OBJECTIVES: Hepatocellular carcinoma is one of the most common primary malignant tumors with the third highest mortality rate worldwide. This study aims to identify key genes associated with hepatocellular carcinoma prognosis using the Gene Expression Omnibus (GEO) database and provide a theoretical basis for discovering novel prognostic biomarkers for hepatocellular carcinoma. METHODS: Hepatocellular carcinoma-related datasets were retrieved from the GEO database. Differentially expressed genes (DEGs) were identified using the GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and key genes were identified using Cytoscape software. The University of Alabama at Birmingham Cancer Data Analysis Resource (UALCAN) was used to analyze the expression levels of key genes in normal and hepatocellular carcinoma tissues, as well as their associations with pathological grade, clinical stage, and patient survival. The Human Protein Atlas (THPA) was used to further validate the impact of key genes on overall survival. Expression levels of key genes in the blood of hepatocellular carcinoma patients were evaluated using the expression atlas of blood-based biomarkers in the early diagnosis of cancers (BBCancer). RESULTS: A total of 78 DEGs were identified from the GEO database. GO and KEGG analyses indicated that these genes may contribute to hepatocellular carcinoma progression by promoting cell division and regulating protein kinase activity. Sixteen key genes were screened via Cytoscape and validated using UALCAN and THPA. These genes were overexpressed in hepatocellular carcinoma tissues and were associated with disease progression and poor prognosis. Finally, BBCancer analysis showed that ASPM and NCAPG were also elevated in the blood of hepatocellular carcinoma patients. CONCLUSIONS This study identified 16 key genes as potential prognostic biomarkers for hepatocellular carcinoma, among which ASPM and NCAPG may serve as promising blood-based markers for hepatocellular carcinoma.
Humans ; Carcinoma, Hepatocellular/mortality* ; Liver Neoplasms/pathology* ; Prognosis ; Computational Biology/methods* ; Protein Interaction Maps/genetics* ; Biomarkers, Tumor/genetics* ; Gene Expression Regulation, Neoplastic ; Gene Expression Profiling ; Gene Ontology ; Databases, Genetic

Stathmin 1 (STMN1) is a microtubule-binding cytoplasmic phosphoprotein that promotes microtubule depolymerization or inhibits microtubule assembly, thereby regulating cytoskeletal organization and cell cycle progression. STMN1 is upregulated in a variety of malignant tumors, where it drives proliferation, invasion, metastasis, and angiogenesis through classic pathways such as nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), and ferroptosis. STMN1 can also modulate the function of immune cells, thereby influencing antitumor immunity. Clinical data show that its high expression correlates positively with tumor drug resistance and poor prognosis, suggesting that STMN1 has potential as a tumor biomarker and therapeutic molecular target with important clinical significance.
Humans ; Stathmin/metabolism* ; Neoplasms/genetics* ; Biomarkers, Tumor/metabolism* ; NF-kappa B/metabolism* ; Cell Proliferation ; Drug Resistance, Neoplasm

OBJECTIVES: To investigate the association of NUF2 expression with tumor prognosis and its regulatory role in tumor microenvironment. METHODS: We analyzed NUF2 expression, its prognostic value, and is immune-related functions across different cancer types using datasets from the Human Protein Atlas (HPA), TCGA, GTEx, CCLE, and TIMER. RT-qPCR, Western blotting, and immunohistochemistry were used to detect NUF2 expression in liver cancer cell lines and tissue and blood samples from patients with liver cancer. GO, KEGG, and GSEA analyses were conducted to explore the molecular mechanisms of NUF2 and its related genes, and a competitive endogenous RNA (ceRNA) network for NUF2 in liver cancer was constructed. RESULTS: NUF2 expression was upregulated in the tumor tissues of 27 cancers and was associated with clinical stages in several cancers. High NUF2 expressions were correlated with poor overall survival, disease-specific survival, progression-free survival, and disease-free survival of cancer patients. NUF2 expression levels were positively correlated with tumor mutational burden, microsatellite instability, infiltrating immune cells, immune cell marker genes and immune checkpoint genes in different cancers. RT-qPCR, Western blotting, and immunohistochemistry confirmed that NUF2 expression was upregulated in liver cancer cell lines and tumor tissues and blood samples of liver cancer patients, and was decreased significantly after operation. GO, KEGG and GSEA analyses indicated that NUF2 was involved in chromosome segregation and cell cycle and was associated with glycine, serine and threonine metabolism. CONCLUSIONS NUF2 expression is upregulated in 27 cancers and is associated with clinical stage and poor prognosis in some malignancies. NUF2 expression is closely correlated with immune cell infiltration in different cancers, suggesting its potential value for predicting immunotherapy response in these cancers.
Humans ; Prognosis ; Immunotherapy ; Tumor Microenvironment ; Liver Neoplasms/metabolism* ; Cell Line, Tumor ; Neoplasms/genetics* ; Gene Expression Regulation, Neoplastic ; Biomarkers, Tumor/genetics*

OBJECTIVES: To explore the potential of pyrroline-5-carboxylate reductase 1 (PYCR1) as a pan-cancer biomarker and investigate its expression, function, and clinical significance in bladder cancer (BLCA). METHODS: Bioinformatics analysis was conducted to evaluate the associations of PYCR1 with prognosis, immune microenvironment remodeling, tumor mutation burden (TMB), and microsatellite instability (MSI) in cancer patients. Using the TCGA-BLCA dataset, univariate and multivariate regression analyses were performed to assess the potential of PYCR1 as an independent prognostic risk factor for BLCA, and a clinical decision model was constructed. The IMvigor210 cohort was utilized to evaluate the potential of PYCR1 for independently predicting the efficacy of immunotherapy. The pRRophetic was employed to screen candidate chemotherapeutic agents for treating BLCA with high PYCR1 expression. The CMap-XSum algorithm and molecular docking techniques were used to explore and validate small molecule inhibitors of PYCR1. RESULTS: A high expression of PYCR1 was significantly associated with poor prognosis, immune cell infiltration, TMB and MSI in various tumors (r>0.3). PYCR1 was overexpressed in BLCA, and high PYCR1 expression was closely related to poor prognosis in BLCA patients (HR: 1.14, 95% CI: 1.02-1.68, P=0.006). The IC₅₀ of the anti-cancer drugs cetuximab, 5-fluorouracil, and doxorubicin increased significantly in BLCA cell lines with high PYCR1 expressions (P<0.0001). CONCLUSIONS High PYCR1 expression is an independent risk factor for poor prognosis in BLCA patients and can serve as a significant indicator for clinical decision-making as well as a marker for predicting sensitivity to chemotherapeutic agents and the efficacy of immunotherapy.
Humans ; Urinary Bladder Neoplasms/genetics* ; Immunotherapy ; Prognosis ; Pyrroline Carboxylate Reductases/metabolism* ; Biomarkers, Tumor/genetics* ; delta-1-Pyrroline-5-Carboxylate Reductase ; Microsatellite Instability ; Tumor Microenvironment ; Mutation ; Computational Biology ; Molecular Docking Simulation

OBJECTIVES: To investigate the prognostic significance of PDZ-binding kinase (PBK) in pan-cancer and its potential as a therapeutic target for pancreatic cancer. METHODS: PBK expression levels were investigated in 33 cancer types based on data from TCGA, GEO and CPTAC databases. RT-PCR and Western blotting were employed to examine PBK expression in clinical pancreatic cancer specimens and cell lines. The diagnostic and prognostic value of PBK in pancreatic cancer was evaluated using survival analysis, Cox regression analysis, ROC curve analysis, and clinical correlation studies. Gene enrichment and immune correlation analyses were conducted to explore the potential role of PBK in tumor microenvironment, and its correlation with drug sensitivity was investigated using GDSC and CTRP datasets. In pancreatic cancer BXPC-3 cells, the effects of lentivirus-mediated PBK knockdown on cell proliferation, migration, and invasion were examined using CCK-8, colony formation, and Transwell assays. The interaction between PBK and non-SMC condensin II complex subunit G2 (NCAPG2) was analyzed using co-immunoprecipitation and Western blotting. RESULTS: PBK was overexpressed in multiple cancer types, including pancreatic cancer. A high PBK expression was associated with a poor prognosis of the patients and correlated with immune infiltration and alterations in the tumor microenvironment. Elevated PBK expression was positively correlated with the sensitivity to MEK inhibitors (Trametinib) and EGFR inhibitors (Afatinib) but negatively with the sensitivity to Bcl-2 inhibitors (TW37) and niclosamide. In BXPC-3 cells, PBK knockdown significantly suppressed NCAPG2 expression and inhibited cell proliferation, migration, and invasion. Co-immunoprecipitation confirmed a direct binding between PBK and NCAPG2. CONCLUSIONS PBK is a key regulator of pancreatic cancer and interacts with NCAPG2 to promote tumor progression, suggesting its value as a potential biomarker and therapeutic target for pancreatic cancer.
Humans ; Pancreatic Neoplasms/genetics* ; Prognosis ; Biomarkers, Tumor/genetics* ; Cell Line, Tumor ; Cell Proliferation ; Adenocarcinoma/metabolism* ; Tumor Microenvironment ; Cell Movement ; Mitogen-Activated Protein Kinase Kinases

Mitochondria are the convergence point of multiple pathways that trigger programmed cell death (PCD). Mitochondrial-associated PCD (mtPCD) is involved in the pathogenesis of several diseases. However, the role of mtPCD in the prognostic prediction of cancers including non-small-cell lung cancer (NSCLC) remains to be investigated. Here, 12 mtPCD patterns were analyzed in transcriptomics, genomics, and clinical data collected from 4 datasets containing 977 patients. A risk-score assessment system containing 18 genes was established. We found that NSCLC patients with a high-risk score had a poorer prognosis. A nomogram was constructed by incorporating the risk score with clinical features. The risk score was further associated with clinicopathological information, tumor-mutation frequency, and immunotherapy responses. NSCLC patients with a high risk score had more Treg cells infiltration. However, these patients had higher tumor-mutation burden scores and may be more sensitive to immunotherapy. Moreover, receptor-interacting serine/threonine protein kinase 2 (RIPK2) was selected from mtPCD gene model for validation. We found that RIPK2 exhibited oncogenic function, and its expression level was inversely associated with the overall survival of NSCLC. Taken together, our results indicated the accuracy and practicability of the mtPCD gene model and RIPK2 in predicting the prognosis of NSCLC.
Humans ; Carcinoma, Non-Small-Cell Lung/pathology* ; Lung Neoplasms/pathology* ; Prognosis ; Male ; Female ; Nomograms ; Middle Aged ; Mitochondria/metabolism* ; Apoptosis/genetics* ; Mutation ; Biomarkers, Tumor/genetics* ; Aged

OBJECTIVE: Circadian rhythm disruption (CRD) is a risk factor that correlates with poor prognosis across multiple tumor types, including hepatocellular carcinoma (HCC). However, its mechanism remains unclear. This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity. METHODS: To quantify CRD, the HCC CRD score (HCCcrds) was developed. Using machine learning algorithms, we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort (n = 369), and the robustness of this method was validated. Furthermore, we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes. RESULTS: We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis. The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis, higher pathological grade, and advanced clinical stages, while the CRD-related subtype with low HCCcrds had better clinical outcomes. We also identified novel biomarkers for each subtype, such as nicotinamide n-methyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1. CONCLUSION We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers. Within these groups greater HCCcrds was associated with worse prognosis. This approach has the potential to improve prediction of an individual's prognosis, guide precision treatments, and assist clinical decision making for HCC patients. Please cite this article as: Li XJ, Chang L, Mi Y, Zhang G, Zhu SS, Zhang YX, et al. Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm. J Integr Med. 2025; 23(4): 445-456.
Humans ; Carcinoma, Hepatocellular/pathology* ; Liver Neoplasms/pathology* ; Circadian Rhythm/genetics* ; Prognosis ; Male ; Female ; Biomarkers, Tumor/genetics* ; Middle Aged ; Machine Learning ; Computational Biology

OBJECTIVE: To explore the correlation between chromosome 8 open reading frame 76 (C8orf76) and cyclin-dependent kinase 4 (CDK4) and the potential predictive effect of C8orf76 and CDK4 on the prognosis of colorectal cancer (CRC). METHODS: We constructed a protein-protein interaction network of C8orf76-related genes and analyzed the prognostic signatures of C8orf76 and CDK4. Clinicopathological features of C8orf76 and CDK4 were visualized using a nomogram. RESULTS: C8orf76 and CDK4 levels were positively correlated in two independent human CRC cohorts ( n = 83 and n = 597). A consistent positive correlation was observed between C8orf76 and CDK4 expression in the CRC cell lines. The nomogram included prognostic genes (C8orf76 and CDK4) and pathological N and M stages. The concordance index (C-index) in our cohort was 0.776, which suggests that the ability of the indicators to predict the overall survival of patients with CRC in our cohort was strong. CONCLUSION We found that C8orf76 was positively correlated with CDK4 in both the cohorts as well as in CRC cell lines. Therefore, C8orf76 and CDK4 can be used as potential biomarkers to predict the prognosis of CRC.
Humans ; Colorectal Neoplasms/diagnosis* ; Cyclin-Dependent Kinase 4/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/genetics* ; Aged ; Cell Line, Tumor ; Gene Expression Regulation, Neoplastic

Humans ; Colorectal Neoplasms/pathology* ; Pathology, Molecular/methods* ; Biomarkers, Tumor/genetics* ; Genetic Testing ; China

Objective To explore the clinical and immunological significance of CCDC97 in hepatocellular carcinoma (HCC). Methods Clinical data and RNA sequencing results from HCC patients were retrieved from TCGA and ICGC databases. Bioinformatics analysis and in vitro experiments were performed to investigate the role of CCDC97 in HCC. Results The expression level of CCDC97 was elevated in HCC patients and HCC cells, closely associated with pathological features and prognosis. CCDC97 was identified as a novel prognostic biomarker. It is linked to the spliceosome pathway, which is significantly active in tumors and potentially promotes carcinogenesis. CCDC97 is also highly expressed in various immune cells and is associated with microenvironment. Furthermore, knocking down CCDC97 in vitro suppressed cell migration, invasion, and proliferation. Conclusion CCDC97 plays a critical role in HCC progression and the immune microenvironment, making it a potential target for prognosis and therapeutic intervention.
Humans ; Carcinoma, Hepatocellular/metabolism* ; Liver Neoplasms/metabolism* ; Tumor Microenvironment/genetics* ; Cell Movement/genetics* ; Cell Proliferation ; Prognosis ; Cell Line, Tumor ; Gene Expression Regulation, Neoplastic ; Biomarkers, Tumor/genetics* ; Male