Cohort Of Hepatocellular Carcinoma Patients Research Articles

Prognostic PET [11C]-acetate uptake is associated with hypoxia gene expression in patients with late-stage hepatocellular carcinoma – a bench to bed study

BackgroundPositron Emission Tomography (PET) with combined [18F]-FDG and [11C]-acetate (dual-tracer) is used for the management of hepatocellular carcinoma (HCC) patients, although its prognostic value and underlying molecular mechanism remain poorly understood. We hypothesized that radiotracer uptake might be associated with tumor hypoxia and validated our findings in public and local human HCC cohorts.MethodsTwelve orthotopic HCC xenografts were established using MHCC97L cells in female nude mice, with 5 having undergone hepatic artery ligation (HAL) to create tumor hypoxia in vivo. Tumors in both Control and HAL-treated xenografts were imaged with [11C]-acetate and [18F]-FDG PET-MR and RNA sequencing was performed on the resected tumors. Semiquantitative analysis of PET findings was then performed, and the findings were then validated on the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and patients from our institution.ResultsHAL-treated mice showed lower [11C]-acetate (HAL-treated vs. Control, tumor-to-liver SUV ratio (SUVTLR): 2.14[2.05–2.21] vs 3.11[2.75–5.43], p = 0.02) but not [18F]-FDG (HAL-treated vs. Control, SUVTLR: 3.73[3.12–4.35] vs 3.86[3.7–5.29], p = 0.83) tumor uptakes. Gene expression analysis showed the PET phenotype is associated with upregulation of hallmark hypoxia signature. The prognostic value of the hypoxia gene signature was tested on the TCGA-LIHC cohort with upregulation of hypoxia gene signature associated with poorer overall survival (OS) in late-stage (stage III and IV) HCC patients (n = 66, OS 2.05 vs 1.67 years, p = 0.046). Using a local cohort of late-stage HCC patients who underwent dual-tracer PET-CT, tumors without [11C]-acetate uptake are associated with poorer prognosis (n = 51, OS 0.25 versus 1.21 years, p < 0.0001) and multivariable analyses showed [11C]-acetate tumor uptake as an independent predictor of OS (HR 0.17 95%C 0.06–0.42, p < 0.0001).Conclusions[11C]-acetate uptake is associated with alteration of tumor hypoxia gene expression and poorer prognosis in patients with advanced HCC.

Abstract 7102: The central dogma of hepatocellular carcinoma: Genomic, transcriptomic, and proteomic changes

Abstract Cancer is a disease condition characterized by remarkable heterogeneity, wherein numerous molecular features display considerable disparities even with the same patient cohorts, leading to varied treatment outcomes. The primary factor contributing to the substantial differences observed across cancers stems from unique combinations of genetic mutations. Epigenetic alterations further contribute to differential gene expression and splicing, thereby enhancing transcriptomic diversity. The protein products originating from the cancer transcriptome constitute the specific intracellular and extracellular environment, consequently exerting supplementary effects on epigenetic, transcriptomic, and proteomic changes. The complex interplay and mutual influence between genetic aberrations, transcriptomes, and proteomes significantly contribute to shaping the extensive spectrum of molecular characteristics observed in cancer. With label-free mass spectrometry, RNA-sequencing, and low-pass whole genome sequencing, the quantification of the proteome, transcriptome, and genetic abbreviation of the cancer can be evaluated. With the mouse hydrodynamic tail vein injection (HDVI) models of hepatocellular carcinoma (HCC), different subtypes of HCC derived from different genetic abbreviations can be generated. With the proteome, transcriptome, and genetic abbreviation data of the better-defined HCC from HDVI models and HCC patients, the patient-derived HCC can be classified according to the origin of the genetic abbreviation used in the generation of the HDVI-derived HCC. Furthermore, the proteome of patient-derived plasma will be analyzed, and the signature change unique to HCC classified by different origins of genetic abbreviation will provide an abstract of the proteome, transcriptome, and genetic abbreviation of the HCC tissue. The transcriptomics and proteomics data of HDVI mice produced from five distinct sets of genetic abbreviations have been measured. The proteome and transcriptome of tissue, as well as the proteome of plasma, from a small cohort of HCC patients were studied and classified using this resource to illuminate the fundamental landscape of HCC. The final results will be presented and discussed at the meeting. Citation Format: Hoi Tang MA, Chun Yin YU, Lau Yan NG. The central dogma of hepatocellular carcinoma: Genomic, transcriptomic, and proteomic changes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7102.

Abstract 6524: Single-cell landscape of cancer-associated fibroblasts in immunotherapy resistance of hepatocellular carcinoma

Abstract Introduction: The advent of immune checkpoint blockade (ICB) therapy has revolutionized the treatment approach for hepatocellular carcinoma (HCC). However, the response rate to ICB therapy remains low (below 20%). This limited response rate can be attributed to the considerable heterogeneity observed in HCC cells and the tumor microenvironment (TME). Recent research has highlighted the pivotal role of cancer-associated fibroblasts (CAFs) in orchestrating various components within the TME of HCC. Although the significance of lipid metabolism-associated CAFs in the efficacy of ICB therapy has been demonstrated in HCC murine models [1], the functions and contributions of other CAF subtypes remain largely unknown. Therefore, identifying CAF heterogeneity could advance our comprehension of HCC TME and potentially augment ICB efficacy. Methods: We performed single-cell RNA sequencing on tumor biopsy specimens obtained from patients with advanced HBV-related HCC who had participated in a pembrolizumab (anti-PD1) phase II clinical trial (NCT03419481). Our objective was to examine the dynamic alterations in the HCC TME before and during anti-PD1 treatment (upon 2-cycle). We utilized the Seurat and Cellchat packages for bioinformatics analysis which enabled us to investigate the associations between changes in the proportions of CAF subtypes and the patients' clinical responses, as well as the potential cell-cell interactions involving CAF and other TME components. Results: We identified four CAF subtypes within the TME: cycling, inflammatory, matrix, and vascular CAFs in our anti-PD1 HCC patient cohort. Among the anti-PD1 non-responders, there was a significant increase in the proportions of cycling CAFs (cCAFs) and matrix CAFs (matCAFs) compared to the responders. Notably, matCAFs exhibited a high enrichment of Gene Ontology (GO) Terms related to the extracellular matrix (ECM), whose higher proportion correlated with poor prognosis of patients. Moreover, a distinct collagen pathway signal was found between matCAFs and two immunosuppressive cell types, namely regulatory T cells and M2 macrophages in the non-responders. Discussion and Conclusion: The presence of matCAFs within the HCC tumor may associate with the development of an immunosuppressive TME and unfavorable prognosis for patients. Targeting this specific CAF subtype holds promise as a potential strategy to overcome resistance to ICB therapy. Acknowledgments: The CUHK Strategic Seed Funding for Collaborative Research Scheme and The Li Ka Shing Foundation.

Clinical significance of small nuclear ribonucleoprotein U1 subunit 70 in patients with hepatocellular carcinoma.

Small nuclear ribonucleoprotein U1 subunit 70 (SNRNP70) as one of the components of the U1 small nuclear ribonucleoprotein (snRNP) is rarely reported in cancers. This study aims to estimate the application potential of SNRNP70 in hepatocellular carcinoma (HCC) clinical practice. Based on the TCGA database and cohort of HCC patients, we investigated the expression patterns and prognostic value of SNRNP70 in HCC. Then, the combination of SNRNP70 and alpha-fetoprotein (AFP) in 278 HCC cases was analyzed. Next, western blotting and immunohistochemistry were used to detect the expression of SNRNP70 in nucleus and cytoplasm. Finally, Cell Counting Kit-8 (CCK-8) and scratch wound healing assays were used to detect the effect of SNRNP70 on the proliferation and migration of HCC cells. SNRNP70 was highly expressed in HCC. Its expression was increasingly high during the progression of HCC and was positively related to immune infiltration cells. Higher SNRNP70 expression indicated a poor outcome of HCC patients. In addition, nuclear SNRNP70/AFP combination could be a prognostic biomarker for overall survival and recurrence. Cell experiments confirmed that knockdown of SNRNP70 inhibited the proliferation and migration of HCC cells. SNRNP70 may be a new biomarker for HCC progression and HCC diagnosis as well as prognosis. SNRNP70 combined with serum AFP may indicate the prognosis and recurrence status of HCC patients after operation.

Development and validation of prealbumin-bilirubin score (preALBI score) for predicting long-term survival after hepatectomy for hepatocellular carcinoma: A multicenter analysis versus ALBI score

BackgroundThe Albumin-Bilirubin (ALBI) score, widely used in predicting long-term prognosis for patients with hepatocellular carcinoma (HCC), has limitations due to serum albumin variability. This study aimed to develop and validate the Prealbumin-Bilirubin (preALBI) score as a reliable alternative. MethodsA multicenter cohort of HCC patients who underwent hepatectomy was randomly divided into the training and validation cohorts. The preALBI score was developed using Cox regression models within the training cohort, incorporating serum prealbumin and bilirubin levels as crucial determinants. The survival predictive accuracy was evaluated and compared between the preALBI score with two other staging systems, including the ALBI score and the Child-Pugh grade. ResultsA total of 2409 patients were enrolled. In the training cohort, the preALBI score demonstrated superior performance in predicting long-term survival after hepatectomy. The preALBI score was associated with the best monotonicity of gradients (linear trend χ2: 72.84) and homogeneity (likelihood ratio χ2: 74.69), and the highest discriminatory ability (the areas under curves for 1-, 3-, and 5-year mortality: 0.663, 0.654, and 0.644, respectively). In addition, the preALBI was the most informative staging system in predicting survival (Akaike information criterion: 11325.65).The results remained consistent in both training and validation cohorts, indicating its reliable performance across different populations. ConclusionThe preALBI score, leveraging the stability of prealbumin, represents a promising tool for better patient stratification, providing more accurate prognostic predictions than the ALBI score and the Child-Pugh grade.

SP1-activated USP27X-AS1 promotes hepatocellular carcinoma progression via USP7-mediated AKT stabilisation.

Hepatocellular carcinoma (HCC) continues to pose a significant threat to patient survival. Emerging evidence underscores the pivotal involvement of long non-coding RNAs (lncRNAs) in the cancer process. Nevertheless, our understanding of the roles and processes of lncRNAs in HCC remains limited. The expression level of USP27X-AS1 was assessed in an HCC patient cohort through a combination of bioinformatics analysis and qRT-PCR. Subsequent biological experiments were conducted to delve into the functional aspects of USP27X-AS1. Additional molecular biology techniques, including RNA pulldown and RNA immunoprecipitation (RIP), were employed to elucidate the potential mechanisms involving USP27X-AS1 in HCC. Finally, CUT-RUN assay and other investigations were carried out to determine the factors contributing to the heightened expression of USP27X-AS1 in HCC. High expression of the novel oncogene USP27X-AS1 predicted poor prognosis in HCC patients. Further investigation confirmed that USP27X-AS1 promoted the proliferation and metastasis of HCC by enabling USP7 to interact with AKT, which reduced level of AKT poly-ubiquitylation and enhanced AKT protein stability, which improves protein stabilisation of AKT and promotes the progression of HCC. Moreover, we also revealed that SP1 binds to USP27X-AS1 promoter to activate its transcription. Novel oncogenic lncRNA USP27X-AS1 promoted HCC progression via recruiting USP7 to deubiquitinate AKT. SP1 transcriptionally activated USP27X-AS1 expression. These findings shed light on HCC and pointed to USP27X-AS1 as a potential predictive biomarker and treatment target for the malignancy.

Predicting T Cell-Inflamed Gene Expression Profile in Hepatocellular Carcinoma Based on Dynamic Contrast-Enhanced Ultrasound Radiomics.

The T cell-inflamed gene expression profile (GEP) quantifies 18 genes' expression indicative of a T-cell immune tumor microenvironment, playing a crucial role in the immunotherapy of hepatocellular carcinoma (HCC). Our study aims to develop a radiomics-based machine learning model using contrast-enhanced ultrasound (CEUS) for predicting T cell-inflamed GEP in HCC. The primary cohort of HCC patients with preoperative CEUS and RNA sequencing data of tumor tissues at the single center was used to construct the model. A total of 5936 radiomics features were extracted from the regions of interest in representative images of each phase, and the least absolute shrinkage and selection operator and logistic regression were used to construct four models including three phase-specific models and an integrated model. The area under the curve (AUC) was calculated to evaluate the performance of the model. The independent cohort of HCC patients with preoperative CEUS and Immunoscore based on immunohistochemistry and digital pathology was used to validate the correlation between model prediction value and T-cell infiltration. There were 268 patients enrolled in the primary cohort and 46 patients enrolled in the independent cohort. Compared with the other three models, the AP model constructed by 36 arterial phase (AP) features showed good performance with a mean AUC of 0.905 in the 5-fold cross-validation and was easier to apply in the clinical setting. The decision curve and calibration curve confirmed the clinical utility of the model. In the independent cohort, patients with high Immunoscores showed significantly higher GEP prediction values than those with low Immunoscores (t=-2.359, p=0.029). The CEUS-based model is a reliable predictive tool for T cell-inflamed GEP in HCC, and might facilitate individualized immunotherapy decision-making.

Safety and Effectiveness of Transarterial Chemoembolization in Hepatocellular Carcinoma Patients Aged Greater versus Less Than 80 Years.

Population aging has emerged as a pressing global concern and a significant medical challenge. The use of transarterial chemoembolization (TACE) has been extensively employed for managing unresectable hepatocellular carcinoma (HCC). However, there is limited evidence regarding the safety and effectiveness of TACE specifically in individuals aged 80 years and above. To examine the safety and effectiveness of TACE in elderly patients (≥ 80 years) compared to younger patients (< 80 years) with HCC, and the potential risk factors that may impact the progression-free survival (PFS) for TACE were also identified. A retrospective analysis was conducted on a consecutive cohort of unresectable HCC patients who were initially treated with TACE. The patients were categorized into two groups based on the age at which they underwent TACE, and the efficacy and safety of the treatment were evaluated. The PFS was investigated, and the prognostic factors were analyzed using the Kaplan-Meier method and Cox proportional hazard models. A total of 198 patients were included in this study, with 44 patients aged 80 years or older and 154 patients younger than 80 years. The cumulative risk of PFS after TACE was similar between the two groups (P = 0.800). In the multivariate analysis, a lower ECOG score (P = 0.039) and an earlier BCLC stage (P = 0.004) were identified as independent predictors of better PFS. Patients in both groups tolerated the TACE treatment well. The impact of aging on poor PFS is not significant. In patients with HCC, TACE therapy is both safe and effective for octogenarians, similar to younger patients. Furthermore, the better PFS is associated with a low ECOG score and an early BCLC stage.

Clinical and Prognostic Biomarker Value of Blood-Circulating Inflammatory Cytokines in Hepatocellular Carcinoma

Introduction: Circulating inflammatory cytokines play critical roles in tumor-associated inflammation and immune responses. Recent data have suggested that several interleukins (ILs) mediate carcinogenesis in hepatocellular carcinoma (HCC). However, the predictive and prognostic value of circulating ILs is yet to be validated. Our study aimed to evaluate the association of the serum ILs with overall survival (OS) and clinicopathologic features in a large cohort of HCC patients. Methods: We prospectively collected data and serum samples from 767 HCC patients treated at the University of Texas MD Anderson Cancer Center between 2001 and 2014, with a median follow-up of 67.4 months (95% confidence interval [CI]: 52.5, 83.3). Biomarker association with OS was evaluated by the log-rank method. Results: The median OS in this cohort was 14.2 months (95% CI: 12, 16.1 months). Clinicopathologic features were more advanced, and OS was significantly inferior in patients with high circulating levels of IL1-R1, IL-6, IL-8, IL-10, IL-15, IL-16, and IL-18. Conclusion: Our study shows that several serum IL levels are valid prognostic biomarker candidates and potential targets for therapy in HCC.

Unresectable hepatocellular carcinoma at dawn of immunotherapy era: real-world data from the French prospective CHIEF cohort.

Hepatocellular carcinoma epidemiological data are limited in France. The Epidemio Liver Immunotherapy Tecentriq outcome research (ELITor) retrospective study, based on real-world data from the Carcinome HépatocellulaIrE en France (CHIEF) French cohort of hepatocellular carcinoma patients, aimed to get insight into the treatment patterns, the sociodemographic, clinical, biological, and etiological characteristics, and the quality of life of patients with unresectable hepatocellular carcinoma. Between 1 September 2019 and 4 December 2020, 367 patients from the CHIEF cohort received at least one locoregional (52.8%) chemoembolization or radioembolization or systemic treatment (88.3%) and were selected for ELITor. Most patients had a Barcelona Clinic Liver Cancer (BCLC) C (93.2%) hepatocellular carcinoma stage and were affected by cirrhosis (67.7%). Alcohol was confirmed as the main etiology both as a single etiology (29.1%) and in association with other risk factors (26.9%), mainly metabolic disorders (16.2%).Tyrosine-kinase inhibitors, mainly sorafenib, were the most administered systemic treatments in first line. Patients who received at least one combination of atezolizumab and bevacizumab during the study period ( N = 53) had a better performance status and less portal hypertension frequency than the overall population and more hepatitis B virus infection and fewer metabolic disorders as single etiology. Overall, the global health score before treatment (62.3 ± 21.9) was in line with that of reference cancer patients and worsened in 51.9% of the cases after first-line palliative-intent treatment. This study provided real-life data on advanced hepatocellular carcinoma characteristics and treatment patterns and described the first patients to receive the atezolizumab-bevacizumab combination before it became the new standard of care for advanced hepatocellular carcinoma.

Machine learning-based integration develops a neutrophil-derived signature for improving outcomes in hepatocellular carcinoma.

The heterogeneity of tumor immune microenvironments is a major factor in poor prognosis among hepatocellular carcinoma (HCC) patients. Neutrophils have been identified as playing a critical role in the immune microenvironment of HCC based on recent single-cell studies. However, there is still a need to stratify HCC patients based on neutrophil heterogeneity. Therefore, developing an approach that efficiently describes "neutrophil characteristics" in HCC patients is crucial to guide clinical decision-making. We stratified two cohorts of HCC patients into molecular subtypes associated with neutrophils using bulk-sequencing and single-cell sequencing data. Additionally, we constructed a new risk model by integrating machine learning analysis from 101 prediction models. We compared the biological and molecular features among patient subgroups to assess the model's effectiveness. Furthermore, an essential gene identified in this study was validated through molecular biology experiments. We stratified patients with HCC into subtypes that exhibited significant differences in prognosis, clinical pathological characteristics, inflammation-related pathways, levels of immune infiltration, and expression levels of immune genes. Furthermore, A risk model called the "neutrophil-derived signature" (NDS) was constructed using machine learning, consisting of 10 essential genes. The NDS's RiskScore demonstrated superior accuracy to clinical variables and correlated with higher malignancy degrees. RiskScore was an independent prognostic factor for overall survival and showed predictive value for HCC patient prognosis. Additionally, we observed associations between RiskScore and the efficacy of immune therapy and chemotherapy drugs. Our study highlights the critical role of neutrophils in the tumor microenvironment of HCC. The developed NDS is a powerful tool for assessing the risk and clinical treatment of HCC. Furthermore, we identified and analyzed the feasibility of the critical gene RTN3 in NDS as a molecular marker for HCC.

Serum AKR1B10 as an indicator of unfavorable survival of hepatocellular carcinoma.

A large-scale multicenter study validated aldo-keto reductase 1B10 (AKR1B10) as a new serum marker of hepatocellular carcinoma (HCC). This study aimed to evaluate the prognostic value of serum AKR1B10 in HCC. 273 naïve HCC patients enrolled for serum AKR1B10 tests were followed up for 2years. Survival and clinical data were collected. Kaplan-Meier survival analysis and log-rank tests were used to estimate correlation of patient survival with serum AKR1B10. Univariate and multivariate COX regression analyses were used to evaluate the prognostic value of serum AKR1B10 level independently or in combination with other clinicopathological factors. α-fetoprotein (AFP) was analyzed in parallel for comparison. Serum AKR1B10 associated with tumor stage (p = 0.012), size (p = 0.004), primary tumor number (p = 0.019), and Child-Pugh classification (p = 0.003). HCC patients with a high level of serum AKR1B10 (≥ 267.9pg/ml) had median survival (MS) of 25months (95% confidence interval [CI] 20.788-29.212) vs. MS of 34months (CI 28.911-39.089) in patients with normal serum AKR1B10 (p < 0.001). Univariate and multivariate COX regression analyses showed that serum AKR1B10 level was an unfavorable prognostic marker of HCC independently (HR 1.830, 95% CI 1.312-2.552; p < 0.001) or in combination with other clinical factors (HR 1.883, 95% CI 1.264-2.806; p = 0.002), such as TNM stage, tumor size and portal invasion. In the same cohort of HCC patients, AFP exhibited prognostic value at a cut-off of 400ng/ml, but not at 20ng/ml and 200ng/ml. Serum AKR1B10 is a new prognostic marker of HCC, better than AFP.

MiR-494 induces metabolic changes through G6pc targeting and modulates sorafenib response in hepatocellular carcinoma

BackgroundMetabolic reprogramming is a well-known marker of cancer, and it represents an early event during hepatocellular carcinoma (HCC) development. The recent approval of several molecular targeted agents has revolutionized the management of advanced HCC patients. Nevertheless, the lack of circulating biomarkers still affects patient stratification to tailored treatments. In this context, there is an urgent need for biomarkers to aid treatment choice and for novel and more effective therapeutic combinations to avoid the development of drug-resistant phenotypes. This study aims to prove the involvement of miR-494 in metabolic reprogramming of HCC, to identify novel miRNA-based therapeutic combinations and to evaluate miR-494 potential as a circulating biomarker.MethodsBioinformatics analysis identified miR-494 metabolic targets. QPCR analysis of glucose 6-phosphatase catalytic subunit (G6pc) was performed in HCC patients and preclinical models. Functional analysis and metabolic assays assessed G6pc targeting and miR-494 involvement in metabolic changes, mitochondrial dysfunction, and ROS production in HCC cells. Live-imaging analysis evaluated the effects of miR-494/G6pc axis in cell growth of HCC cells under stressful conditions. Circulating miR-494 levels were assayed in sorafenib-treated HCC patients and DEN-HCC rats.ResultsMiR-494 induced the metabolic shift of HCC cells toward a glycolytic phenotype through G6pc targeting and HIF-1A pathway activation. MiR-494/G6pc axis played an active role in metabolic plasticity of cancer cells, leading to glycogen and lipid droplets accumulation that favored cell survival under harsh environmental conditions. High miR-494 serum levels associated with sorafenib resistance in preclinical models and in a preliminary cohort of HCC patients. An enhanced anticancer effect was observed for treatment combinations between antagomiR-494 and sorafenib or 2-deoxy-glucose in HCC cells.ConclusionsMiR-494/G6pc axis is critical for the metabolic rewiring of cancer cells and associates with poor prognosis. MiR-494 deserves attention as a candidate biomarker of likelihood of response to sorafenib to be tested in future validation studies. MiR-494 represents a promising therapeutic target for combination strategies with sorafenib or metabolic interference molecules for the treatment of HCC patients who are ineligible for immunotherapy.

Atezolizumab and bevacizumab in advanced hepatocellular carcinoma: Real-world data.

e16167 Background: Treatment of advanced unresectable hepatocellular carcinoma (HCC) has advanced substantially in the past few years with the use of immunotherapy. The IMbrave 150 phase III study assessed the combined treatment of atezolizumab plus bevacizumab (atezobev) and has demonstrated better overall and progression-free survival compared with sorafenib. We aimed to assess the efficacy and toxicity of atezobev in real-world data. Methods: We reviewed the medical records of patients with a diagnosis of advanced HCC treated at the Sheba Medical Center between January 2020 and February 2023. Eligible patients were those treated with atezobev as first line systemic therapy. Adverse events were recorded according to the Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Response assessment was performed according to the Response Evaluation Criteria In Solid Tumors (RECIST) v1.1. Results: We identified 37 patients that were treated with atezobev, mean age of the study population was 70 (IQR 60-72), 19% were females (n = 7), median ECOG performance status was 1 (IQR 0-1.5) and HCC etiology was non-viral in 35% (n = 13) and viral (HBV/HCV) in 65% of patients (n = 24). Overall response rate (ORR) was 29.7% (n = 11), stable disease was noted in 27.0% (n = 10) and progressive disease in 43.2% (n = 16) of patients. In comparison, the ORR reported in the IMbrave 150 study was 27%. There was no difference in response rate according to previous local treatment or HCC etiology. Grade 3/4 adverse events included grade 3 hepatitis (10.8%, n = 4), grade 3 diarrhea (2.7%, n = 1), and grade 4 infusion-related reaction (2.7%, n = 1). In comparison, the IMbrave 150 study reported grade 3/4 hepatitis, diarrhea, and infusion-related reaction in 7.0%, 1.8% and 2.4% of patients, respectively. Conclusions: In this cohort of advanced HCC patients treated in a large tertiary medical center, the efficacy and toxicity profile of atezobev was similar to that reported in the IMbrave 150 phase III study.

Diagnostic and prognostic biomarker value of blood circulating inflammatory cytokines in hepatocellular carcinoma.

e16115 Background: Circulating inflammatory cytokines play critical roles in tumor-associated inflammation and immune responses. Recent data has suggested that several interleukins (ILs) mediate carcinogenesis in hepatocellular carcinoma (HCC). However, the predictive and prognostic value of circulating ILs has yet to be validated. Our study aimed to evaluate the association of the serum ILs with overall survival (OS) and clinicopathologic features in a large cohort of HCC patients. Methods: We prospectively collected data, and serum samples from 767 HCC patients treated at The University of Texas MD Anderson Cancer Center between 2001 and 2014, with a median follow-up of 67.4 months (95% CI: 52.5, 83.3). Biomarker association with overall survival (OS) was evaluated by the Log-rank method. Results: The median OS in this cohort was 14.2 months (95% confidence interval [CI]: 12, 16.1 months). Clinicopathologic features were more advanced, and OS was significantly inferior in patients with high circulating levels of IL1-R1, IL-6, IL-8, IL-10, IL-15, IL-16, and IL-18. Conclusions: In conclusion, our study shows that several serum IL levels are valid prognostic biomarker candidates and potential targets for therapy in HCC.

A transcriptomic intratumour heterogeneity-free signature overcomes sampling bias in prognostic risk classification for hepatocellular carcinoma

Background & AimsIntratumour heterogeneity (ITH) fosters the vulnerability of RNA expression-based biomarkers derived from a single biopsy to tumour sampling bias, and is regarded as an unaddressed confounding factor for patient precision stratification using molecular biomarkers. This study aimed to identify an ITH-free predictive biomarker in hepatocellular carcinoma (HCC). MethodsWe interrogated the confounding effect of ITH on performance of molecular biomarkers and quantified transcriptomic heterogeneity utilising three multiregional HCC transcriptome datasets involving 142 tumoural regions from 30 patients. A de novo strategy based on the heterogeneity metrics was devised to develop a surveillant biomarker (a utility gadget using RNA; AUGUR) using three datasets involving 715 liver samples from 509 patients with HCC. The performance of AUGUR was assessed in seven cross-platform HCC cohorts that encompassed 1,206 patients. ResultsAn average discordance rate of 39.9% at the level of individual patients was observed applying 13 published prognostic signatures to classify tumour regions. We partitioned genes into four heterogeneity quadrants, from which we developed and validated a reproducible robust ITH-free expression signature AUGUR that showed significant positive associations with adverse features of HCC. High AUGUR risk increased the risk of disease progression and mortality independent of established clinicopathological indices, which maintained concordance across seven cohorts. Moreover, AUGUR compared favourably to the discriminative ability, prognostic accuracy, and patient risk concordant rates of 13 published signatures. Finally, a well-calibrated predictive nomogram integrating AUGUR and tumour-node-metastasis (TNM) stage was established, which generated a numerical probability of mortality. ConclusionsWe constructed and validated an ITH-free AUGUR and nomogram that overcame sampling bias and provided reliable prognostic information for patients with HCC. Impact and ImplicationsIntratumour heterogeneity (ITH) is prevalent in hepatocellular carcinoma (HCC), and is regarded as an unaddressed confounding factor for biomarker design and application. We examined the confounding effect of transcriptomic ITH in patient risk classification, and found existing molecular biomarkers of HCC were vulnerable to tumour sampling bias. We then developed an ITH-free expression biomarker (a utility gadget using RNA; AUGUR) that overcame clinical sampling bias and maintained prognostic reproducibility and generalisability across multiple HCC patient cohorts from different commercial platforms. Furthermore, we established and validated a well-calibrated nomogram based on AUGUR and tumour-node-metastasis (TNM) stage that provided an individualised prognostic information for patients with HCC.

Targeting WDxR motif reprograms immune microenvironment and inhibits hepatocellular carcinoma progression.

The WD-repeat (WDR) family affects carcinogenesis, but its role in the immune microenvironment is poorly characterized. Although functional loss or gain of WDR6 does not markedly change in vitro proliferative and invasive capacity of HCC cells, its deficiency in hepa1-6 cells drastically inhibits the growth and lung metastasis of orthotopically implanted tumors in immune-competent C57BL/6J mice. Mechanistically, WDR6 targets tumor suppressor UVRAG to the CUL4A-DDB1-ROC1 E3 ubiquitin ligase complex through a unique WDxR motif and promotes its degradation. This upregulates chromatin accessibility at the TNFα locus by blocking autophagic degradation of p65, elevates intratumoral myeloid-derived suppressor cell (MDSC) number, and reduces CD8+ T cell infiltration, thereby promoting HCC progression. These immunosuppressive effects are reversed by TNFα blockade. TNFα recruits NF-κB to activate the transcription of WDR6, establishing a WDR6-TNFα loop. Clinically, the WDR6/UVRAG/NF-κB pathway is hyperactivated in HCC, predicting a poor prognosis. Importantly, a WDxR-like peptide disrupts the WDR6/UVRAG complex and enhances the efficiency of anti-PD-L1 against HCC with WDR6 dysregulation.

Characterization of heterogeneous metabolism in hepatocellular carcinoma identifies new therapeutic target and treatment strategy.

Metabolic reprogramming is a well-known hallmark of cancer. Systematical identification of clinically relevant metabolic subtypes of Hepatocellular carcinoma (HCC) is critical to understand tumor heterogeneity and develop efficient treatment strategies. We performed an integrative analysis of genomic, transcriptomic, and clinical data from an HCC patient cohort in The Cancer Genome Atlas (TCGA). Four metabolic subtypes were defined: mHCC1, mHHC2, mHCC3, and mHCC4. These subtypes had distinct differences in mutations profiles, activities of metabolic pathways, prognostic metabolism genes, and immune features. The mHCC1 was associated with poorest outcome and was characterized by extensive metabolic alterations, abundant immune infiltration, and increased expression of immunosuppressive checkpoints. The mHHC2 displayed lowest metabolic alteration level and was associated with most significant improvement in overall survival in response to high CD8+ T cell infiltration. The mHHC3 was a "cold-tumor" with low immune infiltration and few metabolic alterations. The mHCC4 presented a medium degree of metabolic alteration and high CTNNB1 mutation rate. Based on our HCC classification and in vitro study, we identified palmitoyl-protein thioesterase 1 (PPT1) was a specific prognostic gene and therapeutic target for mHCC1. Our study highlighted mechanistic differences among metabolic subtypes and identified potential therapeutic targets for subtype-specific treatment strategies targeting unique metabolic vulnerabilities. The immune heterogeneities across metabolic subtypes may help further clarify the association between metabolism and immune environment and guide the development of novel strategies through targeting both unique metabolic vulnerabilities and immunosuppressive triggers.

Nomogram for tumour response based on prospective cohorts of hepatocellular carcinoma patients receiving immunotherapy combined with targeted therapy: development and validation.

Although immunotherapy combined with targeted therapy can be effective for hepatocellular carcinoma (HCC), not all HCC patients respond to this treatment. Models for predicting tumour response in HCC patients receiving immunotherapy combined with targeted therapy are lacking. A total of 221 HCC patients from two independent prospective cohorts were retrospectively reviewed. The patients were randomly divided into training and validation cohorts at a ratio of 7:3. Standard clinical data were collected from each patient, including age, sex, hepatitis B infection status, laboratory tests, and immune target-related adverse events (itrAEs). Tumour responses were evaluated using the Response Evaluation Criteria in Solid Tumours (RECIST) v1.1 guidelines. ItrAEs were assessed based on the Common Terminology Criteria for Adverse Events version 4.0. The nomogram for tumour response prediction was constructed based on the results of the multivariate logistic regression analysis, areas under the receiver operating characteristic curves (AUROCs) were used to determine the sensitivity and specificity of the model, and calibration plots and Hosmer-Lemeshow chi-square tests were performed to assess the calibration of the model. In the multivariate logistic regression analysis, a solitary tumour (P=0.006), neutropenia (P=0.003) and hypertension (P=0.042) independently predicted objective response (OR). A nomogram for OR was established with AUROCs of 0.734, 0.675, 0.730, and 0.707 in the training, validation, first-line and second-line treatment sets, respectively. Tumour sizes less than 5 cm (P=0.005), a solitary tumour (P=0.037), prognostic nutritional indices greater than or equal to 54.3 (P=0.037), neutropenia (P=0.004) and fatigue (P=0.041) independently predicted disease control (DC). A nomogram for DC was established with AUROCs of 0.804, 0.667, and 0.768 in the training, first-line and second-line treatment sets, respectively. All the Hosmer-Lemeshow tests and calibration curves showed acceptable calibration. The current provides clinicians with new insights into selecting patients for immunotherapy combined with targeted therapy and contributes to the development of immunotherapy for HCC. It is necessary to expand the scale of our research and perform prospective studies to verify our findings.

A transcriptomic intratumour heterogeneity-free signature overcomes sampling bias in prognostic risk classification for hepatocellular carcinoma

Background & AimsIntratumour heterogeneity (ITH) fosters the vulnerability of RNA expression-based biomarkers derived from a single biopsy to tumour sampling bias, and is regarded as an unaddressed confounding factor for patient precision stratification using molecular biomarkers. This study aimed to identify an ITH-free predictive biomarker in hepatocellular carcinoma (HCC). MethodsWe interrogated the confounding effect of ITH on performance of molecular biomarkers and quantified transcriptomic heterogeneity utilising three multiregional HCC transcriptome datasets involving 142 tumoural regions from 30 patients. A de novo strategy based on the heterogeneity metrics was devised to develop a surveillant biomarker (a utility gadget using RNA; AUGUR) using three datasets involving 715 liver samples from 509 patients with HCC. The performance of AUGUR was assessed in seven cross-platform HCC cohorts that encompassed 1,206 patients. ResultsAn average discordance rate of 39.9% at the level of individual patients was observed applying 13 published prognostic signatures to classify tumour regions. We partitioned genes into four heterogeneity quadrants, from which we developed and validated a reproducible robust ITH-free expression signature AUGUR that showed significant positive associations with adverse features of HCC. High AUGUR risk increased the risk of disease progression and mortality independent of established clinicopathological indices, which maintained concordance across seven cohorts. Moreover, AUGUR compared favourably to the discriminative ability, prognostic accuracy, and patient risk concordant rates of 13 published signatures. Finally, a well-calibrated predictive nomogram integrating AUGUR and tumour-node-metastasis (TNM) stage was established, which generated a numerical probability of mortality. ConclusionsWe constructed and validated an ITH-free AUGUR and nomogram that overcame sampling bias and provided reliable prognostic information for patients with HCC. Impact and ImplicationsIntratumour heterogeneity (ITH) is prevalent in hepatocellular carcinoma (HCC), and is regarded as an unaddressed confounding factor for biomarker design and application. We examined the confounding effect of transcriptomic ITH in patient risk classification, and found existing molecular biomarkers of HCC were vulnerable to tumour sampling bias. We then developed an ITH-free expression biomarker (a utility gadget using RNA; AUGUR) that overcame clinical sampling bias and maintained prognostic reproducibility and generalisability across multiple HCC patient cohorts from different commercial platforms. Furthermore, we established and validated a well-calibrated nomogram based on AUGUR and tumour-node-metastasis (TNM) stage that provided an individualised prognostic information for patients with HCC.