Decreased expression of STAT5A predicts poor prognosis in osteosarcoma

A novel classification predicts prognosis and drug sensitivity in osteosarcoma based on alterations in gene sets

Osteosarcoma is a cancer originating in the bone cells, specifically in the osteoblasts. Previous studies mainly focused on particular molecules but the whole pathway network. We comprehensively analyzed the enrichment score of each signal pathway and identified a novel classification by 20 machine learning algorithms. Furthermore, differences in tumor immune infiltration cells and drug sensitivity were compared in low and high groups. We identified a model consisting of four signaling pathways that predict the prognosis and the immune status of the tumor microenvironment and drug sensitivity in osteosarcoma patients. The novel classification may be used in clinical applications to predict prognosis and drug sensitivity.

Effect of traditional Chinese medicine in osteosarcoma: Cross-interference of signaling pathways and potential therapeutic targets

Osteosarcoma (OS) has a high recurrence rate, disability rate, mortality and metastasis, it brings great economic burden and psychological pressure to patients, and then seriously affects the quality of life of patients. At present, the treatment methods of OS mainly include radiotherapy, chemotherapy, surgical therapy and neoadjuvant chemotherapy combined with limb salvage surgery. These treatment methods can relieve the clinical symptoms of patients to a certain extent, and also effectively reduce the disability rate, mortality and recurrence rate of OS patients. However, because metastasis of tumor cells leads to new complications, and OS cells become resistant with prolonged drug intervention, which reduces the sensitivity of OS cells to drugs, these treatments still have some limitations. More and more studies have shown that traditional Chinese medicine (TCM) has the characteristics of "multiple targets and multiple pathways," and can play an important role in the development of OS through several key signaling pathways, including PI3K/AKT, Wnt/β-catenin, tyrosine kinase/transcription factor 3 (JAK/STAT3), Notch, transforming growth factor-β (TGF-β)/Smad, nuclear transcription factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nuclear factor E2-related factor 2 (Nrf2), Hippo/YAP, OPG/RANK/RANKL, Hedgehog and so on. In this paper, the signaling pathways of cross-interference between active ingredients of TCM and OS were reviewed, and the development status of novel OS treatment was analyzed. The active ingredients in TCM can provide therapeutic benefits to patients by targeting the activity of signaling pathways. In addition, potential strategies for targeted therapy of OS by using ferroptosis were discussed. We hope to provide a unique insight for the in-depth research and clinical application of TCM in the fields of OS growth, metastasis and chemotherapy resistance by understanding the signaling crosstalk between active ingredients in TCM and OS.

Expression and prognostic role of STAT5a across cancer types

Studies examining the role of signal transducer and activator of transcription 5 (STAT5) in various cancers have produced controversial results. To address this controversy, we examined the prognostic role of STAT5a in cancer patients across multiple cancers. Transcription levels of STAT5a between tumors and normal tissues, obtained from public databases, were analyzed for statistical differences using Cox regression analysis with the outcome as overall survival and covariate of interest as high STAT5a expression. Meta-analysis was then conducted to summarize the hazard ratio estimate from the Cox regression analyses. We found that STAT5a was significantly under-expressed in breast, lung, and ovarian cancers, while STAT5a was significantly overexpressed in lymphoid neoplasm diffuse large B-cell lymphoma, glioblastoma, and glioma. High STAT5a expression was significantly associated with favorable survival in bladder cancer (lnHR = -0.8689 [-1.4087, -0.3292], P-value = 0.0016), breast cancer (lnHR = -0.7805 [-1.1394, -0.4215], P-value < 0.0001) and lung cancer (lnHR = -0.3255 [-0.6427, -0.0083], P-value = 0.0443). After adjusting for clinicopathological factors, high STAT5a expression remained significantly associated with favorable survival in breast cancer (lnHR = -0.6091 [-1.0810, -0.1372], P-value = 0.0114). These results suggest that higher STAT5a expression is associated with favorable overall survival in breast cancer, and therefore might have protective effects, and that STAT5a expression could be a potential prognostic biomarker, especially in breast cancer. However, the prognostic role of STAT5a is dependent on cancer type.

Construction of Molecular Subtype and Prognosis Prediction Model of Osteosarcoma Based on Aging-Related Genes

Background

Osteosarcoma (OS) is a rare form of malignant bone cancer that is usually detected in young adults and adolescents. This disease shows a poor prognosis owing to its metastatic status and resistance to chemotherapy. Hence, it is necessary to design a risk model that can successfully forecast the OS prognosis in patients.

Methods

The researchers retrieved the RNA sequencing data and follow-up clinical data related to OS patients from the TARGET and GEO databases, respectively. The coxph function in R software was used for carrying out the Univariate Cox regression analysis for deriving the aging-based genes related sto the OS prognosis. The researchers conducted consistency clustering using the ConcensusClusterPlus R package. The R software package ESTIMATE, MCPcounter, and GSVA packages were used for assessing the immune scores of various subtypes using the ssGSEA technique, respectively. The Univariate Cox and Lasso regression analyses were used for screening and developing a risk model. The ROC curves were constructed, using the pROC package. The performance of their developed risk model and designed survival curve was conducted, with the help of the Survminer package.

Results

The OS patients were classified into 2 categories, as per the aging-related genes. The results revealed that the Cluster 1 patients showed a better prognosis than the Cluster 2 patients. Both clusters showed different immune microenvironments. Additional screening of the prognosis-associated genes revealed the presence of 5 genes, i.e., ERCC4, GPX4, EPS8, TERT, and STAT5A, and these data were used for developing the risk model. This risk model categorized the training set samples into the high- and low-risk groups. The patients classified into the high-risk group showed a poor OS prognosis compared to the low-risk patients. The researchers verified the reliability and robustness of the designed 5-gene signature using the internal and external datasets. This risk model was able to effectively predict the prognosis even in the samples having differing clinical features. Compared with other models, the 5- gene model performs better in predicting the risk of osteosarcoma.

Conclusion

The 5-gene signature developed by the researchers in this study could be effectively used for forecasting the OS prognosis in patients.

STAT6 correlates with response to immune checkpoint blockade therapy and predicts worse survival in thyroid cancer

Aim: The signal transducer and activator of transcription (STAT) family has been documented. However, the role of STATs in thyroid cancer was not fully studied. Materials & methods: A survival analysis of STATs was performed. The function modulated by STAT6 was examined. The role of STAT6 in cancer immune infiltrates and immune checkpoint blockade molecules was investigated. Results: Only low STAT6 expression correlated with worse survival. STAT6 is involved in cell cycle, cell adhesion, apoptosis and notch signaling pathways. STAT6 was significantly positively associated with immune infiltration of B cells, CD4+ T cells, neutrophils, macrophages, dendritic cells and the immune checkpoint blockade molecules programmed cell death-ligand 1, programmed cell death-ligand 2 and cytotoxic T-lymphocyte-associated protein 4. Conclusion: STAT6 may act as a prognostic biomarker and provide useful information for immunotherapy in thyroid carcinoma.

Identification of aberrantly methylated differentially expressed genes targeted by differentially expressed miRNA in osteosarcoma

Background

Osteosarcoma (OS) is the most common primary bone tumors diagnosed in children and adolescents. Recent studies have shown a prognostic role of DNA methylation in various cancers, including OS. The aim of this study was to identify the aberrantly methylated genes that are prognostically relevant in OS.

Methods

The differentially expressed mRNAs, miRNAs and methylated genes (DEGs, DEMs and DMGs respectively) were screened from various GEO databases, and the potential target genes of the DEMs were predicted by the RNA22 program. The protein-protein interaction (PPI) networks were constructed using the STRING database and visualized by Cytoscape software. The functional enrichment and survival analyses of the screened genes was performed using the R software.

Results

Forty-seven downregulated hypermethylated genes and three upregulated hypomethylated genes were identified that were enriched in cell activation, migration and proliferation functions, and were involved in cancer-related pathways like JAK-STAT and PI3K-AKT. Eight downregulated hypermethylated tumor suppressor genes (TSGs) were identified among the screened genes based on the TSGene database. These hub genes are likely involved in OS genesis, progression and metastasis, and are potential prognostic biomarkers and therapeutic targets.

Conclusions

TSGs including PYCARD, STAT5A, CXCL12 and CXCL14 were aberrantly methylated in OS, and are potential prognostic biomarkers and therapeutic targets. Our findings provide new insights into the role of methylation in OS progression.