Unveiling prognostics biomarkers of tyrosine metabolism reprogramming in liver cancer by cross-platform gene expression analyses

Longitudinal multi-tracer imaging of hepatocellular carcinoma identifies novel stage- and oncogene-specific changes

BACKGROUND

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths, globally. There is a need for novel biomarkers for early detection and novel, effective targeted therapies. Molecular imaging can faithfully visualize, characterize and quantify specific relevant biological processes.

BASIC PROCEDURE

We performed longitudinal dedicated small-animal positron emission tomography-computed tomography (PET/CT) imaging to analyze changes in glucose metabolism using [18F]fluorodeoxyglucose ([18F]FDG), amino acid turnover with [18F]fluoroethyltyrosine ([18F]FET), and chemokine receptor expression using [68Ga]pentixafor targeting CXCR4, during stages of early tumor development, overt HCC and regression. We used two conditional transgenic mouse models of HCC, driven by clinically relevant oncogenes c-MYC (LT2/MYC) or HRASV12 (LT2/RAS). Conditional doxycycline-regulated mouse models, enable liver-specific oncogene activation or inhibition, leading to liver tumor development and regression, respectively. Correlation of our PET/CT findings with our gene expression and metabolomics data and with histological analyses followed.

MAIN FINDINGS

We show PET/CT identifies HCC stage-specific and oncogene-specific molecular changes that may serve as potential novel biomarkers and therapeutic targets. Glucose metabolism and CXCR4 chemokine expression are differentially deregulated during HCC development in an oncogene-specific manner. Our [18F]FDG results correlated with glucose transporter GLUT1 gene expression and with our metabolomics data. Increased expression of CXCR4 and CD68 inflammatory markers mirrored [68Ga]pentixafor results in LT2/MYC mice. FET-based measurement of amino acid turnover are insensitive to stages of HCC-development, in our studies. Concurrently, no significant changes in expression of tyrosine metabolism genes were observed.

PRINCIPAL CONCLUSIONS

Our study highlights that identified changes in targeted molecular imaging can facilitate a better understanding of underlying biological processes and may help guide novel oncogene-specific targeted anti-tumor therapies in HCC, with promising translational potential.

Analysis and Validation of Tyrosine Metabolism-related Prognostic Features for Liver Hepatocellular Carcinoma Therapy

AIMS

To explore tyrosine metabolism-related characteristics in liver hepatocellular carcinoma (LIHC) and to establish a risk signature for the prognostic prediction of LIHC. Novel prognostic signatures contribute to the mining of novel biomarkers, which are essential for the construction of a precision medicine system for LIHC and the improvement of survival.

BACKGROUND

Tyrosine metabolism plays a critical role in the initiation and development of LIHC. Based on the tyrosine metabolism-related characteristics in LIHC, this study developed a risk signature to improve the prognostic prediction of patients with LIHC.

OBJECTIVE

To investigate the correlation between tyrosine metabolism and progression of LIHC and to develop a tyrosine metabolism-related prognostic model.

METHODS

Gene expression and clinicopathological information of LIHC were obtained from The Cancer Genome Atlas (TCGA) database. Distinct subtypes of LIHC were classified by performing consensus cluster analysis on the tyrosine metabolism-related genes. Univariate and Lasso Cox regression were used to develop a RiskScore prognosis model. Kaplan-Meier (KM) survival analysis with log-rank test and area under the curve (AUC) of receiver operating characteristic (ROC) were employed in the prognostic evaluation and prediction validation. Immune infiltration, tyrosine metabolism score, and pathway enrichment were evaluated using single-sample gene set enrichment analysis (ssGSEA). Finally, a nomogram model was developed with the RiskScore and other clinicopathological features.

RESULTS

Based on the tyrosine metabolism genes in the TCGA cohort, we identified 3 tyrosine metabolism-related subtypes showing significant prognostic differences. Four candidate genes selected from the common differentially expressed genes (DEGs) between the 3 subtypes were used to develop a RiskScore model, which could effectively divide LIHC patients into high- and lowrisk groups. In both the training and validation sets, high-risk patients tended to have worse overall survival, less active immunotherapy response, higher immune infiltration and clinical grade, and higher oxidative, fatty, and xenobiotic metabolism pathways. Multivariate analysis confirmed that the RiskScore was an independent indicator for the prognosis of LIHC. The results from pan-- cancer analysis also supported that the RiskScore had a strong prognostic performance in other cancers. The nomogram demonstrated that the RiskScore contributed the most to the prediction of LIHC prognosis.

CONCLUSION

Our study developed a tyrosine metabolism-related risk model that performed well in survival prediction, showing the potential to serve as an independent prognostic predictor for LIHC treatment.

A multi-omic analysis reveals that Gamabufotalin exerts anti-hepatocellular carcinoma effects by regulating amino acid metabolism through targeting STAMBPL1

BACKGROUND

Hepatocellular carcinoma (HCC), a prevalent type of liver cancer, is characterized by an unfavorable prognosis and a high mortality rate. Identifying novel treatments to prevent HCC recurrence and metastasis remains crucial for improving patient survival. Gamabufotalin (CS-6), a primary bufadienolide derived from the traditional Chinese medicine Chansu, has demonstrated significant anti-tumor activity. However, the effects and underlying mechanisms of CS-6 on HCC cells are not yet fully understood.

PURPOSE

This study sought to elucidate the anti-HCC effects and potential mechanisms of CS-6. In vitro experiments were conducted using the HCC cell lines MHCC97H and Huh-7, employing CCK-8 assays, colony formation assays, wound healing assays, transwell invasion and migration assays, and flow cytometry to assess apoptosis and cell cycle dynamics. A multi-omics approach, including metabolomics and RNA sequencing analysis, was utilized to identify CS-6's molecular targets and mechanisms in HCC therapy. Additionally, in vivo assessments were performed using xenografts in nude mice.

RESULTS

CS-6 significantly inhibited HCC cell proliferation, migration, and invasion. Multi-omics analysis suggested that CS-6's anti-HCC effects may involve the modulation of metabolic pathways, potentially through the downregulation of STAMBPL1, resulting in reduced mTOR signaling, increased apoptosis, and suppression of malignant HCC behavior. In vivo studies further confirmed that CS-6 significantly suppressed tumor growth and enhanced apoptosis and autophagy within tumors.

CONCLUSION

These results underscore the therapeutic potential of CS-6 in HCC treatment. The study offers novel insights into the mechanism of CS-6, suggesting that its therapeutic efficacy may be uniquely mediated by targeting STAMBPL1. This distinct mechanism sets CS-6 apart from existing HCC treatments and positions it as a promising candidate for further clinical investigation.

Metabolomics analysis reveals resembling metabolites between humanized γδ TCR mice and human plasma

Gamma delta (γδ) T cells, which reside in mucosal and epithelial tissues, are integral to immune responses and are involved in various cancers, autoimmune, and infectious diseases. To study human γδ T cells to a translational level, we developed γδ humanized TCR-T1 (HuTCR-T1) mice using our TruHumanization platform. We compared the metabolomic profiles from plasma samples of wild-type (WT), γδ HuTCR-T1 mice, and humans using UHPLC-MS/MS. Untargeted metabolomics and lipidomics were used to screen all detectable metabolites. Principal component analysis revealed that the metabolomic profiles of γδ HuTCR-T1 mice closely resemble those of humans, with a clear segregation of metabolites between γδ HuTCR-T1 and WT mice. Most humanized γδ metabolites were classified as lipids, followed by organic compounds and amino acids. Pathway analysis identified significant alterations in the metabolism of tryptophan, tyrosine, sphingolipids, and glycerophospholipids, shifting these pathways towards a more human-like profile. Immunophenotyping showed that γδ HuTCR-T1 mice maintained normal proportions of both lymphoid and myeloid immune cell populations, closely resembling WT mice, with only a few exceptions. These findings demonstrate that the γδ HuTCR-T1 mouse model exhibits a metabolomic profile that is remarkably similar to that of humans, highlighting its potential as a relevant model for investigating the role of metabolites in disease development and progression. This model also offers an opportunity to discover therapeutic human TCRs.

Structural and Evolutionary Relationships of Melanin Cascade Proteins in Cnidarian Innate Immunity

Melanin is an essential product that plays an important role in innate immunity in a variety of organisms across the animal kingdom. Melanin synthesis is performed by many organisms using the tyrosine metabolism pathway, a general pathway that utilizes a type-three copper oxidase protein, called PO-candidates (phenoloxidase candidates). While melanin synthesis is well-characterized in organisms like arthropods and humans, it is not as well-understood in non-model organisms such as cnidarians. With the rising anthropomorphic climate change influence on marine ecosystems, cnidarians, specifically corals, are under an increased threat of bleaching and disease. Understanding innate immune pathways, such as melanin synthesis, is vital for gaining insights into how corals may be able to fight these threats. In this study, we use comparative bioinformatic approaches to provide a comprehensive analysis of genes involved in tyrosine-mediated melanin synthesis in cnidarians. Eighteen PO-candidates representing five phyla were studied to identify their evolutionary relationship. Cnidarian species were most similar to chordates due to domain presents in the amino acid sequences. From there, functionally conserved domains in coral proteins were identified in a coral disease dataset. Five stony corals exposed to stony coral tissue loss disease were leveraged to identify 18 putative tyrosine metabolism genes, genes with functionally conserved domains to their Homo sapiens counterpart. To put this pathway in the context of coral health, putative genes were correlated to melanin concentration from tissues of stony coral species in the disease exposure dataset. In this study, tyrosinase was identified in stony corals as correlated to melanin concentrations and likely plays a key role in immunity as a resistance trait. In addition, stony coral genes were assigned to all modules within the tyrosine metabolism pathway, indicating an evolutionary conservation of this pathway across phyla. Overall, this study provides a comprehensive analysis of the genes involved in tyrosine-mediated melanin synthesis in cnidarians.

Preclinical evaluation of dalbergin loaded PLGA-galactose-modified nanoparticles against hepatocellular carcinoma via inhibition of the AKT/NF-κB signaling pathway

Prior research has shown the effectiveness of dalbergin (DL), dalbergin nanoformulation (DLF), and dalbergin-loaded PLGA-galactose-modified nanoparticles (DLMF) in treating hepatocellular carcinoma (HCC) cells. The present investigation constructs upon our previous research and delves into the molecular mechanisms contributing to the anticancer effects of DLF and DLMF. This study examined the anti-cancer effects of DL, DLF, and DLMF by diethyl nitrosamine (DEN)-induced HCC model in albino Wistar rats. In addition, we performed biochemical, antioxidant, lipid profile tests, and histological studies of liver tissue. The anticancer efficacy of DLMF is equivalent to that of 5-fluorouracil, a commercially available therapy for HCC. Immunoblotting studies revealed a reduction in the expression of many apoptotic markers, such as p53, BAX, and Cyt-C, in HCC. Conversely, the expression of Bcl-2, TNF-α, NFκB, p-AKT, and STAT-3 was elevated. Nevertheless, the administration of DL, DLF, and DLMF effectively controlled the levels of these apoptotic markers, resulting in a considerable decrease in the expression of Bcl-2, TNF-α, NFκB, p-AKT, and STAT-3. Specifically, the activation of TNF-alpha and STAT-3 triggers the signalling pathways that include the Bcl-2 family of proteins, Cyt-C, caspase 3, and 9. This ultimately leads to apoptosis and the suppression of cell growth. Furthermore, metabolomic analysis using 1H NMR indicated that the metabolites of animals reverted to normal levels after the treatment.

In Vivo Chemosuppressive Effects of Kolaviron on 7,12-Dimethylbenzanthracene-Induced Mammary Lesions are Associated with Changes in Levels of Estrogen Receptor-α, CYP 1A1, Proinflammatory Cytokines, and Alterations to Metabolic Pathways Implicated in Mammary Carcinogenesis

Garcinia kola is a medicinal food commonly consumed in Sub-Sahara Africa, for which Kolaviron (KV) is the active portion. As a follow-up to our earlier chemopreventive studies, we investigated the chemotherapeutic effects of KV on experimentally induced mammary carcinogenesis in female Wistar rats. Mammary carcinogenesis was induced using 80 mg/kg of 7,12-dimethylbenzanthracene (DMBA) administered by oral gavage. One hundred-fifty days post-DMBA induction, estrogen receptor-α (ER-α) levels were determined in the experimental rats before treatment with KV commenced. Treatment was done using 50, 100, and 200 mg/kg KV thrice a week for 4 weeks, after which the experiment was terminated. Significantly higher levels of estrogen receptor-α, CYP 1A1, malondialdehyde, formation of lobular neoplastic cells, epithelial hyperplasia, lymphocyte infiltration, and increased cytokine (interleukin-6 and tumor necrosis factor-α) activity were observed in DMBA-induced rats, which were attenuated in KV-treated rats. Tyrosine metabolism was exclusively enriched in DMBA-induced rats in contrast to KV-treated rats. Collectively, the results point to the chemotherapeutic potential of KV.

TRIM21-mediated ubiquitylation of TAT suppresses liver metastasis in gallbladder cancer

Liver metastasis is common in patients with gallbladder cancer (GBC), imposing a significant challenge in clinical management and serving as a poor prognostic indicator. However, the mechanisms underlying liver metastasis remain largely unknown. Here, we report a crucial role of tyrosine aminotransferase (TAT) in liver metastasis of GBC. TAT is frequently up-regulated in GBC tissues. Increased TAT expression is associated with frequent liver metastasis and poor prognosis of GBC patients. Overexpression of TAT promotes GBC cell migration and invasion in vitro, as well as liver metastasis in vivo. TAT knockdown has the opposite effects. Intriguingly, TAT promotes liver metastasis of GBC by potentiating cardiolipin-dependent mitophagy. Mechanistically, TAT directly binds to cardiolipin and leads to cardiolipin externalization and subsequent mitophagy. Moreover, TRIM21 (Tripartite Motif Containing 21), an E3 ubiquitin ligase, interacts with TAT. The histine residues 336 and 338 at TRIM21 are essential for this binding. TRIM21 preferentially adds the lysine 63 (K63)-linked ubiquitin chains on TAT principally at K136. TRIM21-mediated TAT ubiquitination impairs its dimerization and mitochondrial location, subsequently inhibiting tumor invasion and migration of GBC cells. Therefore, our study identifies TAT as a novel driver of GBC liver metastasis, emphasizing its potential as a therapeutic target.

Alterations in serum metabolic profiles of early-stage hepatocellular carcinoma patients after radiofrequency ablation therapy

OBJECTIVE

To investigate the alterations in serum metabolic profiles and early-stage hepatocellular carcinoma (HCC) patient characteristics after radiofrequency ablation (RFA) therapy. This evaluation aimed to assess treatment effectiveness and identify potential novel approaches and targets for HCC treatment and prognosis monitoring.

METHODS

Untargeted metabolomics technology was employed to analyze serum metabolic profiles in healthy volunteer controls (NCs) and early stage HCC patients before and after RFA therapy. Additionally, Human Metabolome Database and Kyoto Encyclopedia of Genes and Genomes database were used to identify the differential metabolites (DMs) and metabolic pathways. Cystoscape was utilized to construct DM gene networks. Amino acid analyses were performed to validate our findings.

RESULTS

We identified 11, 14, and six DMs between the NC and HCC groups, HCC patients before and after RFA therapy, and post-RFA HCC and NC groups, respectively. The expression levels of these DMs, particularly those of amino acids and lipids, significantly changed. Compared with the NC group, higher levels of L-tyrosine, aspartate, and 18-oxo-oleate were observed in HCC patients, which were significantly reduced in patients after RFA therapy. Meanwhile, HCC patients after RFA therapy had increased levels of L-arginine, phosphatidic acid (20:3), and lysophosphatidyl choline (LPC) (20:4) compared to those before therapy, while their levels before therapy were lower than those of NC. Moreover, most metabolites in the post-RFA and NC groups showed no significant changes in expression, except for L-tyrosine and LPC (16:0). These metabolites could potentially serve as characteristic factors of early-stage HCC patients after RFA therapy. Joint pathway analysis revealed striking changes, mainly in phenylalanine, tyrosine, and tryptophan biosynthesis; alanine, aspartate, and glutamate metabolism; and arginine and aminoacyl-tRNA biosynthesis. Bioinformatics analysis of publicly available data preliminarily identified 187 DM-related metabolic enzymes.

CONCLUSION

Our study proposed novel targets for early-stage HCC treatment, laying the groundwork for improving treatment efficacy and prognosis of early-stage HCC patients.

Pulsed electric field induces exocytosis and overexpression of MAGE antigens in melanoma

Nanosecond pulsed electric field (nsPEF) has emerged as a promising approach for inducing cell death in melanoma, either as a standalone treatment or in combination with chemotherapeutics. However, to date, there has been a shortage of studies exploring the impact of nsPEF on the expression of cancer-specific molecules. In this investigation, we sought to assess the effects of nsPEF on melanoma-specific MAGE (Melanoma Antigen Gene Protein Family) expression. To achieve this, melanoma cells were exposed to nsPEF with parameters set at 8 kV/cm, 200 ns duration, 100 pulses, and a frequency of 10 kHz. We also aimed to comprehensively describe the consequences of this electric field on melanoma cells' invasion and proliferation potential. Our findings reveal that following exposure to nsPEF, melanoma cells release microvesicles containing MAGE antigens, leading to a simultaneous increase in the expression and mRNA content of membrane-associated antigens such as MAGE-A1. Notably, we observed an unexpected increase in the expression of PD-1 as well. While we did not observe significant differences in the cells' proliferation or invasion potential, a remarkable alteration in the cells' metabolomic and lipidomic profiles towards a less aggressive phenotype was evident. Furthermore, we validated these results using ex vivo tissue cultures and 3D melanoma culture models. Our study demonstrates that nsPEF can elevate the expression of membrane-associated proteins, including melanoma-specific antigens. The mechanism underlying the overexpression of MAGE antigens involves the initial release of microvesicles containing MAGE antigens, followed by a gradual increase in mRNA levels, ultimately resulting in elevated expression of MAGE antigens post-experiment. These findings shed light on a novel method for modulating cancer cells to overexpress cancer-specific molecules, thereby potentially enhancing their sensitivity to targeted anticancer therapy.

Changes in the composition of the fecal metabolome and gut microbiota contribute to intervertebral disk degeneration in a rabbit model

PURPOSE

Lower back pain (LBP), mainly caused by intervertebral disk (IVD) degeneration (IDD), is widely prevalent worldwide and is a serious socioeconomic burden. Numerous factors may trigger this degenerative process, and microbial dysbiosis has recently been implicated as one of the likely causes. However, the exact relationship between IDD and the microbiome remains obscure. In this study, we investigated the gut microbiota composition and fecal metabolic phenotype and discussed the possible influences of microbiome dysbiosis on IDD.

METHODS

Fecal DNA was extracted from 16 fecal samples (eight rabbit models with IDD and eight sex- and age-matched healthy controls) and analyzed by high-throughput 16S rDNA sequencing. The fecal samples were also analyzed by liquid chromatography-mass spectrometry-based metabolomics. Multivariate analyses were conducted for the relationship between the omics data and IDD, linear discriminant analysis effect size was employed for biomarker discovery. Moreover, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate the differential metabolites. The potential correlation between differential gut microbiota and metabolites was then assessed.

RESULTS

The 16S rDNA sequencing results showed that the β-diversity of the gut microbiota was significantly different between the IDD and control groups, with distinct abundance levels of dominant genera. Moreover, 59 metabolites were significantly upregulated and 91 were downregulated in IDD rabbits versus the controls. The KEGG enrichment analysis revealed that the top pathways remarkably impacted by IDD were tyrosine metabolism, amino sugar and nucleotide sugar metabolism, benzoate degradation, ABC transporters, ascorbate and aldarate metabolism, pantothenate and CoA biosynthesis, and pyrimidine metabolism. The correlation analysis revealed that DL-tyrosine and N-acetylmuramic acid were associated with multiple differential bacterial genera, including Helicobacter and Vibrio, which may play important roles in the process of IVD degeneration.

CONCLUSION

Our findings revealed that IDD altered gut microbiota and fecal metabolites in a rabbit model. The correlation analysis of microbiota and metabolome provides a deeper understanding of IDD and its possible etiopathogenesis. These results also provide a direction and theoretical basis for the clinical application of fecal transplantation, probiotics, and other methods to regulate gut microbiota in the treatment of LBP caused by IDD.

Signaling metabolite succinylacetone activates HIF-1α and promotes angiogenesis in GSTZ1-deficient hepatocellular carcinoma

Aberrant angiogenesis in hepatocellular carcinoma (HCC) is associated with tumor growth, progression, and local or distant metastasis. Hypoxia-inducible factor 1α (HIF-1α) is a transcription factor that plays a major role in regulating angiogenesis during adaptation of tumor cells to nutrient-deprived microenvironments. Genetic defects in Krebs cycle enzymes, such as succinate dehydrogenase and fumarate hydratase, result in elevation of oncometabolites succinate and fumarate, thereby increasing HIF-1α stability and activating the HIF-1α signaling pathway. However, whether other metabolites regulate HIF-1α stability remains unclear. Here, we reported that deficiency of the enzyme in phenylalanine/tyrosine catabolism, glutathione S-transferase zeta 1 (GSTZ1), led to accumulation of succinylacetone, which was structurally similar to α-ketoglutarate. Succinylacetone competed with α-ketoglutarate for prolyl hydroxylase domain 2 (PHD2) binding and inhibited PHD2 activity, preventing hydroxylation of HIF-1α, thus resulting in its stabilization and consequent expression of vascular endothelial growth factor (VEGF). Our findings suggest that GSTZ1 may serve as an important tumor suppressor owing to its ability to inhibit the HIF-1α/VEGFA axis in HCC. Moreover, we explored the therapeutic potential of HIF-1α inhibitor combined with anti-programmed cell death ligand 1 therapy to effectively prevent HCC angiogenesis and tumorigenesis in Gstz1-knockout mice, suggesting a potentially actionable strategy for HCC treatment.

TPO as an indicator of lymph node metastasis and recurrence in papillary thyroid carcinoma

The objective of this study was to investigate the expression of thyroid peroxidase (TPO) in papillary thyroid carcinoma (PTC) and to preliminarily investigate its value as a marker of lymph node metastasis and recurrence in patients with PTC. Clinical data of PTC patients and TPO expression were collected from The Cancer Genome Atlas (TCGA) database for analysis. We recruited 230 consecutive PTC patients from the Department of Thyroid Surgery of the First Affiliated Hospital of Kunming Medical University, collected their clinicopathological data, and also performed immunohistochemical analysis of TPO expression on their thyroid specimens to validate the results of bioinformatics analysis. In addition, the construction of protein-protein interaction networks was performed too. Functional enrichment analysis and immuno-infiltration analysis characterized the pathways in which TPO genes may be involved. Data mining based on the TCGA database showed that TPO expression in PTC tissues was significantly lower than in paired normal thyroid tissues. The expression level of TPO in PTC tissues correlated with tumor lymph node metastasis and recurrence. Follow-up data from our center also validated the difference in TPO expression and its relationship with lymph node metastasis in PTC patients. Functional enrichment analysis showed that TPO function was significantly associated with signaling pathways related to amino acid metabolism, gene expression regulation and tumorigenesis. TPO expression was also significantly associated with immune infiltration. Our study showed that reduced TPO expression was significantly associated with lymph node metastasis and recurrence in patients with PTC, and we validated this result in our central cohort. These data suggest that TPO may serve as a prognostic indicator for PTC.

Protein-Protein Interfaces as Druggable Targets: A Common Motif of the Pyridoxal-5'-Phosphate-Dependent Enzymes to Receive the Coenzyme from Its Producers

Pyridoxal-5'-phosphate (PLP), a phosphorylated form of vitamin B6, acts as a coenzyme for numerous reactions, including those changed in cancer and/or associated with the disease prognosis. Since highly reactive PLP can modify cellular proteins, it is hypothesized to be directly transferred from its donors to acceptors. Our goal is to validate the hypothesis by finding common motif(s) in the multitude of PLP-dependent enzymes for binding the limited number of PLP donors, namely pyridoxal kinase (PdxK), pyridox(am)in-5'-phosphate oxidase (PNPO), and PLP-binding protein (PLPBP). Experimentally confirmed interactions between the PLP donors and acceptors reveal that PdxK and PNPO interact with the most abundant PLP acceptors belonging to structural folds I and II, while PLPBP - with those belonging to folds III and V. Aligning sequences and 3D structures of the identified interactors of PdxK and PNPO, we have identified a common motif in the PLP-dependent enzymes of folds I and II. The motif extends from the enzyme surface to the neighborhood of the PLP binding site, represented by an exposed alfa-helix, a partially buried beta-strand, and residual loops. Pathogenicity of mutations in the human PLP-dependent enzymes within or in the vicinity of the motif, but outside of the active sites, supports functional significance of the motif that may provide an interface for the direct transfer of PLP from the sites of its synthesis to those of coenzyme binding. The enzyme-specific amino acid residues of the common motif may be useful to develop selective inhibitors blocking PLP delivery to the PLP-dependent enzymes critical for proliferation of malignant cells.

Single Cell Metabolic Landscape of Pituitary Neuroendocrine Tumor Subgroups and Lineages

Pituitary neuroendocrine tumors (PitNETs) are common intracranial tumors comprising numerous subtypes whose metabolic profiles have yet to be fully examined. The present in silico study analyzed single-cell expression profiles from 2311 PitNET cells from various lineages and subtypes to elucidate differences in metabolic activities. Gonadotroph tumors exhibited high activities with histidine metabolism, whose activity is low in lactotroph tumors. Somatotroph tumors enriched for sulfur and tyrosine metabolism, while lactotroph tumors were enriched metabolism of nitrogen, ascorbate, and aldarate. PIT-1 lineage tumors exhibited high sulfur and thiamine metabolism. These results set precedence for further translational studies for subgroup/lineage specific targeted therapies.

Function of TRPC1 in modulating hepatocellular carcinoma progression

The liver is the main organ of metabolism in the human body, and it is easy to suffer from hepatitis, cirrhosis, liver cancer, and other diseases, the most serious of which is liver cancer. Worldwide, liver cancer is the most common and deadly malignant tumor, the third leading cause of cancer death in the world. Based on TCGA and ICGC databases, our research discovered the important role of TRPC1 in liver cancer through bioinformatics. The results showed that TRPC1 was over-expressed in hepatocellular carcinoma, and the higher the expression level of TRPC1, the worse the OS and the lower the survival rate. TRPC1 was a risk factor affecting the overall survival probability of hepatocellular carcinoma patients. By analyzing the function of the TRP family in liver cancer, TRPC1 might promote the occurrence of liver cancer by up-regulating common signal pathways in tumors such as tumor proliferation signature, and down-regulating important metabolic reactions such as retinol metabolism. In addition, TRPC1 could promote the development of liver cancer by up-regulating the expression of ABI2, MAPRE1, YEATS2, MTA3, TMEM237, MTMR2, CCDC6, AC069544.2, and NCBP2 genes. These results illustrate that TRPC1 is very valuable in the study of liver cancer.

Identification and validation of a tyrosine metabolism-related prognostic prediction model and characterization of the tumor microenvironment infiltration in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is an aggressive and heterogeneous disease characterized by high morbidity and mortality. The liver is the vital organ that participates in tyrosine catabolism, and abnormal tyrosine metabolism could cause various diseases, including HCC. Besides, the tumor immune microenvironment is involved in carcinogenesis and can influence the patients' clinical outcomes. However, the potential role of tyrosine metabolism pattern and immune molecular signature is poorly understood in HCC.

METHODS

Gene expression, somatic mutations, copy number variation data, and clinicopathological information of HCC were downloaded from The Cancer Genome Atlas (TCGA) database. GSE14520 from the Gene Expression Omnibus (GEO) databases was used as a validation dataset. We performed unsupervised consensus clustering of tyrosine metabolism-related genes (TRGs) and classified patients into distinct molecular subtypes. We used ESTIMATE algorithms to evaluate the immune infiltration. We then applied LASSO Cox regression to establish the TRGs risk model and validated its predictive performance.

RESULTS

In this study, we first described the alterations of 42 TRGs in HCC cohorts and characterized the clinicopathological characteristics and tumor microenvironmental landscape of the two distinct subtypes. We then established a tyrosine metabolism-related scoring system and identified five TRGs, which were highly correlated with prognosis and representative of this gene set, namely METTL6, GSTZ1, ADH4, ADH1A, and LCMT1. Patients in the high-risk group had an inferior prognosis. Univariate and multivariate Cox proportional hazards regression analysis also showed that the tyrosine metabolism-related signature was an independent prognostic indicator. Besides, receiver operating characteristic curve (ROC) analysis demonstrated the predictive accuracy of the TRGs signature that could reliably predict 1-, 3-, and 5-year survival in both TCGA and GEO cohorts. We also got consistent results by performing clone formation and invasion analysis, and immunohistochemical (IHC) assays. Moreover, we also discovered that the TRGs signature was significantly associated with the different immune landscapes and therapeutic drug sensitivity.

CONCLUSION

Our comprehensive analysis revealed the potential molecular signature and clinical utilities of TRGs in HCC. The model based on five TRGs can accurately predict the survival outcomes of HCC, improving our knowledge of TRGs in HCC and paving a new path for guiding risk stratification and treatment strategy development for HCC patients.

Transcriptomic Harmonization as the Way for Suppressing Cross-Platform Bias and Batch Effect

(1) Background: Emergence of methods interrogating gene expression at high throughput gave birth to quantitative transcriptomics, but also posed a question of inter-comparison of expression profiles obtained using different equipment and protocols and/or in different series of experiments. Addressing this issue is challenging, because all of the above variables can dramatically influence gene expression signals and, therefore, cause a plethora of peculiar features in the transcriptomic profiles. Millions of transcriptomic profiles were obtained and deposited in public databases of which the usefulness is however strongly limited due to the inter-comparison issues; (2) Methods: Dozens of methods and software packages that can be generally classified as either flexible or predefined format harmonizers have been proposed, but none has become to the date the gold standard for unification of this type of Big Data; (3) Results: However, recent developments evidence that platform/protocol/batch bias can be efficiently reduced not only for the comparisons of limited transcriptomic datasets. Instead, instruments were proposed for transforming gene expression profiles into the universal, uniformly shaped format that can support multiple inter-comparisons for reasonable calculation costs. This forms a basement for universal indexing of all or most of all types of RNA sequencing and microarray hybridization profiles; (4) Conclusions: In this paper, we attempted to overview the landscape of modern approaches and methods in transcriptomic harmonization and focused on the practical aspects of their application.

Gene Expression Analysis Reveals Prognostic Biomarkers of the Tyrosine Metabolism Reprogramming Pathway for Prostate Cancer

Background

Tyrosine metabolism pathway-related genes were related to prostate cancer progression, which may be used as potential prognostic markers.

Aims

To dissect the dysregulation of tyrosine metabolism in prostate cancer and build a prognostic signature based on tyrosine metabolism-related genes for prostate cancer. Materials and Method. Cross-platform gene expression data of prostate cancer cohorts were collected from both The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Based on the expression of tyrosine metabolism-related enzymes (TMREs), an unsupervised consensus clustering method was used to classify prostate cancer patients into different molecular subtypes. We employed the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to evaluate prognostic characteristics based on TMREs to obtain a prognostic effect. The nomogram model was established and used to synthesize molecular subtypes, prognostic characteristics, and clinicopathological features. Kaplan–Meier plots and logrank analysis were used to clarify survival differences between subtypes.

Results

Based on the hierarchical clustering method and the expression profiles of TMREs, prostate cancer samples were assigned into two subgroups (S1, subgroup 1; S2, subgroup 2), and the Kaplan–Meier plot and logrank analysis showed distinct survival outcomes between S1 and S2 subgroups. We further established a four-gene-based prognostic signature, and both in-group testing dataset and out-group testing dataset indicated the robustness of this model. By combining the four gene-based signatures and clinicopathological features, the nomogram model achieved better survival outcomes than any single classifier. Interestingly, we found that immune-related pathways were significantly concentrated on S1-upregulated genes, and the abundance of memory B cells, CD4+ resting memory T cells, M0 macrophages, resting dendritic cells, and resting mast cells were significantly different between S1 and S2 subgroups.

Conclusions

Our results indicate the prognostic value of genes related to tyrosine metabolism in prostate cancer and provide inspiration for treatment and prevention strategies.

[Exploration of the therapeutic mechanism of Yiqi Jiedu recipe for treatment of primary liver cancer based on network pharmacology and molecular docking]

OBJECTIVE

To explore the effective components of Yiqi Jiedu recipe and the main biological processes and signal pathways involved in the therapeutic mechanism of the recipe in treatment of primary liver cancer through network pharmacology and molecular docking approaches.

METHODS

TCMSP, Uniport, Genecards and String databases were searched to obtain the target genes of drugs and disease using Cytoscape 3.8.2 software. GO and KEGG enrichment analyses were performed to identify the common genes in the target genes of the drugs and disease. Using Pubcham, RCSB and Autoduck, the effective components of the drugs were connected with the final core genes. The effects of different concentrations of Yiqi Jiedu recipe on the expressions of the core genes DHX9, HNRNPK, NCL and PABPC1 in HepG2 cells were analyzed with Western blotting and real- time fluorescence quantitative PCR.

RESULTS

We finally identified 8 core genes from the drug and disease targets, including DDX5, HNRNPK, PABPC1, DHX9, RPS3A, RPS3, RPL13, and NCL. GO analysis showed that these core genes were involved mainly in the biological processes of adrenaline receptor signal communication, movement of cellular or subcellular components, blood particles, adhesion class and iron ion binding. KEGG analysis showed that the Ras signaling pathway had the greatest gene enrichment. The results of molecular docking suggested that the effective components of the recipe were capable of docking with the core genes under natural conditions, and PABPC1 and stigmasterol had the highest binding energy. In HepG2 cells, treatment with 10% medicated serum for 48 h had the strongest effect on the expression of DHX9, HNRNPK, NCL and PABPC1 (P < 0.05).

CONCLUSION

Yiqi Jiedu recipe is capable of regulating viral expression of primary liver cancer multiple effective components that bind to DHX9, HNRNPK, NCL and PABPC1.

Predictive significance of circulating histones in hepatocellular carcinoma patients treated with sorafenib

Background: Predictive biomarkers for advanced hepatocellular carcinoma are lacking. EZH2 drives sorafenib resistance through H3K27me3 and is counteracted by SETD2, which catalyzes H3K36me3. The authors tested the predictive power of circulating H3K27me3 and H3K36me3 in advanced hepatocellular carcinoma patients treated with sorafenib. Methods: A total of 80 plasma samples were tested for histone variants by ELISA. Changes from baseline to best response or progressive disease were correlated with patient survival. Results: A higher EZH2/SETD2 ratio predicted worse prognosis in this setting. H3K27me3 and H3K36me3 decreased from baseline to best response. The H3K27me3/H3K36me3 ratio increased from baseline to progressive disease. Higher ratios at best response were associated with shorter progression-free survival. Conclusion: The authors suggest that circulating H3K27me3/H3K36me3 ratio level acts as a predictive biomarker for sorafenib treatment outcomes in patients with advanced hepatocellular carcinoma.

AC093797.1 as a Potential Biomarker to Indicate the Prognosis of Hepatocellular Carcinoma and Inhibits Cell Proliferation, Invasion, and Migration by Reprogramming Cell Metabolism and Extracellular Matrix Dynamics

Purpose: The risk signature composed of four lncRNA (AC093797.1, POLR2J4, AL121748.1, and AL162231.4.) can be used to predict the overall survival (OS) of patients with hepatocellular carcinoma (HCC). However, the clinical significance and biological function of AC093797.1 are still unexplored in HCC or other malignant tumors. In this study, we aimed to investigate the biological function of AC093797.1 in HCC and screen the candidate hub genes and pathways related to hepatocarcinogenesis.

Methods: RT-qPCR was employed to detect AC093797.1 in HCC tissues and cell lines. The role of AC093797.1 in HCC was evaluated via the cell-counting kit-8, transwell, and wound healing assays. The effects of AC093797.1 on tumor growth in vivo were clarified by nude mice tumor formation experiments. Then, RNA-sequencing and bioinformatics analysis based on subcutaneous tumor tissue was performed to identify the hub genes and pathways associated with HCC.

Results: The expression of AC093797.1 decreased in HCC tissues and cell lines, and patients with low expressed AC093797.1 had poor overall survival (OS). AC093797.1 overexpression impeded HCC cell proliferation, invasion, and migration in vitro and suppressed tumor growth in vivo. Compared with the control group, 710 differentially expressed genes (243 upregulated genes and 467 downregulated genes) were filtered via RNA-sequencing, which mainly enriched in amino acid metabolism, extracellular matrix structure constituents, cell adhesion molecules cams, signaling to Ras, and signaling to ERKs.

Conclusion: AC093797.1 may inhibit cell proliferation, invasion, and migration in HCC by reprograming cell metabolism or regulating several pathways, suggesting that AC093797.1 might be a potential therapeutic and prognostic marker for HCC patients.

Self-inactivating, all-in-one AAV vectors for precision Cas9 genome editing via homology-directed repair in vivo

Adeno-associated virus (AAV) vectors are important delivery platforms for therapeutic genome editing but are severely constrained by cargo limits. Simultaneous delivery of multiple vectors can limit dose and efficacy and increase safety risks. Here, we describe single-vector, ~4.8-kb AAV platforms that express Nme2Cas9 and either two sgRNAs for segmental deletions, or a single sgRNA with a homology-directed repair (HDR) template. We also use anti-CRISPR proteins to enable production of vectors that self-inactivate via Nme2Cas9 cleavage. We further introduce a nanopore-based sequencing platform that is designed to profile rAAV genomes and serves as a quality control measure for vector homogeneity. We demonstrate that these platforms can effectively treat two disease models [type I hereditary tyrosinemia (HT-I) and mucopolysaccharidosis type I (MPS-I)] in mice by HDR-based correction of the disease allele. These results will enable the engineering of single-vector AAVs that can achieve diverse therapeutic genome editing outcomes.

Long-term expression of Cas9 following precision genome editing in vivo may lead to undesirable consequences. Here we show that a single-vector, self-inactivating AAV system containing Cas9 nuclease, guide, and DNA donor can use homology-directed repair to correct disease mutations in vivo.

Chemosensitivity analysis and study of gene resistance on tumors and cancer stem cell isolates from patients with colorectal cancer

Colorectal cancer (CRC) is one of the main causes of mortality. Recent studies suggest that cancer stem cells (CSCs) can survive after chemotherapy and promote tumor invasiveness and aggression. According to a higher hierarchy complexity of CSC, different protocols for isolation, expansion, and characterization have been used; however, there are no available resistance biomarkers that allow predicting the clinical response of treatment 5‑fluorouracil (5FU) and oxaliplatin. Therefore, the primary aim of the present study was to analyze the expression of gene resistance on tumors and CSC‑derived isolates from patients CRC. In the present study, adenocarcinomas of the colon and rectum (CRAC) were classified based on an in vitro adenosine triphosphate‑based chemotherapy response assay, as sensitive and resistant and the percentage of CD24 and CD44 markers are evaluated by immunohistochemistry. To isolate resistant colon‑CSC, adenocarcinoma tissues resistant to 5FU and oxaliplatin were evaluated. Finally, all samples were sequenced using a custom assay with chemoresistance‑associated genes to find a candidate gene on resistance colon‑CSC. Results showed that 59% of the CRC tissue analyzed was resistant and had a higher percentage of CD44 and CD24 markers. An association was found in the expression of some genes between the tumor‑resistant tissue and CSC. Overall, isolates of the CSC population CD44+ resistant to 5FU and oxaliplatin demonstrated different expression profiles; however, the present study was able to identify overexpression of the KRT‑18 gene, in most of the isolates. In conclusion, the results of the present study showed overexpression of KRT‑18 in CD44+ cells is associated with chemoresistance to 5FU and oxaliplatin in CRAC.

Glucose and Amino Acid Metabolic Dependencies Linked to Stemness and Metastasis in Different Aggressive Cancer Types

Malignant cells are commonly characterised by being capable of invading tissue, growing self-sufficiently and uncontrollably, being insensitive to apoptosis induction and controlling their environment, for example inducing angiogenesis. Amongst them, a subpopulation of cancer cells, called cancer stem cells (CSCs) shows sustained replicative potential, tumor-initiating properties and chemoresistance. These characteristics make CSCs responsible for therapy resistance, tumor relapse and growth in distant organs, causing metastatic dissemination. For these reasons, eliminating CSCs is necessary in order to achieve long-term survival of cancer patients. New insights in cancer metabolism have revealed that cellular metabolism in tumors is highly heterogeneous and that CSCs show specific metabolic traits supporting their unique functionality. Indeed, CSCs adapt differently to the deprivation of specific nutrients that represent potentially targetable vulnerabilities. This review focuses on three of the most aggressive tumor types: pancreatic ductal adenocarcinoma (PDAC), hepatocellular carcinoma (HCC) and glioblastoma (GBM). The aim is to prove whether CSCs from different tumour types share common metabolic requirements and responses to nutrient starvation, by outlining the diverse roles of glucose and amino acids within tumour cells and in the tumour microenvironment, as well as the consequences of their deprivation. Beyond their role in biosynthesis, they serve as energy sources and help maintain redox balance. In addition, glucose and amino acid derivatives contribute to immune responses linked to tumourigenesis and metastasis. Furthermore, potential metabolic liabilities are identified and discussed as targets for therapeutic intervention.

Altered Serum Metabolic Profile Assessed by Advanced 1H-NMR in Breast Cancer Patients

Simple Summary

Previously, our group demonstrated high FABP4 circulating levels in breast cancer (BC) patients. Moreover, increased cholesterol and triglycerides (TG) were found. To deeply analyse the lipid metabolism in our BC cohort, lipid and low molecular weight metabolomics processes are performed in 240 women (171 BC and 69 control women). This paper provides original data related to a novel link between TG-enriched particles and BC. The main result of this study is that TG-enriched particles and some branched amino acids, as well as tyrosine and alanine, are positively associated with BC. This suggests that BC patients have a different metabolic signature that could be used for better stratification and treatment. To our knowledge, this is the first time that advanced NMR profiling has been used to identify relevant and specifically altered lipid and amino acid metabolites in BC serum samples, which could be used for early and reliable diagnosis and prognosis.

Abstract

Background: Altered lipid metabolism has been described in some types of cancer. To analyse in depth the metabolic modifications in breast cancer patients, advanced 1H-nuclear magnetic resonance was performed in these patients. The main objective of this paper was to define a specific lipidomic signature for these cancer patients. Materials and methods: Serum from 240 women (171 breast cancer patients and 69 control women) were studied and analysed by nuclear magnetic resonance. Results: Triglyceride-enriched particles, specifically very low-density lipoprotein triglycerides, intermediate-density lipoprotein triglycerides, low-density lipoprotein triglycerides, and high-density lipoprotein triglycerides, were positively associated with breast cancer. Moreover, alanine, tyrosine, and branched amino acids were also associated with increased risk of breast cancer. Conclusions: Breast cancer patients showed a modified metabolome, giving a very interesting tool to draw different radar charts between control women and breast cancer patients. To our knowledge, this is the first time that advanced nuclear magnetic resonance profiling has been used to identify relevant and specifically altered lipid or amino acid metabolites in BC serum samples. The altered metabolic signature could be analysed for early and reliable BC patient diagnosis and prognosis.

Loss of tyrosine catabolic enzyme HPD promotes glutamine anaplerosis through mTOR signaling in liver cancer

The liver plays central roles in coordinating different metabolic processes, such as the catabolism of amino acids. In this study, we identify a loss of tyrosine catabolism and a concomitant increase in serum tyrosine levels during liver cancer development. Liver cells with disordered tyrosine catabolism, as exemplified by the suppression of a tyrosine catabolic enzyme 4-hydroxyphenylpyruvate dioxygenase (HPD), display augmented tumorigenic and proliferative potentials. Metabolomics profiling and isotope tracing reveal the metabolic reliance of HPD-silenced cells on glutamine, coupled with increased tricarboxylic acid cycle metabolites and their associated amino acid pools. Mechanistically, HPD silencing reduces ketone bodies, which regulate the proliferative and metabolic phenotypes via the AMPK/mTOR/p70S6 kinase pathway and mTOR-dependent glutaminase (GLS) activation. Collectively, our results demonstrate a metabolic link between tyrosine and glutamine metabolism, which could be exploited as a potentially promising anticancer therapy for liver cancer.

Molecular Subtypes of Oral Squamous Cell Carcinoma Based on Immunosuppression Genes Using a Deep Learning Approach

Background: The mechanisms through which immunosuppressed patients bear increased risk and worse survival in oral squamous cell carcinoma (OSCC) are unclear. Here, we used deep learning to investigate the genetic mechanisms underlying immunosuppression in the survival of OSCC patients, especially from the aspect of various survival-related subtypes. Materials and methods: OSCC samples data were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and OSCC-related genetic datasets with survival data in the National Center for Biotechnology Information (NCBI). Immunosuppression genes (ISGs) were obtained from the HisgAtlas and DisGeNET databases. Survival analyses were performed to identify the ISGs with significant prognostic values in OSCC. A deep learning (DL)-based model was established for robustly differentiating the survival subpopulations of OSCC samples. In order to understand the characteristics of the different survival-risk subtypes of OSCC samples, differential expression analysis and functional enrichment analysis were performed. Results: A total of 317 OSCC samples were divided into one inferring cohort (TCGA) and four confirmation cohorts (ICGC set, GSE41613, GSE42743, and GSE75538). Eleven ISGs (i.e., BGLAP, CALCA, CTLA4, CXCL8, FGFR3, HPRT1, IL22, ORMDL3, TLR3, SPHK1, and INHBB) showed prognostic value in OSCC. The DL-based model provided two optimal subgroups of TCGA-OSCC samples with significant differences (p = 4.91E-22) and good model fitness [concordance index (C-index) = 0.77]. The DL model was validated by using four external confirmation cohorts: ICGC cohort (n = 40, C-index = 0.39), GSE41613 dataset (n = 97, C-index = 0.86), GSE42743 dataset (n = 71, C-index = 0.87), and GSE75538 dataset (n = 14, C-index = 0.48). Importantly, subtype Sub1 demonstrated a lower probability of survival and thus a more aggressive nature compared with subtype Sub2. ISGs in subtype Sub1 were enriched in the tumor-infiltrating immune cells-related pathways and cancer progression-related pathways, while those in subtype Sub2 were enriched in the metabolism-related pathways. Conclusion: The two survival subtypes of OSCC identified by deep learning can benefit clinical practitioners to divide immunocompromised patients with oral cancer into two subpopulations and give them target drugs and thus might be helpful for improving the survival of these patients and providing novel therapeutic strategies in the precision medicine area.

Plasma metabolomic profile associated with fatigue in cancer patients

BACKGROUND

Metabolomics is the newest -omics methodology and allows for a functional snapshot of the biochemical activity and cellular state. The goal of this study is to characterize metabolomic profiles associated with cancer-related fatigue, a debilitating symptom commonly reported by oncology patients.

METHODS

Untargeted ultrahigh performance liquid chromatography/mass spectrometry metabolomics approach was used to identify metabolites in plasma samples collected from a total of 197 participants with or without cancer. Partial least squares-discriminant analysis (PLS-DA) was used to identify discriminant metabolite features, and diagnostic performance of selected classifiers was quantified using area under the receiver operating characteristics (AUROC) curve analysis. Pathway enrichment analysis was performed using Fisher's exact test and the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway database.

FINDINGS

The global metabolomics approach yielded a total of 1120 compounds of known identity. Significant metabolic pathways unique to fatigued cancer versus control groups included sphingolipid metabolism, histidine metabolism, and cysteine and methionine metabolism. Significant pathways unique to non-fatigued cancer versus control groups included inositol phosphate metabolism, primary bile acid biosynthesis, ascorbate and aldarate metabolism, starch and sucrose metabolism, and pentose and glucuronate interconversions. Pathways shared between the two comparisons included caffeine metabolism, tyrosine metabolism, steroid hormone biosynthesis, sulfur metabolism, and phenylalanine metabolism.

CONCLUSIONS

We found significant metabolomic profile differences associated with cancer-related fatigue. By comparing metabolic signatures unique to fatigued cancer patients with metabolites associated with, but not unique to, fatigued cancer individuals (overlap pathways) and metabolites associated with cancer but not fatigue, we provided a broad view of the metabolic phenotype of cancer-related fatigue.

Transcriptomic identification of HBx-associated hub genes in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignancies around the world. Among the risk factors involved in liver carcinogenesis, hepatitis B virus (HBV) X protein (HBx) is considered to be a key regulator in hepatocarcinogenesis. Whether HBx promotes or protects against HCC remains controversial, therefore exploring new HBx-associated genes is still important.

METHODS

HBx was overexpressed in HepG2, HepG2.2.15 and SMMC-7721 cell lines, primary mouse hepatocytes and livers of C57BL/6N mice. High-throughput RNA sequencing profiling of HepG2 cells with HBx overexpression and related differentially-expressed genes (DEGs), pathway enrichment analysis, protein-protein interaction networks (PPIs), overlapping analysis were conducted. In addition, Gene Expression Omnibus (GEO) and proteomic datasets of HBV-positive HCC datasets were used to verify the expression and prognosis of selected DEGs. Finally, we also evaluated the known oncogenic role of HBx by oncogenic array analysis.

RESULTS

A total of 523 DEGs were obtained from HBx-overexpressing HepG2 cells. Twelve DEGs were identified and validated in cells transiently transfected with HBx and three datasets of HBV-positive HCC transcription profiles. In addition, using the Kaplan-Meier plotter database, the expression levels of the twelve different genes were further analyzed to predict patient outcomes.

CONCLUSION

Among the 12 identified HBx-associated hub genes, HBV-positive HCC patients expressing ARG1 and TAT showed a good overall survival (OS) and relapse-free survival (RFS). Thus, ARG1 and TAT expression could be potential prognostic markers.