Identification of a Pyroptosis-Related Gene Signature for Predicting the Immune Status and Prognosis in Lung Adenocarcinoma

ASIC1a regulates airway epithelial cell pyroptosis in acute lung injury by NLRP3-Caspase1-GSDMD pathway

BACKGROUND

Acidosis is the most common complication that seriously affects the prognosis of acute respiratory distress syndrome (ARDS). Acid-sensitive ion channel 1a (ASIC1a) is activated in acidic environments to regulate inflammatory process. However, the role of ASIC1a in ARDS is unclear.

METHODS

In this study, we examined the expression of ASIC1a in airway epithelial cells in an acidic environment. We then investigated whether blocking ASIC1a could inhibit pyroptosis of airway epithelial cells and the molecular mechanism. In the mouse acute lung injury (ALI) model, we observed the changes of lung histopathology, arterial blood gas and pyroptosis related indexes after ASIC1a inhibition. Bronchoalveolar lavage fluid (BALF) from patients with ARDS were collected to explore the expression level of ASIC1a in ARDS patients.

RESULTS

Inhibiting ASIC1a can reduce the airway epithelial cell pyroptosis induced by an extracellular acidic environment. ASIC1a can bind to PRKACA, and silencing ASIC1a and PRKACA can inhibit the occurrence of pyroptosis in airway epithelial cells. Compared with control group, arterial blood pH and PaO2 in ALI group were significantly reduced. The inflammation in the lungs is more intense, and the mRNA and protein of NLRP3, Caspase1 and GSDMD were increased, while ASIC1a specific blocker psalmotoxin-1 alleviated this phenomenon. The expression of ASIC1a in BALF of ARDS patients was significantly increased, especially in non-survival group.

CONCLUSION

Acidic micro-environment can induce the increased expression of ASIC1a, and inhibition of ASIC1a can alleviate the inflammation and airway epithelial cell pyroptosis in ARDS. ASIC1a may be a new target for the treatment of ARDS.

Building endoplasmic reticulum stress-related LncRNAs signatures of lung adenocarcinoma

BACKGROUND

Endoplasmic reticulum stress (ERS) could be a strategy for treating malignant tumors. Moreover, long noncoding RNAs (lncRNAs) can promote tumorigenesis and progression, and forecast the prognosis of cancers. Nevertheless, the prognostic value of ERS-related lncRNAs has not been reported in lung adenocarcinoma (LUAD).

METHODS

The messenger RNA (mRNA), microRNA (miRNA) and lncRNA expression data related to LUAD were obtained in public databases (TCGA and GEO databases). Prognostic ERS-related differentially expressed lncRNAs (ERS-DELs) were obtained and used to build an ERS-related model by Cox regression analysis. Moreover, we further screened independent prognostic elements and built a nomogram. Furthermore, enrichment analysis of genes was conducted to investigate the functions. A lncRNA-miRNA-mRNA network was built to explore mechanism of lncRNAs. Finally, qRT-PCR was utilized to examine the expression levels of lncRNAs.

RESULTS

30 ERS-DELs were identified, and an ERS-related signature was built based on AF131215.2, LINC00472, LINC01352, RP1-78O14.1, RP11-253E3.3, RP11-98D18.9, and SNHG12. Gene set enrichment analysis indicated that genes in the high-risk group were chiefly focused on the regulation of mRNA binding, and genes in the low-risk group were significantly focused on protein localization to cilia. A lncRNA-miRNA-mRNA network, containing 7 signature lncRNAs, 23 miRNAs, and 128 mRNAs, was also established. Eventually, quantitative real-time polymerase chain reaction was used to confirm that seven prognostic lncRNAs had a consistent expression with the analysis.

CONCLUSIONS

An ERS-related signature containing seven prognostic lncRNAs was built, which offered new thinking concerning the role of ERS-related lncRNAs in LUAD.

Deciphering the prognostic role of endoplasmic reticulum stress in lung adenocarcinoma: integrating prognostic prediction and immunotherapy strategies

Endoplasmic reticulum stress (ERS) is a critical factor influencing lung adenocarcinoma (LUAD) progression and patient outcomes. In this study, we analyzed gene expression data from LUAD samples sourced from The Cancer Genomic Atlas and Gene Expression Omnibus databases. Utilizing advanced statistical methods including LASSO and Cox regression, we developed a ERS-associated signature (ERAS) based on ten ERS-related genes. This model stratified patients into high- and low-risk groups, with the high-risk group exhibiting decreased survival rates, elevated tumor mutational burden, and heightened chemotherapy sensitivity. Additionally, we observed lower immune and ESTIMATE scores in the high-ERAS group, indicating a potentially compromised immune response. Experimental validation through quantitative real-time polymerase chain reaction confirmed the utility of our model. Furthermore, we constructed a nomogram to predict 1-, 3-, and 5-year survival rates, providing clinicians with a valuable tool for personalized patient management. In conclusion, our study demonstrates the efficacy of the ERAS in identifying high-ERAS LUAD patients, offering promising implications for improved prognostication and treatment strategies.

Pyroptosis Signature Gene CHMP4B Regulates Microglia Pyroptosis by Inhibiting GSDMD in Alzheimer's Disease

In this study, we aimed to work through the key genes involved in the process of pyroptosis in Alzheimer's disease (AD) to identify potential biomarkers using bioinformatics technology and further explore the underlying molecular mechanisms. The transcriptome data of brain tissue in AD patients were screened from the GEO database, and pyroptosis-related genes were analyzed. The functions of differential genes were analyzed by enrichment analysis and protein-protein interaction. The diagnostic model was established using LASSO and logistic regression analysis, and the correlation of clinical data was analyzed. Based on single-cell analysis of brain tissues of patients with AD, immunofluorescence and western blotting were used to explore the key cells affected by the hub gene. After GSEA, qRT-PCR, western blotting, LDH, ROS, and JC-1 were used to investigate the potential mechanism of the hub gene on pyroptosis. A total of 15 pyroptosis differentially expressed genes were identified. A prediction model consisting of six genes was established by LASSO and logistic regression analysis, and the area under the curve was up to 0.81. As a hub gene, CHMP4B was negatively correlated with the severity of AD. CHMP4B expression was decreased in the hippocampal tissue of patients with AD and mice. Single-cell analysis showed that CHMP4B was downregulated in AD microglia. Overexpression of CHMP4B reduced the release of LDH and ROS and restored mitochondrial membrane potential, thereby alleviating the inflammatory response during microglial pyroptosis. In summary, CHMP4B as a hub gene provides a new strategy for the diagnosis and treatment of AD.

Characterization of immunogenic cell death regulators predicts survival and immunotherapy response in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is highly lethal tumor; understanding immune response is crucial for current effective treatment. Research investigated immunogenic cell death (ICD) impact on LUAD through 75 ICD-related genes which encompass cell damage, endoplasmic reticulum stress, microenvironment, and immunity. Transcriptome data and clinical info were analyzed, revealing two ICD-related clusters: B, an immune osmotic subgroup, had better prognosis, stronger immune signaling, and higher infiltration, while A represented an immune-deficient subgroup. Univariate Cox analysis identified six prognostic genes (AGER, CD69, CD83, CLEC9A, CTLA4, and NT5E), forming a validated risk score model. It was validated across datasets, showing predictive performance. High-risk group had unfavorable prognosis, lower immune infiltration, and higher chemotherapy sensitivity. Conversely, low-risk group had better prognosis, higher immune infiltration, and favorable immunotherapy response. The key gene NT5E was examined via immunohistochemistry, with higher expression linked to poorer prognosis. NT5E was predominantly expressed in B cells, fibroblasts, and endothelial cells, correlated with immune checkpoints. These outcomes suggest that NT5E can serve as a LUAD therapeutic target. The study highlights gene predictive value, offers an efficient tumor assessment tool, guides clinical treatment strategies, and identifies NT5E as therapeutic target for LUAD.

Single-cell transcriptomics reveals heterogeneity in esophageal squamous epithelial cells and constructs models for predicting patient prognosis and immunotherapy

Background

Esophageal squamous cell carcinoma (ESCC), characterized by its high invasiveness and malignant potential, has long been a formidable challenge in terms of treatment.

Methods

A variety of advanced analytical techniques are employed, including single-cell RNA sequencing (scRNA-seq), cell trajectory inference, transcription factor regulatory network analysis, GSVA enrichment analysis, mutation profile construction, and the inference of potential immunotherapeutic drugs. The purpose is to conduct a more comprehensive exploration of the heterogeneity among malignant squamous epithelial cell subgroups within the ESCC microenvironment and establish a model for predicting the prognosis and immunotherapy outcomes of ESCC patients.

Results

An analysis was conducted through scRNA-seq, and three Cluster of malignant epithelial cells were identified using the infer CNV method. Cluster 0 was found to exhibit high invasiveness, whereas Cluster 1 displayed prominent characteristics associated with epithelial-mesenchymal transition. Confirmation of these findings was provided through cell trajectory analysis, which positioned Cluster 0 at the initiation stage of development and Cluster 1 at the final developmental stage. The abundance of Cluster 0-2 groups in TCGA-LUAD samples was assessed using ssGSEA and subsequently categorized into high and low-expression groups. Notably, it was observed that Cluster 0-1 had a significant impact on survival (p<0.05). Furthermore, GSVA enrichment analysis demonstrated heightened activity in hallmark pathways for Cluster 0, whereas Cluster 1 exhibited notable enrichment in pathways related to cell proliferation. It is noteworthy that a prognostic model was established utilizing feature genes from Cluster 0-1, employing the Lasso and stepwise regression methods. The results revealed that in TCGA and GSE53624 cohorts, the low-risk group demonstrated significantly higher overall survival and increased levels of immune infiltration. An examination of four external immunotherapy cohorts unveiled that the low-risk group exhibited improved immunotherapeutic efficacy. Additionally, more meaningful treatment options were identified for the low-risk group.

Conclusion

The findings revealed distinct interactions between malignant epithelial cells of ESCC and subgroups within the tumor microenvironment. Two cell clusters, strongly linked to survival, were pinpointed, and a signature was formulated. This signature is expected to play a crucial role in identifying and advancing precision medicine approaches for the treatment of ESCC.

Implications of different cell death patterns for prognosis and immunity in lung adenocarcinoma

In recent years, lung adenocarcinoma (LUAD) has become a focus of attention due to its low response to treatment, poor prognosis, and lack of reliable indicators to predict the progression or therapeutic effect of LUAD. Different cell death patterns play a crucial role in tumor development and are promising for predicting LUAD prognosis. From the TCGA and GEO databases, we obtained bulk transcriptomes, single-cell transcriptomes, and clinical information. Genes in 15 types of cell death were analyzed for cell death index (CDI) signature establishment. The CDI signature using necroptosis + immunologic cell death-related genes was established in the TCGA cohort with the 1-, 2-, 3-, 4- and 5-year AUC values were 0.772, 0.736, 0.723, 0.795, and 0.743, respectively. The prognosis was significantly better in the low CDI group than in the high CDI group. We also investigated the relationship between the CDI signature and clinical variables, published prognosis biomarkers, immune cell infiltration, functional enrichment pathways, and immunity biomarkers. In vitro assay showed that HNRNPF and FGF2 promoted lung cancer cell proliferation and migration and were also involved in cell death. Therefore, as a robust prognosis biomarker, CDI signatures can screen for patients who might benefit from immunotherapy and improve diagnostic accuracy and LUAD patient outcomes.

GPX4 in cell death, autophagy, and disease

Selenoprotein GPX4 (glutathione peroxidase 4), originally known as PHGPX (phospholipid hydroperoxide glutathione peroxidase), is the main oxidoreductase in the use of glutathione as a reducing agent in scavenging lipid peroxidation products. There are three GPX4 isoforms: cytosolic (cGPX4), mitochondrial (mGPX4), and nuclear (nGPX4), with distinct spatiotemporal expression patterns during embryonic development and adult life. In addition to inducing the main phenotype of ferroptosis, the loss of GPX4 can in some cells trigger apoptosis, necroptosis, pyroptosis, or parthanatos, which mediates or accelerates developmental defects, tissue damage, and sterile inflammation. The interaction of GPX4 with the autophagic degradation pathway further modulates cell fate in response to oxidative stress. Impaired GPX4 function is implicated in tumorigenesis, neurodegeneration, infertility, inflammation, immune disorders, and ischemia-reperfusion injury. Additionally, the R152H mutation in GPX4 can promote the development of Sedaghatian-type spinal metaphyseal dysplasia, a rare and fatal disease in newborns. Here, we discuss the roles of classical GPX4 functions as well as emerging GPX4-regulated processes in cell death, autophagy, and disease.Abbreviations: AA: arachidonic acid; cGPX4: cytosolic GPX4; CMA: chaperone-mediated autophagy; DAMPs: danger/damage-associated molecular patterns; mGPX4: mitochondrial GPX4; nGPX4: nuclear GPX4; GSDMD-N: N-terminal fragment of GSDMD; I/R: ischemia-reperfusion; PLOOH: phospholipid hydroperoxide; PUFAs: polyunsaturated fatty acids; RCD: regulated cell death; ROS: reactive oxygen species; Se: selenium; SSMD: Sedaghatian-type spondylometaphyseal dysplasia; UPS: ubiquitin-proteasome system.

Identification of a novel pyroptosis-related gene signature in human spermatogenic dysfunction

PURPOSE

To reveal the underlying roles that pyroptosis-related genes (PRGs) played in human spermatogenic dysfunction.

METHODS

One discovery set and three validation sets were employed to inspect the previously reported 33 PRGs in the human testis with different status of spermatogenesis. PRGs that differentially expressed in all sets were considered as key differentially expressed pyroptosis-related genes (PR-DEGs). The relationships between key PR-DEGs and samples' clinicopathological, therapeutic, and immune patterns were respectively studied. Single-cell RNA sequencing (scRNS-seq) analyses were conducted to show the expression changes and related mechanisms of key PR-DEGs at a single-cell resolution.

RESULTS

CASP4 and GPX4 were identified as two key PR-DEGs. These two genes were significantly dysregulated in spermatogenic dysfunctional samples, but with opposite tendency. CASP4 was negatively correlated with Johnsen scores but positively correlated with follicle-stimulating hormone (FSH) levels (all p < 0.05), while GPX4 exhibited significant positive correlations with Johnsen scores and negative relevance with FSH. For treatments, both molecules showed a prospective value of being predictors for sperm retrieval surgeries. Moreover, CASP4 and GPX4 were potential immunoregulators in the testicular immune microenvironment and showed significant correlations to testicular macrophages and mast cell infiltration. In scRNA-seq analyses, GPX4 was highly expressed in germ cells, which therefore suffered a sharp reduction with the loss of germ cells in spermatogenic dysfunction. On the other hand, CASP4 were basically somatic cell-derived, and the proportion of CASP4-positive Leydig cells significantly increased in disease testes (p = 0.0001).

CONCLUSION

In all, we revealed two key PRGs of human testes that might be functional in spermatogenic dysfunction.

Pyroptosis: A promising target for lung cancer therapy

Pyroptosis is a type of programed cell death that differs from apoptosis, ferroptosis, or necrosis. Numerous studies have reported that it plays a critical role in tumorigenesis and modification of the tumor microenvironment in multiple tumors. In this review, we briefly describe the canonical, non-canonical, and alternative mechanisms of pyroptotic cell death. We also summarize the potential roles of pyroptosis in oncogenesis, tumor development, and lung cancer treatment, including chemotherapy, radiotherapy, targeted therapy, and immunotherapy. Pyroptosis has double-edged effects on the modulation of the tumor environment and lung cancer treatment. Further exploration of pyroptosis-based drugs could provide novel therapeutic strategies for lung cancer.

An ICD-Associated DAMP Gene signature predicts survival and immunotherapy response of patients with lung adenocarcinoma

BACKGROUND

While some lung adenocarcinoma (LUAD) patients benefit long-term from treatment with immune checkpoint inhibitors, the sad reality is that a considerable proportion of patients do not. The classification of the LUAD tumor microenvironment (TME) can be used to conceptually comprehend primary resistance mechanisms. In addition, the most recent research demonstrates that the release of damage-associated molecular pattern (DAMP) in TME by immunogenic cell death (ICD) may contribute to the adaptive immune response. Currently, however, there is no such comprehensive research on this topic in LUAD patients. Therefore, we set out to investigate how to reverse the poor infiltration characteristics of immune cells and boost antitumor immunity by identifying DAMP model.

METHODS

In this study, ICD-related DAMP genes were selected to investigate their effects on the prognosis of LUAD. To create a risk signature using the TCGA-LUAD cohort, the univariate COX regression and the least absolute shrinkage and selection operator regression were carried out, and the results were verified in a GEO dataset. Subsequently, the multivariate COX regression was applied to establish a prognostic nomogram. And the ESTIMATE and ssGSEA algorithms were utilized to analyze immune activity and the TIDE algorithm was for responsiveness to immunotherapy. Moreover, clinical tissue samples were used to verify the differential expression of 9 DAMP genes in the signature.

RESULTS

We identified two distinct DAMP molecular subtypes, and there are remarkable differences in survival probability between the two subtypes, and patients with higher levels of DAMP-related genes are "hot tumors" with increased immune activity. In addition, 9 DAMP genes were selected as prognostic signature genes, and clinical outcomes and immunotherapy response were better for participants in the low-risk group. Importantly, according to the area under the curve (AUC) value in evaluating the efficacy of immunotherapy, this signature is superior to existing predictors, such as PD-L1 and TIDE.

CONCLUSIONS

Our study suggests ICD plays an important part in modeling the TME of LUAD patients. And this signature could be utilized as a reliable predictor to estimate clinical outcomes and predict immunotherapy efficacy among LUAD patients.

Comprehensive analyses reveal the prognosis and biological function roles of chromatin regulators in lung adenocarcinoma

The present study explored the prognosis and biological function roles of chromatin regulators (CRs) in patients with lung adenocarcinoma (LUAD). Using transcriptome profile and clinical follow-up data of LUAD dataset, we explored the molecular classification, developed, and validated a CR prognostic model, built an individual risk scoring system in LUAD, and compared the clinical and molecular characteristics between different subtypes and risk stratifications. We investigated the chemotherapy sensitivity and predicted potential immunotherapy response. Lastly, we collected the clinical samples and validated the prognosis and potential function role of NAPS2. Our study indicated that LUAD patients could be classified into two subtypes that had obviously different clinical background and molecular features. We constructed a prognostic model with eight CR genes, which was well validated in several other population cohort. We built high- and low-risk stratifications for LUAD patients. Patients from high-risk group were totally different from low-risk groups in clinical, biological function, gene mutation, microenvironment, and immune infiltration levels. We idented several potential molecular compounds for high-risk group treatment. We predicted that high-risk group may have poor immunotherapy response. We finally found that Neuronal PAS Domain Protein 2 (NPAS2) involved in the progression of LUAD via regulating cell adhesion. Our study indicated that CR involved in the progression of LUAD and affect their prognosis. Different therapeutic strategies should be developed for different molecular subtypes and risk stratifications. Our comprehensive analyses uncover specific determinants of CRs in LUAD and provides implications for investigating disease-associated CRs.

A novel pyroptosis-related prognostic signature for lung adenocarcinoma: Identification and multi-angle verification

Background: Lung adenocarcinoma (LUAD) is an aggressive disease of heterogeneous characteristics with poor prognosis and high mortality. Pyroptosis, a newly uncovered type of programmed cell death with an inflammatory nature, has been determined to hold substantial importance in the progression of tumors. Despite this, the knowledge about pyroptosis-related genes (PRGs) in LUAD is limited. This study aimed to develop and validate a prognostic signature for LUAD based on PRGs.

Methods: In this research, gene expression information from The Cancer Genome Atlas (TCGA) served as the training cohort and data from Gene Expression Omnibus (GEO) was utilized as the validation cohort. PRGs list was taken from the Molecular Signatures Database (MSigDB) and previous studies. Univariate Cox regression and Lasso analysis were then conducted to identify prognostic PRGs and develop a LUAD prognostic signature. The Kaplan-Meier method, univariate and multivariate Cox regression models were employed to assess the independent prognostic value and forecasting accuracy of the pyroptosis-related prognostic signature. The correlation between prognostic signature and immune infiltrating was analyzed to examine the role in tumor diagnosis and immunotherapy. Further, RNA-seq as well as quantitative real-time polymerase chain reaction (qRT-PCR) analysis in separate data sets was applied in order to validate the potential biomarkers for LUAD.

Results: A novel prognostic signature based on 8 PRGs (BAK1, CHMP2A, CYCS, IL1A, CASP9, NLRC4, NLRP1, and NOD1) was established to predict the survival of LUAD. The prognostic signature proved to be an independent prognostic factor of LUAD with satisfactory sensitivity and specificity in the training and validation sets. High-risk scores subgroups in the prognostic signature were significantly associated with advanced tumor stage, poor prognosis, less immune cell infiltration, and immune function deficiency. RNA sequencing and qRT-PCR analysis confirmed that the expression of CHMP2A and NLRC4 could be used as biomarkers for LUAD.

Conclusion: We have successfully developed a prognostic signature consisting of eight PRGs that providing a novel perspective on predicting prognosis, assessing infiltration levels of tumor immune cells, and determining the outcomes of immunotherapy for LUAD.

Application of an angiogenesis-related genes risk model in lung adenocarcinoma prognosis and immunotherapy

Lung adenocarcinoma (LUAD) is an essential pathological subtype of non-small cell lung cancer and offers a severe problem for worldwide public health. There is mounting proof that angiogenesis is a crucial player in LUAD progression. Consequently, the purpose of this research was to construct a novel LUAD risk assessment model based on genetic markers related to angiogenesis. We accessed The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases for LUAD mRNA sequencing data and clinical information. Based on machine algorithms and bioinformatics, angiogenic gene-related risk scores (RS) were calculated. Patients in the high-risk category had a worse prognosis (p < 0.001) in the discovery TCGA cohort, and the results were confirmed by these three cohorts (validation TCGA cohort, total TCGA cohort, and GSE68465 cohort). Moreover, risk scores for genes involved in angiogenesis were independent risk factors for lung cancer in all four cohorts. The low-risk group was associated with better immune status and lower tumor mutational load. In addition, the somatic mutation study revealed that the low-risk group had a lower mutation frequency than the high-risk group. According to an analysis of tumor stem cell infiltration, HLA expression, and TIDE scores, the low-risk group had higher TIDE scores and HLA expression levels than the high-risk group, and the amount of tumor stem cell infiltration correlated with the risk score. In addition, high-risk groups may benefit from immune checkpoint inhibitors and targeted therapies. In conclusion, we developed an angiogenesis-related gene risk model to predict the prognosis of LUAD patients, which may aid in the classification of patients with LUAD and select medications for LUAD patients.

Pyroptosis-based risk score predicts prognosis and drug sensitivity in lung adenocarcinoma

Pyroptosis is a recently identified form of programmed cell death; however, its role in lung adenocarcinoma (LUAD) remains unclear. Therefore, we set out to explore the prognostic potential of pyroptosis-related genes in LUAD. The pyroptosis-related risk score (PRRS) was developed by least absolute shrinkage and selection operator Cox regression and multivariate Cox regression. We found that PRRS was an independent prognostic factor for LUAD. LUAD patients in the high-PRRS group showed a significantly shorter overall survival (OS) and enriched in cell proliferation-related pathways. Then pathway enrichment analyses, mutation profile, tumor microenvironment, and drug sensitivity analysis were further studied in PRRS stratified LUAD patients. Tumor purity (TP) analyses revealed that L-PRRS LUAD patients had a lower TP, and patients in L-TP + L-PRRS subgroup had the most prolonged OS. Mutation analyses suggested that the L-PRRS LUAD patients had a lower tumor mutation burden (TMB), and patients in H-TMB + L-PRRS subgroup had the most prolonged OS. Drug sensitivity analyses showed that PRRS was significantly negatively correlated with the sensitivity of cisplatin, besarotene, etc., while it was significantly positively correlated with the sensitivity of kin001-135. Eventually, a nomogram was constructed based on PRRS and clinical characters of LUAD. Overall, the pyroptosis-related signature is helpful for prognostic prediction and in guiding treatment for LUAD patients.

Identification of pyroptosis-related lncRNA signature and AC005253.1 as a pyroptosis-related oncogene in prostate cancer

Background

Pyroptosis and prostate cancer (PCa) are closely related. The role of pyroptosis-related long non-coding RNAs (lncRNAs) (PRLs) in PCa remains elusive. This study aimed to explore the relationship between PRL and PCa prognosis.

Methods

Gene expression and clinical signatures were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. A PRL risk prediction model was established by survival random forest analysis and least absolute shrinkage and selection operator regression. Functional enrichment, immune status, immune checkpoints, genetic mutations, and drug susceptibility analyses related to risk scores were performed by the single-sample gene set enrichment analysis, gene set variation analysis, and copy number variation analysis. PRL expression was verified in PCa cells. Cell Counting Kit-8, 5-ethynyl-2′-deoxyuridine, wound healing, transwell, and Western blotting assay were used to detect the proliferation, migration, invasion, and pyroptosis of PCa cells, respectively.

Results

Prognostic features based on six PRL (AC129507.1, AC005253.1, AC127502.2, AC068580.3, LIMD1-AS1, and LINC01852) were constructed, and patients in the high-score group had a worse prognosis than those in the low-score group. This feature was determined to be independent by Cox regression analysis, and the area under the curve of the 1-, 3-, and 5-year receiver operating characteristic curves in the testing cohort was 1, 0.93, and 0.92, respectively. Moreover, the external cohort validation confirmed the robustness of the PRL risk prediction model. There was a clear distinction between the immune status of the two groups. The expression of multiple immune checkpoints was also reduced in the high-score group. Gene mutation proportion in the high-score group increased, and the sensitivity to drugs increased significantly. Six PRLs were upregulated in PCa cells. Silencing of AC005253.1 inhibited cell proliferation, migration, and invasion in DU145 and PC-3 cells. Moreover, silencing of AC005253.1 promoted pyroptosis and inflammasome AIM2 expression.

Conclusions

Overall, we constructed a prognostic model of PCa with six PRLs and identified their expression in PCa cells. The experimental verification showed that AC005253.1 could affect the proliferation, migration, and invasion abilities of PCa cells. Meanwhile, AC005253.1 may play an important role in PCa by affecting pyroptosis through the AIM2 inflammasome. This result requires further research for verification.

Comprehensive analysis of a novel signature incorporating lipid metabolism and immune-related genes for assessing prognosis and immune landscape in lung adenocarcinoma

Background

As the crosstalk between metabolism and antitumor immunity continues to be unraveled, we aim to develop a prognostic gene signature that integrates lipid metabolism and immune features for patients with lung adenocarcinoma (LUAD).

Methods

First, differentially expressed genes (DEGs) related to lipid metabolism in LUAD were detected, and subgroups of LUAD patients were identified via the unsupervised clustering method. Based on lipid metabolism and immune-related DEGs, variables were determined by the univariate Cox and LASSO regression, and a prognostic signature was established. The prognostic value of the signature was evaluated by the Kaplan–Meier method, time-dependent ROC, and univariate and multivariate analyses. Five independent GEO datasets were employed for external validation. Gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and immune infiltration analysis were performed to investigate the underlying mechanisms. The sensitivity to common chemotherapeutic drugs was estimated based on the GDSC database. Finally, we selected PSMC1 involved in the signature, which has not been reported in LUAD, for further experimental validation.

Results

LUAD patients with different lipid metabolism patterns exhibited significant differences in overall survival and immune infiltration levels. The prognostic signature incorporated 10 genes and stratified patients into high- and low-risk groups by median value splitting. The areas under the ROC curves were 0.69 (1-year), 0.72 (3-year), 0.74 (5-year), and 0.74 (10-year). The Kaplan–Meier survival analysis revealed a significantly poorer overall survival in the high-risk group in the TCGA cohort (p < 0.001). In addition, both univariate and multivariate Cox regression analyses indicated that the prognostic model was the individual factor affecting the overall survival of LUAD patients. Through GSEA and GSVA, we found that tumor progression and inflammatory and immune-related pathways were enriched in the high-risk group. Additionally, patients with high-risk scores showed higher sensitivity to chemotherapeutic drugs. The in vitro experiments further confirmed that PSMC1 could promote the proliferation and migration of LUAD cells.

Conclusions

We developed and validated a novel signature incorporating both lipid metabolism and immune-related genes for all-stage LUAD patients. This signature can be applied not only for survival prediction but also for guiding personalized chemotherapy and immunotherapy regimens.

A m6A methyltransferase-mediated immune signature determines prognosis, immune landscape and immunotherapy efficacy in patients with lung adenocarcinoma

BACKGROUND

As the most abundant modification in mRNA, the N⁶-methyladenosine (m⁶A) RNA modification is involved in the occurrence and development of various tumors. However, the underlying functions of this alteration in the immune microenvironment of lung adenocarcinoma (LUAD) remain unknown.

METHODS

We identified m⁶A-mediated immune genes by performing a correlation analysis. Next, a m⁶A-mediated immune model was constructed using multiple machine learning algorithms, including univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses. The potential of this model to predict the immune landscapes, drug sensitivities, and immunotherapy responses of different LUAD risk groups was studied.

RESULTS

A m⁶A-mediated immune model containing 13 m⁶A-mediated immune genes was established and found to be an independent predictor of survival time. The prognosis of low-risk patients was significantly better than that of high-risk patients. These two risk groups displayed different immune environments, genomic backgrounds, chemotherapy responses and immunotherapy response tendencies. The low- and high-risk groups strongly corresponded to the immune-hot and immune-cold phenotypes, respectively. The low-risk group was more enriched in immune-related biological processes, and the high-risk group was more enriched in proliferation-related biological processes. Furthermore, low-risk patients responded better to immunotherapy based on the results obtained from the tumor immune dysfunction and exclusion (TIDE) algorithm and subclass mapping algorithm using five external independent immunotherapy cohorts.

CONCLUSIONS

Our results suggest that the m⁶A modification participates in regulating the tumor microenvironment. The m⁶A-mediated immune model may be useful to predict the immunotherapy responses and outcomes of patients with LUAD.