Prognostic Risk Signature and Comprehensive Analyses of Endoplasmic Reticulum Stress-Related Genes in Lung Adenocarcinoma

A novel prognostic signature based on smoking-associated genes for predicting prognosis and immune microenvironment in NSCLC smokers

BACKGROUND

As a highly heterogeneous tumor, non-small cell lung cancer (NSCLC) is famous for its high incidence and mortality worldwide. Smoking can cause genetic changes, which leading to the occurrence and progress of NSCLC. Nevertheless, the function of smoking-related genes in NSCLC needs more research.

METHODS

We downloaded transcriptome data and clinicopathological parameters from Gene Expression Omnibus (GEO) databases, and screened smoking-related genes. Lasso regression were applied to establish the 7-gene signature. The associations between the 7-gene signature and immune microenvironment analysis, survival analysis, drug sensitivity analysis and enriched molecular pathways were studied. Ultimately, cell function experiments were conducted to research the function of FCGBP in NSCLC.

RESULTS

Through 7-gene signature, NSCLC samples were classified into high-risk group (HRG) and low-risk group (LRG). Significant difference in overall survival (OS) between HRG and LRG was found. Nomograms and ROC curves indicated that the 7-gene signature has a stable ability in predicting prognosis. Through the analysis of immune microenvironment, we found that LRG patients had better tumor immune activation. FCGBP showed the highest mutation frequency among the seven prognostic smoking related genes (LRRC31, HPGD, FCGBP, SPINK5, CYP24A1, S100P and FGG), and was notable down-regulated in NSCLC smokers compared with non-smoking NSCLC patients. The cell experiments confirmed that FCGBP knockdown promoting proliferation, migration, and invasion in NSCLC cells.

CONCLUSION

This smoking-related prognostic signature represents a promising tool for assessing prognosis and tumor microenvironment in smokers with NSCLC. The role of FCGBP in NSCLC was found by cell experiments, which can be served as diagnostic biomarker and immunotherapy target for NSCLC.

Endoplasmic reticulum stress regulators exhibit different prognostic, therapeutic and immune landscapes in pancreatic adenocarcinoma

Endoplasmic reticulum stress (ERS) and unfolded protein response are the critical processes of tumour biology. However, the roles of ERS regulatory genes in pancreatic adenocarcinoma (PAAD) remain elusive. A novel ERS-related risk signature was constructed using the Lasso regression analysis. Its prognostic value, immune effect, metabolic influence, mutational feature and therapeutic correlation were comprehensively analysed through multiple bioinformatic approaches. The biofunctions of KDELR3 and YWHAZ in pancreatic cancer (PC) cells were also investigated through colony formation, Transwell assays, flow cytometric detection and a xenograft model. The upstream miRNA regulatory mechanism of KDELR3 was predicted and validated. ERS risk score was identified as an independent prognostic factor and could improve traditional prognostic model. Meanwhile, it was closely associated with metabolic reprogramming and tumour immune. High ERS risk enhanced glycolysis process and nucleotide metabolism, but was unfavourable for anti-tumour immune response. Moreover, ERS risk score could act as a potential biomarker for predicting the efficacy of ICBs. Overexpression of KDELR3 and YWHAZ stimulated the proliferation, migration and invasion of SW1990 and BxPC-3 cells. Silencing KDELR3 suppressed tumour growth in a xenograft model. miR-137 could weaken the malignant potentials of PC cells through inhibiting KDELR3 (5'-AGCAAUAA-3'). ERS risk score greatly contributed to PAAD clinical assessment. KDELR3 and YWHAZ possessed cancer-promoting capacities, showing promise as a novel treatment target.

An endoplasmic reticulum stress-related signature featuring ASNS for predicting prognosis and immune landscape in prostate cancer

Prostate cancer (PRAD) is one of the common malignant tumors of the urinary system. In order to predict the treatment results for PRAD patients, this study proposes to develop a risk profile based on endoplasmic reticulum stress (ERS). Based on the Memorial Sloan-Kettering Cancer Center (MSKCC) cohort and the Gene Expression Omnibus database (GSE70769), we verified the predictive signature. Using a random survival forest analysis, prognostically significant ERS-related genes were found. An ERS-related risk score (ERscore) was created using multivariable Cox analysis. In addition, the biological functions, genetic mutations and immune landscape related to ERscore are also studied to reveal the underlying mechanisms related to ERS in PRAD. We further explored the ERscore-related mechanisms by profiling a single-cell RNA sequencing (scRNA-seq) dataset (GSE137829) and explored the oncogenic role of ASNS in PRAD through in vitro experiments. The risk signature composed of eight ERS-related genes constructed in this study is an independent prognostic factor and validated in the MSKCC and GSE70769 data sets. The scRNA-seq data additionally revealed that several carcinogenic pathways were noticeably overactivated in the group with high ERS scores. As one of the prognostic genes, ASNS will significantly inhibit the proliferation, migration and invasion abilities of PRAD cells after its expression is interfered with. In conclusion, this study developed a novel risk-specific ERS-based clinical treatment strategy for patients with PRAD.

Comprehensive Analysis Reveals the Potential Roles of CDKN3 in Pancancer and Verification in Endometrial Cancer

Background

Cyclin-dependent kinase inhibitor 3 (CDKN3) has been studied in many cancers. However, the comprehensive and systematic pancancer analysis of CDKN3 genes is still lacking.

Methods

Data were downloaded from online databases. R was used for analysis of the differential expression and gene alteration of CDKN3 and of the associations between CDKN3 expression and survival, signaling pathways, and drug sensitivity. Clinical samples and in vitro experiments were selected for verification.

Results

CDKN3 expression was higher in most types of cancers, and this phenotype was significantly correlated with poor survival. CDKN3 showed gene alterations and copy number alterations in many cancers and associated with some immune-related pathways and factors. Drug sensitivity analysis elucidated that CDKN3 could be a useful marker for therapy selection. Clinical samples elucidated CDKN3 expressed high in endometrial cancer tissue. In vitro studies showed that CDKN3 induced pro-tumor effect in immune environment and facilitated endometrial cancer cell proliferation and G1/S phase transition.

Conclusion

CDKN3 has been shown to be highly expressed in most types of cancers and promoted cancer cell progression. CDKN3 may serve as a novel marker in clinical diagnosis, treatment, and prognosis prediction in future.

Identifying endoplasmic reticulum stress-related molecular subtypes and prognostic model for predicting the immune landscape and therapy response in pancreatic cancer

Endoplasmic reticulum stress (ERS) is caused by the accumulation of intracellular misfolded or unfolded proteins and is associated with cancer development. In this study, pan-cancer analysis revealed complex genetic variations, including copy number variation, methylation, and somatic mutations for ERS-related genes (ERGs) in 33 kinds of cancer. Consensus clustering divided pancreatic cancer (PC) patients from TCGA and GEO databases into two ERS-related subtypes: ERGcluster A and B. Compared with ERGcluster A, ERGcluster B had a more active ERS state and worse prognosis. Subsequently, the ERS-related prognostic model was established to quantify the ERS score for a single sample. The patient with a low ERS score had remarkably longer survival times. ssGSEA and CIBERSORT algorithms revealed that activated B cells and CD8+ T cells had higher infiltration in the low ERS score group, but higher infiltration of activated CD4+ T cells, activated dendritic cells, macrophages, and neutrophils in the high ERS score group. Drug sensitivity analysis indicated the low ERS score group had a better response to gemcitabine, paclitaxel, 5-fluorouracil, oxaliplatin, and irinotecan. RT-qPCR validated that MET, MUC16, and KRT7 in the model had higher expression levels in pancreatic tumour tissues. Single-cell analysis further revealed that MET, MUC16, and KRT7 were mainly expressed in cancer cells in PC tumour microenvironment. In all, we first constructed the ERS-related molecular subtypes and prognostic model in PC. Our research highlighted the vital role of ERS in PC and contributed to further research on molecular mechanisms and novel therapeutic strategies for PC in the future.

FHL1 as a novel prognostic biomarker and correlation with immune infiltration levels in lung adenocarcinoma

Aim: We aimed to examine the effect of FHL1 in the diagnosis and prognosis of non-small-cell lung cancer and its relationship with tumor-infiltrating immune cells. Methods: FHL1 expression status and influence on clinical characteristics, diagnosis and prognosis in non-small-cell lung cancer were assessed. Interaction networks of FHL1 were revealed, and a correlation analysis between FHL1 expression and tumor immunity was performed. Results: FHL1 expression was significantly lower in tumors, and downregulated FHL1 predicted a worse prognosis for lung adenocarcinoma. FHL1 expression was correlated with tumor-infiltrating immune cells, immune checkpoints and chemokine levels. Conclusion: FHL1 is a powerful biomarker to evaluate the diagnosis and prognosis and immune infiltration level of lung adenocarcinoma.

Identification and validation of a muscle failure index to predict prognosis and immunotherapy in lung adenocarcinoma through integrated analysis of bulk and single-cell RNA sequencing data

Background

It was previously reported that the production of exerkines is positively associated with the beneficial effects of exercise in lung adenocarcinoma (LUAD) patients. This study proposes a novel scoring system based on muscle failure-related genes, to assist in clinical decision making.

Methods

A comprehensive analysis of bulk and single cell RNA sequencing (scRNA-seq) of early, advanced and brain metastatic LUAD tissues and normal lung tissues was performed to identify muscle failure-related genes in LUAD and to determine the distribution of muscle failure-related genes in different cell populations. A novel scoring system, named MFI (Muscle failure index), was developed and validated. The differences in biological functions, immune infiltration, genomic alterations, and clinical significance of different subtypes were also investigated.

Results

First, we conducted single cell analysis on the dataset GSE131907 and identified eight cell subpopulations. We found that four muscle failure-related genes (BDNF, FNDC5, IL15, MSTN) were significantly increased in tumor cells. In addition, IL15 was widely distributed in the immune cell population. And we have validated it in our own clinical cohort. Then we created the MFI model based on 10 muscle failure-related genes using the LASSO algorithm, and MFI remained an independent prognostic factor of OS in both the training and validation cohorts. Moreover, we generated MFI in the single-cell dataset, in which cells with high MFI received and sent more signals compared to those with low MFI. Biological function analysis of both subtypes revealed stronger anti-tumor immune activity in the low MFI group, while tumor cells with high MFI had stronger metabolic and proliferative activity. Finally, we systematically assessed the immune cell activity and immunotherapy responses in LUAD patients, finding that the low MFI group was more sensitive to immunotherapy.

Conclusion

Overall, our study can improve the understanding of the role of muscle failure-related genes in tumorigenesis and we constructed a reliable MFI model for predicting prognosis and guiding future clinical decision making.

Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer

Background: An imbalance in the redox homeostasis has been reported in multiple cancers and is associated with a poor prognosis of disease. However, the prognostic value of redox-related genes in non-small-cell lung cancer (NSCLC) remains unclear.

Methods: RNA sequencing data, DNA methylation data, mutation, and clinical data of NSCLC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Redox-related differentially expressed genes (DEGs) were used to construct the prognostic signature using least absolute shrinkage and selection operator (LASSO) regression analysis. Kaplan–Meier survival curve and receiver operator characteristic (ROC) curve analyses were applied to validate the accuracy of the gene signature. Nomogram and calibration plots of the nomogram were constructed to predict prognosis. Pathway analysis was performed using gene set enrichment analysis. The correlations of risk score with tumor stage, immune infiltration, DNA methylation, tumor mutation burden (TMB), and chemotherapy sensitivity were evaluated. The prognostic signature was validated using GSE31210, GSE26939, and GSE68465 datasets. Real-time polymerase chain reaction (PCR) was used to validate dysregulated genes in NSCLC.

Results: A prognostic signature was constructed using the LASSO regression analysis and was represented as a risk score. The high-risk group was significantly correlated with worse overall survival (OS) (p < 0.001). The area under the ROC curve (AUC) at the 5-year stage was 0.657. The risk score was precisely correlated with the tumor stage and was an independent prognostic factor for NSCLC. The constructed nomogram accurately predicted the OS of patients after 1-, 3-, and 5-year periods. DNA replication, cell cycle, and ECM receptor interaction were the main pathways enriched in the high-risk group. In addition, the high-risk score was correlated with higher TMB, lower methylation levels, increased infiltrating macrophages, activated memory CD4⁺ T cells, and a higher sensitivity to chemotherapy. The signature was validated in GSE31210, GSE26939, and GSE68465 datasets. Real-time PCR validated dysregulated mRNA expression levels in NSCLC.

Conclusions: A prognostic redox-related gene signature was successfully established in NSCLC, with potential applications in the clinical setting.