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Metabolomic profiles of hepatocellular carcinoma in a European prospective cohort.

Fages A, Duarte-Salles T, Stepien M, Ferrari P, Fedirko V, Pontoizeau C, Trichopoulou A, Aleksandrova K, Tjønneland A, Olsen A, Clavel-Chapelon F, Boutron-Ruault MC, Severi G, Kaaks R, Kuhn T, Floegel A, Boeing H, Lagiou P, Bamia C, Trichopoulos D, Palli D, Pala V, Panico S, Tumino R, Vineis P, Bueno-de-Mesquita HB, Peeters PH, Weiderpass E, Agudo A, Molina-Montes E, Huerta JM, Ardanaz E, Dorronsoro M, Sjöberg K, Ohlsson B, Khaw KT, Wareham N, Travis RC, Schmidt JA, Cross A, Gunter M, Riboli E, Scalbert A, Romieu I, Elena-Herrmann B, Jenab M - BMC Med (2015)

Bottom Line: A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed.Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk.Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer.

View Article: PubMed Central - PubMed

Affiliation: Institut des Sciences Analytiques, Centre de RMN à très hauts champs, CNRS/ENS Lyon/UCB Lyon-1, Université de Lyon, 5 rue de la Doua, 69100, Villeurbanne, France.

ABSTRACT

Background: Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is difficult to diagnose and has limited treatment options with a low survival rate. Aside from a few key risk factors, such as hepatitis, high alcohol consumption, smoking, obesity, and diabetes, there is incomplete etiologic understanding of the disease and little progress in identification of early risk biomarkers.

Methods: To address these aspects, an untargeted nuclear magnetic resonance metabolomic approach was applied to pre-diagnostic serum samples obtained from first incident, primary HCC cases (n = 114) and matched controls (n = 222) identified from amongst the participants of a large European prospective cohort.

Results: A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed. Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk. The influence of hepatitis infection and potential liver damage was assessed, and further analyses were made to distinguish patterns of early or later diagnosis.

Conclusion: Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer.

No MeSH data available.


Related in: MedlinePlus

Analyses stratified by the interval between recruitment into the EPIC cohort and clinical diagnosis of HCC (<2 years after recruitment vs. ≥2 years after recruitment). (a) O-PLS score plot including HCC cases that were diagnosed <2 years (n = 22) after blood collection and matched controls (n = 43), R2 = 45 % and Q2 = 33 %, and the metabolic signature colored for correlation after significance to ANOVA tests (Benjamini-Hochberg multiple corrected). (b) O-PLS score plot including HCC cases that were diagnosed ≥2 years after blood collection (n = 92) and their matched controls (n = 179), R2 = 27 % and Q2 = 16 %, and the metabolic signature colored for correlation after significance to ANOVA tests (Benjamini-Hochberg multiple corrected). (c) ROC analyses for each stratified group including AFP, liver function score, O-PLS score, O-PLS cross validated (CV) status, and a combination between O-PLS CV status and AFP or liver function score. The ROC curves of the O-PLS CV status and the O-PLS CV status + AFP are almost overlapped for the ROC analysis performed on cases diagnosed <2 years. The characteristics of each model are presented in Table 3. The validations of the O-PLS models are presented in Additional file 1: Figure S3. 1, CH3 bond of lipids mainly VLDL; 2, Leucine; 3, Isoleucine; 4, Valine; 5, Propylene glycol; 6, Ethanol; 7, CH2 bond of lipids; 8, CH2-CH2-COOC bond of lipids; 9, Acetate; 10, CH2-CH = bond of lipids; 11, N-acetyl glycoproteins; 12, Acetone and CH2-CH2-COOC bond of lipids; 13, Glutamate; 14, Glutamine; 15, Citrate; 16 = CH-CH2-CH = bond of lipids; 17, Choline; 18, Glucose; 19, Lipid O-CH2; 20, Mannose and lipids; 21, CH = CH bond of lipids; 22, Tyrosine; 23, Phenylalanine
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Fig4: Analyses stratified by the interval between recruitment into the EPIC cohort and clinical diagnosis of HCC (<2 years after recruitment vs. ≥2 years after recruitment). (a) O-PLS score plot including HCC cases that were diagnosed <2 years (n = 22) after blood collection and matched controls (n = 43), R2 = 45 % and Q2 = 33 %, and the metabolic signature colored for correlation after significance to ANOVA tests (Benjamini-Hochberg multiple corrected). (b) O-PLS score plot including HCC cases that were diagnosed ≥2 years after blood collection (n = 92) and their matched controls (n = 179), R2 = 27 % and Q2 = 16 %, and the metabolic signature colored for correlation after significance to ANOVA tests (Benjamini-Hochberg multiple corrected). (c) ROC analyses for each stratified group including AFP, liver function score, O-PLS score, O-PLS cross validated (CV) status, and a combination between O-PLS CV status and AFP or liver function score. The ROC curves of the O-PLS CV status and the O-PLS CV status + AFP are almost overlapped for the ROC analysis performed on cases diagnosed <2 years. The characteristics of each model are presented in Table 3. The validations of the O-PLS models are presented in Additional file 1: Figure S3. 1, CH3 bond of lipids mainly VLDL; 2, Leucine; 3, Isoleucine; 4, Valine; 5, Propylene glycol; 6, Ethanol; 7, CH2 bond of lipids; 8, CH2-CH2-COOC bond of lipids; 9, Acetate; 10, CH2-CH = bond of lipids; 11, N-acetyl glycoproteins; 12, Acetone and CH2-CH2-COOC bond of lipids; 13, Glutamate; 14, Glutamine; 15, Citrate; 16 = CH-CH2-CH = bond of lipids; 17, Choline; 18, Glucose; 19, Lipid O-CH2; 20, Mannose and lipids; 21, CH = CH bond of lipids; 22, Tyrosine; 23, Phenylalanine

Mentions: Figure 4 presents the O-PLS and ROC analyses stratified by lag time between blood collection and diagnosis. The metabolic signature of HCC cases diagnosed within 2 years after blood collection is characterized by (1) higher levels in AAA and glutamate, and (2) lower levels in unsaturated lipids and choline while in addition, the metabolic signature of HCC diagnosed later (≥2 years) presented (1) higher levels in glucose, ethanol, and propylene glycol and (2) lower levels in BCAA and N-acetyl glycoproteins. Among the cases diagnosed <2 years from recruitment, the AUC of ROC curves from the O-PLS metabolic signature and from O-PLS CV data were 93 % and 82 %, respectively (Fig. 4c).Fig. 4


Metabolomic profiles of hepatocellular carcinoma in a European prospective cohort.

Fages A, Duarte-Salles T, Stepien M, Ferrari P, Fedirko V, Pontoizeau C, Trichopoulou A, Aleksandrova K, Tjønneland A, Olsen A, Clavel-Chapelon F, Boutron-Ruault MC, Severi G, Kaaks R, Kuhn T, Floegel A, Boeing H, Lagiou P, Bamia C, Trichopoulos D, Palli D, Pala V, Panico S, Tumino R, Vineis P, Bueno-de-Mesquita HB, Peeters PH, Weiderpass E, Agudo A, Molina-Montes E, Huerta JM, Ardanaz E, Dorronsoro M, Sjöberg K, Ohlsson B, Khaw KT, Wareham N, Travis RC, Schmidt JA, Cross A, Gunter M, Riboli E, Scalbert A, Romieu I, Elena-Herrmann B, Jenab M - BMC Med (2015)

Analyses stratified by the interval between recruitment into the EPIC cohort and clinical diagnosis of HCC (<2 years after recruitment vs. ≥2 years after recruitment). (a) O-PLS score plot including HCC cases that were diagnosed <2 years (n = 22) after blood collection and matched controls (n = 43), R2 = 45 % and Q2 = 33 %, and the metabolic signature colored for correlation after significance to ANOVA tests (Benjamini-Hochberg multiple corrected). (b) O-PLS score plot including HCC cases that were diagnosed ≥2 years after blood collection (n = 92) and their matched controls (n = 179), R2 = 27 % and Q2 = 16 %, and the metabolic signature colored for correlation after significance to ANOVA tests (Benjamini-Hochberg multiple corrected). (c) ROC analyses for each stratified group including AFP, liver function score, O-PLS score, O-PLS cross validated (CV) status, and a combination between O-PLS CV status and AFP or liver function score. The ROC curves of the O-PLS CV status and the O-PLS CV status + AFP are almost overlapped for the ROC analysis performed on cases diagnosed <2 years. The characteristics of each model are presented in Table 3. The validations of the O-PLS models are presented in Additional file 1: Figure S3. 1, CH3 bond of lipids mainly VLDL; 2, Leucine; 3, Isoleucine; 4, Valine; 5, Propylene glycol; 6, Ethanol; 7, CH2 bond of lipids; 8, CH2-CH2-COOC bond of lipids; 9, Acetate; 10, CH2-CH = bond of lipids; 11, N-acetyl glycoproteins; 12, Acetone and CH2-CH2-COOC bond of lipids; 13, Glutamate; 14, Glutamine; 15, Citrate; 16 = CH-CH2-CH = bond of lipids; 17, Choline; 18, Glucose; 19, Lipid O-CH2; 20, Mannose and lipids; 21, CH = CH bond of lipids; 22, Tyrosine; 23, Phenylalanine
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Fig4: Analyses stratified by the interval between recruitment into the EPIC cohort and clinical diagnosis of HCC (<2 years after recruitment vs. ≥2 years after recruitment). (a) O-PLS score plot including HCC cases that were diagnosed <2 years (n = 22) after blood collection and matched controls (n = 43), R2 = 45 % and Q2 = 33 %, and the metabolic signature colored for correlation after significance to ANOVA tests (Benjamini-Hochberg multiple corrected). (b) O-PLS score plot including HCC cases that were diagnosed ≥2 years after blood collection (n = 92) and their matched controls (n = 179), R2 = 27 % and Q2 = 16 %, and the metabolic signature colored for correlation after significance to ANOVA tests (Benjamini-Hochberg multiple corrected). (c) ROC analyses for each stratified group including AFP, liver function score, O-PLS score, O-PLS cross validated (CV) status, and a combination between O-PLS CV status and AFP or liver function score. The ROC curves of the O-PLS CV status and the O-PLS CV status + AFP are almost overlapped for the ROC analysis performed on cases diagnosed <2 years. The characteristics of each model are presented in Table 3. The validations of the O-PLS models are presented in Additional file 1: Figure S3. 1, CH3 bond of lipids mainly VLDL; 2, Leucine; 3, Isoleucine; 4, Valine; 5, Propylene glycol; 6, Ethanol; 7, CH2 bond of lipids; 8, CH2-CH2-COOC bond of lipids; 9, Acetate; 10, CH2-CH = bond of lipids; 11, N-acetyl glycoproteins; 12, Acetone and CH2-CH2-COOC bond of lipids; 13, Glutamate; 14, Glutamine; 15, Citrate; 16 = CH-CH2-CH = bond of lipids; 17, Choline; 18, Glucose; 19, Lipid O-CH2; 20, Mannose and lipids; 21, CH = CH bond of lipids; 22, Tyrosine; 23, Phenylalanine
Mentions: Figure 4 presents the O-PLS and ROC analyses stratified by lag time between blood collection and diagnosis. The metabolic signature of HCC cases diagnosed within 2 years after blood collection is characterized by (1) higher levels in AAA and glutamate, and (2) lower levels in unsaturated lipids and choline while in addition, the metabolic signature of HCC diagnosed later (≥2 years) presented (1) higher levels in glucose, ethanol, and propylene glycol and (2) lower levels in BCAA and N-acetyl glycoproteins. Among the cases diagnosed <2 years from recruitment, the AUC of ROC curves from the O-PLS metabolic signature and from O-PLS CV data were 93 % and 82 %, respectively (Fig. 4c).Fig. 4

Bottom Line: A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed.Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk.Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer.

View Article: PubMed Central - PubMed

Affiliation: Institut des Sciences Analytiques, Centre de RMN à très hauts champs, CNRS/ENS Lyon/UCB Lyon-1, Université de Lyon, 5 rue de la Doua, 69100, Villeurbanne, France.

ABSTRACT

Background: Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is difficult to diagnose and has limited treatment options with a low survival rate. Aside from a few key risk factors, such as hepatitis, high alcohol consumption, smoking, obesity, and diabetes, there is incomplete etiologic understanding of the disease and little progress in identification of early risk biomarkers.

Methods: To address these aspects, an untargeted nuclear magnetic resonance metabolomic approach was applied to pre-diagnostic serum samples obtained from first incident, primary HCC cases (n = 114) and matched controls (n = 222) identified from amongst the participants of a large European prospective cohort.

Results: A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed. Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk. The influence of hepatitis infection and potential liver damage was assessed, and further analyses were made to distinguish patterns of early or later diagnosis.

Conclusion: Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer.

No MeSH data available.


Related in: MedlinePlus