Background: Necroptosis has been identified recently as a newly recognized programmed cell death that has an impact on tumor progression and prognosis, although the necroptosis-related gene (NRGs) potential prognostic value in skin cutaneous melanoma (SKCM) has not been identified. The aim of this study was to construct a prognostic model of SKCM through NRGs in order to help SKCM patients obtain precise clinical treatment strategies. Methods: RNA sequencing data collected from The Cancer Genome Atlas (TCGA) were used to identify differentially expressed and prognostic NRGs in SKCM. Depending on 10 NRGs via the univariate Cox regression analysis usage and LASSO algorithm, the prognostic risk model had been built. It was further validated by the Gene Expression Omnibus (GEO) database. The prognostic model performance had been assessed using receiver operating characteristic (ROC) curves. We evaluated the predictive power of the prognostic model for tumor microenvironment (TME) and immunotherapy response. Results: We constructed a prognostic model based on 10 NRGs (FASLG, TLR3, ZBP1, TNFRSF1B, USP22, PLK1, GATA3, EGFR, TARDBP, and TNFRSF21) and classified patients into two high- and low-risk groups based on risk scores. The risk score was considered a predictive factor in the two risk groups regarding the Cox regression analysis. A predictive nomogram had been built for providing a more beneficial prognostic indicator for the clinic. Functional enrichment analysis showed significant enrichment of immune-related signaling pathways, a higher degree of immune cell infiltration in the low-risk group than in the high-risk group, a negative correlation between risk scores and most immune checkpoint inhibitors (ICIs), anticancer immunity steps, and a more sensitive response to immunotherapy in the low-risk group. Conclusions: This risk score signature could be applied to assess the prognosis and classify low- and high-risk SKCM patients and help make the immunotherapeutic strategy decision.

/pdf/a-novel-necroptosis-related-gene-signature-in-skin-cutaneous-3iflotud.pdf

A Novel Necroptosis-Related Gene Signature in Skin Cutaneous Melanoma Prognosis and Tumor Microenvironment

Objective: Accumulated evidence highlights the biological significance of oxidative stress in tumorigenicity and progression of colorectal cancer (CRC). Our study aimed to establish a reliable oxidative stress-related signature to predict patients’ clinical outcomes and therapeutic responses. Methods: Transcriptome profiles and clinical features of CRC patients were retrospectively analyzed from public datasets. LASSO analysis was used to construct an oxidative stress-related signature to predict overall survival, disease-free survival, disease-specific survival, and progression-free survival. Additionally, antitumor immunity, drug sensitivity, signaling pathways, and molecular subtypes were analyzed between different risk subsets through TIP, CIBERSORT, oncoPredict, etc. approaches. The genes in the signature were experimentally verified in the human colorectal mucosal cell line (FHC) along with CRC cell lines (SW-480 and HCT-116) through RT-qPCR or Western blot. Results: An oxidative stress-related signature was established, composed of ACOX1, CPT2, NAT2, NRG1, PPARGC1A, CDKN2A, CRYAB, NGFR, and UCN. The signature displayed an excellent capacity for survival prediction and was linked to worse clinicopathological features. Moreover, the signature correlated with antitumor immunity, drug sensitivity, and CRC-related pathways. Among molecular subtypes, the CSC subtype had the highest risk score. Experiments demonstrated that CDKN2A and UCN were up-regulated and ACOX1, CPT2, NAT2, NRG1, PPARGC1A, CRYAB, and NGFR were down-regulated in CRC than normal cells. In H2O2-induced CRC cells, their expression was notably altered. Conclusion: Altogether, our findings constructed an oxidative stress-related signature that can predict survival outcomes and therapeutic response in CRC patients, thus potentially assisting prognosis prediction and adjuvant therapy decisions.

/pdf/establishment-and-external-verification-of-an-oxidative-h256b2fb.pdf

Establishment and external verification of an oxidative stress-related gene signature to predict clinical outcomes and therapeutic responses of colorectal cancer

Melanoma is the most dangerous form of skin cancer because of its high metastatic potential. Potential-N6-methyladenosine (m6A)-related long noncoding RNAs (pMRlncRNAs) play a vital role in malignancy. The identification of prognostic-related pMRlncRNAs and development of risk signatures could improve the prognosis and promote the precise treatment of melanoma.Gene expression and relevant clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Prognostic-related pMRlncRNAs were selected using univariate Cox regression analysis. Patients with melanoma were classified into different subtypes using the "ConsensusClusterPlus" package, and the ESTIMATE algorithm was applied to depict their immune landscape. A pMRlncRNA risk signature was developed using least absolute shrinkage and selection operator regression analysis and verified using survival analysis and receiver operating characteristic curves. Gene set enrichment analysis (GSEA) was used to investigate the underlying biological pathways. The relationships between risk score and clinicopathological characteristics, as well as programmed cell death-ligand 1 (PD-L1) expression level, were investigated. A nomogram with calibration curves was established to comprehensively predict the outcome of melanoma.Fifteen pMRlncRNAs were significantly associated with overall survival (OS). Two cluster subtypes were identified by consensus clustering. Patients in cluster 2 were associated with better OS, higher PD-L1 expression level, lower T stage, and higher ESTIMATEScore, ImmuneScore, and StromalScore than those in cluster 1. There were differences in immune cell infiltration between the 2 clusters. Ten pMRlncRNAs with prognostic value were selected to develop a risk signature, that functioned as an independent prognostic factor for melanoma. Patients with low-risk scores had a better prognosis in general. The area under the curve (AUC) value (0.720), as well as 1-, 3-, and 5-year calibration curves, revealed that the risk signature has suitable predictive power for prognosis. GSEA revealed 10 pathways that might play important roles in melanoma. Moreover, patients with high-risk scores were associated with advanced T stage, cluster 1, lower ImmuneScore, and higher PD-L1 expression level.We developed a novel 10-pMRlncRNA risk signature that could elucidate the crucial role of pMRlncRNAs in the immune landscape of melanoma and predict prognosis. 

Genome-wide screening and immune landscape suggest a potential-m6A-related lncRNA risk signature for predicting prognosis of melanoma

Objective Mitochondrial dysfunction and oxidative stress are known to involved in tumor occurrence and progression. This study aimed to explore the molecular subtypes of lower-grade gliomas (LGGs) based on oxidative stress-related and mitochondrial-related genes (OMRGs) and construct a prognostic model for predicting prognosis and therapeutic response in LGG patients. Methods A total of 223 OMRGs were identified by the overlap of oxidative stress-related genes (ORGs) and mitochondrial-related genes (MRGs). Using consensus clustering analysis, we identified molecular subtypes of LGG samples from TCGA database and confirmed the differentially expressed genes (DEGs) between clusters. We constructed a risk score model using LASSO regression and analyzed the immune-related profiles and drug sensitivity of different risk groups. The prognostic role of the risk score was confirmed using Cox regression and Kaplan-Meier curves, and a nomogram model was constructed to predict OS rates. We validated the prognostic role of OMRG-related risk score in three external datasets. Quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) staining confirmed the expression of selected genes. Furthermore, wound healing and transwell assays were performed to confirm the gene function in glioma. Results We identified two OMRG-related clusters and cluster 1 was significantly associated with poor outcomes (P<0.001). The mutant frequencies of IDH were significantly lower in cluster 1 (P<0.05). We found that the OMRG-related risk scores were significantly correlated to the levels of immune infiltration and immune checkpoint expression. High-risk samples were more sensitive to most chemotherapeutic agents. We identified the prognostic role of OMRG-related risk score in LGG patients (HR=2.665, 95%CI=1.626-4.369, P<0.001) and observed that patients with high-risk scores were significantly associated with poor prognosis (P<0.001). We validated our findings in three external datasets. The results of qRT-PCR and IHC staining verified the expression levels of the selected genes. The functional experiments showed a significant decrease in the migration of glioma after knockdown of SCNN1B. Conclusion We identified two molecular subtypes and constructed a prognostic model, which provided a novel insight into the potential biological function and prognostic significance of mitochondrial dysfunction and oxidative stress in LGG. Our study might help in the development of more precise treatments for gliomas.

/pdf/identification-of-heterogeneous-subtypes-and-a-prognostic-8g09lv8h.pdf

Identification of heterogeneous subtypes and a prognostic model for gliomas based on mitochondrial dysfunction and oxidative stress-related genes

(1) Background: Uveal malignant melanoma is the most common adult eye cancer and presents metabolic reprogramming that affects the tumoral microenvironment by altering the redox balance and producing oncometabolites. (2) Methods: The study prospectively evaluated patients undergoing enucleation surgery or stereotactic radiotherapy for uveal melanoma by following systemic oxidative-stress redox markers serum lipid peroxides, total albumin groups and total antioxidant levels (3) Results: Serum antioxidants and lipid peroxides were elevated from pre-treatment to longer-term follow-up. Antioxidants inversely correlated to lipid peroxides: higher in stereotactic radiosurgery patients pre/6/12/18 months post-treatment (p = 0.001–0.049) versus higher lipid peroxides in enucleation surgery patients pre/after/6 months post-treatment (p = 0.004–0.010). An increased variance in serum antioxidants was observed for enucleation surgery patients (p < 0.001), however enucleation did not increase mean serum antioxidants or albumin thiols; only lipid peroxides were increased post-enucleation (p < 0.001) and at 6-month follow-up (p = 0.029). Mean albumin thiols were increased for 18- and 24-month follow-ups (p = 0.017–0.022). Males who had enucleation surgery presented higher variance in serum determinations and overall higher lipid peroxides values pre/post-treatment and at the 18-month follow-up. (4) Conclusions: Initial oxidative stress-inducing events of surgical enucleation or stereotactic radiotherapy for uveal melanoma are followed by a longer-term inflammatory cascade gradually subsiding at later follow-ups.

/pdf/the-effects-of-oncological-treatment-on-redox-balance-in-vkv6esp8.pdf

The Effects of Oncological Treatment on Redox Balance in Patients with Uveal Melanoma

Background Oxidative stress (OS) is key to various diseases and is implicated in cancer progression and oncogenesis. However, the potential diagnostic value of OS-related genes in skin cutaneous melanoma (SKCM) remains unclear. Methods We used data of RNA sequencing from 471 tumor tissues and one healthy tissue acquired from The Cancer Genome Atlas (TCGA)-SKCM cohort. The Genome Tissue Expression database was used to acquire transcriptome data from 812 healthy samples. OS-related genes that were differentially expressed between SKCM and healthy samples were investigated and 16 prognosis-associated OS genes were identified. The prognostic risk model was built using univariate and Cox multivariate regressions. The prognostic value of the hub genes was validated in the GSE65904 cohort, which included 214 SKCM patients. Results The overall survival rate of SKCM patients in the high-risk group was decreased compared to the low-risk group. In both TCGA and GSE65904 cohorts, the ROC curves suggested that our prognostic risk model was more accurate than other clinicopathological characteristics to diagnose SKCM. Moreover, risk score and nomograms associated with the expression of hub genes were developed. These presented reiterated our prognostic risk model. Altogether, this study provides novel insights with regards to the pathogenesis of SKCM. The 16 hub genes identified may help in SKCM prognosis and individualized clinical treatment.

Development and validation of an oxidative stress-associated prognostic risk model for melanoma.

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Development and validation of an oxidative stress-associated prognostic risk model for melanoma.