Integrative Pathway Analysis of Metabolic Signature in Bladder Cancer: A Linkage to The Cancer Genome Atlas Project and Prediction of Survival

Abstract

PurposeWe used targeted mass spectrometry to study the metabolic fingerprint of urothelial cancer and determine whether the biochemical pathway analysis gene signature would have a predictive value in independent cohorts of patients with bladder cancer.Materials and MethodsPathologically evaluated, bladder derived tissues, including benign adjacent tissue from 14 patients and bladder cancer from 46, were analyzed by liquid chromatography based targeted mass spectrometry. Differential metabolites associated with tumor samples in comparison to benign tissue were identified by adjusting the p values for multiple testing at a false discovery rate threshold of 15%. Enrichment of pathways and processes associated with the metabolic signature were determined using the GO (Gene Ontology) Database and MSigDB (Molecular Signature Database). Integration of metabolite alterations with transcriptome data from TCGA (The Cancer Genome Atlas) was done to identify the molecular signature of 30 metabolic genes. Available outcome data from TCGA portal were used to determine the association with survival.ResultsWe identified 145 metabolites, of which analysis revealed 31 differential metabolites when comparing benign and tumor tissue samples. Using the KEGG (Kyoto Encyclopedia of Genes and Genomes) Database we identified a total of 174 genes that correlated with the altered metabolic pathways involved. By integrating these genes with the transcriptomic data from the corresponding TCGA data set we identified a metabolic signature consisting of 30 genes. The signature was significant in its prediction of survival in 95 patients with a low signature score vs 282 with a high signature score (p = 0.0458).ConclusionsTargeted mass spectrometry of bladder cancer is highly sensitive for detecting metabolic alterations. Applying transcriptome data allows for integration into larger data sets and identification of relevant metabolic pathways in bladder cancer progression.

Large‐scale profiling of serum metabolites in African American and European American patients with bladder cancer reveals metabolic pathways associated with patient survival

“…[11][12][13] As markers, metabolites could be used to improve individual risk prediction in BLCA. [11][12][13] As markers, metabolites could be used to improve individual risk prediction in BLCA.…”

“…Metabolomic studies have now begun to identify disease-specific metabolic signatures and correlate them with clinical outcomes. [11][12][13] As markers, metabolites could be used to improve individual risk prediction in BLCA. Mass spectrometry (MS), in combination with various liquid chromatography methods, has been previously applied to study BLCA-induced metabolomic alterations in tissues, 11,14-17 urine, [18][19][20][21] and serum.…”

Knockdown of SIRT1 Suppresses Bladder Cancer Cell Proliferation and Migration and Induces Cell Cycle Arrest and Antioxidant Response through FOXO3a-Mediated Pathways

“…A horrible threat as it is to human health, its underlying mechanism, especially its metabolic alterations, has not been fully clarified yet [3–5]. …”

Innovative methods for biomarker discovery in the evaluation and development of cancer precision therapies

“…These signatures which can be detected via differing metabolic profiling modalities generally indicate a modulation in the metabolic process, with levels of amino acids, choline derivatives, tricarboxylic acid cycle intermediates, and among other metabolites being altered [101]. Distinct metabolic profiling signatures with potential predictive and prognostic value have been identified for colon cancer, ovarian cancer [6], breast cancer [102], and bladder cancer [103]. In glioma, mutations affecting isocitrate dehydrogenase (IDH) are associated with a unique metabolic signature [104].…”