TP53 R249S mutation in hepatic organoids captures the predisposing cancer risk

Programmed cell death protein 1 in cancer cells

Programmed cell death protein 1 (PD-1) is frequently detected in certain subsets of tumor cells, and our understanding of PD-1 signaling consequences has expanded to include control of tumor growth, stemness and drug resistance. Nonetheless, tumor cell-intrinsic PD-1 has been comparatively underexplored in relation to PD-1 expressed on the surface of immune cells as an immune checkpoint, despite the imperative need to comprehensively elucidate the underlying mechanisms of action for achieving optimal responses in tumor immunotherapy. Here, we review the roles of the regulation and function of tumor-intrinsic PD-1 from its expression to degradation processes. Our primary focus is on unraveling its enigmatic influence on tumorigenesis and progression as proposed by recent findings, while navigating the labyrinthine network of regulatory mechanisms governing its expression and intricate functional interplay. We also discuss how the elucidation of the mechanistic underpinnings of tumor-intrinsic PD-1 expression holds the potential to explain the divergent therapeutic outcomes observed with anti-PD-1-based combination therapies, thereby furnishing indispensable insights crucial for synergistic anti-tumor strategies.

Decoding driver and phenotypic genes in cancer: Unveiling the essence behind the phenomenon

Gray hair, widely regarded as a hallmark of aging. While gray hair is associated with aging, reversing this trait through gene targeting does not alter the fundamental biological processes of aging. Similarly, certain oncogenes (such as CXCR4, MMP-related genes, etc.) can serve as markers of tumor behavior, such as malignancy or prognosis, but targeting these genes alone may not lead to tumor regression. We pioneered the name of this class of genes as "phenotypic genes". Historically, cancer genetics research has focused on tumor driver genes, while genes influencing cancer phenotypes have been relatively overlooked. This review explores the critical distinction between driver genes and phenotypic genes in cancer, using the MAPK and PI3K/AKT/mTOR pathways as key examples. We also discuss current research techniques for identifying driver and phenotypic genes, such as whole-genome sequencing (WGS), RNA sequencing (RNA-seq), RNA interference (RNAi), CRISPR-Cas9, and other genomic screening methods, alongside the concept of synthetic lethality in driver genes. The development of these technologies will help develop personalized treatment strategies and precision medicine based on the characteristics of relevant genes. By addressing the gap in discussions on phenotypic genes, this review significantly contributes to clarifying the roles of driver and phenotypic genes, aiming at advancing the field of targeted cancer therapy.

ZFP-CanPred: Predicting the effect of mutations in zinc-finger proteins in cancers using protein language models

Zinc-finger proteins (ZNFs) constitute the largest family of transcription factors and play crucial roles in various cellular processes. Missense mutations in ZNFs significantly alter protein-DNA interactions, potentially leading to the development of various types of cancers. This study presents ZFP-CanPred, a novel deep learning-based model for predicting cancer-associated driver mutations in ZNFs. The representations derived from protein language models (PLMs) from the structural neighbourhood of mutated sites were utilized to train ZFP-CanPred for differentiating between cancer-causing and neutral mutations. ZFP-CanPred, achieved a superior performance with an accuracy of 0.72, F1-score of 0.79, and area under the Receiver Operating Characteristics (ROC) Curve (AUC) of 0.74, on an independent test set. In a comparative analysis against 11 existing prediction tools using a curated dataset of 331 mutations, ZFP-CanPred demonstrated the highest AU-ROC of 0.74, outperforming both generic and cancer-specific methods. The model's balanced performance across specificity and sensitivity addresses a significant limitation of current methodologies. The source code and other related files are available on GitHub at https://github.com/amitphogat/ZFP-CanPred.git. We envisage that the present study contributes to understand the oncogenic processes and developing targeted therapeutic strategies.

Miniaturization and characterization of patient derived hepatocellular carcinoma tumor organoid cultures for cancer drug discovery applications

Patient derived tumor organoid (PDTO) models retain the structural, morphological, genetic, and clonal heterogeneity of the original tumors. The ability to efficiently generate, expand, and biobank PDTOs has the potential to make the clinical diversity of cancer accessible for personalized medicine assay guided therapeutic drug selection and drug discovery. We describe the miniaturization and growth in 96- and 384-well formats of a single non-tumor liver and two Hepatocellular carcinoma (HCC) organoids derived from cryopreserved PDTO cells and the application of high content imaging (HCI) to characterize the models and enhance drug sensitivity testing. Non-invasive sequentially acquired transmitted light images showed that seeding cryopreserved cells from non-tumoral and HCC PDTOs into 96- or 384-well plates in reduced growth factor Matrigel (rgf-MG) that were fed with growth medium every 3 days supported organoid growth up to 15 days. The number and sizes of organoids increased with longer times in culture. HCC PDTO's had more heterogeneous morphologies than non-tumor organoids with respect to size, shape, and optical density. Organoids cultured in rgf-MG could be stained in situ with HCI reagents without mechanical, chemical or enzymatic disruption of the hydrogel matrices and quantitative data extracted by image analysis. Hoechst and live/dead reagents provided organoid numbers and viability comparisons. HCC PDTO's stained with phalloidin or immuno-stained with α-tubulin antibodies revealed F-actin and microtubule cytoskeleton organization. HCC PDTO's stained with antibodies to signaling pathway proteins and their phosphorylation status allowed comparisons of relative expression levels and inference of pathway activation. Images of HCC PDTO's exposed to ellipticine showed that drugs penetrate Matrigel hydrogels and accumulate in organoid cells. 9-day 384-well HCC organoid cultures exhibited robust and reproducible growth signals suitable for cancer drug testing. Complimenting cell viability readouts with multiple HCI parameters including morphological features and dead cell staining improved the analysis of drug impact and enhanced the value that could be extracted from these more physiologically relevant three-dimensional HCC organoid cultures.

Hepatocellular-Carcinoma-Derived Organoids: Innovation in Cancer Research

Hepatocellular carcinomas (HCCs) are highly heterogeneous malignancies. They are characterized by a peculiar tumor microenvironment and dense vascularization. The importance of signaling between immune cells, endothelial cells, and tumor cells leads to the difficult recapitulation of a reliable in vitro HCC model using the conventional two-dimensional cell cultures. The advent of three-dimensional organoid tumor technology has revolutionized our understanding of the pathogenesis and progression of several malignancies by faithfully replicating the original cancer genomic, epigenomic, and microenvironmental landscape. Organoids more closely mimic the in vivo environment and cell interactions, replicating factors such as the spatial organization of cell surface receptors and gene expression, and will probably become an important tool in the choice of therapies and the evaluation of tumor response to treatments. This review aimed to describe the ongoing and potential applications of organoids as an in vitro model for the study of HCC development, its interaction with the host's immunity, the analysis of drug sensitivity tests, and the current limits in this field.

Organoid as a promising tool for primary liver cancer research: a comprehensive review

Primary liver cancer (PLC) is one of the most common malignant gastrointestinal tumors worldwide. Limited by the shortage of liver transplantation donors and the heterogeneity of tumors, patients with liver cancer lack effective treatment options, which leads to rapid progression and metastasis. Currently, preclinical models of PLC fall short of clinical reality and are limited in their response to disease progression and the effectiveness of drug therapy. Organoids are in vitro three-dimensional cultured preclinical models with a high degree of heterogeneity that preserve the histomorphological and genomic features of primary tumors. Liver cancer organoids have been widely used for drug screening, new target discovery, and precision medicine; thus representing a promising tool to study PLC. Here, we summarize the progress of research on liver cancer organoids and their potential application as disease models. This review provides a comprehensive introduction to this emerging technology and offers new ideas for researchers to explore in the field of precision medicine.

Mutation-Selected Amplification droplet digital PCR: A new single nucleotide variant detection assay for TP53R249S mutant in tumor and plasma samples

The early detection of gene mutations in physiological and pathological processes is a powerful approach to guide decisions in precision medicine. However, detecting low-copy mutant DNA from clinical samples poses a challenge due to the enrichment of wild-type DNA backgrounds. In this study, we devised a novel strategy, named Mutation-Selected Amplification droplet digital PCR (MSA-ddPCR), to quantitatively analyze single nucleotide variants (SNVs) at low variant allele frequencies (VAFs). Using TP53R249S (a hotspot mutation associated with hepatocellular carcinoma) as a model, we optimized the concentration ratio of primers, the annealing temperature and nucleic acid amplification modifiers. Subsequently, we evaluated the linear range and precision of MSA-ddPCR by detecting TP53R249S and TP53wild-type (TP53WT) plasmid DNA, respectively. MSA-ddPCR demonstrated superior ability to discriminate between mutant DNA and wild-type DNA compared to traditional TaqMan-MGB PCR. We further applied MSA-ddPCR to analyze the TP53R249S mutation in 20 plasma samples and 15 formalin-fixed paraffin-embedded (FFPE) tissue samples, and assessed the agreement rates between MSA-ddPCR and amplicon high-throughput sequencing. The results showed that the limit of blanks of MSA-ddPCR are 0.449 copies μL-1 in the FAM channel and 0.452 copies μL-1 in the VIC channel. MSA-ddPCR could accurately quantify VAFs as low as 0.01 %, surpassing existing PCR and next-generation sequencing (NGS) methods. In the detection of clinical samples, a high correlation was found between MSA-ddPCR and amplicon high-throughput sequencing. Additionally, MSA-ddPCR outperformed sequencing methods in terms of detection time and simplicity of data analysis. MSA-ddPCR can be easily implemented into clinical practice and serve as a robust tool for detecting mutant genes due to its high sensitivity and accuracy.

EVA1A reverses lenvatinib resistance in hepatocellular carcinoma through regulating PI3K/AKT/p53 signaling axis

Lenvatinib is a commonly used first-line drug for the treatment of advanced hepatocellular carcinoma (HCC). However, its clinical efficacy is limited due to the drug resistance. EVA1A was a newly identified tumor suppressor, nevertheless, the impact of EVA1A on resistance to lenvatinib treatment in HCC and the potential molecular mechanisms remain unknown. In this study, the expression of EVA1A in HCC lenvatinib-resistant cells is decreased and its low expression was associated with a poor prognosis of HCC. Overexpression of EVA1A reversed lenvatinib resistance in vitro and in vivo, as demonstrated by its ability to promote cell apoptosis and inhibit cell proliferation, invasion, migration, EMT, and tumor growth. Silencing EVA1A in lenvatinib-sensitive parental HCC cells exerted the opposite effect and induced resistance to lenvatinib. Mechanistically, upregulated EVA1A inhibited the PI3K/AKT/MDM2 signaling pathway, resulting in a reduced interaction between MDM2 and p53, thereby stabilizing p53 and enhancing its antitumor activity. In addition, upregulated EVA1A suppressed the PI3K/AKT/mTOR signaling pathway and promoted autophagy, leading to the degradation of mutant p53 and attenuating its oncogenic impact. On the contrary, loss of EVA1A activated the PI3K/AKT/MDM2 signaling pathway and inhibited autophagy, promoting p53 proteasomal degradation and mutant p53 accumulation respectively. These findings establish a crucial role of EVA1A loss in driving lenvatinib resistance involving a mechanism of modulating PI3K/AKT/p53 signaling axis and suggest that upregulating EVA1A is a promising therapeutic strategy for alleviating resistance to lenvatinib, thereby improving the efficacy of HCC treatment.

Recent Advances in Biosensor Technology for Early-Stage Detection of Hepatocellular Carcinoma-Specific Biomarkers: An Overview

Hepatocellular carcinoma is currently the most common malignancy of the liver. It typically occurs due to a series of oncogenic mutations that lead to aberrant cell replication. Most commonly, hepatocellular carcinoma (HCC) occurs as a result of pre-occurring liver diseases, such as hepatitis and cirrhosis. Given its aggressive nature and poor prognosis, the early screening and diagnosis of HCC are crucial. However, due to its plethora of underlying risk factors and pathophysiologies, patient presentation often varies in the early stages, with many patients presenting with few, if any, specific symptoms in the early stages. Conventionally, screening and diagnosis are performed through radiological examination, with diagnosis confirmed by biopsy. Imaging modalities tend to be limited by their requirement of large, expensive equipment; time-consuming operation; and a lack of accurate diagnosis, whereas a biopsy's invasive nature makes it unappealing for repetitive use. Recently, biosensors have gained attention for their potential to detect numerous conditions rapidly, cheaply, accurately, and without complex equipment and training. Through their sensing platforms, they aim to detect various biomarkers, such as nucleic acids, proteins, and even whole cells extracted by a liquid biopsy. Numerous biosensors have been developed that may detect HCC in its early stages. We discuss the recent updates in biosensing technology, highlighting its competitive potential compared to conventional methodology and its prospects as a tool for screening and diagnosis.

Research progress and application of liver organoids for disease modeling and regenerative therapy

The liver is a major metabolic organ of the human body and has a high incidence of diseases. In recent years, the annual incidence of liver disease has increased, seriously endangering human life and health. The study of the occurrence and development mechanism of liver diseases, discovery of new therapeutic targets, and establishment of new methods of medical treatment are major issues related to the national economy and people's livelihood. The development of stable and effective research models is expected to provide new insights into the pathogenesis of liver diseases and the search for more effective treatment options. Organoid technology is a new in vitro culture system, and organoids constructed by human cells can simulate the morphological structure, gene expression, and glucose and lipid metabolism of organs in vivo, providing a new model for related research on liver diseases. This paper reviews the latest research progress on liver organoids from the establishment of cell sources and application of liver organoids and discusses their application potential in the field of liver disease research.

Evolutionary screening of precision oncology biomarkers and its applications in prognostic model construction

Biomarker screening is critical for precision oncology. However, one of the main challenges in precision oncology is that the screened biomarkers often fail to achieve the expected clinical effects and are rarely approved by regulatory authorities. Considering the close association between cancer pathogenesis and the evolutionary events of organisms, we first explored the evolutionary feature underlying clinically approved biomarkers, and two evolutionary features of approved biomarkers (Ohnologs and specific evolutionary stages of genes) were identified. Subsequently, we utilized evolutionary features for screening potential prognostic biomarkers in four common cancers: head and neck squamous cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, and lung squamous cell carcinoma. Finally, we constructed an evolution-strengthened prognostic model (ESPM) for cancers. These models can predict cancer patients' survival time across different cancer cohorts effectively and perform better than conventional models. In summary, our study highlights the application potentials of evolutionary information in precision oncology biomarker screening.

Integrating Network Pharmacology and Experimental Validation to Decipher the Mechanism of Action of Astragalus-Atractylodes Herb Pair in Treating Hepatocellular Carcinoma

Purpose

Traditional Chinese medicine (TCM) therapy is an important means to treat hepatocellular carcinoma (HCC), Astragalus (Latin name: Hedysarum Multijugum Maxim; Chinese name: Huangqi, HQ) and Atractylodes (Latin name: Atractylodes Macrocephala Koidz; Chinese name: Baizhu, BZ) (HQBZ), a classic herb pair, is often used in combination to HCC. However, the main components and potential mechanisms of HQBZ therapy in HCC remain unclear. This study aimed to identify the potential active ingredients and molecular mechanisms of action of HQBZ in HCC treatment.

Methods

The HQBZ-Compound-Target-HCC network and HQBZ-HCC transcriptional regulatory network were constructed to screen the core active compound components and targets of HQBZ therapy for HCC. Molecular docking techniques are used to verify the stability of binding core active compound components to targets. GO and KEGG enrichment analysis were used to explore the signaling pathway of HQBZ in HCC treatment, the mechanism of HQBZ treatment of HCC was verified based on in vivo H22 tumor bearing mice and in vitro cell experiments.

Results

Network pharmacology and molecular docking studies showed that HQBZ treatment of HCC was related to the targeted regulation of IL-6 and STAT3 by the active compound biatractylolide, KEGG pathway enrichment analysis suggest that HQBZ may play a role in the treatment of HCC through IL-6/STAT3 signaling pathway. In vitro experiment results proved that HQBZ could regulate IL-6/STAT3 signaling pathway transduction on CD8+T cells, inhibit CD8+T cell exhaustion and restore the function of exhausted CD8+T cells. In vivo experiment results proved that HQBZ can regulate IL-6/STAT3 signaling pathway transduction in H22 liver cancer model mouse tumor tissue, increased the proportion of tumor infiltrating CD8+T cells.

Conclusion

This study found that HQBZ may play a therapeutic role in HCC by targeting IL-6 and STAT3 through biatractylolide, its mechanism of action is related to regulating IL-6/STAT3 signaling pathway, reversing T cell failure and increasing tumor infiltration CD8+T cells.

A novel single-cell model reveals ferroptosis-associated biomarkers for individualized therapy and prognostic prediction in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a prevalent malignancy with a pressing need for improved therapeutic response and prognosis prediction. This study delves into a novel predictive model related to ferroptosis, a regulated cell death mechanism disrupting metabolic processes.

RESULTS

Single-cell sequencing data analysis identified subpopulations of HCC cells exhibiting activated ferroptosis and distinct gene expression patterns compared to normal tissues. Utilizing the LASSO-Cox algorithm, we constructed a model with 10 single-cell biomarkers associated with ferroptosis, namely STMN1, S100A10, FABP5, CAPG, RGCC, ENO1, ANXA5, UTRN, CXCR3, and ITM2A. Comprehensive analyses using these biomarkers revealed variations in immune infiltration, tumor mutation burden, drug sensitivity, and biological functional profiles between risk groups. Specific associations were established between particular immune cell subtypes and certain gene expression patterns. Treatment response analyses indicated potential benefits from anti-tumor immune therapy for the low-risk group and chemotherapy advantages for the high-risk group.

CONCLUSIONS

The integration of this single-cell level model with clinicopathological features enabled accurate overall survival prediction and effective risk stratification in HCC patients. Our findings illuminate the potential of ferroptosis-related genes in tailoring therapy and prognosis prediction for HCC, offering novel insights into the intricate interplay among ferroptosis, immune response, and HCC progression.

Exploring tumor organoids for cancer treatment

As a life-threatening chronic disease, cancer is characterized by tumor heterogeneity. This heterogeneity is associated with factors that lead to treatment failure and poor prognosis, including drug resistance, relapse, and metastasis. Therefore, precision medicine urgently needs personalized tumor models that accurately reflect the tumor heterogeneity. Currently, tumor organoid technologies are used to generate in vitro 3D tissues, which have been shown to precisely recapitulate structure, tumor microenvironment, expression profiles, functions, molecular signatures, and genomic alterations in primary tumors. Tumor organoid models are important for identifying potential therapeutic targets, characterizing the effects of anticancer drugs, and exploring novel diagnostic and therapeutic options. In this review, we describe how tumor organoids can be cultured and summarize how researchers can use them as an excellent tool for exploring cancer therapies. In addition, we discuss tumor organoids that have been applied in cancer therapy research and highlight the potential of tumor organoids to guide preclinical research.

Exploring the molecular mechanism of Artemisia rupestris L. for the treatment of hepatocellular carcinoma via PI3K/AKT pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Hepatocellular carcinoma (HCC) is a common gastrointestinal malignancy in China. Most tumors develop from chronic inflammation. Artemisia rupestris L. (ARL) has been found to have a significant effect on viral influenza and hepatitis, but the mechanism of action of ARL against liver cancer is unclear.

AIM OF THE STUDY

The study objective was to explore the mechanism of action of ARL for the treatment of hepatocellular carcinoma (HCC) by ethanol extract and in vitro experimental design.

MATERIALS AND METHODS

Interactions between ARL and cellular target proteins against HCC were analyzed through network pharmacology and network topology with the utilization of the DAVID database. The rate of HepG2 cells' growth inhibition was assessed using the MTT assay in vitro cellular assay; hoechst33342 detects apoptosis of cells; the ability of HepG2 cells to migrate and invade was assessed using the transwell assay and the cell scratch experiment; and the levels of protein expression in HepG2 cells were assessed using the western blot assay.

RESULTS

Network pharmacology prediction results demonstrated that 22 active ingredients were tested, 176 possible action targets were discovered, and the PI3K/Akt signaling pathway was found to be the most pertinent action pathway for the treatment of hepatocellular carcinoma. In vitro results showed that it can effectively restrict HepG2 cell proliferation, apoptosis, migration, and invasion as well as the regulation of protein expressions.

CONCLUSION

Conclusively, Quercetin, Linarin, and Kaempferol were found most essential active ingredients from ARL that regulate the antitumor effects against HCC through the PI3K/Akt signaling pathway. The study provides a fundamental basis for further comprehensive evaluation of ARL to treat tumor diseases in general and its therapeutic potential against hepatocellular carcinoma in particular.

CHEK2 knockout is a therapeutic target for TP53-mutated hepatocellular carcinoma

Currently, there is still a lack of novel and effective drug targets to improve the prognosis of hepatocellular carcinoma (HCC). Additionally, the role of CHEK2 in HCC has not been reported yet. The eQTLgen database and two HCC Genome-Wide Association Study (GWAS) datasets (ieu-b-4953, ICD10 C22.0) were used to find the drug target: CHEK2. Next, Colony, Edu, β-gal, and cell cycle analysis were facilitated to evaluate the role of CHEK2 knockout in HCC. In addition, Nultin-3 was added to evaluate the apoptosis of TP53-mutated HCC cells with CHEK2 knockout. Furthermore, MitoSox, electron microscopy, mitochondrial ATP, and NADH+/NADH levels were assessed in the CHEK2 knockout HCC cells with or without Metformin. Finally, cell-derived tumor xenograft was used to evaluate the role of CHEK2 knockout in vivo. We initially identified a potential drug target, CHEK2, through GWAS data analysis. Furthermore, we observed a significant upregulation of CHEK2 expression in HCC, which was found to be correlated with a poor prognosis. Subsequently, the results indicated that knocking out CHEK2 selectively affects the proliferation, cell cycle, senescence, and apoptosis of TP53-mutant HCC cells. Additionally, the introduction of Nultin-3 further intensified the functional impact on TP53-mutant cells. Then ClusterProfiler results showed high CHEK2 and TP53 mutation group was positively enriched in the mitochondrial ATP pathway. Then we used MitoSox, electron microscopy, mitochondrial ATP, and NADH + /NADH assay and found knockout of CHECK could induce the ATP pathway to inhibit the growth of HCC. Our research introduces a novel drug target for TP53-mutant HCC cells via mitochondrial ATP, addressing the limitation of Nultin-3 as a standalone treatment that does not induce tumor cell death.

Construction of tumor organoids and their application to cancer research and therapy

Cancer remains a severe public health burden worldwide. One of the challenges hampering effective cancer therapy is that the existing cancer models hardly recapitulate the tumor microenvironment of human patients. Over the past decade, tumor organoids have emerged as an in vitro 3D tumor model to mimic the pathophysiological characteristics of parental tumors. Various techniques have been developed to construct tumor organoids, such as matrix-based methods, hanging drop, spinner or rotating flask, nonadhesive surface, organ-on-a-chip, 3D bioprinting, and genetic engineering. This review elaborated on cell components and fabrication methods for establishing tumor organoid models. Furthermore, we discussed the application of tumor organoids to cancer modeling, basic cancer research, and anticancer therapy. Finally, we discussed current limitations and future directions in employing tumor organoids for more extensive applications.

Advancements and application prospects of three-dimensional models for primary liver cancer: a comprehensive review

Primary liver cancer (PLC) is one of the most commonly diagnosed cancers worldwide and a leading cause of cancer-related deaths. However, traditional liver cancer models fail to replicate tumor heterogeneity and the tumor microenvironment, limiting the study and personalized treatment of liver cancer. To overcome these limitations, scientists have introduced three-dimensional (3D) culture models as an emerging research tool. These 3D models, utilizing biofabrication technologies such as 3D bioprinting and microfluidics, enable more accurate simulation of the in vivo tumor microenvironment, replicating cell morphology, tissue stiffness, and cell-cell interactions. Compared to traditional two-dimensional (2D) models, 3D culture models better mimic tumor heterogeneity, revealing differential sensitivity of tumor cell subpopulations to targeted therapies or immunotherapies. Additionally, these models can be used to assess the efficacy of potential treatments, providing guidance for personalized therapy. 3D liver cancer models hold significant value in tumor biology, understanding the mechanisms of disease progression, and drug screening. Researchers can gain deeper insights into the impact of the tumor microenvironment on tumor cells and their interactions with the surrounding milieu. Furthermore, these models allow for the evaluation of treatment responses, offering more accurate guidance for clinical interventions. In summary, 3D models provide a realistic and reliable tool for advancing PLC research. By simulating tumor heterogeneity and the microenvironment, these models contribute to a better understanding of the disease mechanisms and offer new strategies for personalized treatment. Therefore, 3D models hold promising prospects for future PLC research.

TP53/mTORC1-mediated bidirectional regulation of PD-L1 modulates immune evasion in hepatocellular carcinoma

BACKGROUND

Immunotherapy has facilitated great breakthroughs in the treatment of hepatocellular carcinoma (HCC). However, the efficacy and response rate of immunotherapy are limited and vary among different patients with HCC. TP53 mutation substantially affects the expression of immune checkpoint molecules in multiple cancers. However, the regulatory relationship between programmed death ligand 1 (PD-L1) and TP53 is poorly studied in HCC. We aimed to elucidate the regulatory mechanism of PD-L1 in HCC with different TP53 statuses and to assess its role in modulating immune evasion in HCC.

METHODS

HCC mouse models and cell lines with different TP53 statuses were constructed. PD-L1 levels were detected by PCR, western blotting and flow cytometry. RNA-seqencing, immunoprecipitation, chromatin immunoprecipitation and transmission electron microscopy were used to elucidate the regulatory mechanism in HCC with different TP53 status. HCC mouse models and patient with HCC samples were analyzed to demonstrate the preclinical and clinical significance of the findings.

RESULTS

We report that loss of p53 promoted PD-L1 expression and reduced CD8+ T-cell infiltration in patient with HCC samples and mouse models. Mammalian target of rapamycin (mTOR) pathway was activated in p53-loss-of-function HCC or after knocking down TP53. The transcription factor E2F1 was found to bind to the p53 protein in TP53 wild-type HCC cells, and inhibiting mammalian target of rapamycin complex 1 (mTORC1) disrupted this binding and enhanced E2F1 translocation to the nucleus, where it bound to the PD-L1 promoter and transcriptionally upregulated PD-L1. In p53-loss-of-function HCC cells, autophagosomes were activated after mTORC1 suppression, promoting the degradation of PD-L1 protein. The combination of mTOR inhibitor and anti-PD-L1 antibody enhanced CD8+ T-cell infiltration and tumor suppression in TP53 wild-type HCC mouse models, but no benefit was observed in p53-loss-of-function HCC mouse models. In patients with TP53 wild-type HCC, PD-L1 levels were significantly higher in the high E2F1 group than in the low E2F1 group, and the low E2F1 level group had significantly superior survival.

CONCLUSION

We revealed the bidirectional regulatory mechanism of PD-L1 mediated by TP53/mTORC1 in HCC. The combination of mTOR inhibitor and anti-PD-L1 antibody could be a novel precise immunotherapy scheme for TP53 wild-type HCC.

Heterogeneity characterization of hepatocellular carcinoma based on the sensitivity to 5-fluorouracil and development of a prognostic regression model

Background: 5-Fluorouracil (5-FU) is a widely used chemotherapeutic drug in clinical cancer treatment, including hepatocellular carcinoma (HCC). A correct understanding of the mechanisms leading to a low or lack of sensitivity of HCC to 5-FU-based treatment is a key element in the current personalized medical treatment. Methods: Weighted gene co-expression network analysis (WGCNA) was used to analyze the expression profiles of the cancer cell line from GDSC2 to identify 5-FU-related modules and hub genes. According to hub genes, HCC was classified and the machine learning model was developed by ConsensusClusterPlus and five different machine learning algorithms. Furthermore, we performed quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis on the genes in our model. Results: A total of 19 modules of the cancer cell line were divided by WGCNA, and the most negative correlation with 5-FU was the midnight blue module, from which 45 hub genes were identified. HCC was divided into three subgroups (C1, C2, and C3) with significant overall survival (OS) differences. OS of C1 was the shortest, which was characterized by a high clinical grade and later T stage and stage. OS of C3 was the longest. OS of C2 was between the two subtypes, and its immune infiltration was the lowest. Five out of 45 hub genes, namely, TOMM40L, SNRPA, ILF3, CPSF6, and NUP205, were filtered to develop a risk regression model as an independent prognostic indicator for HCC. The qRT-PCR results showed that TOMM40L, SNRPA, ILF3, CPSF6, and NUP205 were remarkably highly expressed in hepatocellular carcinoma. Conclusion: The HCC classification based on the sensitivity to 5-FU was in line with the prognostic differences observed in HCC and most of the genomic variation, immune infiltration, and heterogeneity of pathological pathways. The regression model related to 5-FU sensitivity may be of significance in individualized prognostic monitoring of HCC.

Micro-Engineered Organoid-on-a-Chip Based on Mesenchymal Stromal Cells to Predict Immunotherapy Responses of HCC Patients

Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide. Patient-derived organoid (PDO) has great potential in precision oncology, but low success rate, time-consuming culture, and lack of tumor microenvironment (TME) limit its application. Mesenchymal stromal cells (MSC) accumulate in primary site to support tumor growth and recruit immune cells to form TME. Here, MSC and peripheral blood mononuclear cells (PBMC) coculture is used to construct HCC organoid-on-a-chip mimicking original TME and provide a high-throughput drug-screening platform to predict outcomes of anti-HCC immunotherapies. HCC-PDOs and PBMC are co-cultured with MSC and Cancer-associated fibroblasts (CAF). MSC increases success rate of biopsy-derived PDO culture, accelerates PDO growth, and promotes monocyte survival and differentiation into tumor-associated macrophages. A multi-layer microfluidic chip is designed to achieve high-throughput co-culture for drug screening. Compared to conventional PDOs, MSC-PDO-PBMC and CAF-PDO-PBMC models show comparable responses to chemotherapeutic or targeted anti-tumor drugs but more precise prediction potential in assessing patients' responses to anti-PD-L1 drugs. Moreover, this microfluidic platform shortens PDO growth time and improves dimensional uniformity of organoids. In conclusion, the study successfully constructs microengineered organoid-on-a-chip to mimic TME for high-throughput drug screening, providing novel platform to predict immunotherapy response of HCC patients.

Liver organoids: a promising three-dimensional model for insights and innovations in tumor progression and precision medicine of liver cancer

Primary liver cancer (PLC) is one type of cancer with high incidence rate and high mortality rate in the worldwide. Systemic therapy is the major treatment for PLC, including surgical resection, immunotherapy and targeted therapy. However, mainly due to the heterogeneity of tumors, responses to the above drug therapy differ from person to person, indicating the urgent needs for personalized treatment for PLC. Organoids are 3D models derived from adult liver tissues or pluripotent stem cells. Based on the ability to recapitulate the genetic and functional features of in vivo tissues, organoids have assisted biomedical research to make tremendous progress in understanding disease origin, progression and treatment strategies since their invention and application. In liver cancer research, liver organoids contribute greatly to reflecting the heterogeneity of liver cancer and restoring tumor microenvironment (TME) by co-organizing tumor vasculature and stromal components in vitro. Therefore, they provide a promising platform for further investigation into the biology of liver cancer, drug screening and precision medicine for PLC. In this review, we discuss the recent advances of liver organoids in liver cancer, in terms of generation methods, application in precision medicine and TME modeling.