Integrative proteogenomic characterization of hepatocellular carcinoma across etiologies and stages

Genomic and immune landscape in hepatocellular carcinoma: Implications for personalized therapeutics

Hepatocellular carcinoma (HCC) is a globally prevalent malignancy, marked by genetic heterogeneity and intricate tumor microenvironment interactions. In this study, we undertook a detailed single-cell analysis of six active HCC patients, highlighting strong correlations between gene expression levels and cellular characteristics. UMAP clustering revealed seven distinct cell categories with associated gene expressions. A divergence was observed in tumor cells into high and low cuproptosis groups, each associated with distinct pathways: oxidative stress for the high cuproptosis group and inflammatory and angiogenesis pathways for the low group. CellChat analysis on the TCGA-LIHC cohort displayed unique intercellular interactions among hepatocytes, T cells, and other cells, with pathways like COLLAGEN and VEGF being pivotal. Functional enrichment analyses exposed pathways enriched between cuproptosis groups, with KEGG emphasizing diseases like Parkinson's. COX survival analysis identified key prognostic genes, revealing distinct survival rates between risk groups in TCGA and GSE14520 cohorts. Mutation data highlighted missense mutations, with TTN, TP53, and CTNNB1 being the most mutated in HCC. Immune infiltration analysis via CIBERSORTx indicated differences between risk groups in NK cells, neutrophils, and other cells. Our drug sensitivity investigation showed significant correlations between model genes and drug responsiveness, emphasizing the importance of patient risk stratification for therapeutic approaches. Further, ATP6V1G1 was recognized in its role in apoptosis and migration in HCC cells. In conclusion, our findings illuminate the complexities of HCC progression, potential predictive genetic markers for drug response, and the pivotal role of ATP6V1G1, suggesting avenues for targeted therapeutic strategies in HCC.

Precision treatment in advanced hepatocellular carcinoma

The past decade has witnessed significant advances in the systemic treatment of advanced hepatocellular carcinoma (HCC). Nevertheless, the newly developed treatment strategies have not achieved universal success and HCC patients frequently exhibit therapeutic resistance to these therapies. Precision treatment represents a paradigm shift in cancer treatment in recent years. This approach utilizes the unique molecular characteristics of individual patient to personalize treatment modalities, aiming to maximize therapeutic efficacy while minimizing side effects. Although precision treatment has shown significant success in multiple cancer types, its application in HCC remains in its infancy. In this review, we discuss key aspects of precision treatment in HCC, including therapeutic biomarkers, molecular classifications, and the heterogeneity of the tumor microenvironment. We also propose future directions, ranging from revolutionizing current treatment methodologies to personalizing therapy through functional assays, which will accelerate the next phase of advancements in this area.

WNT/β-catenin regulatory roles on PD-(L)1 and immunotherapy responses

Dysregulation of WNT/β-catenin is a hallmark of many cancer types and a key mediator of metastasis in solid tumors. Overactive β-catenin signaling hampers dendritic cell (DC) recruitment, promotes CD8+ T cell exclusion and increases the population of regulatory T cells (Tregs). The activity of WNT/β-catenin also induces the expression of programmed death-ligand 1 (PD-L1) on tumor cells and promotes programmed death-1 (PD-1) upregulation. Increased activity of WNT/β-catenin signaling after anti-PD-1 therapy is indicative of a possible implication of this signaling in bypassing immune checkpoint inhibitor (ICI) therapy. This review is aimed at giving a comprehensive overview of the WNT/β-catenin regulatory roles on PD-1/PD-L1 axis in tumor immune ecosystem, discussing about key mechanistic events contributed to the WNT/β-catenin-mediated bypass of ICI therapy, and representing inhibitors of this signaling as promising combinatory regimen to go with anti-PD-(L)1 in cancer immunotherapy. Ideas presented in this review imply the synergistic efficacy of such combination therapy in rendering durable anti-tumor immunity.

Tumor suppressor CLCA1 inhibits angiogenesis via TGFB1/SMAD/VEGF cascade and sensitizes hepatocellular carcinoma cells to Sorafenib

BACKGROUND

Hepatocellular carcinoma (HCC) is a highly vascularized tumor with a poor prognosis. Novel vascular-related therapeutic targets and prognostic markers remain urgently needed.

AIMS

To investigate the role and mechanism of CLCA1 in hepatocellular carcinoma.

METHODS

Immunofluorescence, Co-immunoprecipitation and rescue experiment were used to determine the specific mechanisms of CLCA1. Chemosensitivity assay was used to measure the impact of CLCA1 on Sorafenib.

RESULTS

CLCA1 was dramatically downregulated in hepatocellular carcinoma cell lines and tissues. Ectopic expression of CLCA1 induced cell apoptosis and G0/G1 phase arrest while suppressed cell growth, inhibited migration and invasion, reversal of epithelial mesenchymal transition in vitro and reduced xenograft tumor growth in vivo. Mechanistically, CLCA1 could co-localize and interact with TGFB1, thereby suppressing HCC angiogenesis through the TGFB1/SMAD/VEGF signaling cascade in vitro and in vivo. Moreover, CLCA1 also enhanced the sensitivity of HCC cells to the first-line targeted therapy, Sorafenib.

CONCLUSION

CLCA1 sensitizes HCC cells to Sorafenib and suppresses hepatocellular carcinoma angiogenesis through downregulating TGFB1 signaling cascade. This newly identified CLCA1 signaling pathway may help guide the anti-angiogenesis therapies for hepatocellular carcinoma. We also support the possibility of CLCA1 being a prognostic biomarker for hepatocellular carcinoma.

Integrated omics landscape of hepatocellular carcinoma suggests proteomic subtypes for precision therapy

Patients with hepatocellular carcinoma (HCC) at the same clinical stage can have extremely different prognoses, and molecular subtyping provides an opportunity for individualized precision treatment. In this study, genomic, transcriptomic, proteomic, and phosphoproteomic profiling of primary tumor tissues and paired para-tumor tissues from HCC patients (N = 160) are integrated. Proteomic profiling identifies three HCC subtypes with different clinical prognosis, which are validated in three publicly available external validation sets. A simplified panel of nine proteins associated with metabolic reprogramming is further identified as a potential subtype-specific biomarker for clinical application. Multi-omics analysis further reveals that three proteomic subtypes have significant differences in genetic alterations, microenvironment dysregulation, kinase-substrate regulatory networks, and therapeutic responses. Patient-derived cell-based drug tests (N = 26) show personalized responses for sorafenib in three proteomic subtypes, which can be predicted by a machine-learning response prediction model. Overall, this study provides a valuable resource for better understanding of HCC subtypes for precision clinical therapy.

MicroRNA-204-5p Inhibits Hepatocellular Carcinoma by Targeting the Regulator of G Protein Signaling 20

Although the oncogenic roles of regulator of G protein signaling 20 (RGS20) and its upstream microRNAs (miRNAs) have been reported, their involvement in hepatocellular carcinoma (HCC) remains unexplored. We utilized the starBase, miRDB, TargetScan, and mirDIP databases, along with a dual-luciferase reporter assay and cDNA chip analysis to identify miRNAs targeting RGS20. miR-204-5p was selected for further experiments to confirm its direct targeting and downregulation of the RGS20 expression. To study the miR-204-5p/RGS20 axis in HCC, RGS20 and miR-204-5p were increased in PLC/PRF/5/Hep3B cells, and the viability, hyperplasia, apoptosis, cell cycle, and invasion/migration of the cells were assessed. RGS20 exhibited optimism, while miR-204-5p exhibited pessimism in tumors. miR-204-5p directly targeted RGS20 and downregulated its expression, whereas high RGS20 expression indicated a poor prognosis. Transfection of miR-204-5p inhibited the hyperplasia, migration, and invasion of HCC cells, but promoted apoptosis and influenced the levels of cyclin-dependent kinase 2 (CDK2), cyclin E1, B-cell lymphoma-2 (Bcl-2), Bax, and cleaved caspase-3/8. These effects were reversed by overexpression of RGS20. We recognized miR-204-5p as an upstream regulator targeting RGS20, thereby inhibiting HCC progression by downregulating RGS20 expression. RGS20 may prove to be a potential target for HCC treatment, and miR-204-5p might seem like to be a potential miRNA in gene therapy.

A precise prognostic signature in CTNNB1-mutant hepatocellular carcinoma: Prognosis prediction and precision treatment exploration

Background

CTNNB1 mutates in most hepatocellular carcinoma (HCC) which is the most familiar form of liver cancer with high heterogeneity. It is critical to create a specific prognostication methodology and to investigate additional treatment options for CTNNB1-mutant HCCs.

Methods

A total of 926 samples in five independent cohorts were enrolled in this study, including 127 CTNNB1-mutant samples and 75 estimated CTNNB1-mutant samples. The prognostic signature was constructed by LASSO-Cox regression and evaluated by bioinformatics analyses. The selection of possible drug targets and agents was produced based on the expression profiles and drug sensitivity data of cancer cell lines in two databases.

Results

A prognostic signature based on 15 genes categorized the CTNNB1-mutant HCCs into two groups with different risks. Compared to low-risk patients, high-risk patients had significantly inferior prognoses. ROC curve and multivariate analysis also indicated the superior performance of our signature on the prognosis estimation, particularly in CTNNB1-mutant HCCs. Besides, the nomogram was constructed according to the prognostic signature with excellent predictive performance confirmed by the calibration curve. Subsequently, we suggested that AT-7519 and PHA-793887 might be potential drug agents for high-risk patients.

Conclusion

We established a 15-gene prognostic model, particularly in HCCs with CTNNB1 mutations with good predictive efficiency. Besides, we explored the potential drug targets and agents for patients with high risk. Our findings offered a fresh idea for personalized prognosis management in HCCs with CTNNB1 mutations and threw new insight for precise treatment in HCCs as well.

Decoding the role of aberrant RNA alternative splicing in hepatocellular carcinoma: a comprehensive review

During eukaryotic gene expression, alternative splicing of messenger RNA precursors is critical in increasing protein diversity and regulatory complexity. Multiple transcript isoforms could be produced by alternative splicing from a single gene; they could eventually be translated into protein isoforms with deleted, added, or altered domains or produce transcripts containing premature termination codons that could be targeted by nonsense-mediated mRNA decay. Alternative splicing can generate proteins with similar, different, or even opposite functions. Increasingly strong evidence indicates that abnormal RNA splicing is a prevalent and crucial occurrence in cellular differentiation, tissue advancement, and the development and progression of cancer. Aberrant alternative splicing could affect cancer cell activities such as growth, apoptosis, invasiveness, drug resistance, angiogenesis, and metabolism. This systematic review provides a comprehensive overview of the impact of abnormal RNA alternative splicing on the development and progression of hepatocellular carcinoma.

Arginine reprograms metabolism in liver cancer via RBM39

Metabolic reprogramming is a hallmark of cancer. However, mechanisms underlying metabolic reprogramming and how altered metabolism in turn enhances tumorigenicity are poorly understood. Here, we report that arginine levels are elevated in murine and patient hepatocellular carcinoma (HCC), despite reduced expression of arginine synthesis genes. Tumor cells accumulate high levels of arginine due to increased uptake and reduced arginine-to-polyamine conversion. Importantly, the high levels of arginine promote tumor formation via further metabolic reprogramming, including changes in glucose, amino acid, nucleotide, and fatty acid metabolism. Mechanistically, arginine binds RNA-binding motif protein 39 (RBM39) to control expression of metabolic genes. RBM39-mediated upregulation of asparagine synthesis leads to enhanced arginine uptake, creating a positive feedback loop to sustain high arginine levels and oncogenic metabolism. Thus, arginine is a second messenger-like molecule that reprograms metabolism to promote tumor growth.

Transarterial chemoembolization plus camrelizumab is an effective and tolerable bridging therapy for patients with intermediate‑stage hepatocellular carcinoma: A pilot study

Transarterial chemoembolization (TACE) has been reported to synergize with camrelizumab in the treatment of hepatocellular carcinoma (HCC). The present study aimed to explore the potential of TACE and camrelizumab as a bridging therapy prior to surgery for patients with HCC. For this purpose, 11 patients with HCC with intermediate stage disease [classified by China Liver Cancer (CNLC) staging] who received TACE combined with camrelizumab as a bridging therapy prior to surgery were enrolled in this study. The treatment response was evaluated at 2 weeks following TACE therapy and following camrelizumab treatment. The relapse-free survival (RFS) and overall survival (OS) of the patients were calculated. The objective response and disease control rates were 72.7 and 100.0% following TACE treatment, and were 100.0 and 100.0% following camrelizumab treatment, respectively. The α-fetoprotein levels gradually decreased following TACE, camrelizumab treatment and surgical resection (all P<0.05). Of note, the CNLC stage decreased following treatment (P=0.007) and the downstaging success rate was 63.6%. In terms of survival profiles, the mean RFS (95% CI) was 14.1 (11.7-16.5) months and the 1-year RFS rate was 77.9±14.1%. Furthermore, the mean OS (95% CI) was 15.0 (13.2-16.8) months and the 1-year OS rate was 80.0±17.9%. Successful downstaging was associated with RFS (P=0.041), but not OS (P=0.221). With regard to safety, 6 (54.5%) patients experienced reactive cutaneous capillary endothelial proliferation, 5 (45.5%) patients reported pain and 4 (36.4%) patients had a fever. On the whole, the present study demonstrated that TACE plus camrelizumab may be an effective and safe strategy that has potential for use as a bridging strategy prior to surgery in patients with intermediate-stage HCC.

PPIH gene regulation system and its prognostic significance in hepatocellular carcinoma: a comprehensive analysis

BACKGROUND

Peptidyl-prolyl isomerase H (PPIH) is a member of the cyclophilin protein family, which functions as a molecular chaperone and is involved in the splicing of pre-mRNA. According to reports, the malignant progression of HCC related to hepatitis B virus (HBV) is tightly associated with RNA-binding proteins. Nevertheless, there is no research on PPIH expression or its function in the occurrence and progression of HCC.

RESULTS

We are the first to reveal that the mRNA and protein levels of Ppih are substantially overexpressed in HCC, as the outcomes show. A significant correlation existed between enriched expression of Ppih within HCC and more advanced, poorly differentiated, and TP53-mutated tumors.

CONCLUSION

These findings, which suggest that Ppih may serve as a predictive biomarker for people with HCC, serve as a starting point for further investigation into the function of Ppih in the progression of carcinogenesis.

METHODS

Accordingly, we utilized clinical samples and bioinformatics analysis to assess Ppih's mRNA, protein expression, and gene regulatory system in HCC. Additionally, Wilcoxon signed-rank testing and logistic regression were utilized to inspect the association between clinicopathological factors and Ppih. Clinical pathological traits linked to overall survival (OS) among HCC patients were examined via TCGA data via Cox regression and the Kaplan-Meier approach. Additionally, via TCGA data collection, gene set enrichment assessment was also conducted.

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

Quantitative phosphoproteomics reveals molecular pathway network alterations in human early-stage primary hepatic carcinomas: potential for 3P medical approach

Objective

Hepatic carcinoma is one of the most common types of malignant tumors in the digestive system, and its biological characteristics determine its high rate of metastasis and recurrence after radical resection, leading to a poor prognosis for patients. Increasing evidence demonstrates that phosphoproteins and phosphorylation-mediated molecular pathways influence the occurrence and development of hepatic carcinoma. It is urgent need to develop early-stage biomarkers for improving diagnosis, therapy, medical service, and prognostic assessment. We hypothesize that phosphoproteome and phosphorylation-mediated signaling pathway networks significantly differ in human early-stage primary hepatic carcinomas relative to control liver tissues, which will identify the key differentially phosphorylated proteins and phosphorylation-mediated signaling pathway network alterations in human early-stage primary hepatic carcinoma to innovate predictive diagnosis, prognostic assessment, and personalized medical services and progress beyond the state of the art in the framework of predictive, preventive, and personalized medicine (PPPM).

Methods

Tandem mass tag (TMT)-based quantitative proteomics coupled with TiO2 enrichment of phosphopeptides was used to identify phosphorylation profiling, and bioinformatics was used to analyze the pathways and biological functions of phosphorylation profiling between early-stage hepatic carcinoma tissues and tumor-adjacent normal control tissues. Furthermore, the integrative analysis with transcriptomic data from TCGA database obtained differently expressed genes (DEGs) corresponding to differentially phosphorylated proteins (DPPs) and overall survival (OS)-related DPPs.

Results

A total of 1326 phosphopeptides derived from 858 DPPs in human early-stage primary hepatic carcinoma were identified. KEGG pathway network analysis of 858 DPPs revealed 33 statistically significant signaling pathways, including spliceosome, glycolysis/gluconeogenesis, B-cell receptor signaling pathway, HIF-1 signaling pathway, and fatty acid degradation. Gene Ontology (GO) analysis of 858 DPPs revealed that protein phosphorylation was involved in 57 biological processes, 40 cellular components, and 37 molecular functions. Protein-protein interaction (PPI) network constructed multiple high-combined scores and co-expressed DPPs. Integrative analysis of transcriptomic data and DPP data identified 105 overlapped molecules (DPPs; DEGs) between hepatic carcinoma tissues and control tissues and 125 OS-related DPPs. Overlapping Venn plots showed 14 common molecules among datasets of DPPs, DEGs, and OS-related DDPs, including FTCD, NDRG2, CCT2, PECR, SLC23A2, PNPLA7, ANLN, HNRNPM, HJURP, MCM2, STMN1, TCOF1, TOP2A, and SSRP1. The drug sensitivities of OS-related DPPs were identified, including LMOD1, CAV2, UBE2E2, RAPH1, ANXA5, HDLBP, CUEDC1, APBB1IP, VCL, SRSF10, SLC23A2, EPB41L2, ESR1, PLEKHA4, SAFB2, SMARCAD1, VCAN, PSD4, RDH16, NOP56, MEF2C, BAIAP2L2, NAGS, SRSF2, FHOD3, and STMN1.

Conclusions

Identification and annotation of phosphoproteomes and phosphorylation-mediated signaling pathways in human early-stage primary hepatic carcinoma tissues provided new directions for tumor prevention and treatment, which (i) helps to enrich phosphorylation functional research and develop new biomarkers; (ii) enriches phosphorylation-mediated signaling pathways to gain a deeper understanding of the underlying mechanisms of early-stage primary hepatic carcinoma; and (iii) develops anti-tumor drugs that facilitate targeted phosphorylated sites. We recommend quantitative phosphoproteomics in early-stage primary hepatic carcinoma, which offers great promise for in-depth insight into the molecular mechanism of early-stage primary hepatic carcinoma, the discovery of effective therapeutic targets/drugs, and the construction of reliable phosphorylation-related biomarkers for patient stratification, predictive diagnosis, prognostic assessment, and personalized medical services in the framework of PPPM.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00335-3.

Impact of tumor suppressor genes inactivation on the multidrug resistance phenotype of hepatocellular carcinoma cells

The response of advanced hepatocellular carcinoma (HCC) to pharmacological treatments is unsatisfactory and heterogeneous. Inactivation of tumor suppressor genes (TSGs) by genetic and epigenetic events is frequent in HCC. This study aimed at investigating the impact of frequently altered TSGs on HCC chemoresistance. TSG alterations were screened by in silico analysis of TCGA-LIHC database, and their relationship with survival was investigated. These TSGs were silenced in HCC-derived cell lines using CRISPR/Cas9. TLDA was used to determine the expression of a panel of 94 genes involved in the resistome. Drug sensitivity, cell proliferation, colony formation and cell migration were assessed. The in silico study revealed the down-regulation of frequently inactivated TSGs in HCC (ARID1A, PTEN, CDH1, and the target of p53, CDKN1A). The presence of TP53 and ARID1A variants and the low expression of PTEN and CDH1 correlated with a worse prognosis of HCC patients. In PLC/PRF/5 cells, ARID1A knockout (ARID1AKO) induced increased sensitivity to cisplatin, doxorubicin, and cabozantinib, without affecting other characteristics of malignancy. PTENKO and E-CadKO showed minimal changes in malignancy, resistome, and drug response. In p53KO HepG2 cells, enhanced malignant properties and higher resistance to cisplatin, doxorubicin, sorafenib, and regorafenib were found. This was associated with changes in the resistome. In conclusion, the altered expression and function of several TSGs are involved in the heterogeneity of HCC chemoresistance and other features of malignancy, contributing to the poor prognosis of these patients. Individual identification of pharmacological vulnerabilities is required to select the most appropriate treatment for each patient.

A gene mutation-based risk model for prognostic prediction in liver metastases

BACKGROUND

Liver metastasis is the major challenge in the treatment for malignant tumors. Genomic profiling is increasingly used in the diagnosis, treatment and prediction of prognosis in malignancies. In this study, we constructed a gene mutation-based risk model to predict the survival of liver metastases.

METHOD

We identified the gene mutations associated with survival and constructed the risk model in the training cohort including 800 patients with liver metastases from Memorial Sloan-Kettering Cancer Center (MSKCC) dataset. Other 794 patients with liver metastases were collected from 4 cohorts for validation. Furthermore, the analyses of tumor microenvironment (TME) and somatic mutations were performed on 51 patients with breast cancer liver metastases (BCLM) who had both somatic mutation data and RNA-sequencing data.

RESULTS

A gene mutation-based risk model involved 10 genes was constructed to divide patients with liver metastases into the high- and low-risk groups. Patients in the low-risk group had a longer survival time compared to those in the high-risk group, which was observed in both training and validation cohorts. The analyses of TME in BCLM showed that the low-risk group exhibited more immune infiltration than the high-risk group. Furthermore, the mutation signatures of the high-risk group were completely different from those of the low-risk group in patients with BCLM.

CONCLUSIONS

The gene mutation-based risk model constructed in our study exhibited the reliable ability of predicting the prognosis in liver metastases. The difference of TME and somatic mutations among BCLM patients with different risk score can guide the further research and treatment decisions for liver metastases.

DNA methylation-mediated high expression of CCDC50 correlates with poor prognosis and hepatocellular carcinoma progression

Hepatocellular carcinoma (HCC) is one of the most common and lethal cancer types worldwide. Recent studies found Coiled-coil domain-containing protein 50 (CCDC50) could regulate the nuclear factor kappa-B and p53 signalling pathways in cancer. Nevertheless, the underlying biological function and potential mechanisms of CCDC50 driving the progression of HCC remain unclear. In this study, we found that CCDC50 was up-regulated in HCC, and its higher expression was associated with adverse clinical outcomes and poor clinical characteristics. The results of the Cox regression analysis revealed that CCDC50 was an independent factor for the prognosis of HCC. Meanwhile, we also established a nomogram based on CCDC50 to predict the 1-, 3-, or 5-year survival in HCC patients. Furthermore, we found that DNA hypomethylation results in its overexpression in HCC. In addition, functional annotation confirmed that CCDC50 was mainly involved in the neuroactive ligand-receptor interaction and protein digestion and absorption. Importantly, we found that CCDC50 was highly expressed in HCC cell lines. Depletion of CCDC50 significantly inhibits HCC cell proliferation and migration abilities. This is the first study to identify CCDC50 as a new potential prognostic biomarker and characterize the functional roles of CCDC50 in the progression of HCC, and provides a novel potential diagnostic and therapeutic biomarker for HCC in the future.

Infectious Agents Induce Wnt/β-Catenin Pathway Deregulation in Primary Liver Cancers

Interaction between infectious agents and liver tissue, as well as repeated and extreme biological events beyond adaptive capacities, may result in pathological conditions predisposing people to development of primary liver cancers (PLCs). In adults, PLCs mainly comprise hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA). Various infectious agents in the hepatic microenvironment can destabilize normal liver cell functions by modulating the Wnt/β-catenin pathway components. Among them, hepatotropic viruses B, C, and D are involved in Wnt/β-catenin signaling dysregulation. Other microbial agents, including oncogenic viruses such as Epstein-Barr virus (EBV) and human papilloma virus (HPV), bacteria, e.g., Mycoplasma hyorhinis and Salmonella Typhi, the protozoan parasite Toxoplasma gondii, the fungus Aspergillus flavus, and liver flukes such as Clonorchissinensis or Opisthorchis viverrini, may induce malignant transformation in hepatocytes or in target cells of the biliary tract through aberrant Wnt signaling activation. This review focuses on new insights into infectious agents implicated in the deregulation of Wnt signaling and PLC development. Since the Wnt/β-catenin pathway is a driver of cancer following viral and bacterial infections, molecules inhibiting the complex axis of Wnt signaling could represent novel therapeutic approaches in PLC treatment.

Integrated proteogenomic characterization reveals an imbalanced hepatocellular carcinoma microenvironment after incomplete radiofrequency ablation

BACKGROUND

Efforts to precisely assess tumor-specific T-cell immune responses still face major challenges, and the potential molecular mechanisms mediating hepatocellular carcinoma (HCC) microenvironment imbalance after incomplete radiofrequency ablation (iRFA) are unclear. This study aimed to provide further insight into the integrated transcriptomic and proteogenomic landscape and identify a new target involved in HCC progression following iRFA.

METHODS

Peripheral blood and matched tissue samples were collected from 10 RFA-treated HCC patients. Multiplex immunostaining and flow cytometry were used to assess local and systemic immune responses. Differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) were explored via transcriptomic and proteogenomic analyses. Proteinase-3 (PRTN3) was identified in these analyses. And then, the ability of PRTN3 to predict overall survival (OS) was assessed in 70 HCC patients with early recurrence after RFA. In vitro CCK-8, wound healing and transwell assays were conducted to observe interactions between Kupffer cells (KCs) and HCC cells induced by PRTN3. The protein levels of multiple oncogenic factors and signaling pathway components were detected by western blotting. A xenograft mouse model was built to observe the tumorigenic effect of PRTN3 overexpression on HCC.

RESULTS

Multiplex immunostaining revealed no immediate significant change in local immune cell counts in periablational tumor tissues after 30 min of iRFA. Flow cytometry showed significantly increased levels of CD4+ T cells, CD4+CD8+ T cells, and CD4+CD25+CD127- Tregs and significantly decreased the levels of CD16+CD56+ natural killer cells on day 5 after cRFA (p < 0.05). Transcriptomics and proteomics revealed 389 DEGs and 20 DEPs. Pathway analysis showed that the DEP-DEGs were mainly enriched in the immunoinflammatory response, cancer progression and metabolic processes. Among the DEP-DEGs, PRTN3 was persistently upregulated and closely associated with the OS of patients with early recurrent HCC following RFA. PRTN3 expressed in KCs may affect the migration and invasion of heat stress-treated HCC cells. PRTN3 promotes tumor growth via multiple oncogenic factors and the PI3K/AKT and P38/ERK signaling pathways.

CONCLUSIONS

This study provides a comprehensive overview of the immune response and transcriptomic and proteogenomic landscapes of the HCC milieu induced by iRFA, revealing that PRTN3 promotes HCC progression after iRFA.

TRIAL REGISTRATION

ChiCTR2200055606, http://www.chictr.org.cn/showproj.aspx?proj=32588 .

Characterization of heterogeneous metabolism in hepatocellular carcinoma identifies new therapeutic target and treatment strategy

Background

Metabolic reprogramming is a well-known hallmark of cancer. Systematical identification of clinically relevant metabolic subtypes of Hepatocellular carcinoma (HCC) is critical to understand tumor heterogeneity and develop efficient treatment strategies.

Methods

We performed an integrative analysis of genomic, transcriptomic, and clinical data from an HCC patient cohort in The Cancer Genome Atlas (TCGA).

Results

Four metabolic subtypes were defined: mHCC1, mHHC2, mHCC3, and mHCC4. These subtypes had distinct differences in mutations profiles, activities of metabolic pathways, prognostic metabolism genes, and immune features. The mHCC1 was associated with poorest outcome and was characterized by extensive metabolic alterations, abundant immune infiltration, and increased expression of immunosuppressive checkpoints. The mHHC2 displayed lowest metabolic alteration level and was associated with most significant improvement in overall survival in response to high CD8+ T cell infiltration. The mHHC3 was a “cold-tumor” with low immune infiltration and few metabolic alterations. The mHCC4 presented a medium degree of metabolic alteration and high CTNNB1 mutation rate. Based on our HCC classification and in vitro study, we identified palmitoyl-protein thioesterase 1 (PPT1) was a specific prognostic gene and therapeutic target for mHCC1.

Conclusion

Our study highlighted mechanistic differences among metabolic subtypes and identified potential therapeutic targets for subtype-specific treatment strategies targeting unique metabolic vulnerabilities. The immune heterogeneities across metabolic subtypes may help further clarify the association between metabolism and immune environment and guide the development of novel strategies through targeting both unique metabolic vulnerabilities and immunosuppressive triggers.

Expanding individualized therapeutic options via genoproteomics

Clinical next-generation sequencing (NGS)² tests have enabled treatment recommendations for cancer patients with driver gene mutations. Targeted therapy options for patients without driver gene mutations are currently unavailable. Herein, we performed NGS and proteomics tests on 169 formalin-fixed paraffin-embedded (FFPE)³ samples of non-small cell lung cancers (NSCLC, 65),⁴ colorectal cancers (CRC, 61),⁵ thyroid carcinomas (THCA, 14),⁶ gastric cancers (GC, 2),⁷ gastrointestinal stromal tumors (GIST, 11),⁸ and malignant melanomas (MM, 6).⁹ Of the 169 samples, NGS detected 14 actionable mutated genes in 73 samples, providing treatment options for 43% of the patients. Proteomics identified 61 actionable clinical drug targets approved by the FDA or undergoing clinical trials in 122 samples, providing treatment options for 72% of the patients. In vivo experiments demonstrated that the Mitogen-Activated Protein Kinase (MEK)¹⁰ inhibitor induced the overexpression of MEK1 (Map2k1) to block lung tumor growth in mice. Therefore, protein overexpression is a potentially feasible indicator for guiding targeted therapies. Collectively, our analysis suggests that combining NGS and proteomics (genoproteomics) could expand the targeted treatment options to 85% of cancer patients.

Prediction of 3-year recurrence rate of hepatocellular carcinoma after resection based on contrast-enhanced CT: a single-centre study

OBJECTIVE

We present a new artificial intelligence-powered method to predict 3-year hepatocellular carcinoma (HCC) recurrence by analysing the radiomic profile of contrast-enhanced CT (CECT) images that was validated in patient cohorts.

METHODS

This retrospective cohort study of 224 HCC patients with follow-up for at least 3 years was performed at a single centre from 2012 to 2019. Two groups of radiomic signatures were extracted from the arterial and portal venous phases of pre-operative CECT. Then, the radiological model (RM), deep learning-based radiomics model (DLRM), and clinical & deep learning-based radiomics model (CDLRM) were established and validated in the area under curve (AUC), calibration curve, and clinical decision curve.

RESULTS

Comparison of the clinical baseline variables between the non-recurrence (n = 109) and recurrence group (n = 115), three clinical independent factors (Barcelona Clinic Liver Cancer staging, microvascular invasion, and α-fetoprotein) were incorporated into DLRM for the CDLRM construction. Among the 30 radiomic features most crucial to the 3 year recurrence rate, the selection from deep learning-based radiomics (DLR) features depends on CECT. through the Gini index. In most cases, CDLRM has shown superior accuracy and distinguished performance than DLRM and RM, with the 0.98 AUC in the training cohorts and 0.83 in the testing.

CONCLUSION

This study proposed that DLR-based CDLRM construction would be allowed for the predictive utility of 3-year recurrence outcomes of HCCs, providing high-risk patients with an effective and non-invasive method to possess extra clinical intervention.

ADVANCES IN KNOWLEDGE

This study has highlighted the predictive value of DLR in the 3-year recurrence rate of HCC.

Comprehensive pan-cancer analysis and the regulatory mechanism of AURKA, a gene associated with prognosis of ferroptosis of adrenal cortical carcinoma in the tumor micro-environment

Background: The only curative option for patients with locally or locally advanced adrenocortical carcinoma is primary tumor curative sexual resection (ACC). However, overall survival remains low, with most deaths occurring within the first 2 years following surgery. The 5-year survival rate after surgery is less than 30%. As a result, more accurate prognosis-related predictive biomarkers must be investigated urgently to detect patients' disease status after surgery. Methods: Data from FerrDb were obtained to identify ferroptosis-related genes, and ACC gene expression profiles were collected from the GEO database to find differentially expressed ACC ferroptosis-related genes using differential expression analysis. The DEFGs were subjected to Gene Ontology gene enrichment analysis and KEGG signaling pathway enrichment analysis. PPI network building and predictive analysis were used to filter core genes. The expression of critical genes in ACC pathological stage and pan-cancer was then investigated. In recent years, immune-related factors, DNA repair genes, and methyltransferase genes have been employed in diagnosing and prognosis of different malignancies. Cancer cells are mutated due to DNA repair genes, and highly expressed DNA repair genes promote cancer. Dysregulation of methyltransferase genes and Immune-related factors, which are shown to be significantly expressed in numerous malignancies, also plays a crucial role in cancer. As a result, we investigated the relationship of AURKA with immunological checkpoints, DNA repair genes, and methyltransferases in pan-cancer. Result: The DEGs found in the GEO database were crossed with ferroptosis-related genes, yielding 42 differentially expressed ferroptosis-related genes. Six of these 42 genes, particularly AURKA, are linked to the prognosis of ACC. AURKA expression was significantly correlated with poor prognosis in patients with multiple cancers, and there was a significant positive correlation with Th2 cells. Furthermore, AURKA expression was positively associated with tumor immune infiltration in Lung adenocarcinoma (LUAD), Liver hepatocellular carcinoma (LIHC), Sarcoma (SARC), Esophageal carcinoma (ESCA), and Stomach adenocarcinoma (STAD), but negatively correlated with the immune score, matrix score, and calculated score in these tumors. Further investigation into the relationship between AURKA expression and immune examination gene expression revealed that AURKA could control the tumor-resistant pattern in most tumors by regulating the expression level of specific immune examination genes. Conclusion: AURKA may be an independent prognostic marker for predicting ACC patient prognosis. AURKA may play an essential role in the tumor microenvironment and tumor immunity, according to a pan-cancer analysis, and it has the potential to be a predictive biomarker for multiple cancers.

Cell Pair Algorithm-Based Immune Infiltrating Cell Signature for Improving Outcomes and Treatment Responses in Patients with Hepatocellular Carcinoma

BACKGROUND

Immune interactions play important roles in the regulation of T cells' cytotoxic function, further impacting the anti-tumor efficacy of immunotherapy. A comprehensive analysis of immune cell types in HCC and immune-cell-related signatures predicting prognosis and monitoring immunotherapy efficacy is still absent.

METHODS

More than 1,300 hepatocellular carcinomas (HCC) patients were collected from public databases and included in the present study. The ssGSEA algorithm was applied to calculate the infiltration level of 28 immunocyte subpopulations. A cell pair algorithm was applied to construct an immune-cell-related prognostic index (ICRPI). Survival analyses were performed to measure the survival difference across ICRPI risk groups. Spearman's correlation analyses were used for the relevance assessment. A Wilcoxon test was used to measure the expression level's differences.

RESULTS

In this study, 28 immune subpopulations were retrieved, and 374 immune cell pairs (ICPs) were established, 38 of which were picked out by the least absolute shrinkage and selection operator (LASSO) algorithm. By using the selected ICPs, the ICRPI was constructed and validated to play crucial roles in survival stratification and dynamic monitoring of immunotherapy effect. We also explored several candidate drugs targeting ICRPI. A composite ICRPI and clinical prognostic index (ICPI) was then constructed, which achieved a more accurate estimation of HCC's survival and is a better choice for prognosis predictions in HCC.

CONCLUSIONS

In conclusion, we constructed and validated ICRPI based on the cell pair algorithm in this study, which might provide some novel insights for increasing the survival estimation and clinical response to immune therapy for individual HCC patients and contribute to the personalized precision immunotherapy strategy of HCC.

Transcription factors TEAD2 and E2A globally repress acetyl-CoA synthesis to promote tumorigenesis

Acetyl-coenzyme A (acetyl-CoA) plays an important role in metabolism, gene expression, signaling, and other cellular processes via transfer of its acetyl group to proteins and metabolites. However, the synthesis and usage of acetyl-CoA in disease states such as cancer are poorly characterized. Here, we investigated global acetyl-CoA synthesis and protein acetylation in a mouse model and patient samples of hepatocellular carcinoma (HCC). Unexpectedly, we found that acetyl-CoA levels are decreased in HCC due to transcriptional downregulation of all six acetyl-CoA biosynthesis pathways. This led to hypo-acetylation specifically of non-histone proteins, including many enzymes in metabolic pathways. Importantly, repression of acetyl-CoA synthesis promoted oncogenic dedifferentiation and proliferation. Mechanistically, acetyl-CoA synthesis was repressed by the transcription factors TEAD2 and E2A, previously unknown to control acetyl-CoA synthesis. Knockdown of TEAD2 and E2A restored acetyl-CoA levels and inhibited tumor growth. Our findings causally link transcriptional reprogramming of acetyl-CoA metabolism, dedifferentiation, and cancer.

The Role of Chronic Liver Diseases in the Emergence and Recurrence of Hepatocellular Carcinoma: An Omics Perspective

Hepatocellular carcinoma (HCC) typically develops from a background of cirrhosis resulting from chronic inflammation. This inflammation is frequently associated with chronic liver diseases (CLD). The advent of next generation sequencing has enabled extensive analyses of molecular aberrations in HCC. However, less attention has been directed to the chronically inflamed background of the liver, prior to HCC emergence and during recurrence following surgery. Hepatocytes within chronically inflamed liver tissues present highly activated inflammatory signaling pathways and accumulation of a complex mutational landscape. In this altered environment, cells may transform in a stepwise manner toward tumorigenesis. Similarly, the chronically inflamed environment which persists after resection may impact the timing of HCC recurrence. Advances in research are allowing an extensive epigenomic, transcriptomic and proteomic characterization of CLD which define the emergence of HCC or its recurrence. The amount of data generated will enable the understanding of oncogenic mechanisms in HCC from the CLD perspective and provide the possibility to identify robust biomarkers or novel therapeutic targets for the treatment of primary and recurrent HCC. Importantly, biomarkers defined by the analysis of CLD tissue may permit the early detection or prevention of HCC emergence and recurrence. In this review, we compile the current omics based evidence of the contribution of CLD tissues to the emergence and recurrence of HCC.