Characterization of the fatty acid metabolism in colorectal cancer to guide clinical therapy
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ABSTRACT:
SUBMITTER: Ding C
PROVIDER: S-EPMC7941088 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundLung adenocarcinoma (LUAD) is a common cancer with a bad prognosis. Numerous investigations have indicated that the metabolism of fatty acids plays an important role in the occurrence, progression, and treatment of cancer. Consequently, the objective of the current investigation was to elucidate the role and prognostic significance of genes associated with fatty acid metabolism in patients diagnosed with LUAD.Materials and methodsThe data files were acquired from The Cancer Genome Atlas database and GSE31210 dataset. Univariate Cox and least absolute shrinkage and selection operator regression analyses were conducted to establish a prognostic risk scoring model depending on fatty acid metabolism-associated genes to predict the prognosis of patients with LUAD. pRRophetic algorithm was utilized to evaluate the potential therapeutic agents. Gene set variation analysis combined with cell-type identification based on the estimation of relative subsets of RNA transcript and single-sample gene set enrichment analysis was used to determine the association between immune cell infiltration and risk score. Tumor immune dysfunction and exclusion algorithm was employed to predict immunotherapeutic sensitivity.ResultsTo forecast the prognosis of patients with LUAD, a risk scoring model based on five genes associated with fatty acid metabolism was developed, including LDHA, ALDOA, CYP4B1, DPEP2, and HPGDS. Using the risk score algorithm, patients were divided into higher- and lower-risk categories. Patients classified as minimal risk showed superior prognosis than those with elevated risk. In addition, individuals in the higher-risk group had a proclivity toward chemoresistance and amenable to immunotherapy.ConclusionThe prognostic risk scoring model aids in estimating the prognosis of LUAD patients. It may also provide new insights into LUAD carcinogenesis and therapeutic strategies.
| S-EPMC9784226 | biostudies-literature
Project description:BackgroundBreast cancer (BRCA) ranks as a leading cause of cancer death in women worldwide. Glucose metabolism is a noticeable characteristic of the occurrence of malignant tumors. In this study, we aimed to construct a novel glycometabolism-related gene (GRG) signature to predict overall survival (OS), immune infiltration and therapeutic response in BRCA patients.Materials and methodsThe mRNA sequencing and corresponding clinical data of BRCA patients were obtained from public cohorts. Lasso regression was applied to establish a GRG signature. The immune infiltration was evaluated with the ESTIMATE and CIBERSORT algorithms. The drug sensitivity was estimated using the value of IC50, and further forecasted the therapeutic response of each patient. The candidate target was selected in Cytoscape. A nomogram was constructed via the R package of "rms".ResultsWe constructed a six-GRG signature based on CACNA1H, CHPF, IRS2, NT5E, SDC1 and ATP6AP1, and the high-risk patients were correlated with poorer OS (P = 2.515 × 10-7). M2 macrophage infiltration was considerably superior in high-risk patients, and CD8+ T cell infiltration was significantly higher in low-risk patients. Additionally, the high-risk group was more sensitive to Lapatinib. Fortunately, SDC1 was recognized as candidate target and patients had a better OS in the low-SDC1 group. A nomogram integrating the GRG signature was developed, and calibration curves were consistent between the actual and predicted OS.ConclusionsWe identified a novel GRG signature complementing the present understanding of the targeted therapy and immune biomarker in breast cancer. The GRGs may provide fresh insights for individualized management of BRCA patients.
| S-EPMC9580338 | biostudies-literature
Project description:BackgroundBladder cancer is one of the most common malignancies of the urinary system with an unfavorable prognosis. More and more studies have suggested that lipid metabolism could influence the progression and treatment of tumors. However, there are few studies exploring the relationship between lipid metabolism and bladder cancer. This study aimed to explore the roles that lipid metabolism-related genes play in patients with bladder cancer.MethodsTCGA_BLCA cohort and GSE13507 cohort were included in this study, and transcriptional and somatic mutation profiles of 309 lipid metabolism-related genes were analyzed to discover the critical lipid metabolism-related genes in the incurrence and progression of bladder cancer. Furthermore, the TCGA_BLCA cohort was randomly divided into training set and validation set, and the GSE13507 cohort was served as an external independent validation set. We performed the LASSO regression and multivariate Cox regression in training set to develop a prognostic signature and further verified this signature in TCGA_BLCA validation set and GSE13507 external validation set. Finally, we systematically investigated the association between this signature and tumor microenvironment, drug response, and potential functions and then verified the differential expression status of signature genes in the protein level by immunohistochemistry.ResultsA novel 6-lipidmetabolism-related gene signature was identified and validated, and this risk score model could predict the prognosis of patients with bladder cancer. In addition, the prognostic model was tightly related to immune cell infiltration and tumor mutation burden. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) showed that mTOR signaling pathway, G2M checkpoint, fatty acid metabolism, and hypoxia were enriched in patients in the high-risk score groups. Furthermore, 3 therapies specific for bladder cancer patients in different risk scores were identified.Conclusions. In conclusion, we investigated the lipid metabolism-related genes in bladder cancer through comprehensive bioinformatic analysis. A novel 6-gene signature associated with lipid metabolism for predicting the outcomes of patients with bladder cancer was conducted and validated. Furthermore, the risk score model could be utilized to indicate the choice of therapy in bladder cancer.
| S-EPMC9484922 | biostudies-literature
Project description:BackgroundLung adenocarcinoma (LUAD) has a very high morbidity and mortality rate, and its pathogenesis and treatment are still in the exploratory stage. Fatty acid metabolism plays a significant role in tumorigenesis, progression, and immune regulation. However, the gene expression of fatty acid metabolism in patients with LUAD and its relationship with prognosis remain unclear.MethodsWe collected 309 fatty acid metabolism-related genes, established a LUAD risk model based on The Cancer Genome Atlas (TCGA) using Least Absolute Shrinkage Selection Operator (LASSO) regression analysis, and divided LUAD patients into high-risk and low-risk groups, which were further validated using the Gene Expression Omnibus (GEO) database. The nomogram, principal component analysis (PCA), and receiver operating characteristic (ROC) curves showed that the model had the best predictive performance. The ROC curves and calibration plots confirmed that the nomogram had good predictive power. We further analyzed the differences in clinical characteristics, immune cell infiltration, immune-related functions, chemotherapy drug sensitivity, and immunotherapy efficacy between the high-risk and low-risk groups. We also analyzed the enrichment pathways and protein-protein interaction (PPI) networks of different genes in the high-risk and low-risk groups to screen for target genes and further explored the correlation between target genes and differences in survival prognosis, clinical characteristics, gene mutations, and immune cells.ResultsRisk score and staging are independent prognostic factors for patients with LUAD. The high-risk group had lower immune cell infiltration, was more sensitive to chemotherapeutic agents, and had a poorer survival prognosis. We also obtained three pivotal genes with poor survival prognosis in the high expression group, which were strongly associated with clinical symptoms and immune cells.ConclusionRisk score and staging are independent prognostic factors for patients with LUAD. The high-risk group had lower immune cell infiltration, was more sensitive to chemotherapeutic agents, and had a poorer survival prognosis. We also obtained three survival prognosis-associated target genes that are closely associated with clinical symptoms and immune cells and may be potential targets for immune-targeted therapy in LUAD.
| S-EPMC9289740 | biostudies-literature
Project description:Colorectal cancer (CRC) is a leading cause of cancer death worldwide. Epidemiological risk factors for CRC included dietary fat intake; consequently, the role of genes in the fatty acid biosynthesis and metabolism pathways is of particular interest. Moreover, hyperlipidaemia has been associated with different type of cancer and serum lipid levels could be affected by genetic factors, including polymorphisms in the lipid metabolism pathway. The aim of this study is to assess the association between single-nucleotide polymorphisms (SNPs) in fatty acid metabolism genes, serum lipid levels, body mass index (BMI) and dietary fat intake and CRC risk; 30 SNPs from 8 candidate genes included in fatty acid biosynthesis and metabolism pathways were genotyped in 1780 CRC cases and 1864 matched controls from the Molecular Epidemiology of Colorectal Cancer study. Information on clinicopathological characteristics, lifestyle and dietary habits were also obtained. Logistic regression and association analysis were conducted. Several LIPC (lipase, hepatic) polymorphisms were found to be associated with CRC risk, although no particular haplotype was related to CRC. The SNP rs12299484 showed an association with CRC risk after Bonferroni correction. We replicate the association between the T allele of the LIPC SNP rs1800588 and higher serum high-density lipoprotein levels. Weak associations between selected polymorphism in the LIPC and PPARG genes and BMI were observed. A path analysis based on structural equation modelling showed a direct effect of LIPC gene polymorphisms on colorectal carcinogenesis as well as an indirect effect mediated through serum lipid levels. Genetic polymorphisms in the hepatic lipase gene have a potential role in colorectal carcinogenesis, perhaps though the regulation of serum lipid levels.
| S-EPMC3269001 | biostudies-literature
Project description:High-grade serous ovarian cancer (HGSOC) is a heterogeneous cancer characterized by high relapse rate. Approximately 80% of women are diagnosed with late-stage disease, and 15–25% of patients experience primary treatment resistance. Ovarian cancer brings tremendous suffering and is the most malignant type in all gynecologic malignancies. Metabolic reprogramming in tumor microenvironment (TME), especially fatty acid metabolism, has been identified to play a crucial role in cancer prognosis. Yet, the underlying mechanism of fatty acid metabolism on ovarian cancer progression is severely understudied. Recently, studies have demonstrated the role of fatty acid metabolism reprogramming in immune cells, but their roles on cancer cell metastasis and cancer immunotherapy response are poorly characterized. Here, we reported that the fatty acid–related genes are aberrantly varied between ovarian cancer and normal samples. Using samples in publicly databases and bio-informatic analyses with fatty acid–related genes, we disentangled that cancer cases can be classified into high- and low-risk groups related with prognosis. Furthermore, the nomogram model was constructed to predict the overall survival. Additionally, we reported that different immune cells infiltration was presented between groups, and immunotherapy response differed in two groups. Results showed that our signature may have good prediction value on immunotherapy efficacy, especially for anti–PD-1 and anti–CTLA-4. Our study systematically marked the critical association between cancer immunity in TME and fatty acid metabolism, and bridged immune phenotype and metabolism programming in tumors, thereby constructed the metabolic-related prognostic model and help to understand the underlying mechanism of immunotherapy response.
| S-EPMC9577003 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is a prevalent malignancy and there is a lack of effective biomarkers for HCC diagnosis. Living organisms are complex, and different omics molecules interact with each other to implement various biological functions. Genomics and metabolomics, which are the top and bottom of systems biology, play an important role in HCC clinical management. Fatty acid metabolism is associated with malignancy, prognosis, and immune phenotype in cancer, which is a potential hallmark in malignant tumors. In this study, the genes and metabolites related to fatty acid metabolism were thoroughly investigated by a dynamic network construction algorithm named EWS-DDA for the early diagnosis and prognosis of HCC. Three gene ratios and eight metabolite ratios were identified by EWS-DDA as potential biomarkers for HCC clinical management. Further analysis using biological analysis, statistical analysis and document validation in the discovery and validation sets suggested that the selected potential biomarkers had great clinical prognostic value and helped to achieve effective early diagnosis of HCC. Experimental results suggested that in-depth evaluation of fatty acid metabolism from different omics viewpoints can facilitate the further understanding of pathological alterations associated with HCC characteristics, improving the performance of early diagnosis and clinical prognosis.
| S-EPMC10728109 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2016-12-31 | GSE51244 | GEO
Project description:Metastasis is the most common cause of death in colorectal cancer patients. Fatty acid synthase (FASN) and sphingosine kinase-1 and -2 (SPHK1 and 2) are overexpressed in many cancers, including colorectal cancer. However, the contribution of FASN-mediated upregulation of sphingolipid metabolism to colorectal cancer metastasis and the potential of these pathways as targets for therapeutic intervention remain unknown. This study determined that sphingosine kinases (SPHK) are overexpressed in colorectal cancer as compared with normal mucosa. FASN expression significantly correlated with SPHK2 expression in data sets from The Cancer Genome Atlas (TCGA) and a colorectal cancer tumor microarray. FASN, SPHK1, and SPHK2 colocalized within invadopodia of primary colorectal cancer cells. Moreover, FASN inhibition decreased SPHK2 expression and the levels of dihydrosphingosine 1-phosphate (DH-S1P) and sphingosine 1-phosphate (S1P) in colorectal cancer cells and tumor tissues. Inhibition of FASN using TVB-3664 and sphingolipid metabolism using FTY-720 significantly inhibited the ability of primary colorectal cancer cells to proliferate, migrate, form focal adhesions, and degrade gelatin. Inhibition of the FASN/SPHK/S1P axis was accompanied by decreased activation of p-MET, p-FAK, and p-PAX. S1P treatment rescued FASN-mediated inhibition of these proteins, suggesting that FASN promotes metastatic properties of colorectal cancer cells, in part, through an increased sphingolipid metabolism. These data demonstrate that upregulation of the FASN/SPHK/S1P axis promotes colorectal cancer progression by enhancing proliferation, adhesion, and migration. IMPLICATIONS: This study provides a strong rationale for further investigation of the interconnection of de novo lipogenesis and sphingolipid metabolism that could potentially lead to the identification of new therapeutic targets and strategies for colorectal cancer.
| S-EPMC6318071 | biostudies-literature
Project description:Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Fatty acid metabolism takes part in malignancy progression. However, the roles fatty acid metabolism plays in LUAD are still unclear. Methods: The transcriptomic and clinical data of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were extracted. ssGSEA, WGCNA, univariable Cox regression, and LASSO Cox regression analyses were performed to identify the fatty acid metabolism-related genes which influenced the overall survival (OS) and build a fatty acid-related risk score (FARS) model. A nomogram was established based on the FARS and other clinicopathological features, and ROC and calibration plots were used to validate the prediction accuracy. The tumor microenvironment (TME) of patients with high and low FARS was compared. Results: A total of 38 genes were identified to be independently related to the survival outcome and put into a FARS model. High FARS patients exhibited significantly worse OS. The nomogram included the FARS and pathological stage, and the AUC of the nomogram predicting 1-, 2-, 3-, 4-, and 5-year OS was 0.789, 0.807, 0.798, 0.809, and 0.753, respectively. Calibration plots also indicated good accuracy. Moreover, the samples of the high FARS had higher expression of PDL1. Conclusion: We constructed a FARS model which could accurately predict the survival outcome of the LUAD patients. The genes of the FARS are related to the tumor microenvironment and patients with high FARS can potentially benefit more from anti-PD1/PDL1 immunotherapy. In addition, the mechanisms of the genes in the FARS affecting prognosis are worthy of further research to develop new gene-targeted drugs.
| S-EPMC9329533 | biostudies-literature