Phase II Trial of the Combination of Temsirolimus and Sorafenib in Advanced Hepatocellular Carcinoma with Tumor Mutation Profiling

Radiographic and serologic response in patients with unresectable hepatocellular carcinoma receiving systemic antineoplastic treatments: A trial-level analysis

BACKGROUND

In a disease like unresectable hepatocellular carcinoma, overall survival is an inadequate outcome measure for evaluating the effectiveness of treatments given the high risk of death from liver failure. There is an unmet need for reliable alternative end points for clinical trials and daily clinical practice. To evaluate treatment response in patients with unresectable or metastatic hepatocellular carcinoma (mHCC), imaging-related end points are often used, whereas serologic end points have been developed for patients with serum alpha-fetoprotein levels >20 ng/mL. The objective of this study was to evaluate clinical trials that report concomitant assessment of radiographic and serologic response in patients with mHCC.

METHODS

After a systematic review, studies that evaluated response according to radiographic and serologic criteria were selected. A correlation between progression-free survival (PFS) and overall survival (OS) was performed, and a linear regression of each response-related outcome measure with OS was reported. Finally, the effect of eight baseline variables on OS and response-related measures was evaluated.

RESULTS

Twenty-six studies were included, including 16 first-line studies and 10 second-line studies. PFS and response rates demonstrated a significant relationship with OS, whereas disease control rates did not. The responses were correlated with OS, particularly in the first-line setting, after targeted therapy, and whenever assessment was early. Among the baseline variables, only performance status had a prognostic role, whereas hepatitis B virus-related liver disease was associated with higher radiographic response rates.

CONCLUSIONS

PFS and radiographic and serologic response rates appear to be reliable intermediate end points in patients with mHCC who are undergoing systemic antineoplastic therapy. However, the serologic response is available earlier.

Understanding Gene Involvement in Hepatocellular Carcinoma: Implications for Gene Therapy and Personalized Medicine

Hepatocellular carcinoma (HCC) is the dominant type of liver cancers and is one of the deadliest health threats globally. The conventional therapeutic options for HCC are hampered by low efficiency and intolerable side effects. Gene therapy, however, now offers hope for the treatment of many disorders previously considered incurable, and gene therapy is beginning to address many of the shortcomings of conventional therapies. Herein, we summarize the involvement of genes in the pathogenesis and prognosis of HCC, with a special focus on dysregulated signaling pathways, genes involved in immune evasion, and non-coding RNAs as novel two-edged players, which collectively offer potential targets for the gene therapy of HCC. Herein, the opportunities and challenges of HCC gene therapy are discussed. These include innovative therapies such as genome editing and cell therapies. Moreover, advanced gene delivery technologies that recruit nanomedicines for use in gene therapy for HCC are highlighted. Finally, suggestions are offered for improved clinical translation and future directions in this area of endeavor.

Transferrin receptor 1 promotes hepatocellular carcinoma progression and metastasis by activating the mTOR signaling pathway

BACKGROUND

Aberrant iron metabolism is commonly observed in multiple tumor types, including hepatocellular carcinoma (HCC). However, as the key regulator of iron metabolism involved in iron absorption, the role of transferrin receptor (TFRC) in HCC remains elusive.

METHODS

The mRNA and protein expression of TFRC were evaluated in paired HCC and adjacent non-tumor specimens. The correlation between TFRC level and clinicopathological features or prognostic significance was also analyzed. The role of TFRC on biological functions was finally studied in vitro and in vivo.

RESULTS

The TFRC level was remarkably upregulated in HCC tissues compared to paired peritumor tissues. Overexpressed TFRC positively correlated with serum alpha-fetoprotein, carcinoembryonic antigen, and poor tumor differentiation. Multivariate analysis demonstrated that upregulated TFRC was an independent predictive marker for poorer overall survival and disease-free survival in HCC patients. Loss of TFRC markedly impaired cell proliferation and migration in vitro and notably suppressed HCC growth and metastasis in vivo, while overexpression of TFRC performed an opposite effect. Mechanistically, the mTOR signaling pathway was downregulated with TFRC knockdown, and the mTOR agonist MHY1485 completely reversed the biological inhibition in HCC cells caused by TFRC knockdown. Furthermore, exogenous ferric citrate (FAC) or iron chelator reversed the changed biological functions and signaling pathway expression of HCC cells caused by TFRC knockdown or overexpression, respectively.

CONCLUSIONS

Our study indicates that TFRC exerts an oncogenic role in HCC and may become a promising therapeutic target to restrain HCC progression.

Targeting LRRC41 as a potential therapeutic approach for hepatocellular carcinoma

Introduction: Hepatocellular carcinoma (HCC) is the most common primary liver cancer, characterized by high mortality rate. In clinical practice, several makers of liver cancer, such as VEGFR1, FGFR1 and PDGFRα, were identified and their potentials as a therapeutic target were explored. However, the unsatisfied treatment results emphasized the needs of new therapeutic targets. Methods: 112 HCC patients samples were obtained to evaluate the expression of LRRC41, SOX9, CD44, and EPCAM in HCC, combined with prognosis analysis. A DEN-induced HCC rat model was constructed to verify the expression of LRRC41 and SOX9 in HCC and lung metastasis tissues. Immune score evaluation was analysized by bioinformatics methods. Network pharmacology was performed to explored the potential FDA-approved drugs targeting LRRC41. Results: Through analysis of the Timer database and tissue micro-array, we confirmed that LRRC41 was over-expressed in HCC and exhibited a significant positive correlation with recurrence and metastasis. Immunohistochemistry staining of human HCC tissue samples revealed significant upregulation of LRRC41, SOX9, CD44, and EPCAM, with LRRC41 showing a positive correlation with SOX9, CD44, and EPCAM expression. UALCAN database analysis indicated that LRRC41 and SOX9 contribute to poor prognosis whereas CD44 and EPCAM did not demonstrate the same significance. Furthermore, analysis of a DEN-induced HCC rat model confirmed the significantly elevated expression of LRRC41 and SOX9 in HCC and lung metastasis tissues. Drug sensitivity analysis and molecular docking targeting LRRC41 identified several FDA-approved drugs, which may have potential antitumor effects on HCC by targeting LRRC41. Conclusion: Our findings highlight the role of LRRC41 overexpression in promoting HCC progression and its association with a poor prognosis. Drug sensitivity analysis and molecular docking shows several FDA-approved drugs may be potential therapeutic targets for HCC. Targeting LRRC41 may hold promise as a potential therapeutic strategy for HCC.

Targeting EGFR/PI3K/AKT/mTOR Signaling in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) poses a significant global health concern, with its incidence steadily increasing. The development of HCC is a multifaceted, multi-step process involving alterations in various signaling cascades. In recent years, significant progress has been made in understanding the molecular signaling pathways that play central roles in hepatocarcinogenesis. In particular, the EGFR/PI3K/AKT/mTOR signaling pathway in HCC has garnered renewed attention from both basic and clinical researchers. Preclinical studies in vitro and in vivo have shown the effectiveness of targeting the key components of this signaling pathway in human HCC cells. Thus, targeting these signaling pathways with small molecule inhibitors holds promise as a potential therapeutic option for patients with HCC. In this review, we explore recent advancements in understanding the role of the EGFR/PI3K/AKT/mTOR signaling pathway in HCC and assess the effectiveness of targeting this signaling cascade as a potential strategy for HCC therapy based on preclinical studies.

Metabolic adverse events of multitarget kinase inhibitors: a systematic review

PURPOSE

Multitargeted kinase inhibitors (MKIs) are used for the treatment of several cancers. By targeting multiple signaling pathways, MKIs have become cornerstones of the oncologic treatment. Although their use leads to important results in terms of survival, treatment with MKIs can determine important side effects the clinician must be aware of. Among those, arterial hypertension, mucositis and skin lesions are universally reported, while data about metabolic alterations are scarce. In our review, we focused on glucose and lipid alterations in MKI-treated patients.

METHODS

We searched for articles, published between January 2012 and December 2022, evaluating the effects on lipid and glucose metabolism of four MKIs (Cabozantinib, Lenvatinib, Sorafenib, and Vandetanib) in adult patients with cancer. We focused on drugs approved for thyroid malignancies, since a worse metabolic control may potentially impact life expectancy, due to their better overall survival rate.

RESULTS

As for glucose metabolism, the majority of the studies reported elevation of glucose levels (prevalence: 1-17%) with different grades of severity, including death. As for cholesterol, 12 studies reported worsening or new-onset hypercholesterolemia (prevalence: 4-40%). Finally, 19 studies reported different grades of hypertriglyceridemia (prevalence: 1-86%), sometimes leading to life-threatening events.

CONCLUSIONS

Despite some inherent limitations, our analysis may cast light upon some of the MKIs metabolic disorders that can impact on patients' health, especially when long-term survival is expected. Future clinical trials should consider routine assessment of glucose and lipid levels, because underdetection and underreporting of alterations can lead to the overlooking of important adverse events.

Targeting the PI3K/AKT/mTOR and RAF/MEK/ERK pathways for cancer therapy

The PI3K/AKT/mTOR and RAF/MEK/ERK pathways are commonly activated by mutations and chromosomal translocation in vital targets. The PI3K/AKT/mTOR signaling pathway is dysregulated in nearly all kinds of neoplasms, with the component in this pathway alternations. RAF/MEK/ERK signaling cascades are used to conduct signaling from the cell surface to the nucleus to mediate gene expression, cell cycle processes and apoptosis. RAS, B-Raf, PI3K, and PTEN are frequent upstream alternative sites. These mutations resulted in activated cell growth and downregulated cell apoptosis. The two pathways interact with each other to participate in tumorigenesis. PTEN alterations suppress RAF/MEK/ERK pathway activity via AKT phosphorylation and RAS inhibition. Several inhibitors targeting major components of these two pathways have been supported by the FDA. Dozens of agents in these two pathways have attracted great attention and have been assessed in clinical trials. The combination of small molecular inhibitors with traditional regimens has also been explored. Furthermore, dual inhibitors provide new insight into antitumor activity. This review will further comprehensively describe the genetic alterations in normal patients and tumor patients and discuss the role of targeted inhibitors in malignant neoplasm therapy. We hope this review will promote a comprehensive understanding of the role of the PI3K/AKT/mTOR and RAF/MEK/ERK signaling pathways in facilitating tumors and will help direct drug selection for tumor therapy.

Evolving therapeutic landscape of advanced hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common solid malignancies worldwide. A large proportion of patients with HCC are diagnosed at advanced stages and are only amenable to systemic therapies. We have witnessed the evolution of systemic therapies from single-agent targeted therapy (sorafenib and lenvatinib) to the combination of a checkpoint inhibitor plus targeted therapy (atezolizumab plus bevacizumab therapy). Despite remarkable advances, only a small subset of patients can obtain durable clinical benefit, and therefore substantial therapeutic challenges remain. In the past few years, emerging systemic therapies, including new molecular-targeted monotherapies (for example, donafenib), new immuno-oncology monotherapies (for example, durvalumab) and new combination therapies (for example, durvalumab plus tremelimumab), have shown encouraging results in clinical trials. In addition, many novel therapeutic approaches with the potential to offer improved treatment effects in patients with advanced HCC, such as sequential combination targeted therapy and next-generation adoptive cell therapy, have also been proposed and developed. In this Review, we summarize the latest clinical advances in the treatment of advanced HCC and discuss future perspectives that might inform the development of more effective therapeutics for advanced HCC.

Targeting non-structural proteins of Hepatitis C virus for predicting repurposed drugs using QSAR and machine learning approaches

Hepatitis C virus (HCV) infection causes viral hepatitis leading to hepatocellular carcinoma. Despite the clinical use of direct-acting antivirals (DAAs) still there is treatment failure in 5–10% cases. Therefore, it is crucial to develop new antivirals against HCV. In this endeavor, we developed the “Anti-HCV” platform using machine learning and quantitative structure–activity relationship (QSAR) approaches to predict repurposed drugs targeting HCV non-structural (NS) proteins. We retrieved experimentally validated small molecules from the ChEMBL database with bioactivity (IC₅₀/EC₅₀) against HCV NS3 (454), NS3/4A (495), NS5A (494) and NS5B (1671) proteins. These unique compounds were divided into training/testing and independent validation datasets. Relevant molecular descriptors and fingerprints were selected using a recursive feature elimination algorithm. Different machine learning techniques viz. support vector machine, k-nearest neighbour, artificial neural network, and random forest were used to develop the predictive models. We achieved Pearson’s correlation coefficients from 0.80 to 0.92 during 10-fold cross validation and similar performance on independent datasets using the best developed models. The robustness and reliability of developed predictive models were also supported by applicability domain, chemical diversity and decoy datasets analyses. The “Anti-HCV” predictive models were used to identify potential repurposing drugs. Representative candidates were further validated by molecular docking which displayed high binding affinities. Hence, this study identified promising repurposed drugs viz. naftifine, butalbital (NS3), vinorelbine, epicriptine (NS3/4A), pipecuronium, trimethaphan (NS5A), olodaterol and vemurafenib (NS5B) etc. targeting HCV NS proteins. These potential repurposed drugs may prove useful in antiviral drug development against HCV.

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

INTRODUCTION

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

AREA COVERED

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

EXPERT OPINION

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

Evaluation of Therapeutic Effects of Computed Tomography Imaging Classification Algorithm-Based Transcatheter Arterial Chemoembolization on Primary Hepatocellular Carcinoma

To investigate the evaluation of therapeutic effects of computerized tomography (CT) imaging machine learning classification algorithm-based transcatheter arterial chemoembolization (TACE) on primary hepatocellular carcinoma (PHC), machine learning algorithm was optimized to propose the feature extraction of soft margin, analyze CT images, and acquire relevant texture features to assess if it can predict the multistage features of PHC for the application of the therapeutic effects of TACE on PHC. Besides, PHC patients receiving surgical excision were retrospectively collected, and then 483 patients with hepatocellular carcinoma (HCC) were determined from cases. After that, a total of 162 cases meeting the standards were selected. Besides, the features of images were classified and analyzed by machine learning algorithm, and volume of interest (VOI) images of patients in each group were acquired by image segmentation layer by layer. In addition, the texture features of images were extracted. The results showed that 5 CT image-based texture features, including 2 histogram features and 3 matrix-based features, all described the specificity and heterogeneity of tumors. The analysis of the diagnostic effectiveness of the evaluation of response group by each texture parameter demonstrated that its sensitivity, specificity, and area under curve (AUC) were 83.63%, 90.91%, and 0.08%, respectively. Based on CT prediction, machine learning algorithm was fused to realize excellent classification effects on multistage and multiphase features and offer imaging support to the clinical selection of reasonable therapeutic plans. In addition, multiphase and multifeature-based medical tumor classification method was put forward.