This study aimed to investigate the regulatory effect and mechanism of thymopentin on the growth of subcutaneous hepatocellular carcinoma in mice. A subcutaneous tumor model of Hepa1-6 liver cancer in immunocompetent mice was constructed, with three randomly divided groups based on tumor volume: control group, low-dose thymopentin (TP5) group (10 mg/kg), and high-dose TP5 group (20 mg/kg), with 6 mice in each group. Drugs were administered, and the intervention effect of thymopentin on tumor growth was evaluated. Hepa1-6 cells were then cultured in vitro and treated with blank medium and TP5 of different concentrations (10, 100, 1000 ng/mL) for 72 hours. Cell viability was detected by sulforhodamine B (SRB) colorimetry. A subcutaneous tumor model of liver cancer LM3 in immunocompromised mice was constructed, with three randomly divided groups based on tumor volume: control group, TP5 group (20 mg/kg), and positive drug Sorafinib group (30 mg/kg). The intervention effect of thymopentin on the growth of subcutaneous tumors in immunocompromised mice was evaluated. Flow cytometry was used to analyze the changes in the proportion of T cells and myeloid-derived suppressor cells (MDSCs) in the tumor microenvironment 11 days after TP5 administration in the Hepa1-6 model. MDSCs were cultured in vitro and treated with TP5. The effect of TP5 on MDSCs was evaluated by detecting the levels of ROS, IL-6, and NO, which are effector molecules of MDSCs. The mouse subcutaneous liver cancer model was established again using C57BL/6N mice. After 10 days, they were randomly divided into four groups based on tumor volume: control group, low-dose TP5 group (10 mg/kg), high-dose TP5 group (20 mg/kg), and arginine-deficient TP5 group (15 mg/kg). Drugs were administered continuously for 11 days, and the intervention effect of arginine-deficient TP5 on tumor growth was evaluated based on tumor weight. Annexin-V staining was used to detect the impact of TP5 on T cell survival. The results showed that both low and high doses of TP5 inhibited the growth of subcutaneous liver cancer in immunocompetent mice (P < 0.05), yet TP5 had no direct inhibitory effect on the proliferation of tumor cells cultured in vitro. Besides, a high dose of TP5 could not inhibit the growth of subcutaneous liver cancer in immunocompromised mice. Furthermore, TP5 promoted the infiltration of CD4 and CD8 T cells but decreased MDSCs in the subcutaneous tumor microenvironment of immunocompetent mice. TP5 did not affect the levels of ROS, IL-6, and NO in MDSCs. Lastly, arginine-deficient TP5 could not inhibit the growth of subcutaneous liver cancer in immunocompetent mice. Accordingly, TP5 but not arginine-deficient TP5 promoted the increase in the proportion of viable CD4 and CD8 T cells cultured in vitro. These results suggest that TP5 may inhibit the growth of liver cancer by increasing T cell number in the liver cancer microenvironment.
thymopentin ; hepatocellular carcinoma ; tumor microenvironment ; arginine ; T cells

The circadian clock is a highly conserved timekeeping system in organisms, which maintains physiological homeostasis by precisely regulating periodic fluctuations in gene expression. Substantial clinical and experimental evidence has established a close association between circadian rhythm disruption and the development of various malignancies. Research has revealed characteristic alterations in the circadian gene expression profiles in tumor tissues, primarily manifested as a dysfunction of core clock components (particularly circadian locomotor output cycles kaput (CLOCK) and brain and muscle ARNT-like 1 (BMAL1)) and the widespread dysregulation of their downstream target genes. Notably, CLOCK demonstrates non-canonical oncogenic functions, including epigenetic regulation via histone acetyltransferase activity and the circadian-independent modulation of cancer pathways. This review systematically elaborates on the oncogenic mechanisms mediated by CLOCK/BMAL1, encompassing multidimensional effects such as cell cycle control, DNA damage response, metabolic reprogramming, and tumor microenvironment (TME) remodeling. Regarding the therapeutic strategies, we focus on cutting-edge approaches such as chrononutritional interventions, chronopharmacological modulation, and treatment regimen optimization, along with a discussion of future perspectives. The research breakthroughs highlighted in this work not only deepen our understanding of the crucial role of circadian regulation in cancer biology but also provide novel insights for the development of chronotherapeutic oncology, particularly through targeting the non-canonical functions of circadian proteins to develop innovative anti-cancer strategies.
Humans ; ARNTL Transcription Factors/physiology* ; Neoplasms/therapy* ; CLOCK Proteins/physiology* ; Circadian Clocks/genetics* ; Animals ; Circadian Rhythm/genetics* ; Tumor Microenvironment ; Epigenesis, Genetic ; Gene Expression Regulation, Neoplastic

Osteosarcoma (OS), chondrosarcoma (CS), and Ewing sarcoma (ES) represent primary malignant bone tumors and pose significant challenges in oncology research and clinical management. Conventional research methods, such as two-dimensional (2D) cultured tumor cells and animal models, have limitations in recapitulating the complex tumor microenvironment (TME) and often fail to translate into effective clinical treatments. The advancement of three-dimensional (3D) culture technology has revolutionized the field by enabling the development of in vitro constructed bone tumor models that closely mimic the in vivo TME. These models provide powerful tools for investigating tumor biology, assessing therapeutic responses, and advancing personalized medicine. This comprehensive review summarizes the recent advancements in research on 3D tumor models constructed in vitro for OS, CS, and ES. We discuss the various techniques employed in model construction, their applications, and the challenges and future directions in this field. The integration of advanced technologies and the incorporation of additional cell types hold promise for the development of more sophisticated and physiologically relevant models. As research in this field continues to evolve, we anticipate that these models will play an increasingly crucial role in unraveling the complexities of malignant bone tumors and accelerating the development of novel therapeutic strategies.
Bone Neoplasms/pathology* ; Humans ; Osteosarcoma/pathology* ; Tumor Microenvironment ; Sarcoma, Ewing/pathology* ; Chondrosarcoma/pathology* ; Animals ; Cell Culture Techniques/methods* ; Cell Culture Techniques, Three Dimensional/methods* ; Cell Line, Tumor

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 expression of hexokinase 2 (HK2) in colorectal cancer (CRC) and its possible mechanisms for regulating tumor cell behaviors and tumor immune microenvironment. METHODS: We analyzed HK2 expression in CRC and its impact on patient prognosis and tumor immune microenvironment using public databases. HK2 expression was also examined in 8 CRC and paired adjacent tissues using immunohistochemistry, Western blotting and RT-qPCR. In cultured CRC cell lines CT26 and HCT116 with low HK2 expression, the effects of lentivirus-mediated HK2 overexpression and JAK/STAT3 inhibitors on cell proliferation, migration, and invasion were assessed using CCK-8 assay, colony formation assay and Transwell assay and in a subcutaneous tumor-bearing mouse model; the changes were also observed in MC38 and CACO2 cells with high HK2 expressions following treatment with HK2 inhibitor 3-BP. Western blotting was performed to verify the relationship between HK2 and JAK/STAT signaling pathway protein expressions. RESULTS: Informatics analyses suggested that HK2 expression was significantly higher in CRC tissues than in adjacent tissues (P<0.001), and patients with high HK2 expressions had worse prognosis (P=0.09). In the 8 clinical CRC tissues, HK2 expressions were significantly higher in the tumor tissues than in the adjacent tissues (P<0.01). In CT26 and HCT116 cells, HK2 overexpression significantly enhanced cell proliferation, migration and invasion, while in HK2-overexpressing MC38 and CACO2 cells, inhibiting HK2 with 3-BP strongly suppressed these changes. HK2 overexpression promoted STAT3 phosphorylation, and JAK/STAT3 inhibitors effectively suppressed tumor cell proliferation, migration and invasion. TIMER and MCPcounter analyses indicated correlations between HK2 and immune cells, and TCGA and GEO analyses suggested significant positive correlations between HK2 and the immune checkpoints including PDCD1. CONCLUSIONS HK2 is upregulated in CRC to promote tumor cell proliferation, migration and invasion possibly by activating the JAK-STAT signaling pathway and modulating tumor immune microenvironment.
Humans ; Colorectal Neoplasms/metabolism* ; Cell Proliferation ; Hexokinase/genetics* ; Tumor Microenvironment ; Cell Movement ; Signal Transduction ; Animals ; STAT3 Transcription Factor/metabolism* ; Mice ; Neoplasm Invasiveness ; Cell Line, Tumor ; Janus Kinases/metabolism* ; HCT116 Cells ; Caco-2 Cells

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 explore the association of the expression of WW domain-containing ubiquitin E3 ligase 1 (WWP1) with immune infiltration in tumor microenvironment (TME) of ovarian cancer. METHODS: Ovarian cancer patient data from The Cancer Genome Atlas (TCGA) were used to analyze the association of WWP1 expression with patient prognosis. TISCH2 was utilized to analyze the changes in immune cell subtypes in TME of metastatic tumor and after chemotherapy. The impact of WWP1 on immune cell infiltration, somatic copy number alterations of WWP1 and evolution of immune cell subtypes was evaluated using TIMER and TIGER pseudo-time analysis. A deep learning model was used to analyze TCGA pathological images to investigate the effect of WWP1 on TME of ovarian cancer. RNA-seq analysis was conducted to identify the differentially expressed genes in WWP1-overexpressing SKOV3 cells and validate immune infiltration. Multicolor immunofluorescence assay was used to analyze the immune markers in SKOV3 and SKOV3/DDP cell xenografts in nude mice. RESULTS: The patients with high WWP1 expression levels had significantly lower overall survival rate (P=0.0012). High WWP1 expression levels and Stage IV disease were both associated with a poor prognosis (P<0.05). In metastatic ovarian cancer or after chemotherapy, the percentages of malignant tumor cells and tumor-associated fibroblasts increased in the TME, accompanied by elevated WWP1 levels. WWP1 expression level was positively correlated with pro-tumorigenic immunosuppressive cells (r=0.1323-0.3955, P<0.05) and negatively with tumor-inhibiting immune cells (r=-0.1949- -0.1333, P<0.05). Specific copy number alterations of WWP1 also influenced CD8⁺ T cell percentage and neutrophil infiltration levels in the TME. RNA-seq analysis of WWP1-overexpressing SKOV3 cells and immunofluorescence assay of the tumor-bearing mice yielded findings consistent with those of bioinformatics analysis. CONCLUSIONS WWP1 may serve as a prognostic biomarker and a potential target for immune regulation in the TME of ovarian cancer.
Female ; Ovarian Neoplasms/genetics* ; Humans ; Ubiquitin-Protein Ligases/metabolism* ; Tumor Microenvironment/immunology* ; Animals ; Mice ; Cell Line, Tumor ; Mice, Nude ; Prognosis ; Gene Expression Regulation, Neoplastic

OBJECTIVES: To explore the key role of myeloid-derived suppressive cells (MDSCs) in pre-metastatic niche (PMN) and analyze their interrelationships with the main components in the microenvironment using a mathematical model. METHODS: Mathematical descriptions were used to systematically analyze the functions of MDSCs in tumor metastasis and elucidate their association with the major components (vascular endothelial cells, mesenchymal stromal cells, and cancer-associated macrophages) contributing to the formation of the pre-metastatic microenvironment. Based on the formation principle of the pre-metastatic microenvironment of tumors, the key biological processes were assumed to construct a coupled partial differential diffusion equation model. The existence and uniqueness of the model solutions were investigated using approximation methods, the qualitative theory of partial differential equations and Banach's immovable point theorem, and numerical simulations were carried out by differential numerical methods to verify the reliability and accuracy of the model. RESULTS: The existence and uniqueness of the local and overall solutions of the model were proved using the approximation method, the qualitative theory of partial differential equations and Banach's immovable point theorem in combination with the regularity estimation of the local solutions and the embedding inequality. Numerical simulation results further validated the reliability of the model and demonstrated the important role of MDSCs in the pre-metastatic microenvironment of tumors, especially in angiogenesis and immunosuppression. CONCLUSIONS This study reveals the important functions of MDSCs in the pre-metastatic microenvironment of tumors through mathematical modeling and numerical simulation, which provides an important theoretical basis for understanding the mechanism of tumor metastasis and devising cancer treatment strategies.
Tumor Microenvironment ; Myeloid-Derived Suppressor Cells ; Neoplasm Metastasis ; Humans ; Models, Biological ; Models, Theoretical ; Neoplasms/pathology*

OBJECTIVES: To construct a nomogram for predicting the efficacy of immune checkpoint inhibitors (ICIs) in advanced non-small cell lung cancer (aNSCLC) by integrating chest CT radiomics signature that reflects the tumor microenvironment (TME) and clinical parameters of the patients. METHODS: Transcriptomic and CT imaging data from TCGA, GEO and TCIA databases were integrated for weighted gene co-expression network analysis (WGCNA) of the GEO cohort to identify the immunotherapy-related genes (IRGs) associated with ICIs response. A prognostic model was built using these IRGs in the TCGA cohort to assess immune microenvironment features across different risk groups. Radiomics features were extracted from TCIA lung_3 cohort using PyRadiomics, and 94 features showing strong association with IRGs (|r|>0.4) were selected. A retrospective cohort consisting of 210 aNSCLC patients receiving first-line ICIs at Guangdong Provincial People's Hospital was analyzed and divided into training (n=147) and validation (n=63) groups. Least absolute shrinkage and selection operator was used for radiomic features selection, and logistic regression was applied to construct a combined clinical-radiomic model and nomogram for predicting ICIs therapy response. The performance of the model was evaluated using ROC curve, calibration curve, and decision curve analysis. RESULTS: WGCNA identified 84 IRGs enriched in immune activation pathways. The combined model outperformed individual models in both the training (AUC=0.725, 95% CI: 0.644-0.807) and validation cohorts (AUC=0.706, 95% CI: 0.577-0.836). Calibration curve and decision curve analyses confirmed the clinical efficacy of the nomogram for predicting ICIs therapy response in aNSCLC patients. CONCLUSIONS The genomic-radiomic-clinical multidimensional predictive framework established in this study provides an interpretable biomarker combination and clinical decision-making tool for evaluating ICIs efficacy in aNSCLC, potentially facilitating personalized immunotherapy decision-making.
Humans ; Carcinoma, Non-Small-Cell Lung/therapy* ; Tumor Microenvironment ; Lung Neoplasms/therapy* ; Immunotherapy ; Tomography, X-Ray Computed ; Nomograms ; Retrospective Studies ; Immune Checkpoint Inhibitors/therapeutic use* ; Prognosis ; Male ; Female ; Radiomics

OBJECTIVES: To establish a prognostic model for primary liver cancer (PLC) using bioinformatics methods. METHODS: Based on the data from 404 patients in the Cancer Genome Atlas (TCGA) database, we constructed a prognostic model integrating the differentially expressed genes, anoikis, and immune-related genes (DAIs) using univariate Cox regression and the LASSO-Cox approach. The predictive ability of the model was evaluated using Kaplan-Meier method and receiver-operating characteristic curves, and a nomogram was developed to facilitate its clinical applications. Gene set enrichment analysis (GSEA) was performed to explore the associated pathways and relationship between the DAIs and the tumor immune microenvironment, and the half-maximal inhibitory concentration (IC₅₀) of liver cancer drugs was calculated using the "pRRophetic" R package. We also detected the expression of SEMA7A in paired tumor and adjacent tissues from liver cancer patients. RESULTS: We constructed and validated a prognostic model based on 7 DAIs (NR4A3, SEMA7A, IL11, AR, BIRC5, EGF, and SPP1), and obtained consistent results in both the TCGA training cohort and GEO validation cohort (GSE14520), where the patients in the low-risk group were characterized by more favorable clinical outcomes and immune status. By integrating this prognostic signature with clinical information, a composite nomogram was generated. Somatic mutation analysis showed that TTN, TP53, and CTNNB1 mutations accounted for the largest proportion of total mutations, and the patients in the low-risk-low-TMB group had higher survival rate. Drug sensitivity analysis revealed differences in sensitivity to chemotherapeutic agents between high- and low-risk groups and between TP53 mutations and non-mutations. In clinical tissue specimens, SEMA7A expression was significantly higher in liver cancer tissues than in the adjacent tissues. CONCLUSIONS We established a new prognostic model based on DAIs for predicting clinical outcomes and therapeutic response of patients with primary liver cancer.
Humans ; Liver Neoplasms/diagnosis* ; Prognosis ; Anoikis ; Nomograms ; Computational Biology ; Tumor Microenvironment ; Semaphorins/metabolism*