Hypoxic Upregulation of IER2 Increases Paracrine GMFG Signaling of Endoplasmic Reticulum Stress-CAF to Promote Chordoma Progression via Targeting ITGB1.

Currently, the oncogenic mechanism of endoplasmic reticulum stress-CAF (ERS-CAF) subpopulation in chordoma remains unknown. Here, single-cell RNA sequencing, spatial transcriptomics, GeoMx Digital Spatial Profiler, data-independent acquisition proteomics, bulk RNA-seq, and multiplexed quantitative immunofluorescence are used to unveil the precise molecular mechanism of how ERS-CAF affected chordoma progression. Results show that hypoxic microenvironment reprograms CAFs into ERS-CAF subtype. Mechanistically, this occurrs via hypoxia-mediated transcriptional upregulation of IER2. Overexpression of IER2 in CAFs promotes chordoma progression, which can be impeded by IER2 knockdown or use of ERS inhibitors. IER2 also induces expression of ERS-CAF marker genes and results in production of a pro-tumorigenic paracrine GMFG signaling, which exert its biological function via directly binding to ITGB1 on tumor cells. ITGB1 inhibition attenuates tumor malignant progression, which can be partially reversed by exogenous GMFG intervention. Further analyses reveal a positive correlation between ITGB1high tumor cell counts and SPP1+ macrophage density, as well as the spatial proximity of these two cell types. Clinically, a significant correlation of high IER2/ITGB1 expression with tumor aggressive phenotype and poor patient survival is observed. Collectively, the findings suggest that ERS-CAF regulates SPP1+ macrophage to aggravate chordoma progression via the IER2/GMFG/ITGB1 axis, which may be targeted therapeutically in future.

Insights into a Machine Learning-Based Palmitoylation-Related Gene Model for Predicting the Prognosis and Treatment Response of Breast Cancer Patients.

BACKGROUND: Breast cancer is a prevalent public health concern affecting numerous women globally and is associated with palmitoylation, a post-translational protein modification. Despite increasing focus on palmitoylation, its specific implications for breast cancer prognosis remain unclear. The work aimed to identify prognostic factors linked to palmitoylation in breast cancer and assess its effectiveness in predicting responses to chemotherapy and immunotherapy. METHODS: We utilized the "limma" package to analyze the differential expression of palmitoylation-related genes between breast cancer and normal tissues. Hub genes were identified using the "WGCNA" package. Using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis, we identified a prognostic feature associated with palmitoylation and developed a prognostic nomogram with the "regplot" package. The predictive values of the model for chemotherapy and immunotherapy responses were assessed using immunophenoscore (IPS) and the "pRophetic" package. RESULTS: We identified 211 differentially expressed genes related to palmitoylation, among which 44 demonstrated prognostic potential. Subsequently, a predictive model comprising eleven palmitoylation-related genes was developed. Patients were classified into high-risk and low-risk groups based on the median risk score. The findings revealed that individuals in the high-risk group exhibited lower survival rates, while those in the low-risk group showed increased immune cell infiltration and improved responses to chemotherapy and immunotherapy. Moreover, the BC-Palmitoylation Tool website was established. CONCLUSION: This study developed the first machine learning-based predictive model for palmitoylation-related genes and created a corresponding website, providing clinicians with a valuable tool to improve patient outcomes.

Is Type 2 Diabetes Mellitus Associated with Spinal Degenerative Disorders?: Evidence from Observational and 2-Sample Mendelian Randomization Analyses.

BACKGROUND: Type 2 diabetes mellitus (T2DM) and spinal degenerative disorders (SDD) are common diseases that frequently coexist. However, both traditional observational studies and recent Mendelian randomization (MR) studies have demonstrated conflicting evidence on the association between T2DM and SDD. This comparative study explored and compared the association between T2DM and SDD using observational and MR analyses. METHODS: For observational analyses, cross-sectional studies (44,972 participants with T2DM and 403,095 participants without T2DM), case-control studies (38,234 participants with SDD and 409,833 participants without SDD), and prospective studies (35,550 participants with T2DM and 392,046 participants without T2DM with follow-up information until 2022) were performed to test the relationship between T2DM and SDD using individual-level data from the U.K. Biobank from 2006 to 2022. For MR analyses, the associations between single-nucleotide polymorphisms with SDD susceptibility obtained using participant data from the U.K. Biobank, which had 407,938 participants from 2006 to 2022, and the FinnGen Consortium, which had 227,388 participants from 2017 to 2022, and genetic predisposition to T2DM obtained using summary statistics from a pooled genome-wide association study involving 1,407,282 individuals were examined. The onset and severity of T2DM are not available in the databases being used. RESULTS: Participants with T2DM were more likely to have SDD than their counterparts. Logistic regression analysis identified T2DM as an independent risk factor for SDD, which was confirmed by the Cox proportional hazard model results. However, using single-nucleotide polymorphisms as instruments, the MR analyses demonstrated no causal relationship between T2DM and SDD. The lack of such an association was robust in the sensitivity analysis, and no pleiotropy was seen. CONCLUSIONS: Our results suggest that the association between T2DM and SDD may be method-dependent. Researchers and clinicians should be cautious in interpreting the association, especially the causal association, between T2DM and SDD. Our findings provide fresh insights into the association between T2DM and SDD by various analysis methods and guide future research and clinical efforts in the effective prevention and management of T2DM and SDD. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

ß-Lapachone promotes the recruitment and polarization of tumor-associated neutrophils (TANs) toward an antitumor (N1) phenotype in NQO1-positive cancers.

NAD(P)H:quinone oxidoreductase 1 (NQO1) is overexpressed in most solid cancers, emerging as a promising target for tumor-selective killing. ß-Lapachone (ß-Lap), an NQO1 bioactivatable drug, exhibits significant antitumor effects on NQO1-positive cancer cells by inducing immunogenic cell death (ICD) and enhancing tumor immunogenicity. However, the interaction between ß-Lap-mediated antitumor immune responses and neutrophils, novel antigen-presenting cells (APCs), remains unknown. This study demonstrates that ß-Lap selectively kills NQO1-positive murine tumor cells by significantly increasing intracellular ROS formation and inducing DNA double strand breaks (DSBs), resulting in DNA damage. Treatment with ß-Lap efficiently eradicates immunocompetent murine tumors and significantly increases the infiltration of tumor-associated neutrophils (TANs) into the tumor microenvironment (TME), which plays a crucial role in the drug's therapeutic efficacy. Further, the presence of ß-Lap-induced antigen medium leads bone marrow-derived neutrophils (BMNs) to directly kill murine tumor cells, aiding in dendritic cells (DCs) recruitment and significantly enhancing CD8+ T cell proliferation. ß-Lap treatment also drives the polarization of TANs toward an antitumor N1 phenotype, characterized by elevated IFN-ß expression and reduced TGF-ß cytokine expression, along with increased CD95 and CD54 surface markers. ß-Lap treatment also induces N1 TAN-mediated T cell cross-priming. The HMGB1/TLR4/MyD88 signaling cascade influences neutrophil infiltration into ß-Lap-treated tumors. Blocking this cascade or depleting neutrophil infiltration abolishes the antigen-specific T cell response induced by ß-Lap treatment. Overall, this study provides comprehensive insights into the role of tumor-infiltrating neutrophils in the ß-Lap-induced antitumor activity against NQO1-positive murine tumors.

Single-cell RNA sequencing reveals the MIF/ACKR3 receptor-ligand interaction between neutrophils and nucleus pulposus cells in intervertebral disc degeneration.

OBJECTIVES: To unravel the heterogeneity and function of microenvironmental neutrophils during intervertebral disc degeneration (IDD). METHODS: Single-cell RNA sequencing (scRNA-seq) was utilized to dissect the cellular landscape of neutrophils in intervertebral disc (IVD) tissues and their crosstalk with nucleus pulposus cells (NPCs). The expression levels of macrophage migration inhibitory factor (MIF) and ACKR3 in IVD tissues were detected. The MIF/ACKR3 axis was identified and its effects on IDD were investigated in vitro and in vivo. RESULTS: We sequenced here 71520 single cells from 5 control and 9 degenerated IVD samples using scRNA-seq. We identified a unique cluster of neutrophils abundant in degenerated IVD tissues that highly expressed MIF and was functionally enriched in extracellular matrix organization (ECMO). Cell-to-cell communication analyses showed that this ECMO-neutrophil subpopulation was closely interacted with an effector NPCs subtype, which displayed high expression of ACKR3. Further analyses revealed that MIF was positively correlated with ACKR3 and functioned via directly binding to ACKR3 on effector NPCs. MIF inhibition attenuated degenerative changes of NPCs and extracellular matrix, which could be partially reversed by ACKR3 overexpression. Clinically, a significant correlation of high MIF/ACKR3 expression with advanced IDD grade was observed. Furthermore, we also found a positive association between MIF+ ECMO-neutrophil counts and ACKR3+ effector NPCs density as well as higher expression of the MIF/ACKR3 signaling in areas where these two cell types were neighbors. CONCLUSIONS: These data suggest that ECMO-neutrophil promotes IDD progression by their communication with NPCs via the MIF/ACKR3 axis, which may shed light on therapeutic strategies.

Butyrate increases methylglyoxal production through regulation of the JAK2/Stat3/Nrf2/Glo1 pathway in castration­resistant prostate cancer cells.

Cancer cells are characterized by increased glycolysis, known as the Warburg effect, which leads to increased production of cytotoxic methylglyoxal (MGO) and apoptotic cell death. Cancer cells often activate the protective nuclear factor erythroid 2­related factor2 (Nrf2)/glyoxalase1 (Glo1) system to detoxify MGO. The effects of sodium butyrate (NaB), a product of gut microbiota, on Nrf2/Glos/MGO pathway and the underlying mechanisms in prostate cancer (PCa) cells were investigated in the present study. Treatment with NaB induced the cell death and reduced the proliferation of PCa cells (DU145 and LNCap). Moreover, the protein kinase RNA-like endoplasmic reticulum kinase/Nrf2/Glo1 pathway was greatly inhibited by NaB, thereby accumulating MGO-derived adduct hydroimidazolone (MG-H1). In response to a high amount of MGO, the expression of Nrf2 and Glo1 was attenuated, coinciding with an increased cellular death. NaB also markedly inhibited the Janus kinase 2 (JAK2)/Signal transducer and activator of transcription 3 (Stat3) pathway. Conversely, co­treatment with Colivelin, a Stat3 activator, significantly reversed the effects of NaB on Glo1 expression, MG-H1 production, and the cell migration and viability. As expected, overexpression of Stat3 or Glo1 reduced NaB­induced cell death. The activation of calcium/calmodulin dependent protein kinase II gamma and reactive oxygen species production also contributed to the anticancer effect of NaB. The present study, for the first time, demonstrated that NaB greatly increases MGO production through suppression of the JAK2/Stat3/Nrf2/Glo1 pathway in DU145 cells, a cell line mimicking castration­resistant PCa (CRPC), suggesting that NaB may be a potential agent for PCa therapy.

Integration of multiomics analyses reveals unique insights into CD24-mediated immunosuppressive tumor microenvironment of breast cancer.

BACKGROUND: Tumor immunotherapy brings new light and vitality to breast cancer patients, but low response rate and limitations of therapeutic targets become major obstacles to its clinical application. Recent studies have shown that CD24 is involved in an important process of tumor immune regulation in breast cancer and is a promising target for immunotherapy. METHODS: In this study, singleR was used to annotate each cell subpopulation after t-distributed stochastic neighbor embedding (t-SNE) methods. Pseudo-time trace analysis and cell communication were analyzed by Monocle2 package and CellChat, respectively. A prognostic model based on CD24-related genes was constructed using several machine learning methods. Multiple quantitative immunofluorescence (MQIF) was used to evaluate the spatial relationship between CD24+PANCK+cells and exhausted CD8+T cells. RESULTS: Based on the scRNA-seq analysis, 1488 CD24-related differential genes were identified, and a risk model consisting of 15 prognostic characteristic genes was constructed by combining the bulk RNA-seq data. Patients were divided into high- and low-risk groups based on the median risk score. Immune landscape analysis showed that the low-risk group showed higher infiltration of immune-promoting cells and stronger immune reactivity. The results of cell communication demonstrated a strong interaction between CD24+epithelial cells and CD8+T cells. Subsequent MQIF demonstrated a strong interaction between CD24+PANCK+ and exhausted CD8+T cells with FOXP3+ in breast cancer. Additionally, CD24+PANCK+ and CD8+FOXP3+T cells were positively associated with lower survival rates. CONCLUSION: This study highlights the importance of CD24+breast cancer cells in clinical prognosis and immunosuppressive microenvironment, which may provide a new direction for improving patient outcomes.

Development of machine learning-based malignant pericardial effusion-related model in breast cancer: Implications for clinical significance, tumor immune and drug-therapy.

Background: Malignant pericardial effusion (MPE) is a common complication of advanced breast cancer (BRCA) and plays an important role in BRCA. This study is aims to construct a prognostic model based on MPE-related genes for predicting the prognosis of breast cancer. Methods: The BRCA samples are analyzed based on the expression of MPE-related genes by using an unsupervised cluster analysis method. This study processes the data by least absolute shrinkage and selection operator and multivariate Cox analysis, and uses machine learning algorithms to construct BRCA prognostic model and develop web tool. Results: BRCA patients are classified into three clusters and a BRCA prognostic model is constructed containing 9 MPE-related genes. There are significant differences in signature pathways, immune infiltration, immunotherapy response and drug sensitivity testing between the high and low-risk groups. Of note, a web-based tool (http://wys.helyly.top/cox.html) is developed to predict overall survival as well as drug-therapy response of BRCA patients quickly and conveniently, which can provide a basis for clinicians to formulate individualized treatment plans. Conclusion: The MPE-related prognostic model developed in this study can be used as an effective tool for predicting the prognosis of BRCA and provides new insights for the diagnosis and treatment of BRCA patients.

Integrating single-cell and spatial transcriptomics reveals endoplasmic reticulum stress-related CAF subpopulations associated with chordoma progression.

BACKGROUND: With cancer-associated fibroblasts (CAFs) as the main cell type, the rich myxoid stromal components in chordoma tissues may likely contribute to its development and progression. METHODS: Single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, bulk RNA-seq, and multiplexed quantitative immunofluorescence (QIF) were used to dissect the heterogeneity, spatial distribution, and clinical implication of CAFs in chordoma. RESULTS: We sequenced here 72 097 single cells from 3 primary and 3 recurrent tumor samples, as well as 3 nucleus pulposus samples as controls using scRNA-seq. We identified a unique cluster of CAF in recurrent tumors that highly expressed hypoxic genes and was functionally enriched in endoplasmic reticulum stress (ERS). Pseudotime trajectory and cell communication analyses showed that this ERS-CAF subpopulation originated from normal fibroblasts and widely interacted with tumoral and immune cells. Analyzing the bulk RNA-seq data from 126 patients, we found that the ERS-CAF signature score was associated with the invasion and poor prognosis of chordoma. By integrating the results of scRNA-seq with spatial transcriptomics, we demonstrated the existence of ERS-CAF in chordoma tissues and revealed that this CAF subtype displayed the most proximity to its surrounding tumor cells. In subsequent QIF validation involving 105 additional patients, we confirmed that ERS-CAF was abundant in the chordoma microenvironment and located close to tumor cells. Furthermore, both ERS-CAF density and its distance to tumor cells were correlated with tumor malignant phenotype and adverse patient outcomes. CONCLUSIONS: These findings depict the CAF landscape for chordoma and may provide insights into the development of novel treatment approaches.

Cardiovascular-specific mortality and risk factors in colorectal Cancer patients: A cohort study based on registry data of over 500,000 individuals in the US.

BACKGROUND: Colorectal cancer (CRC) is one of the most common cancers worldwide, and recent studies have found that CRC patients are at increased risk for cardiovascular disease (CVD). This study aimed to investigate competing causes of death and prognostic factors among a large cohort of CRC patients and to describe cardiovascular-specific mortality in relation to the US standard population. METHODS: This registry-based cohort study identified patients diagnosed with CRC between 1973 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database in the US. Cumulative mortality functions, conditional standardized mortality ratios, and cause-specific hazard ratios were calculated. RESULTS: Of the 563,298 eligible CRC patients included in this study, 407,545 died during the follow-up period. CRC was the leading cause of death, accounting for 49.8% of all possible competing causes of death. CVD was the most common non-cancer cause of death, accounting for 17.8% of total mortality. This study found that CRC patients have a significantly increased risk of cardiovascular-specific mortality compared to the US standard population, with the risk increasing with age and extended survival time. CONCLUSION: This study highlights the need to develop multidisciplinary prevention and management strategies for CRC and CVD to improve CRC patients' survival and quality of life.

A breast cancer classification and immune landscape analysis based on cancer stem-cell-related risk panel.

This study sought to identify molecular subtypes of breast cancer (BC) and develop a breast cancer stem cells (BCSCs)-related gene risk score for predicting prognosis and assessing the potential for immunotherapy. Unsupervised clustering based on prognostic BCSC genes was used to determine BC molecular subtypes. Core genes of BC subtypes identified by non-negative matrix factorization algorithm (NMF) were screened using weighted gene co-expression network analysis (WGCNA). A risk model based on prognostic BCSC genes was constructed using machine learning as well as LASSO regression and multivariate Cox regression. The tumor microenvironment and immune infiltration were analyzed using ESTIMATE and CIBERSORT, respectively. A CD79A+CD24-PANCK+-BCSC subpopulation was identified and its spatial relationship with microenvironmental immune response state was evaluated by multiplexed quantitative immunofluorescence (QIF) and TissueFAXS Cytometry. We identified two distinct molecular subtypes, with Cluster 1 displaying better prognosis and enhanced immune response. The constructed risk model involving ten BCSC genes could effectively stratify patients into subgroups with different survival, immune cell abundance, and response to immunotherapy. In subsequent QIF validation involving 267 patients, we demonstrated the existence of CD79A+CD24-PANCK+-BCSC in BC tissues and revealed that this BCSC subtype located close to exhausted CD8+FOXP3+ T cells. Furthermore, both the densities of CD79A+CD24-PANCK+-BCSCs and CD8+FOXP3+T cells were positively correlated with poor survival. These findings highlight the importance of BCSCs in prognosis and reshaping the immune microenvironment, which may provide an option to improve outcomes for patients.

A novel immune checkpoint-related signature for prognosis and immune analysis in breast cancer.

Breast cancer is one of the most prevailing forms of cancer globally. Immunotherapy has demonstrated efficacy in improving the overall survival of breast cancer. The aim of us was to formulate a novel signature predicated on immune checkpoint-related genes (ICGs) that could anticipate the prognosis and further analyze the immune status of patients with breast cancer. After acquiring data, we pinpointed the definitive ICGs for constructing the prognostic model of breast cancer. We constructed a novel prognostic model and created a fresh risk score called Immune Checkpoint-related Risk Score in breast cancer (ICRSBC). The nomogram was constructed to evaluate the accuracy of the model, and the new web-based tool was created to be more intuitive for predicting prognosis. We also investigated immunotherapy responsiveness and analyzed the tumor mutational burden (TMB) in ICRSBC subgroups. The ICRSBC was found to have significant correlations with the immune environment, immunotherapy responsiveness, and TMB. The expression levels of the 9 ICGs that construct the prognostic model and their promoter methylation levels are significantly different between breast cancer and normal tissues. Furthermore, the mutation profiles, the copy number alterations, and the levels of protein expression also exhibit marked disparities among the 9 ICGs. We have identified and validated a novel signature related to ICGs that is strongly associated with breast cancer progression. This signature enables us to create a risk score for prognosticating the survival and assessing the immune status of individuals affected by breast cancer.

ChatGPT encounters multiple opportunities and challenges in neurosurgery.

BACKGROUND: ChatGPT, powered by the GPT model and Transformer architecture, has demonstrated remarkable performance in the domains of medicine and healthcare, providing customized and informative responses. In our study, we investigated the potential of ChatGPT in the field of neurosurgery, focusing on its applications at the patient, neurosurgery student/resident, and neurosurgeon levels. METHOD: The authors conducted inquiries with ChatGPT from the viewpoints of patients, neurosurgery students/residents, and neurosurgeons, covering a range of topics, such as disease diagnosis, treatment options, prognosis, rehabilitation, and patient care. The authors also explored concepts related to neurosurgery, including fundamental principles and clinical aspects, as well as tools and techniques to enhance the skills of neurosurgery students/residents. Additionally, the authors examined disease-specific medical interventions and the decision-making processes involved in clinical practice. RESULTS: The authors received individual responses from ChatGPT, but they tended to be shallow and repetitive, lacking depth and personalization. Furthermore, ChatGPT may struggle to discern a patient's emotional state, hindering the establishment of rapport and the delivery of appropriate care. The language used in the medical field is influenced by technical and cultural factors, and biases in the training data can result in skewed or inaccurate responses. Additionally, ChatGPT's limitations include the inability to conduct physical examinations or interpret diagnostic images, potentially overlooking complex details and individual nuances in each patient's case. Moreover, its absence in the surgical setting limits its practical utility. CONCLUSION: Although ChatGPT is a powerful language model, it cannot substitute for the expertise and experience of trained medical professionals. It lacks the capability to perform physical examinations, make diagnoses, administer treatments, establish trust, provide emotional support, and assist in the recovery process. Moreover, the implementation of Artificial Intelligence in healthcare necessitates careful consideration of legal and ethical concerns. While recognizing the potential of ChatGPT, additional training with comprehensive data is necessary to fully maximize its capabilities.

Investigation of fatty acid metabolism-related genes in breast cancer: Implications for Immunotherapy and clinical significance.

Breast cancer (BRCA) is a major global health issue, characterized by high mortality and low early diagnosis rates. The tumor immune microenvironment (TME) of BRCA is closely linked to fatty acid metabolism (FAM). This study aimed to identify FAM-related subtypes in BRCA based on gene expression and clinical data from the Cancer Genome Atlas (TCGA) database. The study found two distinct FAM-related subtypes, each with unique immune characteristics and prognostic implications. A FAM-related risk score prognostic model was developed and validated using TCGA and International Cancer Genome Consortium (GEO) cohorts, showing potential clinical applications for chemotherapy and immunotherapy. Additionally, a nomogram was established to facilitate clinical use of the risk score. These results highlight the significant correlation between FAM genes and TME in BRCA, and demonstrate the potential clinical utility of the FAM-related risk score in informing treatment decisions for BRCA patients.

Corrigendum: Coexpression of HHLA2 and PD-L1 on tumor cells independently predicts the survival of spinal chordoma patients.

[This corrects the article DOI: 10.3389/fimmu.2021.797407.].

Network pharmacology analysis reveals potential targets and mechanisms of proton pump inhibitors in breast cancer with diabetes.

Breast cancer and diabetes are significant health challenges, and effective treatments for both diseases are lacking. Proton pump inhibitors (PPIs) have demonstrated anticancer and hypoglycemic effects, but their mechanisms of action are not yet fully understood. We used the GeneCards and PharmMapper databases to identify therapeutic targets for diabetes,  breast cancer and PPIs. We identified common targets and constructed a regulatory network of diseases and drugs using the STRING database and Cytoscape software. We also explored the binding between small molecule ligands and protein receptors using Discovery Studio software. We identified 33 shared targets for breast cancer, diabetes, and PPIs including lansoprazole, omeprazole, and pantoprazole, which play a critical role in fatty acid transport, insulin resistance, apoptosis, and cancer-related signaling pathways. Our findings demonstrated that PPIs had a strong affinity for AKT1 and MMP9. This study provides insights into the mechanisms of action of PPIs in breast cancer and diabetes and identifies AKT1 and MMP9 as critical targets for future drug development. Our findings highlight the potential of PPIs as a novel therapeutic approach for these challenging diseases.

Tumor Growth Rate in Spinal Giant Cell Tumors of Bone and Association With the Immune Microenvironment and Denosumab Treatment Responsiveness: A Multicenter Study.

BACKGROUND: Currently, little is known about the prognostic value of tumor growth rate (TGR) in spinal giant cell tumors of bone (GCTB). OBJECTIVE: To investigate the correlation of TGR with clinicopathological features, immune microenvironment, prognosis, and response to denosumab treatment of spinal GCTB. METHODS: A total of 128 patients with spinal GCTB treated at 5 centers from 2011 to 2021 were included. TGR was assessed by 2 independent neuroradiologists using at least 2 preoperative thin-section magnetic resonance imaging scans at a minimum interval of 2 months. Immunohistochemistry was used to assess tumor-infiltrating lymphocyte subtypes for CD3, CD4, CD8, CD20, PD-1, PD-L1, and Foxp3. Then, these parameters were analyzed for their associations with patient outcomes (progression-free survival and overall survival), clinicopathological features, and denosumab treatment responsiveness. RESULTS: High TGR predicted both poor progression-free survival and overall survival (both P < .001). In addition, TGR was associated with postoperative neurological dysfunction ( P < .001), Enneking staging ( P = .016), denosumab treatment responsiveness ( P = .035), and the number of CD3 + ( P < .001), PD-1 + ( P = .009), PD-L1 + ( P < .001), and FoxP3 + tumor-infiltrating lymphocyte ( P = .02). Importantly, TGR outperformed the traditional Enneking, Campanacci, and American Joint Committee on Cancer staging systems in predicting the clinical outcomes of spinal GCTB. CONCLUSION: These data support the use of TGR as a reliable predictive tool for clinically relevant outcomes and response to denosumab therapy of spinal GCTB, which may be helpful in guiding prognostic risk stratification and therapeutic optimization of patients.

Clinicopathological and Prognostic Characteristics in Spinal Chondroblastomas: A Pooled Analysis of Individual Patient Data From a Single Institute and 27 Studies.

STUDY DESIGN: Retrospective pooled analysis of individual patient data. OBJECTIVES: Spinal chondroblastoma (CB) is a very rare pathology and its clinicopathological and prognostic features remain unclear. Here, we sought to characterize the clinicopathological data of a large spinal CB cohort and determine factors affecting the local recurrence-free survival (LRFS) and overall survival (OS) of patients. METHODS: Electronic searches using Medline, Embase, Google Scholar and Wanfang databases were performed to identify eligible studies per predefined criteria. A retrospective review was also conducted to include additional patients at our center. RESULTS: Twenty-seven studies from the literature and 8 patients from our local institute were identified, yielding a total of 61 patients for analysis. Overall, there were no differences in clinicopathological characteristics between the local and literature cohorts, except for absence or presence of spinal canal invasion by tumor on imagings and chicken-wire calcification in tumor tissues. Univariate Kaplan-Meier analysis revealed that previous treatment, preoperative or postoperative neurological deficits, type of tumor resection, secondary aneurysmal bone cyst (ABC), chicken-wire calcification and radiotherapy correlated closely with LRFS, though only type of tumor resection, chicken-wire calcification and radiotherapy were predictive of outcome based on multivariate Cox analysis. Analyzing OS, we found that a history of preoperative treatment, concurrent ABC, chicken-wire calcification, type of tumor resection and adjuvant radiotherapy had a significant association with survival, whereas only type of tumor resection remained statistically significant after adjusting for other covariables. CONCLUSION: These data may be helpful in prognostic risk stratification and individualized therapy decision making for patients.