001     287441
005     20250814110933.0
024 7 _ |a 10.1016/j.ebiom.2024.104977
|2 doi
024 7 _ |a pmid:38290287
|2 pmid
024 7 _ |a altmetric:158884791
|2 altmetric
037 _ _ |a DKFZ-2024-00244
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Bull, Caroline J
|b 0
245 _ _ |a Impact of weight loss on cancer-related proteins in serum: results from a cluster randomised controlled trial of individuals with type 2 diabetes.
260 _ _ |a Amsterdam [u.a.]
|c 2024
|b Elsevier
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1706708406_24337
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Type 2 diabetes is associated with higher risk of several cancer types. However, the biological intermediates driving this relationship are not fully understood. As novel interventions for treating and managing type 2 diabetes become increasingly available, whether they also disrupt the pathways leading to increased cancer risk is currently unknown. We investigated the effect of a type 2 diabetes intervention, in the form of intentional weight loss, on circulating proteins associated with cancer risk to gain insight into potential mechanisms linking type 2 diabetes and adiposity with cancer development.Fasting serum samples from participants with diabetes enrolled in the Diabetes Remission Clinical Trial (DiRECT) receiving the Counterweight-Plus weight-loss programme (intervention, N = 117, mean weight-loss 10 kg, 46% diabetes remission) or best-practice care by guidelines (control, N = 143, mean weight-loss 1 kg, 4% diabetes remission) were subject to proteomic analysis using the Olink Oncology-II platform (48% of participants were female; 52% male). To identify proteins which may be altered by the weight-loss intervention, the difference in protein levels between groups at baseline and 1 year was examined using linear regression. Mendelian randomization (MR) was performed to extend these results to evaluate cancer risk and elucidate possible biological mechanisms linking type 2 diabetes and cancer development. MR analyses were conducted using independent datasets, including large cancer meta-analyses, UK Biobank, and FinnGen, to estimate potential causal relationships between proteins modified during intentional weight loss and the risk of colorectal, breast, endometrial, gallbladder, liver, and pancreatic cancers.Nine proteins were modified by the intervention: glycoprotein Nmb; furin; Wnt inhibitory factor 1; toll-like receptor 3; pancreatic prohormone; erb-b2 receptor tyrosine kinase 2; hepatocyte growth factor; endothelial cell specific molecule 1 and Ret proto-oncogene (Holm corrected P-value <0.05). Mendelian randomization analyses indicated a causal relationship between predicted circulating furin and glycoprotein Nmb on breast cancer risk (odds ratio (OR) = 0.81, 95% confidence interval (CI) = 0.67-0.99, P-value = 0.03; and OR = 0.88, 95% CI = 0.78-0.99, P-value = 0.04 respectively), though these results were not supported in sensitivity analyses examining violations of MR assumptions.Intentional weight loss among individuals with recently diagnosed diabetes may modify levels of cancer-related proteins in serum. Further evaluation of the proteins identified in this analysis could reveal molecular pathways that mediate the effect of adiposity and type 2 diabetes on cancer risk.The main sources of funding for this work were Diabetes UK, Cancer Research UK, World Cancer Research Fund, and Wellcome.
536 _ _ |a 313 - Krebsrisikofaktoren und Prävention (POF4-313)
|0 G:(DE-HGF)POF4-313
|c POF4-313
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
650 _ 7 |a Cancer
|2 Other
650 _ 7 |a DiRECT
|2 Other
650 _ 7 |a Diabetes
|2 Other
650 _ 7 |a Mendelian randomization
|2 Other
650 _ 7 |a Obesity
|2 Other
650 _ 7 |a Weight loss
|2 Other
700 1 _ |a Hazelwood, Emma
|b 1
700 1 _ |a Legge, Danny N
|b 2
700 1 _ |a Corbin, Laura J
|b 3
700 1 _ |a Richardson, Tom G
|b 4
700 1 _ |a Lee, Matthew
|b 5
700 1 _ |a Yarmolinsky, James
|b 6
700 1 _ |a Smith-Byrne, Karl
|b 7
700 1 _ |a Hughes, David A
|b 8
700 1 _ |a Johansson, Mattias
|b 9
700 1 _ |a Peters, Ulrike
|b 10
700 1 _ |a Berndt, Sonja I
|b 11
700 1 _ |a Brenner, Hermann
|0 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2
|b 12
|u dkfz
700 1 _ |a Burnett-Hartman, Andrea
|b 13
700 1 _ |a Cheng, Iona
|b 14
700 1 _ |a Kweon, Sun-Seog
|b 15
700 1 _ |a Le Marchand, Loic
|b 16
700 1 _ |a Li, Li
|b 17
700 1 _ |a Newcomb, Polly A
|b 18
700 1 _ |a Pearlman, Rachel
|b 19
700 1 _ |a McConnachie, Alex
|b 20
700 1 _ |a Welsh, Paul
|b 21
700 1 _ |a Taylor, Roy
|b 22
700 1 _ |a Lean, Mike E J
|b 23
700 1 _ |a Sattar, Naveed
|b 24
700 1 _ |a Murphy, Neil
|b 25
700 1 _ |a Gunter, Marc J
|b 26
700 1 _ |a Timpson, Nicholas J
|b 27
700 1 _ |a Vincent, Emma E
|b 28
773 _ _ |a 10.1016/j.ebiom.2024.104977
|g Vol. 100, p. 104977 -
|0 PERI:(DE-600)2799017-5
|p 104977
|t EBioMedicine
|v 100
|y 2024
|x 2352-3964
856 4 _ |u https://inrepo02.dkfz.de/record/287441/files/1-s2.0-S2352396424000124-main.pdf
856 4 _ |u https://inrepo02.dkfz.de/record/287441/files/1-s2.0-S2352396424000124-main.pdf?subformat=pdfa
|x pdfa
909 C O |o oai:inrepo02.dkfz.de:287441
|p VDB
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 12
|6 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF4-310
|0 G:(DE-HGF)POF4-313
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Krebsrisikofaktoren und Prävention
|x 0
914 1 _ |y 2024
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b EBIOMEDICINE : 2022
|d 2023-08-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2023-08-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2023-08-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0320
|2 StatID
|b PubMed Central
|d 2023-08-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2023-05-02T08:51:17Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2023-05-02T08:51:17Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Anonymous peer review
|d 2023-05-02T08:51:17Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2023-08-26
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2023-08-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2023-08-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2023-08-26
915 _ _ |a IF >= 10
|0 StatID:(DE-HGF)9910
|2 StatID
|b EBIOMEDICINE : 2022
|d 2023-08-26
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2023-08-26
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2023-08-26
920 1 _ |0 I:(DE-He78)C070-20160331
|k C070
|l C070 Klinische Epidemiologie und Alternf.
|x 0
920 1 _ |0 I:(DE-He78)C120-20160331
|k C120
|l Präventive Onkologie
|x 1
920 1 _ |0 I:(DE-He78)HD01-20160331
|k HD01
|l DKTK HD zentral
|x 2
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)C070-20160331
980 _ _ |a I:(DE-He78)C120-20160331
980 _ _ |a I:(DE-He78)HD01-20160331
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21