Ferroptosis-related lncRNA signature predicts prognosis and immunotherapy efficacy in cutaneous melanoma.

Ferroptosis-related lncRNAs are promising biomarkers for predicting the prognosis of many cancers. However, a ferroptosis-related signature to predict the prognosis of cutaneous melanoma (CM) has not been identified. The purpose of this study was to construct a ferroptosis-related lncRNA signature to predict prognosis and immunotherapy efficacy in CM. Ferroptosis-related differentially expressed genes (FDEGs) and lncRNAs (FDELs) were identified using TCGA, GTEx, and FerrDb datasets. We performed Cox and LASSO regressions to identify key FDELs, and constructed a risk score to stratify patients into high- and low-risk groups. The lncRNA signature was evaluated using the areas under the receiver operating characteristic curves (AUCs) and Kaplan-Meier analyses in the training, testing, and entire cohorts. Multivariate Cox regression analyses including the lncRNA signature and common clinicopathological characteristics were performed to identify independent predictors of overall survival (OS). A nomogram was developed for clinical use. We performed gene set enrichment analyses (GSEA) to identify significantly enriched pathways. Differences in the tumor microenvironment (TME) between the 2 groups were assessed using 7 algorithms. To predict the efficacy of immune checkpoint inhibitors (ICI), we analyzed the association between PD1 and CTLA4 expression and the risk score. Finally, differences in Tumor Mutational Burden (TMB) and molecular drugs Sensitivity between the 2 groups were performed. We identified 5 lncRNAs (AATBC, AC145423.2, LINC01871, AC125807.2, and AC245041.1) to construct the risk score. The AUC of the lncRNA signature was 0.743 in the training cohort and was validated in the testing and entire cohorts. Kaplan-Meier analyses revealed that the high-risk group had poorer prognosis. Multivariate Cox regression showed that the lncRNA signature was an independent predictor of OS with higher accuracy than traditional clinicopathological features. The 1-, 3-, and 5-year survival probabilities for CM patients were 92.7%, 57.2%, and 40.2% with an AUC of 0.804, indicating a good accuracy and reliability of the nomogram. GSEA showed that the high-risk group had lower ferroptosis and immune response. TME analyses confirmed that the high-risk group had lower immune cell infiltration (e.g., CD8+ T cells, CD4+ memory-activated T cells, and M1 macrophages) and lower immune functions (e.g., immune checkpoint activation). Low-risk patients whose disease expressed PD1 or CTLA4 were likely to respond better to ICIs. The analysis demonstrated that the TMB had significantly difference between low- and high- risk groups. Chemotherapy drugs, such as sorafenib, Imatinib, ABT.888 (Veliparib), Docetaxel, and Paclitaxel showed Significant differences in the estimated IC50 between the two risk groups. Our novel ferroptosis-related lncRNA signature was able to accurately predict the prognosis and ICI outcomes of CM patients. These ferroptosis-related lncRNAs might be potential biomarkers and therapeutic targets for CM.

Xu Y ，Chen Y ，Niu Z ，Yang Z ，Xing J ，Yin X ，Guo L ，Zhang Q ，Yang Y ，Han Y ... -  《Frontiers in Surgery》

A Novel Pyroptotic and Inflammatory Gene Signature Predicts the Prognosis of Cutaneous Melanoma and the Effect of Anticancer Therapies.

The purpose of this study was to construct a gene signature comprising genes related to both inflammation and pyroptosis (GRIPs) to predict the prognosis of patients with cutaneous melanoma patients and the efficacy of immunotherapy, chemotherapy, and targeted therapy in these patients. Gene expression profiles were collected from The Cancer Genome Atlas. Weighted gene co-expression network analysis was performed to identify GRIPs. Univariable Cox regression and Lasso regression further selected key prognostic genes. Multivariable Cox regression was used to construct a risk score, which stratified patients into high- and low-risk groups. Areas under the ROC curves (AUCs) were calculated, and Kaplan-Meier analyses were performed for the two groups, following validation in an external cohort from Gene Expression Omnibus (GEO). A nomogram including the GRIP signature and clinicopathological characteristics was developed for clinical use. Gene set enrichment analysis illustrated differentially enriched pathways. Differences in the tumor microenvironment (TME) between the two groups were assessed. The efficacies of immune checkpoint inhibitors (ICIs), chemotherapeutic agents, and targeted agents were predicted for both groups. Immunohistochemical analyses of the GRIPs between the normal and CM tissues were performed using the Human Protein Atlas data. The qRT-PCR experiments validated the expression of genes in CM cell lines, Hacat, and PIG1 cell lines. A total of 185 GRIPs were identified. A novel gene signature comprising eight GRIPs (TLR1, CCL8, EMP3, IFNGR2, CCL25, IL15, RTP4, and NLRP6) was constructed. The signature had AUCs of 0.714 and 0.659 for predicting 3-year overall survival (OS) in the TCGA entire and GEO validation cohorts, respectively. Kaplan-Meier analyses revealed that the high-risk group had a poorer prognosis. Multivariable Cox regression showed that the GRIP signature was an independent predictor of OS with higher accuracy than traditional clinicopathological features. The nomogram showed good accuracy and reliability in predicting 3-year OS (AUC = 0.810). GSEA and TME analyses showed that the high-risk group had lower levels of pyroptosis, inflammation, and immune response, such as lower levels of CD8+ T-cell infiltration, CD4+ memory-activated T-cell infiltration, and ICI. In addition, low-risk patients whose disease expressed PD-1 or CTLA-4 were likely to respond better to ICIs, and several chemotherapeutic and targeted agents. Immunohistochemical analysis confirmed the distinct expression of five out of the eight GRIPs between normal and CM tissues. Our novel 8-GRIP signature can accurately predict the prognosis of patients with CM and the efficacies of multiple anticancer therapies. These GRIPs might be potential prognostic biomarkers and therapeutic targets for CM.

Xu Y ，Chen Y ，Niu Z ，Xing J ，Yang Z ，Yin X ，Guo L ，Zhang Q ，Qiu H ，Han Y ... -  《Frontiers in Medicine》

Construction of a ferroptosis-related five-lncRNA signature for predicting prognosis and immune response in thyroid carcinoma.

Thyroid carcinoma (THCA) is the most common endocrine-related malignant tumor. Despite the good prognosis, some THCA patients may deteriorate into more aggressive diseases, leading to poor survival. This may be alleviated by developing a novel model to predict the risk of THCA, including recurrence and survival. Ferroptosis is an iron-dependent, oxidative, non-apoptotic form of cell death initially described in mammalian cells, and plays an important role in various cancers. To explore the potential prognostic value of ferroptosis in THCA, ferroptosis-related long non-coding RNAs (FRLs) were used to construct model for risk prediction of THCA. RNA-sequencing data of THCA patients and ferroptosis-related genes were downloaded from The Cancer Genome Atlas (TCGA) and FerrDb, respectively. A total of 502 patients with complete data were randomly separated into a training cohort and a validation cohort at the ratio of 2:1. The Pearson correlation coefficients were calculated to determine the correlation between ferroptosis-related genes (FRGs) and the corresponding lncRNAs, and those meeting the screening conditions were defined as FRLs. Gene Expression Omnibus (GEO) database and qRT-PCR were used to verify the expression level of FRLs in THCA tissues. Univariate and multivariate cox regression analysis were performed to construct a FRLs signature based on lowest Akaike information criterion (AIC) value in the training cohort, then further tested in the validation cohort and the entire cohort. Gene set enrichment analysis (GSEA) and functional enrichment analysis were used to analyze the biological functions and signal pathways related to differentially expressed genes between the high-risk and low-risk groups. Finally, the relative abundance of different tumor-infiltrating immune cells were calculated by CIBERSORT algorithm. The patients were divided into high-risk group and low-risk group based on a 5-FRLs signature (AC055720.2, DPP4-DT, AC012038.2, LINC02454 and LINC00900) in training cohort, validation cohort and entire cohort. Through Kaplan-Meier analysis and area under ROC curve (AUC) value, patients in the high-risk group exhibited worse prognosis than patients in the low-risk group. GEO database and qRT-PCR confirmed that LINC02454 and LINC00900 were up-regulated in THCA. Univariate and multivariate cox regression analyses showed that the risk score was an independent prognostic indicator. GSEA and functional enrichment analysis confirmed that immune-related pathways against cancer were significantly activated in the low-risk THCA patients. Further analysis showed that the immune cells such as plasma cells, T cells CD8 and macrophages M1, and the expression of immune checkpoint molecules, including PD-1, PD-L1, CTLA4, and LAG3, were remarkably higher in the low-risk group. Our study used the TCGA THCA dataset to construct a novel FRLs prognostic model which could precisely predict the prognosis of THCA patients. These FRLs potentially mediate anti-tumor immunity and serve as therapeutic targets for THCA, which provided the novel insight into treatment of THCA.

Qin Y ，Zhang D ，Zhang H ，Hou L ，Wang Z ，Yang L ，Zhang M ，Zhao G ，Yao Q ，Ling R ，Zhang J ... -  《Cancer Cell International》

Development and Validation of a Novel Ferroptosis-Related LncRNA Signature for Predicting Prognosis and the Immune Landscape Features in Uveal Melanoma.

Ferroptosis is a newly iron-dependent mode of programmed cell death that is involved in a variety of malignancies. But no research has shown a link between ferroptosis-related long non-coding RNAs (FRLs) and uveal melanoma (UM). We aimed to develop a predictive model for UM and explore its potential function in relation to immune cell infiltration. Identification of FRLs was performed using the Cancer Genome Atlas (TCGA) and FerrDb databases. To develop a prognostic FRLs signature, univariate Cox regression and least absolute shrinkage and selection operator (LASSO) were used in training cohort. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were used to assess the reliability of the risk model. The immunological functions of FRLs signature were determined using gene set enrichment analysis (GSEA). Immunological cell infiltration and immune treatment were studied using the ESTIMATE, CIBERSORT, and ssGSEA algorithms. Finally, in vitro assays were carried out to confirm the biological roles of FRLs with known primer sequences (LINC00963, PPP1R14B.AS1, and ZNF667.AS1). A five-genes novel FRLs signature was identified. The mean risk score generated by this signature was used to create two risk groups. The high-risk score UM patients had a lower overall survival rate. The area under the curve (AUC) of ROC and K-M analysis further validated the strong prediction capacity of the prognostic signature. Immune cells such as memory CD8 T cells, M1 macrophages, monocytes, and B cells showed a substantial difference between the two groups. GSEA enrichment results showed that the FRLs signature was linked to certain immune pathways. Moreover, UM patients with high-risk scores were highly susceptible to several chemotherapy drugs, such as cisplatin, imatinib, bortezomib, and pazopanib. Finally, the experimental validation confirmed that knockdown of three identified lncRNA (LINC00963, PPP1R14B.AS1, and ZNF667.AS1) suppressed the invasive ability of tumor cells in vitro. The five-FRLs (AC104129.1, AC136475.3, LINC00963, PPP1R14B.AS1, and ZNF667.AS1) signature has effects on clinical survival prediction and selection of immunotherapies for UM patients.

Ma X ，Yu S ，Zhao B ，Bai W ，Cui Y ，Ni J ，Lyu Q ，Zhao J ... -  《Frontiers in Immunology》

Identification of a Ferroptosis-Related Long Noncoding RNA Prognostic Signature and Its Predictive Ability to Immunotherapy in Hepatocellular Carcinoma.

Background: Immune checkpoint blockers (ICBs) are increasingly being used to treat patients with advanced hepatocellular carcinoma (HCC), but only a third of these patients are sensitive to ICBs. Emerging evidence suggests that ferroptosis could be a novel target for antitumor treatment, and combined treatment with ferroptosis inducers might enhance sensitivity to immunotherapy. However, there is a lack of information on the crosstalk between ferroptosis-related lncRNAs and anti-tumor immunity. Therefore, we aim to explore prognostic value of ferroptosis-related lncRNAs and clarify potential role in ICBs of HCC. Methods: We obtained mRNA and lncRNA expression data from two independent cohorts (TCGA and GEO database). Univariate Cox, the least absolute shrinkage and selection operator (Lasso) algorithm and multivariate Cox analysis were used to construct a lncRNA signature, which was evaluated using the area under the receiver operating characteristic curve (AUC) and Kaplan-Meier curves. Tumor-infiltrating cell (TIC) profiling and the tumor immune dysfunction and exclusion (TIDE) algorithm were used to validate the signature model and immunotherapy. Finally, we adopted RT-PCR assay to evaluate the differential expression of lncRNAs in HCC tissues in our hospital. Results: The ferroptosis-related lncRNA signature included five lncRNAs, most of which were positively correlated with clinical stage and grade. The signature could stratify patients into two risk groups, with the high-risk group associated with a shorter overall survival (OS, p < 0.05) in TCGA-LIHC and GSE76427. Besides, the AUCs of the 1-, 3-, and 5-years OS were 0.772, 0.707, and 0.666, respectively. Gene set enrichment analysis (GESA) of lncRNAs revealed enrichment of oncogenic and immune-related pathways. The TIC profiling indicated a close correlation between the signature and immune cells. Furthermore, the high-risk group had a better response to immunotherapy than low-risk group. RT-PCR demonstrated these five lncRNAs were upregulated in cancerous tissue than normal tissues. Conclusions: The ferroptosis-related lncRNA signature could accurately predict the OS of HCC patients and may serve as an independent clinical factor for patients' outcomes. Ferroptosis-related lncRNAs may remodel the tumor microenvironment (TME) and affect the anti-cancer ability of ICBs, and therefore, could potentially act as an indicator for the response to immunotherapy in HCC.

Wang L ，Ge X ，Zhang Z ，Ye Y ，Zhou Z ，Li M ，Yan H ，Wu L ，Bai Q ，Li J ，Zhu J ，Wang Y ... -  《Frontiers in Genetics》