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

Abstract

Lung adenocarcinoma (LUAD) is the main pathological subtype of non-small-cell lung cancer. Endoplasmic reticulum stress (ERS) has been found to be involved in multiple tumor-related biological processes. At present, a comprehensive analysis of ERS-related genes in LUAD is still lacking. A total of 1034 samples from TCGA and GEO were used to screen differentially expressed genes. Further, Random Forest algorithm was utilized to screen characteristic genes related to prognosis. Then, LASSO Cox regression was used to construct a prognostic signature. Taking the median of signature score as the threshold, patients were separated into high-risk (HR) group and low-risk (LR) group. Tumor mutation burden (TMB), immune cell infiltration, cancer stem cell infiltration, expression of HLA, and immune checkpoints of the two risk groups were analyzed. TIDE score was used to evaluate the response of the two risk groups to immunotherapy. Finally, the gene expression was verified in clinical tissues with RT-qPCR. An eight-gene signature (ADRB2, AGER, CDKN3, GJB2, SFTPC, SLC2A1, SLC6A4, and SSR4) was constructed. TMB and cancer stem cell infiltration were higher in the HR group than the LR group. TIDE score and expression level of HLA were higher in the LR group than the HR group. Expression level of immune checkpoints, including CD28, CD27, IDO2, and others, were higher in the LR group. Multiple drugs approved by FAD, targeting ERS-related genes, were available for the treatment of LUAD. In summary, we established a stable prognostic model based on ERS-related genes to help the classification of LUAD patients and looked for new treatment strategies from aspects of immunity, tumor mutation, and tumor stem cell infiltration.

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

“…Therefore, our prognostic signature can successfully predict prognosis and is not restricted by different groups of patients, sequence platforms, and technologies. These were consistent with the successfully established signatures for NSCLC ( Ye et al, 2021 ; Yang et al, 2022 ). Finally, a nomogram prediction model was constructed using the risk score, age, and UICC stage to precisely predict OS rate after 1-, 3-, and 5-year periods, and calibration plots of the nomogram showed high agreement between the nomogram-predicted and the actual OS.…”

“…However, in the current study, the AUC value for OS at the 5 year periods was 0.657 in TCGA and 0.717 in GSE31210. Various researches showed that the AUC values of many signatures for lung cancer or NSCLC were more than 0.75 ( Wu et al, 2021a ; Li et al, 2021b ; Ouyang et al, 2021 ; Qu et al, 2021 ; Zhang and Yan, 2021 ; Zou et al, 2021 ; Wang et al, 2022b ; Chen et al, 2022 ; Li et al, 2022 ; Yang et al, 2022 ). Thus, the prognostic biomarkers or signatures with a higher AUC value need to be explored in the future.…”

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

“…However, little is known about the relationship between exercise-mediated genes, exerkines, tumor microenvironment, We first focused our perspective on the dynamic changes caused by muscle injury in LUAD and developed the MFI model, which could accurately predict the OS in patients with LUAD. Several researchers have previously proposed models for the risk of apoptosis, injury and stress-related LUAD (44)(45)(46)(47).Our model showed better accuracy than previously reported methods, which was confirmed by comparing the AUC values. Moreover, our model could also be used to classify "cold" and "hot" tumors, which results in differences in genomic alternation status and sensitivity toward immunotherapy.…”

Implementação da educação em saúde na prevenção de neoplasias penianas: revisão narrativa

“…Sendo assim, o Câncer de Pulmão de Células Não Pequenas (CPCNP), por ser um dos principais tipos que podem afetar fumantes e não fumantes, está mais relacionado com fatores genéticos, tendo como via comum de todos os cânceres as alterações nuclear e enzimática, dois agentes cruciais para o ciclo celular normal (AIRES; GUEDES, 2018;YIN et al, 2021). complexas e diferentes, sendo assim, a IHQ é capaz de classificar os tipos de neoplasias de modo essencial para o tratamento, prognóstico e recidiva, com auxílio dos marcadores tumorais (INAMURA, 2018;RAJGURU et al, 2020;XIE et al, 2022;YANG et al, 2022).…”