A Plasma-Derived Protein-Metabolite Multiplexed Panel for Early-Stage Pancreatic Cancer.

Abstract

BACKGROUND:

We applied a training and testing approach to develop and validate a plasma metabolite panel for the detection of early-stage pancreatic ductal adenocarcinoma (PDAC) alone and in combination with a previously validated protein panel for early-stage PDAC.

METHODS:

A comprehensive metabolomics platform was initially applied to plasmas collected from 20 PDAC cases and 80 controls. Candidate markers were filtered based on a second independent cohort that included nine invasive intraductal papillary mucinous neoplasm cases and 51 benign pancreatic cysts. Blinded validation of the resulting metabolite panel was performed in an independent test cohort consisting of 39 resectable PDAC cases and 82 matched healthy controls. The additive value of combining the metabolite panel with a previously validated protein panel was evaluated.

RESULTS:

Five metabolites (acetylspermidine, diacetylspermine, an indole-derivative, and two lysophosphatidylcholines) were selected as a panel based on filtering criteria. A combination rule was developed for distinguishing between PDAC and healthy controls using the Training Set. In the blinded validation study with early-stage PDAC samples and controls, the five metabolites yielded areas under the curve (AUCs) ranging from 0.726 to 0.842, and the combined metabolite model yielded an AUC of 0.892 (95% confidence interval [CI] = 0.828 to 0.956). Performance was further statistically significantly improved by combining the metabolite panel with a previously validated protein marker panel consisting of CA 19-9, LRG1, and TIMP1 (AUC = 0.924, 95% CI = 0.864 to 0.983, comparison DeLong test one-sided P= .02).

CONCLUSIONS:

A metabolite panel in combination with CA19-9, TIMP1, and LRG1 exhibited substantially improved performance in the detection of early-stage PDAC compared with a protein panel alone.

• Authors: Johannes F Fahrmann, Leonidas E Bantis, Michela Capello, Ghislaine Scelo, Jennifer B Dennison, Nikul Patel, Eunice Murage, Jody Vykoukal, Deepali L Kundnani, Lenka Foretova, Eleonora Fabianova, Ivana Holcatova, Vladimir Janout, Ziding Feng, Michele Yip-Schneider, Jianjun Zhang, Randall Brand, Ayumu Taguchi, Anirban Maitra, Paul Brennan, C Max Schmidt, Samir Hanash
• Journal: Journal of the National Cancer Institute (J Natl Cancer Inst) Vol. 111 Issue 4 Pg. 372-379 (04 01 2019) ISSN: 1460-2105 [Electronic] United States
• PMID: 30137376 (Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't)
• Copyright: © The Author(s) 2018. Published by Oxford University Press.

Chemical References

• Biomarkers, Tumor

Topics

• Adenocarcinoma, Mucinous (genetics, metabolism, pathology)
• Biomarkers, Tumor (blood, genetics)
• Carcinoma, Pancreatic Ductal (genetics, metabolism, pathology)
• Carcinoma, Papillary (genetics, metabolism, pathology)
• Case-Control Studies
• Follow-Up Studies
• Humans
• Metabolome
• Neoplasm Invasiveness
• Neoplasm Staging
• Pancreatic Neoplasms (genetics, metabolism, pathology)
• Transcriptome