Osteosarcoma, chondrosarcoma and Ewing sarcoma: Clinical aspects, biomarker discovery and liquid biopsy

A comprehensive overview of liquid biopsy applications in pediatric solid tumors

Liquid biopsies are emerging as an alternative source for pediatric cancer biomarkers with potential applications during all stages of patient care, from diagnosis to long-term follow-up. While developments within this field are reported, these mainly focus on dedicated items such as a specific liquid biopsy matrix, analyte, and/or single tumor type. To the best of our knowledge, a comprehensive overview is lacking. Here, we review the current state of liquid biopsy research for the most common non-central nervous system pediatric solid tumors. These include neuroblastoma, renal tumors, germ cell tumors, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma and other soft tissue sarcomas, and liver tumors. Within this selection, we discuss the most important or recent studies involving liquid biopsy-based biomarkers, anticipated clinical applications, and the current challenges for success. Furthermore, we provide an overview of liquid biopsy-based biomarker publication output for each tumor type based on a comprehensive literature search between 1989 and 2023. Per study identified, we list the relevant liquid biopsy-based biomarkers, matrices (e.g., peripheral blood, bone marrow, or cerebrospinal fluid), analytes (e.g., circulating cell-free and tumor DNA, microRNAs, and circulating tumor cells), methods (e.g., digital droplet PCR and next-generation sequencing), the involved pediatric patient cohort, and proposed applications. As such, we identified 344 unique publications. Taken together, while the liquid biopsy field in pediatric oncology is still behind adult oncology, potentially relevant publications have increased over the last decade. Importantly, steps towards clinical implementation are rapidly gaining ground, notably through validation of liquid biopsy-based biomarkers in pediatric clinical trials.

Machine learning and experimental analyses identified miRNA expression models associated with metastatic osteosarcoma

Osteosarcoma (OS), as the most common primary bone cancer, has a high invasiveness and metastatic potential, therefore, it has a poor prognosis. This study identified early diagnostic biomarkers using miRNA expression profiles associated with osteosarcoma metastasis. In the first step, we used RNA-seq and online microarray data from osteosarcoma tissues and cell lines to identify differentially expressed miRNAs. Then, using seven feature selection algorithms for ranking, the first-ranked miRNAs were selected as input for five machine learning systems. Using network analysis and machine learning algorithms, we developed new diagnostic models that successfully differentiated metastatic osteosarcoma from non-metastatic samples based on newly discovered miRNA signatures. The results showed that miR-34c-3p and miR-154-3p act as the most promising models in the diagnosis of metastatic osteosarcoma. Validation for this model by RT-qPCR in benign tissue and osteosarcoma biopsies confirmed the lower expression of miR-34c-3p and miR-154-3p in OS samples. In addition, a direct correlation between miR-34c-3p expression, miR-154-3p expression and tumor grade was discovered. The combined values of miR-34c-3p and miR-154-3p showed 90 % diagnostic power (AUC = 0.90) for osteosarcoma samples and 85 % (AUC = 0.85) for metastatic osteosarcoma. Adhesion junction and focal adhesion pathways, as well as epithelial-to-mesenchymal transition (EMT) GO terms, were identified as the most significant KEGG and GO terms for the top miRNAs. The findings of this study highlight the potential use of novel miRNA expression signatures for early detection of metastatic osteosarcoma. These findings may help in determining therapeutic approaches with a quantitative and faster method of metastasis detection and also be used in the development of targeted molecular therapy for this aggressive cancer. Further research is needed to confirm the clinical utility of miR-34c-3p and miR-154-3p as diagnostic biomarkers for metastatic osteosarcoma.

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.

Tumor-informed deep sequencing of ctDNA detects minimal residual disease and predicts relapse in osteosarcoma

Background

Current surveillance modalities of osteosarcoma relapse exhibit limited sensitivity and specificity. Although circulating tumor DNA (ctDNA) has been established as a biomarker of minimal residual disease (MRD) in many solid tumors, a sensitive ctDNA detection technique has not been thoroughly explored for longitudinal MRD detection in osteosarcoma.

Methods

From August 2019 to June 2023, 59 patients diagnosed with osteosarcoma at the First Affiliated Hospital of Sun Yat-sen University were evaluated in this study. Tumor-informed MRD panels were developed through whole exome sequencing (WES) of tumor tissues. Longitudinal blood samples were collected during treatment and subjected to multiplex PCR-based next-generation sequencing (NGS). Kaplan-Meier curves and Log-rank tests were used to compare outcomes, and Cox regression analysis was performed to identify prognostic factors.

Findings

WES analysis of 83 patients revealed substantial mutational heterogeneity, with non-recurrent mutated genes accounting for 58.1%. Tumor-informed MRD panels were successfully obtained for 85.5% of patients (71/83). Among 59 patients with successful MRD panel customization and available blood samples, 13 patients exhibited positive ctDNA detection after surgery. Patients with negative post-operative ctDNA had better event-free survival (EFS) compared to those with positive ctDNA, at 1-6 months after surgery, after adjuvant chemotherapy, and more than 6 months after surgery (p < 0.05). In both univariate and multivariate Cox regression analysis, ctDNA results emerged as a significant predictor of EFS (p < 0.05). ctDNA detection preceded positive imaging in 5 patients, with an average lead time of 92.6 days. Thirty-nine patients remained disease-free, with ctDNA results consistently negative or turning negative during follow-up.

Interpretation

Our study underscores the applicability of tumor-informed deep sequencing of ctDNA in osteosarcoma MRD surveillance and, to our knowledge, represents the largest cohort to date. ctDNA detection is a significant prognostic factor, enabling the early identification of tumor relapse and progression compared to standard imaging, thus offering valuable insights in guiding osteosarcoma patient management.

Funding

The Grants of National Natural Science Foundation of China (No. 82072964, 82072965, 82203798, 82203026), the Natural Science Foundation of Guangdong (No. 2023A1515012659, 2023A1515010302), and the Regional Combination Project of Basic and Applied Basic Research Foundation of Guangdong (No. 2020A1515110010).

The role of programmed cell death in osteosarcoma: From pathogenesis to therapy

Osteosarcoma (OS) is a prevalent bone solid malignancy that primarily affects adolescents, particularly boys aged 14-19. This aggressive form of cancer often leads to deadly lung cancer due to its high migration ability. Experimental evidence suggests that programmed cell death (PCD) plays a crucial role in the development of osteosarcoma. Various forms of PCD, including apoptosis, ferroptosis, autophagy, necroptosis, and pyroptosis, contribute significantly to the progression of osteosarcoma. Additionally, different signaling pathways such as STAT3/c-Myc signal pathway, JNK signl pathway, PI3k/AKT/mTOR signal pathway, WNT/β-catenin signal pathway, and RhoA signal pathway can influence the development of osteosarcoma by regulating PCD in osteosarcoma cell. Therefore, targeting PCD and the associated signaling pathways could offer a promising therapeutic approach for treating osteosarcoma.

A Novel Clinical Tool to Predict Cancer-specific Survival in Postoperative Patients With Primary Spinal and Pelvic Sarcomas: A Large Population-Based Retrospective Cohort Study

STUDY DESIGN

Retrospective cohort study.

OBJECTIVE

Primary osseous sarcomas originating from the spine and pelvis are rare and usually portend inferior prognoses. Currently, the standard treatment for spinal and pelvic sarcomas is surgical resection, but the poor prognosis limits the benefits to postoperative patients. This study aims to identify the independent prognostic factors of cancer-specific survival (CSS) in postoperative patients with primary spinal and pelvic sarcomas and construct a nomogram for predicting these patients' 3-, 5-, and 10-year CSS probability.

METHODS

A total of 452 patients were enrolled from the Surveillance, Epidemiology, and End Results (SEER) database. They were divided into a training cohort and a validation cohort. Univariate and multivariate Cox regression analyses were used to identify these patients' CSS-related independent prognostic factors. Then, those factors were used to construct a prognostic nomogram for predicting the 3-, 5-, and 10-year CSS probability, whose predictive performance and clinical value were verified by the calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Finally, a mortality risk stratification system was constructed.

RESULTS

Sex, histological type, tumor stage, and tumor grade were identified as CSS-related independent prognostic factors. A nomogram with high predictive performance and good clinical value to predict the 3-, 5-, and 10-year CSS probability was constructed, on which a mortality risk stratification system was constructed based to divide these patients into 3 mortality risk subgroups effectively.

CONCLUSIONS

This study constructed and validated a clinical nomogram to predict CSS in postoperative patients with primary spinal and pelvic sarcomas. It could assist clinicians in classifying these patients into different mortality risk subgroups and realize sarcoma-specific management.

The clinical significance of indeterminate pulmonary nodules in patients with primary bone sarcoma: a systematic review

OBJECTIVE

To report the incidence of indeterminate pulmonary nodules (IPN) and the rate of progression of IPNs to metastasis in patients with primary bone cancers. We also aimed to evaluate clinical or radiological parameters that may identify IPNs more likely to progress to metastatic disease and their effect on overall or event-free survival in patients with primary bone sarcoma.

METHODS

A systematic search of the electronic databases Medline, Embase, and Cochrane Library was undertaken for eligible articles on IPNs in patients with primary bone sarcomas, published in the English language from inception of the databases to 2023. The Newcastle-Ottawa Quality Assessment Form for Cohort Studies was utilized to evaluate risk of bias in included studies.

RESULTS

Six studies, involving 1667 patients, were included in this systematic review. Pooled quantitative analysis found the rate of incidence of IPN to be 18.1% (302 out of 1667) and the rate of progression to metastasis to be 45.0% (136 out of 302). Nodule size (more than 5 mm diameter), number (more than or equal to 4), distribution (bilaterally distributed), incomplete calcification, and lobulated margins were associated with an increased likelihood of IPNs progressing to metastasis, however, their impact on overall or event-free survival remains unclear.

CONCLUSION

The risk of IPNs progressing to metastasis in patients with primary bone sarcoma is non-negligible. Large IPNs have a high risk to be an actual metastasis. We suggest that IPNs in these patients be followed up for a minimum of 2 years with CT imaging at 3, 6, and 12 month intervals, particularly for nodules measuring >5 mm in average diameter.

ADVANCES IN KNOWLEDGE

This is the first systematic review on IPNs in patients with primary bone sarcomas only and proposes viable management strategies for such patients.

Molecular characterization of Golgi apparatus-related genes indicates prognosis and immune infiltration in osteosarcoma

BACKGROUND

The Golgi apparatus (GA) is crucial for protein synthesis and modification, and regulates various cellular processes. Dysregulation of GA can lead to pathological conditions like neoplastic growth. GA-related genes (GARGs) mutations are commonly found in cancer, contributing to tumor metastasis. However, the expression and prognostic significance of GARGs in osteosarcoma are yet to be understood.

METHODS

Gene expression and clinical data of osteosarcoma patients were obtained from the TARGET and GEO databases. A consensus clustering analysis identified distinct molecular subtypes based on GARGs. Discrepancies in biological processes and immunological features among the subtypes were explored using GSVA, ssGSEA, and Metascape analysis. A GARGs signature was constructed using Cox regression. The prognostic value of the GARGs signature in osteosarcoma was evaluated using Kaplan-Meier curves and a nomogram.

RESULTS

Two GARG subtypes were identified, with Cluster A showing better prognosis, immunogenicity, and immune cell infiltration than Cluster B. A novel risk model of 3 GARGs was established using the TARGET dataset and validated with independent datasets. High-risk patients had poorer overall survival, and the GARGs signature independently predicted osteosarcoma prognosis. Combining risk scores and clinical characteristics in a nomogram improved prediction performance. Additionally, we discovered Stanniocalcin-2 (STC2) as a significant prognostic gene highly expressed in osteosarcoma and potential disease biomarker.

CONCLUSIONS

Our study revealed that patients with osteosarcoma can be divided into two GARGs subgroups. Furthermore, we have developed a GARGs prognostic signature that can accurately forecast the prognosis of osteosarcoma patients.

A deep learning model for accurately predicting cancer-specific survival in patients with primary bone sarcoma of the extremity: a population-based study

PURPOSE

Primary bone and joint sarcomas of the long bone are relatively rare neoplasms with poor prognosis. An efficient clinical tool that can accurately predict patient prognosis is not available. The current study aimed to use deep learning algorithms to develop a prediction model for the prognosis of patients with long bone sarcoma.

METHODS

Data of patients with long bone sarcoma in the extremities was collected from the Surveillance, Epidemiology, and End Results Program database from 2004 to 2014. Univariate and multivariate analyses were performed to select possible prediction features. DeepSurv, a deep learning model, was constructed for predicting cancer-specific survival rates. In addition, the classical cox proportional hazards model was established for comparison. The predictive accuracy of our models was assessed using the C-index, Integrated Brier Score, receiver operating characteristic curve, and calibration curve.

RESULTS

Age, tumor extension, histological grade, tumor size, surgery, and distant metastasis were associated with cancer-specific survival in patients with long bone sarcoma. According to loss function values, our models converged successfully and effectively learned the survival data of the training cohort. Based on the C-index, area under the curve, calibration curve, and Integrated Brier Score, the deep learning model was more accurate and flexible in predicting survival rates than the cox proportional hazards model.

CONCLUSION

A deep learning model for predicting the survival probability of patients with long bone sarcoma was constructed and validated. It is more accurate and flexible in predicting prognosis than the classical CoxPH model.

Graphene Oxide (GO) for the Treatment of Bone Cancer: A Systematic Review and Bibliometric Analysis

Cancer is a severe disease that, in 2022, caused more than 9.89 million deaths worldwide. One worrisome type of cancer is bone cancer, such as osteosarcoma and Ewing tumors, which occur more frequently in infants. This study shows an active interest in the use of graphene oxide and its derivatives in therapy against bone cancer. We present a systematic review analyzing the current state of the art related to the use of GO in treating osteosarcoma, through evaluating the existing literature. In this sense, studies focused on GO-based nanomaterials for potential applications against osteosarcoma were reviewed, which has revealed that there is an excellent trend toward the use of GO-based nanomaterials, based on their thermal and anti-cancer activities, for the treatment of osteosarcoma through various therapeutic approaches. However, more research is needed to develop highly efficient localized therapies. It is suggested, therefore, that photodynamic therapy, photothermal therapy, and the use of nanocarriers should be considered as non-invasive, more specific, and efficient alternatives in the treatment of osteosarcoma. These options present promising approaches to enhance the effectiveness of therapy while also seeking to reduce side effects and minimize the damage to surrounding healthy tissues. The bibliometric analysis of photothermal and photochemical treatments of graphene oxide and reduced graphene oxide from January 2004 to December 2022 extracted 948 documents with its search strategy, mainly related to research papers, review papers, and conference papers, demonstrating a high-impact field supported by the need for more selective and efficient bone cancer therapies. The central countries leading the research are the United States, Iran, Italy, Germany, China, South Korea, and Australia, with strong collaborations worldwide. At the same time, the most-cited papers were published in journals with impact factors of more than 6.0 (2021), with more than 290 citations. Additionally, the journals that published the most on the topic are high impact factor journals, according to the analysis performed, demonstrating the high impact of the research field.

The novel dynamic nomogram and risk classification system constructed for predicting post-surgical overall survival and mortality risk in primary chondrosarcoma: a population study based on SEER database

BACKGROUND

Surgery is the predominant method to improve the prognosis of primary chondrosarcoma patients. We aimed to construct the first reliable nomogram to predict the post-surgical overall survival (OS) of primary chondrosarcoma patients.

METHODS

We downloaded all primary chondrosarcoma patients treated with surgery between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database, and randomized them into training set (60%) and validation set (40%). Cox proportional regression analysis was applied to the training set to identify independent prognostic variables, and then constructed a nomogram for predicting 3-, 5-, and 8-year OS. The Harrell's concordance index (C-index), receiver operating characteristic curve (ROC), the area under curve (AUC), calibration curve and decision curve analysis (DCA) was used to assess the predictive efficacy and clinical applicability of the nomogram. The nomogram was also compared with The American Joint Committee on Cancer (AJCC) staging system.

RESULTS

A total of 1005 post-surgical primary chondrosarcoma patients were included in this study. We finally identified five independent prognostic variables to construct the nomogram, being age, grade, tumor size, disease stage and histological type. The C-index results showed that the prediction performance of the nomogram was significantly better than the AJCC staging system. In the training set, (C-index: 0.805, 95% CI 0.879-0.730 vs 0.686, 95% CI 0.606-0.766); in the validation set, (C-index: 0.811, 95% CI 0.895-0.727 vs 0.697, 95% CI 0.647-0.799). Additionally, the AUC values generated by the ROC were all greater than 0.8, which also indicated the excellent predictive performance of the nomogram. The calibration curves showed that the predicted survival rate was highly similar to the actual. Time-dependent ROC and DCA showed that the nomogram has better predictive performance and net clinical benefits than the AJCC staging system. Finally, a risk stratification system based on nomogram was constructed.

CONCLUSION

We successfully constructed and validated the first nomogram that could reliably predict 3-, 5-, and 8-year post-surgical OS in primary chondrosarcoma patients. Furthermore, the web-based dynamic nomogram could be more conveniently applied to clinic, providing assistance to surgeons and patients.

Lung and bone metastases patterns in limb osteosarcoma: Surgical treatment of primary site improves overall survival

Osteosarcoma (OS) is one of the most prevalent malignant bone tumors. The proportion of patients with limb OS was relatively high. Lung metastasis (LM) and bone metastasis are the first and second most common metastatic types of OS, respectively. A total of 270 new cases of LM, 55 new cases of bone metastases (BM), and 36 new cases of lung and BM were diagnosed in the surveillance, epidemiology and end results database from 2010 to 2019. Univariate and multivariate logistic regression analyses were used to identify the risk factors for lung and/or BM, and Cox regression analyses were performed to identify the prognostic factors for lung and/or BM. Kaplan-Meier curves and log-rank tests were used to analyze the overall survival of limb OS patients with lung and/or BM. Female sex, telangiectatic OS type, central OS type, T3 stage, N1 stage, BM, surgical treatments, radiotherapy and chemotherapy were significantly correlated with LM. T3 stage, LM, liver metastases, and radiotherapy significantly correlated with BM. The small cell OS type, T2 stage, T3 stage, N1 stage, liver metastases, and radiotherapy were significantly correlated with lung and BM. Among limb OS patients with LM, the mean survival months of older age, black race, N1 stage, BM, brain metastases, no surgery, and no chemotherapy were lower than those of the control group. In limb OS patients with LM and BM, the mean survival months in the no surgery group was lower than in the surgery group. T stage and radiotherapy significantly influence the occurrence of limb OS with lung and/or BM. Surgery at the primary site has been shown to be effective in improving the survival rate of patients with lung and/or BM.

Bone-targeting exosome nanoparticles activate Keap1 / Nrf2 / GPX4 signaling pathway to induce ferroptosis in osteosarcoma cells

BACKGROUND

In recent years, the development of BMSCs-derived exosomes (EXO) for the treatment of osteosarcoma (OS) is a safe and promising modality for OS treatment, which can effectively deliver drugs to tumor cells in vivo. However, the differences in the drugs carried, and the binding of EXOs to other organs limit their therapeutic efficacy. Therefore, improving the OS-targeting ability of BMSCs EXOs and developing new drugs is crucial for the clinical application of targeted therapy for OS.

RESULTS

In this study, we constructed a potential therapeutic nano platform by modifying BMSCs EXOs using the bone-targeting peptide SDSSD and encapsulated capreomycin (CAP) within a shell. These constructed nanoparticles (NPs) showed the ability of homologous targeting and bone-targeting exosomes (BT-EXO) significantly promotes cellular endocytosis in vitro and tumor accumulation in vivo. Furthermore, our results revealed that the constructed NPs induced ferroptosis in OS cells by prompting excessive accumulation of reactive oxygen species (ROS), Fe2+ aggregation, and lipid peroxidation and further identified the potential anticancer molecular mechanism of ferroptosis as transduced by the Keap1/Nrf2/GPX4 signaling pathway. Also, these constructed NP-directed ferroptosis showed significant inhibition of tumor growth in vivo with no significant side effects.

CONCLUSION

These results suggest that these constructed NPs have superior anticancer activity in mouse models of OS in vitro and in vivo, providing a new and promising strategy for combining ferroptosis-based chemotherapy with targeted therapy for OS.

Ewing sarcoma from molecular biology to the clinic

In Europe, with an incidence of 7.5 cases per million, Ewing sarcoma (ES) is the second most common primary malignant bone tumor in children, adolescents and young adults, after osteosarcoma. Since the 1980s, conventional treatment has been based on the use of neoadjuvant and adjuvant chemotherapeutic agents combined with surgical resection of the tumor when possible. These treatments have increased the patient survival rate to 70% for localized forms, which drops drastically to less than 30% when patients are resistant to chemotherapy or when pulmonary metastases are present at diagnosis. However, the lack of improvement in these survival rates over the last decades points to the urgent need for new therapies. Genetically, ES is characterized by a chromosomal translocation between a member of the FET family and a member of the ETS family. In 85% of cases, the chromosomal translocation found is (11; 22) (q24; q12), between the EWS RNA-binding protein and the FLI1 transcription factor, leading to the EWS-FLI1 fusion protein. This chimeric protein acts as an oncogenic factor playing a crucial role in the development of ES. This review provides a non-exhaustive overview of ES from a clinical and biological point of view, describing its main clinical, cellular and molecular aspects.

MicroRNA PC-3p-2869 Regulates Antler Growth and Inhibits Proliferation and Migration of Human Osteosarcoma and Chondrosarcoma Cells by Targeting CDK8, EEF1A1, and NTN1

MicroRNAs (miRNAs) play a crucial role in maintaining the balance between the rapid growth and suppression of tumorigenesis during antler regeneration. This study investigated the role of a novel miRNA, PC-3p-2869 (miR-PC-2869), in antler growth and its therapeutic potential in human osteosarcoma and chondrosarcoma. Stem-loop RT-qPCR showed that miR-PC-2869 was expressed extensively in diverse layers of antler tissues. Overexpression of miR-PC-2869 suppressed the proliferation and migration of antler cartilage cells. Similarly, heterologous expression of miR-PC-2869 reduced the proliferation, colony formation, and migration of osteosarcoma cell line MG63 and U2OS and chondrosarcoma cell line SW1353. Moreover, 18 functional target genes of miR-PC-2869 in humans were identified based on the screening of the reporter library. Among them, 15 target genes, including CDK8, EEF1A1, and NTN1, possess conserved miR-PC-2869-binding sites between humans and red deer (Cervus elaphus). In line with this, miR-PC-2869 overexpression decreased the expression levels of CDK8, EEF1A1, and NTN1 in MG63, SW1353, and antler cartilage cells. As expected, the knockdown of CDK8, EEF1A1, or NTN1 inhibited the proliferation and migration of MG63, SW1353, and antler cartilage cells, demonstrating similar suppressive effects as miR-PC-2869 overexpression. Furthermore, we observed that CDK8, EEF1A1, and NTN1 mediated the regulation of c-myc and cyclin D1 by miR-PC-2869 in MG63, SW1353, and antler cartilage cells. Overall, our work uncovered the cellular functions and underlying molecular mechanism of antler-derived miR-PC-2869, highlighting its potential as a therapeutic candidate for bone cancer.

Circulating Exosomal PD-L1 at Initial Diagnosis Predicts Outcome and Survival of Patients with Osteosarcoma

PURPOSE

It is difficult to predict prognosis of patients with osteosarcoma at initial diagnosis due to lack of efficient prognostic parameters. We evaluated the relationship between level of circulating serum exosomal PD-L1 (Sr-exosomal PD-L1) at initial diagnosis and oncologic outcome during the follow-up.

EXPERIMENTAL DESIGN

Sixty-seven patients with newly diagnosed osteosarcoma were prospectively recruited. Fasting blood was collected and exosome isolation was performed using ultracentrifugation method. Evaluation of Sr-exosomal PD-L1 was performed respectively by immunogold labeling and ELISA method. Correlation between level of Sr-exosomal PD-L1 at initial diagnosis and clinical risk factors was assessed.

RESULTS

Mean follow-up was 46.7 months. Two-year and 5-year overall survival (OS) rates were respectively 96.9% and 62.5%. Two-year and 5-year disease-free survival (DFS) rates were respectively 85.0% and 31.4%. Results revealed a significantly positive association between high PD-L1 cargo of circulating exosomes and clinicopathologic disease markers such as pulmonary metastasis, multiple metastasis, and death. Patients who died of disease at final follow-up had higher level of Sr-exosomal PD-L1 at initial diagnosis, which compared with patients who were still alive at last follow-up. Patients in group of ≥14.23 pg/mL Sr-exosomal PD-L1 at initial diagnosis had inferior DFS compared with patients in group of <14.23 pg/mL at initial diagnosis. Patients in group of ≥25.96 pg/mL at initial diagnosis had poor OS compared with patients in group of <25.96 pg/mL at initial diagnosis.

CONCLUSIONS

Use of liquid biopsy of circulating exosomal PD-L1 at initial diagnosis provides a robust means of predicting prognosis for patients with a newly diagnosed osteosarcoma.

Lung and bone metastases patterns in osteosarcoma: Chemotherapy improves overall survival

Osteosarcoma (OS) is a malignant tumor originating from the mesenchymal tissue. Simultaneous reports of lung and bone metastases (BM) in OS are rare in the literature. A total of 353 new cases of lung metastases (LM), 93 new cases of BM, and 59 new cases of LM and BM were diagnosed in the Surveillance, Epidemiology and End Results (SEER) database from 2010 to 2019. Univariate and multivariate logistic regression analyses were used to identify risk factors for LM and/or BM, and Cox regression analyses were performed to identify the prognostic factors for LM and/or BM. Kaplan-Meier (K-M) curves and log-rank tests were used to analyze the overall survival of patients with LM and/or BM. LM was diagnosed in 353 patients. Female sex, tumor size >100 mm, telangiectatic OS type, central OS type, N1 stage, other locations, BM, surgical treatments, radiotherapy and chemotherapy were significantly correlated with LM. 93 patients were diagnosed with BM. 25 to 59 years old, T1 stage, presence of LM, liver metastases, radiotherapy, and surgical treatments were significantly correlated with the BM. 59 patients were diagnosed with LM and BM. The chondroblastic OS type, small cell OS type, T1 stage, N1 stage, other locations, liver metastases, radiotherapy, and surgical treatments were significantly correlated with LM and BM. Metastases, radiotherapy, and surgery at the primary site were significantly associated with LM and/or BM. Chemotherapy at the primary site has been shown to be effective in improving the survival rate of LM and/or BM. Of the OS patients with LM, 61.47% died, and older age, BM, no surgery, and no chemotherapy were harmful to survival. 72.04% of OS patients with BM died, and N1 stage, no surgery, and no chemotherapy were harmful for survival. 69.49% of OS patients with LM and BM died, and older age and no chemotherapy were harmful for survival.

Lung metastases pattern in limb osteosarcoma: A population-based study from 2010 to 2018

Osteosarcoma (OS) is one of the most prevalent malignant bone tumors. The proportion of limb OS is relatively high, and lung metastases (LM) are one of the most prevalent metastatic types. A total of 1694 new cases of limb OS were identified in the surveillance, epidemiology and end results (SEER) database from 2010 to 2018. Cox regression analyze was performed to identify prognostic factors for limb OS with LM, and univariate and multivariate logistic regression analyses were used to assess risk factors for LM. Kaplan-Meier analysis was performed to calculate overall survival for LM, and a log-rank test was used for comparison. A total of 287 patients (16.94%) were diagnosed with limb OS with LM. 25 to 59 years old (odds ratio, OR 0.68; 95% confidence interval, CI: 0.46-0.99), larger than 100 mm tumors (OR 3.65, 95% CI: 1.54-8.64), telangiectatic osteosarcoma type (OR 0.24, 95% CI: 0.07-0.81), central osteosarcoma type (OR 0.44, 95% CI: 0.19-0.99), T2 stage (OR 2.59, 95% CI: 1.18-5.69), N1 stage (OR 7.79, 95% CI: 3.90-15.56), presence of bone metastases (OR 4.58, 95% CI: 2.43-8.63) and surgical treatments of primary site (OR 0.22, 95% CI: 0.14-0.33) were significant correlations with lung metastases. Elderly age, black race and absence of surgery were harmful for survival. Age between 25 and 59 years, telangiectatic osteosarcoma and central osteosarcoma were identified as high-risk factors in limb OS patients with LM, and surgical treatment of the primary site significantly increased the survival rate of LM in these patients.

Relevance of Abnormal KCNN1 Expression and Osmotic Hypersensitivity in Ewing Sarcoma

Simple Summary

The main oncogene in Ewing sarcoma directly drives a high expression of a previously unknown variant KCNN1 (encoding the K_Ca2.1 channel) that we also verified in samples from >200 patients. Yet, we found that the channel is not functional and does not modulate Ewing sarcoma cell behavior. We could explain this lack of functional impact by the surprising absence of any K_Ca2.1-carried K⁺ current in Ewing sarcoma cells. However, we show in a proof-of-principle study that the essential lack of a K⁺ conductance can be exploited by applying hypoosmotic stress and effectively and selectively killing the Ewing sarcoma cells.

Abstract

Ewing sarcoma (EwS) is a rare and highly malignant bone tumor occurring mainly in childhood and adolescence. Physiologically, the bone is a central hub for Ca²⁺ homeostasis, which is severely disturbed by osteolytic processes in EwS. Therefore, we aimed to investigate how ion transport proteins involved in Ca²⁺ homeostasis affect EwS pathophysiology. We characterized the expression of 22 candidate genes of Ca²⁺-permeable or Ca²⁺-regulated ion channels in three EwS cell lines and found the Ca²⁺-activated K⁺ channel K_Ca2.1 (KCNN1) to be exceptionally highly expressed. We revealed that KCNN1 expression is directly regulated by the disease-driving oncoprotein EWSR1-FL1. Due to its consistent overexpression in EwS, KCNN1 mRNA could be a prognostic marker in EwS. In a large cohort of EwS patients, however, KCNN1 mRNA quantity does not correlate with clinical parameters. Several functional studies including patch clamp electrophysiology revealed no evidence for K_Ca2.1 function in EwS cells. Thus, elevated KCNN1 expression is not translated to K_Ca2.1 channel activity in EwS cells. However, we found that the low K⁺ conductance of EwS cells renders them susceptible to hypoosmotic solutions. The absence of a relevant K⁺ conductance in EwS thereby provides an opportunity for hypoosmotic therapy that can be exploited during tumor surgery.

Subtype Classification and Prognosis Signature Construction of Osteosarcoma Based on Cellular Senescence-Related Genes

Background. Cellular senescence (CS) is an alternative procedure that replaces or reinforces inadequate apoptotic responses and is used as an influencing factor for a variety of cancers. The value of CS gene in evaluating the immunotherapy response and clinical outcome of osteosarcoma (OS) has not been reported, and an accurate risk model based on CS gene has not been developed for OS patients. Methods. 279 CS genes were obtained from CellAge. Univariate Cox regression analysis was used to screen the CS gene which was significantly related to the prognosis of OS samples in TARGET data set. The prognosis, clinicopathological features, immune infiltration, gene expression at immune checkpoints, tumor immune dysfunction and exclusion (TIDE) score, and chemotherapy resistance of OS were analyzed among clusters. Least absolute shrinkage and selection operator (Lasso) Cox regression analysis to build cellular senescence-related gene signature (CSRS). Univariate and multivariate Cox regression analysis of CSRS and clinical parameters were carried out, and the parameters with independent prognostic value were used to construct nomogram. Results. Based on 30 CS genes related to OS prognosis, OS samples were divided into three clusters: C1, C2, and C3. C3 showed the lowest survival rate and metastasis rate and the highest immune score and stromal score and was more likely to respond to immune checkpoint blockade (ICB) treatment. A CSRS scoring system including four CS genes (MYC, DLX2, EPHA3, and LIMK1) was constructed, which could distinguish the survival outcome, tumor microenvironment (TME) status, and ICB treatment response of patients with different CSRS score. Nomogram constructed by CSRS score and metastatic has a high prognostic value for OS. Conclusions. Our study identified a molecular classification determined by CS-related genes and developed a new CSRS that has potential value in OS immunotherapy response and clinical outcome prediction.

Clinical Characteristics, Prognostic Factor and a Novel Dynamic Prediction Model for Overall Survival of Elderly Patients With Chondrosarcoma: A Population-Based Study

Background

Chondrosarcoma is the most common primary bone sarcoma among elderly population. This study aims to explore independent prognostic factors and develop prediction model in elderly patients with CHS.

Methods

This study retrospectively analyzed the clinical data of elderly patients diagnosed as CHS between 2004 and 2018 from the Surveillance, Epidemiology, and End Results (SEER) database. We randomly divided enrolled patients into training and validation group, univariate and multivariate Cox regression analyses were used to determine independent prognostic factors. Based on the identified variables, the nomogram was developed and verified to predict the 12-, 24-, and 36-month overall survival (OS) of elderly patients with CHS. A k-fold cross-validation method (k=10) was performed to validate the newly proposed model. The discrimination, calibration and clinical utility of the nomogram were assessed using the Harrells concordance index (C-index), receiver operating characteristic (ROC) curve and the area under the curve (AUC), calibration curve, decision curve analysis (DCA), the integrated discrimination improvement (IDI) and net reclassification index (NRI). Furthermore, a web-based survival calculator was developed based on the nomogram.

Results

The study finally included 595 elderly patients with CHS and randomized them into the training group (419 cases) and validation group (176 cases) at a ratio of 7:3. Age, sex, grade, histology, M stage, surgery and tumor size were identified as independent prognostic factors of this population. The novel nomogram displayed excellent predictive performance, which can be accessible by https://nomoresearch.shinyapps.io/elderlywithCHS/, with a C-index of 0.800 for the training group and 0.789 for the validation group. The value AUC values at 12-, 24-, and 36-month of 0.866, 0.855, and 0.860 in the training group and of 0.839, 0.856, and 0.840 in the validation group, respectively. The calibration curves exhibited good concordance from the predicted survival probabilities to actual observation. The ROC curves, IDI, NRI, and DCA showed the nomogram was superior to the existing AJCC staging system.

Conclusion

This study developed a novel web-based nomogram for accurately predicting probabilities of OS in elderly patients with CHS, which will contribute to personalized survival assessment and clinical management for elderly patients with CHS.

Trends in Tumor Site-Specific Survival of Bone Sarcomas from 1980 to 2018: A Surveillance, Epidemiology and End Results-Based Study

OBJECTIVES

As diagnosis and treatment guidelines for bone sarcomas continue updating, it is important to examine whether, when, and which kinds of patients have had a survival improvement over the last four decades.

METHODS

This cohort study included 9178 patients with primary bone and joint sarcomas from 1 January 1980 to 31 December 2018 using data from Surveillance, Epidemiology and End Results (SEER)-9 Registries. The follow-up period was extended to November 2020. Patients were divided by decade into four time periods: 1980-1989, 1990-1999, 2000-2009, and 2010-2018. The primary endpoint was bone sarcomas-specific mortality (CSM). The 5-year bone sarcomas-specific survival (CSS) rate was determined stratified by demographic, neoplastic, temporal, economic, and geographic categories. The associations between time periods and CSM were examined using a multivariable Cox regression model, with reported hazard ratio (HR) and 95% confidence interval (CI).

RESULTS

The 5-year CSS rate for bone sarcomas was 58.7%, 69.9%, 71.0%, and 69.2%, in the 1980s, 1990s, 2000s, and 2010s, respectively. Older age, male gender, tumor sites at pelvic bones, sacrum, coccyx and associated joints, as well as vertebral column, osteosarcoma and Ewing tumor, and residence in non-metropolitan areas were independently associated with higher CSM risk. After adjusting for the covariates above, patients in the 1990s (HR = 0.74, 95% CI = 0.68-0.82), 2000s (HR = 0.71, 95% CI = 0.65-0.78), and 2010s (HR = 0.68, 95% CI = 0.62-0.76) had significantly lower CSM risks than patients in the 1980s. However, patients in the 2000s and 2010s did not have lower CSM risks than those in the 1990s (both p > 0.05).

CONCLUSIONS

Although bone sarcomas survival has significantly improved since 1990, it almost halted over the next three decades. Bone sarcomas survival should improve over time, similar to common cancers. New diagnostic and therapeutic strategies such as emerging immune and targeted agents are warranted to overcome this survival stalemate.

The basic characteristics of extracellular vesicles and their potential application in bone sarcomas

Bone sarcomas are rare cancers accompanied by metastatic disease, mainly including osteosarcoma, Ewing sarcoma and chondrosarcoma. Extracellular vesicles (EVs) are membrane vesicles released by cells in the extracellular matrix, which carry important signal molecules, can stably and widely present in various body fluids, such as plasma, saliva and scalp fluid, spinal cord, breast milk, and urine liquid. EVs can transport almost all types of biologically active molecules (DNA, mRNA, microRNA (miRNA), proteins, metabolites, and even pharmacological compounds). In this review, we summarized the basic biological characteristics of EVs and focused on their application in bone sarcomas. EVs can be use as biomarker vehicles for diagnosis and prognosis in bone sarcomas. The role of EVs in bone sarcoma has been analyzed point-by-point. In the microenvironment of bone sarcoma, bone sarcoma cells, mesenchymal stem cells, immune cells, fibroblasts, osteoclasts, osteoblasts, and endothelial cells coexist and interact with each other. EVs play an important role in the communication between cells. Based on multiple functions in bone sarcoma, this review provides new ideas for the discovery of new therapeutic targets and new diagnostic analysis.

Identification of abnormally high expression of POGZ as a new biomarker associated with a poor prognosis in osteosarcoma

Osteosarcoma (OS) is the most prevalent malignant bone tumor in children and young adults. There is an urgent need for a novel biomarker related to the prognosis of OS. We performed a meta-analysis incorporating six independent datasets and performed a survival analysis with one independent dataset GSE21257 in the GEO database for gene screening. The results revealed that one potential biomarker related to OS survival, POGZ was the most significantly upregulated gene. We also verified that the POGZ was overexpressed in clinical samples. The survival analysis revealed that POGZ is associated with a poor prognosis in OS. Moreover, flow cytometry analysis of isolated OS cells demonstrated that OS cells were arrested in the G1 phase after POGZ knockdown. The RNA-seq results indicated that POGZ was co-expressed with CCNE1 and CCNB1. Pathway analysis showed that genes associated with high expression levels of POGZ were related to the cell cycle pathway. A cell model was constructed to detect the effects of POGZ. After POGZ knockdown, OS cell proliferation, invasion and migration were all decreased. Therefore, POGZ is an important gene for evaluating the prognosis of OS patients and is a potential therapeutic target.

Circulating Long Non-Coding RNAs as Novel Potential Biomarkers for Osteogenic Sarcoma

Circulating cell-free nucleic acids recently became attractive targets to develop non-invasive diagnostic tools for cancer detection. Along with DNA and mRNAs, transcripts lacking coding potential (non-coding RNAs, ncRNAs) directly involved in the process of tumor pathogenesis have been recently detected in liquid biopsies. Interestingly, circulating ncRNAs exhibit specific expression patterns associated with cancer and suggest their role as novel biomarkers. However, the potential of circulating long ncRNAs (c-lncRNAs) to be markers in osteosarcoma (OS) is still elusive. In this study we performed a systematic review to identify thirteen c-lncRNAs whose altered expression in blood associate with OS. We herein discuss the potential impact that these c-lncRNAs may have on clinical decision-making in the management of OS. Overall, we aimed to provide novel insights that can contribute to the development of future precision medicine in oncology.