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Plasma Metabolome Analysis for Predicting Antiviral Treatment Efficacy in Chronic Hepatitis B: Diagnostic Biomarkers and Therapeutic Insights

ABSTRACT: The early and accurate identification of predictive biomarkers for antiviral treatment efficacy remains a significant clinical challenge, particularly in the management of chronic hepatitis B (CHB). This study aimed to assess whether the plasma metabolome could reliably predict the success of antiviral therapy in CHB patients. We conducted a retrospective analysis on 56 treatment-naive CHB patients at the First Affiliated Hospital of Zhejiang University from December 2013 to March 2016. Patients were randomly assigned to either a discovery cohort (n=29) or a validation cohort (n=27) and underwent a 48-week treatment regimen of entecavir (ETV) and interferon-alpha (IFN-α). Based on the outcome of the treatment, patients were classified as HBeAg seroconversion either (High responders, Hrp) or the non-remission group (Low responder, Lrp). Our methodology involved an untargeted analysis of the amine/phenol and carboxylic acid submetabolomes in the CHB patients under treatment, utilizing chemical isotope labeling (CIL) techniques with liquid chromatography-mass spectrometry (LC-MS).Several metabolites were identified as having significant diagnostic potential for distinguishing Hrp from Lrp, with areas under the receiver operating characteristic curve (AUC) exceeding those typically clinical indicators. Notably, four metabolites, namely 2-methyl-3-ketovaleric acid, 2-ketohexanoic acid, 6-oxo-1,4,5,6-tetrahydronicotinic acid, and α-ketoisovaleric acid, demonstrated exceptionally high sensitivity and specificity in both cohorts, nearing 100%. In contrast, the clinical indicators, including HBcAb, log(HBsAg), and HBeAb, demonstrated lower and inconsistent sensitivity and specificity between the discovery and validation cohorts. Using HBcAb as a marker, the sensitivity was 87.5% with 76.9% specificity in the discovery cohort; however, the sensitivity dropped to 46.7% with 91.7% specificity in the validation cohort. Using log(HBsAg), the sensitivity was 84.6% with 69.2% specificity in the discovery cohort, compared to 85.7% sensitivity and 83.3% specificity in the validation cohort. For HBeAb, the separation of Hrp and Lrp had a sensitivity of 87.5% with 69.2% specificity in the discovery cohort, while the validation cohort showed 86.7% sensitivity and 91.7% specificity.

INSTRUMENT(S): Liquid Chromatography MS - positive - reverse phase

SUBMITTER: CHEN DEYING

PROVIDER: MTBLS10401 | MetaboLights | 2024-07-10

REPOSITORIES: MetaboLights

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			Action	DRS
	MTBLS10401	Other
	FILES	Other
	a_MTBLS10401_LC-MS_DMPA_positive_reverse-phase_metabolite_profiling.txt	Txt
	a_MTBLS10401_LC-MS_Dansylation_positive_reverse-phase_metabolite_profiling.txt	Txt
	i_Investigation.txt	Txt

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Project description:Background: With the incidence of papillary thyroid carcinoma rising worldwide, the decision about lobectomy versus total thyroidectomy will become relevant for an increasing number of patients. There exists no reliable biomarker for metastatic potential or tendency of recurrence that could assist in the risk stratification of patients. Objective: To develop a gene expression classifier for metastatic potential by measuring RNA expression in the primary tumor at the time of cancer surgery. Further, to investigate the ability of the gene expression classifier to identify metastatic and recurrent cases. Method: Genome-wide expression analyses. The development cohort consisted of freshly frozen tissues from 38 patients collected between the years 1986 and 2009. Validation was performed on a consecutive cohort of formalin fixated paraffin embedded surgical tissue specimens from 183 patients treated at Odense and Aarhus University Hospitals. Results: A 17 gene classifier (ADAMTS1, ANTXR1, C7, CXCL12, EBF1, FBLN2, FOSL2, GGT5, GPR124, JAM3, LRIG1, NDRG1, PRRX1, ROBO1, SORL1, TCF4, and ZEB1) was identified based on the expression values of these genes in the groups with and without metastasis in the development cohort. The 17 gene classifier for regional and/or distant metastasis identified was tested against the clinical status in the validation cohort. Sensitivity was 51.6% (95% CI 41.2%-61.8) and specificity 61.6 % (95% CI 50.5%-71.9%). Further, the Kaplan-Meyer method was used to estimate whether the classifier was useful as a prognostic marker for recurrences. Log-rank testing failed to identify any significance (p=0.32). Conclusion: A 17 gene classifier for metastatic potential was developed, and the results showed a clear biological difference between groups. However, through validation, the prognostic significance of this classifier could not be shown in identifying metastatic cases or in the ability of dichotomizing patients according to risk of recurrence after primary treatment. 38 patients with papillary thyroid carcinoma from a consecutive cohort of patients, no replicates

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Plasma Metabolome Analysis for Predicting Antiviral Treatment Efficacy in Chronic Hepatitis B: Diagnostic Biomarkers and Therapeutic Insights

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