A tool for predicting overall survival in patients with Ewing sarcoma: a multicenter retrospective study

Chimeric protein EWS::FLI1 drives cell proliferation in Ewing Sarcoma via aberrant expression of KCNN1/SK1 and dysregulation of calcium signaling

Ewing sarcoma (ES) is characterized by EWS::FLI1 or EWS::ERG fusion proteins. Knowing that ion channels are involved in tumorigenesis, this work aimed to study the involvement of the KCNN1 gene, which encodes the SK1 potassium channel, in ES development. Bioinformatics analyses from databases were used to study KCNN1 expression in patients and cell lines. Molecular approaches and in vitro assays were used to study the transcriptional regulation of KCNN1 and its involvement in the regulation of ES cell proliferation. KCNN1 is overexpressed in ES patient biopsies, and its expression is inversely correlated with patient survival. EWS::FLI1, like EWS::ERG, promotes KCNN1 and SK1 expression, binding to GGAA microsatellites near the promoter of KCNN1 isoforms. KCNN1 is involved in the regulation of ES cell proliferation, with its silencing being associated with a slowing of the cell cycle, and its expression modulates membrane potential and therefore calcium flux. These results highlight that KCNN1 is a direct target of EWS::FLI1 and EWS::ERG and demonstrate that KCNN1 is involved in the regulation of intracellular calcium activity and ES cell proliferation, making it a promising therapeutic target in ES.

Development and internal validation of prognostic models for event-free survival in newly diagnosed Ewing sarcoma patients based on routinely collected clinical characteristics from the European randomised controlled trial, EE2012

INTRODUCTION

Ewing sarcoma is a rare paediatric cancer. Currently, there is no way of accurately predicting these patients' survival at diagnosis. Disease type (ie, localised disease, lung/pleuropulmonary metastases and other metastases) is used to guide treatment decisions, with metastatic patients generally having worse outcomes than localised disease patients. However, not all patients fit this trend. An accurate prognostic model could be used to guide treatment decisions in clinical practice to avoid patients being incorrectly under or overtreated.

METHODS AND ANALYSIS

This study aims to develop and internally validate prognostic models in newly diagnosed Ewing sarcoma patients, using the EE2012 clinical trial data set. The models will incorporate prognostic factors, identified from a literature review, to predict patients' probability of event-free survival at clinically important time points. Three models will be developed, for comparison of their performance and stability, using different methods of model selection and penalisation for overfitting (full model or backwards selection applying uniform shrinkage; and lasso variable selection). The models will be internally validated using bootstrapping to give optimism-adjusted performance statistics (calibration and discrimination) and model stability results. Patient and clinical user groups will be asked to determine risk thresholds to guide treatment decisions in clinical practice based on the model. Decision curve analyses will examine clinical utility at these thresholds.

ETHICS AND DISSEMINATION

This study is a secondary analysis of EE2012 clinical trial data. The EE2012 trial received ethical approval from the competent authorities (UK ethics reference approval number 12/NW/0827). This study is covered by the trial ethics in place. The results from this study will be published in peer-reviewed journals to act as a benchmark for future studies.

TRIAL REGISTRATION NUMBER

EudraCT number 2012-002107-17. ISRCTN number 92192408.

Transcriptional regulation of KCNA2 coding Kv1.2 by EWS::FLI1: involvement in controlling the YAP/Hippo signalling pathway and cell proliferation

BACKGROUND

Ewing sarcoma (ES), the second main pediatric bone sarcoma, is characterised by a chromosomal translocation leading to the formation of fusion proteins like EWS::FLI1. While several studies have shown that potassium channels drive the development of many tumours, limited data exist on ES. This work therefore aimed to study the transcriptional regulation of KCNA2 and define the involvement of the Kv1.2 channel encoded by KCNA2 in a key function of ES development, cell proliferation.

METHODS

KCNA2 expression in patients and cell lines was measured via bioinformatic analysis (RNA-Seq). The presence of a functional Kv1.2 channel was shown using patch-clamp experiments. Molecular biology approaches were used after EWS::FLI1 silencing to study the transcriptional regulation of KCNA2. Proliferation and cell count assessment were performed using cell biology approaches. KCNA2 silencing (siRNA) and RNA-Seq were performed to identify the signalling pathways involved in the ability of KCNA2 to drive cell proliferation. The regulation of the Hippo signalling pathway by KCNA2 was studied by measuring Hippo/YAP target genes expression, while YAP protein expression was studied with Western-Blot and immunofluorescence approaches.

RESULTS

This research identified KCNA2 (encoding for a functional Kv1.2 channel) as highly expressed in ES biopsies and cell lines. The results indicated a correlation between KCNA2 expression and patient survival. The data also demonstrated that KCNA2/Kv1.2 is a direct target of EWS::FLI1, and identified the molecular mechanisms by which this chimeric protein regulates KCNA2 gene expression at the transcriptional level. Furthermore, the results indicated that KCNA2 expression and Kv1.2 activity regulate ES cell proliferation and that KCNA2 expression drives the Hippo/YAP signalling pathway. Using the specific Kv1.2 channel inhibitor (κ-Conotoxin), the results suggested that two complementary mechanisms are involved in this process, both dependently and independently of Kv1.2 functional channels at the plasma membrane.

CONCLUSION

This study is the first to describe the involvement of KCNA2 expression and Kv1.2 channel in cancer development. The study also unveiled the involvement of KCNA2 in the regulation of the Hippo/YAP signalling cascade. Thus, this work suggests that KCNA2/Kv1.2 could be a potential therapeutic target in ES.

Development and validation of a machine learning-based model to predict postoperative overall survival in patients with soft tissue sarcoma: a retrospective cohort study

BACKGROUND

The aim of this study is to develop a machine learning-based model to predict postoperative overall survival (OS) in patients with soft tissue sarcoma (STS) that demonstrates superior comprehensive performance.

METHODS

This analysis leveraged data from the SEER database spanning 2010-2020, alongside a STS cohort from the National Cancer Center. Machine learning methods were applied for predictor selection by wrapper methods and the development of the predictive model. The optimal model was determined using the concordance index (C-index), time-dependent calibration curves, time dependent receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).

RESULTS

Six machine learning learners identified six feature subsets. Subsequently, six feature subsets and six machine learning learners were combined, resulting in the development of 36 prognostic models. The CAM model, exhibiting the highest prediction performance, was selected. The CAM model achieved a C-index of 0.849 (95% CI 0.837-0.859) in the training cohort and 0.837 (95% CI 0.809-0.871) in the validation cohort. Furthermore, time-dependent calibration curves, time-dependent ROC curves, and DCA indicate that the PAM demonstrates excellent calibration, predictive accuracy, and clinical net benefit. A publicly accessible web tool was developed for the CAM. Notably, CAM's performance exceeds that of all existing STS prognostic nomograms and prediction models.

CONCLUSIONS

The CAM has the potential to identify postoperative OS in STS patients. This can assist clinicians in assessing the severity of the disease, facilitating patient follow-up, and aiding in the formulation of adjuvant treatment strategies.

Prognostic factors and overall survival in pelvic Ewing's sarcoma and chordoma: A comparative SEER database analysis

Background

This study aimed to develop and validate nomograms to predict overall survival (OS) for pelvic Ewing's sarcoma (EWS) and chordoma, identify prognostic factors, and compare outcomes between the two conditions.

Methods

We identified patients diagnosed with pelvic EWS or chordoma from the SEER database (2001-2019). Independent risk factors were identified using univariate and multivariate Cox regression analyses, and these factors were used to construct nomograms predicting 3-, 5-, and 10-year OS. Validation methods included AUC, calibration plots, C-index, and decision curve analysis (DCA). Kaplan-Meier curves and log-rank tests compared survival differences between low- and high-risk groups.

Results

The study included 1175 patients (EWS: 611, chordoma: 564). Both groups were randomly divided into training (70 %) and validation (30 %) cohorts. OS was significantly higher for chordoma. Multivariate analysis showed year of diagnosis, income, stage, and surgery were significant for EWS survival, while age, time to treatment, stage, and surgery were significant for chordoma survival. Validation showed the nomograms had strong predictive performance and clinical utility.

Conclusions

The nomograms reliably predict overall survival (OS) in pelvic EWS and chordoma, helping to identify high-risk patients early and guide preventive measures. The study also found that survival rates are significantly higher for chordoma, highlighting different prognostic profiles between EWS and chordoma.

Serum glutathione peroxidase 4 as a novel biomarker for nontraumatic osteonecrosis of the femoral head: A retrospective case-control study

There are no serum biomarkers available in nontraumatic osteonecrosis of the femoral head in clinical practice. This study aimed to evaluate the clinical value of serum glutathione peroxidase 4 in nontraumatic osteonecrosis of the femoral head. This retrospective study analyzed serum glutathione peroxidase 4 levels and clinical data of 80 patients with nontraumatic osteonecrosis of the femoral head and 80 healthy controls between August 2021 and May 2022. Serum glutathione peroxidase 4 levels were analyzed using an enzyme-linked immunosorbent assay. The Association Research Circulation Osseous classification system determined disease progression. Clinical severity was assessed by Harris hip score and visual analogue scale. Correlations between serum glutathione peroxidase 4 and disease progression as well as clinical severity were evaluated statistically. The diagnostic accuracy of serum glutathione peroxidase 4 in nontraumatic osteonecrosis of the femoral head was determined using receiver operating characteristic analysis. The baseline characteristics of participants between 2 groups were comparable. Patients with nontraumatic osteonecrosis of the femoral head displayed a decreased glutathione peroxidase 4 level compared with healthy controls (11.87 ± 2.76 μU/mL vs 16.54 ± 4.89 μU/mL, P < .01). The levels of glutathione peroxidase 4 were inversely correlated with Association Research Circulation Osseous stage (P < .01) and visual analogue scale scores (P < .01), and positively correlated with Harris score (P < .01). Receiver operating characteristic analyses showed that area under curves of glutathione peroxidase 4 was 0.808 (95% CI 0.721-0.858) and 0.847 (95% CI 0.743-0.951) with regard to diagnosis and collapse prediction in nontraumatic osteonecrosis of the femoral head, respectively. Serum glutathione peroxidase 4 could serve as a novel biomarker for diagnosing nontraumatic osteonecrosis of the femoral head and predicting collapse of the femoral head.

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.

Downregulated annexin A1 expression correlates with poor prognosis, metastasis, and immunosuppressive microenvironment in Ewing's sarcoma

OBJECTIVE

Ewing's sarcoma (ES) is a common bone malignancy in children and adolescents that severely affects the prognosis of patients. The aim of this study was to identify novel biomarkers and potential therapeutic targets for ES.

METHODS

Highly prognosis-related hub genes were identified by independent prognostic analysis in the GSE17679 dataset. We then performed survival analysis, Cox regression analysis and clinical correlation analysis on the key gene and validated them with the GSE63157, GSE45544 and GSE73166 datasets. Differentially expressed genes (DEGs) were screened based on the high and low expression of key gene, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA) were performed to explore the underlying mechanisms of ES, and significant module genes were established based on protein-protein interaction (PPI) networks. Furthermore, the correlations between module genes and the immune microenvironment were analyzed and the correlations between the key gene and immune infiltration levels in sarcoma were investigated using TIMER and TISIDB. Finally, the expression levels of these key genes in ES cell lines (RD-ES and A673 cells) were further validated by real-time quantitative PCR (RT-qPCR). CCK-8 and EdU assays were performed to assess the effect of ANXA1 knockdown on RD-ES cell proliferation.

RESULTS

ANXA1 was identified as a key gene for ES prognosis. The overall survival (OS) time of patients with low ANXA1 expression was shorter, and the expression level of ANXA1 in the metastatic group was significantly lower than that in the primary group (P<0.01). Additionally, the abundance of 12 immune cells in the ANXA1 low-expression group was significantly lower than that in the high-expression group (all P<0.05), which may be related to the inhibition of the immune microenvironment. A PPI network was constructed based on 96 DEGs to further identify the five ANXA1-related module genes (COL1A2, MMP9, VIM, S100A11 and S100A4). The expression levels of ANXA1, COL1A2, MMP9, VIM, S100A11 and S100A4 were significantly different between ES cell lines and mesenchymal stem cells after validation in two ES cell lines (all P<0.01). Among these genes, ANXA1, COL1A2, MMP9, VIM and S100A4 were significantly associated with the prognosis of ES patients (all P<0.05). Importantly, ANXA1 knockdown significantly promoted the proliferation of RD-ES cells, which may explain the susceptibility to ES metastasis in the ANXA1 low-expression group.

CONCLUSIONS

ANXA1 may serve as an independent prognostic biomarker for ES patients and is associated with metastasis and the immunosuppressive microenvironment in ES, which needs to be validated in further studies.

Exploration of Flavonoids as Lead Compounds against Ewing Sarcoma through Molecular Docking, Pharmacogenomics Analysis, and Molecular Dynamics Simulations

Ewing sarcoma (ES) is a highly malignant carcinoma prevalent in children and most frequent in the second decade of life. It mostly occurs due to t(11;22) (q24;q12) translocation. This translocation encodes the oncogenic fusion protein EWS/FLI (Friend leukemia integration 1 transcription factor), which acts as an aberrant transcription factor to deregulate target genes essential for cancer. Traditionally, flavonoids from plants have been investigated against viral and cancerous diseases and have shown some promising results to combat these disorders. In the current study, representative flavonoid compounds from various subclasses are selected and used to disrupt the RNA-binding motif of EWS, which is required for EWS/FLI fusion. By blocking the RNA-binding motif of EWS, it might be possible to combat ES. Therefore, molecular docking experiments validated the binding interaction patterns and structural behaviors of screened flavonoid compounds within the active region of the Ewing sarcoma protein (EWS). Furthermore, pharmacogenomics analysis was used to investigate potential drug interactions with Ewing sarcoma-associated genes. Finally, molecular dynamics simulations were used to investigate the stability of the best selected docked complexes. Taken together, daidzein, kaempferol, and genistein exhibited a result comparable to ifosfamide in the proposed in silico study and can be further analyzed as possible candidate compounds in biological in vitro studies against ES.

Integrating single-cell RNA-seq and bulk RNA-seq to construct prognostic signatures to explore the role of glutamine metabolism in breast cancer

BACKGROUND

Although breast cancer (BC) treatment has entered the era of precision therapy, the prognosis is good in the case of comprehensive multimodal treatment such as neoadjuvant, endocrine, and targeted therapy. However, due to its high heterogeneity, some patients still cannot benefit from conventional treatment and have poor survival prognoses. Amino acids and their metabolites affect tumor development, alter the tumor microenvironment, play an increasingly obvious role in immune response and regulation of immune cell function, and are involved in acquired and innate immune regulation; therefore, amino acid metabolism is receiving increasing attention.

METHODS

Based on public datasets, we carried out a comprehensive transcriptome and single-cell sequencing investigation. Then we used 2.5 Weighted Co-Expression Network Analysis (WGCNA) and Cox to evaluate glutamine metabolism-related genes (GRGs) in BC and constructed a prognostic model for BC patients. Finally, the expression and function of the signature key gene SNX3 were examined by in vitro experiments.

RESULTS

In this study, we constituted a risk signature to predict overall survival (OS) in BC patients by glutamine-related genes. According to our risk signature, BC patients can obtain a Prognostic Risk Signature (PRS), and the response to immunotherapy can be further stratified according to PRS. Compared with traditional clinicopathological features, PRS demonstrated robust prognostic power and accurate survival prediction. In addition, altered pathways and mutational patterns were analyzed in PRS subgroups. Our study sheds some light on the immune status of BC. In in vitro experiments, the knockdown of SNX3, an essential gene in the signature, resulted in a dramatic reduction in proliferation, invasion, and migration of MDA-MB-231 and MCF-7 cell lines.

CONCLUSION

We established a brand-new PRS consisting of genes associated with glutamine metabolism. It expands unique ideas for the diagnosis, treatment, and prognosis of BC.