Purpose: pancreatic adenocarcinoma is the fourth leading cause of cancer related deaths due to its aggressive behavior and poor clinical outcome. There is a considerable variability in the frequency of serum tumor markers in cancer’ patients. We performed a metabolomics screening in patients diagnosed with pancreatic cancer. Experimental Design: Two targeted metabolomic assays were conducted on 40 serum samples of patients diagnosed with pancreatic cancer and 40 healthy controls. Multivariate methods and classification trees were performed. Materials and Methods: Sparse partial least squares discriminant analysis (SPLS-DA) was used to reduce the high dimensionality of a pancreatic cancer metabolomic dataset, differentiating between pancreatic cancer (PC) patients and healthy subjects. Using Random Forest analysis palmitic acid, 1,2-dioleoyl-sn-glycero-3-phospho-rac-glycerollanosterol, lignoceric acid, 1-monooleoyl-rac-glycerol, cholesterol 5α,6α epoxide, erucic acid and taurolithocholic acid (T-LCA), oleoyl-L-carnitine, oleanolic acid were identified among 206 metabolites as highly discriminating between disease states. Comparison between Receiver Operating Characteristic (ROC) curves for palmitic acid and CA 19-9 showed that the area under the ROC curve (AUC) of palmitic acid (AUC=1.000; 95% confidence interval) is significantly higher than CA 19-9 (AUC=0.963; 95% confidence interval: 0.896-1.000). Conclusion: Mass spectrometry-based metabolomic profiling of sera from pancreatic cancer patients and normal subjects showed significant alterations in the profiles of the metabolome of PC patients as compared to controls. These findings offer an information-rich matrix for discovering novel candidate biomarkers with diagnostic or prognostic potentials.

Di Gangi, I.M.; Mazza, T.; Fontana, A.; Copetti, M.; Fusilli, C.; Ippolito, A.; Mattivi, F.; Latiano, A.; Andriulli, A.; Vrhovsek, U.; Pazienza, V. (2016). Metabolomic profile in pancreatic cancer patients: a consensus-based approach to identify highly discriminating metabolites. ONCOTARGET, 7 (5): 5815-5829. doi: 10.18632/oncotarget.6808 handle: http://hdl.handle.net/10449/28089

Metabolomic profile in pancreatic cancer patients: a consensus-based approach to identify highly discriminating metabolites

Di Gangi, Iole Maria;Mattivi, Fulvio;Vrhovsek, Urska;
2016-01-01

Abstract

Purpose: pancreatic adenocarcinoma is the fourth leading cause of cancer related deaths due to its aggressive behavior and poor clinical outcome. There is a considerable variability in the frequency of serum tumor markers in cancer’ patients. We performed a metabolomics screening in patients diagnosed with pancreatic cancer. Experimental Design: Two targeted metabolomic assays were conducted on 40 serum samples of patients diagnosed with pancreatic cancer and 40 healthy controls. Multivariate methods and classification trees were performed. Materials and Methods: Sparse partial least squares discriminant analysis (SPLS-DA) was used to reduce the high dimensionality of a pancreatic cancer metabolomic dataset, differentiating between pancreatic cancer (PC) patients and healthy subjects. Using Random Forest analysis palmitic acid, 1,2-dioleoyl-sn-glycero-3-phospho-rac-glycerollanosterol, lignoceric acid, 1-monooleoyl-rac-glycerol, cholesterol 5α,6α epoxide, erucic acid and taurolithocholic acid (T-LCA), oleoyl-L-carnitine, oleanolic acid were identified among 206 metabolites as highly discriminating between disease states. Comparison between Receiver Operating Characteristic (ROC) curves for palmitic acid and CA 19-9 showed that the area under the ROC curve (AUC) of palmitic acid (AUC=1.000; 95% confidence interval) is significantly higher than CA 19-9 (AUC=0.963; 95% confidence interval: 0.896-1.000). Conclusion: Mass spectrometry-based metabolomic profiling of sera from pancreatic cancer patients and normal subjects showed significant alterations in the profiles of the metabolome of PC patients as compared to controls. These findings offer an information-rich matrix for discovering novel candidate biomarkers with diagnostic or prognostic potentials.
Pancreatic cancer
Metabolomics
Mass spectrometry
UHPLC
Palmitic acid
Biomarkers
Early diagnosis
Tumore al pancreas
Metabolomica
Spettrometria di massa
UHPLC
Acido palmitico
Biomarcatori
Diagnosi precoce
Settore CHIM/01 - CHIMICA ANALITICA
2016
Di Gangi, I.M.; Mazza, T.; Fontana, A.; Copetti, M.; Fusilli, C.; Ippolito, A.; Mattivi, F.; Latiano, A.; Andriulli, A.; Vrhovsek, U.; Pazienza, V. (2016). Metabolomic profile in pancreatic cancer patients: a consensus-based approach to identify highly discriminating metabolites. ONCOTARGET, 7 (5): 5815-5829. doi: 10.18632/oncotarget.6808 handle: http://hdl.handle.net/10449/28089
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