Global Characterization of Metabolic Genes Regulating Survival and Immune Infiltration in Osteosarcoma.
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ABSTRACT:
SUBMITTER: Zhu Z
PROVIDER: S-EPMC8793845 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe Golgi apparatus (GA) is crucial for protein synthesis and modification, and regulates various cellular processes. Dysregulation of GA can lead to pathological conditions like neoplastic growth. GA-related genes (GARGs) mutations are commonly found in cancer, contributing to tumor metastasis. However, the expression and prognostic significance of GARGs in osteosarcoma are yet to be understood.MethodsGene expression and clinical data of osteosarcoma patients were obtained from the TARGET and GEO databases. A consensus clustering analysis identified distinct molecular subtypes based on GARGs. Discrepancies in biological processes and immunological features among the subtypes were explored using GSVA, ssGSEA, and Metascape analysis. A GARGs signature was constructed using Cox regression. The prognostic value of the GARGs signature in osteosarcoma was evaluated using Kaplan-Meier curves and a nomogram.ResultsTwo GARG subtypes were identified, with Cluster A showing better prognosis, immunogenicity, and immune cell infiltration than Cluster B. A novel risk model of 3 GARGs was established using the TARGET dataset and validated with independent datasets. High-risk patients had poorer overall survival, and the GARGs signature independently predicted osteosarcoma prognosis. Combining risk scores and clinical characteristics in a nomogram improved prediction performance. Additionally, we discovered Stanniocalcin-2 (STC2) as a significant prognostic gene highly expressed in osteosarcoma and potential disease biomarker.ConclusionsOur study revealed that patients with osteosarcoma can be divided into two GARGs subgroups. Furthermore, we have developed a GARGs prognostic signature that can accurately forecast the prognosis of osteosarcoma patients.
| S-EPMC11006476 | biostudies-literature
Project description:This work aimed to investigate tumor-infiltrating immune cells (TIICs) and immune-associated genes in the tumor microenvironment of osteosarcoma. An algorithm known as ESTIMATE was applied for immune score assessment, and osteosarcoma cases were assigned to the high and low immune score groups. Immune-associated genes between these groups were compared, and an optimal immune-related risk model was built by Cox regression analyses. The deconvolution algorithm (referred to as CIBERSORT) was applied to assess 22 TIICs for their amounts in the osteosarcoma microenvironment. Osteosarcoma cases with high immune score had significantly improved outcome (P<0.01). The proportions of naive B cells and M0 macrophages were significantly lower in high immune score tissues compared with the low immune score group (P<0.05), while the amounts of M1 macrophages, M2 macrophages, and resting dendritic cells were significantly higher (P<0.05). Important immune-associated genes were determined to generate a prognostic model by Cox regression analysis. Interestingly, cases with high risk score had poor outcome (P<0.01). The areas under the curve (AUC) for the risk model in predicting 1, 3 and 5-year survival were 0.634, 0.781, and 0.809, respectively. Gene set enrichment analysis suggested immunosuppression in high-risk osteosarcoma patients, in association with poor outcome.
| S-EPMC7066877 | biostudies-literature
Project description:BackgroundsOsteosarcomas are one of the most common primary malignant tumors of bone. It primarily occurs in children and adolescents, with the second highest incidence among people over 50 years old. Although there were immense improvements in the survival of patients with osteosarcoma in the past 30 years, targetable mutations and agents of osteosarcomas still have been generally not satisfactory. Therefore, it is of great importance to further explore the highly specialized immune environment of bone, genes related to macrophage infiltration and potential therapeutic biomarkers and targets.MethodsThe 11 expression data sets of OS tissues and the 11 data sets of adjacent non-tumorous tissues available in the GEO database GSE126209 were used to conduct immune infiltration analysis. Then, through WGCNA analysis, we acquired the co-expression modules related to Mast cells activated and performed the GO and KEGG enrichment analysis. Next, we did the survival prognosis analysis and plotted a survival curve. Finally, we analyzed the COX multivariate regression of gene expression on clinical parameters and drew forest maps for visualization by the forest plot package.ResultsOS disease-related immune cell populations, mainly Mast cells activated, have higher cell content (p = 0.006) than the normal group. Then, we identified co-expression modules related to Mast cells activated. In sum, a total of 822 genes from the top three strongest positive correlation module MEbrown4, MEdarkslateblue and MEnavajowhite2 and the strongest negative correlation module MEdarkturquoise. From that, we identified nine genes with different levels in immune cell infiltration related to osteosarcoma, eight of which including SORBS2, BAIAP2L2, ATAD2, CYGB, PAMR1, PSIP1, SNAPC3 and ZDHHC21 in their low abundance have higher disease-free survival probability than the group in their high abundances.ConclusionThese results could assist clinicians to select targets for immunotherapies and individualize treatment strategies for patients with OS.
| S-EPMC8684084 | biostudies-literature
Project description:Chemokine receptors have a crucial role in regulating tumor mediating immunity and are also implicated in the prognosis of some cancers. Here, the association between CXC chemokine receptors (CXCR2-5) and prognosis in osteosarcoma was studied. Differences between CXCR2, CXCR3, CXCR4, and CXCR5 expression and overall survival (OS) and event-free survival (EFS) were compared using Kaplan-Meier analyses. The associations of CXCR3 expression with clinical features and the prognosis were also analyzed. The signaling pathways modulated by CXCR3 were investigated. The correlations between CXCR3 and immune infiltrates were investigated. The expression of CXCR2, CXCR4, and CXCR5 was not associated with the prognosis, but CXCR3 low expression was correlated with worse OS and EFS of osteosarcoma, especially for female, patients aged less than 15.1 years, or patients without metastasis. Low CXCR3 expression was related to tumor site and histologic response (P<0.05), but not associated with other clinical characteristics. Multivariate Cox analysis revealed that CXCR3 remained independently associated with the prognosis, especially for OS (hazard ratio (HR) = 3.26, 95% CI = 1.15-9.24, P=0.026). The cell adhesion, apoptosis, metabolism, KRAS, P53, NOTCH, reactive oxygen species (ROS), PI3K/Akt/mTOR, vascular endothelial growth factor (VEGF), inflammation, and immune-related pathways such as IL-6/JAK/STAT3, TNF-α via NF-κB, Toll/NOD-like receptor, and complement were modulated by CXCR3. CXCR3 expression showed an especially positive correlation with immune infiltration of T cells CD8, macrophages M1, plasma cells, and NK cells activated. CXCR3 may be an independent risk factor for the prognosis and is most likely to benefit from immunotherapy in osteosarcoma.
| S-EPMC6851512 | biostudies-literature
Project description:Osteosarcoma is the most common malignant bone tumor in adolescents and young adults, and identifying biomarkers for prognosis and therapy is necessary. Bone morphogenetic protein receptor 2 (BMPR2) is involved in various cellular functions, including cell adhesion, proliferation and invasion, inflammation, apoptosis and metastatic spread. However, the correlation between BMPR2 expression levels and prognosis and tumor-infiltrating immune cells in osteosarcoma is not well understood. In the present study, the expression level of BMPR2 was investigated using the Oncomine and R2 databases. The association between the expression level of BMPR2 and the clinical prognosis of patients with cancer was analyzed using the R2 database. The relationship between the expression level of BMPR2 and immune cell infiltration in the stroma of osteosarcoma was assessed using the Tumor Immune Estimation Resource (TIMER) and CIBERSORT. The correlations between BMPR2 expression level and infiltrated immune cell gene marker sets in osteosarcoma were validated in the TIMER and R2 databases. Analysis of a cohort of patients with osteosarcoma revealed that BMPR2 expression was significantly higher in osteosarcoma compared with in normal tissue and was correlated with poor prognosis. M0 macrophages, M2 macrophages, resting mast, γ δ T and CD8+ T cells were the top five immune cells with the highest degrees of infiltration in osteosarcoma. In addition, BMPR2 expression level showed a significant negative correlation with the gene markers of CD8+ T cells, monocytes and M2 macrophages. Low levels of infiltrating CD8+ T cells, monocytes or M2 macrophages in osteosarcoma was significantly associated with poor survival. These data suggested that CD8+ T cells, monocytes and M2 macrophages play significant roles in the establishment of the immune microenvironment of osteosarcoma. High BMPR2 expression was associated with poor prognosis and low infiltration of CD8+ T cells, monocytes and M2 macrophages in osteosarcoma. Hence, BMPR2 can be considered a biomarker of the immune infiltration, metastasis and prognosis of osteosarcoma.
| S-EPMC7988701 | biostudies-literature
Project description:Recent studies have shown that tumor stemness has biological significance in tumorigenicity and tumor progression. However, the characteristics of TME immune infiltration in osteosarcoma mediated by the combined effects of multiple cancer stem cell-related genes remain unknown.MethodsIn this study, we identified different cancer stem cell-associated subtypes in osteosarcoma based on 25 cancer stem cell-associated genes by consensus clustering analysis, and we comprehensively evaluated the association between these subtypes and immunocytes infiltration in the TME. The cancer stem cell (CSC) score was constructed to quantify the stemness of individual tumors.ResultsWe performed a comprehensive evaluation of 218 osteosarcoma patients based on 25 cancer stem cell-related genes. Three different cancer stem cells related subtypes were identified, which were related to different biological processes and clinical outcomes. The three subtypes have different TME cells infiltrating characteristics, and CSC Cluster A had a higher level of immunocyte infiltration compared to CSC Cluster B and C. We constructed a scoring system, called the CSC score, to assess the stemness of individual patients. Then we found that the prognosis of patients was predicted by CSC score, and patients with low CSC score had prolonged survival. Further analyses showed that low CSC score was correlated with enhanced immune infiltration. CSC score may predict the effect of immunotherapy, and patients with low CSC score may have better immune response and clinical prognosis.ConclusionsThis study demonstrates that there could be three cancer stem cell-associated subtypes in osteosarcoma and that they were associated with different patient prognosis and TME immune infiltration characteristics. CSC score could be used to assess the stemness of individual patients, improve our comprehension of TME characteristics, and direct more effective immune therapy.
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Project description:BackgroundRNA adenosine modifications, which are primarily mediated by "writer" enzymes (RMWs), play a key role in epigenetic regulation in various biological processes, including tumorigenesis. However, the expression and prognostic role of these genes in osteosarcoma (OS) remain unclear.MethodsUnivariate and multivariate Cox analyses were used to construct the RMW signature for OS using Target datasets. RMW expression in OS tissue was detected by qPCR analysis. Xcell and GSVA were used to determine the relationship between RMWs and immune infiltration. The DGIdb and CMap databases were used for drug prediction. In vivo and in vitro experiments showed that strophanthidin elicited antitumor activity against OS.ResultsA 3-RMW (CSTF2, ADAR and WTAP) prognostic signature in OS was constructed using the Target dataset and verified using GEO datasets and 63 independent OS tissues via qPCR analysis. High-risk OS patients had poor overall survival, and the prognostic signature was an independent prognostic factor for OS. Functional studies showed that tumour-, metabolism-, cell cycle- and immune-related pathways were related to high risk. Next, we found that RMW-derived high-risk patients exhibited increased infiltration of M2 macrophages and cDCs. Furthermore, we predicted the potential drugs for OS using the DGIdb and CMap databases. In vivo and in vitro experiments showed that strophanthidin elicited antitumor activity against OS by repressing cell growth and inducing cell cycle arrest at the G1 phase.ConclusionThe 3-RWM-based prognostic signature established in this study is a novel gene signature associated with immune infiltration, and strophanthidin was identified as a candidate therapy for OS by repressing OS cell growth and the cell cycle.
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Project description:ObjectiveThe primary objective of this study is to conduct a comprehensive screening and analysis of differentially expressed genes related to disulfidoptosis (DEDRGs) in thyroid carcinoma (THCA). This entails delving into the intricate characterization of immune cell infiltration within the THCA context and subsequently formulating and validating a novel prognostic model.MethodTo achieve our objectives, we first delineated two distinct subtypes of disulfidoptosis-related genes (DRGs) via consensus clustering methodology. Subsequently, employing the limma R package, we identified the DEDRGs critical for our investigation. These DEDRGs underwent meticulous validation across various databases, alongside an in-depth analysis of gene regulation. Employing functional enrichment techniques, we explored the potential molecular mechanisms underlying disulfidoptosis in THCA. Furthermore, we scrutinized the immune landscape within the two identified subtypes utilizing CIBERSORT and ESTIMATE algorithms. The construction of the prognostic model for THCA entailed intricate methodologies including univariate, multivariate Cox regression, and LASSO regression algorithms. The validity and efficacy of our prognostic model were corroborated through Kaplan-Meier survival curves and ROC curves. Additionally, a nomogram was meticulously formulated to facilitate the prediction of patient prognosis. To fortify our findings, we conducted a comprehensive Bayesian co-localization analysis coupled with rigorous in vitro experimentation, aimed at unequivocally establishing the validity of the identified DEDRGs.ResultOur analyses unveiled Cluster C1, characterized by elevated expression levels of DEDRGs, as harboring a favorable prognosis accompanied by abundant immune cell infiltration. Correlation analyses underscored predominantly positive associations among the DEDRGs, further affirming their significance in THCA. Differential expression patterns of DEDRGs between tumor samples and normal tissues were evident across the GEPIA and HPA databases. Insights from the TIMER database underscored a robust correlation between DEDRGs and immune cell infiltration. KEGG analysis elucidated the enrichment of DEDRGs primarily in pivotal pathways including MAPK, PPAR signaling pathway, and Proteoglycans in cancer. Furthermore, analyses using CIBERSORT and ESTIMATE algorithms shed light on the crucial role played by DEDRGs in shaping the immune microenvironment. The prognostic model, anchored by five genes intricately associated with THCA prognosis, exhibited commendable predictive accuracy and was intricately linked to the tumor immune microenvironment. Notably, patients categorized with low-risk scores stood to potentially benefit more from immunotherapy. The validation of DEDRGs unequivocally underscores the protective role of INF2 in THCA.ConclusionIn summary, our study delineates two discernible subtypes intricately associated with DRGs, revealing profound disparities in immune infiltration and survival prognosis within the THCA milieu. The implications of our findings extend to potential treatment strategies for THCA patients, which could entail targeted interventions directed towards DEDRGs and prognostic genes, thereby influencing disulfidptosis and the immune microenvironment. Moreover, the robust predictive capability demonstrated by our prognostic model, based on the five genes (ANGPTL7, FIRRE, ODAPH, PROKR1, SFRP5), underscores its potential clinical utility in guiding personalized therapeutic approaches for THCA patients.
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Project description:Osteosarcoma (OS) is a cancer that is frequently found in children and adolescents and has made little improvement in terms of prognosis in recent years. A recently discovered type of programmed cell death called cuproptosis is mediated by copper ions and the tricarboxylic acid (TCA) cycle. The expression patterns, roles, and prognostic and predictive capabilities of the cuproptosis regulating genes were investigated in this work. TARGET and GEO provided transcriptional profiling of OS. To find different cuproptosis gene expression patterns, consensus clustering was used. To identify hub genes linked to cuproptosis, differential expression (DE) and weighted gene co-expression network analysis (WGCNA) were used. Cox regression and Random Survival Forest were used to build an evaluation model for prognosis. For various clusters/subgroups, GSVA, mRNAsi, and other immune infiltration experiments were carried out. The drug-responsive study was carried out by the Oncopredict algorithm. Cuproptosis genes displayed two unique patterns of expression, and high expression of FDX1 was associated with a poor outcome in OS patients. The TCA cycle and other tumor-promoting pathways were validated by the functional study, and activation of the cuproptosis genes may also be connected with immunosuppressive state. The robust survival prediction ability of a five-gene prognostic model was verified. This rating method also took stemness and immunosuppressive characteristics into account. Additionally, it can be associated with a higher sensitivity to medications that block PI3K/AKT/mTOR signaling as well as numerous chemoresistances. U2OS cell migration and proliferation may be encouraged by PLCD3. The relevance of PLCD3 in immunotherapy prediction was verified. The prognostic significance, expressing patterns, and functions of cuproptosis in OS were revealed in this work on a preliminary basis. The cuproptosis-related scoring model worked well for predicting prognosis and chemoresistance.
| S-EPMC10060837 | biostudies-literature
Project description:BackgroundEven though immunotherapy has been an effective treatment for solid tumors, its efficacy in osteosarcoma remains sub-optimal. It is therefore imperative to understand the complex tumor microenvironment (TME) of osteosarcoma to facilitate the development of immunotherapies against this cancer.MethodsThe mRNA expression profiles of osteosarcoma tissues were downloaded from The Cancer Genome Atlas (TCGA) database. Next, the ssGSEA, MCP-counter, CIBERSORT, and Xcell algorithm analyses were performed to characterize the tumor microenvironment of osteosarcoma tissues. The tumor tissues were divided into inflammatory and non-inflammatory. A comprehensive assessment of immune cell infiltration in osteosarcoma tissues was then performed. Sub-group analysis of immune cell infiltration between men and women patients with osteosarcoma was also carried out.ResultsThe results revealed that the infiltration of immune cells including activated B cell, activated CD8 T cell, CD56dim natural killer cell, and cytotoxic lymphocytes cells, in osteosarcoma tissues was higher in male than in female patients. Based on the infiltration profile of different immune cells, the osteosarcoma tissues were grouped into four clusters. The four clusters were further divided into hot and cold tumors. The differently expressed genes (DEGs) between cold and hot tumors were mainly associated with the activation and regulation of immune response. Additionally, a neuronal pentraxin (NPTX2) expression which was upregulated in cold tumors was found to be negatively correlated with the expression of CD8a Molecule (CD8A), Granzyme B (GZMB), and Interferon Gamma (IFNG). NPTX2 decreased CCL4 secretion. Knockdown of NPTX2 in osteosarcoma cells inhibited tumor growth and increased tumor cell apoptosis. Moreover, a prognosis prediction model of osteosarcoma was constructed and validated in patients receiving immunotherapy using external data.ConclusionsTo the best of our knowledge, this is the first study to characterize the infiltration of immune cells in osteosarcoma tissues from patients receiving immune infiltration therapy.
| S-EPMC8366103 | biostudies-literature