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Metabolomics biomarkers of hepatocellular carcinoma in a prospective cohort of patients with cirrhosis

ABSTRACT:

Surveillance for hepatocellular carcinoma (HCC) with biannual ultrasound and serum alpha-fetoprotein, is recommended in patients with cirrhosis. However, its effectiveness for the detection of early-stage tumors is limited due to inadequate risk stratification and suboptimal performance of the current screening modalities. We developed a multi-center prospective cohort of patients with cirrhosis undergoing surveillance with contrast-enhanced MRI, and applied global untargeted metabolomics to 612 longitudinal samples collected from 203 patients. Among them, 37 developed HCC during follow-up. Linear mixed-effects models identified 150 metabolites among the 1263 detected, with significant abundance changes in serum samples collected prior to HCC diagnosis (Cases) compared to serum samples collected from patients who didn’t develop HCC during follow-up (Controls). The largest increases were observed for tauro-conjugated bile acids and gamma-glutamyl amino acids. The largest decreases were observed for derivatives of the bile acid deoxycholate, androgenic steroids, and acyl cholines. Using logistic regression analysis, 7 amino acids including serine and alanine, had stronger associations with HCC risk than AFP. The strongest protective effects were observed for N-acetylglycine and glycerophosphorylcholine (GPC). Analysis of serum samples collected after HCC treatment identified a reverse phenotype for metabolites associated with metabolism of amino acids, bile acids and purine & pyrimidine. Random forest machine learning algorithm using the 150 metabolites together with age, gender, PNPLA3 rs738409 and TMS6SF2 rs58542926 SNPs, identified 18 variables giving optimal model performance. Among them, N-acetylglycine, palmitoloelylcholine, GPC and alanine had better AUCs than AFP in discriminating between Cases and Controls. When restricting Cases to serum samples collected within 1 year prior to HCC diagnosis (Cases-12M), additional metabolites were identified, including several microbiota-derived metabolites. Random forest machine learning algorithm identified 20 top variables giving optimal model performance. The combination of the top 6 variables (AFP, 6-bromotryptophan, N-acetylglycine, salicyluric glucuronide, cortisol 21-sulfate and age) had good performance in discriminating Cases-12M from Controls (AUC=0.88 [0.82-0.94]). Finally, 28 of the 150 metabolites distinguished Cases with LIRAD-3 hepatic lesions who developed HCC during follow-up (Cases-LR3) from Controls with LIRAD-3 lesions who did not develop HCC during follow-up (Controls-LR3). Remarkably, the abundance of 7 acyl-cholines, GPC and GPC-related lysophospholipids were strongly reduced in Cases-LR3 compared to Controls-LR3. Altogether, this comprehensive study identified N-acetylglycine, amino acids, bile acids and choline-derived metabolites as main biomarkers of HCC risk. This study also revealed an important contribution of microbiota-derived metabolites to HCC development.

INSTRUMENT(S): Q Exactive

SUBMITTER: Laura Beretta Zachary Morgan

PROVIDER: MTBLS8764 | MetaboLights | 2024-05-09

REPOSITORIES: MetaboLights

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Project description:Although hepatocellular carcinoma (HCC) has been subjected to continuous investigation and its symptoms are well-known, early stage diagnosis of this disease remains difficult and the survival rate after diagnosis is typically very low (3−5%). Early and accurate detection of metabolic changes in the sera of patients with liver cirrhosis can help improve the prognosis of HCC and lead to a better understanding of its mechanism at the molecular level, thus providing patients with in-time treatment of the disease. In this study, we compared metabolite levels in sera of 40 HCC patients and 49 cirrhosis patients from Egypt by using ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometer (UPLC-QTOF MS). Following data preprocessing, the most relevant ions in distinguishing HCC cases from cirrhotic controls are selected by statistical methods. Putative metabolite identifications for these ions are obtained through mass-based database search. The identities of some of the putative identifications are verified by comparing their MS/MS fragmentation patterns and retention times with those from authentic compounds. Finally, the serum samples are reanalyzed for quantitation of selected metabolites as candidate biomarkers of HCC. This quantitation was performed using isotope dilution by selected reaction monitoring (SRM) on a triple quadrupole linear ion trap (QqQLIT) coupled to UPLC. Statistical analysis of the UPLC-QTOF data identified 274 monoisotopic ion masses with statistically significant differences in ion intensities between HCC cases and cirrhotic controls. Putative identifications were obtained for 158 ions by mass based search against databases. We verified the identities of selected putative identifications including glycholic acid (GCA), glycodeoxycholic acid (GDCA), 3β, 6β-dihydroxy-5β-cholan-24-oic acid, oleoyl carnitine, and Phe-Phe. SRM-based quantitation confirmed significant differences between HCC and cirrhotic controls in metabolite levels of bile acid metabolites, long chain carnitines and small peptide. Our study provides useful insight into appropriate experimental design and computational methods for serum biomarker discovery using LC−MS/MS based metabolomics. This study has led to the identification of candidate biomarkers with significant changes in metabolite levels between HCC cases and cirrhotic controls. This is the first MS-based metabolic biomarker discovery study on Egyptian subjects that led to the identification of candidate metabolites that discriminate early stage HCC from patients with liver cirrhosis.

Project description:Characterizing the metabolic changes pertaining to hepatocellular carcinoma (HCC) in patients with liver cirrhosis is believed to contribute towards early detection, treatment, and understanding of the molecular mechanisms of HCC. In this study, we compare metabolite levels in sera of 78 HCC cases with 184 cirrhotic controls by using ultra performance liquid chromatography coupled with a hybrid quadrupole time-of-flight mass spectrometry (UPLC-QTOF MS). Following data preprocessing, the most relevant ions in distinguishing HCC cases from patients with cirrhosis are selected by parametric and non-parametric statistical methods. Putative metabolite identifications for these ions are obtained through mass-based database search. Verification of the identities of selected metabolites is conducted by comparing their MS/MS fragmentation patterns and retention time with those from authentic compounds. Quantitation of these metabolites is performed in a subset of the serum samples (10 HCC and 10 cirrhosis) using isotope dilution by selected reaction monitoring (SRM) on triple quadrupole linear ion trap (QqQLIT) and triple quadrupole (QqQ) mass spectrometers. The results of this analysis confirm that metabolites involved in sphingolipid metabolism and phospholipid catabolism such as sphingosine-1-phosphate (S-1-P) and lysophosphatidylcholine (lysoPC 17:0) are up-regulated in sera of HCC vs. those with liver cirrhosis. Down-regulated metabolites include those involved in bile acid biosynthesis (specifically cholesterol metabolism) such as glycochenodeoxycholic acid 3-sulfate (3-sulfo-GCDCA), glycocholic acid (GCA), glycodeoxycholic acid (GDCA), taurocholic acid (TCA), and taurochenodeoxycholate (TCDCA). These results provide useful insights into HCC biomarker discovery utilizing metabolomics as an efficient and cost-effective platform. Our work shows that metabolomic profiling is a promising tool to identify candidate metabolic biomarkers for early detection of HCC cases in high risk population of cirrhotic patients.

Project description:Intrahepatic cholestasis of pregnancy (ICP) is estimated to impact between 0.4% and 5% of pregnancies worldwide. This disease is associated with elevated maternal bile acids and frequently untoward neonatal outcomes such as respiratory distress and asphyxia. Multiple candidate genes have been implicated, but none have provided insight into the mechanisms of neonatal respiratory distress and death. Herein our studies demonstrate that maternal cholestasis (due to Abcb11 deficiency) produces 100% neonatal death within 24h due to atelectasis producing pulmonary hypoxia, which recapitulates the respiratory distress and asphyxia of human ICP. We show that these neonates have elevated pulmonary bile acids that are associated with disrupted structure of pulmonary surfactant. Maternal absence of Nr1i2 superimposed upon Abcb11 deficiency strongly increased neonatal survival and is directly related to reduced maternal bile acid concentrations. The mechanism accounting for reduced serum bile acids in the mothers deficient in both Nr1i2 and Abcb11 appears related to disrupted reabsorption of intestinal bile acids due to changes in transporter expression. These findings provide novel insights into pulmonary failure by revealing bile acids capability to disrupt the structure of surfactant producing collapsed alveoli, pulmonary failure and ultimately death. These findings have important implications for neonatal health especially when maternal bile acids are elevated during pregnancy and highlight a potential pathway and targets amenable to therapeutic intervention to ameliorate this condition. We used microarrays to measure changes in gene expression profiles in lung tissues from Abcb11+/- lungs after interbreeding C57BL/6 wild-type female or C57BL/6 Abcb11-/- female mice against either C57BL/6 wild-type male mice or C57BL/6 Abcb11-/- male mice to create only heterozygote offspring. We also measured profiles in liver tissues from age-matched C57BL/6 wild-type and C57BL/6 Abcb11-/- mice. Lung tissues were collected from day E17.5, E18.5 and neonatal (N0) mice. Liver tissues were collected from 1.5-month-old C57BL/6 wildtype and Abcb11-/- mice.

Project description:MicroRNAs (miRNAs) are abundant in the circulation and play a central role in diverse biological processes; they may be useful for early diagnosis of hepatocellular carcinoma (HCC). We conducted a two-phase, case-control study (20 pairs for the discovery set and 49 pairs for the validation set) to test the hypothesis that genome-wide dysregulation of circulating miRNAs differentiate HCC cases from controls. Taqman low density arrays were used to examine genome-wide miRNA expression for the discovery set, and quantitative RT-PCR was used to validate candidate miRNAs for both discovery and validation sets. Sixty-six miRNAs were found to be significantly over-expressed in plasma of HCC cases compared to controls after adjusting for false discovery rate (p<0.05). A volcano plot indicated that 7 miRNAs had greater than 2-fold case-control differences with p<0.01. Four significant miRNAs (miR-150, miR-30c, miR-483-5p and miR-520b) detectable in all samples with varied expression levels were further validated in a validation set. MiR-483-5p was statistically significantly over-expressed in HCC cases compared with controls (3.20 vs. 0.82, p<0.0001). HCC risk factors and clinic-pathological characteristics did not influence miR-483-5p expression. The combination of plasma miR-483-5p level and HCV status can significantly differentiate HCC cases from controls with an AUC of 0.908 (p<0.0001). The sensitivity and specificity were, respectively, 75.5% and 89.8%. These preliminary results suggest the importance of dysregulated circulating miR-483-5p as a potential HCC biomarker. Confirmation of aberrant expression of miR-483-5p in a large prospective HCC study will provide support for its application to HCC detection. A hospital-based HCC case-control study including 20 HCC patients and 20 controls is conducted in Columbia University Medical Center (CUMC), which is approved by the Institutional Review Board. Cases were newly diagnosed HCC patients who were treated in the Hepatobiliary Oncology Clinics, CUMC, and examined pathologically. Controls were recruited from volunteers through the Research Recruitment and Minority Outreach (RRMO) core of Herbert Irving Comprehensive Cancer Center (HICCC). Flyers were placed at strategic locations around CUMC where hospital visitors and employees frequent or were handed out at inreach events at the hospital or at outreach events in the community. Interested participants were directed to contact the trained recruitment staff from the RRMO and given further information about participation. Interested participants were excluded from the control group if diagnosed for any kind of cancer or liver disease. Eligible controls were asked to fill out the same demographic and epidemiological questionnaire as HCC cases. In the current study, controls were matched with HCC cases on age (M-BM-15 yrs), gender (male/female) and ethnicities (Caucasian/Hispanic/African-American/Asian).

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Metabolomics biomarkers of hepatocellular carcinoma in a prospective cohort of patients with cirrhosis

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