Identification and validation of an individualized prognostic signature of lung squamous cell carcinoma based on ferroptosis-related genes

The Evaluation of Prognostic Value and Immune Characteristics of Ferroptosis-Related Genes in Lung Squamous Cell Carcinoma

Background  The purpose of our study was to construct a prognostic model based on ferroptosis-related gene signature to improve the prognosis prediction of lung squamous carcinoma (LUSC). Methods  The mRNA expression profiles and clinical data of LUSC patients were downloaded. LUSC-related essential differentially expressed genes were integrated for further analysis. Prognostic gene signatures were identified through random forest regression and univariate Cox regression analyses for constructing a prognostic model. Finally, in a preliminary experiment, we used the reverse transcription-quantitative polymerase chain reaction assay to verify the relationship between the expression of three prognostic gene features and ferroptosis. Results  Fifty-six ferroptosis-related essential genes were identified by using integrated analysis. Among these, three prognostic gene signatures (HELLS, POLR2H, and POLE2) were identified, which were positively affected by LUSC prognosis but negatively affected by immune cell infiltration. Significant overexpression of immune checkpoint genes occurred in the high-risk group. In preliminary experiments, we confirmed that the occurrence of ferroptosis can reduce three prognostic gene signature expression. Conclusions  The three ferroptosis-related genes could predict the LUSC prognostic risk of antitumor immunity.

Resveratrol Improves the Cytotoxic Effect of CD8+T Cells in the Tumor Microenvironment by Regulating HMMR/Ferroptosis in Lung Squamous Cell Carcinoma

Ferroptosis, an iron-dependent cell death process, is a potential therapeutic strategy for Lung squamous cell carcinoma (LUSC). Resveratrol (RES) is an anti-tumor polyphenol. However, whether and how RES treats LUSC is not yet known. This study aimed to investigate the effect of RES on LUSC and to explore its potential mechanism. This study used a combination of proteomics, bioinformatics, clinical samples, and cell experiments to study the interaction between HMMR and the ferroptosis signaling pathway and investigate the role of RES in regulating tumor immune microenvironment and anti-tumor by cytotoxic CD8 +T cells in LUSC. Ferroptosis signaling pathway and HMMR were involved in the LUSC tumor immune microenvironment and correlated with worse prognosis of LUSC patients. RES+H520 cells induced a higher level of ferroptosis and MDA, mainly by reducing the expression of GPX4 and SLC7A11, inducing the expression of ACSL4 and TFRC. HMMR, GSH, and SOD contents were lower observed than in H520 cells. When HMMR was expressed, SLC7A11 was also highly expressed in LUSC, and there was an interaction between HMMR expression and SLC7A11. In addition, RES increased the TNF-α, IFN-γ, IL-12, and IL-2 expression and increased the cytotoxic effects of CD8 +T cells expressions in LUSC. Resveratrol regulates SLC7A11-HMMR interaction, activates ferroptosis, enhances the cytotoxic effect of CD8 +T cells, and regulates the tumor immune microenvironment. Based on the pathogenesis of LUSC and the clinical efficacy of RES, this study explored the influence of RES on LUSC, clarified its biological effects, and further provided cell biological basis for the clinical application of RES, which could guide clinical combination and personalized medicine, improve the response rate of immunotherapy and benefit more patients with LUSC.

Construction and Validation of Prognosis Nomogram for Metastatic Lung Squamous Cell Carcinoma: A Population-Based Study

Purpose: This study aimed to establish a nomogram to predict overall survival in lung squamous cell carcinoma patients with metastasis for clinical decision-making. Methods: We investigated lung squamous cell carcinoma patients diagnosed with stage M1 in the Surveillance, Epidemiology, and Final Results database between 2010 and 2015. They were divided into training cohort and validation cohort. In the training cohort, statistically significant prognostic factors were identified using univariate and multivariate Cox regression analysis, and an individualized nomogram model was developed. The model was evaluated by C-index, area under the curve, calibration plot, decision curve analysis, and risk group stratification. Results: In total, 9910 patients were included in our study, including 6937 in the training cohort and 2937 in the validation cohort. Factors containing age, T stage, N stage, bone metastasis, brain metastasis, liver metastasis, surgery, chemotherapy, and radiotherapy were independent prognostic factors for overall survival and were used in the construction of the nomogram. The C-index in the training cohort and validation cohort were 0.711 (95% confidenc interval: 0.705-0.717) and 0.707 (95% confidenc interval: 0.697-0.717), respectively. The time-dependent area under the curve of both groups was higher than 0.7 within 5 years. Calibration plots indicated that the nomogram-predicted survival was consistent with the recorded 6-month, 1-year, and 2-year prognoses. Furthermore, decision curve analysis revealed that the nomogram was clinically useful and had a better discriminative ability to recognize patients at high risk than the TNM criteria-based tumor staging. And then we developed an overall survival risk classification system based on the nomogram total points for each patient, which divided all patients into a high-risk group and a low-risk group. Finally, we implemented this nomogram in a free online tool. Conclusion: We constructed a nomogram and a corresponding risk classification system predicting the overall survival of lung squamous cell carcinoma patients with metastasis. These tools can assist in patients’ counseling and guide treatment decision-making.

A Novel Prognosis Signature Based on Ferroptosis-Related Gene DNA Methylation Data for Lung Squamous Cell Carcinoma

Ferroptosis-related genes regulating an iron- and lipid reactive oxygen species (ROS)-dependent form of programmed cell death suggest critical roles for ferroptosis in cancers. However, the prognostic value of ferroptosis-related epigenetic features such as DNA methylation in lung squamous cell carcinoma (LUSC) needs to be studied. Ferroptosis-related genes are collected from the FerrDb database, and the methylation data of these related genes in LUSC methylation data downloaded from the TCGA are retrieved. The DNA methylation data (362 LUSC samples) were analyzed to screen prognostic ferroptosis-related methylation sites. After patients with complete overall survival (OS) information were randomly separated into training cohort (n = 200) and validation cohort (n = 162), the least absolute shrinkage and selection operator (LASSO) and the Cox regression were used to establish and validate the prognostic signature. The time-dependent receiver operating characteristic (ROC) and Kaplan–Meier survival curve analyses, Harrell's concordance index (C-index), calibration analysis, and decision curve analysis (DCA) were performed to evaluate the risk signature and related nomogram. A series of other bioinformatics approaches such as mexpress, cbioportal, maftools, string, metascape, TIMER, and Kaplan–Meier survival curve analysis were also used to determine the methylation, mutation status, protein interaction network or functional enrichment, effects on immune cell infiltration, or expression level prognosis of those signature-related genes. A total of 137 DNA methylation sites were identified as prognostic predictors corresponding to 109 ferroptosis-related genes (FRGs). The methylation signature containing 31 methylation sites proved to be superior predictive efficiency in predicting the 1-, 3-, 5-, and 10-year OS. 8 out of 28 signature-related genes were significantly related to OS time or OS state in patients with LUSC. In addition, DUSP1, ZFN36, and ALOX5 methylation status also correlated with pathological M and ALOX5 methylation correlated with pathological N. The prognostic prediction efficiency of T, N, M, and the stage was inferior to that of the DNA methylation signature. LUSC patients in the high-risk group own a significantly larger number of variants of FRGs than those in the low-risk group. In addition, negative or positive correlation patterns were presented among the different infiltrating immune cells with risk scores or signature-related genes in patients with LUSC. The expression level of 15 signature-related genes showed a significant relationship with OS of LUSC patients. A novel prognostic nomogram survival model containing 4 factors including age, pathologic T, stage, and risk group was constructed and validated, AndC-index, decision curve analysis (DCA), and calibration analysis demonstrated its excellent predictive performance. The FRG DNA methylation data-based prognostic model acts as a powerful prognostic prediction indicator in LUSC patients and is advantageous over the traditional model based on T, N, M, and stage.

Comprehensive analysis of the endoplasmic reticulum stress-related long non-coding RNA in bladder cancer

Background

Bladder cancer is ranked the second most frequent tumor among urological malignancies. The research strived to establish a prognostic model based on endoplasmic reticulum stress (ERS)-related long non-coding RNA (lncRNA) in bladder cancer.

Methods

We extracted the ERS-related genes from the published research and bladder cancer data from the Cancer Genome Atlas database. ERS-related lncRNAs with prognostic significance were screened by univariate Cox regression, least absolute shrinkage and selection operator regression analysis and Kaplan-Meier method. Multivariate Cox analysis was leveraged to establish the risk score model. Moreover, an independent dataset, GSE31684, was used to validate the model’s efficacy. The nomogram was constructed based on the risk score and clinical variables. Furthermore, the biological functions, gene mutations, and immune landscape were investigated to uncover the underlying mechanisms of the ERS-related signature. Finally, we employed external datasets (GSE55433 and GSE89006) and qRT-PCR to investigate the expression profile of these lncRNAs in bladder cancer tissues and cells.

Results

Six ERS-related lncRNAs were identified to be closely coupled with patients’ prognosis. On this foundation, a risk score model was created to generate the risk score for each patient. The ERS-related risk score was shown to be an independent prognostic factor. And the results of GSE31684 dataset also supported this conclusion. Then, a nomogram was constructed based on risk scores and clinical characteristics, and proven to have excellent predictive value. Moreover, the gene function analysis demonstrated that ERS-related lncRNAs were closely linked to fatty extracellular matrix, cytokines, cell adhesion, and tumor pathways. Further analysis revealed the association of the 6-lncRNAs signature with gene mutations and immunity in bladder cancer. Finally, the external datasets and qRT-PCR verified high expressions of the ERS-related lncRNAs in bladder cancer tissues and cells.

Conclusions

Overall, our findings indicated that ERS-related lncRNAs, which may affect tumor pathogenesis in a number of ways, might be exploited to assess the prognosis of bladder cancer patients.

A nomogram based on A-to-I RNA editing predicting overall survival of patients with lung squamous carcinoma

Background

Adenosine-to-inosine RNA editing (ATIRE) is characterized as non-mutational epigenetic reprogramming hallmark of cancer, while little is known about its predictive role in cancer survival.

Methods

To explore survival-related ATIRE events in lung squamous cell carcinoma (LUSC), ATIRE profile, gene expression data, and corresponding clinical information of LUSC patients were downloaded from the TCGA database. Patients were randomly divided into a training (n = 134) and validation cohort (n = 94). Cox proportional hazards regression followed by least absolute shrinkage and selection operator algorithm were performed to identify survival-related ATIRE sites and to generate ATIRE risk score. Then a nomogram was constructed to predict overall survival (OS) of LUSC patients. The correlation of ATIRE level and host gene expression and ATIREs’ effect on transcriptome expression were analyzed.

Results

Seven ATIRE sites that were TMEM120B chr12:122215052A > I, HMOX2 chr16:4533713A > I, CALCOCO2 chr17:46941503A > I, LONP2 chr16:48388244A > I, ZNF440 chr19:11945758A > I, CLCC1 chr1:109474650A > I, and CHMP3 chr2:86754288A > I were identified to generate the risk score, of which high levers were significantly associated with worse OS and progression-free survival in both the training and validation sets. High risk-score was also associated with advanced T stages and worse clinical stages. The nomogram performed well in predicting OS probability of LUSC. Moreover, the editing of ATIRE sites exerted a significant association with expression of host genes and affected several cancer-related pathways.

Conclusions

This is the first comprehensive study to analyze the role of ATIRE events in predicting LUSC survival. The AITRE-based model might serve as a novel tool for LUSC survival prediction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09773-0.