Cookie Settings

We use cookies to optimize our website. These include cookies that are necessary for the operation of the site, as well as those that are only used for anonymous statistic. You can decide for yourself which categories you want to allow. Further information can be found in our data privacy protection .


These cookies are necessary to run the core functionalities of this website and cannot be disabled.

Name Webedition CMS
Purpose This cookie is required by the CMS (Content Management System) Webedition for the system to function correctly. Typically, this cookie is deleted when the browser is closed.
Name econda
Purpose Session cookie emos_jcsid for the web analysis software econda. This runs in the “anonymized measurement” mode. There is no personal reference. As soon as the user leaves the site, tracking is ended and all data in the browser are automatically deleted.

These cookies help us understand how visitors interact with our website by collecting and analyzing information anonymously. Depending on the tool, one or more cookies are set by the provider.

Name econda
Purpose Statistics
External media

Content from external media platforms is blocked by default. If cookies from external media are accepted, access to this content no longer requires manual consent.

Name YouTube
Purpose Show YouTube content
Name Twitter
Purpose activate Twitter Feeds

Better distinguish chronic inflammation and cancer of the pancreas

No. 46 | 20/09/2023 | by Koh

Current diagnostic methods do not always reliably distinguish between chronic inflammation of the pancreas and pancreatic cancer. About one third of all diagnoses are inconclusive. Scientists from the German Cancer Research (DKFZ) and from Heidelberg University Hospital (UKHD) therefore searched for molecular markers that could specify this diagnosis. Supported by machine learning, they were able to identify a pattern of DNA methylations that allowed high accuracy in distinguishing between chronically inflamed and malignantly altered tissue samples. First preliminary results suggest that diagnosis could be performed on blood samples.

© Adobe Stock

Cancer of the pancreas or PDAC for short ("pancreatic ductal adenocarcinoma"), has a dramatically poor prognosis. The reasons for this are its usually late detection at an advanced stage, misdiagnosis and its marked resistance to available therapies.

Imaging techniques are usually used for diagnosis. But these have the disadvantage that they cannot always reliably distinguish pancreatic cancer from chronic pancreatic inflammation. Chronic inflammation is considered an important risk factor for pancreatic cancer. About 6 to 9 percent of patients suffering from chronic inflammation of the pancreas later develop pancreatic cancer. But imaging and even ultrasound-guided fine-needle biopsy too often also provide incorrect diagnoses.

"This is dramatic for the patients: if a malignant tumor is misdiagnosed as chronic inflammation, they lose valuable time to treat the disease. However, if doctors mistakenly think an inflammation is a carcinoma, the patient has to undergo a serious surgical intervention unnecessarily," says Jörg Hoheisel of the German Cancer Research Center.

To improve this situation and find molecular markers to arrive at more precise differential diagnoses, Hoheisel has now joined forces with physicians at Surgical University Clinic Heidelberg to conduct a large-scale study of pancreatic tissue samples. The team analyzed 345 tissue samples (PDAC, chronically inflamed and healthy), and then validated the results on an independent set of 48 additional samples. Prior to this, the material used had been independently assessed twice by experienced pathologists.

The analysis included genome-wide variations in DNA methylation as well as mRNA and microRNA amounts. To filter out relevant differences between malignant tumors and chronic inflammation from the wealth of data, the researchers used machine learning approaches. Other, commonly used methods did not yield useful results. It turned out that differences in DNA methylation allowed substantially higher accuracy with far fewer biomarkers than the mRNA or microRNA data.

A signature of six methylation positions in the PRKCB gene provided the clearest discrimination. This allowed correct identification of inflammatory and malignant tissues.

For clinical use, it would be more advantageous if the analyses could be performed on blood instead of tissue samples. Such blood analyses, which detect the small amounts of DNA that circulate in the blood, are also known as "liquid biopsy."

The Heidelberg team therefore also applied the six methylation markers to a small number of blood samples from patients with chronic pancreatitis or pancreatic cancer to demonstrate their applicability in blood as well. As previously in tissue, the methylation markers were able to diagnose patients with high accuracy.

"Of course, the procedure must be validated on a large number of blood samples and confirmed in a trial under clinical conditions in order to finally assess its actual benefit for clinical practice," says study leader Jörg Hoheisel. "If the result is confirmed in this process, it could have a significant impact on clinical care and patient prognosis."

Hoheisel assumes that the algorithm developed for this data analysis can also be helpful in the search for biomarkers for other diseases.

Yenan Wu, Isabelle Seufert, Fawaz N. Al-Shaheri, Roman Kurilov, Andrea S. Bauer, Mehdi Manoochehri, Evgeny A. Moskalev, Benedikt Brors, Christin Tjaden, Nathalia A. Giese, Thilo Hackert, Markus W. Büchler und Jörg D. Hoheisel: DNA-methylation signature accurately differentiates pancreatic cancer from chronic pancreatitis in tissue and plasma.
GUT 2023, DOI: 10.1136/gutjnl-2023-330155

With more than 3,000 employees, the German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ) is Germany’s largest biomedical research institute. DKFZ scientists identify cancer risk factors, investigate how cancer progresses and develop new cancer prevention strategies. They are also developing new methods to diagnose tumors more precisely and treat cancer patients more successfully. The DKFZ's Cancer Information Service (KID) provides patients, interested citizens and experts with individual answers to questions relating to cancer.

To transfer promising approaches from cancer research to the clinic and thus improve the prognosis of cancer patients, the DKFZ cooperates with excellent research institutions and university hospitals throughout Germany:

  • National Center for Tumor Diseases (NCT, 6 sites)
  • German Cancer Consortium (DKTK, 8 sites)
  • Hopp Children's Cancer Center (KiTZ) Heidelberg
  • Helmholtz Institute for Translational Oncology (HI-TRON Mainz) - A Helmholtz Institute of the DKFZ
  • DKFZ-Hector Cancer Institute at the University Medical Center Mannheim
  • National Cancer Prevention Center (jointly with German Cancer Aid)
The DKFZ is 90 percent financed by the Federal Ministry of Education and Research and 10 percent by the state of Baden-Württemberg. The DKFZ is a member of the Helmholtz Association of German Research Centers.


Subscribe to our RSS-Feed.

to top
powered by webEdition CMS