Liquid Biopsy in Hepatocellular Carcinoma: Opportunities and Challenges for Immunotherapy

Unveiling the Influence of AI Predictive Analytics on Patient Outcomes: A Comprehensive Narrative Review

This comprehensive literature review explores the transformative impact of artificial intelligence (AI) predictive analytics on healthcare, particularly in improving patient outcomes regarding disease progression, treatment response, and recovery rates. AI, encompassing capabilities such as learning, problem-solving, and decision-making, is leveraged to predict disease progression, optimize treatment plans, and enhance recovery rates through the analysis of vast datasets, including electronic health records (EHRs), imaging, and genetic data. The utilization of machine learning (ML) and deep learning (DL) techniques in predictive analytics enables personalized medicine by facilitating the early detection of conditions, precision in drug discovery, and the tailoring of treatment to individual patient profiles. Ethical considerations, including data privacy, bias, and accountability, emerge as vital in the responsible implementation of AI in healthcare. The findings underscore the potential of AI predictive analytics in revolutionizing clinical decision-making and healthcare delivery, emphasizing the necessity of ethical guidelines and continuous model validation to ensure its safe and effective use in augmenting human judgment in medical practice.

Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy

Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits a minority of patients, underscoring the importance of discovering reliable biomarkers that can be used to screen for potential beneficiaries and ultimately reduce the risk of overtreatment. Our comprehensive review focuses on the latest advancements in predictive biomarkers for ICI therapy, particularly emphasizing those that enhance the efficacy of programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors immunotherapies. We explore biomarkers derived from various sources, including tumor cells, the tumor immune microenvironment (TIME), body fluids, gut microbes, and metabolites. Among them, tumor cells-derived biomarkers include tumor mutational burden (TMB) biomarker, tumor neoantigen burden (TNB) biomarker, microsatellite instability (MSI) biomarker, PD-L1 expression biomarker, mutated gene biomarkers in pathways, and epigenetic biomarkers. TIME-derived biomarkers include immune landscape of TIME biomarkers, inhibitory checkpoints biomarkers, and immune repertoire biomarkers. We also discuss various techniques used to detect and assess these biomarkers, detailing their respective datasets, strengths, weaknesses, and evaluative metrics. Furthermore, we present a comprehensive review of computer models for predicting the response to ICI therapy. The computer models include knowledge-based mechanistic models and data-based machine learning (ML) models. Among the knowledge-based mechanistic models are pharmacokinetic/pharmacodynamic (PK/PD) models, partial differential equation (PDE) models, signal networks-based models, quantitative systems pharmacology (QSP) models, and agent-based models (ABMs). ML models include linear regression models, logistic regression models, support vector machine (SVM)/random forest/extra trees/k-nearest neighbors (KNN) models, artificial neural network (ANN) and deep learning models. Additionally, there are hybrid models of systems biology and ML. We summarized the details of these models, outlining the datasets they utilize, their evaluation methods/metrics, and their respective strengths and limitations. By summarizing the major advances in the research on predictive biomarkers and computer models for the therapeutic effect and clinical utility of tumor ICI, we aim to assist researchers in choosing appropriate biomarkers or computer models for research exploration and help clinicians conduct precision medicine by selecting the best biomarkers.

Exploring the mechanism of LncRNA CASC15 affecting hepatocellular carcinoma through miRNA

This study aimed to determine the potential mechanisms through which long noncoding (Lnc) RNA cancer susceptibility candidate 15 (CASC15) affects hepatocellular carcinoma (HCC). We retrieved HCC RNA-seq and clinical information from the UCSC Xena database. The differential expression (DE) of CASC15 was detected. Overall survival was analyzed using Kaplan-Meier (K-M) curves. Molecular function and signaling pathways affected by CASC15 were determined using Gene Set Enrichment Analysis. Associations between CASC15 and the HCC microenvironment were investigated using immuno-infiltration assays. A differential CASC15-miRNA-mRNA network and HCC-specific CASC15-miRNA-mRNA ceRNA network were constructed. The overexpression of CASC15 in HCC tissues was associated with histological grade, clinical stage, pathological T stage, poor survival, more complex immune cell components, and 12 immune checkpoints. We identified 27 DE miRNAs and 270 DE mRNAs in the differential CASC15-miRNA-mRNA network, and 10 key genes that were enriched in 12 cancer-related signaling pathways. Extraction of the HCC-specific CASC15-miRNA-mRNA network revealed that IGF1R, MET, and KRAS were associated with HCC progression and occurrence. Our bioinformatic findings confirmed that CASC15 is a promising prognostic biomarker for HCC, and elevated levels in HCC are associated with the tumor microenvironment. We also constructed a disease-specific CASC15-miRNA-mRNA regulatory ceRNA network that provides a new perspective for the precise indexing of patients with elevated levels of CASC15.

Immunotherapy-related biomarkers: Confirmations and uncertainties

Immunotherapy profoundly changed oncology treatment, becoming one of the main therapeutical strategies. Remarkable improvement has been achieved in survival outcomes, but the percentage of patients who benefit from immunotherapy is still limited. Only one-third of patients receiving immune checkpoint inhibitors (ICIs) achieve long-term response. Several patients are not responsive to treatment or relapse after an initial response. To date, programmed death-ligand 1, microsatellite instability, and tumor mutational burden are the three biomarkers validated to predict the ICIs response, but a single variable seems still insufficient in the patient's selection. Considering the substantial and increasing use of these drugs, the identification of new predictive biomarkers of ICI response is of paramount importance. We summarize the state of the art and the clinical use of immune biomarkers in oncology, highlighting the strength and weaknesses of currently approved biomarkers, describing the emerging tissues and circulating biomarkers, and outlining future perspectives.

Current state and challenges of emerging biomarkers for immunotherapy in hepatocellular carcinoma (Review)

Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer. According to the American Cancer Society, among patients diagnosed with advanced liver cancer, HCC has the sixth-highest incident rate, resulting in a poor prognosis. Surgery, radiofrequency ablation, transcatheter arterial chemoembolization, radiation, chemotherapy, targeted therapy and immunotherapy are the current treatment options available. Immunotherapy, which has emerged as an innovative treatment strategy over the past decade, is serving a vital role in the treatment of advanced liver cancer. Since only a small number of individuals can benefit from immunotherapy, biomarkers are required to help clinicians identify the target populations for this precision medicine. These biomarkers, such as PD-1/PD-L1, tumor mutational burden and circulating tumor DNA, can be used to investigate interactions between immune checkpoint inhibitors and tumors. The present review summarizes information on the currently available biomarkers used for immunotherapy and the challenges that are present.

Peripheral blood-based cell signature indicates response to interstitial brachytherapy in primary liver cancer

PURPOSE

Biomarkers are essential to implement personalized therapies in cancer treatment options. As primary liver tumors are increasing and treatment is coupled to liver function and activation of systemic cells of the immune system, we investigated blood-based cells for their ability to predict response to local ablative therapy.

METHODS

We analyzed peripheral blood cells in 20 patients with primary liver cancer at baseline and following brachytherapy. In addition to platelets, leukocytes, lymphocytes, monocytes, neutrophils and most common ratios PLR, LMR, NMR and NLR, we investigated T cell and NKT cell populations of 11 responders and 9 non-responders using flow cytometry.

RESULTS

We have found a peripheral blood cell signature that differed significantly between responders and non-responders treated with interstitial brachytherapy (IBT). At baseline, non-responders featured higher numbers of platelets, monocytes and neutrophils, a higher platelet-to-lymphocyte ratio and an increase in the NKT cell population with a concurrent reduction in CD16 + NKT cells. Simultaneously, a lower percentage of CD4 + T cells was present in non-responders, as also reflected in a lower CD4/8 ratio. CD45RO + memory cells were lower in both, CD4 + and CD8 + T cell populations whereas PD-1 + T cells were only present in the CD4 + T cell population.

CONCLUSION

Baseline blood-based cell signature may function as a biomarker to predict response following brachytherapy in primary liver cancer.

The Emerging Role of Circulating Tumor DNA in Non-Colorectal Gastrointestinal Cancers

Assays to detect circulating tumor DNA (ctDNA) have multiple clinically important applications in management of multiple types of gastrointestinal cancers. Different methodologies of ctDNA detection have varying sensitivities and potential applications in different contexts. For patients with localized cancers treated for curative intent, ctDNA detection is associated with prognosis in multiple cancer types, and persistent detection of ctDNA after surgical resection is highly concerning for minimal residual disease (MRD) and forebodes impending radiographic and clinical recurrence. CtDNA assays for comprehensive genomic profiling enable genotyping of cancers in the absence of tumor tissue data, and longitudinal testing can also characterize clonal evolution and emergence of putative resistance mechanisms upon treatment with targeted agents. These applications have proven instructive in patients with HER2-amplified gastric and esophageal cancers and in patients with FGFR2 fusion cholangiocarcinomas. In this review, we summarize data supporting the role of ctDNA as a novel predictive and prognostic biomarker and potential impacts on current management of patients with pancreatic, gastroesophageal, and hepatobiliary cancers.

European Society for Organ Transplantation Consensus Statement on Biomarkers in Liver Transplantation

Currently, one-year survival following liver transplantation (LT) exceeds 90% in large international registries, and LT is considered definitive treatment for patients with end-stage liver disease and liver cancer. Recurrence of disease, including hepatocellular carcinoma (HCC), significantly hampers post-LT outcomes. An optimal approach to immunosuppression (IS), including safe weaning, may benefit patients by mitigating the effect on recurrent diseases, as well as reducing adverse events associated with over-/under-IS, including chronic kidney disease (CKD). Prediction of these outcome measures-disease recurrence, CKD, and immune status-has long been based on relatively inaccurate clinical models. To address the utility of new biomarkers in predicting these outcomes in the post-LT setting, the European Society of Organ Transplantation (ESOT) and International Liver Transplant Society (ILTS) convened a working group of experts to review literature pertaining to primary disease recurrence, development of CKD, and safe weaning of IS. Summaries of evidence were presented to the group of panelists and juries to develop guidelines, which were discussed and voted in-person at the Consensus Conference in Prague November 2022. The consensus findings and recommendations of the Liver Working Group on new biomarkers in LT, clinical applicability, and future needs are presented in this article.

Development and in functional study of a bi-specific sustained release drug-loaded nano-liposomes for hepatocellular carcinoma

BACKGROUND

Lenvatinib (LEN) is a first-line therapy for patients with hepatocellular carcinoma (HCC), but has a larger adverse effect profile. In this study, we developed a liposome with drug-carrying function and magnetic resonance imaging (MRI) imaging function to investigate the targeted drug-carrying function and MRI tracing ability of liposome for HCC.

METHODS

Magnetic nano-liposomes (MNL) with dual targeting function of epithelial cell adhesion molecule (EpCAM) and vimentin and capable of encapsulating LEN drugs were prepared. The characterization performance, drug loading efficiency and cytotoxicity of EpCAM/vimentin-LEN-MNL were tested, and the dual-targeting slow release drug loading function and MRI tracing ability were investigated in cellular and animal models.

RESULTS

EpCAM/vimentin-LEN-MNL has a mean particle size of 218.37 ± 5.13 nm and a mean potential of 32.86 ± 4.62 mV, and is spherical in shape and can be uniformly dispersed in solution. The encapsulation rate was 92.66 ± 0.73% and the drug loading rate was 9.35 ± 0.16%. It has low cytotoxicity, can effectively inhibit HCC cell proliferation and promote HCC cell apoptosis, and has specific targeting function and MRI tracing ability for HCC cells.

CONCLUSIONS

In this study, an HCC-specific dual-targeted sustained-release drug delivery liposome with dual-targeted recognition and sensitive MRI tracer was successfully prepared, which provides an important scientific basis for maximizing the multiple effects of nano-carriers in tumor diagnosis and treatment.

Circulating Tumor Cells: From the Laboratory to the Cancer Clinic; A Closing Comment

Cancer recurrence not only shortens the life span of cancer patients, but also leads to a decrease in QOL, so it needs to be controlled [...].

Mesenchymal circulating tumor cells and Ki67: their mutual correlation and prognostic implications in hepatocellular carcinoma

BACKGROUND

Mesenchymal circulating tumor cells (M-CTCs) may be related to tumor progression, and Ki67 expression is known to be involved in tumor proliferation. The aim of the present study was to explore the relationship between M-CTCs and Ki67 in hepatocellular carcinoma (HCC) and their ability to predict prognosis.

METHODS

Peripheral blood samples were obtained from 105 HCC patients before radical surgery. CTCs were isolated using CanPatrol enrichment and classified via in situ hybridization. Ki67 expression in HCC tissue was assessed through immunohistochemistry. Potential relationships of M-CTC, Ki67 with clinicopathological factors and prognosis were evaluated. Overall survival (OS) was analyzed using the Kaplan-Meier method and Cox regression. The prognostic efficacy of M-CTC, Ki67 and both together (M-CTC + Ki67) was assessed in terms of time-dependent receiver operating characteristic (ROC) curves and Harrell's concordance index.

RESULTS

Of the 105 patients, 50 were positive for M-CTCs (count ≥ 1 per 5 mL) and 39 showed high Ki67 expression (≥ 50% tumor cells were Ki67-positive). The presence of M-CTC was significantly associated with alpha-fetoprotein (AFP) ≥ 400 ng/mL (P = 0.007), tumor size ≥ 5 cm (P = 0.023), multiple tumors (P < 0.001), poorly differentiated tumors (P = 0.003), incomplete tumor capsule (P < 0.001), Barcelona Clinic liver cancer (BCLC) stage B or C (P < 0.001), microvascular invasion (MVI) (P = 0.05) and portal vein tumor thrombosis (PVTT) (P = 0.006). High Ki67 expression correlated with AFP ≥ 400 ng/mL (P = 0.015), tumor size ≥ 5 cm (P = 0.012), incomplete tumor capsule (P < 0.001), MVI (P = 0.001), PVTT (P = 0.003), advanced BCLC stage (P = 0.01), and vessel carcinoma embolus (VCE) (P = 0.001). M-CTC positively correlated with Ki67. Patients positive for M-CTCs had a significantly shorter OS than patients negative for them. Similarly, high Ki67 expression was associated with a significantly lower OS. The high-risk group (positive for M-CTCs and high Ki67 expression) had worse OS than the other groups (P < 0.0001). Uni- and multivariate analyses showed that OS was independently predicted by M-CTC [hazard ratio (HR) 1.115; P < 0.001], Ki67 (HR 1.666; P = 0.046) and the combination of both (HR 2.885; P = 0.008). Based on ROC curves and the concordance index, the combination of M-CTC and Ki67 was superior to either parameter alone for predicting the OS of HCC patients.

CONCLUSIONS

The presence of M-CTC correlates with high Ki67 expression in HCC patients, and both factors are associated with poor prognosis. Furthermore, the combination of M-CTC and Ki67 is a useful prognostic indicator for predicting OS in patients with HCC after hepatectomy, performing better than either parameter on its own.

Tyrosine kinase inhibitors as potential sensitizers of adoptive T cell therapy for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a high-incidence malignant tumor worldwide and lacks effective treatment options. Targeted drugs are the preferred recommendations for the systemic treatment of hepatocellular carcinoma. Immunotherapy is a breakthrough in the systemic treatment of malignant tumors, including HCC. However, either targeted therapy or immunotherapy alone is inefficient and has limited survival benefits on part of HCC patients. Investigations have proved that tyrosine kinase inhibitors (TKIs) have regulatory effects on the tumor microenvironment and immune response, which are potential sensitizers for immunotherapy. Herein, a combination therapy using TKIs and immunotherapy has been explored and demonstrated to improve the effectiveness of treatment. As an effective immunotherapy, adoptive T cell therapy in solid tumors is required to improve tumor infiltration and killing activity which can be possibly achieved by combination with TKIs.

Blood-based biomarkers for immune-based therapy in advanced HCC: Promising but a long way to go

The introduction of immune checkpoint inhibitors (ICIs) represents a key shift in the management strategy for patients with hepatocellular carcinoma (HCC). However, there is a paucity of predictive biomarkers that facilitate the identification of patients that would respond to ICI therapy. Although several researchers have attempted to resolve the issue, the data is insufficient to alter daily clinical practice. The use of minimally invasive procedures to obtain patient-derived specimen, such as using blood-based samples, is increasingly preferred. Circulating tumor DNA (ctDNA) can be isolated from the blood of cancer patients, and liquid biopsies can provide sufficient material to enable ongoing monitoring of HCC. This is particularly significant for patients for whom surgery is not indicated, including those with advanced HCC. In this review, we summarize the current state of understanding of blood-based biomarkers for ICI-based therapy in advanced HCC, which is promising despite there is still a long way to go.

Non-Invasive Biomarkers for Immunotherapy in Patients with Hepatocellular Carcinoma: Current Knowledge and Future Perspectives

Simple Summary

The search for non-invasive biomarkers is a hot topic in modern oncology, since a tissue biopsy has significant limitations in terms of cost and invasiveness. The treatment perspectives have been significantly improved after the approval of immunotherapy for patients with hepatocellular carcinoma; therefore, the quick identification of responders is crucial to define the best therapeutic strategy. In this review, the current knowledge on the available non-invasive biomarkers of the response to immunotherapy is described.

Abstract

The treatment perspectives of advanced hepatocellular carcinoma (HCC) have deeply changed after the introduction of immunotherapy. The results in responders show improved survival compared with Sorafenib, but only one-third of patients achieve a significant benefit from treatment. As the tumor microenvironment exerts a central role in shaping the response to immunotherapy, the future goal of HCC treatment should be to identify a proxy of the hepatic tissue condition that is easy to use in clinical practice. Therefore, the search for biomarkers that are accurate in predicting prognosis will be the hot topic in the therapeutic management of HCC in the near future. Understanding the mechanisms of resistance to immunotherapy may expand the patient population that will benefit from it, and help researchers to find new combination regimens to improve patients’ outcomes. In this review, we describe the current knowledge on the prognostic non-invasive biomarkers related to treatment with immune checkpoint inhibitors, focusing on serological markers and gut microbiota.

Immunotherapy for nonalcoholic fatty liver disease-related hepatocellular carcinoma: Lights and shadows

About one-fourth of adults globally suffer from nonalcoholic fatty liver disease (NAFLD), which is becoming a leading cause of chronic liver disease worldwide. Its prevalence has rapidly increased in recent years, and is projected to increase even more. NAFLD is a leading cause of hepatocellular carcinoma (HCC), the sixth-most prevalent cancer worldwide and the fourth most common cause of cancer-related death. Although the molecular basis of HCC onset in NAFLD is not completely known, inflammation is a key player. The tumor microenvironment (TME) is heterogeneous in patients with HCC, and is characterized by complex interactions between immune system cells, tumor cells and other stromal and resident liver cells. The etiology of liver disease plays a role in controlling the TME and modulating the immune response. Markers of immune suppression in the TME are associated with a poor prognosis in several solid tumors. Immunotherapy with immune checkpoint inhibitors (ICIs) has become the main option for treating cancers, including HCC. However, meta-analyses have shown that patients with NAFLD-related HCC are less likely to benefit from therapy based on ICIs alone. Conversely, the addition of an angiogenesis inhibitor showed better results regarding the objective response rate and progression-free survival. Adjunctive diagnostic and therapeutic strategies, such as the application of novel biomarkers and the modulation of gut microbiota, should be considered in the future to guide personalized medicine and improve the response to ICIs in patients with NAFLD-related HCC.

Personalized treatment for hepatocellular carcinoma: Current status and future perspectives

Systemic treatment for hepatocellular carcinoma (HCC) has been advancing rapidly over the last decade. More novel agents, including both targeted agents and immune checkpoint inhibitors, are available for physicians to use sequentially or concurrently for patients with advanced HCC. Despite more options, only a proportion of patients benefit from each regimen. Therefore, clinicians are facing challenges on how to choose the right regimen for the right patient with HCC, which raises the importance of personalized treatment approach. To advance personalized treatment for HCC, one approach relies on the acquisition of biomarker data from clinical trials to evaluate clinical parameters or genotypes in association with outcomes of selected drugs. This approach has led to finding of high baseline alpha-fetoprotein levels in association with benefits of ramucirumab. Cumulative findings from multiple clinical trials and translational studies also suggest that selected etiology and/or genotype of HCC could predict resistance to immune checkpoint inhibitors. The second approach is to decipher the tumor heterogeneity of HCC with an aim to identify clinically relevant patterns to guide clinical decisions. Tumor heterogeneity could exist within a single tumor (intra-tumoral heterogeneity), among different tumors in the same patient (inter-tumoral heterogeneity) or between primary and recurrent tumors (temporal tumor heterogeneity). The analyses of tumor heterogeneity have also been powered by coverage of tumor immune environment and incorporation of circulating tumor nucleic acid technology. Emerging publications have been reported above tumor heterogeneity exist in HCC, which is potentially clinically impactful.

Efficacy and safety of camrelizumab plus apatinib during the perioperative period in resectable hepatocellular carcinoma: a single-arm, open label, phase II clinical trial

Objective

This study aimed to assess the efficacy and safety of camrelizumab plus apatinib in patients with resectable hepatocellular carcinoma (HCC) as neoadjuvant therapy.

Methods

Initially, 20 patients with HCC were screened and 18 patients with resectable HCC were enrolled in this open-label, single-arm, phase II clinical trial. Patients received three cycles of neoadjuvant therapy including three doses of camrelizumab concurrent with apatinib for 21 days followed by surgery. Four to 8 weeks after surgery, patients received eight cycles of adjuvant therapy with camrelizumab in combination with apatinib. Major pathological reactions (MPR), complete pathological reactions (pCR), objective response rate (ORR), relapse-free survival (RFS), and adverse events (AE) were assessed. In addition, cancer tissue and plasma samples were collected before and after treatment, and genetic differences between responding and non-responding lesions were compared by tumor immune microenvironment (TIME) analysis, circulating tumor DNA (ctDNA) analysis and proteomics analysis.

Results

In 18 patients with HCC who completed neoadjuvant therapy, 3 (16.7%) and 6 (33.3%) patients with HCC reached ORR based on Response Evaluation Criteria in Solid Tumors (RECIST) V.1.1 and modified RECIST criteria, respectively. Of the 17 patients with HCC who received surgical resection, 3 (17.6%) patients with HCC reported MPR and 1 (5.9%) patient with HCC achieved pCR. The 1-year RFS rate of the enrolled patients was 53.85% (95% CI: 24.77% to 75.99%). Grade 3/4 AEs were reported in 3 (16.7%) of the 18 patients, with the most common AEs being rash (11.1%), hypertension (5.6%), drug-induced liver damage (5.6%), and neutropenia (5.6%) in the preoperative phase. The 289 NanoString panel RNA sequencing showed that TIME cell infiltration especially dendritic cells (DCs) infiltration was better in responding tumors than in non-responding tumors. Our results of ctDNA revealed a higher positive rate (100%) among patients with HCC with stage IIb–IIIa disease. When comparing patients with pCR/MPR and non-MPR, we observed more mutations in patients who achieved pCR/MPR at baseline (6 mutations vs 2.5 mutations, p=0.025). Patients who were ctDNA positive after adjuvant therapy presented a trend of shorter RFS than those who were ctDNA negative. Proteomic analysis suggested that abnormal glucose metabolism in patients with multifocal HCC might be related to different sensitivity of treatment in different lesions.

Conclusion

Perioperative camrelizumab plus apatinib displays a promising efficacy and manageable toxicity in patients with resectable HCC. DCs infiltration might be a predictive marker of response to camrelizumab and apatinib as well as patients’ recurrence. ctDNA as a compose biomarker can predict pathological response and relapse. Abnormal glucose metabolism in patients with multifocal HCC may be related to different sensitivity of treatment in different lesions.

Trial registration number

NCT04297202.

Implications of genetic heterogeneity in hepatocellular cancer

Hepatocellular carcinoma (HCC) exhibits a remarkable degree of heterogeneity, not only at an inter-patient level but also between and within tumors in the same patient. The advent of next-generation sequencing (NGS)-based technologies has allowed the creation of high-resolution atlases of HCC. This review outlines recent findings from genomic, epigenomic, transcriptomic, and proteomic sequencing that have yielded valuable insights into the spatial and temporal heterogeneity of HCC. The high heterogeneity of HCC has both clinical and therapeutic implications. The challenges in prospectively validating molecular classifications for HCC either for prognostication or for prediction of therapeutic response are partly due to the immense heterogeneity in HCC. Moreover, the heterogeneity of HCC tumors combined with the lack of commonly mutated, druggable targets severely limits treatment options for HCC. Recently, immune checkpoint inhibitors and combination therapies have shown promise for advanced HCC, while T cell therapies and vaccines are currently being investigated. Yet, immunotherapies show benefit only in a limited subset of patients, making it imperative to decipher tumor heterogeneity in HCC in order to enable optimal patient selection. This review summarizes the cutting-edge research on heterogeneity in HCC and explores the implications of heterogeneity on stratifying patients and developing biomarkers and therapies for HCC.

Translational Regulation in Hepatocellular Carcinogenesis

The mortality of hepatocellular carcinoma (HCC) is distributed unevenly worldwide. One of the major causes is hepatitis B or hepatitis C virus infection and the development and progression of liver cirrhosis. The carcinogenesis of HCC is among others regulated via the mTOR (mechanistic target of rapamycin) signaling pathway and represents a possible method of targeted treatment. The aim of our article was to address the most recent clinical advances and findings of basic studies on the mTOR signaling pathway and the involved factors. Risk factors play a key role in dysregulation of the signaling pathway, where both mTORCs are upregulated and protein synthesis is altered. eIFs and, to a lesser extent, eEFs play an essential role in this process. Whether the factor will be upregulated or downregulated, among others, depends on hepatitis B/C virus infection. The amount of a particular factor in a patient sample lets us know whether HCC recurrence will occur, what is the likelihood of chemoresistance, and what outcome is predicted for patients with an increased value. Our analysis shows that in addition to mTOR, eIF3, eIF4, and eIF5 play an important role, as they can serve as biomarkers for non- and virus-related HCC.