Survival In Hepatocellular Carcinoma Research Articles

Comparative analysis of perioperative and long-term outcomes of patients with hepatocellular carcinoma: Nonalcoholic fatty liver disease versus viral hepatitis.

Despite the accumulating evidence regarding the oncological differences between nonalcoholic fatty liver disease (NAFLD)-related hepatocellular carcinoma (HCC) and viral infection-related HCC, the short- and long-term outcomes of surgical resection of NAFLD-related HCC remain unclear. While some reports indicate improved postoperative survival in NAFLD-related HCC, other studies suggest higher postoperative complications in these patients. Patients with NAFLD and those with hepatitis viral infection who underwent hepatectomy for HCC at our department were retrospectively analyzed. The clinical, surgical, pathological, and survival outcomes were compared between the two groups. Among the 1047 consecutive patients who underwent hepatectomy for HCC, 57 had NAFLD-related HCC (NAFLD group), and 727 had virus-related HCC (VH group). The body mass index and serum glycated hemoglobin levels were significantly higher in the NAFLD group than in the VH group. There were no significant differences in operative time and bleeding amount. Moreover, the morbidity and the length of postoperative hospital stays were similar across both groups. The pathological results showed that the tumor size was significantly larger in the NAFLD group than in the VH group. No significant differences between the groups in overall or recurrence-free survival were found. In a subgroup analysis with matched tumor diameters, patients in the NAFLD group had a better prognosis after hepatectomy than those in the VH group. Surgical outcomes after hepatectomy were comparable between the groups. Subgroup analysis reveals early detection and surgical intervention in NAFLD-HCC may improve prognosis.

Suppression of A-to-I RNA-editing enzyme ADAR1 sensitizes hepatocellular carcinoma cells to oxidative stress through regulating Keap1/Nrf2 pathway

BackgroundA-to-I RNA editing is an abundant post-transcriptional modification event in hepatocellular carcinoma (HCC). Evidence suggests that adenosine deaminases acting on RNA 1 (ADAR1) correlates to oxidative stress that is a crucial factor of HCC pathogenesis. The present study investigated the effect of ADAR1 on survival and oxidative stress of HCC, and underlying mechanisms.MethodsADAR1 expression was measured in fifty HCC and normal tissues via real-time quantitative PCR, and immunohistochemistry. For stable knockdown or overexpression of ADAR1, adeno-associated virus vectors carrying sh-ADAR1 or ADAR1 overexpression were transfected into HepG2 and SMMC-7721 cells. Transfected cells were exposed to oxidative stress agonist tBHP or sorafenib Bay 43-9006. Cell proliferation, apoptosis, and oxidative stress were measured, and tumor xenograft experiment was implemented.ResultsADAR1 was up-regulated in HCC and correlated to unfavorable clinical outcomes. ADAR1 deficiency attenuated proliferation of HCC cells and tumor growth and enhanced apoptosis. Moreover, its loss facilitated intracellular ROS accumulation, and elevated Keap1 and lowered Nrf2 expression. Intracellular GSH content and SOD activity were decreased and MDA content was increased in the absence of ADAR1. The opposite results were observed when ADAR1 was overexpressed. The effects of tBHP and Bay 43–9006 on survival, apoptosis, intracellular ROS accumulation, and Keap1/Nrf2 pathway were further exacerbated by simultaneous inhibition of ADAR1.ConclusionsThe current study unveils that ADAR1 is required for survival and oxidative stress of HCC cells, and targeting ADAR1 may sensitize HCC cells to oxidative stress via modulating Keap1/Nrf2 pathway.

Machine Learning-Based Assessment of Survival and Risk Factors in Non-Alcoholic Fatty Liver Disease-Related Hepatocellular Carcinoma for Optimized Patient Management.

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, with an incidence that is exponentially increasing. Hepatocellular carcinoma (HCC) is the most frequent primary tumor. There is an increasing relationship between these entities due to the potential risk of developing NAFLD-related HCC and the prevalence of NAFLD. There is limited evidence regarding prognostic factors at the diagnosis of HCC. This study compares the prognosis of HCC in patients with NAFLD against other etiologies. It also evaluates the prognostic factors at the diagnosis of these patients. For this purpose, a multicenter retrospective study was conducted involving a total of 191 patients. Out of the total, 29 presented NAFLD-related HCC. The extreme gradient boosting (XGB) method was employed to develop the reference predictive model. Patients with NAFLD-related HCC showed a worse prognosis compared to other potential etiologies of HCC. Among the variables with the worst prognosis, alcohol consumption in NAFLD patients had the greatest weight within the developed predictive model. In comparison with other studied methods, XGB obtained the highest values for the analyzed metrics. In conclusion, patients with NAFLD-related HCC and alcohol consumption, obesity, cirrhosis, and clinically significant portal hypertension (CSPH) exhibited a worse prognosis than other patients. XGB developed a highly efficient predictive model for the assessment of these patients.

Three-dimensional morphology scoring of hepatocellular carcinoma stratifies prognosis and immune infiltration

BackgroundThe morphological attributes could serve as pivotal indicators precipitating early recurrence and dismal overall survival in hepatocellular carcinoma (HCC), and quantifying morphological features may better stratify the prognosis of HCC. ObjectiveTo develop a radiomics approach based on 3D tumor morphology features for predicting the prognosis of HCC and identifying differentially expressed genes related to morphology to guide HCC treatment. Materials and methodsRetrospective study of 357 HCC patients. Radiomic features were extracted from MRI tumor regions; 14 morphology-related features predicted early HCC recurrence and patient stratification via LASSO-Cox modeling. Overall survival (OS) and recurrence-free survival (RFS) were analyzed. RNA sequencing from the Cancer Imaging Archive (TCIA) examined drug sensitivity and stratified HCC using morphological immunity genes, validating recurrence and prognosis. ResultsPatients were split into training (n = 225), test (n = 132), and 50 TCIA dataset cohorts. Two features (Maximum2DdiameterColumn, Sphericity) in Cox regression stratified patients into high/low-risk Morphological Radiological Score (Morph-RS) groups. Significant OS and RFS were seen across all sets. Differentially expressed genes focused on T cell receptor signaling; low-risk group had higher T cells (P = 0.039), B cells (P = 0.041), NK cells (P = 0.018). SN-38, GSK2126458 might treat high-risk morphology. Morphology-immune genes stratified HCC, showing significant RFS/OS differences. ConclusionTumor Morph-RS effectively stratifies HCC patients' recurrence and prognosis. Limited immune infiltration seen in Morph-RS high-risk groups signifies the potential of employing tumor morphology as a potent visual biomarker for diagnosing and managing HCC.

Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images.

Accurate preoperative prediction of microvascular invasion (MVI) and recurrence-free survival (RFS) is vital for personalised hepatocellular carcinoma (HCC) management. We developed a multitask deep learning model to predict MVI and RFS using preoperative MRI scans. Utilising a retrospective dataset of 725 HCC patients from seven institutions, we developed and validated a multitask deep learning model focused on predicting MVI and RFS. The model employs a transformer architecture to extract critical features from preoperative MRI scans. It was trained on a set of 234 patients and internally validated on a set of 58 patients. External validation was performed using three independent sets (n = 212, 111, 110). The multitask deep learning model yielded high MVI prediction accuracy, with AUC values of 0.918 for the training set and 0.800 for the internal test set. In external test sets, AUC values were 0.837, 0.815 and 0.800. Radiologists' sensitivity and inter-rater agreement for MVI prediction improved significantly when integrated with the model. For RFS, the model achieved C-index values of 0.763 in the training set and ranged between 0.628 and 0.728 in external test sets. Notably, PA-TACE improved RFS only in patients predicted to have high MVI risk and low survival scores (p < .001). Our deep learning model allows accurate MVI and survival prediction in HCC patients. Prospective studies are warranted to assess the clinical utility of this model in guiding personalised treatment in conjunction with clinical criteria.

Prognostic and clinicopathological significance of systemic inflammation response index in patients with hepatocellular carcinoma: a systematic review and meta-analysis.

It is unclear whether the systemic inflammation response index (SIRI) can predict the prognosis of patients with hepatocellular carcinoma (HCC). Consequently, the present study focused on systematically identifying the relationship between SIRI and the prognosis of patients with HCC through a meta-analysis. Systematic and comprehensive studies were retrieved from PubMed, Web of Science, Embase, and the Cochrane Library from their inception to August 10, 2023. The role of SIRI in predicting overall survival (OS) and progression-free survival (PFS) in HCC was determined using pooled hazard ratios (HRs) and 95% confidence intervals (CIs). Odds ratios (ORs) and 95% CIs were pooled to analyze the correlations between SIRI and the clinicopathological features of HCC. Ten articles involving 2,439 patients were included. An elevated SIRI was significantly associated with dismal OS (HR=1.75, 95% CI=1.52-2.01, p<0.001) and inferior PFS (HR=1.66, 95% CI=1.34-2.05, p<0.001) in patients with HCC. Additionally, according to the combined results, the increased SIRI was significantly related to multiple tumor numbers (OR=1.42, 95% CI=1.09-1.85, p=0.009) and maximum tumor diameter >5cm (OR=3.06, 95% CI=1.76-5.30, p<0.001). However, the SIRI did not show any significant relationship with sex, alpha-fetoprotein content, Child-Pugh class, or hepatitis B virus infection. According to our results, elevated SIRI significantly predicted OS and PFS in patients with HCC. Moreover, the SIRI was significantly associated with tumor aggressiveness. https://inplasy.com/inplasy-2023-9-0003/, identifier INPLASY202390003.

Identification of immune cell-related prognostic genes characterized by a distinct microenvironment in hepatocellular carcinoma.

The development and progression of hepatocellular carcinoma (HCC) have been reported to be associated with immune-related genes and the tumor microenvironment. Nevertheless, there are not enough prognostic biomarkers and models available for clinical use. Based on seven prognostic genes, this study calculated overall survival in patients with HCC using a prognostic survival model and revealed the immune status of the tumor microenvironment (TME). To develop a novel immune cell-related prognostic model of HCC and depict the basic profile of the immune response in HCC. We obtained clinical information and gene expression data of HCC from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. TCGA and ICGC datasets were used for screening prognostic genes along with developing and validating a seven-gene prognostic survival model by weighted gene coexpression network analysis and least absolute shrinkage and selection operator regression with Cox regression. The relative analysis of tumor mutation burden (TMB), TME cell infiltration, immune checkpoints, immune therapy, and functional pathways was also performed based on prognostic genes. Seven prognostic genes were identified for signature construction. Survival receiver operating characteristic curve analysis showed the good performance of survival prediction. TMB could be regarded as an independent factor in HCC survival prediction. There was a significant difference in stromal score, immune score, and estimate score between the high-risk and low-risk groups stratified based on the risk score derived from the seven-gene prognostic model. Several immune checkpoints, including VTCN1 and TNFSF9, were found to be associated with the seven prognostic genes and risk score. Different combinations of checkpoint blockade targeting inhibitory CTLA4 and PD1 receptors and potential chemotherapy drugs hold great promise for specific HCC therapies. Potential pathways, such as cell cycle regulation and metabolism of some amino acids, were also identified and analyzed. The novel seven-gene (CYTH3, ENG, HTRA3, PDZD4, SAMD14, PGF, and PLN) prognostic model showed high predictive efficiency. The TMB analysis based on the seven genes could depict the basic profile of the immune response in HCC, which might be worthy of clinical application.

Surrogacy of one-year survival for overall survival in advanced hepatocellular carcinoma

BackgroundThe increasing number of sequential treatments complicates the evaluation of overall survival (OS) in clinical trials for hepatocellular carcinoma (HCC), therefore, reliable surrogate endpoints (SEs) are required. This study aimed to evaluate the surrogacy of progression-free survival (PFS) and one-year (1-yr) milestone survival for OS in HCC trials.MethodsWe systematically searched databases for randomized clinical trials that evaluated systemic treatments for advanced HCC. Individual patient data were reconstructed to calculate the 1-yr survival rate. We adopted a two-stage meta-analytic validation model to evaluate the correlation between SEs and OS, and the correlation between treatment effects on SEs and OS. The hazard ratio (HR) was calculated to assess the treatment effects on PFS and OS, and the 1-yr survival ratio was calculated to evaluate the treatment effects on the 1-yr milestone survival.ResultsThirty-two HCC trials involving 13,808 patients were included. A weak correlation was detected between the median PFS and median OS (R2 = 0.32), whereas the correlation improved between PFS HR and OS HR (R2 = 0.58). We identified strong correlations between the 1-yr survival rate and median OS and between the 1-yr survival ratio and OS HR (R2 = 0.74 and 0.65, respectively). In subgroup analyses, PFS HR strongly correlated with OS HR in trials relevant to immune checkpoint inhibitors (ICIs). Although the correlation remained weak between PFS and OS even in trials with PFS HR ≤ 0.6, the 1-yr survival rate and 1-yr survival ratio were strong surrogates for median OS and OS HR, respectively (R2 = 0.77 and 0.75).ConclusionsOne-year milestone survival outperformed PFS as a SE for OS in HCC, indicating the application of 1-yr survival as a secondary endpoint. In particular, PFS HR was a potential SE for OS HR in the ICI trials.

Elevated expression of HIGD1A drives hepatocellular carcinoma progression by regulating polyamine metabolism through c-Myc–ODC1 nexus

BackgroundHypoxia contributes to cancer progression through various molecular mechanisms and hepatocellular carcinoma (HCC) is one of the most hypoxic malignancies. Hypoxia-inducible gene domain protein-1a (HIGD1A) is typically induced via epigenetic regulation and promotes tumor cell survival during hypoxia. However, the role of HIGD1A in HCC remains unknown.MethodsHIGD1A expression was determined in 24 pairs of human HCC samples and para-tumorous tissues. Loss-of-function experiments were conducted both in vivo and in vitro to explore the role of HIGD1A in HCC proliferation and metastasis.ResultsIncreased HIGD1A expression was found in HCC tissues and cell lines, which was induced by hypoxia or low-glucose condition. Moreover, HIGD1A knockdown in HCC cells arrested the cell cycle at the G2/M phase and promoted hypoxia-induced cell apoptosis, resulting in great inhibition of cell proliferation, migration, and invasion, as well as tumor xenograft formation. Interestingly, these anti-tumor effects were not observed in normal hepatocyte cell line L02. Further, HIGD1A knockdown suppressed the expression of ornithine decarboxylase 1 (ODC1), a rate-limiting enzyme of polyamine metabolism under c-Myc regulation. HIGD1A was found to bind with the c-Myc promoter region, and its knockdown decreased the levels of polyamine metabolites. Consistently, the inhibitory effect on HCC phenotype by HIGD1A silencing could be reversed by overexpression of c-Myc or supplementation of polyamines.ConclusionsOur results demonstrated that HIGD1A activated c-Myc–ODC1 nexus to regulate polyamine synthesis and to promote HCC survival and malignant phenotype, implying that HIGD1A might represent a novel therapeutic target for HCC.

Signature construction and molecular subtype identification based on liver-specific genes for prediction of prognosis, immune activity, and anti-cancer drug sensitivity in hepatocellular carcinoma

BackgroundLiver specific genes (LSGs) are crucial for hepatocyte differentiation and maintaining normal liver function. A deep understanding of LSGs and their heterogeneity in hepatocellular carcinoma (HCC) is necessary to provide clues for HCC diagnosis, prognosis, and treatment.MethodsThe bulk and single-cell RNA-seq data of HCC were downloaded from TCGA, ICGC, and GEO databases. Through unsupervised cluster analysis, LSGs-based HCC subtypes were identified in TCGA-HCC samples. The prognostic effects of the subtypes were investigated with survival analyses. With GSVA and Wilcoxon test, the LSGs score, stemness score, aging score, immune score and stromal score of the samples were estimated and compared. The HCC subtype-specific genes were identified. The subtypes and their differences were validated in ICGC-HCC samples. LASSO regression analysis was used for key gene selection and risk model construction for HCC overall survival. The model performance was estimated and validated. The key genes were validated for their heterogeneities in HCC cell lines with quantitative real-time PCR and at single-cell level. Their dysregulations were investigated at protein level. Their correlations with HCC response to anti-cancer drugs were estimated in HCC cell lines.ResultsWe identified three LSGs-based HCC subtypes with different prognosis, tumor stemness, and aging level. The C1 subtype with low LSGs score and high immune score presented a poor survival, while the C2 subtype with high LSGs score and immune score indicated an enduring survival. Although no significant survival difference between C2 and C3 HCCs was shown, the C2 HCCs presented higher immune score and stroma score. The HCC subtypes and their differences were confirmed in ICGC-HCC dataset. A five-gene prognostic signature for HCC survival was constructed. Its good performance was shown in both the training and validation datasets. The five genes presented significant heterogeneities in different HCC cell lines and hepatocyte subclusters. Their dysregulations were confirmed at protein level. Furthermore, their significant associations with HCC sensitivities to anti-cancer drugs were shown.ConclusionsLSGs-based HCC subtype classification and the five-gene risk model might provide useful clues not only for HCC stratification and risk prediction, but also for the development of more personalized therapies for effective HCC treatment.

Diagnostic and Prognostic Value of Methyltransferase Like 13 in Hepatocellular Carcinoma Based on Bioinformatics Analysis.

Hepatocellular carcinoma (HCC) is one of the cancers with the highest incidence and mortality rates. This study aims to explore the diagnostic and prognostic utility of methyltransferase like 13 (METTL13) in patients with HCC via bioinformatics analysis. We obtained mRNA data of HCC from the database of the Cancer Genome Atlas (TCGA), drawing survival curve by R 4.2.1 software. Cox regression analysis was conducted based on tumor stage and METTL13 expression. The GSE114564 dataset was chosen from the Gene Expression Omnibus. The differences in serum METTL13 levels between the groups of early HCC (eHCC) and non-cancer controls were evaluated. Using a receiver operating characteristic curve, we calculated the area under the curve (AUC) of serum METTL13 for diagnosing eHCC. A total of 225 cases with HCC were screened from TCGA, and 29 cases were normal controls. The results showed that the METTL13 expression in the HCC group was higher than that in the normal controls (P <.001). The univariate [hazard ratio (HR) = 1.895, P = .006] and multivariate Cox regression (HR = 1.702, P = .037) analyses showed that high METTL13 expression reduced overall survival in HCC. Serum METTL13 levels were higher in the eHCC group than in the non-cancer controls (P = .008). The optimum AUC for predicting eHCC by serum METTL13 was 0.7091. Serum METTL13 has a moderate diagnostic value for eHCC. High METTL13 expression is correlated with a worse prognosis in patients with HCC. Methyltransferase like 13 possesses the potential to be a novel biomarker for HCC.

Development of a novel lncRNA-derived immune gene score using machine learning-based ensembles for predicting the survival of HCC

BackgroundLong noncoding RNAs (lncRNAs) are implicated in the tumor immunology of hepatocellular carcinoma (HCC). MethodsHCC mRNA and lncRNA expression profiles were used to extract immune-related genes with the ImmPort database, and immune-related lncRNAs with the ImmLnc algorithm. The MOVICS package was used to cluster immune-related mRNA, immune-related lncRNA, gene mutation and methylation data on HCC from the TCGA. GEO and ICGC datasets were used to validate the model. Data from single-cell sequencing was used to determine the expression of genes from the model in various immune cell types. ResultsWith this model, the area under the curve (AUC) for 1-, 3- and 5-year survival of HCC patients was 0.862, 0.869 and 0.912, respectively. Single-cell sequencing showed EREG was significantly expressed in a variety of immune cell types. Knockdown of the EREG target gene resulted in significant anti-apoptosis, pro-proliferation and pro-migration effects in HepG2 and HUH7 cells. Moreover, serum and liver tissue EREG levels in HCC patients were significantly higher than those of healthy control patients. ConclusionWe built a prognostic model with good accuracy for predicting HCC patient survival. EREG is a potential immunotherapeutic target and a promising prognostic biomarker.

Advanced lung cancer inflammation index predicts overall survival of hepatocellular carcinoma after hepatectomy.

Limited data are available regarding ALI's clinical relevance and prognostic value in patients with hepatocellular carcinoma (HCC) after hepatectomy. HCC patients who received hepatectomy at the Meizhou People's Hospital from May 2011 to February 2022 were enrolled in the study cohort. The ALI was calculated as follows: ALI = BMI (kg/m2) × ALB (g/dL)/(absolute neutrophil count/absolute lymphocyte count). The primary outcome was overall survival (OS). The secondary outcome was cancer-specific survival (CSS). Univariate and multivariate Cox regression analyses were performed, followed by nomogram construction and decision curve analysis (DCA). 425 HCC patients were enrolled for analyses. Lower preoperative ALI was significantly correlated with incomplete tumor capsule and advanced tumor stage. Lower preoperative ALI was an adverse independent prognostic factor for OS (HR: 1.512, 95% CI: 1.122-2.039, P 0.007) and CSS (HR: 1.754, 95% CI: 1.262-2.438, P <0.001) in HCC patients. The nomogram plot was built based on three (including age, TNM stage, and ALI) and two (including TNM stage and ALI) independent prognostic factors for OS and CSS, respectively. Further analyses indicated that the nomogram had better predictive value and some net benefit than the traditional TNM stage alone, especially in long-term OS. Our study further indicated that ALI could be a prognostic marker for OS and CSS in HCC patients after hepatectomy, especially in long-term OS.

Most deprived Louisiana census tracts have higher hepatocellular carcinoma incidence and worse survival.

Liver cancer incidence increased in the US from 1975 through 2015 with heterogeneous rates across subpopulations. Upstream or distal area-level factors impact liver cancer risks. The aim of this study was to examine the association between area-level deprivation and hepatocellular carcinoma (HCC) incidence and survival. We also explored the association between area deprivation and treatment modalities. Louisiana Tumor Registry identified 4,151 adult patients diagnosed with malignant HCC from 2011 to 2020 and linked residential address to census tract (CT)-level Area Deprivation Index (ADI) categorized into quartiles (Q1 = least deprived). ANOVA examined the association between ADI quartile and CT age-adjusted incidence rate (AAIR) per 100,000. Chi-square tested the distribution of demographic and clinical characteristics across ADI quartiles. Kaplan-Meier and proportional hazard models evaluated survival by deprivation quartile. Among the 1,084 CTs with incident HCC, the average (SD) AAIR was 8.02 (7.05) HCC cases per 100,000 population. ADI was observed to be associated with incidence, and the mean (SD) AAIR increased from 5.80 (4.75) in Q1 to 9.26 (7.88) in Q4. ADI was also associated with receipt of surgery (p < 0.01) and radiation (p < 0.01) but not chemotherapy (p = 0.15). However, among those who received chemotherapy, people living in the least deprived areas began treatment approximately 10 days sooner than those living in other quartiles. Q4 patients experienced the worst survival with a median of 247 (95% CI 211-290) days vs. Q1 patients with a median of 474 (95% CI 407-547) days (p < 0.0001). Q4 had marginally poorer survival (HR 1.20, 1.05-1.37) than Q1 but the association became non-significant (HR 1.12, 0.96-1.30) when adjusted for rurality, liquor store density, sex, race/ethnicity, age, insurance, BMI, stage, hepatitis diagnosis, and comorbidities. Increasing neighborhood (CT) deprivation (ADI) was observed to be associated with increased HCC incidence and poorer HCC survival. However, the association with poorer survival becomes attenuated after adjusting for putative confounders.

Stereotactic Body Radiation Therapy (SBRT) Versus Transarterial Chemoembolization (TACE) for Treatment Of Hepatocellular Carcinoma: a Meta-Analysis of Propensity Matched Studies

Introduction: There are currently limited data comparing the efficacy of stereotactic body radiation therapy (SBRT) to transarterial chemoembolization (TACE) for the treatment of hepatocellular carcinoma (HCC). The aim of this systematic review and meta-analysis was to report on the summary effect estimate of overall survival and local control at 1-year based on available evidence.&#x0D; Methods: A literature search was conducted in PubMed from database inception until April 2020. Articles were independently screened by two reviewers and included if they reported on a propensity-matched study design comparing SBRT to TACE for the treatment of HCC with at least 1 year follow up. Event data of overall survival and local control at 1-year were extracted. A random-effects model was applied to generate summary odds ratio and corresponding 95% confidence intervals (CI).&#x0D; Results: Four studies with 606 patients were identified and included. SBRT (73.6%) and TACE (67.0%) had similar 1-year rates of OS, with an OR of 0.87 (0.56, 1.37). SBRT (88.4%) had greater local control at 1 year compared to TACE (71.7%); OR of 0.34 (0.13, 0.86).&#x0D; Conclusion: SBRT is comparable to TACE in terms of 1-year survival for the treatment HCC and may provide an advantage in terms of local control. Future controlled trials are necessary to determine the clinical advantages and best indications for each treatment.

A novel disulfidptosis-related lncRNA signature for predicting prognosis and potential targeted therapy in hepatocellular carcinoma.

Disulfidptosis is a recently discovered mode of cell death with a significant role in cancer. Long non-coding RNAs (lncRNAs) have been implicated in numerous biological processes including oncogenesis, invasion, and metastasis. In this work, we developed an lncRNA signature associated with disulfidptosis for prediction of survival of hepatocellular carcinoma (HCC) patients. Detailed HCC expression profiles and clinical information were obtained from The Cancer Genome Atlas, and 599 differentially expressed disulfidptosis-related lncRNAs were identified through Pearson correlation analysis. Finally, by the least absolute shrinkage and selection operator method, we constructed an HCC prognostic model containing 7 disulfidptosis-related lncRNAs. We split patients into high- and low-risk groups based on the risk values generated by this model and showed that patients in the high-risk group had shorter overall survival times. In the training dataset, receiver operating characteristic curves for 1-, 3-, and 5-year survival were drawn according to the standard (0.788, 0.801, 0.803) and internal validation set (0.684, 0.595, 0.704) to assess the efficacy of the signature. Risk value was confirmed as an independent predictor and used to construct a nomogram in combination with several clinical factors. We further assessed the signature with respect to tumor immune landscape, gene set enrichment analysis, principal component analysis, tumor mutation burden, tumor immune dysfunction and exclusion, and drug sensitivity. High-risk patients had higher immune function scores, except for type II IFN response, whereas low-risk patients had significantly lower tumor immune dysfunction and rejection scores, indicating that they were more sensitive to immune checkpoint inhibitors. Drug sensitivity analysis showed that low-risk patients could benefit more from certain anti-tumor drugs, including sulafenib. In summary, we have constructed a novel signature that shows good performance in predicting survival of patients with HCC and may provide new insights for targeted tumor therapy.

Whole-Liver Based Deep Learning for Preoperatively Predicting Overall Survival in Patients with Hepatocellular Carcinoma.

Survival prediction is crucial for treatment decision making in hepatocellular carcinoma (HCC). We aimed to build a fully automated artificial intelligence system (FAIS) that mines whole-liver information to predict overall survival of HCC. We included 215 patients with preoperative contrast-enhance CT imaging and received curative resection from a hospital in China. The cohort was randomly split into developing and testing subcohorts. The FAIS was constructed with convolutional layers and full-connected layers. Cox regression loss was used for training. Models based on clinical and/or tumor-based radiomics features were built for comparison. The FAIS achieved C-indices of 0.81 and 0.72 for the developing and testing sets, outperforming all the other three models. In conclusion, our study suggest that more important information could be mined from whole liver instead of only the tumor. Our whole-liver based FAIS provides a non-invasive and efficient overall survival prediction tool for HCC before the surgery.

Clinical Characteristics and Survival of Hepatocellular Carcinoma: Insights from Single-Centre Experience in Saudi Arabia.

Background Hepatocellular carcinoma (HCC) represents the most common primary liver malignancy, with a high fatality rate. Relatively, Saudi Arabia has a high incidence of HCC, which is detected in later stages with a poor prognosis. This study aims to investigate the patterns, outcomes, and mortality predictors of HCC in Saudi Arabia. Method A retrospective study from April 2018 to June 2022 included patients with HCC who were diagnosedand managed at the Najran Oncology Center, Saudi Arabia. Through our cancer registry, the patients' clinical, laboratory, radiological, and survival profiles were extracted and analyzed to assess factors associated with mortality using a univariate analysis. The overall survival was calculated by the Kaplan-Meier method. Results The study involved 52 patients with an average age of 74.6 years, predominantly male (the male-to-female ratio is 2.25:1). Viral infections were the primary cause of liver disease in 40.3% (n=21) of patients. At diagnosis, the Child-Pugh class distribution included23.1% (n=12) patients in class A, 36.5% (n=19) patients in class B, and 40.4% (n=21) patients in class C. Uninodular tumors with ≤50% liver extension were observed in 65.4% (n=34) of cases, and 30.8% (n=16) had portal vein thrombosis. Elevated alpha-fetoprotein (AFP) levels were noted in 48.1% (n=25) of patients, with 23.1% (n=12) exceeding 400 ng/mL. Curative resection was performed in 32.7% (n=17) of patients. The mean survival time was 23±11.8 months (median of 22.5 months, minimum of six, and maximum of49 months). Relapse occurred in seven (13.5%) cases, while new metastasis occurred in 20 (38.5%) cases. During the study period, 26 (50.0%) patients died. The main cause of death was disease progression in 15 (28.8%) patients. Univariate analysis showed that AFP>400 ng/mL (OR: 4.68; 95% CI: 1.87-11.66, p=0.001), presence of relapse (OR: 0.16; 95% CI: 0.03-0.78, p=0.023), abdominal ascites (OR: 3.38; 95% CI: 1.25-9.14, p=0.016), advanced the Cancer of the Liver Italian Program (CLIP) score (OR: 0.60; 95% CI: 0.41-0.88, p=0.009) were associated with higher mortality rate and were statistically significant. Conclusion Most cases of HCC in our patients were attributed to viral hepatitis, with the majority having liver cirrhosis. Higher AFP (>400 ng/mL), relapse, abdominal ascites, and a higher cancer CLIP score were associated with poorer outcomes. Targeted screening and health education should be advocated; in addition, social determinants should be proactively addressed.

Surrogate endpoints for overall survival in advanced hepatocellular carcinoma: A meta-analysis.

563 Background: Recent advances in systemic therapies have resulted in improved overall survivals (OS) for patients with advanced hepatocellular carcinoma (aHCC). The most commonly utilized primary endpoint for phase III trials in aHCC is OS. A robust surrogate endpoint (SEP) can reduce time and financial costs of future trials and accelerate regulatory approvals of new therapies. We conducted a literature-based meta-analysis to evaluate SEPs for OS in aHCC. Methods: Randomized controlled trials evaluating systemic therapies in aHCC published 2007 - 2023 were identified through a systemic literature search of Cochrane and Medline databases as well as of abstracts presented at ASCO and ESMO meetings. Hazard ratios (HR) for OS and progression-free survival (PFS) and time to progression (TTP) were extracted. ΔORR was calculated as the difference in overall response rates (ORR) between control and experimental arms. Pearson correlation and mixed-effects meta-regression analyses were performed. Surrogate threshold effect (STE) was determined for each comparison when possible. A p &lt; 0.05 was considered to be statistically significant. Results: 26 trials were identified in the first-line setting with 14,827 patients and 11 trials in the subsequent-line setting with 5,316 patients. In first-line trials, immunotherapy (IO) is associated with higher ORR than other agents (p=0.003). There are statistically significant correlations between HRs of PFS/TTP/ΔORR and OS (Table). The relationship between HR-PFS and HR-OS persists in trials with or without IO, but only in trials enrolling &lt; 30% patients of non-viral aetiologies. In subsequent-line trials, there are statistically significant correlations between HRs of PFS/TTP and OS (Table). STE for HR PFS is 0.68 and 0.87 respectively for 1st and subsequent line trials. Conclusions: There are moderate to strong correlations between PFS and OS in aHCC in first-line and subsequent line trials. STE for HR-PFS of 0.68 in first-line and 0.87 in subsequent-line settings can guide sample size calculation in future clinical trials. [Table: see text]

Neo-adjuvant tislelizumab combined with lenvatinib treatment for resectable, recurrent hepatocellular carcinoma.

517 Background: The persistent challenge of elevated re-recurrence rates following secondary hepatectomy complicates the prospects for improving survival in recurrent hepatocellular carcinoma (rHCC) patients. Immunotherapy combined with targeted drugs have been the first-line therapy for advanced HCC and shown good response rate in neoadjuvant situation. However, the effectiveness and safety of the combination treatment has not been reported in rHCC patients. To address this, we conducted the present phase 2 clinical trial of neoadjuvant treatments using tislelizumab in combination with lenvatinib for rHCC patients. Methods: Patients with resectable rHCC patients who had previously undergone curative treatment were enrolled. Enrolled patients were treated with 2 neoadjuvant cycles of a combination of tislelizumab 200mg intravenously every 3 weeks and lenvatinib 8mg every day (12mg for patients over 60kg) for 4 weeks. Hepatectomy was conducted in six weeks after enrollment. One month after surgery, adjuvant combination of tislelizumab and lenvatinib was started for at least one year or until disease progression or intolerance of adverse reactions. The primary objective of the trial is to evaluate one-year disease-free survival (DFS) rate, and secondary endpoints include objective response rate (ORR) as assessed by RECIST 1.1, major pathologic response (defined as over 90% tumor necrosis), and safety considerations. Results: Until Sep 30th, 2023, a total of 14 patients have been enrolled. All participants underwent the complete neoadjuvant therapy with a combination of tislelizumab and lenvatinib before proceeding to hepatectomy. Throughout the neoadjuvant phase, 14.3% (2/14) of patients occurred adverse events below grade 3, with no severe adverse events occurring. The most common adverse events were fatigue (in 2 patients), hypertension (in 1 patient) and reduced appetite (in 1 patient). In 14 patients, 12 patients underwent R0 resection and 2 were waiting for hepatectomy. The average time from the initiation of the neoadjuvant therapy to hepatectomy was approximately 40.42 days. On the radiological front, one patient (8.3%) exhibited a partial response, while 11/12 (91.7%) displayed stable disease with 8 patients had tumor shrinkage. In terms of pathological outcomes, 25% of patients (3/12) achieved a complete response, whereas the remaining patients showed varying degrees of pathologic response, ranging from 5% to 85%. Conclusions: In summary, the dual therapy of tislelizumab and lenvatinib demonstrates encouraging safety and effectiveness as a neoadjuvant intervention for patients with rHCC. The long-term results of this combined treatment approach are eagerly anticipated. Clinical trial information: NCT04615143 .