Effect of Semaglutide on High-Fat-Diet-Induced Liver Cancer in Obese Mice.

This study aims to investigate the impact of semaglutide on the expression of liver cancer proteins in obese mice induced by a high-fat diet. Sixteen obese mice were randomly divided into two groups: the high-fat diet group and the semaglutide group, each consisting of eight mice. Additionally, eight normal male mice were included as the control group. Serum samples were collected, and a differential expression analysis of total proteins in adipose tissue was performed using quantitative tandem mass spectrometry (TMT) in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Significant differential proteins were identified and subjected to a bioinformatics analysis. The findings revealed that these differential proteins, namely, integrin αV (ITGAV), laminin γ1 (LAMC1), fatty acid-binding protein 5 (FABP5), and lipoprotein lipase (LPL), regulate the occurrence and development of liver cancer by participating in the extracellular matrix (ECM) signaling pathway and the peroxisome proliferator-activated receptor (PPAR) signaling pathway. Notably, semaglutide can decelerate the progression of liver cancer by inducing the expression of ITGAV, LAMC1, FABP5, and LPL in the adipose tissue of obese mice.

Identification and validation of palmitoylation metabolism-related signature for liver hepatocellular carcinoma.

BACKGROUND: Protein S-palmitoylation is a reversible posttranslational modification widely involved in tumor progression. Nevertheless, the function of palmitoylation metabolism in prognosis and tumor microenvironment characteristics in liver hepatocellular carcinoma (LIHC) patients is not fully understood. METHODS: mRNA and clinical data of LIHC patients were obtained from the TCGA and ICGC databases. Consensus clustering was used to construct palmitoylation metabolism-related clusters. Univariate Cox and Lasso regression analyses were employed to establish a palmitoylation metabolism-related signature (PMS). ssGSEA was applied to evaluate the immune cell score in each LIHC sample. Functional enrichments were accessed through GO, KEGG and GSVA. Drug sensitivity data were downloaded from the GDSC database. RESULTS: Three palmitoylation metabolism-related clusters with different prognostic and immune infiltration characteristics were constructed in LIHC. We identified PMS with distinct survival, clinical, and tumor immune microenvironment characteristics. The high PMS group had a poorer prognosis, higher infiltration of immunosuppressive cells and higher expression of immune checkpoints. ZDHHC20 exerted a tumor-promoting role in LIHC and was significantly associated with immunosuppressive cells and immunosuppressive checkpoints. Additionally, in HepG-2 and SMCC-7721 cells, si-ZDHHC20 boosted apoptosis but decreased proliferation and migration when compared to si-NC. CONCLUSION: Our research revealed that PMS may accurately predict the prognosis and immune characteristics of LIHC patients. ZDHHC20 has significant clinical and immune relevance in LIHC and may contribute to the formulation of new targets for LIHC immunotherapy.

Fanconi Anemia Complementary Group A (FANCA) Facilitates the Occurrence and Progression of Liver Hepatocellular Carcinoma.

BACKGROUND: Liver hepatocellular carcinoma (LIHC) is a serious liver disease worldwide, and its pathogenesis is complicated. AIMS: This study investigated the potential role of FANCA in the advancement and prognosis of LIHC. METHODS: Public databases, quantitative reverse transcription polymerase chain reaction (qRT-PCR), western blot (WB) and immunohistochemistry (IHC) were employed to measure FANCA expression between tumor and normal samples. The relationship between FANCA expression and prognosis of LIHC patients were examined. Functional enrichment of FANCA-related genes was performed. Furthermore, univariate and multivariate analyses were conducted to determine the independent prognosis value of FANCA in LIHC. Finally, influence of FANCA knockout on the proliferation, migration, and invasion of HepG2 cell was validated with cloning formation, CCK8, and Transwell assays. RESULTS: Expression analysis presented that FANCA had high expression level in LIHC tissues and cells. Receiver operating characteristic (ROC) curve analysis showed that FANCA was of great diagnosis value in LIHC. Clinicopathological analysis revealed that FANCA was significantly greater expressed in the advanced stage than in the early stage of LIHC. Univariate, multivariate, and Kaplan-Meier survival analysis confirmed that high expression of FANCA was strongly associated with poor survival of LIHC patients. In addition, high level of FANCA in LIHC showed a negative association with immunoinfiltrated B cells, T cells, and stromal scores. Moreover, Knockout of FANCA significantly inhibited HepG2 cell proliferative activity, migration, and invasion ability. CONCLUSIONS: Our data revealed that high level of FANCA was closely associated with LIHC malignant progression, suggesting its potential utility as a diagnostic, predictive indicator, and therapeutic target.

A prognostic model for hepatocellular carcinoma patients based on polyunsaturated fatty acid-related genes.

OBJECTIVE: Polyunsaturated fatty acids (PUFAs) have attracted increasing attention for their role in liver cancer development. The objective of this study is to develop a prognosis prediction model for patients with liver cancer based on PUFA-related metabolic gene characteristics. METHOD: Transcriptome data and clinical data were obtained from public databases, while gene sets related to PUFAs were acquired from the gene set enrichment analysis (GSEA) database. Univariate Cox analysis was conducted on the training set, followed by LASSO logistic regression and multivariate Cox analysis on genes with p < .05. Subsequently, the stepwise Akaike information criterion method was employed to construct the model. The high- and low-risk groups were divided based on the median score, and the model's survival prediction ability, diagnostic efficiency, and risk score distribution of clinical features were validated. The above procedures were also validated in the validation set. Immune infiltration levels were evaluated using four algorithms, and the immunotherapeutic potential of different groups was explored. Significant enrichment pathways among different groups were selected based on the GSEA algorithm, and mutation analyses were conducted. Nomogram prognostic models were constructed by incorporating clinical factors and risk scores using univariate and multivariate Cox regression analysis, validated through calibration curves and clinical decision curves. Additionally, sensitivity analysis of drugs was performed to screen potential targeted drugs. RESULTS: We constructed a prognostic model comprising eight genes (PLA2G12A, CYP2C8, ABCCI, CD74, CCR7, P2RY4, P2RY6, and YY1). Validation across multiple datasets indicated the model's favorable prognostic prediction ability and diagnostic efficiency, with poorer grading and staging observed in the high-risk group. Variations in mutation status and pathway enrichment were noted among different groups. Incorporating Stage, Grade, T.Stage, and RiskScore into the nomogram prognostic model demonstrated good accuracy and clinical decision benefits. Multiple immune analyses suggested greater benefits from immunotherapy in the low-risk group. We predicted multiple targeted drugs, providing a basis for drug development. CONCLUSION: Our study's multifactorial prognostic model across multiple datasets demonstrates good applicability, offering a reliable tool for personalized therapy. Immunological and mutation-related analyses provide theoretical foundations for further research. Drug predictions offer important insights for future drug development and treatment strategies. Overall, this study provides comprehensive insights into tumor prognosis assessment and personalized treatment planning.

Exploring the Roles of Key Mediators IKBKE and HSPA1A in Alzheimer's Disease and Hepatocellular Carcinoma through Bioinformatics Analysis.

Recent studies have hinted at a potential link between Alzheimer's Disease (AD) and cancer. Thus, our study focused on finding genes common to AD and Liver Hepatocellular Carcinoma (LIHC), assessing their promise as diagnostic indicators and guiding future treatment approaches for both conditions. Our research utilized a broad methodology, including differential gene expression analysis, Weighted Gene Co-expression Network Analysis (WGCNA), gene enrichment analysis, Receiver Operating Characteristic (ROC) curves, and Kaplan-Meier plots, supplemented with immunohistochemistry data from the Human Protein Atlas (HPA) and machine learning techniques, to identify critical genes and significant pathways shared between AD and LIHC. Through differential gene expression analysis, WGCNA, and machine learning methods, we identified nine key genes associated with AD, which served as entry points for LIHC analysis. Subsequent analyses revealed IKBKE and HSPA1A as shared pivotal genes in patients with AD and LIHC, suggesting these genes as potential targets for intervention in both conditions. Our study indicates that IKBKE and HSPA1A could influence the onset and progression of AD and LIHC by modulating the infiltration levels of immune cells. This lays a foundation for future research into targeted therapies based on their shared mechanisms.

Pan-cancer analysis of SYNGR2 with a focus on clinical implications and immune landscape in liver hepatocellular carcinoma.

BACKGROUND: Synaptogyrin-2 (SYNGR2), as a member of synaptogyrin gene family, is overexpressed in several types of cancer. However, the role of SYNGR2 in pan-cancer is largely unexplored. METHODS: From the TCGA and GEO databases, we obtained bulk transcriptomes, and clinical information. We examined the expression patterns, prognostic values, and diagnostic value of SYNGR2 in pan-cancer, and investigated the relationship of SYNGR2 expression with tumor mutation burden (TMB), microsatellite instability (MSI), immune infiltration, and immune checkpoint (ICP) genes. The gene set enrichment analysis (GSEA) software was used to perform pathway analysis. Besides, we built a nomogram of liver hepatocellular carcinoma patients (LIHC) and validated its prediction accuracy. RESULTS: SYNGR2 was highly expressed in most cancers. The high expression of SYNGR2 significantly reduced the overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) in multiple types of cancer. Also, receiver operating characteristic (ROC) curve analysis demonstrated that SYNGR2 showed high accuracy in distinguishing cancerous tissues from normal ones. Moreover, SYNGR2 expression was correlated with TMB, MSI, immune scores, and immune cell infiltrations. We also analyzed the association of SYNGR2 with immunotherapy response in LIHC. Finally, a nomogram including SYNGR2 and pathologic T, N, M stage was built and exhibited good predictive power for the OS, DSS, and PFI of LIHC patients. CONCLUSION: Overall, SYNGR2 is a critical oncogene in various tumors. SYNGR2 participates in the carcinogenic progression, and may contribute to the immune infiltration in tumor microenvironment. Our study suggests that SYNGR2 can serve as a predictor related to prognosis in pan-cancer, especially LIHC.

Exploring the diagnostic value, prognostic value, and biological functions of NPC gene family members in hepatocellular carcinoma based on a multi-omics analysis.

Liver cancer is a cunning malignancy with a high incidence and mortality rate among cancers worldwide. The NPC gene family members (NPCs: NPC1, NPC2, and NPC1L1) are closely linked to the development of multiple cancers, but their role in liver cancer remains unclear. As a result, we must investigate their functions in liver hepatocellular carcinoma (LIHC). NPCs were significantly differentially expressed between normal and LIHC tissues, with a high mutation frequency in LIHC. The ROC curve analysis revealed that NPC1/NPC2 had high diagnostic and prognostic values in LIHC. NPC1 expression was also found to be negatively correlated with its methylation level. The differentially expressed genes between high and low NPC1 expression groups in LIHC were mainly related to channel activity, transporter complexes, and plasma membrane adhesion molecules. Additionally, NPC1 expression was significantly associated with multiple immune cells and immunization checkpoints. It was hypothesized that a TUG1/SNHG4-miR-148a-3p-NPC1 regulatory axis is associated with hepatocarcinogenesis. Finally, the protein expression of NPC1 in LIHC tissues and paraneoplastic tissues was detected, and NPC1-knockdown HepG2 cells (NPC1KO) inhibited the proliferation, migration, and invasion. This study helped to identify new prognostic markers and potential immunotherapeutic targets for LIHC and revealed the molecular mechanisms underlying NPC1 regulation in LIHC. The NPCs play a key role in the prognosis and diagnosis of LIHC and may be an important indicator for LIHC prognosis and diagnosis; NPC1 might be a potential therapeutic target in LIHC.

Anoikis-related signature in liver hepatocellular carcinoma defines the YBX1/SPP1 axis by machine learning strategies and valid experiments.

BACKGROUND: Liver hepatocellular carcinoma (LIHC) remains a malignant malignancy with a low cure rate. Anoikis is a newly recognized cancer hallmark. However, an Anoikis-related model has not been clarified in LIHC. METHODS: The Anoikis-related score in the present study was created using Survival Random Forest and least absolute shrinkage and selection operator (LASSO) machine learning algorithms. Anoikis-related scores with respect to mutation analysis, immunological analysis, function annotation, and medication prediction were all thoroughly investigated. RESULTS: The Anoikis-related score accurately predicted the patients' immunological activity, altered genes, and medication sensitivity. SPP1 immunological analysis, function annotation, medication prediction, and immunotherapy prediction were systematically investigated. SPP1 may effectively predict the outcomes of immunotherapy. SPP1 was revealed to be a mediator of LIHC cell proliferation and migration. A putative axis in LIHC was YBX1/SPP1. CONCLUSIONS: Clinical care and the treatment plan for patients with LIHC were anticipated to benefit significantly from the established Anoikis-related score.

Therapeutic effect and transcriptome-methylome characteristics of METTL3 inhibition in liver hepatocellular carcinoma.

Methyltransferase-like 3 (METTL3) is the key subunit of methyltransferase complex responsible for catalyzing N6-methyladenosine (m6A) modification on mRNA, which is the most prevalent post-transcriptional modification in eukaryotes. In this study, we utilized online databases to analyze the association between METTL3 expression and various aspects of tumorigenesis, including gene methylation, immunity, and prognosis. Our investigation revealed that METTL3 serves as a prognostic marker and therapeutic target for liver hepatocellular carcinoma (LIHC). Through experimental studies, we observed frequent upregulation of METTL3 in LIHC tumor tissue and cells. Subsequent inhibition of METTL3 using a novel small molecule inhibitor, STM2457, significantly impeded tumor growth in LIHC cell lines, spheroids, and xenograft tumor model. Further, transcriptome and m6A sequencing of xenograft bodies unveiled that inhibition of METTL3-m6A altered genes enriched in SMAD and MAPK signaling pathways that are critical for tumorigenesis. These findings suggest that targeting METTL3 represents a promising therapeutic strategy for LIHC.

Identification and in vitro and in vivo validation of the key role of GSDME in pyroptosis-related genes signature in hepatocellular carcinoma.

We used pyroptosis-related genes to establish a risk-score model for prognostic prediction of liver hepatocellular carcinoma (LIHC) patients. A total of 52 pyroptosis-associated genes were identified. Then, data for 374 LIHC patients and 50 normal individuals were acquired from the TCGA database. Through gene expression analyses, differentially expressed genes (DEGs) were determined. The 13 pyroptosis-related genes (PRGs) confirmed as potential prognostic factors through univariate Cox regression analysis were entered into Lasso and multivariate Cox regression to build a PRGs prognostic signature, containing four PRGs (BAK1, GSDME, NLRP6, and NOD2) determined as independent prognostic factors. mRNA levels were evaluated by qRT-PCR, while overall survival (OS) rates were assessed by the Kaplan-Meier method. Enrichment analyses were done to establish the mechanisms associated with differential survival status of LIHC patients from a tumor immunology perspective. Additionally, a risk score determined by the prognostic model could divide LIHC patients into low- and high-risk groups using median risk score as cut-off. A prognostic nomogram, derived from the prognostic model and integrating clinical characteristics of patients, was constructed. The prognostic function of the model was also validated using GEO, ICGC cohorts, and online databases Kaplan-Meier Plotter. Small interfering RNA-mediated knockdown of GSDME, as well as lentivirus-mediated GSDME knockdown, were performed to validate that knockdown of GSDME markedly suppressed growth of HCC cells both in vivo and in vitro. Collectively, our study demonstrated a PRGs prognostic signature that had great clinical value in prognosis assessment.

Translocation of Methionine Adenosyl Transferase MAT2A and Its Prognostic Relevance for Liver Hepatocellular Carcinoma.

Methionine adenosyl transferases (MATs) catalyze the synthesis of the biological methyl donor adenosylmethionine (SAM). Dysregulation of MATs has been associated with carcinogenesis in humans. We previously found that downregulation of the MAT1A gene enriches the protein-associated translation process and worsens liver hepatocellular carcinoma (LIHC) prognosis. We also discovered that subcellular localization of the MAT2A protein has independently prognostic relevance in breast cancer patients. The present study aimed to examined the clinical relevance of MAT2A translocation in human LIHC. Essential methionine cycle gene expressions in TCGA LIHC datasets were analyzed using Gene Expression Profiling Interactive Analysis 2 (GEPIA2). The protein expression pattern of MAT2A was determined in the tissue array of our own LIHC cohort (n = 261) using immuno-histochemistry, and the prognostic relevance of MAT2A protein's subcellular localization expression was examined using Kaplan-Meier survival curves. LIHC patients with higher MAT2A mRNA expression had a worse survival rate (p = 0.0083). MAT2A protein immunoreactivity was observed in both cytoplasm and nucleus fractions in the tissue array. Tumor tissues had elevated MAT2A protein expression in both cytoplasm and nucleus compared to their adjacent normal tissues. A higher cytoplasmic to nuclear MAT2A protein expression ratio (C/N) was found in female LIHC patients compared to that of male patients (p = 0.047). Kaplan-Meier survival curves showed that a lower MAT2A C/N correlated with poor overall survival in female LIHC patients (10-year survival rate: 29.2% vs. 68.8%, C/N ≤ 1.0 vs. C/N > 1.0, log-rank p = 0.004). Moreover, we found that specificity protein 1 (SP1) may have a potential interaction with nuclear MAT2A protein, using protein-protein interaction; this we found using the GeneMANIA algorithm. We explored the possible protective effects of the estrogen axis in LIHC using the Human Protein Atlas (HPA), and found evidence supporting a possible protective effect of estrogen-related protein ESSRG in LIHC. The localization of SP1 and MAT2 appeared to be inversely associated with ESRRG expression in LIHC. The present study demonstrated the translocation of MAT2A and its prognostic relevance in female LIHC patients. Our findings suggest the potential of estrogen in SP1 regulation and localization of MAT2A, as therapeutic modalities against in female LIHC patients.

The Prognostic and Therapeutic Role of Histone Acetylation Modification in LIHC Development and Progression.

Background and Objectives: The modification of histone acetylation plays a vital role in regulating tumor occurrence and development, but the interaction between histone acetylation modulator genes and the liver hepatocellular carcinoma (LIHC) microenvironment, as well as immunotherapy, has not been investigated. Materials and Methods: Analysis of all statistical data was carried out using R software (Version 4.2.0) and the online tool Sangerbox. Comprehensive bioinformatics analysis, including signature construction and validation, functional analyses, immune and genomic features analyses, and immunotherapy prediction analyses, were performed to explore the prognostic and therapeutic role of histone acetylation modulator genes in LIHC development and progression. Results: The LIHC cohort from The Cancer Genome Atlas (TCGA) database was selected as the training cohort; the GSE76427 cohort from the Gene Expression Omnibus (GEO) database and the LIRI-JP cohort from the International Cancer Genome Consortium (ICGC) database were selected as the validation cohorts. The histone acetylation modulator gene-based prognostic signature was constructed and validated successfully. Immune infiltration analysis showed that most immune cells and immune functions were enriched in patients with high histone acetylation risk scores (HARS). Additionally, high levels of checkpoint inhibitors (ICIs) and human leukocyte antigens (HLAs) were also observed in high HARS patients. Meanwhile, TIDE algorithm analysis was conducted to explore the relationship between HARS and immunotherapy response, and submap algorithm analysis was used for the verification of the results, from which we found that high HAPS patients were more likely to respond to immunotherapy. Conclusions: Our findings revealed that the histone acetylation modulator genes, particularly for KAT21, SIRT6, and HAT1, may have the potential to function as a new prognostic marker and therapeutic target for LIHC.

Identification of ZBTB9 as a potential therapeutic target against dysregulation of tumor cells proliferation and a novel biomarker in Liver Hepatocellular Carcinoma.

BACKGROUND: Zinc finger and bric-a-brac/tramtrack/broad (ZBTB) domain-containing proteins have been reported to be associated with many tumors' development. However, in tumor initiation and progression, the role of ZBTB9, one of the protein family, and its prognostic value were yet to be elucidated in Liver Hepatocellular Carcinoma (LIHC). METHODS: We used R software and online bioinformatics analysis tools such as GEPIA2, cBioPortal, TIMER2, Metascape, UALCAN, STRING, TISIDB, and COSMIC to investigate ZBTB9's characteristics and function in LIHC, including abnormal expression, carcinogenic role, related signaling pathways and prognostic value. Furthermore, cell experiments (such as formation, wound healing, and transwell assays) and analyses based on clinical samples (such as immunohistochemistry (IHC) and promoter methylation analysis) were conducted to verify pivotal conclusions. RESULTS: ZBTB9 was overexpressed in LIHC samples compared to adjacent normal tissues. Through the analysis of genomic alteration and promoter hypomethylation, the clinical value and etiology of abnormal expression of ZBTB9 were preliminarily exlpored. Subsequent evidence showed that it could result in tumor progression and poor prognosis via activating cell cycle, DNA repair, MYC, and KRAS-associated signaling pathways as well as rendering immune dysregulation. After the knockdown of ZBTB9, evidently inhibited capacities of tumor cells proliferation and migration were observed. These results together indicated that ZBTB9 could be a promising prognostic biomarker and had the potential value to offer novel therapeutic targets for LIHC treatment. CONCLUSIONS: ZBTB9 was identified as a novel biomarker to predict the prognosis and tumor progression in LIHC, and a promising therapeutic target to invert tumor development.

Integrative and Comprehensive Pan-Cancer Analysis of Lymphocyte-Specific Protein Tyrosine Kinase in Human Tumors.

Lymphocyte-specific protein tyrosine kinase (LCK) is common in a variety of hematologic malignancies but comparatively less common in solid tumors. This study aimed to explore the potential diagnostic and prognostic value of LCK across tumors through integrative and comprehensive pan-cancer analysis, as well as experimental validation. Multiple databases were used to explore the expression, alteration, prognostic value, association with immune infiltration, and potential functional pathways of LCK in pan-cancers. The results were further validated by western blotting and qPCR of patient samples as well as tumor cell lines. High LCK expression typically represents a better prognosis. Notably, drug sensitivity prediction of LCK identified P-529 as a candidate for drug development. Gene Annotations (GO) and KEGG analyses showed significant enrichment of PD-L1 and the T-cell receptor pathway. The results from patient samples and tumor cell lines confirmed these conclusions in LIHC. In conclusion, LCK is differentially expressed in multiple tumors and normal tissues. Further analysis highlighted its association with prognostic implications, pan-cancer genetic alterations, and immune signatures. Our data provide evidence for a diagnostic marker of LCK and the possible use of LCK as a target for the treatment of tumors.

METTL3-mediated m6A methylation of ASPM drives hepatocellular carcinoma cells growth and metastasis.

BACKGROUND: Abnormal spindle-like microcephaly (ASPM) has been proved to participate in tumor progression. However, the underlying mechanism of ASPM in liver hepatocellular carcinoma (LIHC) remains elusive. METHODS: The mRNA and protein expression were determined using Western blot and qRT-PCR, and the capacities of cells proliferation, migration, and invasion were evaluated by CCK-8, colony formation, wound healing, and transwell. MeRIP was performed to validate the interaction between ASPM and methyltransferase-like 3 (METTL3). RESULTS: Herein, we found that ASPM was significantly upregulated in LIHC, and the high expression of ASPM was associated with poor LIHC prognosis. Furthermore, ASPM knockdown could suppress LIHC cells proliferation, migration, and invasion, while ASPM overexpression exerted reverse effect. Mechanistically, we revealed that the N6-methyladenosine (m6A) modification of ASPM mRNA mediated by METTL3 promoted its expression in LIHC. More importantly, silencing METTL3 suppressed LIHC cells proliferation, migration, and invasion, which could be retained by ASPM overexpression. CONCLUSION: Collectively, our findings suggested that METTL3/ASPM axis could serve as a novel promising therapeutic candidate for LIHC.

Good or not good: Role of miR-18a in cancer biology.

miR-18a is a member of primary transcript called miR-17-92a (C13orf25 or MIR17HG) which also contains five other miRNAs: miR-17, miR-19a, miR-20a, miR-19b and miR-92a. This cluster as a whole shows specific characteristics, where miR-18a seems to be unique. In contrast to the other members, the expression of miR-18a is additionally controlled and probably functions as its own internal controller of the cluster. miR-18a regulates many genes involved in proliferation, cell cycle, apoptosis, response to different kinds of stress, autophagy and differentiation. The disturbances of miR-18a expression are observed in cancer as well as in different diseases or pathological states. The miR-17-92a cluster is commonly described as oncogenic and it is known as 'oncomiR-1', but this statement is a simplification because miR-18a can act both as an oncogene and a suppressor. In this review we summarize the current knowledge about miR-18a focusing on its regulation, role in cancer biology and utility as a potential biomarker.

Novel significant stage-specific differentially expressed genes in hepatocellular carcinoma.

BACKGROUND: Liver cancer is among top deadly cancers worldwide with a very poor prognosis, and the liver is a vulnerable site for metastases of other cancers. Early diagnosis is crucial for treatment of the predominant liver cancers, namely hepatocellular carcinoma (HCC). Here we developed a novel computational framework for the stage-specific analysis of HCC. METHODS: Using publicly available clinical and RNA-Seq data of cancer samples and controls and the AJCC staging system, we performed a linear modelling analysis of gene expression across all stages and found significant genome-wide changes in the log fold-change of gene expression in cancer samples relative to control. To identify genes that were stage-specific controlling for confounding differential expression in other stages, we developed a set of six pairwise contrasts between the stages and enforced a p-value threshold (< 0.05) for each such contrast. Genes were specific for a stage if they passed all the significance filters for that stage. The monotonicity of gene expression with cancer progression was analyzed with a linear model using the cancer stage as a numeric variable. RESULTS: Our analysis yielded two stage-I specific genes (CA9, WNT7B), two stage-II specific genes (APOBEC3B, FAM186A), ten stage-III specific genes including DLG5, PARI, NCAPG2, GNMT and XRCC2, and 35 stage-IV specific genes including GABRD, PGAM2, PECAM1 and CXCR2P1. Overexpression of DLG5 was found to be tumor-promoting contrary to the cancer literature on this gene. Further, GABRD was found to be signifincantly monotonically upregulated across stages. Our work has revealed 1977 genes with significant monotonic patterns of expression across cancer stages. NDUFA4L2, CRHBP and PIGU were top genes with monotonic changes of expression across cancer stages that could represent promising targets for therapy. Comparison with gene signatures from the BCLC staging system identified two genes, HSP90AB1 and ARHGAP42. Gene set enrichment analysis indicated overrepresented pathways specific to each stage, notably viral infection pathways in HCC initiation. CONCLUSIONS: Our study identified novel significant stage-specific differentially expressed genes which could enhance our understanding of the molecular determinants of hepatocellular carcinoma progression. Our findings could serve as biomarkers that potentially underpin diagnosis as well as pinpoint therapeutic targets.

KEAP1 overexpression is correlated with poor prognosis and immune infiltration in liver hepatocellular carcinoma.

Purpose: Liver hepatocellular carcinoma (LIHC) is the most common type of liver cancer, but there is a lack of effective indicators for its early diagnosis and prognosis, so we explored the role of KEAP1 in LIHC patients in this study. Methods: The Cancer Genome Atlas (TCGA) dataset was used to investigate the relationship between KEAP1 expression and clinicopathological features and prognosis of LIHC patients. KEAP1 expression related pathways were enriched by Gene Ontology (GO) and gene set enrichment analysis (GSEA). Besides, KEAP1 expression-related immune infiltration was performed by single-sample GSEA (ssGSEA), and function of immune cells was detected by flow cytometry. Results: It was found that KEAP1 expression was significantly increased and correlated with overall survival of LIHC patients. A total of 231 differentially expressed genes (DEGs) between LIHC patients with high- and low-KEAP1 expression were found, which associated with various biological pathways. Besides, KEAP1 expression was positively correlated with the infiltration level of T helper cells and Th2 cells but negatively correlated with DCs and cytotoxic cells. Functional analysis revealed that the expression of IL 4 in Th2 cells and CD107a, GrA and GrB in cytotoxic cells was significantly greater in LIHC patients than in HCs. In addition, KEAP1 expression was closely correlated with liver function in LIHC patients. Conclusion: Highly expressed KEAP1 was closely related to the diagnosis, prognosis, immune cell infiltration, and liver function of LIHC, which might promote the progression of LIHC through regulating cell development, signal transduction, and abnormal immune response. The current study partially revealed the role of KEAP1 in LIHC and provided a potential biomarker for the diagnosis, prognosis and treatment of LIHC.

Comprehensive analysis of PSMG3 in pan-cancer and validation of its role in hepatocellular carcinoma.

BACKGROUND: Proteasome assembly chaperone 3 (PSMG3), a subunit of proteasome, has been found to be associated with lung cancer. However, the role of PSMG3 in other cancers has not been elucidated. The objective of this study was to explore the immune role of PSMG3 in pan-cancer and confirm the oncogenic significance in liver hepatocellular carcinoma (LIHC). METHODS: We examined the differential expression of PSMG3 across various cancer types using data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. We investigated the prognostic value of PSMG3 and examined its relationship with tumor mutation burden (TMB), microsatellite instability (MSI), and immune infiltration. The functional enrichment analysis was performed to explore the potential molecular mechanism of PSMG3. To elucidate the biological function of PSMG3, we conducted in vitro experiments using liver cancer cell lines. RESULTS: PSMG3 was highly expressed in most cancers. The high PSMG3 expression value of PSMG3 was closely related to poor prognosis. We observed correlations between PSMG3 and TMB, and MSI immune infiltration. PSMG3 may be involved in metabolic reprogramming, cell cycle, and PPAR pathways. The over-expression of PSMG3 promoted the proliferation, migration, and invasion capabilities of liver cancer cells. CONCLUSION: Our study demonstrated that PSMG3 was a pivotal oncogene in multiple cancers. PSMG3 contributed to the progression and immune infiltration in pan-cancer, especially in LIHC.

Prognostic significance of LRPPRC and its association with immune infiltration in liver hepatocellular carcinoma.

BACKGROUND: Leucine rich pentatricopeptide repeat containing (LRPPRC) protein is a multifunctional protein involved in cell cycle progression and tumor development. However, its prognostic significance and association with immune infiltration in Liver hepatocellular carcinoma (LIHC) remain unclear. METHODS: We utilized transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases of LIHC patients to investigate the potential pro-cancer role of LRPPRC, including differential expression of LRPPRC in LIHC, prognostic value, clinicopathological features, immune cell infiltration relevance and function enrichment analysis. RESULTS: Our findings suggest that LRPPRC is upregulated in LIHC and exhibits correlations with survival, clinical stage, and tumor grade in LIHC patients. Additionally, immune infiltration analysis revealed significant negative correlations between LRPPRC expression and multiple tumor-infiltrating immune cells, including CTLs, DCs, pDCs, B cells, Th17 cells, neutrophils, T cells, Mast cells, Th1 cells, Tregs, and NK cells, whereas a significant positive correlation was observed with infiltration of Th2 cells, T helper cells and Tcms. Furthermore, functional enrichment analysis indicated that LRPPRC may be involved in G2m checkpoint, mitotic spindle, E2f targets, Wnt Beta catenin signaling, spermatogenesis and other processes.