Dynamic Prediction of Overall Survival for Patients with Osteosarcoma: A Retrospective Analysis of the EURAMOS-1 Clinical Trial Data.

Current prediction models for patients with ostosarcoma are restricted to predictions from a single, static point in time, such as diagnosis or surgery. These approaches discard information which becomes available during follow-up and may have an impact on patient's prognosis. This study aims at developing a dynamic prediction model providing 5-year overall survival (OS) predictions from different time points during follow-up. The developed model considers relevant baseline prognostic factors, accounting for where appropriate time-varying effects and time-varying intermediate events such as local recurrence (LR) and new metastatic disease (NM). A landmarking approach is applied to 1965 patients with high-grade resectable osteosarcoma from the EURAMOS-1 trial (NCT00143030). Results show that LR and NM negatively affected 5-year OS (HRs: 2.634, 95% CI 1.845-3.761; 8.558, 95% CI 7.367-9.942, respectively). Baseline factors with strong prognostic value (HRs > 2) included poor histological response (≥10% viable tumor), axial tumor location, and the presence of lung metastases. The effect of poor versus good histological response changed over time, becoming non-significant from 3.25 years post-surgery onwards. This time-varying effect, as well as the strong impact of disease-related time-varying variables, show the importance of including updated information collected during follow-up in the model to provide more accurate survival predictions.

A novel prognostic signature related to programmed cell death in osteosarcoma.

Background: Osteosarcoma primarily affects children and adolescents, with current clinical treatments often resulting in poor prognosis. There has been growing evidence linking programmed cell death (PCD) to the occurrence and progression of tumors. This study aims to enhance the accuracy of OS prognosis assessment by identifying PCD-related prognostic risk genes, constructing a PCD-based OS prognostic risk model, and characterizing the function of genes within this model. Method: We retrieved osteosarcoma patient samples from TARGET and GEO databases, and manually curated literature to summarize 15 forms of programmed cell death. We collated 1621 PCD genes from literature sources as well as databases such as KEGG and GSEA. To construct our model, we integrated ten machine learning methods including Enet, Ridge, RSF, CoxBoost, plsRcox, survivalSVM, Lasso, SuperPC, StepCox, and GBM. The optimal model was chosen based on the average C-index, and named Osteosarcoma Programmed Cell Death Score (OS-PCDS). To validate the predictive performance of our model across different datasets, we employed three independent GEO validation sets. Moreover, we assessed mRNA and protein expression levels of the genes included in our model, and investigated their impact on proliferation, migration, and apoptosis of osteosarcoma cells by gene knockdown experiments. Result: In our extensive analysis, we identified 30 prognostic risk genes associated with programmed cell death (PCD) in osteosarcoma (OS). To assess the predictive power of these genes, we computed the C-index for various combinations. The model that employed the random survival forest (RSF) algorithm demonstrated superior predictive performance, significantly outperforming traditional approaches. This optimal model included five key genes: MTM1, MLH1, CLTCL1, EDIL3, and SQLE. To validate the relevance of these genes, we analyzed their mRNA and protein expression levels, revealing significant disparities between osteosarcoma cells and normal tissue cells. Specifically, the expression levels of these genes were markedly altered in OS cells, suggesting their critical role in tumor progression. Further functional validation was performed through gene knockdown experiments in U2OS cells. Knockdown of three of these genes-CLTCL1, EDIL3, and SQLE-resulted in substantial changes in proliferation rate, migration capacity, and apoptosis rate of osteosarcoma cells. These findings underscore the pivotal roles of these genes in the pathophysiology of osteosarcoma and highlight their potential as therapeutic targets. Conclusion: The five genes constituting the OS-PCDS model-CLTCL1, MTM1, MLH1, EDIL3, and SQLE-were found to significantly impact the proliferation, migration, and apoptosis of osteosarcoma cells, highlighting their potential as key prognostic markers and therapeutic targets. OS-PCDS enables accurate evaluation of the prognosis in patients with osteosarcoma.

Efficacy and safety of sorafenib in adult metastatic osteosarcoma patients.

BACKGROUND: There are limited data on the efficacy of targeted therapy in metastatic osteosarcoma. The goal of this study was to assess the effectiveness of sorafenib in adult patients with heavily pretreated metastatic osteosarcoma. METHOD: Patients with metastatic osteosarcoma aged more than 18 years were assessed retrospectively. The patients' clinical, pathological, and therapeutic data were collected. For survival analysis, Kaplan-Meier models were used. RESULTS: The research involved 15 patients. The ratio of male and female patients was 2/1, with a median age of 25 years (range: 19-64 years). The most common primary tumor localization was the extremities (66.6%). Fourteen (93.3%) patients had previously received palliative chemotherapy and six (40%) patients had palliative radiotherapy. The median progression-free survival was found as 5.5 months (95% confidence interval, 1.3-9.7). A stable response was observed in seven (46.6%) patients and progressive disease in eight (53.4%) patients. Grade 1-2 toxicities were detected in 50% of the patients, while grade 3-4 toxicities were observed in 14.3% of the patients. CONCLUSIONS: We demonstrated real-life results of sorafenib for disease management in pretreated adult patients with metastatic osteosarcoma in the study. Sorafenib was effective for disease control and well tolerated in the patients. Sorafenib may be a treatment option for disease control after the disease progresses with chemotherapy in patients with metastatic osteosarcoma.

SPP1 could be an immunological and prognostic biomarker: From pan-cancer comprehensive analysis to osteosarcoma validation.

Secreted phosphoprotein 1 (SPP1), also known as osteopontin, is a phosphorylated protein. High SPP1 expression levels have been detected in multiple cancers and are associated with poor prognosis and reduced survival rates. However, only a few pan-cancer analyses have targeted SPP1. We conducted a comprehensive analysis using multiple public databases, including TIMER and TCGA, to investigate the expression levels of SPP1 in 33 different tumor types. In addition, we verified the effect of SPP1 on osteosarcoma. To assess the impact of SPP1 on patient outcomes, we employed univariate Cox regression and Kaplan-Meier survival analyses to analyze overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in these tumor patients. We also explored SPP1 gene alterations in various tumor tissues using cBioPortal. We then examined the relationship between SPP1 and clinical characteristics, TME, immune regulatory genes, immune checkpoints, TMB, and MSI using R language. In addition, we used GSEA to investigate the molecular mechanisms underlying the role of SPP1. Bioinformatics analysis indicated that SPP1 was upregulated in 17 tumors. Overexpression of SPP1 results in poor OS, DSS, and PFI in CESC, ESCA, GBM, LGG, LIHC, PAAD, PRAD, and skin cutaneous melanoma. SPP1 expression was positively associated with immunocyte infiltration, immune regulatory genes, immune checkpoints, TMB, MSI, and drug sensitivity in certain cancers. We found that high expression of SPP1 in osteosarcoma was related to drug resistance and metastasis and further demonstrated that SPP1 can stimulate osteosarcoma cell proliferation via CCND1 by activating the PI3K/Akt pathway. These findings strongly suggest that SPP1 is a potential prognostic marker and novel target for cancer immunotherapy.

Multi-omic validation of the cuproptosis-sphingolipid metabolism network: modulating the immune landscape in osteosarcoma.

Background: The current understanding of the mechanisms by which metal ion metabolism promotes the progression and drug resistance of osteosarcoma remains incomplete. This study aims to elucidate the key roles and mechanisms of genes involved in cuproptosis-related sphingolipid metabolism (cuproptosis-SPGs) in regulating the immune landscape, tumor metastasis, and drug resistance in osteosarcoma cells. Methods: This study employed multi-omics approaches to assess the impact of cuproptosis-SPGs on the prognosis of osteosarcoma patients. Lasso regression analysis was utilized to construct a prognostic model, while multivariate regression analysis was applied to identify key core genes and generate risk coefficients for these genes, thereby calculating a risk score for each osteosarcoma patient. Patients were then stratified into high-risk and low-risk groups based on their risk scores. The ESTIMATE and CIBERSORT algorithms were used to analyze the level of immune cell infiltration within these risk groups to construct the immune landscape. Single-cell analysis was conducted to provide a more precise depiction of the expression patterns of cuproptosis-SPGs among immune cell subtypes. Finally, experiments on osteosarcoma cells were performed to validate the role of the cuproptosis-sphingolipid signaling network in regulating cell migration and apoptosis. Results: In this study, seven cuproptosis-SPGs were identified and used to construct a prognostic model for osteosarcoma patients. In addition to predicting survival, the model also demonstrated reliability in forecasting the response to chemotherapy drugs. The results showed that a high cuproptosis-sphingolipid metabolism score was closely associated with reduced CD8 T cell infiltration and indicated poor prognosis in osteosarcoma patients. Cellular functional assays revealed that cuproptosis-SPGs regulated the LC3B/ERK signaling pathway, thereby triggering cell death and impairing migration capabilities in osteosarcoma cells. Conclusion: The impact of cuproptosis-related sphingolipid metabolism on the survival and migration of osteosarcoma cells, as well as on CD8 T cell infiltration, highlights the potential of targeting copper ion metabolism as a promising strategy for osteosarcoma patients.

Adjacent venous tumour thrombus in primary osteosarcoma of the pelvis and limbs.

Aims: Venous tumour thrombus (VTT) is a rare finding in osteosarcoma. Despite the high rate of VTT in osteosarcoma of the pelvis, there are very few descriptions of VTT associated with extrapelvic primary osteosarcoma. We therefore sought to describe the prevalence and presenting features of VTT in osteosarcoma of both the pelvis and the limbs. Methods: Records from a single institution were retrospectively reviewed for 308 patients with osteosarcoma of the pelvis or limb treated between January 2000 and December 2022. Primary lesions were located in an upper limb (n = 40), lower limb (n = 198), or pelvis (n = 70). Preoperative imaging and operative reports were reviewed to identify patients with thrombi in proximity to their primary lesion. Imaging and histopathology were used to determine presence of tumour within the thrombus. Results: Tumours abutted the blood vessels in 131 patients (43%) and encased the vessels in 30 (10%). Any form of venous thrombus was identified in 31 patients (10%). Overall, 21 of these thrombi were determined to be involved with the tumour based on imaging (n = 9) or histopathology (n = 12). The rate of VTT was 25% for pelvic osteosarcoma and 1.7% for limb osteosarcoma. The most common imaging features associated with histopathologically proven VTT were enhancement with contrast (n = 12; 100%), venous enlargement (n = 10; 83%), vessel encasement (n = 8; 66%), and visible intraluminal osteoid matrix (n = 6; 50%). Disease-specific survival (DSS) for patients with VTT was 95% at 12 months (95% CI 0.87 to 1.00), 50% at three years (95% CI 0.31 to 0.80), and 31% at five years (95% CI 0.14 to 0.71). VTT was associated with worse DSS (hazard ratio 2.3 (95% CI 1.11 to 4.84). Conclusion: VTT is rare with osteosarcoma and occurs more commonly in the pelvis than the limbs. Imaging features suggestive of VTT include enhancement with contrast, venous dilation, and vessel encasement. VTT portends a worse prognosis for patients with osteosarcoma, with a similar survivability to metastatic disease.

Identification of a pro-protein synthesis osteosarcoma subtype for predicting prognosis and treatment.

Osteosarcoma (OS) is a heterogeneous malignant spindle cell tumor that is aggressive and has a poor prognosis. Although combining surgery and chemotherapy has significantly improved patient outcomes, the prognosis for OS patients with metastatic or recurrent OS has remained unsatisfactory. Therefore, it is imperative to gain a fresh perspective on OS development mechanisms and treatment strategies. After studying single-cell RNA sequencing (scRNA-seq) data in public databases, we identified seven OS subclonal types based on intra-tumor heterogeneity. Subsequently, we constructed a prognostic model based on pro-protein synthesis osteosarcoma (PPS-OS)-associated genes. Correlation analysis showed that the prognostic model performs extremely well in predicting OS patient prognosis. We also demonstrated that the independent risk factors for the prognosis of OS patients were tumor primary site, metastatic status, and risk score. Based on these factors, nomograms were constructed for predicting the 3- and 5-year survival rates. Afterward, the investigation of the tumor immune microenvironment (TIME) revealed the vital roles of γδ T-cell and B-cell activation. Drug sensitivity analysis and immune checkpoint analysis identified drugs that have potential application value in OS. Finally, the jumping translocation breakpoint (JTB) gene was selected for experimental validation. JTB silencing suppressed the proliferation, migration, and invasion of OS cells. Therefore, our research suggests that PPS-OS-related genes facilitate the malignant progression of OS and may be employed as prognostic indicators and therapeutic targets in OS.

Machine learning survival prediction using tumor lipid metabolism genes for osteosarcoma.

Osteosarcoma is a primary malignant tumor that commonly affects children and adolescents, with a poor prognosis. The existence of tumor heterogeneity leads to different molecular subtypes and survival outcomes. Recently, lipid metabolism has been identified as a critical characteristic of cancer. Therefore, our study aims to identify osteosarcoma's lipid metabolism molecular subtype and develop a signature for survival outcome prediction. Four multicenter cohorts-TARGET-OS, GSE21257, GSE39058, and GSE16091-were amalgamated into a unified Meta-Cohort. Through consensus clustering, novel molecular subtypes within Meta-Cohort patients were delineated. Subsequent feature selection processes, encompassing analyses of differentially expressed genes between subtypes, univariate Cox analysis, and StepAIC, were employed to pinpoint biomarkers related to lipid metabolism in TARGET-OS. We selected the most effective algorithm for constructing a Lipid Metabolism-Related Signature (LMRS) by utilizing four machine-learning algorithms reconfigured into ten unique combinations. This selection was based on achieving the highest concordance index (C-index) in the test cohort of GSE21257, GSE39058, and GSE16091. We identified two distinct lipid metabolism molecular subtypes in osteosarcoma patients, C1 and C2, with significantly different survival rates. C1 is characterized by increased cholesterol, fatty acid synthesis, and ketone metabolism. In contrast, C2 focuses on steroid hormone biosynthesis, arachidonic acid, and glycerolipid and linoleic acid metabolism. Feature selection in the TARGET-OS identified 12 lipid metabolism genes, leading to a model predicting osteosarcoma patient survival. The LMRS, based on the 12 identified genes, consistently accurately predicted prognosis across TARGET-OS, testing cohorts, and Meta-Cohort. Incorporating 12 published signatures, LMRS showed robust and significantly superior predictive capability. Our results offer a promising tool to enhance the clinical management of osteosarcoma, potentially leading to improved clinical outcomes.

[Delayed diagnosis of osteosarcoma in adults: a prognostic factor to be considered]. / Retraso en el diagnóstico de osteosarcoma en adultos: un factor pronóstico que debemos considerar.

INTRODUCTION: different variables have been associated with a worse prognosis of patients with osteosarcoma (OS), highlighting tumor size, location in the axial skeleton and the presence of metastases. The objective of this study is to analyze the prognostic impact of diagnostic delay in osteosarcoma in adults in the Mexican population in a center specialized in sarcomas. MATERIAL AND METHODS: retrospective cohort study from January 1, 2005, to December 31, 2016, 96 patients over 21 years of age with a diagnosis of osteosarcoma were analyzed. RESULTS: the median time to diagnosis from the onset of symptoms was six months (range: 2-36). This variable was dichotomized by applying the operator-dependent curve (ROC) analysis and we determined a cut-off value greater than five months, with an area under the curve (AUC) = 0.93 [95% CI 0.86-0.97], sensitivity 93.2% and specificity 94.6%. CONCLUSION: time until diagnosis is a critical factor in the survival of adult patients with osteosarcoma, highlighting its influence on disease progression and the appearance of metastasis. The correlation between diagnostic delay and an unfavorable prognosis reinforces the need for rapid and efficient evaluation in suspected cases of osteosarcoma.

INTRODUCCIÓN: diferentes variables se han asociado con un peor pronóstico de los pacientes con osteosarcoma, destacando el tamaño tumoral, la localización en esqueleto axial y la presencia de metástasis. El objetivo de este estudio fue analizar el impacto pronóstico del retraso diagnóstico en osteosarcoma en adultos en población mexicana en un centro especializado en sarcomas. MATERIAL Y MÉTODOS: estudio de tipo cohorte retrospectiva del 1 de Enero del 2005 al 31 de Diciembre de 2016, se analizaron 96 pacientes mayores de 21 años con diagnóstico de osteosarcoma. RESULTADOS: la mediana de tiempo al diagnóstico desde el inicio de síntomas fue de seis meses (rango: 2-36). Esta variable se dicotomizó aplicando el análisis de curva dependiente de operador (ROC) y determinamos un valor de corte mayor a cinco meses con un área bajo la curva (AUC) = 0.93 [IC95% 0.86-0.97], sensibilidad 93.2% y especificidad 94.6%. CONCLUSIÓN: el tiempo hasta el diagnóstico es un factor crítico en la supervivencia de los pacientes adultos con osteosarcoma, destacando su influencia en la progresión de la enfermedad y la aparición de metástasis. La correlación entre el retraso diagnóstico y un pronóstico desfavorable refuerza la necesidad de una evaluación rápida y eficiente en casos sospechosos de osteosarcoma.

Prolonged 14-day continuous infusion of high-dose ifosfamide for patients with relapsed and refractory high-grade osteosarcoma: a retrospective multicentre cohort study.

BACKGROUND: The prognosis of patients with Relapsed/Refractory Osteosarcoma (R/R OS) remains dismal without an agreement on systemic therapy. The use of High-Dose Ifosfamide (14 g/sqm) with an external pump in outpatient setting (14-IFO) in R/R OS patients is limited. This study represents the first retrospective cohort analysis focused on evaluating the activity and toxicity of 14-IFO in this setting. PATIENTS AND METHODS: The study investigated 14-IFO activity, in terms of tumour response according to RECIST 1.1 criteria, as well as survival rates and toxicity, according to CTCAE v.5. RESULTS: The trial enrolled 26 patients with R/R OS. The Overall Response Rate (ORR) and Disease Control Rate (DCR) obtained was 23% and 57.5%, respectively. Patients with relapsed OS showed a higher ORR (45%) and DCR (82%) compared to refractory patients, irrespective of the number of prior treatment lines received. The achievement of disease control with 14-IFO administration enabled 27% of patients to undergo new local treatment. Four-month Progression-Free Survival (PFS) was 54% for all patients and 82% for the relapsed OS sub-group. Median Overall Survival (OSurv) was 13.7 months, with 1-year OSurv of 51% for all patients and 71% for relapsed patients. Age over 18 years and the presence of refractory disease were identified as negative prognostic factors for this patient cohort. A total of 101 cycles were evaluated for toxic assessment, demonstrating a tolerable profile without grade 3-4 non-haematological toxicities. CONCLUSIONS: 14-IFO should be considered a viable treatment option for R/R OS, particularly due to its well tolerated toxicity profile and the potential for home-administration, which can improve patient quality of life without compromising efficacy.

PSMD14 is a novel prognostic marker and therapeutic target in osteosarcoma.

BACKGROUND: Osteosarcoma is a bone tumor that is characterized by high malignancy and a high mortality rate, and that originates from primitive osteoblastic mesenchymal cells and is most common in rapidly growing long bones. PSMD14, also known as RPN11 or POH1, is a member of the JAMM isopeptidase family, which is able to remove the substrate protein ubiquitination label, thereby regulating the stability and function of the substrate protein. In this study, we explored the expression and potential biological significance of the PSMD14 deubiquitinating enzyme in osteosarcoma. METHODS: Immunohistochemical methods were used to detect the expression of PSMD14 in biopsies of 91 osteosarcoma patients, and the specimens were classified into high and low PSMD14 expression groups. The correlation between PSMD14 expression and clinical indicators and prognosis was compared.SiRNA was used to downregulate PSMD14 in two osteosarcoma cell lines (HOS and SJSA-1), and the effects of downregulation of PSMD14 on the viability, proliferation, and invasion ability of osteosarcoma cells were analyzed. RESULTS: We identified significant differences in recurrence, metastasis, and survival time of the osteosarcoma patients on the basis of PSMD14 expression. High expression of PSMD14 in osteosarcoma patients was associated with a low survival rate and high risk of metastasis and recurrence. Down-regulation of PSMD14 inhibited the viability, proliferation, and invasiveness of osteosarcoma cell lines. CONCLUSIONS: PSMD14 may be a new prognostic marker and therapeutic target for osteosarcoma.

An immune-related eleven-RNA signature-drived risk score model for prognosis of osteosarcoma metastasis.

This study aimed to determine an immune-related RNA signature as a prognostic marker, in this study, we developed a risk score model for predicting the prognosis of osteosarcoma metastasis. We first downloaded the clinical information and expression data of osteosarcoma samples from the UCSC Xena and GEO databases, of which the former was the training set and the latter was the validation set. Immune infiltration was assessed using the ssGSEA and ESTIMATE algorithms, and the osteosarcoma samples were divided into the Immunity_L and Immunity_H groups. Then, eleven RNAs were identified as the optimal prognostic RNA signatures using LASSO Cox regression analysis for establishing a risk score (RS) model. Kaplan-Meier approach indicated the high-risk group exhibited a shorter survival. Furthermore, we analyzed the tumor metastasis, age, and RS model status were determined to be independent clinical prognostic factors using Cox regression analysis. Decision curve analysis (DCA) indicated that the prognostic factor + RS model had the best net benefit. Finally, nine tumor-infiltrating immune cells (TIICs) showed significant differences in abundance between high- and low-risk groups via CIBERSORT deconvolution algorithm. In conclusion, the immune-related eleven-RNA signature be could served as a potential prognostic biomarker for osteosarcoma metastasis.

Identification of hub genes related to metastasis and prognosis of osteosarcoma and establishment of a prognostic model with bioinformatic methods.

Osteosarcoma (OS) is the most common primary malignant bone tumor occurring in children and adolescents. Improvements in our understanding of the OS pathogenesis and metastatic mechanism on the molecular level might lead to notable advances in the treatment and prognosis of OS. Biomarkers related to OS metastasis and prognosis were analyzed and identified, and a prognostic model was established through the integration of bioinformatics tools and datasets in multiple databases. 2 OS datasets were downloaded from the Gene Expression Omnibus database for data consolidation, standardization, batch effect correction, and identification of differentially expressed genes (DEGs); following that, gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the DEGs; the STRING database was subsequently used for protein-protein interaction (PPI) network construction and identification of hub genes; hub gene expression was validated, and survival analysis was conducted through the employment of the TARGET database; finally, a prognostic model was established and evaluated subsequent to the screening of survival-related genes. A total of 701 DEGs were identified; by gene ontology and KEGG pathway enrichment analyses, the overlapping DEGs were enriched for 249 biological process terms, 13 cellular component terms, 35 molecular function terms, and 4 KEGG pathways; 13 hub genes were selected from the PPI network; 6 survival-related genes were identified by the survival analysis; the prognostic model suggested that 4 genes were strongly associated with the prognosis of OS. DEGs related to OS metastasis and survival were identified through bioinformatics analysis, and hub genes were further selected to establish an ideal prognostic model for OS patients. On this basis, 4 protective genes including TPM1, TPM2, TPM3, and TPM4 were yielded by the prognostic model.

Neoadjuvant chemotherapy-induced hemoglobin decline as a prognostic factor in osteosarcoma around the knee joint: a single-center retrospective analysis of 242 patients.

PURPOSE: Anemia is relatively common in cancer patients, and is associated with poor survival in patients with various malignancies. However, how anemia would affect prognosis and response to neoadjuvant chemotherapy (NAC) in osteosarcoma (OS) is still without substantial evidence. METHODS: We retrospectively analysed 242 patients with stage II OS around the knee joint in our institute. Changed hemoglobin (Hb) levels (before and after NAC) were recorded to assess the prognostic value in DFS (disease-free survival) and tumor response to NAC. Univariate and multivariate analyses were conducted to identify prognostic factors related with outcome in OS patients. RESULTS: The mean Hb level significantly decreased after NAC (134.5 ± 15.3 g/L vs. 117.4 ± 16.3 g/L). The percentage of mild (21%), moderate (4.2%) and severe (0%) anemia patients markedly increased after NAC: 41%, 24% and 4.1% respectively. There was higher percentage of ≥ 5% Hb decline in patients with tumor necrosis rate < 90% (141 out of 161), compared with those with tumor necrosis rate ≥ 90% (59 out of 81). Further univariate and survival analysis demonstrated that Hb decline had a significant role in prediction survival in OS patients. Patients with ≥ 5% Hb decline after NAC had an inferior DFS compared with those with < 5% Hb decline. CONCLUSION: In osteosarcoma, patients with greater Hb decrease during neoadjuvant treatment were shown to have worse DFS and a poorer response to NAC than those without. Attempts to correct anemia and their effects on outcomes for osteosarcoma patients should be explored in future studies.

The prognostic value of ubiquitin/ubiquitin-like-related genes along with immune cell infiltration and clinicopathological features in osteosarcoma.

BACKGROUND: Ubiquitin/ubiquitin-like (Ub/UBL)-related genes have been reported to be associated with the survival of osteosarcoma patients but have not yet been systematically explored. METHODS: The prognostic value of Ub/UBL-related genes, immune cell infiltration and clinicopathological features of patients were explored by Cox and LASSO regression analyses. A prognostic model was established and then validated in the GSE21257 dataset. The differential expression of hub genes in osteosarcoma was confirmed by qRT-PCR, western blotting and immunohistochemistry. RESULTS: Tripartite Motif Containing 8 (TRIM8) and Ubiquitin Like With PHD And Ring Finger Domains 2 (UHRF2) were screened as genes with prognostic value in osteosarcoma. Kaplan-Meier analysis and scatter plots indicated that patients in the high gene significance score group tended to have a worse prognosis. The concordance index, calibration analysis and receiver operating characteristic analysis suggested that the model had good prediction accuracy and high sensitivity and specificity. Decision curve analysis revealed that patients could obtain greater net benefit from this model. Functional analyses of the differentially expressed genes indicated that they were involved in important functions and pathways. TRIM8 and UHRF2 were confirmed to be highly expressed in osteosarcoma cell lines and tissues. CONCLUSIONS: TRIM8 and UHRF2 are potential prognostic genes in osteosarcoma, and these results provide insights into the roles of these genes and their implications for patient outcomes.

PDE1B, a potential biomarker associated with tumor microenvironment and clinical prognostic significance in osteosarcoma.

PDE1B had been found to be involved in various diseases, including tumors and non-tumors. However, little was known about the definite role of PDE1B in osteosarcoma. Therefore, we mined public data on osteosarcoma to reveal the prognostic values and immunological roles of the PDE1B gene. Three osteosarcoma-related datasets from online websites were utilized for further data analysis. R 4.3.2 software was utilized to conduct difference analysis, prognostic analysis, gene set enrichment analysis (GSEA), nomogram construction, and immunological evaluations, respectively. Experimental verification of the PDE1B gene in osteosarcoma was conducted by qRT-PCR and western blot, based on the manufacturer's instructions. The PDE1B gene was discovered to be lowly expressed in osteosarcoma, and its low expression was associated with poor OS (all P < 0.05). Experimental verifications by qRT-PCR and western blot results remained consistent (all P < 0.05). Univariate and multivariate Cox regression analyses indicated that the PDE1B gene had independent abilities in predicting OS in the TARGET osteosarcoma dataset (both P < 0.05). GSEA revealed that PDE1B was markedly linked to the calcium, cell cycle, chemokine, JAK STAT, and VEGF pathways. Moreover, PDE1B was found to be markedly associated with immunity (all P < 0.05), and the TIDE algorithm further shed light on that patients with high-PDE1B expression would have a better immune response to immunotherapies than those with low-PDE1B expression, suggesting that the PDE1B gene could prevent immune escape from osteosarcoma. The PDE1B gene was found to be a tumor suppressor gene in osteosarcoma, and its high expression was related to a better OS prognosis, suppressing immune escape from osteosarcoma.

Evaluating the Outcome and Patient Safety of Methotrexate, Doxorubicin, and Cisplatin Regimen for Chemotherapy in Osteosarcoma: A Meta-Analysis.

BACKGROUND: Several studies of multi-drug regimens for osteosarcoma have shown different efficacies and are still controversial. Meanwhile, chemotherapy options have remained largely unchanged over a couple of decades. This study is designed to ascertain the outcome and safety of Methotrexate, Doxorubicin, and Cisplatin regimen for chemotherapy in osteosarcoma patients through the utilization of meta-analysis. METHODS: We interrogated trials that compared the MAP regimen with other regimens as chemotherapy for osteosarcoma from several databases encompassing PubMed, Science Direct, and grey literature (Google Scholar) until December 2022. The analyzed outcomes including Event-Free Survival (EFS), Overall Survival (OS), Tumor Necrosis (TN) rate, and Adverse Event (AE) were then analyzed using RevMan 5.4 software in fixed or random effect models. RESULTS: Our meta-analysis comprised 8 prospective articles that evaluated a cumulative number of 2920 OS patients. The analysis results indicated no meaningful difference in 5-year EFS (OR=0.99, 95% CI=0.77-1.27, [P = 0.91]) and neoadjuvant chemotherapy response (TN) (OR=0.76, 95% CI=0.49-1.17, [P = 0.22]) between the MAP and control groups. Furthermore, 5-year OS analysis revealed a significant association in the control group (OR=0.82, 95% CI=0.68-0.99, [P = 0.04]). However, the control group was associated with statistically meaningful AE compared to the MAP group, particularly in thrombocytopenia (OR=0.46, 95% CI=0.23-0.90, [P = 0.02]) and fever (OR=0.34, 95% CI=0.26-0.46, [P < 0.00001]). CONCLUSION: The present meta-analysis showed that the MAP regimen remains preferable in treating osteosarcoma patients despite no significant outcome compared to the other regimens considering the less frequent AE in the MAP regimen.

Lumbar functional evaluation of pelvic bone sarcomas after surgical resection and spinal pelvic fixation: A clinical study of 304 cases.

AIMS: We endeavored to introduce a novel scoring system (Lumbar Functional Index, LFI) capable of evaluating lumbar function in pelvic bone sarcoma patients who underwent surgical resection and spinal pelvic fixation, while simultaneously identifying the incidence, outcomes, and risk factors of lumbar function impairment among these populations. PATIENTS AND METHODS: A cohort of 304 primary bone sarcoma patients were recruited. The LFI was created based on the Oswestry Dysfunction Index (ODI) and Japanese Orthopaedic Association (JOA) scores. Lumbar function impairment was defined as LFI score ≥ 18 points, which was identified as high LFI. Demographic data, clinical characteristics, and oncological outcomes were analyzed. RESULTS: The cohort included chondrosarcoma (39.8%), osteosarcoma (29.9%), Ewing sarcoma (8.6%), bone-derived undifferentiated pleomorphic sarcoma (7.2%), giant cell tumor of bone (7.2%), chordoma (2.3%), and other bone sarcomas (5.0%). The LFI score exhibited significant negative correlation with common scoring systems of bone sarcoma. The incidence of high LFI was 23.0%. Patients with high LFI demonstrated a higher prevalence of type I + II + III + IV pelvic tumor, more sacrificed nerve roots and bilateral lumbar spine fixation during surgery, while lower percentage of R0 resection and local control of pelvic tumor. Decreased median overall survival (30 vs. 52 months, p < 0.001) and recurrence-free survival (14 vs. 24 months, p < 0.001) time were observed in these patients. Type I + II + III + IV pelvic tumor and sacrificed nerve roots≥2 were identified as risk factors for high LFI, while R0 resection and local control were identified as protective factors. CONCLUSION: The LFI scoring system exhibited a significant negative correlation to current scoring systems. High LFI patients had worse prognosis and distinct characteristics. The risk factors of high LFI included type I + II + III + IV pelvic tumor and sacrificed nerve roots≥2, and the protective factors included R0 resection and local control.

Cell Cycle Checkpoints p16 and p21-Strong Predictors of Clinicopathologic Outcomes in High-Grade Osteosarcoma.

PURPOSE: In this study, we used a series of immunohistochemical measurements of 2 cell cycle regulators, p16 and p21, to evaluate their prognostic value, separately and in combination, for the disease outcomes. METHOD: A total of 101 patients with high-grade osteosarcoma were included in this study. Clinicopathologic data were collected, and immunohistochemistry for p16 and p21 was performed and interpreted by 3 independent pathologists. Statistical analysis was performed to assess the strength of each of these markers relative to disease outcome. RESULTS: Our results indicate that more than 90% expression (high) of p16 by immunohistochemistry on the initial biopsy has a strong predictive value for good histologic response to chemotherapy. The patients are also more likely to survive the past 5 years and less likely to develop metastasis than patients with less than 90% p16 (low) expression. The results for p21, on the other hand, show a unique pattern of relationship to the clinicopathologic outcomes of the disease. Patients with less than 1% (low) or more than 50% (high) expression of p21 by immunohistochemistry show a higher chance of metastasis, poor necrotic response to chemotherapy, and an overall decreased survival rate when compared with p21 expression between 1% and 50% (moderate). Our results also showed that the expression of p16 and combined p16 and p21 demonstrates a stronger predictive relationship to 5-year survival than tumor histologic necrosis and p21 alone. DISCUSSION: The results of this study, once proven to be reproducible by a larger number of patients, will be valuable in the initial assessment and risk stratification of the patients for treatment and possibly the clinical trials.

Incidence and survival outcomes of patients with high-grade appendicular bone sarcoma and isolated regional lymph node metastasis: A national cohort database study.

BACKGROUND: While distant metastases in primary bone sarcomas have been extensively studied, the impact of isolated regional lymph node (LN) metastasis on survival remains unknown. In patients with primary bone sarcomas, we sought to assess the prevalence of isolated regional LN metastasis and the survival of this population. METHODS: A total of 6651 patients with histologically-confirmed high-grade osteosarcoma, Ewing sarcoma, or chondrosarcoma were retrieved from the SEER database. We defined four subgroups for our analysis: localized disease (N0 M0), isolated regional LN metastasis (N1 M0), isolated distant metastasis (N0 M1), and combined regional LN and distant metastasis (N1 M1). Disease-specific survival (DSS) was assessed using the Kaplan-Meier method. RESULTS: Prevalence of isolated regional LN metastasis (N1 M0) was highest in Ewing sarcoma (27/1097; 3.3 %), followed by chondrosarcoma (18/1702; 1.4 %) and osteosarcoma (26/3740; 0.9 %). In all three histologies, patients with isolated regional LN metastasis had a worse 2-year, 5-year, and 10-year DSS than those with localized disease. Chondrosarcoma patients with isolated regional LN (N1 M0) metastasis had a significantly higher DSS in comparison to those with only distant metastasis (N0 M1) at the 5- and 10-year marks; for osteosarcoma and Ewing sarcoma, only a pattern towards higher survival was seen. Risk factors for presenting isolated regional LN metastasis included tumor location in lower-limb (OR = 2.01) or pelvis (OR = 2.49), diagnosis of Ewing sarcoma (OR = 2.98), and tumor >10 cm (OR = 1.96). CONCLUSIONS: Isolated regional LN metastases in primary bone sarcomas is an infrequent presentation associated with worse survival than localized disease. LEVEL OF EVIDENCE: III.