The identification of metabolism-related subtypes and potential treatments for idiopathic pulmonary fibrosis

Abstract

Background: Idiopathic pulmonary fibrosis (IPF) is caused by aberrant repair because of alveolar epithelial injury and can only be effectively treated with several compounds. Several metabolism-related biomolecular processes were found to be involved in IPF. We aimed to identify IPF subtypes based on metabolism-related pathways and explore potential drugs for each subtype.Methods: Gene profiles and clinical information were obtained from the Gene Expression Omnibus (GEO) database (GSE70867 and GSE93606). The enrichment scores for 41 metabolism-related pathways, immune cells, and immune pathways were calculated using the Gene Set Variation Analysis (GSVA) package. The ConsensusClusterPlus package was used to cluster samples. Novel modules and hub genes were identified using weighted correlation network analysis (WGCNA). Receiver operating characteristic (ROC) and calibration curves were plotted, and decision curve analysis (DCA) were performed to evaluate the model in the training and validation cohorts. A connectivity map was used as a drug probe.Results: Two subtypes with significant differences in prognosis were identified based on the metabolism-related pathways. Subtype C1 had a poor prognosis, low metabolic levels, and a unique immune signature. CDS2, LCLAT1, GPD1L, AGPAT1, ALDH3A1, LAP3, ADH5, AHCYL2, and MDH1 were used to distinguish between the two subtypes. Finally, subtype-specific drugs, which can potentially treat IPF, were identified.Conclusion: The aberrant activation of metabolism-related pathways contributes to differential prognoses in patients with IPF. Collectively, our findings provide novel mechanistic insights into subtyping IPF based on the metabolism-related pathway and potential treatments, which would help clinicians provide subtype-specific individualized therapeutic management to patients.

Targeting glutamate metabolism in chronic lung diseases

“…Metabolomics, which focuses on small molecule metabolites such as amino acids (AAs), lipids, fatty acids and carbohydrates, holds great promise for identifying biomarkers for chronic lung diseases due to its high sensitivity, specificity and accuracy. [3][4][5][6] Maintaining metabolic homeostasis is crucial for normal cellular structure and function, as any imbalance can lead to various cell injuries and even cell death, ultimately affecting the integrity of lung function and contributing to the development of lung diseases. Current research is striving to incorporate metabolomics as part of a comprehensive approach for disease diagnosis and prognosis.…”

“…Despite important advances in therapy for these lung diseases, there remain unmet clinical needs for targeted and highly effective treatment. Metabolomics, which focuses on small molecule metabolites such as amino acids (AAs), lipids, fatty acids and carbohydrates, holds great promise for identifying biomarkers for chronic lung diseases due to its high sensitivity, specificity and accuracy 3–6 . Maintaining metabolic homeostasis is crucial for normal cellular structure and function, as any imbalance can lead to various cell injuries and even cell death, ultimately affecting the integrity of lung function and contributing to the development of lung diseases.…”

GPD1L As a prognostic biomarker associated with Treg immune-infiltration and lipid metabolism for Clear cell renal cell carcinoma

“…As a gene implicated in metabolism, GPD1L plays a crucial role in regulating energy metabolism and maintaining cellular homeostasis [5,6]. Dysfunction of GPD1L may be critical for the survival of tumor cells that lead to abnormal energy metabolism [7]. Several studies have reported that GPD1L can inhibit the progression of various types of cancer cells, including those found in oropharyngeal cancer, kidney cancer, lung adenocarcinoma, and colorectal cancer [8][9][10][11].…”