study suggests that VETC is an effective predictor of cTACE response in patients with HCC.

Molecular and radiopathologic spectrum between HCC and intrahepatic cholangiocarcinoma

BACKGROUND AND AIMS

Primary liver cancers (LCs), including HCC and intrahepatic cholangiocarcinoma (iCCA), are derived from a common developmental lineage, conferring a molecular spectrum between them. To elucidate the molecular spectrum, we performed an integrative analysis of transcriptome profiles associated with patients' radiopathologic features.

APPROACH AND RESULTS

We identified four LC subtypes (LC1-LC4) from RNA-sequencing profiles, revealing intermediate subtypes between HCC and iCCA. LC1 is a typical HCC characterized by active bile acid metabolism, telomerase reverse transcriptase promoter mutations, and high uptake of gadoxetic acid in MRI. LC2 is an iCCA-like HCC characterized by expression of the progenitor cell-like trait, tumor protein p53 mutations, and rim arterial-phase hyperenhancement in MRI. LC3 is an HCC-like iCCA, mainly small duct (SD) type, associated with HCC-related etiologic factors. LC4 is further subclassified into LC4-SD and LC4-large duct iCCAs according to the pathological features, which exhibited distinct genetic variations (e.g., KRAS , isocitrate dehydrogenase 1/2 mutation, and FGF receptor 2 fusion), stromal type, and prognostic outcomes.

CONCLUSIONS

Our integrated view of the molecular spectrum of LCs can identify subtypes associated with transcriptomic, genomic, and radiopathologic features, providing mechanistic insights into heterogeneous LC progression.

Preoperative prediction model for macrotrabecular-massive hepatocellular carcinoma based on contrast-enhanced CT and clinical characteristics: a retrospective study

Objective

To investigate the predictive value of contrast-enhanced computed tomography (CECT) imaging features and clinical factors in identifying the macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) preoperatively.

Methods

This retrospective study included 101 consecutive patients with pathology-proven HCC (35 MTM subtype vs. 66 non-MTM subtype) who underwent liver surgery and preoperative CECT scans from January 2017 to November 2021. The imaging features were evaluated by two board-certified abdominal radiologists independently. The clinical characteristics and imaging findings were compared between the MTM and non-MTM subtypes. Univariate and multivariate logistic regression analyses were performed to investigate the association of clinical-radiological variables and MTM-HCCs and develop a predictive model. Subgroup analysis was also performed in BCLC 0-A stage patients. Receiver operating characteristic (ROC) curves analysis was used to determine the optimal cutoff values and the area under the curve (AUC) was employed to evaluate predictive performance.

Results

Intratumor hypoenhancement (odds ratio [OR] = 2.724; 95% confidence interval [CI]: 1.033, 7.467; p = .045), tumors without enhancing capsules (OR = 3.274; 95% CI: 1.209, 9.755; p = .03), high serum alpha-fetoprotein (AFP) (≥ 228 ng/mL, OR = 4.101; 95% CI: 1.523, 11.722; p = .006) and high hemoglobin (≥ 130.5 g/L; OR = 3.943; 95% CI: 1.466, 11.710; p = .009) were independent predictors for MTM-HCCs. The clinical-radiologic (CR) model showed the best predictive performance, achieving an AUC of 0.793, sensitivity of 62.9% and specificity of 81.8%. The CR model also effectively identify MTM-HCCs in early-stage (BCLC 0-A stage) patients.

Conclusion

Combining CECT imaging features and clinical characteristics is an effective method for preoperatively identifying MTM-HCCs, even in early-stage patients. The CR model has high predictive performance and could potentially help guide decision-making regarding aggressive therapies in MTM-HCC patients.

Evaluation of transcriptomic molecular classification, biological behavior, and clinicopathological features in hepatocellular carcinoma

BACKGROUND

Studies in France, Korea, and Singapore found that G1-G6 transcriptomes are involved in hepatocellular carcinoma (HCC) carcinogenesis. However, the suitability of this method in Chinese HCC patients has remained unknown.

METHODS

The correlation between the G1-G6 molecular classification and clinicopathological features were analyzed in 107 Chinese HCC patients through the retrospective cohort study. RNA sequencing and bioinformatics analysis were performed to screen related targets and molecular signaling pathways.

RESULTS

We found that the G1-G3 subgroups were associated with high serum alpha-fetoprotein (AFP) level, high copy number of hepatitis B virus (HBV) DNA, complex histopathological structure, macrovascular invasion. The G1 subgroup was mainly related to liver cancer stemness, and G3 subgroup showed the worst prognosis. The G5 and G6 subgroups were associated with activation of the Wnt/β-catenin pathway. Compared with the G4-G6 group, the G1-G3 group showed significantly higher expression levels of regenerating family member 1 beta (REG1B), regenerating family member 3 gamma (REG3G), and inositol 1,4,5-trisphosphate receptor type 1 (ITPR1), and enriched calcium signaling pathway.

CONCLUSIONS

This study enhances our understanding of the heterogenicity of China HCC and indicates that the G1-G6 signatures can be used to identify predictive biomarkers against HCC patients in China.

Early alpha-fetoprotein response predicts prognosis of immune checkpoint inhibitor and targeted therapy for hepatocellular carcinoma: a systematic review with meta-analysis

BACKGROUND

The prognostic value of alpha-fetoprotein (AFP) response for efficacy of targeted therapy or immune checkpoint inhibitors (ICIs) has not been established. The purpose of this meta-analysis is to elucidate the relationship between AFP response and survival outcomes in hepatocellular carcinoma (HCC) patients who received targeted therapy or ICIs.

METHODS

The hazard ratio (HR) with 95% confidence interval (CI) was used to evaluate the relationship between AFP response and overall survival (OS)/progression-free survival (PFS).

RESULTS

Twenty-six articles containing 3056 HCC patients were finally included in the study. The pooled results showed that after targeted therapy or ICIs, patients with decrease in AFP had better prognosis (OS:HR = 0.48, 95%CI:0.40-0.56; PFS:HR = 0.39, 95%CI:0.33-0.46), while patients with increase in AFP had worse prognosis (OS:HR = 2.30, 95%CI:1.82-2.89; PFS:HR = 2.34, 95%CI = 1.69-3.24). Subgroup analysis revealed that compared to AFP decrease >50%, AFP decrease >20% can better predict the prognosis of patients who received targeted therapy (OS:HR = 0.51, 95%CI:0.41-0.62; PFS:HR = 0.39, 95%CI:0.30-0.51) or ICIs treatment (OS:HR = 0.34, 95%CI:0.16-0.71; PFS:HR = 0.22, 95%CI:0.10-0.47), and 8 weeks after targeted therapy may be the appropriate time point for AFP assessment.

CONCLUSION

AFP decrease >20% within 8 weeks may be the appropriate definition for early AFP response which probably works best in predicting the efficacy of therapy.

REGISTRATION

The review was not registered.

Hepatic Sarcomatoid Carcinoma Is an Aggressive Hepatic Neoplasm Sharing Common Molecular Features With Its Conventional Carcinomatous Counterparts

Hepatic sarcomatoid carcinoma is a rare hepatic tumor with an aggressive clinical behavior and dismal outcome. However, the molecular pathogenesis is incompletely defined. In this study, we analyzed 59 hepatic sarcomatoid carcinomas using targeted next-generation sequencing and immunohistochemistry. A panel of 14 genes commonly mutated in primary liver carcinomas was examined. PD-L1 and loss of expression for switch/sucrose nonfermenting complexes, including BAP1, ARID1A, ARID2, and PBRM1, were detected by immunohistochemistry. The 59 hepatic sarcomatoid carcinomas encompass various carcinomatous subtypes and tumors with complete sarcomatoid transformation. Mutations in TP53 and promoter of TERT (pTERT) were frequently identified in sarcomatoid hepatocellular carcinoma, sarcomatoid combined hepatocellular cholangiocarcinoma, and hepatic sarcomatoid carcinomas with complete sarcomatoid transformation but rarely in sarcomatoid cholangiocarcinoma. Alterations involving switch/sucrose nonfermenting complexes were uncommon in hepatic sarcomatoid carcinoma (n = 2). PD-L1 expressed in tumor-associated immune cells in 67% of the tumors and in tumor cells in 33% of the tumors. A multivariate survival analysis indicated that PD-L1 expression in immune cells served as an independent favorable predictive factor of patient survival (P = .036). In conclusion, hepatic sarcomatoid carcinoma displays molecular similarity with its conventional carcinomatous counterparts. This finding suggests persistent genetic characteristics during sarcomatous evolution. PD-L1 expression in immune cells is a favorable prognostic factor for patient outcomes and may be a potential biomarker for immunotherapeutic treatment.

Prediction for Aggressiveness and Postoperative Recurrence of Hepatocellular Carcinoma Using Gadoxetic Acid-Enhanced Magnetic Resonance Imaging

RATIONALE AND OBJECTIVES

To investigate the predictive value of gadoxetic acid-enhanced magnetic resonance imaging (MRI) features on the pathologic grade, microvascular invasion (MVI), and cytokeratin-19 (CK19) expression in hepatocellular carcinomas (HCC), and to evaluate their association with postoperative recurrence of HCC.

MATERIALS AND METHODS

This retrospective study included 147 patients with surgically confirmed HCCs who underwent gadoxetic-enhanced MRI. The lesions were evaluated quantitatively in terms of the relative enhancement ratio (RER), and qualitatively based on imaging features and clinical parameters. Logistic regression analyses were performed to investigate the value of these parameters in predicting the pathologic grade, MVI, and CK19 in HCC. Predictive factors for postoperative recurrence were determined using a Cox proportional hazards model.

RESULTS

Peritumoral enhancement (odds ratio [OR], 3.396; p = 0.025) was an independent predictor of high pathologic grades. Serum protein induced by vitamin K absence or antagonist (PIVKA) level > 40 mAU/mL (OR, 3.763; p = 0.018) and peritumoral hypointensity (OR, 4.343; p = 0.003) were independent predictors of MVI. Predictors of CK19 included serum alpha-fetoprotein (AFP) level > 400 ng/mL (OR, 4.576; p = 0.005), rim enhancement (OR, 5.493; p = 0.024), and lower RER (OR, 0.013; p = 0.011). Peritumoral hypointensity (hazard ratio [HR], 1.957; p = 0.027) and poor pathologic grades (HR, 2.339; p = 0.043) were independent predictors of recurrence.

CONCLUSION

We demonstrated the value of preoperative gadoxetic-enhanced MRI in predicting aggressive pathological features of HCC. Poor pathologic grades and peritumoral hypointensity may independently predict the recurrence of HCC.

The benefit of immunotherapy in patients with hepatocellular carcinoma: a systematic review and meta-analysis

Background: A systemic review of the survival benefit of immune checkpoint inhibitors (ICIs) in phase III hepatocellular carcinoma (HCC) trials was conducted. Methods: Meta-analyses were performed with the generic inverse-variance method with a fixed-effects model. Results: In 10 trials encompassing 6123 patients, ICI-based therapy (monotherapy/combination) improved overall survival (OS) compared with the control arm (hazard ratio [HR]: 0.77; 95% CI: 0.70-0.84; p < 0.001). The survival benefit was consistent across variable treatment lines, Eastern Cooperative Oncology Group performance status and AFP levels. While the OS benefit was more pronounced in hepatitis B-related HCC (HR: 0.70; 95% CI: 0.63-0.77; p < 0.001), OS was improved in hepatitis C-related (HR: 0.83; 95% CI: 0.71-0.98) and nonviral HCC (HR: 0.86; 95% CI: 0.77-0.97). Conclusion: ICI-based therapies should be the standard for all patients with advanced HCC.

CT Radiomics to Predict Macrotrabecular-Massive Subtype and Immune Status in Hepatocellular Carcinoma

Background Macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is an aggressive variant associated with angiogenesis and immunosuppressive tumor microenvironment, which is expected to be noninvasively identified using radiomics approaches. Purpose To construct a CT radiomics model to predict the MTM subtype and to investigate the underlying immune infiltration patterns. Materials and Methods This study included five retrospective data sets and one prospective data set from three academic medical centers between January 2015 and December 2021. The preoperative liver contrast-enhanced CT studies of 365 adult patients with resected HCC were evaluated. The Third Xiangya Hospital of Central South University provided the training set and internal test set, while Yueyang Central Hospital and Hunan Cancer Hospital provided the external test sets. Radiomic features were extracted and used to develop a radiomics model with machine learning in the training set, and the performance was verified in the two test sets. The outcomes cohort, including 58 adult patients with advanced HCC undergoing transarterial chemoembolization and antiangiogenic therapy, was used to evaluate the predictive value of the radiomics model for progression-free survival (PFS). Bulk RNA sequencing of tumors from 41 patients in The Cancer Genome Atlas (TCGA) and single-cell RNA sequencing from seven prospectively enrolled participants were used to investigate the radiomics-related immune infiltration patterns. Area under the receiver operating characteristics curve of the radiomics model was calculated, and Cox proportional regression was performed to identify predictors of PFS. Results Among 365 patients (mean age, 55 years ± 10 [SD]; 319 men) used for radiomics modeling, 122 (33%) were confirmed to have the MTM subtype. The radiomics model included 11 radiomic features and showed good performance for predicting the MTM subtype, with AUCs of 0.84, 0.80, and 0.74 in the training set, internal test set, and external test set, respectively. A low radiomics model score relative to the median value in the outcomes cohort was independently associated with PFS (hazard ratio, 0.4; 95% CI: 0.2, 0.8; P = .01). The radiomics model was associated with dysregulated humoral immunity involving B-cell infiltration and immunoglobulin synthesis. Conclusion Accurate prediction of the macrotrabecular-massive subtype in patients with hepatocellular carcinoma was achieved using a CT radiomics model, which was also associated with defective humoral immunity. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Yoon and Kim in this issue.

Preoperative prediction of macrotrabecular-massive hepatocellular carcinoma based on B-Mode US and CEUS

OBJECTIVES

To develop a preoperative prediction model to identify macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) and evaluate the model's diagnostic performance in differentiating MTM-HCC from HCC.

METHODS

We conducted a mono-center retrospective study in a grade A tertiary hospital in China. Consecutive patients with suspected HCC from February 2019 to December 2020 were eligible for inclusion. All consenting patients underwent CEUS examination and were histologically diagnosed. Based on the clinical and US features between the two groups, we developed a binary logistic regression model and a nomogram for predicting MTM-HCC.

RESULTS

A total of 161 patients (median age, 57 years; interquartile range, 48-64 years; 129 men) were included in the analysis. Twenty-seven of the HCCs (16.8%) were of the MTM subtype. Binary logistic regression analysis indicated that PVP hypoenhancement (OR = 15.497; 95% CI: 1.369, 175.451; p = 0.027), AFP > 454.6 ng/mL (OR = 8.658; 95% CI: 3.030, 24.741; p < 0.001), ALB ≤ 29.9 g/L (OR = 3.937; 95% CI: 1.017, 15.234; p = 0.047), halo sign (OR = 3.868; 95% CI: 1.314, 11.391; p = 0.016), and intratumoral artery (OR = 2.928; 95% CI: 1.039, 8.255; p = 0.042) were predictors for MTM subtype. Combining any two criteria showed a high sensitivity (100.0%); combining all five criteria showed a high specificity (99.2%); and the AUC value of the logistic regression model was 0.88 (95% CI: 0.81, 0.92).

CONCLUSIONS

BMUS and CEUS could be used for identifying patients suspected of having MTM-HCC. Combining clinical information, BMUS, and CEUS features could achieve a noninvasive diagnosis of MTM-HCC.

KEY POINTS

• Contrast-enhanced ultrasound examination helps clinicians to identify MTM-HCCs preoperatively. • PVP hypoenhancement, high AFP levels, low ALB levels, halo signs, and intratumoral arteries could be used to predict MTM-HCCs. • A logistic regression model and nomogram were built to noninvasively diagnose MTM-HCCs with an AUC value of 0.88 (95% CI: 0.81, 0.92).

Deciphering a mitochondria-related signature to supervise prognosis and immunotherapy in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a major public health problem in humans. The imbalance of mitochondrial function has been discovered to be closely related to the development of cancer recently. However, the role of mitochondrial-related genes in HCC remains unclear.

Methods

The RNA-sequencing profiles and patient information of 365 samples were derived from the Cancer Genome Atlas (TCGA) dataset. The mitochondria-related prognostic model was established by univariate Cox regression analysis and LASSO Cox regression analysis. We further determined the differences in immunity and drug sensitivity between low- and high-risk groups. Validation data were obtained from the International Cancer Genome Consortium (ICGC) dataset of patients with HCC. The protein and mRNA expression of six mitochondria-related genes in tissues and cell lines was verified by immunohistochemistry and qRT-PCR.

Results

The six mitochondria-related gene signature was constructed for better prognosis forecasting and immunity, based on which patients were divided into high-risk and low-risk groups. The ROC curve, nomogram, and calibration curve exhibited admirable clinical predictive performance of the model. The risk score was associated with clinicopathological characteristics and proved to be an independent prognostic factor in patients with HCC. The above results were verified in the ICGC validation cohort. Compared with normal tissues and cell lines, the protein and mRNA expression of six mitochondria-related genes was upregulated in HCC tissues and cell lines.

Conclusion

The signature could be an independent factor that supervises the immunotherapy response of HCC patients and possess vital guidance value for clinical diagnosis and treatment.

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

BACKGROUND & AIMS

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

LAY SUMMARY

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.

Combined hepatocellular-cholangiocarcinoma derives from liver progenitor cells and depends on senescence and IL-6 trans-signaling

BACKGROUND & AIMS

Primary liver cancers include hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (CCA) and combined HCC-CCA tumors (cHCC-CCA). It has been suggested, but not unequivocally proven, that hepatic progenitor cells (HPCs) can contribute to hepatocarcinogenesis. We aimed to determine whether HPCs contribute to HCC, cHCC-CCA or both types of tumors.

METHODS

To trace progenitor cells during hepatocarcinogenesis, we generated Mdr2-KO mice that harbor a yellow fluorescent protein (YFP) reporter gene driven by the Foxl1 promoter which is expressed specifically in progenitor cells. These mice (Mdr2-KO^{Foxl1-CRE;RosaYFP}) develop chronic inflammation and HCCs by the age of 14-16 months, followed by cHCC-CCA tumors at the age of 18 months.

RESULTS

In this Mdr2-KO^{Foxl1-CRE;RosaYFP} mouse model, liver progenitor cells are the source of cHCC-CCA tumors, but not the source of HCC. Ablating the progenitors, caused reduction of cHCC-CCA tumors but did not affect HCCs. RNA-sequencing revealed enrichment of the IL-6 signaling pathway in cHCC-CCA tumors compared to HCC tumors. Single-cell RNA-sequencing (scRNA-seq) analysis revealed that IL-6 is expressed by immune and parenchymal cells during senescence, and that IL-6 is part of the senescence-associated secretory phenotype. Administration of an anti-IL-6 antibody to Mdr2-KO^{Foxl1-CRE;RosaYFP} mice inhibited the development of cHCC-CCA tumors. Blocking IL-6 trans-signaling led to a decrease in the number and size of cHCC-CCA tumors, indicating their dependence on this pathway. Furthermore, the administration of a senolytic agent inhibited IL-6 and the development of cHCC-CCA tumors.

CONCLUSION

Our results demonstrate that cHCC-CCA, but not HCC tumors, originate from HPCs, and that IL-6, which derives in part from cells in senescence, plays an important role in this process via IL-6 trans-signaling. These findings could be applied to develop new therapeutic approaches for cHCC-CCA tumors.

LAY SUMMARY

Combined hepatocellular carcinoma-cholangiocarcinoma is the third most prevalent type of primary liver cancer (i.e. a cancer that originates in the liver). Herein, we show that this type of cancer originates in stem cells in the liver and that it depends on inflammatory signaling. Specifically, we identify a cytokine called IL-6 that appears to be important in the development of these tumors. Our results could be used for the development of novel treatments for these aggressive tumors.

2022 KLCA-NCC Korea Practice Guidelines for the Management of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the fourth most common cancer among men in South Korea, where the prevalence of chronic hepatitis B infection is high in middle and old age. The current practice guidelines will provide useful and sensible advice for the clinical management of patients with HCC. A total of 49 experts in the fields of hepatology, oncology, surgery, radiology, and radiation oncology from the Korean Liver Cancer Association-National Cancer Center Korea Practice Guideline Revision Committee revised the 2018 Korean guidelines and developed new recommendations that integrate the most up-to-date research findings and expert opinions. These guidelines provide useful information and direction for all clinicians, trainees, and researchers in the diagnosis and treatment of HCC.

Systemic therapies in hepatocellular carcinoma: Existing and emerging biomarkers for treatment response

Hepatocellular carcinoma (HCC) is the fifth most common malignancy and the third most common cause of cancer-related death worldwide. Due to asymptomatic patients in the early stage, most patients are diagnosed at an advanced stage and lose the opportunity for radical resection. In addition, for patients who underwent procedures with curative intent for early-stage HCC, up to 70% of patients may have disease recurrence within 5 years. With the advent of an increasing number of systemic therapy medications, we now have more options for the treatment of HCC. However, data from clinical studies show that with different combinations of regimens, the objective response rate is approximately 40%, and most patients will not respond to treatment. In this setting, biomarkers for predicting treatment response are of great significance for precise treatment, reducing drug side effects and saving medical resources. In this review, we summarized the existing and emerging biomarkers in the literature, with special emphasis on the pathways and mechanism underlying the prediction value of those biomarkers for systemic treatment response.

Expression of IRAK1 in Hepatocellular Carcinoma, Its Clinical Significance, and Docking Characteristics with Selected Natural Compounds

This study aimed to explore clinical significance of interleukin-1 receptor-associated kinase 1 (IRAK1) in the diagnosis, prognosis, and targeted therapy of hepatocellular carcinoma. A systematic analysis based on the cancer genome atlas (TCGA) indicated that IRAK1 was highly expressed in 18 cancer types (p < 0.01) and may be a pan-cancer biomarker. In hepatocellular carcinoma, the alteration rate of IRAK1 was rather high (62.4%), in which mRNA high relative to normal predominated (58.9%). Higher expression was associated with shorter overall survival (p < 0.01). IRAK1 expression correlated positively with pathology stage and tumor grade (for the latter there was only a slight trend). Interestingly, it correlated positively with TP53 mutation (p < 0.001), suggesting a possible strategy for targeting TP53 via IRAK1. Immunohistochemistry experiments confirmed a higher positive rate of IRAK1 in carcinoma than in para-carcinoma tissues (χ² = 18.006, p < 0.001). Higher tumor grade correlated with more strongly positive staining. Molecular docking revealed cryptotanshinone, matrine, and harmine as the best hit compounds with inhibition potential for IRAK1. Our findings suggest that IRAK1 may play biologically predictive roles in hepatocellular carcinoma. The suppression of IRAK1/NF-κB signaling via inhibition of IRAK1 by the hit compounds can be a potential strategy for the targeted therapy.

Custom gene expression panel for evaluation of potential molecular markers in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. It is a highly heterogeneous disease with poor prognosis and limited treatment options, which highlights the need for reliable biomarkers. This study aims to explore molecular markers that allow stratification of HCC and may lead to better prognosis and treatment prediction.

MATERIALS AND METHODS

We studied 20 candidate genes (HCC hub genes, potential drug target genes, predominant somatic mutant genes) retrieved from literature and public databases with potential to be used as the molecular markers. We analysed expression of the genes by RT-qPCR in 30 HCC tumour and adjacent non-tumour paired samples from Vietnamese patients. Fold changes in expression were then determined using the 2^-∆∆CT method, and unsupervised hierarchical clustering was generated using Cluster v3.0 software.

RESULTS

Clustering of expression data revealed two subtypes of tumours (proliferative and normal-like) and four clusters for genes. The expression profiles of the genes TOP2A, CDK1, BIRC5, GPC3, IGF2, and AFP were strongly correlated. Proliferative tumours were characterized by high expression of the c-MET, ARID1A, CTNNB1, RAF1, LGR5, and GLUL1 genes. TOP2A, CDK1, and BIRC5 HCC hub genes were highly expressed (> twofold) in 90% (27/30), 83% (25/30), and 83% (24/30) in the tissue samples, respectively. Among the drug target genes, high expression was observed in the GPC3, IGF2 and c-MET genes in 77% (23/30), 63% (19/30), and 37% (11/30), respectively. The somatic mutant Wnt/ß-catenin genes (CTNNB1, GLUL and LGR5) and TERT were highly expressed in 40% and 33% of HCCs, respectively. Among the HCC marker genes, a higher percentage of tumours showed GPC3 expression compared to AFP expression [73% (23/30) vs. 43% (13/30)].

CONCLUSION

The custom panel and molecular markers from this study may be useful for diagnosis, prognosis, biomarker-guided clinical trial design, and prediction of treatment outcomes.

Understanding the Immunoenvironment of Primary Liver Cancer: A Histopathology Perspective

One of the most common cancers worldwide, primary liver cancer remains a major cause of cancer-related mortality. Hepatocellular carcinoma and cholangiocarcinoma represent the majority of primary liver cancer cases. Despite advances in the development of novel anti-cancer therapies that exploit targets within the immune system, survival rates from liver cancer remain poor. Furthermore, responses to immunotherapies, such as immune checkpoint inhibitors, have revealed limited and variable responses amongst patients with hepatocellular carcinoma, although combination immunotherapies have shown recent breakthroughs in clinical trials. This has shifted the focus towards improving our understanding of the underlying immune and molecular characteristics of liver tumours that may influence their response to immune-modulating treatments. In this review, we outline the complex interactions that occur in the tumour microenvironment of hepatocellular carcinoma and cholangiocarcinoma, respectively, from a histopathological perspective. We explore the potential role of a classification system based on immune-specific characteristics within each cancer type, the importance of understanding inter- and intra-tumoural heterogeneity and consider the future role of histopathology and novel technologies within this field.

Chemokine clouding and liver cancer heterogeneity: Does it impact clinical outcomes?

Tumor heterogeneity is a predominant feature of hepatocellular carcinoma (HCC) that plays a crucial role in chemoresistance and limits the efficacy of available chemo/immunotherapy regimens. Thus, a better understanding regarding the molecular determinants of tumor heterogeneity will help in developing newer strategies for effective HCC management. Chemokines, a sub-family of cytokines are one of the key molecular determinants of tumor heterogeneity in HCC and are involved in cell survival, growth, migration, and angiogenesis. Herein, we provide a panoramic insight into the role of chemokines in HCC heterogeneity at genetic, epigenetic, metabolic, immune cell composition, and tumor microenvironment levels and its impact on clinical outcomes. Interestingly, our in-silico analysis data showed that expression of chemokine receptors impacts infiltration of various immune cell populations into the liver tumor and leads to heterogeneity. Thus, it is evident that aberrant chemokines clouding impacts HCC tumor heterogeneity and understanding this phenomenon in depth could be harnessed for the development of personalized medicine strategies in future.

Delineation of a SMARCA4-specific competing endogenous RNA network and its function in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignancy worldwide, and the mortality rate continues to rise each year. SMARCA4 expression has been associated with poor prognosis in various types of cancer; however, the specific mechanism of action of SMARCA4 in HCC needs to be fully elucidated.

AIM

To explore the specific mechanism of action of SMARCA4 in HCC.

METHODS

Herein, the expression level of SMARCA4 as well as its association with HCC prognosis were evaluated using transcriptome profiling and clinical data of 18 different types of cancer collected from The Cancer Genome Atlas database. Furthermore, SMARCA4-high and -low groups were identified. Thereafter, gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to identify the function of SMARCA4, followed by construction of a SMARCA4-specific competing endogenous RNA (ceRNA) network using starBase database. The role of SMARCA4 in immunotherapy and its association with immune cells were assessed using correlation analysis.

RESULTS

It was observed that SMARCA4 was overexpressed and negatively correlated with prognosis in HCC. Further, SMARCA4 expression was positively associated with tumor mutational burden, microsatellite stability, and immunotherapy efficacy. The SNHG3/THUMP3-AS1-miR-139-5p-SMARCA4 ceRNA network was established and could be assumed to serve as a stimulatory mechanism in HCC.

CONCLUSION

The findings of this study demonstrated that SMARCA4 plays a significant role in progression and immune infiltration in HCC. Moreover, a ceRNA network was detected, which was found to be correlated with poor prognosis in HCC. The findings of this study could contribute towards the identification of predictive markers for immunotherapy and a novel mechanism of action for HCC treatment.

2022 KLCA-NCC Korea practice guidelines for the management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the fourth most common cancer among men in South Korea, where the prevalence of chronic hepatitis B infection is high in middle and old age. The current practice guidelines will provide useful and sensible advice for the clinical management of patients with HCC. A total of 49 experts in the fields of hepatology, oncology, surgery, radiology, and radiation oncology from the Korean Liver Cancer Association-National Cancer Center Korea Practice Guideline Revision Committee revised the 2018 Korean guidelines and developed new recommendations that integrate the most up-to-date research findings and expert opinions. These guidelines provide useful information and direction for all clinicians, trainees, and researchers in the diagnosis and treatment of HCC.

Prognostic implications of CT/MRI LI-RADS in hepatocellular carcinoma: State of the art and future directions

Hepatocellular carcinoma (HCC) is the fourth most lethal malignancy with an increasing incidence worldwide. Management of HCC has followed several clinical staging systems that rely on tumour morphologic characteristics and clinical variables. However, these algorithms are unlikely to profile the full landscape of tumour aggressiveness and allow accurate prognosis stratification. Noninvasive imaging biomarkers on computed tomography (CT) or magnetic resonance imaging (MRI) exhibit a promising prospect to refine the prognostication of HCC. The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system for standardizing the terminology, techniques, interpretation, reporting and data collection of liver imaging. At present, it has been widely accepted as an effective diagnostic system for HCC in at-risk patients. Emerging data have provided new insights into the potential of CT/MRI LI-RADS in HCC prognostication, which may help refine the prognostic paradigm of HCC that promises to direct individualized management and improve patient outcomes. Therefore, this review aims to summarize several prognostic imaging features at CT/MRI for patients with HCC; the available evidence regarding the use of LI-RDAS for evaluation of tumour biology and clinical outcomes, pitfalls of current literature, and future directions for LI-RADS in the management of HCC.

Circular RNA hsa_circ_0062682 Binds to YBX1 and Promotes Oncogenesis in Hepatocellular Carcinoma

Simple Summary

Circular RNA (circRNA) have a role in carcinogenesis in different cancers, also in hepatocellular carcinoma (HCC). The transcriptome analyses of HCC tumours identified an upregulated circRNA hsa_circ_0062682. We show that this circRNA affects several aspects of oncogenesis, which are cell proliferation, migration, and invasion. Using transcriptome analyses we identified modulated signalling pathways and transcription factors, confirming the observed phenotype in cells. We identified Y-box-binding protein 1 (YBX1), a known oncogene and RNA-binding protein, as a binding partner, which was in line with transcriptome analyses. We also identified a cell-specific response to sorafenib after circRNA modulation, which is in line with a heterogeneous molecular pathology of HCC subtypes.

Abstract

Circular RNAs (circRNAs) have been shown to play an important role in the pathogenesis of hepatocellular carcinoma (HCC). By implementing available transcriptomic analyses of HCC patients, we identified an upregulated circRNA hsa_circ_0062682. Stable perturbations of hsa_circ_0062682 in Huh-7 and SNU-449 cell lines influenced colony formation, migration, cell proliferation, sorafenib sensitivity, and additionally induced morphological changes in cell lines, indicating an important role of hsa_circ_0062682 in oncogenesis. Pathway enrichment analysis and gene set enrichment analysis of the transcriptome data from hsa_circ_0062682 knockdown explained the observed phenotypes and exposed transcription factors E2F1, Sp1, HIF-1α, and NFκB1 as potential downstream targets. Biotinylated oligonucleotide pulldown combined with proteomic analyses identified protein interaction partners of which YBX1, a known oncogene, was confirmed by RNA immunoprecipitation. Furthermore, we discovered a complex cell-type-specific phenotype in response to the oncogenic potential of hsa_circ_0062682. This finding is in line with different classes of HCC tumours, and more studies are needed to shed a light on the molecular complexity of liver cancer.

Immune checkpoint and angiogenic inhibitors for the treatment of hepatocellular carcinoma: It takes two to tangle

Immunotherapy represents an effective and promising option in various cancers, including in hepatocellular carcinoma (HCC). The immune checkpoint inhibitors (ICIs) have shown a remarkable breakthrough in the last decade, in addition to molecular targeted therapy of angiogenesis such as tyrosine kinases inhibitors. ICIs provide new regimen that can be applied in different stages of the disease. In parallel, HCC progression is related to the tumor microenvironment (TME), involving the cross-talk between various cellular and non-cellular components within the TME niche. It appears logical to synergistically target several HCC components to increase the efficacy of the treatment. In this paper, we summarize evidence that the combination therapy of ICIs and angiogenesis inhibitors would be a potentially better strategy for HCC treatment.

A Novel Oxidative Phosphorylation-Associated Gene Signature for Prognosis Prediction in Patients with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common type of malignant tumor with high morbidity and mortality. The oxidative phosphorylation (OXPHOS) metabolic pathway produces adenosine triphosphate (ATP) by delivering electrons to transmembrane protein complexes in the mitochondria. This research was dedicated to identifying an OXPHOS-associated signature for the assessment of prognosis of HCC patients. A total of 371 HCC patients from the Cancer Genome Atlas (TCGA) and 231 HCC patients from the International Cancer Genome Consortium (ICGC) with RNA expression data and clinical data were employed as construction and validation cohorts, respectively. The least absolute shrinkage and selection operator (LASSO) Cox regression was applied to establish a multigene signature in the TCGA cohort, and the ICGC cohort was used for validation. The prognostic value of the risk signature was evaluated using univariate and multivariate Cox regression, Kaplan–Meier curves, and receiver operating characteristic (ROC) curves. The potential enrichment of biological functions was investigated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Meanwhile, we analyzed the correlation between the risk score and the tumor microenvironment (TME). A five-gene signature including ATP6V0B, ATP6V1C1, ATP6V1E1, TIMM9, and UQCRH was identified by LASSO Cox regression to classify patients into low- and high-risk groups. ROC curve analysis indicated that the five-gene signature is a prospective prognostic factor in HCC patients. Univariate and multivariate Cox regression analyses demonstrated that the risk score was an independent prognostic factor for overall survival (OS). Functional analysis showed that differentially expressed genes (DEGs) between the low- and high-risk groups were enriched in mitosis and the cell cycle pathway. In addition, the five-gene signature was associated with innate immune cell infiltration, immune subtypes, and tumor stemness. A novel OXPHOS-associated gene signature can be used for prognostic prediction for patients with HCC.

Novel Nanotechnology Approaches to Overcome Drug Resistance in the Treatment of Hepatocellular Carcinoma: Glypican 3 as a Useful Target for Innovative Therapies

Hepatocellular carcinoma (HCC) is the second most lethal tumor, with a 5-year survival rate of 18%. Early stage HCC is potentially treatable by therapies with curative intent, whereas chemoembolization/radioembolization and systemic therapies are the only therapeutic options for intermediate or advanced HCC. Drug resistance is a critical obstacle in the treatment of HCC that could be overcome by the use of targeted nanoparticle-based therapies directed towards specific tumor-associated antigens (TAAs) to improve drug delivery. Glypican 3 (GPC3) is a member of the glypican family, heparan sulfate proteoglycans bound to the cell surface via a glycosylphosphatidylinositol anchor. The high levels of GPC3 detected in HCC and the absence or very low levels in normal and non-malignant liver make GPC3 a promising TAA candidate for targeted nanoparticle-based therapies. The use of nanoparticles conjugated with anti-GPC3 agents may improve drug delivery, leading to a reduction in severe side effects caused by chemotherapy and increased drug release at the tumor site. In this review, we describe the main clinical features of HCC and the common treatment approaches. We propose the proteoglycan GPC3 as a useful TAA for targeted therapies. Finally, we describe nanotechnology approaches for anti-GPC3 drug delivery systems based on NPs for HCC treatment.

Distinct phenotypic spectra of hepatocellular carcinoma in liver-specific tumor suppressor-deficient hepatitis B virus transgenic mice

The hepatitis B virus (HBV) transgenic mouse model was used to interrogate the origins of HCC heterogeneity. HBV biosynthesis was used as a marker of liver tumor heterogeneity. Principal component and correlation analysis of HBV and cellular transcript levels demonstrated major differences within and between the gene expression profiles of Apc-deficient, Apc-deficient Pten-deficient, and Pten-deficient HCC. Hence, both oncogenic stimuli and zonal hepatocyte properties determine heterogeneous HCC phenotypes. Additionally, Apc-deficient HCC display decreased expression of Apob, Otc and Tet2 relative to Pten-deficient HCC and control liver tissue suggesting their gene products may represent markers of Apc-deficient HCC. A subset of human HCC with mutations in the β-catenin gene (CTNNB1) displayed a gene expression profile similar to that observed in the mouse Apc-deficient HCC indicating this model of liver cancer may be useful for interrogating the molecular properties of these tumors and their potential therapeutic vulnerabilities.

Four-copy number alteration (CNA)-related lncRNA prognostic signature for liver cancer

The objective of this study was to identify CNA-related lncRNAs that can better evaluate the prognosis of patients with liver cancer. Prognostic molecular subtypes were identified, followed by tumor mutation and differential expression analyses. Genomic copy number anomalies and their association with lncRNAs were also evaluated. A risk model was built based on lncRNAs, as well as a nomogram, and the differences in the tumor immune microenvironment and drug sensitivity between the High_ and Low_risk groups were compared. Weighted gene co-expression network analysis was used to identify modules with significant enrichment in prognostic-related lncRNAs. In total, two subtypes were identified, TP53 and CTNNB1 were common high-frequency mutated genes in the two subtypes. A total of 8,372 differentially expressed (DE) mRNAs and 798 DElncRNAs were identified between cluster1 and cluster2. In addition, a four-lncRNA signature was constructed, and statistically significant differences between the Low_ and High_risk groups were found in terms of CD8 T cells, resting memory CD4 T cells, etc. Enrichment analysis showed that prognostic-related lncRNAs were involved in the cell cycle, p53 signaling pathway, non-alcoholic fatty liver disease, etc. A prognostic prediction signature, based on four-CNA-related lncRNAs, could contribute to a more accurate prognosis of patients with liver cancer.

Nomogram for the Preoperative Prediction of the Macrotrabecular-Massive Subtype of Hepatocellular Carcinoma

Background

The macrotrabecular-massive subtype of hepatocellular carcinoma (MTM-HCC) is an aggressive histological type and results in poor prognosis. We developed a nomogram model based on laboratory results to predict the presence of MTM-HCC.

Methods

A total of 357 HCC patients who underwent radical surgery between January 2015 and December 2020 at Ningbo Medical Center Lihuili Hospital were grouped according to histological type. After propensity score matching (PSM), 267 patients were divided into MTM-HCC (n = 76) and non-MTM-HCC (n = 191) groups. A LASSO regression analysis model was used to select predictive factors. Finally, a nomogram for predicting the presence of MTM-HCC was established. Decision curve analysis (DCA) was conducted to determine the clinical usefulness of the nomogram model by quantifying the net benefits along with the increase in threshold probabilities.

Results

The 1-, 3-, and 5-year disease-free survival (DFS) and overall survival (OS) rates for MTM-HCC were 60.0%, 36.0%, 32.4% and 92.1%, 68.7%, 52.2%, respectively. Survival analysis indicated that the probabilities of achieving DFS and OS were significantly worse in the MTM-HCC group than in the non-MTM-HCC group (P < 0.05). The nomogram model that included AST levels, PT and AFP levels achieved a better C-index of 0.723 (95% CI: 0.659-0.787). DCA revealed that the nomogram model could lead to net benefits and exhibited a wider range of threshold probabilities in the prediction of MTM-HCC.

Conclusion

The nomogram model included AST, PT and AFP could achieve an optimal performance in the preoperative prediction of MTM-HCC.

Prognostic Value of MUC16 Mutation and Its Correlation with Immunity in Hepatocellular Carcinoma Patients

Objective

Identifying gene mutation signatures will enable a better understanding for the occurrence, development, and prognosis of hepatocellular carcinoma (HCC) and provide some potential biomarkers for clinical practice. This study investigated the mutated genes in HCC patients and assessed their relationship with tumor mutation burden (TMB) and prognosis.

Methods

The somatic mutation annotation format (MAF) document, mRNA expression matrix, and clinical information of HCC patients were obtained from the International Cancer Genome Consortium (ICGC) and the Cancer Genome Atlas (TCGA) database. The differences of TMB between the mutant type and the wild-type genes were detected using the Mann–Whitney U test. The link of gene mutations with prognosis was explored by the Kaplan–Meier analysis. The proportion of 22 immune cells' composition was measured using CIBERSORT algorithm.

Results

The two databases screened 16 common mutated genes, which included TP53, TTN, LRP1B, ZFHX4, MUC16, OBSCN, CSMD3, FLG, CSMD1, SYNE1, SPTA1, USH2A, KMT2C, PCLO, HMCN1, and FAT3. After a series of analysis, MUC16 mutation was found to be highly correlated with TMB and was regarded as an independent factor predicting HCC. Furthermore, gene set enrichment analysis (GSEA) indicated that the MUC16 mutation was significantly involved in HCC cell metabolism.

Conclusions

MUC16 mutation seems to be a valuable potential biomarker for HCC development and its overall survival.

A Novel hepatocellular carcinoma specific hypoxic related signature for predicting prognosis and therapeutic responses

Hypoxia is an important feature of the tumor microenvironment(TME) and is closely associated with cancer metastasis, immune evasion, and drug resistance. However, the precise role of hypoxia in hepatocellular carcinoma(HCC), as well as its influence on the TME, and drug sensitivity remains unclear. We found the excellent survival prediction value of Hypoxia_DEGs_Score model. In hypoxic HCC, somatic mutation, copy number variation, and DNA methylation were closely related to hypoxic changes and affected tumorigenesis, progression, metastasis, and drug resistance. In HCC, aggravated hypoxic stress was found to be accompanied by an immune exclusion phenotype and increased infiltration of immunosuppressive cells. In the validation cohort, patients with high Hypoxia_DEGs_Score were found to have worse immunotherapeutic outcomes and prognoses, and may benefit from drugs against cell cycle signaling pathways rather than those inhibiting the PI3K/mTOR pathway. Hypoxia_DEGs_Score has an excellent predictive capability of changes in the TME, the efficacy of immunotherapy, and the response of drugs. Therefore, Hypoxia_DEGs_Score can help develop personalized immunotherapy regimens and improve the prognosis of HCC patients.

High expression of serine and arginine-rich splicing factor 9 (SRSF9) is associated with hepatocellular carcinoma progression and a poor prognosis

BACKGROUND

Serine and arginine-rich splicing factor 9 (SRSF9) has been linked to the occurrence and progression of various cancers; however, its effects and mechanism of action hepatocellular carcinoma (HCC) have not been reported. In this study, we used a bioinformatics approach and in vitro assays to evaluate the expression of SRSF9 in HCC, its prognostic value, and its underlying regulatory mechanisms, including analyses of related pathways and the role of methylation.

METHODS

Transcriptomic and DNA methylation data for 357 HCC cases and 50 paratumor tissues in The Cancer Genome Atlas database were obtained. Additionally, protein expression data for cell lines and tissue samples were obtained from the Human Protein Atlas. The CMap databased was used to predict candidate drugs targeting SRSF9. Various cell lines were used for in vitro validation.

RESULTS

SRSF9 expression was significantly elevated in HCC and was negatively regulated by its methylation site cg06116271. The low expression of SRSF9 and hypermethylation of cg06116271 were both associated with a longer overall survival time. A correlation analysis revealed ten genes that were co-expressed with SRSF9; levels of CDK4, RAN, DENR, RNF34, and ANAPC5 were positively correlated and levels of RBP4, APOC1, MASP2, HP, and HPX were negatively correlated with SRSF9 expression. The knockdown of SRSF9 in vitro inhibited the proliferation and migration of HCC cells and significantly reduced the expression of proteins in the Wnt signaling pathway (DVL2 and β-catenin) and cell cycle pathway (Cyclin D and Cyclin E). A CMap analysis identified two drugs, camptothecin and apigenin, able to target and inhibit the expression of SRSF9.

CONCLUSIONS

This study expands our understanding of the molecular biological functions of SRSF9 and cg06116271 and provides candidate diagnostic and therapeutic targets for HCC.

Hallmark-guided subtypes of hepatocellular carcinoma for the identification of immune-related gene classifiers in the prediction of prognosis, treatment efficacy, and drug candidates

Hepatocellular carcinoma (HCC), accounting for ~90% of all primary liver cancer, is a prevalent malignancy worldwide. The intratumor heterogeneity of its causative etiology, histology, molecular landscape, and immune phenotype makes it difficult to precisely recognize individuals with high mortality risk or tumor-intrinsic treatment resistance, especially immunotherapy. Herein, we comprehensively evaluated the activities of cancer hallmark gene sets and their correlations with the prognosis of HCC patients using gene set variation analysis (GSVA) and identified two HCC subtypes with distinct prognostic outcomes. Based on these subtypes, seven immune-related genes (TMPRSS6, SPP1, S100A9, EPO, BIRC5, PLXNA1, and CDK4) were used to construct a novel prognostic gene signature [hallmark-guided subtypes-based immunologic signature (HGSIS)] via multiple statistical approaches. The HGSIS-integrated nomogram suggested an enhanced predictive performance. Interestingly, oncogenic hallmark pathways were significantly enriched in the high-risk group and positively associated with the risk score. Distinct mutational landscapes and immune profiles were observed between different risk groups. Moreover, immunophenoscore (IPS) and tumor immune dysfunction and exclusion (TIDE) analysis showed different sensitivities of HGSIS risk groups for immune therapy efficacy, and the pRRophetic algorithm indicated distinguishable responses for targeted/chemotherapies in different groups. KIF2C was picked out as the key target concerning HGSIS, and the top 10 small molecules were predicted to bind to the active site of KIF2C via molecular docking, which might be further used for candidate drug discovery of HCC. Taken together, our study offers novel insights for clinically significant subtype recognition, and the proposed signature may be a helpful guide for clinicians to improve the treatment regimens.

Non-transplantable recurrence after percutaneous thermal ablation of ≤3-cm HCC: Predictors and implications for treatment allocation

Percutaneous thermal ablation (PTA), resection, and liver transplantation are the standard curative options for hepatocellular carcinoma (HCC). Liver transplantation yields the best long‐term outcomes but is limited by graft shortage. Thus, patients with ≤3‐cm HCC are primarily treated by PTA even though recurrence is frequent and may occur outside transplant criteria. Data on non‐transplantable recurrence (NTR) following PTA are lacking, however. We therefore investigated the incidence and predictors of NTR among 213 potentially transplantable patients (cirrhosis, 93%; Child‐Pugh A, 98.6%; alcohol‐related disease, 62%) with ≤3‐cm HCC(s) treated by PTA, to stratify them according to their NTR risk and to improve treatment allocation. During follow‐up (median: 41.2 months), NTR occurred in 18.3% (alpha‐fetoprotein [AFP] model) and 23% (Milan) patients. NTR prediction with competing‐risk analysis and internal validation revealed AFP > 100 ng/ml (subdistribution hazard ratio: 7.28; p < 0.001) and prior HCC (subdistribution hazard ratio: 3.77; p = 0.002) as independent predictors (Harrell's C: 0.76). Based on this model using the AFP score (equally predictive within Milan criteria), patients were stratified into three NTR risk categories: HCC‐naïve with AFP < 100 ng/ml (low risk, n = 108 of 213), non‐HCC naïve with AFP < 100 ng/ml (intermediate risk, n = 92 of 213), AFP ≥ 100 ng/ml (high risk, n = 13 of 213), among whom 9.3% (3.7% [Milan]), 22.8% (25% [Milan]), and 61.5% (38/5% [Milan]) presented NTR (p < 0.001). Median recurrence‐free survival was 4.6, 14.5, and 43.4 months, respectively, in high‐risk, intermediate‐risk, and low‐risk categories (p < 0.001). Median overall survival, which was 19.1 months in high‐risk patients, was not reached otherwise (p < 0.001). Conclusion: Overall, PTA of ≤3‐cm HCC incurs a low NTR risk. Simple and noninvasive predictors (HCC naivety, AFP) accurately stratified patients' risk of NTR, and should help to improve treatment allocation. Patients with AFP ≥ 100 ng/ml have a high risk of NTR, poor recurrence‐free survival, and overall survival. Further studies evaluating preemptive transplantation or adjuvant/neoadjuvant strategies are highly needed in this small patient subset.

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

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

RNA sequencing analysis of hepatocellular carcinoma identified oxidative phosphorylation as a major pathologic feature

Dysregulation of expression of functional genes and pathways plays critical roles in the etiology and progression of hepatocellular carcinoma (HCC). Next generation-based RNA sequencing (RNA-seq) offers unparalleled power to comprehensively characterize HCC at the whole transcriptome level. In this study, 17 fresh-frozen HCC samples with paired non-neoplastic liver tissue from Caucasian patients undergoing liver resection or transplantation were used for RNA-seq analysis. Pairwise differential expression analysis of the RNA-seq data was performed to identify genes, pathways, and functional terms differentially regulated in HCC versus normal tissues. At a false discovery rate (FDR) of 0.10, 13% (n = 4335) of transcripts were up-regulated and 19% (n = 6454) of transcripts were down-regulated in HCC versus non-neoplastic tissue. Eighty-five Kyoto Encyclopedia of Genes and Genomes pathways were differentially regulated (FDR, <0.10), with almost all pathways (n = 83) being up-regulated in HCC versus non-neoplastic tissue. Among the top up-regulated pathways was oxidative phosphorylation (hsa00190; FDR, 1.12E-15), which was confirmed by Database for Annotation, Visualization, and Integrated Discovery (DAVID) gene set enrichment analysis. Consistent with potential oxidative stress due to activated oxidative phosphorylation, DNA damage-related signals (e.g., the up-regulated hsa03420 nucleotide excision repair [FDR, 1.14E-04] and hsa03410 base excision repair [FDR, 2.71E-04] pathways) were observed. Among down-regulated genes (FDR, <0.10), functional terms related to cellular structures (e.g., cell membrane [FDR, 3.05E-21] and cell junction [FDR, 2.41E-07], were highly enriched, suggesting compromised formation of cellular structure in HCC at the transcriptome level. Interestingly, the olfactory transduction (hsa04740; FDR, 1.53E-07) pathway was observed to be down-regulated in HCC versus non-neoplastic tissue, suggesting impaired liver chemosensory functions in HCC. Our findings suggest oxidative phosphorylation and the associated DNA damage may be the major driving pathologic feature in HCC.

MRI features of histologic subtypes of hepatocellular carcinoma: correlation with histologic, genetic, and molecular biologic classification

HCC is a heterogeneous group of tumors in terms of histology, genetic aberration, and protein expression. Advancements in imaging techniques have allowed imaging diagnosis to become a critical part of managing HCC in the clinical setting, even without pathologic diagnosis. With the identification of many HCC subtypes, there is increasing correlative evidence between imaging phenotypes and histologic, molecular, and genetic characteristics of various HCC subtypes. In this review, current knowledge of histologic heterogeneity of HCC correlated to features on gadolinium-enhanced dynamic liver MRI will be discussed. In addition, HCC subtype classification according to transcriptomic profiles will be outlined with descriptions of histologic, genetic, and molecular characteristics of some relatively well-established morphologic subtypes, namely the low proliferation class (steatohepatitic HCC and CTNNB1-mutated HCC) and the high proliferation class (macrotrabecular-massive HCC (MTM-HCC), scirrhous HCC, and CK19-positive HCC). Characteristics of sarcomatoid HCC and fibrolamellar HCC will also be discussed. Further research on radiological characteristics of HCC subtypes may ultimately enable non-invasive diagnosis and serve as a biomarker in predicting prognosis, molecular characteristics, and therapeutic response. In the era of precision medicine, a multidisciplinary effort to develop an integrated radiologic and clinical diagnostic system of various HCC subtypes is necessary. KEY POINTS: • HCC is a heterogeneous group of tumors in terms of histology, genetic aberration, and protein expression, which can be divided into many subtypes according to transcriptome profiles. • There is increasing evidence of a correlation between imaging phenotypes and histologic, genetic, and molecular biologic characteristics of various HCC subtypes. • Imaging characteristics may ultimately enable non-invasive diagnosis and subtype characterization, serving as a biomarker for predicting prognosis, molecular characteristics, and therapeutic response.

Deleting the β-catenin degradation domain in mouse hepatocytes drives hepatocellular carcinoma or hepatoblastoma-like tumor growth

BACKGROUND & AIMS

One-third of hepatocellular carcinomas (HCCs) harbor mutations activating the β-catenin pathway, predominantly via mutations in the CTNNB1 gene itself. Mouse models of Apc loss-of-function are widely used to mimic β-catenin-dependent tumorigenesis. Given the low prevalence of APC mutations in human HCCs, we aimed to generate liver tumors through CTNNB1 exon 3 deletion (βcat^Δex3). We then compared βcat^Δex3 liver tumors with liver tumors generated via frameshift in exon 15 of Apc (Apc^fs-ex15).

METHODS

We used hepatocyte-specific and inducible mouse models generated through either a Cre-Lox or a CRISPR/Cas9 approach using adeno-associated virus vectors. Tumors generated by the Cre-Lox models were phenotypically analyzed using immunohistochemistry and were selected for transcriptomic analysis by RNA-sequencing (RNAseq). Mouse RNAseq data were compared to human RNAseq data (8 normal tissues, 48 HCCs, 9 hepatoblastomas) in an integrative analysis. Tumors generated via CRISPR were analyzed using DNA sequencing and immuno-histochemistry.

RESULTS

Mice with CTNNB1 exon 3 deletion in hepatocytes developed liver tumors indistinguishable from Apc^fs-ex15 liver tumors. Both Apc^fs-ex15 and βcat^Δex3 mouse models induced growth of phenotypically distinct tumors (differentiated or undifferentiated). Integrative analysis of human and mouse tumors showed that differentiated mouse tumors cluster with well-differentiated human CTNNB1-mutated tumors. Conversely, undifferentiated mouse tumors cluster with human mesenchymal hepatoblastomas and harbor activated YAP signaling.

CONCLUSION

Apc^fs-ex15 and βcat^Δex3 mouse models both induce growth of tumors that are transcriptionally similar to either well-differentiated and β-catenin-activated human HCCs or mesenchymal hepatoblastomas.

LAY SUMMARY

New and easy-to-use transgenic mouse models of primary liver cancers have been generated, with mutations in the gene encoding beta-catenin, which are frequent in both adult and pediatric primary liver cancers. The mice develop both types of cancer, constituting a strong preclinical model.

Necroptosis throws novel insights on patient classification and treatment strategies for hepatocellular carcinoma

Introduction

Necroptosis is a novel pattern of immunogenic cell death and has triggered an emerging wave in antitumor therapy. More evidence has suggested the potential associations between necroptosis and intra-tumoral heterogeneity. Currently, the underlying role of necroptosis remains elusive in hepatocellular carcinoma (HCC) at antitumor immunity and inter-tumoral heterogeneity.

Methods

This study enrolled a total of 728 HCC patients and 139 immunotherapy patients from eight public datasets. The consensus clustering approach was employed to depict tumor heterogeneity of cancer necroptosis. Subsequently, our study further decoded the heterogeneous clinical outcomes, genomic landscape, biological behaviors, and immune characteristics in necroptosis subtypes. For each patient, providing curative clinical recommendations and developing potential therapeutic drugs were used to promote precise medicine.

Results

With the use of the weighted gene coexpression network analysis (WGCNA) algorithm, necroptosis-associated long non-coding RNAs (lncRNAs) (NALRs) were identified in HCC. Based on the NALR expression, two heterogeneous subtypes were decoded with distinct clinical outcomes. Compared to patients in C1, patients in C2 harbored superior pathological stage and presented more unfavorable overall survival and recurrence-free survival. Then, the robustness and reproducibility of necroptosis subtypes were further validated via the nearest template prediction (NTP) approach and classical immune phenotypes. Through comprehensive explorations, C1 was characterized by enriched immune-inflammatory and abundant immune infiltration, while C2 possessed elevated proliferative and metabolic activities and highly genomic instability. Moreover, our results indicated that C1 was more prone to obtain desirable benefits from immunotherapy. For patients in C2, numerous underlying therapeutic agents were developed, which might produce significant efficacy.

Conclusion

This study identified two necroptosis subtypes with distinct characteristics, decoding the tumor heterogeneity. For an individualized patient, our work tailored corresponding treatment strategies to improve clinical management.

USP28 Deubiquitinates TCF7L2 to Govern the Action of Wnt Signaling Pathway in Hepatic Carcinoma

Overexpression of ubiquitin‐specific protease 28 (USP28) is found in hepatic carcinoma. It is unclear whether the deubiquitinase plays a role in hepatocarcinogenesis. Deregulation of the Wnt signaling pathway is frequently associated with liver cancer. Transcription factor 7‐like 2 (TCF7L2) is an important downstream transcription factor of the Wnt/β‐catenin signaling pathway, but the mechanisms by which TCF7L2 itself is regulated have not yet been revealed. Here, we report that USP28 promotes the activity of the Wnt signaling pathway through maintaining the stability of TCF7L2. We further show that FBXW7 is the E3 ubiquitin ligase for TCF7L2. By regulating the levels of TCF7L2, USP28 modulates the Wnt/β‐catenin signaling in liver cancer and USP28 depletion or inhibition by a small molecule inhibitor leads to a halt of growth in liver cancer cells. These results suggest that USP28 could be a potential therapeutic target for liver cancer.

Immune Evasion and Drug Resistance Mediated by USP22 in Cancer: Novel Targets and Mechanisms

Regulation of ubiquitination is involved in various processes in cancer occurrence and development, including cell cycle arrest, cell proliferation, apoptosis, invasion, metastasis, and immunity. Ubiquitination plays an important role not only at the transcriptional and post-translational levels but also at the protein level. When ubiquitination is in a pathological state, abnormally activated biological processes will not only induce cancer progression but also induce immune evasion. The main function of deubiquitinases (DUBs) is to remove ubiquitin chains from substrates, changing the biological activity of the substrates. It has great potential to improve the prognosis of cancer by targeting DUB to regulate proteome. Ubiquitin-specific peptidase 22 (USP22) belongs to the ubiquitin-specific protease (USP) family of DUBs and has been reported to be related to various physiological and pathological processes. USP22 is abnormally expressed in various malignant tumors such as prostate cancer, lung cancer, liver cancer, and colorectal cancer, which suggests that USP22 may play an important role in tumors. USP22 may stabilize programmed death ligand 1 (PD-L1) by deubiquitination while also regulating T-cell infiltration into tumors. Regulatory T cells (Tregs) are a unique class of immunosuppressive CD4⁺ T cells that primarily suppress the immune system by expressing the master transcription factor forkhead box protein 3 (FOXP3). USP22 was found to be a positive regulator of stable FOXP3 expression. Treg-specific ablation of USP22 leads to reduced tumor volume in multiple cancer models. This suggests that USP22 may regulate tumor resistance to immunotherapy. In this article, we review and summarize the biological functions of USP22 in multiple signal transduction pathways during tumorigenesis, immune evasion, and drug resistance. Furthermore, we propose a new possibility of combining USP22 with chemotherapeutic, targeted, and immunosuppressive drugs in the treatment of cancer.

Comprehensive Analysis Identifies and Validates the Tumor Microenvironment Subtypes to Predict Anti-Tumor Therapy Efficacy in Hepatocellular Carcinoma

Objective

The objective of this study was to explore and verify the subtypes in hepatocellular carcinoma based on the immune (lymphocyte and myeloid cells), stem, and stromal cells in the tumor microenvironment and analyze the biological characteristics and potential relevance of each cluster.

Methods

We used the xCell algorithm to calculate cell scores and got subtypes by k-means clustering. In the external validation sets, we verified the conclusion stability by a neural network model. Simultaneously, we speculated the inner connection between clusters by pseudotime trajectory analysis and confirmed it by pathway enrichment, TMB, CNV, etc., analysis.

Result

According to the results of the consensus cluster, we chose k = 4 as the optimal value and got four different subtypes (C1, C2, C3, and C4) with different biological characteristics based on infiltrating levels of 48 cells in TME. In univariable Cox regression, the hazard ratio (HR) value of C3 versus C1 was 2.881 (95% CI: 1.572–5.279); in multivariable Cox regression, we corrected the age and TNM stage, and the HR value of C3 versus C1 was 2.510 (95% CI: 1.339–4.706). C1 and C2 belonged to the immune-active type, C3 and C4 related to the immune-insensitive type and the potential conversion relationships between clusters. We established a neural network model, and the area under the curves of the neural network model was 0.949 in the testing cohort; the same survival results were also observed in the external validation set. We compared the differences in cell infiltration, immune function, pathway enrichment, TMB, and CNV of four clusters and speculated that C1 and C2 were more likely to benefit from immunotherapy and C3 may benefit from FGF inhibitors.

Discussion

Our analysis provides a new approach for the identification of four tumor microenvironment clusters in patients with liver cancer and identifies the biological differences and predicts the immunotherapy efficacy between the four subtypes.

RBM47 inhibits hepatocellular carcinoma progression by targeting UPF1 as a DNA/RNA regulator

The mechanisms by which the tumor behaviors of hepatocellular carcinoma (HCC) support growth and metastasis remain largely unknown, and it has become increasingly apparent that molecular dysregulation is of considerable importance for cellular signaling pathways. Recently, RNA-binding motif protein 47 (RBM47) has been suggested to function as a tumor regulator by acting as an RNA binding protein (RBP), but its role in HCC remains ambiguous. Here, in HCC, we identified that RBM47 had an inhibitory influence on tumor behaviors in vitro and accordingly suppressed the growth and metastasis of xenograft tumors in vivo. Additionally, RBM47 was verified to positively regulate Upframeshift 1 (UPF1), which is a crucial protein involved in the nonsense-mediated RNA decay (NMD) process and was previously determined to be an HCC suppressor. Mechanistically, the stability of UPF1 mRNA was demonstrated to be enhanced with its 3’UTR bound by RBM47, which acted as an RNA binding protein. Meanwhile, RBM47 was also proven to promote the transcription of UPF1 as a transcription factor. Taken together, we concluded that RBM47 functioned as a tumor suppressor by upregulating UPF1, acting as a DNA/RNA binding protein at the transcriptional and posttranscriptional levels.

Construction of a Novel Clinical Stage-Related Gene Signature for Predicting Outcome and Immune Response in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) with high heterogeneity is one of the most frequent malignant tumors. However, there were no studies to create a clinical stage-related gene signature for HCC patients. Differentially expressed genes (DEGs) associated with clinical stage of HCC were analyzed based on TCGA datasets. Functional enrichment analysis was carried out by the use of stage-related DEGs. Then, the least absolute shrinkage and selection operator (LASSO) regression and univariate Cox regression were performed to reduce the overfit and the number of genes for further analysis. Next, survival and ROC assays were carried out to demonstrate the model using TCGA. Functional analysis and immune microenvironment analysis related to stage-related DEGs were performed. Reverse transcriptase polymerase chain reaction (RT-PCR) and Cell Counting Kit-8 (CCK-8) assays were applied to examine the expression and function of PNCK in HCC. In this research, there were 21 DEGs between HCC specimens with stage (I-II) and HCC specimens with stage (III-IV), including 20 increased genes and 1 decreased genes. A novel seven-gene signature (including PITX2, PNCK, GLIS1, SCNN1G, MMP1, ZNF488, and SHISA9) was created for the prediction of outcomes of HCC patients. The ROC curves confirmed the prognostic value of the new model. Cox assays demonstrated that the seven-gene signature can independently forecast overall survival. The immune analysis revealed that patients with low risk score exhibited more immune activities. Moreover, we confirmed that PNCK expressions were distinctly increased in HCC, and its silence suppressed the proliferation of HCC cells. Overall, our research offered a robust and reliable gene signature which displayed an important value in the prediction of overall survival of HCC patients and might deliver more effective personalized therapies.