Dataset Information

Metabolomics evaluation of serum markers for cachexia and their intra-day variation in patients with advanced pancreatic cancer.

ABSTRACT:

Purpose

Cancer cachexia is a multifactorial syndrome characterized by progressive loss of weight and muscle atrophy. Using metabolomics, we investigated serum markers and their intra-day variation in advanced pancreatic cancer patients with cachexia.

Methods

Patients were enrolled in two groups: those with or without cachexia. Blood samples collected at 6:30 AM, 11:30 AM, 4:30 PM, and 9:30 PM were analyzed using metabolomics, and serum levels of IL-6, TNF-?, and leptin were measured and compared between the two groups. Intra-day variation was then evaluated.

Results

Twenty-one patients were enrolled in total. In the cachexia group (n?=?9), median body weight loss rate over 6 months was greater, performance status was poorer, and anorexia was more severe than in the non-cachexia group (n?=?12). Each metabolites level showed substantial intra-day variation, and some of them displayed significant differences between the two groups. Levels of paraxanthine remained markedly lower in the cohort with cachexia at all measurement points. Besides, median IL-6 and TNF-? levels appeared higher and leptin concentration appeared lower in the cachexia group, albeit without statistical significance.

Conclusion

Some metabolites and some serological marker levels were affected by cancer cachexia. Although paraxanthine levels were consistently lower in patients with cachexia, we identified that many metabolites indicated large intra- and inter-day variation and that it might be necessary to pay attention to intra-day variation in metabolomics research.

SUBMITTER: Fujiwara Y

PROVIDER: S-EPMC4239056 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Metabolomics evaluation of serum markers for cachexia and their intra-day variation in patients with advanced pancreatic cancer.

Fujiwara Yutaka Y Kobayashi Takashi T Chayahara Naoko N Imamura Yoshinori Y Toyoda Masanori M Kiyota Naomi N Mukohara Toru T Nishiumi Shin S Azuma Takeshi T Yoshida Masaru M Minami Hironobu H

PloS one 20141120 11

<h4>Purpose</h4>Cancer cachexia is a multifactorial syndrome characterized by progressive loss of weight and muscle atrophy. Using metabolomics, we investigated serum markers and their intra-day variation in advanced pancreatic cancer patients with cachexia.<h4>Methods</h4>Patients were enrolled in two groups: those with or without cachexia. Blood samples collected at 6:30 AM, 11:30 AM, 4:30 PM, and 9:30 PM were analyzed using metabolomics, and serum levels of IL-6, TNF-α, and leptin were measur ...[more]

PMID: 25411961

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Project description:BackgroundCachexia is a multifactorial metabolic syndrome with high morbidity and mortality in patients with advanced cancer. The diagnosis of cancer cachexia depends on objective measures of clinical symptoms and a history of weight loss, which lag behind disease progression and have limited utility for the early diagnosis of cancer cachexia. In this study, we performed a nuclear magnetic resonance-based metabolomics analysis to reveal the metabolic profile of cancer cachexia and establish a diagnostic model.MethodsEighty-four cancer cachexia patients, 33 pre-cachectic patients, 105 weight-stable cancer patients, and 74 healthy controls were included in the training and validation sets. Comparative analysis was used to elucidate the distinct metabolites of cancer cachexia, while metabolic pathway analysis was employed to elucidate reprogramming pathways. Random forest, logistic regression, and receiver operating characteristic analyses were used to select and validate the biomarker metabolites and establish a diagnostic model.ResultsForty-six cancer cachexia patients, 22 pre-cachectic patients, 68 weight-stable cancer patients, and 48 healthy controls were included in the training set, and 38 cancer cachexia patients, 11 pre-cachectic patients, 37 weight-stable cancer patients, and 26 healthy controls were included in the validation set. All four groups were age-matched and sex-matched in the training set. Metabolomics analysis showed a clear separation of the four groups. Overall, 45 metabolites and 18 metabolic pathways were associated with cancer cachexia. Using random forest analysis, 15 of these metabolites were identified as highly discriminating between disease states. Logistic regression and receiver operating characteristic analyses were used to create a distinct diagnostic model with an area under the curve of 0.991 based on three metabolites. The diagnostic equation was Logit(P) = -400.53 - 481.88 × log(Carnosine) -239.02 × log(Leucine) + 383.92 × log(Phenyl acetate), and the result showed 94.64% accuracy in the validation set.ConclusionsThis metabolomics study revealed a distinct metabolic profile of cancer cachexia and established and validated a diagnostic model. This research provided a feasible diagnostic tool for identifying at-risk populations through the detection of serum metabolites.

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Dataset Information

Metabolomics evaluation of serum markers for cachexia and their intra-day variation in patients with advanced pancreatic cancer.

Purpose

Methods

Results

Conclusion

Publications

Metabolomics evaluation of serum markers for cachexia and their intra-day variation in patients with advanced pancreatic cancer.

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