Twenty-year outcome of prevalence, incidence, mortality and survival rate in patients with malignant bone tumors

Enhanced boundary-directed lightweight approach for digital pathological image analysis in critical oncological diagnostics

BackgroundPathological images play a crucial role in the diagnosis of critically ill cancer patients. Since cancer patients often seek medical assistance when their condition is severe, doctors face the urgent challenge of completing accurate diagnoses and developing surgical plans within a limited timeframe. The complexity and diversity of pathological images require a significant investment of time from specialized physicians for processing and analysis, which can lead to missing the optimal treatment window.PurposeCurrent medical decision support systems are challenged by the high computational complexity of deep learning models, which demand extensive data training, making it difficult to meet the real-time needs of emergency diagnostics.MethodThis study addresses the issue of emergency diagnosis for malignant bone tumors such as osteosarcoma by proposing a Lightened Boundary-enhanced Digital Pathological Image Recognition Strategy (LB-DPRS). This strategy optimizes the self-attention mechanism of the Transformer model and innovatively implements a boundary segmentation enhancement strategy, thereby improving the recognition accuracy of tissue backgrounds and nuclear boundaries. Additionally, this research introduces row-column attention methods to sparsify the attention matrix, reducing the computational burden of the model and enhancing recognition speed. Furthermore, the proposed complementary attention mechanism further assists convolutional layers in fully extracting detailed features from pathological images.ResultsThe DSC value of LB-DPRS strategy reached 0.862, the IOU value reached 0.749, and the params was only 10.97 M.ConclusionExperimental results demonstrate that the LB-DPRS strategy significantly improves computational efficiency while maintaining prediction accuracy and enhancing model interpretability, providing powerful and efficient support for the emergency diagnosis of malignant bone tumors such as osteosarcoma.

Evaluation of tumorous LCP1 and ADPGK as predictive biomarker for immune-related adverse events in bone and soft tissue sarcomas treated with anti-PD-1 and anti-PD-L1 antibodies

Immune checkpoint inhibitor (ICI) have been utilized in bone and soft tissues sarcoma patients under multiple circumstances in combination with surgeries and chemotherapy. Regretfully, immune-related adverse events (irAE) increases as the usage of ICI increases. Since a large portion of bone and soft tissues sarcoma patients gain long survival times after successful removal of the tumors which makes clinicians to avoid regimens that causes adverse events, especially lifetime irAE. Hence, predicting the development of irAE are of special significance for utilizing ICI in bone and soft tissues sarcoma patients. We have retrospectively stained tumorous LCP1 and ADPGK, two biomarkers previously reported to predict ICI induced irAE, with surgical removed, formalin-fixed and parrffin-embedded samples in a cohort of 50 bone and soft tissues sarcoma patients. We observed that the most common irAE in bone and soft tissues sarcoma patients received ICI is hyperglycemia and high grade irAE happens predominately in patients over 30 years old. Immunochemistry revealed that both LCP1 and ADPGK were elevated in tumorous tissues of patients developed irAE and bivariate-model of LCP1 and ADPGK severs as a better biomarker in comparison to LCP1 or ADPGK alone in the entire cohort. In osteosarcoma, LCP1 alone exhibited an outstanding predication value with an AUC of 0.9244 (P value of 0.0013 and a 95% CI of 0.8178 to 1.000). LCP1 and ADPGK bivariate-model serves as a promising biomarker for predicting ICI induced irAE in bone and soft tissues sarcoma patients while LCP1 alone works better in bone malignancy especially in osteosarcoma.

Evaluation of Indoleamine 2,3-Dioxygenase (IDO) Expression in Osteosarcoma: Insights From a 10-Year Retrospective Cohort

Introduction

Osteosarcoma, a prevalent bone malignancy in children and adolescents, is currently treated through surgical resection and chemotherapy. Advancements in cancer research are targeting immune checkpoint molecules, such as indoleamine 2,3-dioxygenase, to advance the development of immunotherapy. However, the scarcity of research on IDO in osteosarcoma results in an absence of comprehensive data, highlighting the conflicting findings surrounding IDO's role in various cancers. Our study aims to explore IDO expression in primary tumors and metastatic lesions among osteosarcoma patients, investigating its association with clinicopathological characteristics and assessing its impact on survival outcomes.

Methods

150 patients diagnosed with osteosarcoma were selected between 2009 and 2019 from the Shaukat Khanum Memorial Cancer Hospital and Research Centre, Lahore, Pakistan. FFPE tissue samples of primary tumors and metastatic lesions were retrieved to conduct immunohistochemical analysis. Moreover, the clinicopathological data of these patients were gathered from the hospital information system.

Results

Out of 150 patients, primary tumors were accessible for 134 individuals, while metastatic lesions were available for 49 patients. IDO expression was identified in 9 (6.71%) primary tumors and 2 (4.08%) metastatic lesions among osteosarcoma patients. Furthermore, 3 patients exhibited high expression (27.3%), while 8 displayed low IDO expression (72.7%).

Conclusion

Our comprehensive study findings indicate that most osteosarcoma patients do not exhibit expression of IDO. This absence of expression aligns with the characteristic "cold" tumor microenvironment observed in osteosarcoma. Further investigations are imperative to provide deeper insights into the intricacies of this immunomodulatory factor in the context of osteosarcoma.

Delay in Diagnosis and Treatment of Bone Sarcoma-Systematic Review

Delay in the diagnosis and treatment of rare types of cancers such as bone sarcoma still remains an important problem [...].

Bone tumors: a systematic review of prevalence, risk determinants, and survival patterns

BACKGROUND

Though relatively rare, bone tumors significantly impact patient health and treatment outcomes.

OBJECTIVE

This systematic review analyzes the incidence, types, survival rates, and risk factors associated with bone tumors, including both benign and malignant forms.

METHODS

This systematic review was conducted using the keywords "bone tumors," "epidemiology," "benign bone tumors," "malignant bone tumors," "osteosarcoma," "Ewing sarcoma," "chondrosarcoma," "risk factors," and "survival" in electronic databases including PubMed, Scopus, Web of Science, and Google Scholar from 2000 to 2024. The search strategy was based on the PRISMA statement. Finally, 9 articles were selected for inclusion in the study.

RESULTS

The systematic review highlights that primary bone tumors can be classified into benign and malignant types, with osteosarcoma being the most prevalent malignant form, particularly among adolescents and young adults. The epidemiology of bone tumors is influenced by factors such as age, gender, geographic location, and genetic predispositions. Recent advancements in imaging techniques have improved the detection of these tumors, contributing to an increasing recognition of their prevalence. Data shows that the limited-duration prevalence of malignant bone tumors has increased significantly. This increase is from 0.00069% in 2000 to 0.00749% in 2018, indicating an increasing recognition and diagnosis of these rare tumors over time. Survival rates vary significantly by tumor type, with approximately 50-60% for osteosarcoma and around 70% for Ewing's sarcoma, though these rates decrease with metastasis. Key risk factors identified include genetic predispositions such as Li-Fraumeni syndrome and TP53 mutations, environmental exposures like radiation, and growth patterns related to height.

CONCLUSION

The review highlights the importance of early diagnosis and treatment intervention, as survival rates are significantly better for patients with localized disease compared to those with metastatic conditions. The observed variations in survival rates across different tumor types underscore the need for tailored treatment strategies. Key risk factors include genetic predispositions and environmental exposures, highlighting the need for targeted screening and ongoing research to enhance diagnostic accuracy and treatment strategies.

Chondrosarcoma: New Molecular Insights, Challenges in Near-Patient Preclinical Modeling, and Therapeutic Approaches

Chondrosarcoma (CS), the second most common malignant bone tumor after osteosarcoma, accounts for 20-30% of all malignant bone tumors. It mainly affects adults, middle-aged, and elderly people. The CS family includes various entities displaying peculiar biological, genetic, and epigenetic characteristics and clinical behaviors. Conventional CS is the most common subtype. High-grade, dedifferentiated, and mesenchymal CS, as well as unresectable and metastatic CS, exhibit poor prognoses due to their intrinsic resistance to radiotherapy and chemotherapy, underscoring the urgent need for novel therapeutic strategies. CS research is dealing with several challenges. Experimental studies can rely on animal and patient-derived models, but the paucity of representative near-patient preclinical models has hampered predictive drug screening research. This review describes the main clinical and molecular features of CS subtypes, discussing recent data on the genetic alterations and molecular mechanisms involved in CS pathogenesis and progression. The review provides an overview of the current in vitro and in vivo CS models, discusses their advantages and limitations, and highlights the recent efforts in the development of new targeted therapies against CS dependencies, including IDH1/2 mutations, NAD+ dependency, and SIRT1-HIF-2α axis, or exploring DR5 targeting, antiangiogenic therapies, epigenetic drugs, and immunological approaches. All such strategies, in combination with advanced preclinical modeling and personalized multi-omic profiling, hold promise for improving the survival of patients with advanced CS.

Image-guided cryoablation for palliation of painful bone metastases: a systematic review and meta-analysis

OBJECTIVE

To assess the efficacy of cryoablation in controlling pain from metastatic bone lesions.

MATERIALS AND METHODS

A systematic search of PubMed, Embase, Scopus, Cochrane library, and Web of Science was conducted from inception to April 2024, focusing on cryoablation for palliation of painful bone metastases. The inclusion criteria were as follows: studies involving patients over 18 years of age who were affected by bone metastases; bone metastases treated with stand-alone cryoablation; studies reporting patients' pain levels before and at least at one time point after cryoablation; and studies published in English.

RESULTS

A total of 844 articles were initially screened, resulting in 12 articles involving 309 patients included. Pain assessments were conducted at various time points ranging from 1 day to 6 months after the cryoablation procedure. Included studies reported significant improvements in pain scores based on the visual analog scale (VAS), the numeric rating scale (NRS) and brief pain inventory-short form (BPI-SF) following treatment at 1, 4, 8 and 12 weeks. The most notable mean difference between pre- and post-procedure pain scores was observed at 12 weeks, with a standardized mean difference of -3.71 (95% confidence interval [CI]: -5.29 to -2.00; p < 0.001). Regarding pain relief outcomes, by the fourth week, the proportion of patients experiencing pain relief was 0.69 (95% CI: 0.62 to 0.75; p < 0.001).

CONCLUSIONS

Cryoablation could be an effective method for palliation of painful bone metastases. Further studies are needed to compare its efficacy with other palliative methods and to define its role in cancer management.

Exploration of metastasis-related signatures in osteosarcoma based on tumor microenvironment by integrated bioinformatic analysis

Background

The present study aims to explore the metastasis-related signatures in connection with tumor microenvironment (TME), revealing new molecular targets promising in improving osteosarcoma (OS) patients' outcomes.

Methods

The high-throughput sequencing data was downloaded from the TARGET database and performed the ESTIMATE algorithm. Metastasis-related information was obtained from the GSE21257 dataset. Differentially expressed genes (DEGs) associated with the stromal and immune cell infiltration patterns were identified. DEGs with similar biological functions were grouped into the same module by Gene Ontology (GO) analysis and MCODE analysis. Prognostic DEGs were selected in two datasets through survival analysis. Weighted gene co-expression network analysis (WGCNA) was performed to find metastasis-related modules and genes. RT-PCR was utilized to evaluate the expression of the key prognostic DEGs associated with metastasis in OS patients.

Results

The median scores of the stromal and immune groups of OS samples were 58 and -416, and a total of 200 overlapping DEGs were identified. These DEGs basically played fundamental roles in immune response relevant GO terms and were clustered into 9 different modules. Among them, 24 metastasis-related DEGs were selected from the GSE21257 dataset which contains the stromal and immune cell infiltration patterns. Finally, IRF8, HLA-DMA, and HLA-DMB were proved to exhibit significant higher expression levels in cancerous tissues than in para-cancerous tissues for OS patients.

Conclusion

We identified three principal genes as promising signatures for predicting the survival the prognosis of OS patients. Exploration of metastasis-related signatures in TME may be valuable for enhancing treatment strategies for OS.

UBE2L3 Suppresses Oxidative Stress-regulated Necroptosis to Accelerate Osteosarcoma Progression

BACKGROUND

Osteosarcoma is a highly invasive bone marrow stromal tumor with limited treatment options. Oxidative stress plays a crucial role in the development and progression of tumors, but the underlying regulatory mechanisms are not fully understood. Recent studies have revealed the significant involvement of UBE2L3 in oxidative stress, but its specific role in osteosarcoma remains poorly investigated.

OBJECTIVE

This study aimed to explore the molecular mechanisms by which UBE2L3 promotes oxidative stress-regulated necroptosis to accelerate the progression of osteosarcoma using in vitro cell experiments.

METHODS

Human osteoblast hFOB1.19 cells and various human osteosarcoma cell lines (MG-63, U2OS, SJSA-1, HOS, and 143B) were cultured in vitro. Plasmids silencing UBE2L3 and negative control plasmids were transfected into U2OS and HOS cells. The cells were divided into the following groups: U2OS cell group, HOS cell group, si-NC-U2OS cell group, si-UBE2L3-U2OS cell group, si-NC-HOS cell group, and si-UBE2L3-HOS cell group. Cell viability and proliferation capacity were measured using the Tunnel method and clonogenic assay. Cell migration and invasion abilities were assessed by Transwell and scratch assays. Cell apoptosis was analyzed by flow cytometry, and ROS levels were detected using immunofluorescence. The oxidative stress levels in various cell groups and the expression changes of necroptosis-related proteins were assessed by PCR and WB. Through these experiments, we aim to evaluate the impact of oxidative stress on necroptosis and uncover the specific mechanisms by which targeted regulation of oxidative stress promotes tumor cell necroptosis as a potential therapeutic strategy for osteosarcoma.

RESULTS

The mRNA expression levels of UBE2L3 in human osteosarcoma cell lines were significantly higher than those in human osteoblast hFOB1.19 cells (p <0.01). UBE2L3 expression was significantly decreased in U2OS and HOS cells transfected with si-UBE2L3, indicating the successful construction of stable cell lines with depleted UBE2L3. Tunnel assay results showed a significant increase in the number of red fluorescent-labeled cells in si-UBE2L3 groups compared to si-NC groups in both cell lines, suggesting a pronounced inhibition of cell viability. Transwell assay demonstrated a significant reduction in invasion and migration capabilities of si-UBE2L3 groups in osteosarcoma cells. The clonogenic assay revealed significant suppression of proliferation and clonogenic ability in both U2OS and HOS cells upon UBE2L3 knockdown. Flow cytometry confirmed that UBE2L3 knockdown significantly enhanced apoptosis in U2OS and HOS cells. Immunofluorescence results showed that UBE2L3 silencing promoted oxidative stress levels in osteosarcoma cells and facilitated tumor cell death. WB analysis indicated a significant increase in phosphorylation levels of necroptosis-related proteins, RIP1, RIP3, and MLKL, in both osteosarcoma cell lines after UBE2L3 knockdown. In addition, the expression of necrosis-associated proteins was inhibited by the addition of the antioxidant N-acetylcysteine (NAC).

CONCLUSION

UBE2L3 is upregulated in osteosarcoma cells, and silencing of UBE2L3 promotes oxidative stress in these cells, leading to enhanced necroptosis and delayed progression of osteosarcoma.

Analysis of foot-originating malignant bone tumors: Epidemiology, characteristics, and survival outcomes

BACKGROUND

The study examines the characteristics and outcomes of foot-originating malignant bone tumors via Surveillance Epidemiology and End Results (SEER) database analysis.

METHODS

A retrospective review of 14,695 malignant bone tumor cases from 2000 to 2019 was conducted.

RESULTS

Of the eligible cases, 147 (2.3 %) were foot-origin tumors, typically smaller and more commonly treated with surgery than those in other locations. These tumors were more frequently treated with surgical resection, with a higher proportion undergoing amputation. In contrast, foot-origin tumors were less often managed with chemotherapy and radiation. Foot-origin tumors exhibited higher survival rates compared to non-foot-origin tumors as shown in univariate analysis, although multivariate analysis did not reflect significant differences.

CONCLUSION

Foot-originating malignant bone tumors tend to be smaller and are frequently surgically treated, correlating with favorable survival outcomes. These findings point to early detection as a potential factor in the improved survival rates, not necessarily the tumor's origin.

Automated detection of bone lesions using CT and MRI: a systematic review

PURPOSE

The aim of this study was to systematically review the use of automated detection systems for identifying bone lesions based on CT and MRI, focusing on advancements in artificial intelligence (AI) applications.

MATERIALS AND METHODS

A literature search was conducted on PubMed and MEDLINE. Data were extracted and grouped into three main categories, namely baseline study characteristics, model validation strategies, and the type of AI algorithms.

RESULTS

A total of 10 studies were selected and analyzed, including 2,768 patients overall with a median of 187 per study. These studies utilized various AI algorithms, predominantly deep learning models (6 studies) such as Convolutional Neural Networks. Among machine learning validation strategies, K-fold cross-validation was the mostly used (5 studies). Clinical validation was performed using data from the same institution (internal testing) in 8 studies and from both the same and different (external testing) institutions in 1 study, respectively.

CONCLUSION

AI, particularly deep learning, holds significant promise in enhancing diagnostic accuracy and efficiency. However, the review highlights several limitations, such as the lack of standardized validation methods and the limited use of external datasets for testing. Future research should address these gaps to ensure the reliability and applicability of AI-based detection systems in clinical settings.

Development of Machine Learning Models for Predicting the 1-Year Risk of Reoperation After Lower Limb Oncological Resection and Endoprosthetic Reconstruction Based on Data From the PARITY Trial

BACKGROUND

Oncological resection and reconstruction involving the lower extremities commonly lead to reoperations that impact patient outcomes and healthcare resources. This study aimed to develop a machine learning (ML) model to predict this reoperation risk.

METHODS

This study was conducted according to TRIPOD + AI. Data from the PARITY trial was used to develop ML models to predict the 1-year reoperation risk following lower extremity oncological resection and reconstruction. Six ML algorithms were tuned and calibrated based on fivefold cross-validation. The best-performing model was identified using classification and calibration metrics.

RESULTS

The polynomial support vector machine (SVM) model was chosen as the best-performing model. During internal validation, the SVM exhibited an AUC-ROC of 0.73 and a Brier score of 0.17. Using an optimal threshold that balances all quadrants of the confusion matrix, the SVM exhibited a sensitivity of 0.45 and a specificity of 0.81. Using a high-sensitivity threshold, the SVM exhibited a sensitivity of 0.68 and a specificity of 0.68. Total operative time was the most important feature for reoperation risk prediction.

CONCLUSION

The models may facilitate reoperation risk stratification, allowing for better patient counseling and for physicians to implement measures that reduce surgical risks.

The causal relationship between gut microbiota and 2 neoplasms, malignant and benign neoplasms of bone and articular cartilage: A two-sample Mendelian randomization study

Previous research has demonstrated a close connection between the development of bone neoplasms and variations in the abundance of specific gut microbiota. It remains unclear, however, how the gut microbiota and bone neoplasms are causally related. Hence, in our study, we aim to clarify this relationship between gut microbiota and 2 neoplasms, malignant neoplasm of bone and articular cartilage (MNBAC) and benign neoplasm of bone and articular cartilage (BNBAC), by employing a two-sample Mendelian randomization (MR) approach. In this study, single nucleotide polymorphisms (SNPs) from genome-wide association studies-pooled data related to bone neoplasms and gut microbiota abundance were evaluated. The inverse variance weighted was employed as the major method for assessing the aforementioned causal relationship. Furthermore, the horizontal multiplicity was evaluated utilizing the Mendelian randomization pleiotropy residual sum and outlier and the MR-Egger intercept test. Finally, inverse MR analysis was performed to assess reverse causality. Inverse variance weighted results indicate a potential genetic relationship between 4 gut microbiota and MNBAC, and 3 gut microbiota and BNBAC. On the one hand, Eubacterium eligens group (OR = 0.16, 95% CI = 0.04-0.67, P = .01), Odoribacter (OR = 0.23, 95% CI = 0.06-0.84, P = .03), Slackia (OR = 0.35, 95% CI = 0.13-0.93, P = .04), and Tyzzerella3 (OR = 0.44, 95% CI = 0.24-0.82, P = .01) exhibited a protective effect against MNBAC. On the other hand, of the 3 gut microbes identified as potentially causally related to BNBAC, Oscillibacter (OR = 0.79, 95% CI = 0.63-0.98, P = .03) and Ruminococcus torques group (OR = 0.62, 95% CI = 0.39-0.98, P = .04) were regarded as protective strains of B, while Eubacterium ruminantium group (OR = 1.24, 95% CI = 1.04-1.47, P = .02) was considered to be a risk factor for increasing the incidence of BNBAC. Additionally, the bone neoplasms were not found to have a reverse causal relationship with the above 7 gut microbiota taxa. Four gut microbiota showed causal effects on MNBAC, and 3 gut microbiota demonstrated causality in BNBAC, providing insights into the design of future interventions to reduce the burden of neoplasms.

Exploring Pediatric Vertebral, Sacral, and Pelvic Osteosarcomas through the NCDB: Demographics, Treatment Utilization, and Survival Outcomes

BACKGROUND AND OBJECTIVES

Retrieve data from the National Cancer Database (NCDB) to examine information on the epidemiological prevalence, treatment strategies, and survival outcomes of pediatric vertebral, sacral and pelvic osteosarcomas.

METHODS

We reviewed NCDB data from 2008 to 2018, concentrating on vertebral, sacral, and pelvic osteosarcomas in children 0 to 21 years. Our analysis involved logistic and Poisson regression, Kaplan-Meier survival estimates, and Cox proportional hazards models.

RESULTS

The study population included 207 patients. For vertebral osteosarcomas, 62.5% of patients were female, and 78.1% were white. Regional lymph node involvement predicted 80 times higher mortality hazard (p = 0.021). Distant metastasis predicted 25 times higher mortality hazard (p = 0.027). For sacral and pelvic osteosarcomas, 58.3% of patients were male, and 72% were white. Patients with residual tumor were 4 times more likely to have prolonged LOS (p = 0.031). No residual tumor (HR = 0.53, p = 0.03) and radiotherapy receipt (HR = 0.46, p = 0.034) were associated with lower mortality hazards. Distant metastasis predicted 3 times higher mortality hazard (p < 0.001). Hispanic ethnicity was linked to lower resection odds (OR = 0.342, p = 0.043), possibly due to language barriers affecting patient understanding and care decisions.

CONCLUSIONS

In conclusion, our examination of NCDB offers a thorough exploration of demographics, treatment patterns, and results, highlighting the importance of personalized approaches to enhance patient outcomes.

Cucurbitacin B modulates M2 macrophage differentiation and attenuates osteosarcoma progression via PI3K/AKT pathway

Osteosarcoma is a common malignant bone tumour characterised by an aggressive metastatic potential. The tumour microenvironment, particularly the M2-polarised macrophages, is crucial for tumour progression. Cucurbitacin B (CuB), a triterpenoid derivative, is recognised for its anti-inflammatory and antitumour properties. This study investigates CuB and its effect on M2 macrophage differentiation and osteosarcoma progression, aiming to contribute to new treatment strategies. In vitro, THP-1 monocytes were stimulated with PMA, IL-13 and IL-4 to induce differentiation into M2 macrophages. Additionally, the influence of CuB on the proliferation, migration and invasion of osteosarcoma cells in the context of M2 macrophages was scrutinised. Crucial signalling pathways, especially the PI3K/AKT pathway, affected by CuB were identified and validated. In vivo, the osteosarcoma model was employed to gauge the effects of CuB on tumour weight, lung metastasis, angiogenesis, cell proliferation and M2 macrophage markers. The results showed that CuB inhibited M2 macrophage differentiation, leading to reduced proliferation, migration and invasion of osteosarcoma cells. CuB manifested an inhibitory effect on the PI3K/AKT pathway during the differentiation of M2 macrophages. In mouse models, CuB markedly reduced the tumour weight and the number of lung metastases. It also reduced the expression of angiogenesis and cell proliferation markers in tumour tissues, decreased the quantity of M2 macrophages and their associated markers and pathway proteins. In conclusion, CuB impedes osteosarcoma progression by inhibiting M2 macrophage differentiation via the PI3K/AKT pathway, presenting the potential for therapeutic advancements in osteosarcoma treatment.

Single-cell aggrephagy-related patterns facilitate tumor microenvironment intercellular communication, influencing osteosarcoma progression and prognosis

Osteosarcoma, a common malignant tumor in children, has emerged as a major threat to the life and health of pediatric patients. Presently, there are certain limitations in the diagnosis and treatment methods for this disease, resulting in inferior therapeutic outcomes. Therefore, it is of great importance to study its pathogenesis and explore innovative approaches to diagnosis and treatment. In this study, a non-negative matrix decomposition method was employed to conduct a comprehensive investigation and analysis of aggregated autophagy-related genes within 331,394 single-cell samples of osteosarcoma. Through this study, we have elucidated the intricate communication patterns among various cells within the tumor microenvironment. Based on the classification of aggregated autophagy-related genes, we are not only able to more accurately predict patients' prognosis but also offer robust guidance for treatment strategies. The findings of this study hold promise for breakthroughs in the diagnosis and treatment of osteosarcoma, intervention of aggrephagy is expected to improve the survival rate and quality of life of osteosarcoma patients.

Identification of TNFRSF1A as a potential biomarker for osteosarcoma

BACKGROUND

Osteosarcoma (OS) is a relatively rare malignant bone tumor in teenagers; however, its molecular mechanisms are not yet understood comprehensively.

OBJECTIVE

The study aimed to use necroptosis-related genes (NRGs) and their relationships with immune-related genes to construct a prognostic signature for OS.

METHODS

TARGET-OS was used as the training dataset, and GSE 16091 and GSE 21257 were used as the validation datasets. Univariate regression, survival analysis, and Kaplan-Meier curves were used to screen for hub genes. The immune-related targets were screened using immune infiltration assays and immune checkpoints. The results were validated using nomogram and decision curve analyses (DCA).

RESULTS

Using univariate Cox regression analysis, TNFRSF1A was screened from 14 NRGs as an OS prognostic signature. Functional enrichment was analyzed based on the median expression of TNFRSF1A. The prognosis of the TNFRSF1A low-expression group in the Kaplan-Meier curve was notably worse. Immunohistochemistry analysis showed that the number of activated T cells and tumor purity increased considerably. Furthermore, the immune checkpoint lymphocyte activation gene 3 (LAG-3) is a possible target for intervention. The nomogram accurately predicted 1-, 3-, and 5-year survival rates. DCA validated the model (C = 0.669).

Conclusion

TNFRSF1A can be used to elucidate the potential relationship between the immune microenvironment and NRGs in OS pathogenesis.