Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster session 01

156P - The association between fibrotic endotypes, determined by pre-treatment serum levels of collagen metabolites, and survival outcomes in patients with pancreatic cancer

Date

21 Oct 2023

Session

Poster session 01

Topics

Genetic and Genomic Testing

Tumour Site

Pancreatic Adenocarcinoma

Presenters

Rasmus Pedersen

Citation

Annals of Oncology (2023) 34 (suppl_2): S233-S277. 10.1016/S0923-7534(23)01932-4

Authors

R.S. Pedersen1, J. Thorlacius-Ussing2, N.I. Nissen2, A. Johansen3, I. Chen3, C. Jensen4, C. Hansen5, M. Karsdal2, J.S. Johansen3, N. Willumsen6

Author affiliations

  • 1 Department Of Biomedical Sciences, Copenhagen University, 1017 - Copenhagen/DK
  • 2 Biomarkers And Research, Nordic Bioscience A/S, 2730 - Herlev/DK
  • 3 Department Of Oncology, Herlev and Gentofte Hospital, 2730 - Herlev/DK
  • 4 Department Of Biomarkers & Research, Nordic Bioscience A/S, 2730 - Herlev/DK
  • 5 Department Of Surgery, Rigshospitalet, 2100 - Copenhagen/DK
  • 6 Department Of Biomarkers And Research, Nordic Bioscience A/S, 2730 - Herlev/DK

Resources

Login to get immediate access to this content.

If you do not have an ESMO account, please create one for free.

Abstract 156P

Background

Abnormal collagen fiber architectures in tumor fibrosis affect prognosis and treatment response in pancreatic cancer (PC) patients. Increased fibrotic activity releases collagen metabolites into the bloodstream. The aim was to explore these metabolites to cluster PC patients into tumor fibrosis endotypes and evaluate overall survival (OS).

Methods

Serum was collected from patients with PC prior to chemotherapy or resection and included in the BIOPAC Study (ID: NCT03311776) (stage I (n=15), Stage II (n=201), stage III (n=164) and stage 4 (n=434)). Principal component analysis was performed on the levels of five collagen metabolites (Table) measured by ELISAs. K-means clustering was used to discover clusters and Kaplan-Meier curves and the cox proportional hazards model used to dicover associations with OS. Table: 156P

Biomarker name collagen metabolite
C3M Neo-epitope of MMP-9 mediated degradation of type III collagen
PRO-C3 Released N-terminal pro-peptide of type III collagen
PRO-C5 Released C-terminal pro-peptide of type V collagen
PRO-C6 C-terminal of released C5 domain of type VI collagen α3 chain (endotrophin)
PRO-C11 Released N-terminal pro-peptide of type XI collagen

Results

Three putative endotypes (cluster A, B, C) were identified. Patients in cluster B had higher C3M, PRO-C5 and PRO-C11 levels compared to cluster A, whereas patients in cluster C had higher PRO-C3 and PRO-C6 levels compared to cluster A. Patients with endotype A had a median OS of 332 days vs. 185 and 144 days for endotype B and C (p<0.001). Compared to endotype A, both endotype B (HR=1.56, 95% CI 1.28–1.91, p<0.001) and endotype C (HR=1.69, 95% CI 1.26–2.26, p<0.001) were predictors of poor OS when corrected for age, sex, performance status, body mass index, diabetes, cachexia, stage, number of metastatic sites, and CA19-9.

Conclusions

Clustering of patients with PC based on five collagen-derived metabolites measured in serum identifies 3 distinct endotypes that were associated with poor OS independent of other common risk factors. These findings indicate that non-invasive collagen biomarkers can be used to identify fibrotic endotypes in patients with PC and that such endotypes may inform on patient prognostication.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

The Danish Research Foundation.

Disclosure

J. Thorlacius-Ussing, N.I. Nissen, C. Jensen, M. Karsdal, N. Willumsen: Financial Interests, Institutional, Full or part-time Employment: Nordic bioscience A/S. All other authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.