Project description:BackgroundPyroptosis is a newly found form of programmed cell death, accompanied by inflammatory response as well as immune response. Here, the specific function and prognosis predictive of pyroptosis-related genes (PRGs) were systematically explored in lung adenocarcinoma (LUAD).MethodsThe gene expression data and corresponding clinical information of LUAD patients were obtained from The Cancer Genome Atlas (TCGA), and the expression level of PRGs was identified between normal and tumor tissues. Furthermore, univariate Cox proportional hazards regression was conducted to filter the PRGs related to overall survival, and least absolute shrinkage and selection operator (LASSO) regression was subsequent employed to establish the PRGs risk model. Besides, the correlation of risk score with patients' clinical features, tumor mutational burden (TMB) as well as tumor microenvironment (TME) was also investigated.ResultsA total of 5 PRGs (NLRC4, NLRP1, NLRP3, NOD1, PLCG1, and BAK1) was used to establish the risk prognostic model. According the median value of risk score, all the patients were classified into low- and high-risk score group. Kaplan-Meier analysis indicted that the LUAD patients in low-risk group exhibited a better survival outcome compared the patients in high-risk group (P<0.001). After adjusting for age, gender, and clinical stage, the risk score was also considered as and independent risk factor affecting the overall survival of LUAD patients (HR =2.949, 95% CI: 1.762-4.937). Moreover, low-risk score group exhibited a higher Immune score and lower Tumor purity compared with high-risk score group. ssGSEA results proved that the enrichment scores of most immune cells and immune related signal pathway in low-risk score group was significant higher than that in high-risk score group. In addition, the PRGs risk score was also positive correlated with TMB in LUAD tissues.ConclusionsIn this study, a novel prognostic model based on PRGs was constructed and used to predict the survival outcome of LUAD patients. In addition, the PRGs risk signature was also associated with TMB and anti-tumor immune environment. The induction of pyroptosis inside tumors might be considered a potential strategy in cancer treatments.
Project description:The role of reactive oxygen species (ROS) is critical in the emergence and progression of lung adenocarcinoma (LUAD), affecting cell survival, proliferation, angiogenesis, and metastasis. Further investigations are needed to elucidate these effects' precise pathways and devise therapeutic approaches targeting ROS. Moreover, the expression pattern and clinical significance of the ROS-related genes in LUAD remain elusive. Through comprehensive analysis incorporating 1494 LUAD cases from The Cancer Genome Atlas, six Gene Expression Omnibus series, and a Chinese LUAD cohort, we identified a ROS-related signature with substantial predictive value in various LUAD patient cohorts. The ROS-related signature has demonstrated a significant negative relationship with antitumor immunity and dendritic cell maturation and activation. Moreover, The ROS-related signature showed predictive value on immunotherapy outcomes across multiple types of solid tumors, including LUAD. These findings reinforce the ROS-related signature as a predictive tool for LUAD and provide new insights into its link with antitumor immunity and immunotherapy efficacy. These results have implications for refining clinical assessments and tailoring immunotherapeutic strategies for patients with LUAD.
Project description:As a novel form of regulated cell death (RCD), disulfidptosis offering a significant opportunity in better understanding of tumor pathogenesis and therapeutic strategies. Long non-coding RNAs (lncRNAs) regulate the biology functions of tumor cells by engaging with a range of targets. However, the prognostic value of disulfidptosis-related lncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains unclear. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRlncRNAs. RNA-seq data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Subsequently, a prognostic model based on DRlncRNAs was constructed using LASSO and COX regression analysis. Patients were stratified into high- and low-risk groups based on their risk scores. Differences between the high-risk and low-risk groups were investigated in terms of overall survival (OS), functional enrichment, tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, the role of lncRNA GSEC in LUAD was validated through in vitro experiments. Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells. Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD.
Project description:Mounting evidence has found that tumor microenvironment (TME) plays an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of tumor microenvironment-related genes in immunotherapy and clinical outcomes remain unclear. In this study, 6 TME-related genes (PLK1, LDHA, FURIN, FSCN1, RAB27B, and MS4A1) were identified to construct the prognostic model. The established risk scores were able to predict outcomes at 1, 3, and 5 years with greater accuracy than previously known models. Moreover, the risk score was closely associated with immune cell infiltration and the immunoregulatory genes including T cell exhaustion markers. In conclusion, the TME risk score can function as an independent prognostic biomarker and a predictor for evaluating immunotherapy response in LUAD patients, which provides recommendations for improving patients' response to immunotherapy and promoting personalized tumor immunotherapy in the future.
Project description:Kidney renal clear cell carcinoma (KIRC) is one of the most prevalent primary malignancies with high heterogeneity in the urological system. Growing evidence implies that lactate is a significant carbon source for cell metabolism and plays a vital role in tumor development, maintenance, and therapeutic response. However, the global influence of lactate-related genes (LRGs) on prognostic significance, tumor microenvironment characteristics, and therapeutic response has not been comprehensively elucidated in patients with KIRC. In the present study, we collected RNA sequencing and clinical data of KIRC from The Cancer Genome Atlas (TCGA), E-MTAB-1980, and GSE22541 cohorts. Unsupervised clustering of 17 differentially expressed LRG profiles divided the samples into three clusters with distinct immune characteristics. Three genes (FBP1, HADH, and TYMP) were then identified to construct a lactate-related prognostic signature (LRPS) using the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses. The novel signature exhibited excellent robustness and predictive ability for the overall survival of patients. In addition, the constructed nomogram based on the LRPS-based risk scores and clinical factors (age, gender, tumor grade, and stage) showed a robust predictive performance. Furthermore, patients classified by risk scores had distinguishable immune status, tumor mutation burden, response to immunotherapy, and sensitivity to drugs. In conclusion, we developed an LRPS for KIRC that was closely related to the immune landscape and therapeutic response. This LRPS may guide clinicians to make more precise and personalized treatment decisions for KIRC patients.
Project description:Ferroptosis is a newly discovered, iron-dependent, nonapoptotic form of programmed cell death that plays an important role in the development of lung adenocarcinoma (LUAD). In this study, ferroptosis-related genes (FRGs) were identified from the FerrDb dataset, and the mRNA expression profiles and corresponding clinical data of LUAD patients were downloaded from the University of California, Santa Cruz (UCSC) databases. Data from LUAD patients from the Gene Expression Omnibus (GEO) dataset were used as the verification set. Cox and Lasso regression analyses were used to screen the FRGs with prognostic value, and six prognostic-related FRGs were selected to construct prognostic risk score signatures. Immunohistochemistry was utilized to manifest the differential expression of six FRGs in tumor and normal tissues at the protein level. Functional enrichment analysis indicated that FRGs were mainly enriched in ferroptosis-related pathways. Patients were divided into high- and low-risk groups based on the median risk score. The Kaplan-Meier survival curves confirmed that patients with a high score had significantly worse overall survival. Receiver operating characteristic (ROC) curves proved that the prognostic signature has good sensitivity and specificity for predicting the prognosis of LUAD patients. Nomogram analysis showed that the prognostic signature has potential independent prognostic value. Moreover, the prognostic signature has been shown to be significantly associated with some clinical features (T stage, N stage, tumor stage, and survival status) as well as many immune-activity-related genes and immune-checkpoint-related genes. In conclusion, we constructed a prognostic signature consisting of six FGRs, which can provide a reference for predicting the prognosis of LUAD patients.
Project description:Background: 7-Methylguanosine (m7G) is an important posttranscriptional modification that regulates gene expression and is involved in tumorigenesis and development. Tumor microenvironment has been proven to be highly involved in tumor progression and prognosis. However, how m7G-associated genes affect the tumor microenvironment of patients with lung adenocarcinoma (LUAD) remains to be further clarified. Methods: The genetic alterations of m7G-associated genes and their associations with the prognosis and tumor microenvironment in LUAD patients were systemically analyzed. An m7G-Riskscore was established and analyzed for its performance in disease prognosis and association with patient response to immunotherapy. Expression of the model genes at the protein level was investigated through ex vivo experiments. A nomogram was finally obtained based on the m7G-Riskscore and several significant clinical pathological features. Results: m7G-Associated genes were obtained from five LUAD datasets from The Cancer Genome Atlas and Gene Expression Omnibus databases, and their expression pattern was determined. Based on the m7G-associated genes, three LUAD clusters were defined. The differentially expressed genes from the three clusters were screened and used to further divide the LUAD patients into two gene clusters. It was demonstrated that the alterations of m7G-associated genes were associated with the clinical pathological features, prognosis, and tumor immune infiltration in LUAD patients. An m7G-Riskscore including CAND1, RRM2, and SLC2A1 was obtained with robust and accurate prognostic performance. WB and cell immunofluorescence also showed significant dysregulation of CAND1, RRM2, and SLC2A1 in LUAD. In addition, a nomogram was established to improve the clinical feasibility of the m7G-Riskscore. Correlation analysis revealed that patients with a lower m7G-Riskscore had higher immune and stromal scores, responded well to chemotherapeutics and multiple targeted drugs, and survived longer. Patients with a higher m7G-Riskscore tended to suffer from a higher tumor mutation burden. Furthermore, the m7G-Riskscore exhibited significant associations with immune cell infiltration and cancer stemness. Conclusion: This study systemically analyzed m7G-associated genes and identified their potential role in tumor microenvironment and prognosis in patients with LUAD. The findings of the present study may help better understand LUAD from the m7G perspective and also provide a new thought toward the prognosis and treatment of LUAD.
Project description:Because of immunotherapy failure in lung adenocarcinoma, we have tried to find new potential biomarkers for differentiating different tumor subtypes and predicting prognosis. We identified two subtypes based on tumor microenvironment-related genes in this study. We used seven methods to analyze the immune cell infiltration between subgroups. Further analysis of tumor mutation load and immune checkpoint expression among different subgroups was performed. The least absolute shrinkage and selection operator Cox regression was applied for further selection. The selected genes were used to construct a prognostic 14-gene signature for LUAD. Next, a survival analysis and time-dependent receiver operating characteristics were performed to verify and evaluate the model. Gene set enrichment analyses and immune analysis in risk groups was also performed. According to the expression of genes related to the tumor microenvironment, lung adenocarcinoma can be divided into cold tumors and hot tumors. The signature we built was able to predict prognosis more accurately than previously known models. The signature-based tumor microenvironment provides further insight into the prediction of lung adenocarcinoma prognosis and may guide individualized treatment.
Project description:Lactic acid, once considered as an endpoint or a waste metabolite of glycolysis, has emerged as a major regulator of cancer development, maintenance, and progression. However, studies about lactic acid metabolism-related genes (LRGs) in lung adenocarcinoma (LUAD) remain unclear. Two distinct molecular subtypes were identified on basis of 24 LRGs and found the significant enrichment of subtype A in metabolism-related pathways and had better overall survival (OS). Subsequently, a prognostic signature based on 5 OS-related LRGs was generated using Lasso Cox hazards regression analysis in TCGA dataset and was validated in two external cohorts. Then, a highly accurate nomogram was cosntructed to improve the clinical application of the LRG_score. By further analyzing the LRG_score, higher immune score and lower stromal score were found in the low LRG_score group, which presented a better prognosis. Patients with low LRG_score also exhibited lower somatic mutation rate, tumor mutation burden (TMB), and cancer stem cell (CSC) index. Three more independent cohorts (GSE126044: anti-PD-1, GSE135222: anti-PD-1, and IMvigor210: anti-PD-L1) were analyzed, and the results showed that patients in the low LRG_score category were more responsive to anti-PD-1/PD-L1 medication and had longer survival times. It was also determined that gefitinib, etoposide, erlotinib, and gemcitabine were more sensitive to the low LRG_score group. Finally, we validated the stability and reliability of LRG_score in cell lines, clinical tissue samples and HPA databases. Overall, the LRG_score may improve prognostic information and provide directions for current research on drug treatment strategies for LUAD patients.