Identification of a novel cuproptosis-related gene signature and integrative analyses in patients with lower-grade gliomas.

Background: Cuproptosis is a newly discovered unique non-apoptotic programmed cell death distinguished from known death mechanisms like ferroptosis, pyroptosis, and necroptosis. However, the prognostic value of cuproptosis and the correlation between cuproptosis and the tumor microenvironment (TME) in lower-grade gliomas (LGGs) remain unknown. Methods: In this study, we systematically investigated the genetic and transcriptional variation, prognostic value, and expression patterns of cuproptosis-related genes (CRGs). The CRG score was applied to quantify the cuproptosis subtypes. We then evaluated their values in the TME, prognostic prediction, and therapeutic responses in LGG. Lastly, we collected five paired LGG and matched normal adjacent tissue samples from Sun Yat-sen University Cancer Center (SYSUCC) to verify the expression of signature genes by quantitative real-time PCR (qRT-PCR) and Western blotting (WB). Results: Two distinct cuproptosis-related clusters were identified using consensus unsupervised clustering analysis. The correlation between multilayer CRG alterations with clinical characteristics, prognosis, and TME cell infiltration were observed. Then, a well-performed cuproptosis-related risk model (CRG score) was developed to predict LGG patients' prognosis, which was evaluated and validated in two external cohorts. We classified patients into high- and low-risk groups according to the CRG score and found that patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (P<0.001). A high CRG score implies higher TME scores, more significant TME cell infiltration, and increased mutation burden. Meanwhile, the CRG score was significantly correlated with the cancer stem cell index, chemoradiotherapy sensitivity-related genes and immune checkpoint genes, and chemotherapeutic sensitivity, indicating the association with CRGs and treatment responses. Univariate and multivariate Cox regression analyses revealed that the CRG score was an independent prognostic predictor for LGG patients. Subsequently, a highly accurate predictive model was established for facilitating the clinical application of the CRG score, showing good predictive ability and calibration. Additionally, crucial CRGs were further validated by qRT-PCR and WB. Conclusion: Collectively, we demonstrated a comprehensive overview of CRG profiles in LGG and established a novel risk model for LGG patients' therapy status and prognosis. Our findings highlight the potential clinical implications of CRGs, suggesting that cuproptosis may be the potential therapeutic target for patients with LGG.

Corrigendum: The risk of heart disease-related death among anaplastic astrocytoma patients after chemotherapy: A SEER population-based analysis.

[This corrects the article DOI: 10.3389/fonc.2022.870843.].

The Risk of Heart Disease-Related Death Among Anaplastic Astrocytoma Patients After Chemotherapy: A SEER Population-Based Analysis.

Background: Despite improved overall survival outcomes, chemotherapy has brought concerns for heart disease-related death (HDRD) among cancer patients. The effect of chemotherapy on the risk of HDRD in anaplastic astrocytoma (AA) patients remains unclear. Methods: We obtained 7,129 AA patients from the Surveillance, Epidemiology, and End Results (SEER) database from 1975 to 2016. Kaplan-Meier and Cox regression analysis were conducted to evaluate the effect of chemotherapy on the HDRD risk. Based on the competing risk model, we calculated the cumulative incidences of HDRD and non-HDRD and performed univariate and multivariate regression analyses. Then, a 1:1 propensity score matching (PSM) was used to improve the comparability between AA patients with and without chemotherapy. Landmark analysis at 216 and 314 months was employed to minimize immortal time bias. Results: AA patients with chemotherapy were at a lower HDRD risk compared to those patients without chemotherapy (adjusted HR=0.782, 95%CI=0.736-0.83, P<0.001). For competing risk regression analysis, the cumulative incidence of HDRD in non-chemotherapy exceeded HDRD in the chemotherapy group (P<0.001) and multivariable analysis showed a lower HDRD risk in AA patients with chemotherapy (adjusted SHR=0.574, 95%CI=0.331-0.991, P=0.046). In the PSM-after cohort, there were no significant association between chemotherapy and the increased HDRD risk (adjusted SHR=0.595, 95%CI=0.316-1.122, P=0.11). Landmark analysis showed that AA patients who received chemotherapy had better heart disease-specific survival than those in the non-chemotherapy group (P=0.007) at the follow-up time points of 216 months. No difference was found when the follow-up time was more than 216 months. Conclusion: AA patients with chemotherapy are associated with a lower risk of HDRD compared with those without chemotherapy. Our findings may help clinicians make a decision about the management of AA patients and provide new and important evidence for applying chemotherapy in AA patients as the first-line treatment. However, more research is needed to confirm these findings and investigate the correlation of the risk of HDRD with different chemotherapy drugs and doses.

Deciphering a Novel Necroptosis-Related miRNA Signature for Predicting the Prognosis of Clear Cell Renal Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common histological and devastating subtype of renal cell carcinoma. Necroptosis is a form of programmed cell death that causes prominent inflammatory responses. miRNAs play a significant role in cancer progression through necroptosis. However, the prognostic value of necroptosis-related miRNAs remains ambiguous. In this study, 39 necroptosis-related miRNAs (NRMs) were extracted and 17 differentially expressed NRMs between normal and tumor samples were identified using data form The Cancer Genome Atlas (TCGA). After applying univariate Cox proportional hazard regression analysis and LASSO Cox regression model, six necroptosis-related miRNA signatures were identified in the training cohort and their expression levels were verified by qRT-PCR. Using the expression levels of these miRNAs, all patients were divided into the high- and low-risk groups. Patients in the high-risk group showed poor overall survival (P < 0.0001). Time-dependent ROC curves confirmed the good performance of our signature. The results were verified in the testing cohort and the entire TCGA cohort. Univariate and multivariate Cox regression models demonstrated that the risk score was an independent prognostic factor. Additionally, a predictive nomogram with good performance was constructed to enhance the implementation of the constructed signature in a clinical setting. We then employed miRBD, miRTarBase, and TargetScan to predict the target genes of six necroptosis-related miRNAs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses indicated that 392 potential target genes were enriched in cell proliferation-related biological processes. Six miRNAs and 59 differentially expressed target genes were used to construct an miRNA-mRNA interaction network, and 11 hub genes were selected for survival and tumor infiltration analysis. Drug sensitivity analysis revealed potential drugs that may contribute to cancer management. Hence, necroptosis-related genes play an important role in cancer biology. We developed, for the first time, a necroptosis-related miRNA signature to predict ccRCC prognosis.

Effects of interleukin 1ß on long noncoding RNA and mRNA expression profiles of human synovial fluid derived mesenchymal stem cells.

Synovial fluid-derived mesenchymal stem cells (SFMSCs) play important regulatory roles in the physiological balance of the temporomandibular joint. Interleukin (IL)-1ß regulates the biological behavior of SFMSCs; however, the effects of IL-1ß on long noncoding RNA (lncRNA) and mRNA expression in SFMSCs in the temporomandibular joint are unclear. Here, we evaluated the lncRNA and mRNA expression profiles of IL-1ß-stimulated SFMSCs. Using microarrays, we identified 264 lncRNAs (203 upregulated, 61 downregulated) and 258 mRNAs (201 upregulated, 57 downregulated) that were differentially expressed after treatment with IL-1ß (fold changes ≥ 2, P < 0.05). Kyoto Encyclopedia of Genes and Genomes pathway analysis found that one of the most significantly enriched pathways was the NF-κB pathway. Five paired antisense lncRNAs and mRNAs, eight paired enhancer lncRNAs and mRNAs, and nine paired long intergenic noncoding RNAs and mRNAs were predicted to be co-expressed. A network constructed by the top 30 K-score genes was visualized and evaluated. We found a co-expression relationship between RP3-467K16.4 and IL8 and between LOC541472 and IL6, which are related to NF-κB pathway activation. Overall, our results provide important insights into changes in lncRNA and mRNA expression in IL-1ß-stimulated SFMSCs, which can facilitate the identification of potential therapeutic targets.