Hepatic Cancer Stem Cells: Molecular Mechanisms, Therapeutic Implications, and Circulating Biomarkers

Reappraisal of the Roles of the Sonic Hedgehog Signaling Pathway in Hepatocellular Carcinoma

HCC remains one of the leading causes of cancer-related death globally. The main challenges in treatments of hepatocellular carcinoma (HCC) primarily arise from high rates of postoperative recurrence and the limited efficacy in treating advanced-stage patients. Various signaling pathways involved in HCC have been reported. Among them, the Sonic hedgehog (SHH) signaling pathway is crucial. The presence of SHH ligands is identified in approximately 60% of HCC tumor tissues, including tumor nests. PTCH-1 and GLI-1 are detected in more than half of HCC tissues, while GLI-2 is found in over 84% of HCC tissues. The SHH signaling pathway (including canonical and non-canonical) is involved in different aspects of HCC, including hepatocarcinogenesis, tumor growth, tumor invasiveness, progression, and migration. The SHH signaling pathway also contributes to recurrence, metastasis, modulation of the cancer microenvironment, and sustaining cancer stem cells. It also affects the resistance of HCC cells to chemotherapy, target therapy, and radiotherapy. Reappraisal of the roles of the SHH signaling pathway in HCC may trigger some novel therapies for HCC.

Cellular and Molecular Biology of Cancer Stem Cells of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death globally. The cancer stem cells (CSCs) of HCC are responsible for tumor growth, invasion, metastasis, recurrence, chemoresistance, target therapy resistance and radioresistance. The reported main surface markers used to identify liver CSCs include epithelial cell adhesion/activating molecule (EpCAM), cluster differentiation 90 (CD90), CD44 and CD133. The main molecular signaling pathways include the Wnt/β-catenin, transforming growth factors-β (TGF-β), sonic hedgehog (SHH), PI3K/Akt/mTOR and Notch. Patients with EpCAM-positive alpha-fetoprotein (AFP)-positive HCC are usually young but have advanced tumor-node-metastasis (TNM) stages. CD90-positive HCCs are usually poorly differentiated with worse prognosis. Those with CD44-positive HCC cells develop early metastases. Those with CD133 expression have a higher recurrence rate and a shorter overall survival. The Wnt/β-catenin signaling pathway triggers angiogenesis, tumor infiltration and metastasis through the enhancement of angiogenic factors. All CD133+ liver CSCs, CD133+/EpCAM+ liver CSCs and CD44+ liver CSCs contribute to sorafenib resistance. SHH signaling could protect HCC cells against ionizing radiation in an autocrine manner. Reducing the CSC population of HCC is crucial for the improvement of the therapy of advanced HCC. However, targeting CSCs of HCC is still challenging.

Animal Models of Hepatocellular Carcinoma: Current Applications in Clinical Research

In the last decade, relevant advances have occurred in the treatment of hepatocellular carcinoma (HCC), with novel drugs entering the clinical practice, among which tyrosine kinase inhibitors (TKIs) such as lenvatinib, cabozantinib and regorafenib, and immune checkpoint inhibitors (ICPIs) either alone or in combination with VEGF inhibitors. Clinical trials have driven the introduction of such novel molecules into the clinics but, at present, no biomarker drives the choice of first-line options, which relies only upon clinical and imaging assessment. Remarkably, clinical and imaging-based evaluations do not consider the huge heterogeneity of HCC and do not allow to realize the potential of personalized treatments. Preclinical research still does not inform the design of clinical trials, even though many animal models mimicking specific subgroups of HCC are available and might provide relevant information. Although animal models directly informing the clinical practice, such as patients-derived xenografts, are not used to help the choice of treatment in advanced HCC, however, the preclinical research can count on a wide range of valuable models. Here we will review some HCC models which might turn informative for specific questions in defined patient subgroups, and we will describe recent preclinical studies for the mechanistic evaluation of immunotherapy-based treatment approaches. To this aim, we will mainly focus on two issues: (i) HCC models informative on NAFLD-NASH HCC and (ii) HCC models helping to elucidate mechanisms underneath immunotherapy. We have chosen these two settings since they represent, respectively, the most rapidly arising cause of chronic liver disease (CLD) and HCC in western countries and the most promising therapeutic option for advanced HCC.

Development and Optimization of a Prognostic Model Associated with Stemness Genes in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide, which is associated with a variety of risk factors. Cancer stem cells are self-renewal cells, which can promote the occurrence and metastasis of tumors and enhance the drug resistance of tumor treatment. This study aimed to develop a stemness score model to assess the prognosis of hepatocellular carcinoma (HCC) patients for the optimization of treatment. The single-cell sequencing data GSE149614 was downloaded from the GEO database. Then, we compared the gene expression of hepatic stem cells and other hepatocytes in tumor samples to screen differentially expressed genes related to stemness. R package "clusterProfiler" was used to explore the potential function of stemness-related genes. We then constructed a prognostic model using LASSO regression analysis based on the TCGA and GSE14520 cohorts. The associations of stemness score with clinical features, drug sensitivity, gene mutation, and tumor immune microenvironment were further explored. R package "rms" was used to construct the nomogram model. A total of 18 stemness-related genes were enrolled to construct the prognosis model. Kaplan-Meier analysis proved the good performance of the stemness score model at predicting overall survival (OS) of HCC patients. The stemness score was closely associated with clinical features, drug sensitivity, and tumor immune microenvironment of HCC. The infiltration level of CD8+ T cells was lower, and tumor-associated macrophages were higher in patients with high-stemness score, indicating an immunosuppressive microenvironment. Our study established an 18 stemness-related gene model that reliably predicts OS in HCC. The findings may help clarify the biological characteristics and progression of HCC and help the future diagnosis and therapy of HCC.

A Gold Nanoparticle Bioconjugate Delivery System for Active Targeted Photodynamic Therapy of Cancer and Cancer Stem Cells

Cancer stem cells (CSCs), also called tumor-initiating cells, are a subpopulation of cancer cells believed to be the leading cause of cancer initiation, growth, metastasis, and recurrence. Presently there are no effective treatments targeted at eliminating CSCs. Hence, an urgent need to develop measures to target CSCs to eliminate potential recurrence and metastasis associated with CSCs. Cancer stem cells have inherent and unique features that differ from other cancer cells, which they leverage to resist conventional therapies. Targeting such features with photodynamic therapy (PDT) could be a promising treatment for drug-resistant cancer stem cells. Photodynamic therapy is a light-mediated non-invasive treatment modality. However, PDT alone is unable to eliminate cancer stem cells effectively, hence the need for a targeted approach. Gold nanoparticle bioconjugates with PDT could be a potential approach for targeted photodynamic therapy of cancer and CSCs. This approach has the potential for enhanced drug delivery, selective and specific attachment to target tumor cells/CSCs, as well as the ability to efficiently generate ROS. This review examines the impact of a smart gold nanoparticle bioconjugate coupled with a photosensitizer (PS) in promoting targeted PDT of cancer and CSC.

The Relevance of Circadian Clocks to Stem Cell Differentiation and Cancer Progression

The molecular mechanism of circadian clocks depends on transcription-translation feedback loops (TTFLs) that have known effects on key cellular processes. However, the distinct role of circadian TTFLs in mammalian stem cells and other less differentiated cells remains poorly understood. Neural stem cells (NSCs) of the brain generate neurons and glia postnatally but also may become cancer stem cells (CSCs), particularly in astrocytomas. Evidence indicates clock TTFL impairment is needed for tumor growth and progression; although, this issue has been examined primarily in more differentiated cancer cells rather than CSCs. Similarly, few studies have examined circadian rhythms in NSCs. After decades of research, it is now well recognized that tumors consist of CSCs and a range of other cancer cells along with noncancerous stromal cells. The circadian properties of these many contributors to tumor properties and treatment outcome are being widely explored. New molecular tools and ones in development will likely enable greater discrimination of important circadian and non-circadian cells within malignancies at multiple stages of cancer progression and following therapy. Here, we focus on adult NSCs and glioma CSCs to address how cells at different stages of differentiation may harbor unique states of the molecular circadian clock influencing differentiation and cell fate.