Dataset Information

Penetrating Exploration of Prognostic Correlations of the FKBP Gene Family with Lung Adenocarcinoma.

ABSTRACT: The complexity of lung adenocarcinoma (LUAD), the development of which involves many interacting biological processes, makes it difficult to find therapeutic biomarkers for treatment. FK506-binding proteins (FKBPs) are composed of 12 members classified as conservative intracellular immunophilin family proteins, which are often connected to cyclophilin structures by tetratricopeptide repeat domains and have peptidyl prolyl isomerase activity that catalyzes proline from residues and turns the trans form into the cis form. Since FKBPs belong to chaperone molecules and promote protein folding, previous studies demonstrated that FKBP family members significantly contribute to the degradation of damaged, misfolded, abnormal, and foreign proteins. However, transcript expressions of this gene family in LUAD still need to be more fully investigated. In this research, we adopted high-throughput bioinformatics technology to analyze FKBP family genes in LUAD to provide credible information to clinicians and promote the development of novel cancer target drugs in the future. The current data revealed that the messenger (m)RNA levels of FKBP2, FKBP3, FKBP4, FKBP10, FKBP11, and FKBP14 were overexpressed in LUAD, and FKBP10 had connections to poor prognoses among LUAD patients in an overall survival (OS) analysis. Based on the above results, we selected FKBP10 to further conduct a comprehensive analysis of the downstream pathway and network. Through a DAVID analysis, we found that FKBP10 was involved in mitochondrial electron transport, NADH to ubiquinone transport, mitochondrial respiratory chain complex I assembly, etc. The MetaCore pathway analysis also indicated that FKBP10 was involved in "Ubiquinone metabolism", "Translation_(L)-selenoaminoacid incorporation in proteins during translation", and "Transcription_Negative regulation of HIF1A function". Collectively, this study revealed that FKBP family members are both significant prognostic biomarkers for lung cancer progression and promising clinical therapeutic targets, thus providing new targets for treating LUAD patients.

SUBMITTER: Wang CC

PROVIDER: S-EPMC9862762 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Penetrating Exploration of Prognostic Correlations of the FKBP Gene Family with Lung Adenocarcinoma.

Wang Chin-Chou CC Shen Wan-Jou WJ Anuraga Gangga G Hsieh Yu-Hsiu YH Khoa Ta Hoang Dang HD Xuan Do Thi Minh DTM Shen Chiu-Fan CF Wang Chih-Yang CY Wang Wei-Jan WJ

Journal of personalized medicine 20221226 1

The complexity of lung adenocarcinoma (LUAD), the development of which involves many interacting biological processes, makes it difficult to find therapeutic biomarkers for treatment. FK506-binding proteins (FKBPs) are composed of 12 members classified as conservative intracellular immunophilin family proteins, which are often connected to cyclophilin structures by tetratricopeptide repeat domains and have peptidyl prolyl isomerase activity that catalyzes proline from residues and turns the tran ...[more]

PMID: 36675710

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Project description:Accumulating evidence has implicated members of the procollagen-lysine, 2-oxoglutarate 5-dioxygenase (PLOD) gene family, PLOD1, PLOD2, and PLOD3, in cancer progression and metastasis. However, their expression, prognostic value, and mechanisms underlying their roles in lung adenocarcinoma (LUAD) have not yet been reported. We downloaded PLOD data for LUAD and normal tissues from The Cancer Genome Atlas (TCGA). PLOD1-3 protein expression was evaluated using the Clinical Proteomics Tumor Analysis Consortium and Human Protein Atlas. Survival analysis was performed using the Kaplan-Meier method. A protein-protein interaction network was constructed using STRING software. The "ClusterProfiler" package was used for functional-enrichment analysis. The relationship between PLOD mRNA expression and immune infiltration was analyzed using the Tumor Immunity Assessment Resource and Tumor Immune System Interaction Database. The expression of PLODs in LUAD tissues was significantly upregulated compared with that in adjacent normal tissues. PLOD mRNA overexpression is associated with lymph node metastasis and high TNM staging. Receiver operating characteristic curve analysis showed that when the cut-off level was 6.073, the accuracy, sensitivity, and specificity of PLOD1 in distinguishing LUAD from adjacent controls were 84.4, 79.7, and 82.6%, respectively. The accuracy, sensitivity, and specificity of PLOD2 in distinguishing LUAD from adjacent controls were 81.0, 98.3, and 68.0%, respectively, at a cut-off value of 4.360. The accuracy, sensitivity, and specificity of PLOD3 in distinguishing LUAD from adjacent controls were 69.0, 86.4, and 52.0%, respectively, with a cut-off value of 5.499. Kaplan-Meier survival analysis demonstrated that LUAD patients with high PLODs had a worse prognosis than those with low PLODs. Correlation analysis showed that PLOD mRNA expression was related to immune infiltration and tumor purity. Upregulation of PLOD expression was significantly associated with poor survival and immune cell infiltration in LUAD. Our research shows that PLOD family members have potential as novel biomarkers for poor prognosis and as potential immunotherapy targets for LUAD.

Project description:Given the importance of solute carrier (SLC) proteins in maintaining cellular metabolic homeostasis and that their dysregulation contributes to cancer progression, here we constructed a robust SLC family signature for lung adenocarcinoma (LUAD) patient stratification. Transcriptomic profiles and relevant clinical information of LUAD patients were downloaded from the TCGA and GEO databases. SLC family genes differentially expressed between LUAD tissues and adjacent normal tissues were identified using limma in R. Of these, prognosis-related SLC family genes were further screened out and used to construct a novel SLC family-based signature in the training cohort. The accuracy of the prognostic signature was assessed in the testing cohort, the entire cohort, and the external GSE72094 cohort. Correlations between the prognostic signature and the tumor immune microenvironment and immune cell infiltrates were further explored. We found that seventy percent of SLC family genes (279/397) were differentially expressed between LUAC tissues and adjacent normal. Twenty-six genes with p-values < 0.05 in univariate Cox regression analysis and Kaplan-Meier survival analysis were regarded as prognosis-related SLC family genes, six of which were used to construct a prognostic signature for patient classification into high- and low-risk groups. Kaplan-Meier survival analysis in all internal and external cohorts revealed a better overall survival for patients in the low-risk group than those in the high-risk group. Univariate and multivariate Cox regression analyses indicated that the derived risk score was an independent prognostic factor for LUAD patients. Moreover, a nomogram based on the six-gene signature and clinicopathological factors was developed for clinical application. High-risk patients had lower stromal, immune, and ESTIMATE scores and higher tumor purities than those in the low-risk group. The proportions of infiltrating naive CD4 T cells, activated memory CD4 T cells, M0 macrophages, resting dendritic cells, resting mast cells, activated mast cells, and eosinophils were significantly different between the high- and low-risk prognostic groups. In all, the six-gene SLC family signature is of satisfactory accuracy and generalizability for predicting overall survival in patients with LUAD. Furthermore, this prognostics signature is related to tumor immune status and distinct immune cell infiltrates in the tumor microenvironment.

Project description:BackgroundAlternative splicing (AS) plays critical roles in generating protein diversity and complexity. Dysregulation of AS underlies the initiation and progression of tumors. Machine learning approaches have emerged as efficient tools to identify promising biomarkers. It is meaningful to explore pivotal AS events (ASEs) to deepen understanding and improve prognostic assessments of lung adenocarcinoma (LUAD) via machine learning algorithms.MethodRNA sequencing data and AS data were extracted from The Cancer Genome Atlas (TCGA) database and TCGA SpliceSeq database. Using several machine learning methods, we identified 24 pairs of LUAD-related ASEs implicated in splicing switches and a random forest-based classifiers for identifying lymph node metastasis (LNM) consisting of 12 ASEs. Furthermore, we identified key prognosis-related ASEs and established a 16-ASE-based prognostic model to predict overall survival for LUAD patients using Cox regression model, random survival forest analysis, and forward selection model. Bioinformatics analyses were also applied to identify underlying mechanisms and associated upstream splicing factors (SFs).ResultsEach pair of ASEs was spliced from the same parent gene, and exhibited perfect inverse intrapair correlation (correlation coefficient = - 1). The 12-ASE-based classifier showed robust ability to evaluate LNM status of LUAD patients with the area under the receiver operating characteristic (ROC) curve (AUC) more than 0.7 in fivefold cross-validation. The prognostic model performed well at 1, 3, 5, and 10 years in both the training cohort and internal test cohort. Univariate and multivariate Cox regression indicated the prognostic model could be used as an independent prognostic factor for patients with LUAD. Further analysis revealed correlations between the prognostic model and American Joint Committee on Cancer stage, T stage, N stage, and living status. The splicing network constructed of survival-related SFs and ASEs depicts regulatory relationships between them.ConclusionIn summary, our study provides insight into LUAD researches and managements based on these AS biomarkers.

Dataset Information

Penetrating Exploration of Prognostic Correlations of the FKBP Gene Family with Lung Adenocarcinoma.

Publications

Penetrating Exploration of Prognostic Correlations of the FKBP Gene Family with Lung Adenocarcinoma.

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