Challenges of Systemic Therapy Investigations for Bone Sarcomas

pH-responsive paclitaxel prodrug encapsulated in a polypeptide-chitosan polymer delivery system for osteosarcoma treatment

Osteosarcoma, a highly invasive and metastatic primary bone malignancy, remains a significant clinical challenge due to the limited improvement in overall survival despite advances in treatment strategies. This highlights the urgent need for the development of more effective therapeutic options. In response, we have developed a novel paclitaxel (PTX)-loaded nanodrug system, PLGA-CS-1@PTX, by incorporating a synthesized epoxy-tetrapeptide derivative (compound 1) with poly(lactic-co-glycolic acid) (PLGA) and chitosan (CS), forming the PLGA-CS-1 composite system. The system was thoroughly characterized for its physicochemical properties, including morphology, particle size, and in vitro release behavior. Scanning electron microscopy (SEM) confirmed the nanostructure of the particles, with particle sizes around 170 nm and a narrow PDI (<0.15), indicating a uniform distribution. In vitro release studies showed a pH-responsive release profile, with 84.8 % of PTX released at pH 5.4 after 65 h of incubation, compared to 68.1 % at pH 6.4 and 14.8 % at pH 7.4, demonstrating good drug release control in acidic environments. Biological assays demonstrated significant inhibition of osteosarcoma cell proliferation in both HOS and U2OS cell lines, with a dose-dependent reduction in SPICE1 expression, suggesting that PLGA-CS-1@PTX can effectively suppress the proliferative activity of osteosarcoma cells by modulating SPICE1 levels. The hydrophobic segment of the peptide enhanced the drug loading capacity and minimized side effects, improving the overall safety profile of the system. This composite system effectively integrates the strengths of each component, offering a promising, safe, and efficient strategy for osteosarcoma treatment with great potential for clinical application.

DCC-2036 inhibits osteosarcoma via targeting HCK and the PI3K/AKT-mTORC1 axis to promote autophagy

BACKGROUND

Osteosarcoma is a common bone tumor in adolescents and children, characterized by rapid progression, high malignancy, poor prognosis, and a tendency for pulmonary metastasis. Despite extensive research efforts, the specific driver gene associated with osteosarcoma remains unidentified, underscoring the urgent need for novel therapeutic targets and targeted treatment options.

METHODS

In vitro studies were conducted to assess the effects of DCC-2036 on the proliferation, migration, and invasion of osteosarcoma (OS) cell lines, employing cloning and Transwell experiments. Network pharmacological analysis, complemented by in vitro experimental validation, indicated the critical target responsible for the inhibitory effects of DCC-2036. RNA sequencing analysis demonstrated that DCC-2036 could induce autophagy in OS cells, with relative protein levels assessed using Western blotting following treatment with the autophagy inhibitor 3-MA and the mTOR agonist MHY1485. In vivo studies further confirmed the role of DCC-2036 in cell proliferation through subcutaneous tumorigenesis.

RESULTS

In this study, we demonstrated that the small molecule tyrosine kinase inhibitor DCC-2036 effectively inhibited osteosarcoma (OS) cells in both cellular and animal models. We found that DCC-2036 significantly suppressed the proliferation of osteosarcoma cells and induced apoptosis; additionally, it notably inhibited cell migration, invasion, and epithelial-to-mesenchymal transition (EMT). HCK was identified as the key target mediating the effects of DCC-2036 on osteosarcoma. Mechanistically, DCC-2036 was shown to inhibit the expression of phosphorylated AKT (p-AKT), phosphorylated S6 kinase (p-S6K), and phosphorylated 4E-binding protein 1 (p-4EBP1) within the downstream PI3K/AKT/mTORC1 signaling pathway. Furthermore, in vivo experiments utilizing subcutaneous tumor xenografts in mice demonstrated that DCC-2036 effectively inhibited the growth of xenografted 143B cells in BALB/C-nude mice.

CONCLUSIONS

Collectively, these findings indicate that DCC-2036 promotes autophagy in osteosarcoma (OS) cells by targeting the HCK/AKT/mTORC1 axis and exerts anti-tumor effects without significant toxicity. Consequently, DCC-2036 emerges as a promising therapeutic agent for the treatment of HCK-overexpressing osteosarcoma.

Research Progress on Natural Products That Regulate miRNAs in the Treatment of Osteosarcoma

miRNAs are small non-coding RNA molecules that play critical roles in the regulation of gene expression and have been closely associated with various diseases, including cancer. These molecules significantly influence the cell cycle of tumor cells and control programmed cell death (apoptosis). Currently, research on miRNAs has become a major focus in developing cancer therapies. Osteosarcoma, a malignant neoplasm predominantly occurring during adolescence and later in life, is characterized by a high propensity for metastasis. This review explores the role of miRNAs in the initiation and progression of cancer, highlighting their potential as predictive biomarkers for disease. It discusses the mechanisms by which natural products modulate miRNA activity to influence apoptosis, ferroptosis, and autophagy in osteosarcoma cells, aiming to identify new strategies for osteosarcoma treatment. Recent studies on how natural products regulate miRNAs to reduce tumor cell resistance to chemotherapy are also reviewed. Furthermore, the review elaborates on how natural products regulate m6A modifications to influence miRNA expression, thereby exerting antitumor effects. In this process, interactions between m6A modifications and miRNAs have been identified, with both jointly influencing tumorigenesis and cancer progression, offering a new perspective in osteosarcoma treatment. These approaches could help uncover novel regulatory mechanisms in osteosarcoma pathways and provide a theoretical foundation for developing new drugs and identifying novel therapeutic targets.

Cuproptosis related lncRNA signature as a prognostic and therapeutic biomarker in osteosarcoma immunity

Osteosarcoma is one of the most common malignant bone tumours in children. In this study, we aimed to construct a cuproptosis-related lncRNAs signature to predict the prognosis and immune landscape of osteosarcoma patients. Databases from TARGET were used to acquire osteosarcoma patient datasets, which included clinical information and RNA sequencing data. Cuproptosis-related lncRNAs was obtained by correlation analysis. Through univariate Cox regression analysis, prognosis-related lncRNAs were obtained. We used nonnegative matrix factorization clustering to identify potential molecular subgroups with different cuproptosis-related lncRNA expression patterns. The least absolute shrinkage and selection operator algorithm and multivariate Cox regression analysis were used to construct the prognostic signature. The ESTIMATE algorithm, Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes were applied to explore the underlying mechanisms in the immune landscape of osteosarcoma. We used gene set enrichment analysis to compare the different enrichments in the high-risk group and the low-risk group. Furthermore, we predicted the response to targeted drugs in patients with different risk groups. Using multivariable analysis, we developed a risk scoring model based on 7 long noncoding RNAs and calculated two molecular subgroups from osteosarcoma patients from the database. There is a better immune microenvironment in the low-risk group compared to the high-risk group. At the same time, the gene functional enrichment analysis based on the differently expressed genes obtained by grouping showed they were mainly related to immunity, indicating that cuproptosis-related lncRNAs may affect the prognosis of osteosarcoma by regulating immunity. Moreover, these patients in high-risk group were more susceptible to targeted drugs than the low-risk group. We identified a cuproptosis-related lncRNA prognostic signature for osteosarcoma and showed a close connection in terms of immunity. Moreover, we provided some potential targeted drugs for the treatment of osteosarcoma.

Large-Scale Comparative Analysis of Canine and Human Osteosarcomas Uncovers Conserved Clinically Relevant Tumor Microenvironment Subtypes

PURPOSE

Osteosarcoma is an aggressive bone cancer lacking robust biomarkers for personalized treatment. Despite its scarcity in humans, it is relatively common in adult pet dogs. This study aimed to analyze clinically annotated bulk tumor transcriptomic datasets of canine and patients with human osteosarcoma to identify potentially conserved patterns of disease progression.

EXPERIMENTAL DESIGN

Bulk transcriptomic data from 245 pet dogs with treatment-naïve appendicular osteosarcoma were analyzed using deconvolution to characterize the tumor microenvironment (TME). The TME of both primary and metastatic tumors derived from the same dog was compared, and its impact on canine survival was assessed. A machine learning model was developed to classify the TME based on its inferred composition using canine tumor data. This model was applied to eight independent human osteosarcoma datasets to assess its generalizability and prognostic value.

RESULTS

This study found three distinct TME subtypes of canine osteosarcoma based on cell type composition of bulk tumor samples: immune enriched, immune enriched dense extracellular matrix-like, and immune desert. These three TME-based subtypes of canine osteosarcomas were conserved in humans and could predict progression-free survival outcomes of human patients, independent of conventional prognostic factors such as percent tumor necrosis post standard of care chemotherapy treatment and disease stage at diagnosis.

CONCLUSIONS

These findings demonstrate the potential of leveraging data from naturally occurring cancers in canines to model the complexity of the human osteosarcoma TME, offering a promising avenue for the discovery of novel biomarkers and developing more effective precision oncology treatments.

Assessment of Artificial Intelligence Chatbot Responses to Common Patient Questions on Bone Sarcoma

BACKGROUND AND OBJECTIVES

The potential impacts of artificial intelligence (AI) chatbots on care for patients with bone sarcoma is poorly understood. Elucidating potential risks and benefits would allow surgeons to define appropriate roles for these tools in clinical care.

METHODS

Eleven questions on bone sarcoma diagnosis, treatment, and recovery were inputted into three AI chatbots. Answers were assessed on a 5-point Likert scale for five clinical accuracy metrics: relevance to the question, balance and lack of bias, basis on established data, factual accuracy, and completeness in scope. Responses were quantitatively assessed for empathy and readability. The Patient Education Materials Assessment Tool (PEMAT) was assessed for understandability and actionability.

RESULTS

Chatbots scored highly on relevance (4.24) and balance/lack of bias (4.09) but lower on basing responses on established data (3.77), completeness (3.68), and factual accuracy (3.66). Responses generally scored well on understandability (84.30%), while actionability scores were low for questions on treatment (64.58%) and recovery (60.64%). GPT-4 exhibited the highest empathy (4.12). Readability scores averaged between 10.28 for diagnosis questions to 11.65 for recovery questions.

CONCLUSIONS

While AI chatbots are promising tools, current limitations in factual accuracy and completeness, as well as concerns of inaccessibility to populations with lower health literacy, may significantly limit their clinical utility.

Machine learning-based individualized survival prediction model for prognosis in osteosarcoma: Data from the SEER database

Patient outcomes of osteosarcoma vary because of tumor heterogeneity and treatment strategies. This study aimed to compare the performance of multiple machine learning (ML) models with the traditional Cox proportional hazards (CoxPH) model in predicting prognosis and explored the potential of ML models in clinical decision-making. From 2000 to 2018, 1243 patients with osteosarcoma were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Three ML methods were chosen for model development (DeepSurv, neural multi-task logistic regression [NMTLR]) and random survival forest [RSF]) and compared them with the traditional CoxPH model and TNM staging systems. 871 samples were used for model training, and the rest were used for model validation. The models' overall performance and predictive accuracy for 3- and 5-year survival were assessed by several metrics, including the concordance index (C-index), the Integrated Brier Score (IBS), receiver operating characteristic curves (ROC), area under the ROC curves (AUC), calibration curves, and decision curve analysis. The efficacy of personalized recommendations by ML models was evaluated by the survival curves. The performance was highest in the DeepSurv model (C-index, 0.77; IBS, 0.14; 3-year AUC, 0.80; 5-year AUC, 0.78) compared with other methods (C-index, 0.73-0.74; IBS, 0.16-0.17; 3-year AUC, 0.73-0.78; 5-year AUC, 0.72-0.78). There are also significant differences in survival outcomes between patients who align with the treatment option recommended by the DeepSurv model and those who do not (hazard ratio, 1.88; P < .05). The DeepSurv model is available in an approachable web app format at https://survivalofosteosarcoma.streamlit.app/. We developed ML models capable of accurately predicting the survival of osteosarcoma, which can provide useful information for decision-making regarding the appropriate treatment.

Lung and bone metastases patterns in Ewing sarcoma: Chemotherapy improves overall survival

Ewing sarcoma (ES) is a small round cell malignancy, mainly in the bone tissue, followed by the soft tissue. Lung metastases (LM) and bone metastases (BM) are the most common types of metastases. From 2010 to 2018, the Surveillance, Epidemiology, and End Results database diagnosed 242 cases of ES with LM, 186 cases of ES with BM, and 74 cases of ES with LM and BM. Univariate and multivariate logistic regression analyses were used to determine the risk factors for LM and/or BM, and Kaplan-Meier curves and Cox regression analysis were used to determine the prognostic factors for LM and/or BM. Tumor size ≥50 mm, N1 stage, BM, liver metastases, and surgical treatment were significantly correlated with LM; tumor size >100 mm, brain metastases, LM, surgical treatment, and chemotherapy were significantly correlated with BM; female, N1 stage, brain metastases, liver metastases, and surgical treatment were significantly correlated with LM and BM. Older age, BM, higher T stage, no surgical treatment, and no chemotherapy were harmful to the survival of ES patients with LM; older age, female, LM, and no chemotherapy were harmful to the survival of ES patients with BM; older age and no chemotherapy were harmful to the survival of ES patients with LM and BM. Larger tumor size, N1 stages, and organ metastases were significantly associated with ES patients with LM and/or BM. Chemotherapy is effective in improving the survival.

Prognostic Signature in Osteosarcoma Based on Amino Acid Metabolism-Associated Genes

Background: Osteosarcoma (OS) is undeniably a formidable bone malignancy characterized by a scarcity of effective treatment options. Reprogramming of amino acid (AA) metabolism has been associated with OS development. The present study was designed to identify metabolism-associated genes (MAGs) that are differentially expressed in OS and to construct a MAG-based prognostic risk signature for this disease. Methods: Expression profiles and clinicopathological data were downloaded from Gene Expression Omnibus (GEO) and UCSC Xena databases. A set of AA MAGs was obtained from the MSigDB database. Differentially expressed genes (DEGs) in GEO dataset were identified using "limma." Prognostic MAGs from UCSC Xena database were determined through univariate Cox regression and used in the prognostic signature development. This signature was validated using another dataset from GEO database. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, single sample gene set enrichment analysis, and GDSC2 analyses were performed to explore the biological functions of the MAGs. A MAG-based nomogram was established to predict 1-, 3-, and 5-year survival. Real-time quantitative polymerase chain reaction, Western blot, and immunohistochemical staining confirmed the expression of MAGs in primary OS and paired adjacent normal tissues. Results: A total of 790 DEGs and 62 prognostic MAGs were identified. A MAG-based signature was constructed based on four MAGs: PIPOX, PSMC2, SMOX, and PSAT1. The prognostic value of this signature was successfully validated, with areas under the receiver operating characteristic curves for 1-, 3-, and 5-year survival of 0.714, 0.719, and 0.715, respectively. This MAG-based signature was correlated with the infiltration of CD56dim natural killer cells and resistance to several antiangiogenic agents. The nomogram was accurate in predictions, with a C-index of 0.77. The expression of MAGs verified by experiment was consistent with the trends observed in GEO database. Conclusion: Four AA MAGs were prognostic of survival in OS patients. This MAG-based signature has the potential to offer valuable insights into the development of treatments for OS.

Clemastine and hyperthermia enhance sensitization of osteosarcoma cells for apoptosis

Clemastine is an antagonist of histamine H1 receptor may provide benefits in the treatment of osteosarcoma (OS). In the current study, we used hyperthermia approach to sensitize OS cells to clemastine-mediated cell death. Osteosarcoma U-2 OS and Saos-2 cells were treated with clemastine at 37°C, followed by 42°C for 2 h, and released at 37°C for 6 h. The impact of clemastine and hyperthermia on OS cell survival and autophagy-mediated cell death was investigated. Exposure of U-2 OS and Saos-2 cells to clemastine and hyperthermia (42°C) inhibited dose-dependent clemastine-mediated cell survival by increasing cell apoptosis. Hyperthermia and clemastine exposure modulated inflammatory and unfolded protein response (UPR) signaling differentially in U-2 OS and Saos-2 cells. Exposure of U-2 OS and Saos-2 cells to hyperthermia and clemastine inhibited AKT/mTOR and induced expression of the autophagy biomarkers LC3B II and LC3-positive puncta formation. The inhibition of autophagy by 3-methyladenine blocked hyperthermia and clemastine-mediated induction of LC3B II, LC3-positive puncta formation, and OS cell apoptosis. These results indicate that clemastine and hyperthermia sensitize OS cell lines by inducing increased autophagic cell death. Collectively, our data suggest that hyperthermia along with antihistamine therapy may provide an improved approach for the treatment of OS.

Construction of a 5-gene prognostic signature based on oxidative stress related genes for predicting prognosis in osteosarcoma

BACKGROUND

The understanding of the complex biological scenario of osteosarcoma will open the way to identifying new strategies for its treatment. Oxidative stress is a cancer-related biological scenario. At present, it is not clear the oxidative stress genes in affecting the prognosis and progression of osteosarcoma, the underlying mechanism as well as their impact on the classification of osteosarcoma subtypes.

METHODS

We selected samples and sequencing data from TARGET data set and GSE21257 data set, and downloaded oxidative stress related-genes (OSRGs) from MsigDB. Univariate Cox analysis of OSRG was conducted using TARGET data, and the prognostic OSRG was screened to conduct unsupervised clustering analysis to identify the molecular subtypes of osteosarcoma. Through least absolute shrinkage and selection operator (LASSO) regression analysis and COX regression analysis of differentially expressed genes (DEGs) between subgroups, a risk assessment system for osteosarcoma was developed.

RESULTS

45 prognosis-related OSRGs genes were acquired, and two molecular subtypes of osteosarcoma were clustered. C2 cluster displayed prolonged overall survival (OS) accompanied with high degree of immune infiltration and enriched immune pathways. While cell cycle related pathways were enriched in C2 cluster. Based on DEGs between subgroups and Lasso analysis, 5 hub genes (ZYX, GJA5, GAL, GRAMD1B, and CKMT2) were screened to establish a robust prognostic risk model independent of clinicopathological features. High-risk group had more patients with cancer metastasis and death as well as C1 subtype with poor prognosis. Low-risk group exhibited favorable OS and high immune infiltration status. Additionally, the risk assessment system was optimized by building decision tree and nomogram.

CONCLUSIONS

This study defined two molecular subtypes of osteosarcoma with different prognosis and tumor immune microenvironment status based on the expression of OSRGs, and provided a new risk assessment system for the prognosis of osteosarcoma.

Large Scale Comparative Deconvolution Analysis of the Canine and Human Osteosarcoma Tumor Microenvironment Uncovers Conserved Clinically Relevant Subtypes

Osteosarcoma is a relatively rare but aggressive cancer of the bones with a shortage of effective biomarkers. Although less common in humans, Osteosarcomas are fairly common in adult pet dogs and have been shown to share many similarities with their human analogs. In this work, we analyze bulk transcriptomic data of 213 primary and 100 metastatic Osteosarcoma samples from 210 pet dogs enrolled in nation-wide clinical trials to uncover three Tumor Microenvironment (TME)-based subtypes: Immune Enriched (IE), Immune Enriched Dense Extra-Cellular Matrix-like (IE-ECM) and Immune Desert (ID) with distinct cell type compositions, oncogenic pathway activity and chromosomal instability. Furthermore, leveraging bulk transcriptomic data of canine primary tumors and their matched metastases from different sites, we characterize how the Osteosarcoma TME evolves from primary to metastatic disease in a standard of care clinical setting and assess its overall impact on clinical outcomes of canines. Most importantly, we find that TME-based subtypes of canine Osteosarcomas are conserved in humans and predictive of progression free survival outcomes of human patients, independently of known prognostic biomarkers such as presence of metastatic disease at diagnosis and percent necrosis following chemotherapy. In summary, these results demonstrate the power of using canines to model the human Osteosarcoma TME and discover novel biomarkers for clinical translation.

A retrospective case-control study for the comparison of 5-year survival rates: the role of adjuvant and neoadjuvant chemotherapy in craniofacial bone sarcoma in adults

Background

The impact of adjuvant or neoadjuvant chemotherapy in the treatment of craniofacial bone sarcomas has not been clarified. This study aimed to assess whether survival outcomes differed between patients who underwent adjuvant or neoadjuvant chemotherapy.

Methods

A retrospective search for adult patients diagnosed with malignant neoplasms of the craniofacial bones (International Classification of Diseases 10 codes C41.0-C41.1), within the past 20 years from the access date 28 April 2022, was conducted using the TriNetX network (TriNetX, Cambridge, MA, USA). Cohort I included patients who underwent adjuvant chemotherapy and cohort II included patients with neoadjuvant chemotherapy. A refined search for individuals that received common chemotherapeutic agents, such as methotrexate, doxorubicin, cisplatin, and/or ifosfamide, was conducted and patients were assigned to cohort A (adjuvant chemotherapy) and cohort B (neoadjuvant chemotherapy). Following matching for age and sex, Kaplan-Meier analysis was performed, and risk ratio, odds ratio (OR), and hazard ratio were calculated.

Results

Patients were assigned to two cohorts, with 181 patients each after matching. In cohorts I and II, 55 and 41 patients died, respectively. No significant differences were found between the two cohorts regarding the 5-year survival probability (I: 59.87% versus II: 68.45%; p = 0.076; log-rank test), or the risk of dying (I: 0.304 versus II: 0.227; risk difference: 0.077; p = 0.096). The risk analysis before matching for age and sex showed a significant survival benefit in cohort II (OR: 1.586; p = 0.0295; risk difference: 0.093). After a refined query to identify patients treated with methotrexate, doxorubicin, cisplatin, and/or ifosfamide, the two cohorts included 47 patients, respectively. In cohort A (adjuvant chemotherapy), 19 patients died, whereas 12 patients died in cohort B (neoadjuvant chemotherapy) within 5 years after diagnosis. Further analysis indicated a greater survival in cohort B, but the survival probability between the cohorts did not differ significantly (A: 43.55% versus B: 54.49%; p = 0.171).

Conclusion

The use of neoadjuvant chemotherapy may improve survival rates in patients with surgically treated craniofacial bone sarcomas. Due to the retrospective nature of this study, randomized controlled studies are required to derive treatment recommendations.

Molecular and Translational Research on Bone Tumors

Primary bone tumors (PBTs) represent a huge variety of rare malignancies that originate in the skeletal system [...].

Ewing sarcoma: what trends in recent works? A holistic analysis with global productivity: A cross-sectional study

Advances in the biology of Ewing sarcoma, which continues to be an important cause of mortality, have caused an increase in information in the literature related to the underlying molecular base of the disease and discussions of new treatment approaches. In this study, we aimed to comprehensively analyze the published scientific articles on Ewing sarcoma. The Web of Science database was used to obtain and statistically analysis articles on Ewing sarcoma that were published between 1980 and 2021. Maps of network visualization were used to reveal trending topics, global collaborations, and the most effective studies. Correlation analysis was performed using Spearman's correlation coefficient. A total of 3236 articles were analyzed. The first 3 countries that contributed the most to the literature and cooperated most intensively were USA (1194, 36.8%), Germany (293, 9%), Italy (254, 7.8%). Pediatric Blood & Cancer (n = 122), Cancer (87), Journal of Pediatric Hematology Oncology (71) were among the top 3 journals with the most articles. The most active author was Piero Picci (n = 94). High-income countries have a great effect on the literature on this subject. The most studied trend topics in recent years were pediatric oncology, EWS RNA Binding Protein 1 (EWSR1), EWSR1-FL1, epigenetics, bioinformatics, microRNA, gene expression, metastasis, migration, biomarker, immunotherapy, survival, outcomes, surveillance epidemiology and end results (SEER), nomogram, temozolomide, irinotecan, and drug resistance. Genetic studies, metastasis, immunotherapy, life analyses/nomogram based on new data obtained from SEER, and chemotherapy with irinotecan and temozolomide combination, were seen to be the topics researched in recent years.

Inflammatory Surrogate Parameters for Predicting Ifosfamide-Induced Neurotoxicity in Sarcoma Patients

Sarcomas compromise a heterogenous group of tumors of a mesenchymal origin. Although treatment options in many solid tumors have evolved over the past decades, the treatment of advanced sarcoma is still based on conventional chemotherapeutic agents. Beside anthracyclines, alkylating agents such as ifosfamide are frequently used in sarcoma treatment. However, treatment with ifosfamide can cause severe dose- and treatment-limiting side effects, such as ifosfamide-induced neurotoxicity (IIN). Especially in sarcoma, consecutive risk assessment analyses investigating the individual factors associated with the increased incidence in IIN, remain insufficient so far. In this retrospective analysis, we investigated 172 sarcoma patients treated with ifosfamide. Out of 172 patients, 49 patients (28.5%) developed IIN. While gender, age, histologic origin, and tumor stage were not associated with the occurrence of IIN, infusion times, simultaneous radiotherapy, and concomitant use of opioids or anticonvulsants affected the risk of developing IIN. Sarcoma patients with IIN showed an alteration in several inflammatory markers, including a lower lymphocyte count, hemoglobin levels, and calcium levels, as well as elevated GGT, sodium, and CRP levels. Remarkably, the occurrence of IIN was associated with a worse prognosis regarding progression free and overall survival. In addition, high CTCAE grades were negatively associated with overall survival in sarcoma. The observation that an inflammatory state is associated with an increased risk of IIN in sarcoma patients can be used prospectively to further investigate the relationship of inflammation and IIN. In addition, the easily accessible blood markers used in our study to predict IIN can be incorporated into clinical decision making.

Curcumol Synergizes with Cisplatin in Osteosarcoma by Inhibiting M2-like Polarization of Tumor-Associated Macrophages

Osteosarcoma is the most prevalent bone cancer, and chemotherapy is still an indispensable treatment in its clinical practice. Cisplatin (CDDP) has become the most commonly used agent for osteosarcoma, although the outcomes of CDDP chemotherapy remain unsatisfactory because of frequent resistance. Here, we report on a promising combination therapy where curcumol, a bioactive sesquiterpenoid, enhanced CDDP-induced apoptosis to eradicate osteosarcoma cells, and revealed that M2-like macrophages might be the underlying associated mechanisms. First, we observed that curcumol enhanced the CDDP-mediated inhibition of cell proliferation and augmented the apoptosis in osteosarcoma cell lines. Curcumol contributed to preventing the migration of osteosarcoma cells when combined with CDDP. Moreover, this drug combination showed more potent tumor-growth suppression in the orthotopic transplantation of osteosarcoma K7M2 WT cells. We then estimated chemotherapy-associated drug-resistant genes, including ABCB1, ABCC1 and ABCG2, and found that curcumol significantly reversed the mRNA levels of CDDP-induced ABCB1, ABCC1 and ABCG2 genes in the tumor tissue. Moreover, M2-like macrophages were enriched in osteosarcoma tissues, and were largely decreased after curcumol and CDDP treatment. Taken together, these findings suggest that curcumol inhibits the polarization of M2-like macrophages and could be a promising combination strategy to synergize with CDDP in the osteosarcoma.