Construction of a prognostic signature in Ewing's sarcoma: Based on metabolism-related genes

ObjectiveBy combining the expression profiles of metabolism-related genes (MRGS) with clinical information, the expression quantities of MRGS and the influence on development and prognosis were systematically analyzed, so as to provide a theoretical basis for the clinical study on the prognosis of Ewing's sarcoma.MethodsMRGs expression profiles of 64 patients with Ewing's sarcoma were obtained from GEO dataset. Univariate Cox regression analysis was used to identify metabolization-related differentially expressed genes (DEGs) related with prognosis in Ewing's sarcoma patients. Then, multivariate Cox analysis was used to calculate novel prognostic markers based on metabolism-related DEGs. Besides, We validate the model using ICGC datasets. Finally, the new prognostic index was verified on the basis of the prognostic models.ResultsMultivariate Cox regression analysis identified 74 metabolization-related DEGs, 25 of which were associated with Ewing's sarcoma patients' overall survival. Subsequently, we used 25 DEGs to construct metabolism-related prognostic signature for patients with Ewing's sarcoma. Based on the 18 DEGs regression coefficient, we propose the formula of each patient's risk score, and then divided the patients into high-risk group and low-risk group. The results indicated that the survival rate and survival time were higher in the low-risk group and lower in the high-risk group. Multivariate Cox analysis showed that risk score index was an independent prognostic factor for Ewing's sarcoma.ConclusionThe experimental results suggest that the 18 metabolism-related DEGs marker may be effective in predicting the prognosis of Ewing's sarcoma to some extent, helping to individualize treatment of patients at different risks.     

Identification of a prognostic signature based on immune-related genes in bladder cancer

Bladder cancer (BLCA) has a high incidence and recurrence rate, and the effect of immunotherapy varies from person to person. Immune-related genes (IRGs) have been shown to be associated with immunotherapy and prognosis in many other cancers, but their role in immunogenic BLCA is less well defined. In this study, we constructed an eight-IRG risk model, which demonstrated strong prognostic and immunotherapeutic predictive power. The signature was significantly related to tumor clinicopathological characteristics, tumor class, immune cell infiltration and mutation status. Additionally, a nomogram containing the risk score and other potential risk factors could effectively predict the long-term overall survival probability of BLCA patients. The enriched mechanisms identified by gene set enrichment analysis suggested that the reason why this signature can accurately distinguish high- and low-risk populations may be closely related to the different degrees of innate immune response and T cell activation in different patients.     

Development and validation of robust metabolism-related gene signature in the prognostic prediction of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours worldwide. Given metabolic reprogramming in tumours was a crucial hallmark, several studies have demonstrated its value in the diagnostics and surveillance of malignant tumours. The present study aimed to identify a cluster of metabolism-related genes to construct a prediction model for the prognosis of HCC. Multiple cohorts of HCC cases (466 cases) from public datasets were included in the present analysis. (GEO cohort) After identifying a list of metabolism-related genes associated with prognosis, a risk score based on metabolism-related genes was formulated via the LASSO-Cox and LASSO-pcvl algorithms. According to the risk score, patients were stratified into low- and high-risk groups, and further analysis and validation were accordingly conducted. The results revealed that high-risk patients had a significantly worse 5-year overall survival (OS) than low-risk patients in the GEO cohort. (30.0% vs. 57.8%; hazard ratio [HR], 0.411; 95% confidence interval [95% CI], 0.302–0.651; p < 0.001) This observation was confirmed in the external TCGA-LIHC cohort. (34.5% vs. 54.4%; HR 0.452; 95% CI, 0.299–0.681; p < 0.001) To promote the predictive ability of the model, risk score, age, gender and tumour stage were integrated into a nomogram. According to the results of receiver operating characteristic curves and decision curves analysis, the nomogram score possessed a superior predictive ability than conventional factors, which indicate that the risk score combined with clinicopathological features was able to achieve a robust prediction for OS and improve the individualized clinical decision making of HCC patients. In conclusion, the metabolic genes related to OS were identified and developed a metabolism-based predictive model for HCC. Through a series of bioinformatics and statistical analyses, the predictive ability of the model was approved.     

Identification of lipid metabolism-related genes as prognostic indicators in papillary thyroid cancer

Lipid metabolism plays important roles not only in the structural basis and energy supply of healthy cells but also in the oncogenesis and progression of cancer...     

Prognostic implication of cuproptosis related genes associates with immunity in Ewing's sarcoma

Growing evidence demonstrated that cuproptosis play critical roles in human cancers. We aimed to identify the roles of cuproptosis related genes (CRGs) in prognosis and immunity of Ewing's sarcoma.The data of GSE17674 and GSE63156 were obtained from GEO. The expression of 17 CRGs and immune cells were explored, then correlation was analyzed. Based on CRGs, two molecular clusters were identified by consensus clustering algorithm. KM survival and IME features including immune cells, immune response, checkpoint genes between clusters were evaluated. NFE2L2, LIAS, and CDKN2A were screened out as prognostic signatures by univariate, LASSO and step regression. A risk model was established, and validated by KM method with p = 0.0026, and perfect AUC values. The accuracy of risk model was also well validated in external dataset. A nomogram was constructed and evaluated by calibration curves and DCA. Low level of immune cells, immune response, and enriched checkpoint genes were found in high-risk group. GSEA of signatures and GSVA of ES-related pathways revealed the potential molecular mechanism involved in ES progression. Several drugs showed sensitivity to ES samples. DEGs between risk groups were screened out, and function enrichment was conducted. Finally, scRNA analysis of GSE146221 was done. NFE2L2, and LIAS played crucial role in the evolution of ES by pesudotime and trajectory methods. Our study provided new aspects for further research in ES.     

Primary Ewing's sarcoma of the kidney: a case report

Primary adult Ewing's sarcoma is a rare entity. They most commonly occur in children and young adults. 6% of them are localized extraosseously. We present a case of a 51 year old patient with primary renal Ewing's sarcoma and multiple metastases in liver and iliac bone. Patients with metastatic disease are usually treated with aggressive chemotherapy and have a poor outcome. Our patient underwent complete surgical excision of tumour, and was treated with aggressive chemotherapy, respectively. Two and half years after presentation he is well, without any symptoms.     

Identification of a metabolism-related gene signature predicting overall survival for bladder cancer

Reprogramming of metabolism is becoming a novel hallmark of cancer. This study aims to perform bioinformatics analysis of metabolism-related genes in bladder cancer, and to construct a signature of metabolism-related genes for predicting the prognosis. A total of 373 differentially expressed metabolism-related genes were identified from TCGA database. Taking survival time and clinical information into consideration, we constructed a risk score to predict clinical prognosis. Low-risk patients had a better prognosis than high-risk patients. Multivariate analysis showed that risk score was an independent prognostic indicator in bladder cancer. ROC curve also proved that risk score had better ability to predict prognosis than other individual indicators. Nomogram also showed a clinical net benefit to evaluate the prognosis of bladder cancer patients. GSEA revealed several metabolism-related pathways that were differentially enriched in the high-risk and low-risk groups, which might help to explain the underlying mechanisms. This signature was confirmed to be an effective prognostic biomarker in bladder cancer.     

Immunologic monitoring and immunotherapy in Ewing's sarcoma

Summary Serial immunological monitoring was performed on 31 patients with Ewing's sarcoma who were on a randomized immunotherapy trial with BCG administered by dermal scarification with a Heaf gun. Patients were skin-tested for delayed hypersensitivity reactions (DCHR) to recall antigens and extracts of tumor cells, and with keyhole limpet hemocyanin (KLH). In vitro testing consisted of lymphocyte counts, percentages of cells forming rosettes with sheep erythrocytes at 29° C and at 4° C, and leukocyte migration inhibition to tuberculin (PPD) and to 3 M KCl extracts of tumor cells. At the time of diagnosis, nearly all patients had positive DCHR to mumps and streptococcal antigens and were negative to PPD. Neither the skin tests nor the lymphocyte counts at this time gave useful prognostic information. In tests during and after therapy, the patients who responded and remained free of detectable disease had a higher incidence of DCHR to KLH and of rosette values in the normal range than did the patients who developed recurrent disease. The BCG immunotherapy had no apparent effect on immunologic parameters except for conversion of reactions to PPD.     

Sex-differential expression of metabolism-related genes in response to a high-fat diet

Objective: The aim of this work was to determine the sex‐associated differences in the expression of genes related to lipid metabolism and fuel partitioning in response to a high‐fat (HF) diet in rats, and whether this is linked to the higher tendency of males to suffer from metabolic disorders. Methods and Procedures: Male and female Wistar rats were fed for 6 months on a normal‐fat (NF) or an HF diet. Body weight, fat depot weight, lipid concentration in liver, blood metabolites, and the expression of genes involved in fuel metabolism and partitioning in the liver, white adipose tissue (WAT), and skeletal muscle were measured. Results: Female rats fed on an HF diet gained more weight and had a greater increase in the adiposity index than male rats, while the circulating insulin levels remained unaltered; these animals also showed an increased expression of genes related to the energy influx in WAT and with fat utilization in skeletal muscle. Male but not female rats showed increased hepatic peroxisome proliferator–activated receptor‐ α (PPAR‐ α ) and CPT1L mRNA expression, suggesting enhanced lipid handling and oxidation by this organ, and have a higher triacylglycerol content in liver. Male rats under the HF diet also displayed higher blood insulin levels. Discussion: These results show sex‐dependent differences in lipid handling and partitioning between tissues in response to an HF diet, with females showing a higher capacity for storing fat in adipose tissue and for oxidizing fatty acids in muscle. These adaptations can help to explain the lower tendency of females to suffer from obesity‐linked disorders under the conditions of an HF diet.     

Molecular characterization of lung cancer: A two-miRNA prognostic signature based on cancer stem-like cells related genes

Lung cancer is one of the deadliest cancers worldwide. To increase the survival rate of lung cancer, it is necessary to explore specific prognosis markers. More and more evidence finds that noncoding RNA is closely associated with the survival of lung cancer, and cancer stem cells (CSCs) also play a significant role in the progress of lung cancer. The objective of this study is to find CSLCs genes that affect the prognosis of lung cancer. The differential expression of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), messenger RNAs (mRNAs) in the Cancer Genome Atlas (TCGA) database and differential expression data from microarray of CD326⁺ and CD326⁻ A549 cell are intersected to identify stable and consistent expression genes (2 lncRNAs, 15 miRNAs, and 134 mRNAs). The intersection of lncRNAs and miRNAs is analyzed by univariate and multivariate Cox regression to obtained prognostic genes. Two miRNAs (miR-30b-5p and miR-29c-3p) are significantly correlated with the overall survival rate. Then using these two miRNAs to construct a risk score model as a prognosis signature of lung cancer. Subsequently, we analyzed the association between two miRNAs and clinical information of lung cancer patients, of which T stage, Neoplasm cancer and risk score (P < .05) can be used as independent prognostic indicators of lung cancer. Finally, target genes of 2 miRNAs and 134 mRNAs were annotated with Gene Ontology and analyzed with Kyoto Encyclopedia of Genes and Genomes pathway, and verified with the GEO database. In summary, this study illustrates the role of miRNAs in the promotion of lung cancer by CSCs, which is important to find molecular biomarkers of lung cancer.     

Construction of a prognostic model for non-small-cell lung cancer based on ferroptosis-related genes

We wished to construct a prognostic model based on ferroptosis-related genes and to simultaneously evaluate the performance of the prognostic model and analyze differences between high-risk and low-risk groups at all levels. The gene-expression profiles and relevant clinical data of patients with non-small-cell lung cancer (NSCLC) were downloaded from public databases. Differentially expressed genes (DEGs) were obtained by analyzing differences between cancer tissues and paracancerous tissues, and common genes between DEGs and ferroptosis-related genes were identified as candidate ferroptosis-related genes. Next, a risk-score model was constructed using univariate Cox analysis and least absolute shrinkage and selection operator (Lasso) analysis. According to the median risk score, samples were divided into high-risk and low-risk groups, and a series of bioinformatics analyses were conducted to verify the predictive ability of the model. Single-sample gene set enrichment analysis (ssGSEA) was used to investigate differences in immune status between high-risk and low-risk groups, and differences in gene mutations between the two groups were investigated. A risk-score model was constructed based on 21 ferroptosis-related genes. A Kaplan–Meier curve and receiver operating characteristic curve showed that the model had good prediction ability. Univariate and multivariate Cox analyses revealed that ferroptosis-related genes associated with the prognosis may be used as independent prognostic factors for the overall survival time of NSCLC patients. The pathways enriched with DEGs in low-risk and high-risk groups were analyzed, and the enriched pathways were correlated significantly with immunosuppressive status.     

Pre-clinical and clinical significance of heparanase in Ewing's sarcoma

Heparanase is an endoglycosidase that specifically cleaves heparan sulphate side chains of heparan sulphate proteoglycans, activity that is strongly implicated in cell migration and invasion associated with tumour metastasis, angiogenesis and inflammation. Heparanase up-regulation was documented in an increasing number of human carcinomas, correlating with reduced post-operative survival rate and enhanced tumour angiogenesis. Expression and significance of heparanase in human sarcomas has not been so far reported. Here, we applied the Ewing's sarcoma cell line TC71 and demonstrated a potent inhibition of cell invasion in vitro and tumour xenograft growth in vivo upon treatment with a specific inhibitor of heparanase enzymatic activity (compound SST0001, non-anticoagulant N-acetylated, glycol split heparin). Next, we examined heparanase expression and cellular localization by immunostaining of a cohort of 69 patients diagnosed with Ewing's sarcoma. Heparanase staining was noted in all patients. Notably, heparanase staining intensity correlated with increased tumour size (P = 0.04) and with patients' age (P = 0.03), two prognostic factors associated with a worse outcome. Our study indicates that heparanase expression is induced in Ewing's sarcoma and associates with poor prognosis. Moreover, it encourages the inclusion of heparanase inhibitors (i.e. SST0001) in newly developed therapeutic modalities directed against Ewing's sarcoma and likely other malignancies.     

Sensitivity of Ewing's sarcoma to TRAIL-induced apoptosis.

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is able to kill transformed cells. We have studied the expression and functionality of the TRAIL apoptotic pathway in Ewing's sarcoma. We demonstrate that tumors from patients with Ewing's sarcoma express receptors TRAIL-R1 and -R2. Using a panel of nine Ewing's sarcoma cell lines TRAIL could induce apoptosis in seven cell lines. Preincubation with interferon-gamma rendered the two resistant cell lines sensitive. TRAIL was the most potent inducer of apoptosis when compared to Fas ligand or TNF. TRAIL-mediated apoptosis could be inhibited by various caspase-inhibitors. No difference in the surface expression of TRAIL-receptors was observed between sensitive and resistant cell lines. Also, all cell lines had similar levels of expression of Flice-like inhibitory protein (FLIP) on immunoblot. However, the two resistant cell lines had only very low level expression of caspase 8 on RNA and protein level. In summary, we show that Ewing's sarcoma expresses receptors for TRAIL, and that cells are exquisitely sensitive to TRAIL-mediated apoptosis. These results may warrant clinical trials with TRAIL in Ewing's sarcoma once the safety of TRAIL for humans has been established.     

Digital cell image analysis of Ewing's sarcoma.

We analyzed the lesional tissue in Ewing's sarcoma by means of a cell image processor computing 15 nuclear parameters in order to quantify the morphologic variability of the tumor cell nuclei. To this end we combined 32 cases (350-400 Feulgen-stained nuclei analyzed per case) in a data file, which was then subjected to principal component and canonical analyses. We found considerable heterogeneity within the cell nucleus population of Ewing's sarcomas. Indeed, after the arbitrary subdivision of the file into two cell classifiers (CC1 and CC2 cell types) on the basis of the first canonical function, the 32 Ewing's sarcomas showed a great deal of variability in the proportion of CC1 and CC2 cell nucleus types. The nuclei of the CC1 type had a more finely textured chromatin when compared to the CC2 type, the nuclei of which exhibited a more granular chromatin pattern. Additionally, these 32 Ewing's sarcomas were characterized by three distinct DNA histogram types. Eight tumors displayed a diploid nonproliferating DNA histogram pattern (type A), 11 a diploid proliferating (type B) and 13 an aneuploid (type C) DNA histogram profile. We found a highly significant relationship between these DNA histogram types and the CC1:CC2 cell type percentage ratio. The eight Ewing's sarcomas with a type A DNA histogram contained a significantly higher proportion of CC1 cell type nuclei as compared to the 13 tumors with a type C DNA histogram, which contained a great proportion of CC2 cell type nuclei.     

Therapeutic use of carminomycin in Ewing's sarcoma in children]

The therapeutic effect of carminomycin in various combinations with other antitumor drugs, i. e. vincristin, cyclophosphan, dactinomycin and metatrexate was studied in clinics on 18 children with wide-spread Juing sarcoma. Satisfactory direct effect was observed with the use of the above combinations in 47.0 per cent of the patients, which was evident from a decrease in the secondary tumor, disappearance of the pains and improvement of the general state of the patients.