Biomarkers may distinguish pancreatic cancer from chronic pancreatitis

Reuters Health Information: Biomarkers may distinguish pancreatic cancer from chronic pancreatitis

Biomarkers may distinguish pancreatic cancer from chronic pancreatitis

Last Updated: 2017-02-20

By Lorraine L. Janeczko

NEW YORK (Reuters Health) รข€“ A metabolic biomarker signature may help doctors distinguish pancreatic ductal adenocarcinoma (PDAC) from chronic pancreatitis, new research suggests.

"The investigators have identified promising metabolic biomarkers that, with further validation and study, could yield a blood test that detects early pancreatic cancer," said Dr. Kenneth H. Yu, a medical oncologist at Memorial Sloan Kettering Cancer Center in New York City.

"A test for detecting pancreatic cancer at an early stage, when the disease is potentially curable, is an important goal. Most patients are diagnosed at a late stage, when the cancer is incurable. We know that patients with pancreatic cancer often experience metabolic changes, such as weight loss and diabetes, therefore, looking for metabolic changes in the blood is a logical strategy," he told Reuters Health by email.

"The findings are not surprising; however, they do remain preliminary. A number of promising biomarkers have been discovered in similar studies in the past, only to fail when subjected to further, rigorous validation," added Dr. Yu, who was not involved in the study.

As reported in Gut, online January 20, Dr. Julia Mayerle of Ernst-Moritz-Arndt-University in Greifswald, Germany and colleagues conducted a case-control study of 271 patients with PDAC, 282 with chronic pancreatitis, 100 with liver cirrhosis and 261 non-pancreatic-disease controls at three medical centers.

Using gas chromatography-mass spectrometry and liquid chromatography-tandem mass spectrometry, the researchers generated metabolomic profiles of plasma and serum samples from 477 metabolites.

They identified a biomarker signature comprising nine metabolites and carbohydrate antigen 19-9 (CA19-9) that differentiated PDAC from chronic pancreatitis in the training set with an area under the curve (AUC) of 0.96 (95% confidence interval (CI) 0.93 to 0.98).

The biomarker signature cutoff at 0.384 with 85% fixed specificity had 94.9% sensitivity (95% CI 87.0% to 97.0%). The test set showed an AUC of 0.94 (95% CI 0.91 to 0.97) as well as 89.9% sensitivity (95% CI 81.0% to 95.5%) and 91.3% specificity (95% CI 82.8% to 96.4%).

In patients with chronic pancreatitis at elevated risk for pancreatic cancer (cumulative incidence 1.95%), the biomarker signature resulted in negative predictive values of 99.9% (95% CI 99.7% to 99.9%) in the training set and 99.8% (95% CI 99.6% to 99.9%) in the test set.

"In one third of our patients, the clinical use of this biomarker signature would have improved diagnosis and treatment stratification in comparison to CA19-9," the authors wrote.

"Metabolomics has just begun to enter the field of cancer diagnostics and tumour biology. Our data clearly demonstrate the value of a comprehensive metabolite profiling platform, including lipidomics, in the largest cancer cohort investigated so far," they added. "The results demonstrate the feasibility of developing a diagnostic test that can detect pancreatic cancer with greater accuracy (>90%) than has previously been achieved with either conventional tumour markers or an miRNA panel."

Dr. Yu cautioned that the study has limitations. "The techniques used by the investigators to measure metabolites cannot easily be performed in a high-throughput fashion in a clinical laboratory. It is also not clear why the biomarkers studied can differentiate cancer from pancreatitis reasonably well, but not normal controls."

"We are hopeful that the investigators will continue to study and develop these biomarkers, and that in the future, their work will yield a clinically useful screening test," he added.

The corresponding author did not respond to requests for comment.

Government funding and grants supported the study. Two authors are affiliated with Metanomics, and patent applications have been filed for the identified biomarkers by Metanomics Health GmbH.


Gut 2017.

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