Objective:Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents,with a poor prognosis.Anchorage-dependent cell death(anoikis)has been proven to be indispensable in ...Objective:Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents,with a poor prognosis.Anchorage-dependent cell death(anoikis)has been proven to be indispensable in tumor metastasis,regulating the migration and adhesion of tumor cells at the primary site.However,as a type of programmed cell death,anoikis is rarely studied in osteosarcoma,especially in the tumor immune microenvironment.This study aims to clarify prognostic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma.Methods:Anoikis-related genes(ANRGs)were obtained from GeneCards.Clinical information and ANRGs expression profiles of osteosarcoma patients were sourced from the therapeutically applicable research to generate effective therapies and Gene Expression Omnibus(GEO)databases.ANRGs highly associated with tumor immune microenvironment were identified by the estimate package and the weighted gene coexpression network analysis(WGCNA)algorithm.Machine learning algorithms were performed to construct long-term survival predictive strategy,each sample was divided into high-risk and low-risk subgroups,which was further verified in the GEO cohort.Finally,based on single-cell RNA-seq from the GEO database,analysis was done on the function of signature genes in the osteosarcoma tumor microenvironment.Results:A total of 51 hub ANRGs closely associated with the tumor microenvironment were identified,from which 3 genes(MERTK,BNIP3,S100A8)were selected to construct the prognostic model.Significant differences in immune cell activation and immune-related signaling pathways were observed between the high-risk and low-risk groups based on tumor microenvironment analysis(all P<0.05).Additionally,characteristic genes within the osteosarcoma microenvironment were identified in regulation of intercellular crosstalk through the GAS6-MERTK signaling pathway.Conclusion:The prognostic model based on ANRGs and tumor microenvironment demonstrate good predictive power and provide more personalized treatment options for patients with osteosarcoma.展开更多
Objective Triple-negative breast cancer(TNBC)is the breast cancer subtype with the worst prognosis,and lacks effective therapeutic targets.Colony stimulating factors(CSFs)are cytokines that can regulate the production...Objective Triple-negative breast cancer(TNBC)is the breast cancer subtype with the worst prognosis,and lacks effective therapeutic targets.Colony stimulating factors(CSFs)are cytokines that can regulate the production of blood cells and stimulate the growth and development of immune cells,playing an important role in the malignant progression of TNBC.This article aims to construct a novel prognostic model based on the expression of colony stimulating factors-related genes(CRGs),and analyze the sensitivity of TNBC patients to immunotherapy and drug therapy.Methods We downloaded CRGs from public databases and screened for differentially expressed CRGs between normal and TNBC tissues in the TCGA-BRCA database.Through LASSO Cox regression analysis,we constructed a prognostic model and stratified TNBC patients into high-risk and low-risk groups based on the colony stimulating factors-related genes risk score(CRRS).We further analyzed the correlation between CRRS and patient prognosis,clinical features,tumor microenvironment(TME)in both high-risk and low-risk groups,and evaluated the relationship between CRRS and sensitivity to immunotherapy and drug therapy.Results We identified 842 differentially expressed CRGs in breast cancer tissues of TNBC patients and selected 13 CRGs for constructing the prognostic model.Kaplan-Meier survival curves,time-dependent receiver operating characteristic curves,and other analyses confirmed that TNBC patients with high CRRS had shorter overall survival,and the predictive ability of CRRS prognostic model was further validated using the GEO dataset.Nomogram combining clinical features confirmed that CRRS was an independent factor for the prognosis of TNBC patients.Moreover,patients in the high-risk group had lower levels of immune infiltration in the TME and were sensitive to chemotherapeutic drugs such as 5-fluorouracil,ipatasertib,and paclitaxel.Conclusion We have developed a CRRS-based prognostic model composed of 13 differentially expressed CRGs,which may serve as a useful tool for predicting the prognosis of TNBC patients and guiding clinical treatment.Moreover,the key genes within this model may represent potential molecular targets for future therapies of TNBC.展开更多
Regulatory T cells(Treg cells)are a specialized subset of CD4+T cells defined by expression of the lineage-specifying transcription factor FOXP3 and a potent capacity to maintain peripheral immune tolerance.The modern...Regulatory T cells(Treg cells)are a specialized subset of CD4+T cells defined by expression of the lineage-specifying transcription factor FOXP3 and a potent capacity to maintain peripheral immune tolerance.The modern concept of Tregs was catalyzed by Shimon Sakaguchi's identification of CD4+CD25+suppressive T cells and subsequent work establishing FOXP3 as a central determinant of Treg cell development and function;together with landmark FOXP3 genetic discoveries by Mary E.Brunkow and Fred Ramsdell,these advances transformed understanding of immune homeostasis and were recognized by the 2025 Nobel Prize in Physiology or Medicine.Under normal physiological conditions,FOXP3+Treg cells restrain autoreactive lymphocytes,prevent excessive inflammation,and shape antigen-presenting cell activity through contact-dependent pathways and suppressive cytokines,thereby protecting tissues from immune-mediated damage.Disruption of Treg abundance,stability,or suppressive capacity can therefore lead to immune dysregulation and disease.Over the past two decades,Treg cells have become a major focus of immunology because their roles are highly context-dependent.In autoimmune and chronic inflammatory diseases,impaired Treg cell function or insufficient Treg activity contributes to loss of tolerance and persistent tissue injury,supporting therapeutic approaches designed to enhance Treg cell number,stability,and suppressive potency.In contrast,many cancers exploit Treg cells by promoting their expansion,activation,and recruitment into the tumor microenvironment(TME),where they blunt antitumor immunity by suppressing cytotoxic T-cell priming and effector function,limiting dendritic cell activation,and fostering immune escape.In both settings,immune checkpoint pathways critically influence Treg cell biology.Beyond PD-1/PD-L1 and CTLA-4,emerging checkpoints and costimulatory receptors,including TIGIT,TIM-3,LAG-3,and OX40,modulate Treg cell generation,stability,and suppressive functions,thereby shaping the balance between tolerance and immunity.Meanwhile,immunometabolic adaptations further tune Treg cell fitness and function in inflamed tissues and tumors;lipid utilization and mitochondrial programs,among other metabolic axes,enable Treg cells to persist in nutrient-and oxygen-restricted microenvironments,while microenvironmental stress can drive functional remodeling or fragility in a subset-dependent manner.In this review,we summarize the discovery and defining biological features of Treg cells,highlight core suppressive mechanisms and regulatory circuits,and synthesize evidence for the dual roles of Treg cells in preventing autoimmunity yet enabling tumor immune evasion.We further outline current and emerging therapeutic strategies aimed at augmenting Treg cell activity to restore tolerance in autoimmune disease,or selectively depleting,functionally inhibiting,and reprogramming tumor-resident Treg cells to enhance cancer immunotherapy.Overall we discuss how deeper insight into Treg heterogeneity,checkpoint control,and immunometabolic regulation may enable more precise Treg celldirected interventions and inform next-generation immunotherapeutic combinations across immune-mediated and malignant diseases.展开更多
基金This work was supported by the National Natural Science Foundation(82172594 and 82373046)the Hunan Graduate Research Innovation Project(CX20230318),China.
文摘Objective:Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents,with a poor prognosis.Anchorage-dependent cell death(anoikis)has been proven to be indispensable in tumor metastasis,regulating the migration and adhesion of tumor cells at the primary site.However,as a type of programmed cell death,anoikis is rarely studied in osteosarcoma,especially in the tumor immune microenvironment.This study aims to clarify prognostic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma.Methods:Anoikis-related genes(ANRGs)were obtained from GeneCards.Clinical information and ANRGs expression profiles of osteosarcoma patients were sourced from the therapeutically applicable research to generate effective therapies and Gene Expression Omnibus(GEO)databases.ANRGs highly associated with tumor immune microenvironment were identified by the estimate package and the weighted gene coexpression network analysis(WGCNA)algorithm.Machine learning algorithms were performed to construct long-term survival predictive strategy,each sample was divided into high-risk and low-risk subgroups,which was further verified in the GEO cohort.Finally,based on single-cell RNA-seq from the GEO database,analysis was done on the function of signature genes in the osteosarcoma tumor microenvironment.Results:A total of 51 hub ANRGs closely associated with the tumor microenvironment were identified,from which 3 genes(MERTK,BNIP3,S100A8)were selected to construct the prognostic model.Significant differences in immune cell activation and immune-related signaling pathways were observed between the high-risk and low-risk groups based on tumor microenvironment analysis(all P<0.05).Additionally,characteristic genes within the osteosarcoma microenvironment were identified in regulation of intercellular crosstalk through the GAS6-MERTK signaling pathway.Conclusion:The prognostic model based on ANRGs and tumor microenvironment demonstrate good predictive power and provide more personalized treatment options for patients with osteosarcoma.
文摘Objective Triple-negative breast cancer(TNBC)is the breast cancer subtype with the worst prognosis,and lacks effective therapeutic targets.Colony stimulating factors(CSFs)are cytokines that can regulate the production of blood cells and stimulate the growth and development of immune cells,playing an important role in the malignant progression of TNBC.This article aims to construct a novel prognostic model based on the expression of colony stimulating factors-related genes(CRGs),and analyze the sensitivity of TNBC patients to immunotherapy and drug therapy.Methods We downloaded CRGs from public databases and screened for differentially expressed CRGs between normal and TNBC tissues in the TCGA-BRCA database.Through LASSO Cox regression analysis,we constructed a prognostic model and stratified TNBC patients into high-risk and low-risk groups based on the colony stimulating factors-related genes risk score(CRRS).We further analyzed the correlation between CRRS and patient prognosis,clinical features,tumor microenvironment(TME)in both high-risk and low-risk groups,and evaluated the relationship between CRRS and sensitivity to immunotherapy and drug therapy.Results We identified 842 differentially expressed CRGs in breast cancer tissues of TNBC patients and selected 13 CRGs for constructing the prognostic model.Kaplan-Meier survival curves,time-dependent receiver operating characteristic curves,and other analyses confirmed that TNBC patients with high CRRS had shorter overall survival,and the predictive ability of CRRS prognostic model was further validated using the GEO dataset.Nomogram combining clinical features confirmed that CRRS was an independent factor for the prognosis of TNBC patients.Moreover,patients in the high-risk group had lower levels of immune infiltration in the TME and were sensitive to chemotherapeutic drugs such as 5-fluorouracil,ipatasertib,and paclitaxel.Conclusion We have developed a CRRS-based prognostic model composed of 13 differentially expressed CRGs,which may serve as a useful tool for predicting the prognosis of TNBC patients and guiding clinical treatment.Moreover,the key genes within this model may represent potential molecular targets for future therapies of TNBC.
文摘Regulatory T cells(Treg cells)are a specialized subset of CD4+T cells defined by expression of the lineage-specifying transcription factor FOXP3 and a potent capacity to maintain peripheral immune tolerance.The modern concept of Tregs was catalyzed by Shimon Sakaguchi's identification of CD4+CD25+suppressive T cells and subsequent work establishing FOXP3 as a central determinant of Treg cell development and function;together with landmark FOXP3 genetic discoveries by Mary E.Brunkow and Fred Ramsdell,these advances transformed understanding of immune homeostasis and were recognized by the 2025 Nobel Prize in Physiology or Medicine.Under normal physiological conditions,FOXP3+Treg cells restrain autoreactive lymphocytes,prevent excessive inflammation,and shape antigen-presenting cell activity through contact-dependent pathways and suppressive cytokines,thereby protecting tissues from immune-mediated damage.Disruption of Treg abundance,stability,or suppressive capacity can therefore lead to immune dysregulation and disease.Over the past two decades,Treg cells have become a major focus of immunology because their roles are highly context-dependent.In autoimmune and chronic inflammatory diseases,impaired Treg cell function or insufficient Treg activity contributes to loss of tolerance and persistent tissue injury,supporting therapeutic approaches designed to enhance Treg cell number,stability,and suppressive potency.In contrast,many cancers exploit Treg cells by promoting their expansion,activation,and recruitment into the tumor microenvironment(TME),where they blunt antitumor immunity by suppressing cytotoxic T-cell priming and effector function,limiting dendritic cell activation,and fostering immune escape.In both settings,immune checkpoint pathways critically influence Treg cell biology.Beyond PD-1/PD-L1 and CTLA-4,emerging checkpoints and costimulatory receptors,including TIGIT,TIM-3,LAG-3,and OX40,modulate Treg cell generation,stability,and suppressive functions,thereby shaping the balance between tolerance and immunity.Meanwhile,immunometabolic adaptations further tune Treg cell fitness and function in inflamed tissues and tumors;lipid utilization and mitochondrial programs,among other metabolic axes,enable Treg cells to persist in nutrient-and oxygen-restricted microenvironments,while microenvironmental stress can drive functional remodeling or fragility in a subset-dependent manner.In this review,we summarize the discovery and defining biological features of Treg cells,highlight core suppressive mechanisms and regulatory circuits,and synthesize evidence for the dual roles of Treg cells in preventing autoimmunity yet enabling tumor immune evasion.We further outline current and emerging therapeutic strategies aimed at augmenting Treg cell activity to restore tolerance in autoimmune disease,or selectively depleting,functionally inhibiting,and reprogramming tumor-resident Treg cells to enhance cancer immunotherapy.Overall we discuss how deeper insight into Treg heterogeneity,checkpoint control,and immunometabolic regulation may enable more precise Treg celldirected interventions and inform next-generation immunotherapeutic combinations across immune-mediated and malignant diseases.
