Precision Medicine for Hepatocellular Carcinoma: Clinical Perspective

Leveraging radiomics and AI for precision diagnosis and prognostication of liver malignancies

Liver tumors, whether primary or metastatic, have emerged as a growing concern with substantial global health implications. Timely identification and characterization of liver tumors are pivotal factors in order to provide optimum treatment. Imaging is a crucial part of the detection of liver tumors; however, conventional imaging has shortcomings in the proper characterization of these tumors which leads to the need for tissue biopsy. Artificial intelligence (AI) and radiomics have recently emerged as investigational opportunities with the potential to enhance the detection and characterization of liver lesions. These advancements offer opportunities for better diagnostic accuracy, prognostication, and thereby improving patient care. In particular, these techniques have the potential to predict the histopathology, genotype, and immunophenotype of tumors based on imaging data, hence providing guidance for personalized treatment of such tumors. In this review, we outline the progression and potential of AI in the field of liver oncology imaging, specifically emphasizing manual radiomic techniques and deep learning-based representations. We discuss how these tools can aid in clinical decision-making challenges. These challenges encompass a broad range of tasks, from prognosticating patient outcomes, differentiating benign treatment-related factors and actual disease progression, recognizing uncommon response patterns, and even predicting the genetic and molecular characteristics of the tumors. Lastly, we discuss the pitfalls, technical limitations and future direction of these AI-based techniques.

New Insights on Liver-Directed Therapies in Hepatocellular Carcinoma

The incidence of hepatocellular carcinoma (HCC) has been increasing over the past decades, but improvements in systemic and locoregional therapies is increasing survival. Current locoregional treatment options include ablation, transarterial chemoembolization (TACE), transarterial radioembolization (TARE), and stereotactic body radiotherapy (SBRT). There is ongoing research regarding the combination of systemic and local therapies to maximize treatment effect as well as in new non-invasive, image-guided techniques such as histotripsy. There is also active research in optimizing the delivery of therapy to tumors via nanostructures and viral-vector-mediated gene therapies. In many cases, patients require a combination of therapies to achieve tumor control and prolong survival. This article provides an overview of the most common liver-directed therapies for HCC as well as insight into more recent advances in personalized medicine and emerging techniques.

Diagnostic role and immune correlates of programmed cell death-related genes in hepatocellular carcinoma

Programmed cell death (PCD) is thought to have multiple roles in tumors. Here, the roles of PCD-related genes were comprehensively analyzed to evaluate their values in hepatocellular carcinoma (HCC) diagnosis and prognosis. Gene expression and single-cell data of HCC patients, and PCD-related genes were collected from public databases. The diagnostic and prognostic roles of differentially expressed PCD-related genes in HCC were explored by univariate and multivariate Cox regression analyses. Single-cell data were further analyzed for the immune cells and expression of feature genes. Finally, we evaluated the expression of genes by quantitative real-time polymerase chain reaction and Western blot, and the proportion of immune cells was detected by flow cytometry in HCC samples. We obtained 52 differentially expressed PCD-related genes in HCC, based on which the consensus clustering analysis cluster 2 was found to have a worse prognosis than cluster 1. Then 10 feature genes were identified using LASSO analysis, and programmed cell death index (PCDI) was calculated to divided HCC patients into high-PCDI and low-PCDI groups. Worse prognosis was observed in high-PCDI group. Cox regression analysis showed that PCDI is an independent prognostic risk factor for HCC patients. Additionally, SERPINE1 and G6PD of feature genes significantly affect patient survival. Macrophages and Tregs were significantly positively correlated with PCDI. G6PD mainly expressed in macrophages, SERPINE1 mainly expressed in fibroblast. The experimental results confirmed the high expression of SERPINE1 and G6PD in HCC compared with the control, and the infiltration level of macrophages and Treg in HCC was also obviously elevated. PCDI may be a new predictor for the diagnosis of patients with HCC. The association of SERPINE1 and G6PD with the immune environment will provide new clues for HCC therapy.

Mutational Landscape and Precision Medicine in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fourth most common malignancy worldwide and exhibits a universal burden as the incidence of the disease continues to rise. In addition to curative-intent therapies such as liver resection and transplantation, locoregional and systemic therapy options also exist. However, existing treatments carry a dismal prognosis, often plagued with high recurrence and mortality. For this reason, understanding the tumor microenvironment and mutational pathophysiology has become the center of investigation for disease control. The use of precision medicine and genetic analysis can supplement current treatment modalities to promote individualized management of HCC. In the search for personalized medicine, tools such as next-generation sequencing have been used to identify unique tumor mutations and improve targeted therapies. Furthermore, investigations are underway for specific HCC biomarkers to augment the diagnosis of malignancy, the prediction of whether the tumor environment is amenable to available therapies, the surveillance of treatment response, the monitoring for disease recurrence, and even the identification of novel therapeutic opportunities. Understanding the mutational landscape and biomarkers of the disease is imperative for tailored management of the malignancy. In this review, we summarize the molecular targets of HCC and discuss the current role of precision medicine in the treatment of HCC.

Cell-Free DNA as a Surveillance Tool for Hepatocellular Carcinoma Patients after Liver Transplant

The liver is the world's sixth most common primary tumor site, responsible for approximately 5% of all cancers and over 8% of cancer-related deaths. Hepatocellular carcinoma (HCC) is the predominant type of liver cancer, accounting for approximately 75% of all primary liver tumors. A major therapeutic tool for this disease is liver transplantation. Two of the most significant issues in treating HCC are tumor recurrence and graft rejection. Currently, the detection and monitoring of HCC recurrence and graft rejection mainly consist of imaging methods, tissue biopsies, and alpha-fetoprotein (AFP) follow-up. However, they have limited accuracy and precision. One of the many possible components of cfDNA is circulating tumor DNA (ctDNA), which is cfDNA derived from tumor cells. Another important component in transplantation is donor-derived cfDNA (dd-cfDNA), derived from donor tissue. All the components of cfDNA can be analyzed in blood samples as liquid biopsies. These can play a role in determining prognosis, tumor recurrence, and graft rejection, assisting in an overall manner in clinical decision-making in the treatment of HCC.

Understanding the Drawbacks of the Current Tumor Staging Systems: How to Improve?

Tumor stage definition is required for the description of the diagnosis and the development and use of treatment guidelines, as well as to enable clinical research (including clinical trials) and cancer surveillance [...].

Metabolomics in hepatocellular carcinoma: From biomarker discovery to precision medicine

Hepatocellular carcinoma (HCC) remains a global health burden, and is mostly diagnosed at late and advanced stages. Currently, limited and insensitive diagnostic modalities continue to be the bottleneck of effective and tailored therapy for HCC patients. Moreover, the complex reprogramming of metabolic patterns during HCC initiation and progression has been obstructing the precision medicine in clinical practice. As a noninvasive and global screening approach, metabolomics serves as a powerful tool to dynamically monitor metabolic patterns and identify promising metabolite biomarkers, therefore holds a great potential for the development of tailored therapy for HCC patients. In this review, we summarize the recent advances in HCC metabolomics studies, including metabolic alterations associated with HCC progression, as well as novel metabolite biomarkers for HCC diagnosis, monitor, and prognostic evaluation. Moreover, we highlight the application of multi-omics strategies containing metabolomics in biomarker discovery for HCC. Notably, we also discuss the opportunities and challenges of metabolomics in nowadays HCC precision medicine. As technologies improving and metabolite biomarkers discovering, metabolomics has made a major step toward more timely and effective precision medicine for HCC patients.

Evaluation of the Clinical Efficacy of Intensity-Modulated Radiotherapy Combined with Transcatheter Arterial Chemoembolization for Hepatocellular Carcinoma with Extrahepatic Oligometastasis and Prognostic Factors for Patient Survival

Objective

To investigate the clinical efficacy of intensity-modulated radiotherapy (IMRT) combined with transcatheter arterial chemoembolization (TACE) in hepatocellular carcinoma (HCC) patients with extrahepatic oligometastasis and the prognosis of patients receiving this treatment.

Patients and Methods

Twenty-one HCC patients with extrahepatic oligometastasis were retrospectively analyzed; seven patients received IMRT only, and 14 received IMRT plus TACE. TACE treatment was administered before IMRT (50 mg epirubicin, oxaliplatin 100 mg, and mitomycin 10 mg). The short-term efficacy of this treatment and patient prognosis were evaluated.

Results

Complete response (CR) and partial response (PR) in the intrahepatic region were achieved in three and 14 patients, respectively. The objective response rate (ORR) approached 81%. CR and PR were achieved in six and 10 patients with extrahepatic metastases, respectively, for an ORR of 100%. Pain was completely relieved in all patients with bone metastases. The median overall survival (OS) and progression-free survival (PFS) were 21 months and 9.1 months, respectively. The 1-year PFS rate was 43%, and the 1-, 2-, 3-, and 4-year OS rates were 83%, 35%, 9%, and 4%, respectively. Univariate analysis showed that the prognostic factors for patient survival included Child-Pugh class, vascular thrombus, Karnofsky performance status (KPS), radiotherapy dose, ascites, combination therapy, and pattern of progression. Multivariate analysis showed that vascular thrombus, combination therapy, and pattern of failure were prognostic factors for PFS, and the KPS was the only prognostic factor for OS. No grade 3-4 adverse reactions were observed.

Conclusion

IMRT combined with TACE is safe and feasible without major toxicities for the treatment of advanced HCC patients with extrahepatic oligometastasis and results in excellent objective efficacy and a potential survival benefit. The KPS is the only predictive factor for OS. This approach is expected to be a useful palliative option for selected HCC patients with extrahepatic metastases.

KLF4 loss in hepatocellular carcinoma: Improving prognostic prediction and correlating immune infiltrates

Introduction: Although the molecular mechanisms of Krüpple-like factor 4 (KLF4) as a tumor suppressor in HCC tumorigenesis have been thoroughly examined, its clinical application in terms of precise prognostication and its influence on tumor immune microenvironment in patients with HCC require further investigation. Methods: Bioinformatics and immunohistochemistry (IHC) were used to validate KLF4 expressions in a tissue microarray (TMA) containing HCC samples. Using Cox regression models, independent prognostic factors were identified and employed in the development of nomograms. Decision curve analysis (DCA) demonstrated the superiority of the nomograms. GO and KEGG pathway analyses were applied to the functional study of KLF4. The GSVA program explored the link between KLF4 expression and tumor-infiltrating immune cells, and CAMOIP was used to construct KLF4 expression immune scores. Changes in immune-related gene markers were also investigated in relation to KLF4 expression. The association between immune cell infiltration and KLF4 expression was validated by IHC in TMA. Results: HCC was reported to have a notable depletion of KLF4. The absence of KLF4 was associated with advanced clinicopathological characteristics of HCC and predicted a bad prognosis for patients. Nomograms constructed using KLF4 expression, tumor differentiation, and TNM stage provided a more accurate prognostic assessment of HCC patients than TNM stage alone. KLF4 expression was associated with immunological-related functions, infiltration of macrophages, CD8⁺ T cells, and other immune cells, and elevation of immune checkpoints. Higher levels of CD8⁺ T cells and macrophage infiltration are associated with increased KLF4 expression in HCC TMA. Conclusion: KLF4 loss in HCC is a prognostic biomarker that influences the tumor immune microenvironment (TIME).

The Role of Cell-Free DNA in Cancer Treatment Decision Making

The aim of this review is to evaluate the present status of the use of cell-free DNA and its fraction of circulating tumor DNA (ctDNA) because this year July 2022, an ESMO guideline was published regarding the application of ctDNA in patient care. This review is for clinical oncologists to explain the concept, the terms used, the pros and cons of ctDNA; thus, the technical aspects of the different platforms are not reviewed in detail, but we try to help in navigating the current knowledge in liquid biopsy. Since the validated and adequately sensitive ctDNA assays have utility in identifying actionable mutations to direct targeted therapy, ctDNA may be used for this soon in routine clinical practice and in other different areas as well. The cfDNA fragments can be obtained by liquid biopsy and can be used for diagnosis, prognosis, and selecting among treatment options in cancer patients. A great proportion of cfDNA comes from normal cells of the body or from food uptake. Only a small part (<1%) of it is related to tumors, originating from primary tumors, metastatic sites, or circulating tumor cells (CTCs). Soon the data obtained from ctDNA may routinely be used for finding minimal residual disease, detecting relapse, and determining the sites of metastases. It might also be used for deciding appropriate therapy, and/or emerging resistance to the therapy and the data analysis of ctDNA may be combined with imaging or other markers. However, to achieve this goal, further clinical validations are inevitable. As a result, clinicians should be aware of the limitations of the assays. Of course, several open questions are still under research and because of it cfDNA and ctDNA testing are not part of routine care yet.

Nanotechnology strategies for hepatocellular carcinoma diagnosis and treatment

Hepatocellular carcinoma (HCC) is a common malignancy threatening human health, and existing diagnostic and therapeutic techniques are facing great challenges. In the last decade or so, nanotechnology has been developed and improved for tumor diagnosis and treatment. For example, nano-intravenous injections have been approved for malignant perivascular epithelioid cell tumors. This article provides a comprehensive review of the applications of nanotechnology in HCC in recent years: (I) in radiological imaging, magnetic resonance imaging (MRI), fluorescence imaging (FMI) and multimodality imaging. (II) For diagnostic applications in HCC serum markers. (III) As embolic agents in transarterial chemoembolization (TACE) or directly as therapeutic drugs. (IV) For application in photothermal therapy and photodynamic therapy. (V) As carriers of chemotherapeutic drugs, targeted drugs, and natural plant drugs. (VI) For application in gene and immunotherapy. Compared with the traditional methods for diagnosis and treatment of HCC, nanoparticles have high sensitivity, reduce drug toxicity and have a long duration of action, and can also be combined with photothermal and photodynamic multimodal combination therapy. These summaries provide insights for the further development of nanotechnology applications in HCC.

Construction of a Novel Oxidative Stress Response-Related Gene Signature for Predicting the Prognosis and Therapeutic Responses in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with poor outcomes, and the assessment of its prognosis as well as its response to therapy is still challenging. In this study, we aimed to construct an oxidative stress response-related genes-(OSRGs-) based gene signature for predicting prognosis and estimating treatment response in patients with HCC. We integrated the transcriptomic data and clinicopathological information of HCC patients from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. LASSO Cox regression analysis was utilized to establish an integrated multigene signature in the TCGA cohort, and its prediction performance was validated in the ICGC cohort. The CIBERSORT algorithm was employed to evaluate immune cell infiltration. The response rate to immune checkpoint inhibition (ICI) therapy was assessed using a TIDE platform. Drug activity data from the Cancer Genome Project and NCI-60 human cancer cell lines were used to predict sensitivity to chemotherapy. We successfully established a gene signature comprising G6PD, MT3, CBX2, CDKN2B, CCNA2, MAPT, EZH2, and SLC7A11. The risk score of each patient, which was determined by the multigene signature, was identified as an independent prognostic marker. The immune cell infiltration patterns, response rates to ICI therapy, and the estimated sensitivity of 89 chemotherapeutic drugs were associated with risk scores. Individual prognostic genes were also associated with susceptibility to various FDA-approved drugs. Our study indicates that a comprehensive transcriptomic analysis of OSRGs can provide a reliable molecular model to predict prognosis and therapeutic response in patients with HCC.

Tumor Promoting Effects of Sulforaphane on Diethylnitrosamine-Induced Murine Hepatocarcinogenesis

Nuclear factor erythroid 2-related factor 2 (NRF2) is a key transcription factor involved in protection against initiation of carcinogenesis in normal cells. Notably, recent studies have demonstrated that aberrant activation of NRF2 accelerates the proliferation and progression of cancer cells. The differential effects of NRF2 on multi-stage carcinogenesis have raised a concern about the validity of NRF2 activators for chemoprevention. This prompted us to assess the effects of sulforaphane (SFN), a prototypic NRF2 activating chemopreventive phytochemical, on experimentally induced carcinogenesis. In the present study, SFN was daily injected intraperitoneally (25 mg/kg) for 3 months to male C57BL/6 mice at 6 months after single intraperitoneal administration of a hepatocarcinogen, diethylnitrosamine (DEN). The liver to body weight ratio, tumor growth, and the number and the size of hepatomas measured at 9 months after DEN administration were significantly higher in SFN-treated mice than those in vehicle-treated mice. Moreover, the expression of NRF2, its target protein NAD(P)H:quinone oxidoreductase 1, and the cell proliferation marker, proliferating cell nuclear antigen was further elevated in DEN plus SFN-treated mice. These results suggest that once hepatocarcinogenesis is initiated, SFN may stimulate tumor progression.

Development of a hepatocellular carcinoma imaging database and structured imaging reports based on PACS, HIS, and repository

Purpose

To establish a hepatocellular carcinoma imaging database and structured imaging reports based on PACS, HIS, and repository.

Methods

This study was approved by the Institutional Review Board. The steps of establishing the database are as follows: 1) According to the standards required for the intelligent diagnosis of HCC, it was attempted to design the corresponding functional modules after analyzing the requirements; 2) Based on client/server (C/S) mode, 3-tier architecture model was adopted. A user interface (UI) could receive data entered by users and show handled data. Business logic layer (BLL) could process the business logic of the data, and data access layer (DAL) could save the data in the database. The storage and management of HCC imaging data could be realized by the SQLSERVER database management software, and Delphi and VC++ programming languages were used.

Results

The test results showed that the proposed database could swiftly obtain the pathological, clinical, and imaging data of HCC from the picture archiving and communication system (PACS) and hospital information system (HIS), and perform data storage and visualization of structured imaging reports. According to the HCC imaging data, liver imaging reporting and data system (LI-RADS) assessment, standardized staging, and intelligent imaging analysis were carried out on the high-risk population to establish a one-stop imaging evaluation platform for HCC, strongly supporting clinicians in the diagnosis and treatment of HCC.

Conclusions

The establishment of a HCC imaging database can not only provide a huge amount of imaging data for the basic and clinical research on HCC, but also facilitate the scientific management and quantitative assessment of HCC. Besides, a HCC imaging database is advantageous for personalized treatment and follow-up of HCC patients.