A novel method to address the association between received dose intensity and survival outcome: benefits of approaching treatment intensification at a more individualised level in a trial of the European Osteosarcoma Intergroup

ETV6::RUNX1 Acute Lymphoblastic Leukemia: how much therapy is needed for cure?

Recent trials show 5-year survival rates >95% for ETV6::RUNX1 Acute Lymphoblastic Leukemia (ALL). Since treatment has many side effects, an overview of cumulative drug doses and intensities between eight international trials is presented to characterize therapy needed for cure. A meta-analysis was performed as a comprehensive summary of survival outcomes at 5 and 10 years. For drug dose comparison in non-high risk trial arms, risk group distribution was applied to split the trials into two groups: trial group A with ~70% (range: 63.5-75%) of patients in low risk (LR) (CCLSG ALL2004, CoALL 07-03, NOPHO ALL2008, UKALL2003) and trial group B with ~45% (range: 38.7-52.7%) in LR (AIEOP-BFM ALL 2000, ALL-IC BFM ALL 2002, DCOG ALL10, JACLS ALL-02). Meta-analysis did not show evidence of heterogeneity between studies in trial group A LR and medium risk (MR) despite differences in treatment intensity. Statistical heterogeneity was present in trial group B LR and MR. Trials using higher cumulative dose and intensity of asparaginase and pulses of glucocorticoids and vincristine showed better 5-year event-free survival but similar overall survival. Based on similar outcomes between trials despite differences in therapy intensity, future trials should investigate, to what extent de-escalation is feasible for ETV6::RUNX1 ALL.

A novel aging-associated lncRNA signature for predicting prognosis in osteosarcoma

Osteosarcoma (OS) is one of the most prevalent bone tumors in adolescents, and the correlation between aging and OS remains unclear. Currently, few accurate and reliable biomarkers have been determined for OS prognosis. To address this issue, we carried out a detailed bioinformatics analysis based on OS with data from the Cancer Genome Atlas data portal and Human Aging Genomic Resources database, as well as in vitro experiments. A total of 88 OS samples with gene expression profiles and corresponding clinical characteristics were obtained. Through univariate Cox regression analysis and survival analysis, 10 aging-associated survival lncRNAs (AASRs) were identified to be associated with the overall survival of OS patients. Based on the expression levels of the 10 AASRs, the OS patients were classified into two clusters (Cluster A and Cluster B). Cluster A had a worse prognosis, while Cluster B had a better prognosis. Then, 5 AASRs were ultimately included in the signature through least absolute shrinkage and selection operator-Cox regression analysis. Kaplan‒Meier survival analysis verified that the high-risk group exhibited a worse prognosis than the low-risk group. Furthermore, univariate and multivariate Cox regression analyses confirmed that the riskScore was an independent prognostic factor for OS patients. Subsequently, we discovered that the risk signature was correlated with the properties of the tumor microenvironment and immune cell infiltration. Specifically, there was a positive association between the risk model and naïve B cells, resting dendritic cells and gamma delta T cells, while it was negatively related to CD8+ T cells. Finally, in vitro experiments, we found that UNC5B-AS1 inhibited OS cells from undergoing cellular senescence and apoptosis, thereby promoting OS cells proliferation. In conclusion, we constructed and verified a 5 AASR-based signature, that exhibited excellent performance in evaluating the overall survival of OS patients. In addition, we found that UNC5B-AS1 might inhibit the senescence process, thus leading to the development and progression of OS. Our findings may provide novel insights into the treatment of OS patients.

Research trends and hotspots in the immune microenvironment related to osteosarcoma and tumor cell aging: a bibliometric and visualization study

Background

It is well known that cancers have a common feature that even if the environment is extremely poor in nutrients, they can still make good use of them to maintain viability as well as to produce new biomass, which is one of the reasons why tumor cells are powerfully less susceptible to senescence and death. The microenvironment has a profound impact on the senescence as well as the growth and development of tumor cells, and it is also the focus of scientists' research because it may even affect the discovery of the treatment and pathogenesis of cancer. And so the study of the microenvironment in the tumor cells is of great significance to the analysis of the tumor cells as well as to the impact of their senescence. Similarly, the microenvironment of osteosarcoma is also crucial for its impact, but to our knowledge, there is no bibliometric study that systematically analyzes and describes the trends and future hotspots in this field of research as we do, and we are going to fill this gap in this study.

Methods

We searched the Web Science Core Collection 2010-2023 in WOS on August 1, 2023. Based on the criteria needed for the search, we retained articles that matched the topic, excluded studies other than articles and reviews, and selected only studies whose language was English. We performed an intuitive visualization and bibliometric approach to analyze the research content in this field and a systematic visualization of global trends and hotspots in the research of osteosarcoma and the microenvironment, for which we used multiple specialized For this purpose, we used several specialized software packages, such as VOSviewer and the Bibliometrix package for R software. Because research in this area of osteosarcoma and the microenvironment has begun to gain popularity in the last 10 years or so, and is a very novel piece of research, there were almost no studies in this area prior to 2010 and they were not very informative, and in the end, we chose to look at studies from after 2010.

Results

Based on the criteria needed for the search, resulting in a final selection of 821 articles. In the research area related to osteosarcoma and microenvironment, we found that China in Asia and the United States in North America and Italy in Europe were the three countries or regions with the highest number of published articles. In addition, the institution that published the most research in this area was Shanghai Jiao Tong University. In terms of publications in the field of osteosarcoma and microenvironmental research, Baldini, Heymann, and Avnet are among the top 3 authors. The terms "cancer", "cells" and "expression" are found to be more commonly employed.

Conclusion

Using a variety of highly specialized software, we have undertaken a visual and bibliometric study of the current state of research and potential future hotspots in the field of osteosarcoma and microenvironment research. The microenvironment has a profound impact on the senescence and growth and development of cells in tumors, including osteosarcoma, and may even influence the discovery of cancer treatment and pathogenesis, and is also a hotspot and focus that scientists have begun to gradually study in recent years. This analysis and visualization will help guide future research in the field.

Molecular Subtyping and Survival Analysis of Osteosarcoma Reveals Prognostic Biomarkers and Key Canonical Pathways

Osteosarcoma (OS) is a common bone malignancy in children and adolescents. Although histological subtyping followed by improved OS treatment regimens have helped achieve favorable outcomes, a lack of understanding of the molecular subtypes remains a challenge to characterize its genetic heterogeneity and subsequently to identify diagnostic and prognostic biomarkers for developing effective treatments. In the present study, global analysis of DNA methylation, and mRNA and miRNA gene expression in OS patient samples were correlated with their clinical characteristics. The mucin family of genes, MUC6, MUC12, and MUC4, were found to be highly mutated in the OS patients. Results revealed the enrichment of molecular pathways including Wnt signaling, Calcium signaling, and PI3K-Akt signaling in the OS tumors. Survival analyses showed that the expression levels of several genes such as RAMP1, CRIP1, CORT, CHST13, and DDX60L, miRNAs and lncRNAs were associated with survival of OS patients. Molecular subtyping using Cluster-Of-Clusters Analysis (COCA) for mRNA, lncRNA, and miRNA expression; DNA methylation; and mutation data from the TARGET dataset revealed two distinct molecular subtypes, each with a distinctive gene expression profile. Between the two subtypes, three upregulated genes, POP4, HEY1, CERKL, and seven downregulated genes, CEACAM1, ABLIM1, LTBP2, ISLR, LRRC32, PTPRF, and GPX3, associated with OS metastasis were found to be differentially regulated. Thus, the molecular subtyping results provide a strong basis for classification of OS patients that could be used to develop better prognostic treatment strategies.

Employing machine learning using ferroptosis-related genes to construct a prognosis model for patients with osteosarcoma

Identifying effective biomarkers in osteosarcoma (OS) is important for predicting prognosis. We investigated the prognostic value of ferroptosis-related genes (FRGs) in OS. Transcriptome and clinical data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus. FRGs were obtained from the ferroptosis database. Univariate COX regression and LASSO regression screening were performed and an FRG-based prognostic model was constructed, which was validated using the Gene Expression Omnibus cohort. The predictive power of the model was assessed via a subgroup analysis. A nomogram was constructed using clinical markers with independent prognostic significance and risk score results. The CIBERSORT algorithm was used to detect the correlation between prognostic genes and 22 tumor-infiltrating lymphocytes. The expression of prognostic genes in erastin-treated OS cell lines was verified via real-time PCR. Six prognostic FRGs (ACSL5, ATF4, CBS, CDO1, SCD, and SLC3A2) were obtained and used to construct the risk prognosis model. Subjects were divided into high- and low-risk groups. Prognosis was worse in the high-risk group, and the model had satisfactory prediction performance for patients younger than 18 years, males, females, and those with non-metastatic disease. Univariate COX regression analysis showed that metastasis and risk score were independent risk factors for patients with OS. Nomogram was built on independent prognostic factors with superior predictive power and patient benefit. There was a significant correlation between prognostic genes and tumor immunity. Six prognostic genes were differentially expressed in ferroptosis inducer-treated OS cell lines. The identified prognostic genes can regulate tumor growth and progression by affecting the tumor microenvironment.

Studies related to osteosarcoma and metabolism from 1990 to 2022: A visual analysis and bibliometric study

BACKGROUND

Osteosarcoma is the most common primary bone tumor, its high incidence of metastasis and poor prognosis have led to a great deal of concern for osteosarcoma. In many cancer types, metabolic processes are important for tumor growth progression, so interfering with the metabolic processes of osteosarcoma may be a therapeutic option to stall osteosarcoma progression. A key mechanism of how metabolic processes contribute to the growth and survival of various cancers, including osteosarcoma, is their ability to support tumor cell metabolism. Research related to this field is a direction of great importance and potential. However, to our knowledge, no bibliometric studies related to this field have been published, and we will fill this research gap.

METHODS

Publications were retrieved on January 1, 2023 from the 1990-2022 Science Citation Index of the Web of Science Core Collection. The Bibliometrix package in R software, VOSviewer and CiteSpace software were used to analyze our research directions and to visualize global trends and hotspots in osteosarcoma and metabolism related research.

RESULTS

Based on the search strategy, 833 articles were finally filtered. In this area of research related to osteosarcoma metabolism, we found that China, the United States and Japan are the top 3 countries in terms of number of articles published, and the journals and institutions that have published the most research in this area are Journal of bone and mineral research, Shanghai Jiao Tong University. In addition, Baldini, Nicola, Reddy, Gs and Avnet, Sofia are the top three authors in terms of number of articles published in studies related to this field. The most popular keywords related to the field in the last 30 years are "metabolism" and "expression", which will guide the possible future directions of the field.

CONCLUSION

We used Bibliometrix, VOSviewer, and Citespace to visualize and bibliometrically analyze the current status and possible future hotspots of research in the field of osteosarcoma metabolism. Possible future hotspots in this field may focus on the related terms "metabolism", "expression", and "migraation".

No Effect on Tumorigenesis in MG63 Cells Induced by Co-Cultured Mesenchymal Stem Cells

Osteosarcoma is a kind of bone tumor with an extremely high malignant degree and often occurs in adolescents. Mesenchymal stem cells are believed to play an important role in the microenvironment of osteosarcoma, but whether they promote or inhibit the development of osteosarcoma is controversial. In this study, the coexpression of mesenchymal stem cells (MSCs) with osteosarcoma cell MG63 was used to explore the effect of MSCs on MG63. We found that co-culture of MSCs with MG63 did not affect the proliferation, invasion, and migration of MG63 cells, nor did it significantly affect the epithelial- and glial-mesenchymal transformation of MG63 cells. Therefore, in this study, we obtained a new concept that MSCs neither promote nor inhibit the occurrence and development of osteosarcoma.

Modelling time-varying covariates effect on survival via functional data analysis: application to the MRC BO06 trial in osteosarcoma

Time-varying covariates are of great interest in clinical research since they represent dynamic patterns which reflect disease progression. In cancer studies biomarkers values change as functions of time and chemotherapy treatment is modified by delaying a course or reducing the dose intensity, according to patient’s toxicity levels. In this work, a Functional covariate Cox Model (FunCM) to study the association between time-varying processes and a time-to-event outcome is proposed. FunCM first exploits functional data analysis techniques to represent time-varying processes in terms of functional data. Then, information related to the evolution of the functions over time is incorporated into functional regression models for survival data through functional principal component analysis. FunCM is compared to a standard time-varying covariate Cox model, commonly used despite its limiting assumptions that covariate values are constant in time and measured without errors. Data from MRC BO06/EORTC 80931 randomised controlled trial for treatment of osteosarcoma are analysed. Time-varying covariates related to alkaline phosphatase levels, white blood cell counts and chemotherapy dose during treatment are investigated. The proposed method allows to detect differences between patients with different biomarkers and treatment evolutions, and to include this information in the survival model. These aspects are seldom addressed in the literature and could provide new insights into the clinical research.

Short-term and long-term prognostic value of histological response and intensified chemotherapy in osteosarcoma: a retrospective reanalysis of the BO06 trial

OBJECTIVES

Cure rate models accounting for cured and uncured patients, provide additional insights into long and short-term survival. We aim to evaluate the prognostic value of histological response and chemotherapy intensification on the cure fraction and progression-free survival (PFS) for the uncured patients.

DESIGN

Retrospective analysis of a randomised controlled trial, MRC BO06 (EORTC 80931).

SETTING

Population-based study but proposed methodology can be applied to other trial designs.

PARTICIPANTS

A total of 497 patients with resectable highgrade osteosarcoma, of which 118 were excluded because chemotherapy was not started, histological response was not reported, abnormal dose was reported or had disease progression during treatment.

INTERVENTIONS

Two regimens with the same anticipated cumulative dose (doxorubicin 6×75 mg/m²/week; cisplatin 6×100 mg/m²/week) over different time schedules: every 3 weeks in regimen-C and every 2 weeks in regimen-DI.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome is PFS computed from end of treatment because cure, if it occurs, may happen at any time during treatment. A mixture cure model is used to study the effect of histological response and intensified chemotherapy on the cure status and PFS for the uncured patients.

RESULTS

Histological response is a strong prognostic factor for the cure status (OR 3.00, 95% CI 1.75 to 5.17), but it has no clear effect on PFS for the uncured patients (HR 0.78, -95% CI 0.53 to 1.16). The cure fractions are 55% (46%-63%) and 29% (22%-35%), respectively, among patients with good and poor histological response (GR, PR). The intensified regimen was associated with a higher cure fraction among PR (OR 1.90, 95% CI 0.93 to 3.89), with no evidence of effect for GR (OR 0.78, 95% CI 0.38 to 1.59).

CONCLUSIONS

Accounting for cured patients is valuable in distinguishing the covariate effects on cure and PFS. Estimating cure chances based on these prognostic factors is relevant for counselling patients and can have an impact on treatment decisions.

TRIAL REGISTRATION NUMBER

ISRCTN86294690.

Identification of an Iron Metabolism-Related lncRNA Signature for Predicting Osteosarcoma Survival and Immune Landscape

Background: Long noncoding RNAs (lncRNAs) act as epigenetic regulators in the process of ferroptosis and iron metabolism. This study aimed to identify an iron metabolism-related lncRNA signature to predict osteosarcoma (OS) survival and the immune landscape.

Methods: RNA-sequencing data and clinical information were obtained from the TARGET dataset. Univariate Cox regression and LASSO Cox analysis were used to develop an iron metabolism-related lncRNA signature. Consensus clustering analysis was applied to identify subtype-based prognosis-related lncRNAs. CIBERSORT was used to analyze the difference in immune infiltration and the immune microenvironment in the two clusters.

Results: We identified 302 iron metabolism-related lncRNAs based on 515 iron metabolism-related genes. The results of consensus clustering showed the differences in immune infiltration and the immune microenvironment in the two clusters. Through univariate Cox regression and LASSO Cox regression analysis, we constructed an iron metabolism-related lncRNA signature that included seven iron metabolism-related lncRNAs. The signature was verified to have good performance in predicting the overall survival, immune-related functions, and immunotherapy response of OS patients between the high- and low-risk groups.

Conclusion: We identified an iron metabolism-related lncRNA signature that had good performance in predicting survival outcomes and showing the immune landscape for OS patients. Furthermore, our study will provide valuable information to further develop immunotherapies of OS.

A New Recombinant Fibronectin/Cadherin Protein-Hydrophobically Modified Glycol Chitosan/Paclitaxel Layer-By-Layer Self-Assembly Strategy for the Postoperative Therapy of Osteosarcoma and Correlated Bone Injury

Osteosarcoma is one of the most aggressive cancers which greatly threatens the health of adolescents and surgery is difficult to resect the whole piece of tumor tissue. The residual tumor cells might proliferate at the tumor site and invade into the blood circulation, leading to tumor recurrence and metastasis. Besides, the invasion of tumor cells could also lead to bone injury. We designed a recombinant fibronectin-cadherin fusion protein/hydrophobically modified glycol chitosan-PTX nanoparticles (rFN-CDH/HGC-PTX) layer-by-layer self-assembly polymer based on biphasic calcium phosphate ceramic (BCP) (BCP-PEI-(rFN/CDH-PTX/HGC)_n-rFN/CDH). The SEM, FTIR, XPS and contact angle experiments proved the successful synthesis of the polymer. The chemotherapy drug PTX and bone-repairing-related rFN/CDH fusion protein could be stably released within one week and the in vitro experiments exhibited the efficacy of the polymer to kill residual tumor cells and promote the proliferation of osteoblast, confirming that our polymer was a superior material for postoperative osteosarcoma therapy.

Recognize the role of CD146/MCAM in the osteosarcoma progression: an in vitro study

Background

Osteosarcoma (OS) is a common malignant bone tumor with poor prognosis. We previously reviewed that CD146 is correlated with multiple cancer progression, while its impact on OS is currently not systematically studied.

Methods

MG63 was transfected with lentivirus to express CD146 ectopically, and anti-CD146 neutralizing antibody ab75769 was used to inhibit 143B. Cyclic migration of MG63 and co-culture between MG63 and 143B were used to explore the role of OS malignancy in CD146 expression. The effect of OS cell medium (CM) on endothelium behaviors was assessed, and the expression changes of CD146 before and after co-culture of endothelium and OS were evaluated. Finally, the expression of CD146 in OS was detected under different culture conditions, including hyperoxia, low oxygen, high glucose and low glucose conditions.

Results

CD146 promoted the colony formation, migration, invasion and homotypic adhesion of OS cells, and reducing the concentration of soluble CD146 in the OS medium inhibited the proliferation, migration and lumen formation of the cultured endothelium. However, CD146 did not affect the adhesion between OS and endothelium, nor did co-culture of both sides affect the CD146 expression. Similarly, the proliferation, migration and CD146 expression of MG63 remained unchanged after many cycles of migration itself, as did its co-culture with 143B for expressing CD146. In addition, we also showed that high glucose promoted the expression of CD146 in OS, while hypoxia had the opposite effect.

Conclusions

These findings demonstrate that CD146 promotes OS progression by mediating pro-tumoral and angiogenic effects. Thus, CD146 could be a potential therapeutic target for OS, especially for OS patients with diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02006-7.

Single-cell RNA landscape of intratumoral heterogeneity and immunosuppressive microenvironment in advanced osteosarcoma

Osteosarcoma is the most frequent primary bone tumor with poor prognosis. Through RNA-sequencing of 100,987 individual cells from 7 primary, 2 recurrent, and 2 lung metastatic osteosarcoma lesions, 11 major cell clusters are identified based on unbiased clustering of gene expression profiles and canonical markers. The transcriptomic properties, regulators and dynamics of osteosarcoma malignant cells together with their tumor microenvironment particularly stromal and immune cells are characterized. The transdifferentiation of malignant osteoblastic cells from malignant chondroblastic cells is revealed by analyses of inferred copy-number variation and trajectory. A proinflammatory FABP4+ macrophages infiltration is noticed in lung metastatic osteosarcoma lesions. Lower osteoclasts infiltration is observed in chondroblastic, recurrent and lung metastatic osteosarcoma lesions compared to primary osteoblastic osteosarcoma lesions. Importantly, TIGIT blockade enhances the cytotoxicity effects of the primary CD3+ T cells with high proportion of TIGIT+ cells against osteosarcoma. These results present a single-cell atlas, explore intratumor heterogeneity, and provide potential therapeutic targets for osteosarcoma.

Targeting Molecular Mechanisms Underlying Treatment Efficacy and Resistance in Osteosarcoma: A Review of Current and Future Strategies

Osteosarcoma is the most common primary malignant bone tumour in children and adolescents. Due to micrometastatic spread, radical surgery alone rarely results in cure. Introduction of combination chemotherapy in the 1970s, however, dramatically increased overall survival rates from 20% to approximately 70%. Unfortunately, large clinical trials aiming to intensify treatment in the past decades have failed to achieve higher cure rates. In this review, we revisit how the heterogenous nature of osteosarcoma as well as acquired and intrinsic resistance to chemotherapy can account for stagnation in therapy improvement. We summarise current osteosarcoma treatment strategies focusing on molecular determinants of treatment susceptibility and resistance. Understanding therapy susceptibility and resistance provides a basis for rational therapy betterment for both identifying patients that might be cured with less toxic interventions and targeting resistance mechanisms to sensitise resistant osteosarcoma to conventional therapies.

The efficacy and safety comparison of first-line chemotherapeutic agents (high-dose methotrexate, doxorubicin, cisplatin, and ifosfamide) for osteosarcoma: a network meta-analysis

BACKGROUND

Osteosarcoma, a primary malignant bone tumor derived from mesenchymal tissue, is the most common type of pleomorphic tumor that occurs in children and adolescents. The aim of this study was to compare the efficacy and safety of high-dose methotrexate (M), doxorubicin (D), cisplatin (C), and ifosfamide (I) in the management of osteosarcoma.

METHODS

Electronic databases including PubMed, Cochrane Library, and Embase database were searched for studies published from when the databases were established to July 13, 2019. The network meta-analysis was performed using software R 3.3.2 and STATA version 41.0 after demographic and outcome data extraction. The ranks based on probabilities of interventions for each outcome were performed. In addition, the consistency of direct and indirect evidence was assessed by node splitting.

RESULTS

The network meta-analysis results revealed that MDCI had a significant lower hazard risk of overall survival [MDCI vs MDC: HR = 0.74, 95% CrI (0.23, 0.87); MDCI vs DC: HR = 0.60, 95% CrI (0.16, 0.92)]. In addition, MDCI had a clearly longer progression-free survival time than that of DC [MDCI: HR = 0.88, 95% CrI (0.46, 0.98)]. No significant difference was detected in MDC and DC in OS, PFS, and AEs. The probabilities of rank plot showed that MDCI ranked first in OS (73.12%) and PFS (52.43%). DC was the best treatment in safety, ranked first (75.43%).

CONCLUSIONS

MDCI showed its superiority among all chemotherapeutic agents in relation to efficacy and safety, followed by MDC. In addition, MDCI was associated with an increased risk of AEs. According to our analysis, DC was less effective but safer for MDC and MDCI.

Drug dose and drug choice: Optimizing medical therapy for veterinary cancer

Although novel agents hold great promise for the treatment of animal neoplasia, there may be room for significant improvement in the use of currently available agents. These improvements include altered dosing schemes, novel combinations, and patient-specific dosing or selection of agents. Previous studies have identified surrogates for "individualized dose intensity,", for example, patient size, development of adverse effects, and pharmacokinetic parameters, as potential indicators of treatment efficacy in canine lymphoma, and strategies for patient-specific dose escalation are discussed. Strategies for treatment selection in individual patients include conventional histopathology, protein-based target assessment (eg, flow cytometry, immunohistochemistry, and mass spectrometry), and gene-based target assessment (gene expression profiling and targeted or global sequencing strategies). Currently available data in animal cancer evaluating these strategies are reviewed, as well as ongoing studies and suggestions for future directions.