Dataset Information

Granulocyte colony-stimulating factor in bronchoalveolar lavage fluid is a potential biomarker for prognostic prediction of idiopathic pulmonary fibrosis.

ABSTRACT:

Background/aims

Neutrophilia is frequently observed in bronchoalveolar lavage fluid (BALF) of idiopathic pulmonary fibrosis (IPF) patients. Granulocyte colony-stimulating factor (G-CSF) is a potent neutrophil-activating glycoprotein. However, the clinical implications of G-CSF remain poorly understood.in patients with IPF. Therefore, we evaluated the relationship between the G-CSF concentration in BALF and the progression of fibrosis, including in terms of the decline in lung function and long-term survival rate.

Methods

G-CSF concentrations were measured in BALF using enzyme-linked immunosorbent assay (ELISA). The survival rate was estimated using Kaplan-Meier survival analyses.

Results

G-CSF protein levels were significantly higher in IPF (n = 87; 1.88 [0 to 5.68 pg/mL]), nonspecific interstitial pneumonia (n = 22; 0.58 [0 to 11.64 pg/mL]), and hypersensitivity pneumonitis (n = 19; 2.48 [0.46 to 5.71 pg/mL]) patients than in normal controls (n = 33; 0 [0 to 0.68 pg/mL]) (all p < 0.01). A receiver operating characteristic curve showed a difference in G-CSF levels between IPF and NC (area under the curve, 0.769): The G-CSF cut-off of 0.96 pg/mL indicated 84.9% specificity and 63.2% sensitivity for IPF. The survival rate was significantly lower in the group with G-CSF > 2.872 pg/mL than in the group with ≤ 2.872 pg/mL (hazard ratio, 2.69; p = 0.041). The annual decline in diffusing capacity of the lung for carbon monoxide was positively correlated with the G-CSF level (p = 0.018).

Conclusion

G-CSF may participate in the development of IPF and be useful for predicting the prognosis of IPF. Therefore, G-CSF should be analyzed in BALF, in addition to differential cell counts.

SUBMITTER: Lee JU

PROVIDER: S-EPMC9449205 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Granulocyte colony-stimulating factor in bronchoalveolar lavage fluid is a potential biomarker for prognostic prediction of idiopathic pulmonary fibrosis.

Lee Jong-Uk JU Choi Jae Sung JS Kim Min Kyung MK Min Sun A SA Park Jong-Sook JS Park Choon-Sik CS

The Korean journal of internal medicine 20220622 5

<h4>Background/aims</h4>Neutrophilia is frequently observed in bronchoalveolar lavage fluid (BALF) of idiopathic pulmonary fibrosis (IPF) patients. Granulocyte colony-stimulating factor (G-CSF) is a potent neutrophil-activating glycoprotein. However, the clinical implications of G-CSF remain poorly understood.in patients with IPF. Therefore, we evaluated the relationship between the G-CSF concentration in BALF and the progression of fibrosis, including in terms of the decline in lung function an ...[more]

PMID: 35730133

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Project description:Background: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive disease with unknown etiology and unfavorable prognosis. Ferroptosis is a form of regulated cell death with an iron-dependent way that is involved in the development of various diseases. Whereas the prognostic value of ferroptosis-related genes (FRGs) in IPF remains uncertain and needs to be further elucidated. Methods: The FerrDb database and the previous studies were screened to explore the FRGs. The data of patients with IPF were obtained from the GSE70866 dataset. Wilcoxon's test and univariate Cox regression analysis were applied to identify the FRGs that are differentially expressed between normal and patients with IPF and associated with prognosis. Next, a multigene signature was constructed by the least absolute shrinkage and selection operator (LASSO)-penalized Cox model in the training cohort and evaluated by using calibration and receiver operating characteristic (ROC) curves. Then, 30% of the dataset samples were randomly selected for internal validation. Finally, the potential function and pathways that might be affected by the risk score-related differently expressed genes (DEGs) were further explored. Results: A total of 183 FRGs were identified by the FerrDb database and the previous studies, and 19 of them were differentially expressed in bronchoalveolar lavage fluid (BALF) between IPF and healthy controls and associated with prognosis (p < 0.05). There were five FRGs (aconitase 1 [ACO1], neuroblastoma RAS viral (v-ras) oncogene homolog [NRAS], Ectonucleotide pyrophosphatase/phosphodiesterase 2 [ENPP2], Mucin 1 [MUC1], and ZFP36 ring finger protein [ZFP36]) identified as risk signatures and stratified patients with IPF into the two risk groups. The overall survival rate in patients with high risk was significantly lower than that in patients with low risk (p < 0.001). The calibration and ROC curve analysis confirmed the predictive capacity of this signature, and the results were further verified in the validation group. Risk score-related DEGs were found enriched in ECM-receptor interaction and focal adhesion pathways. Conclusion: The five FRGs in BALF can be used for prognostic prediction in IPF, which may contribute to improving the management strategies of IPF.

Project description:BackgroundIdiopathic pulmonary fibrosis (IPF) is a chronic and progressive condition with an unfavorable prognosis. A recent study has demonstrated that IPF patients exhibit characteristic alterations in the fatty acid metabolism in their lungs, suggesting an association with IPF pathogenesis. Therefore, in this study, we have explored whether the gene signature associated with fatty acid metabolism could be used as a reliable biological marker for predicting the survival of IPF patients.MethodsData on the fatty acid metabolism-related genes (FAMRGs) were extracted from databases like Kyoto Encyclopedia of Genes and Genomes (KEGG), Hallmark, and Reactome pathway. The GSE70866 dataset with information on IPF patients was retrieved from the Gene Expression Omnibus (GEO). Next, the consensus clustering method was used to identify novel molecular subgroups. Gene Set Enrichment Analysis (GSEA) was performed to understand the mechanisms involved. The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to evaluate the level of immune cell infiltration in the identified subgroups based on gene expression signatures of immune cells. Finally, the Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate Cox regression analysis were performed to develop a prognostic risk model.ResultsThe gene expression signature associated with fatty acid metabolism was used to create two subgroups with significantly different prognoses. GSEA reveals that immune-related pathways were significantly altered between the two subgroups, and the two subgroups had different metabolic characteristics. High infiltration of immune cells, mainly activated NK cells, monocytes, and activated mast cells, was observed in the subgroup with a poor prognosis. A risk model based on FAMRGs had an excellent ability to predict the prognosis of IPF. The nomogram constructed using the clinical features and the risk model could accurately predict the prognosis of IPF patients.ConclusionThe fatty acid metabolism-related gene expression signature could be used as a potential biological marker for predicting clinical outcomes and the level of infiltration of immune cells. This could eventually enhance the accuracy of the treatment of IPF patients.

Project description:BackgroundTripartite motif (TRIM) family genes get involved in the pathogenesis and development of various biological processes; however, the prognostic value of TRIM genes for idiopathic pulmonary fibrosis (IPF) needs to be explored.MethodsWe acquired gene expression based on bronchoalveolar lavage (BAL) cells and clinical data of three independent IPF cohorts in the GSE70866 dataset from the Gene expression omnibus (GEO) database. Differentially expressed TRIM genes (DETGs) between IPF patients and healthy donors were identified and used to establish a risk signature by univariate and multivariate Cox regression analysis in the training cohort. The risk signature was further validated in other IPF cohorts, and compared with previously published signatures. Moreover, we performed functional enrichment analysis to explore the potential mechanisms. Eventually, the quantitative real time PCR was conducted to validate the expressions of the key genes in BAL from 12 IPF patients and 12 non-IPF controls from our institution.ResultsWe identified 4 DETGs including TRIM7, MEFV, TRIM45 and TRIM47 significantly associated with overall survival (OS) of IPF patients (P < 0.05). A multiple stepwise Cox regression analysis was performed to construct a 4-TRIM-gene prognostic signature. We categorized IPF patients into one low-risk group and the other high-risk group as per the average risk value of the TRIM prognostic signature in the training and validation cohorts. The IPF individuals in the low-risk group demonstrated an obvious OS advantage compared with the high-risk one (P < 0.01). The time-dependent receiver operating characteristic approach facilitated the verification of the predictive value of the TRIM prognostic signature in the training and validation cohorts, compared with other published signatures. A further investigation of immune cells and IPF survival displayed that higher proportion of resting memory CD4+ T cells and resting mast cells harbored OS advantage over lower proportion, however lower proportion of neutrophils, activated dendritic cells and activated NK cells indicated worse prognosis.ConclusionThe TRIM family genes are significant for the prognosis of IPF and our signature could serve as a robust model to predict OS.

Dataset Information

Granulocyte colony-stimulating factor in bronchoalveolar lavage fluid is a potential biomarker for prognostic prediction of idiopathic pulmonary fibrosis.

Background/aims

Methods

Results

Conclusion

Publications

Granulocyte colony-stimulating factor in bronchoalveolar lavage fluid is a potential biomarker for prognostic prediction of idiopathic pulmonary fibrosis.

Similar Datasets

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