Home > Publications database > Cell-free DNA aneuploidy score as a dynamic early response marker in prostate cancer. > print |
001 | 299826 | ||
005 | 20250323015713.0 | ||
024 | 7 | _ | |a 10.1002/1878-0261.13797 |2 doi |
024 | 7 | _ | |a pmid:40084488 |2 pmid |
024 | 7 | _ | |a 1574-7891 |2 ISSN |
024 | 7 | _ | |a 1878-0261 |2 ISSN |
024 | 7 | _ | |a altmetric:175218654 |2 altmetric |
037 | _ | _ | |a DKFZ-2025-00563 |
041 | _ | _ | |a English |
082 | _ | _ | |a 610 |
100 | 1 | _ | |a Isebia, Khrystany T |0 0000-0002-3006-5206 |b 0 |
245 | _ | _ | |a Cell-free DNA aneuploidy score as a dynamic early response marker in prostate cancer. |
260 | _ | _ | |a Hoboken, NJ |c 2025 |b John Wiley & Sons, Inc. |
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 1742292049_21169 |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 |
500 | _ | _ | |a epub |
520 | _ | _ | |a Cell-free circulating tumor DNA (ctDNA) has emerged as a promising biomarker for response evaluation in metastatic castration-resistant prostate cancer (mCRPC). The current study evaluated the modified fast aneuploidy screening test-sequencing system (mFast-SeqS), a quick, tumor-agnostic and affordable ctDNA assay that requires a small input of DNA, to generate a genome-wide aneuploidy (GWA) score in mCRPC patients, and correlated this to matched metastatic tumor biopsies. In this prospective multicenter study, GWA scores were evaluated from blood samples of 196 mCRPC patients prior to treatment (baseline) with taxanes (docetaxel and cabazitaxel) and androgen receptor signaling inhibitors (ARSI; abiraterone and enzalutamide), and from 74 mCRPC patients at an early timepoint during treatment (early timepoint; median 21 days). Z-scores per chromosome arm were tested for their association with tumor tissue genomic alterations. We found that a high tumor load in blood (GWAhigh) at baseline was associated with poor response to ARSI [HR: 2.63 (95% CI: 1.86-3.72) P < 0.001] but not to taxanes. Interestingly, GWAhigh score at the early timepoint was associated with poor response to both ARSIs [HR: 6.73 (95% CI: 2.60-17.42) P < 0.001] and taxanes [2.79 (95% CI: 1.34-5.78) P = 0.006]. A significant interaction in Cox proportional hazards analyses was seen when combining GWA status and type of treatment (at baseline P = 0.008; early timepoint P = 0.018). In summary, detection of ctDNA in blood by mFast-SeqS is cheap, fast and feasible, and could be used at different timepoints as a potential predictor for outcome to ARSI and taxane treatment in mCRPC. |
536 | _ | _ | |a 312 - Funktionelle und strukturelle Genomforschung (POF4-312) |0 G:(DE-HGF)POF4-312 |c POF4-312 |f POF IV |x 0 |
588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de |
650 | _ | 7 | |a abiraterone |2 Other |
650 | _ | 7 | |a cabazitaxel |2 Other |
650 | _ | 7 | |a ctDNA |2 Other |
650 | _ | 7 | |a docetaxel |2 Other |
650 | _ | 7 | |a enzalutamide |2 Other |
650 | _ | 7 | |a prostate cancer |2 Other |
700 | 1 | _ | |a de Jong, Anouk C |0 0000-0002-7381-3171 |b 1 |
700 | 1 | _ | |a van Dessel, Lisanne F |b 2 |
700 | 1 | _ | |a de Weerd, Vanja |b 3 |
700 | 1 | _ | |a Beaufort, Corine |b 4 |
700 | 1 | _ | |a Helmijr, Jean |b 5 |
700 | 1 | _ | |a Nakauma-González, José Alberto |0 0000-0002-9153-4280 |b 6 |
700 | 1 | _ | |a van Riet, Job |0 P:(DE-He78)6efdda844232d585b4472cecaed85382 |b 7 |u dkfz |
700 | 1 | _ | |a Hamberg, Paul |b 8 |
700 | 1 | _ | |a Vis, Daniel |b 9 |
700 | 1 | _ | |a van der Heijden, Michiel S |b 10 |
700 | 1 | _ | |a Beije, Nick |b 11 |
700 | 1 | _ | |a Lolkema, Martijn P |b 12 |
700 | 1 | _ | |a Deger, Teoman |0 0000-0002-3055-3066 |b 13 |
700 | 1 | _ | |a Wilting, Saskia M |b 14 |
700 | 1 | _ | |a de Wit, Ronald |b 15 |
700 | 1 | _ | |a Jansen, Maurice P H M |0 0000-0003-1258-9804 |b 16 |
700 | 1 | _ | |a Martens, John W M |0 0000-0002-3428-3366 |b 17 |
773 | _ | _ | |a 10.1002/1878-0261.13797 |g p. 1878-0261.13797 |0 PERI:(DE-600)2322586-5 |p nn |t Molecular oncology |v nn |y 2025 |x 1574-7891 |
909 | C | O | |o oai:inrepo02.dkfz.de:299826 |p VDB |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 7 |6 P:(DE-He78)6efdda844232d585b4472cecaed85382 |
913 | 1 | _ | |a DE-HGF |b Gesundheit |l Krebsforschung |1 G:(DE-HGF)POF4-310 |0 G:(DE-HGF)POF4-312 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-300 |4 G:(DE-HGF)POF |v Funktionelle und strukturelle Genomforschung |x 0 |
914 | 1 | _ | |y 2025 |
915 | _ | _ | |a DEAL Wiley |0 StatID:(DE-HGF)3001 |2 StatID |d 2025-01-07 |w ger |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2025-01-07 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2025-01-07 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0501 |2 StatID |b DOAJ Seal |d 2024-08-08T17:04:26Z |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0500 |2 StatID |b DOAJ |d 2024-08-08T17:04:26Z |
915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b DOAJ : Open peer review |d 2024-08-08T17:04:26Z |
915 | _ | _ | |a Creative Commons Attribution CC BY (No Version) |0 LIC:(DE-HGF)CCBYNV |2 V:(DE-HGF) |b DOAJ |d 2024-08-08T17:04:26Z |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2025-01-07 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2025-01-07 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2025-01-07 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2025-01-07 |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2025-01-07 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2025-01-07 |
915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b MOL ONCOL : 2022 |d 2025-01-07 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2025-01-07 |
915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2025-01-07 |
915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b MOL ONCOL : 2022 |d 2025-01-07 |
915 | _ | _ | |a Article Processing Charges |0 StatID:(DE-HGF)0561 |2 StatID |d 2025-01-07 |
915 | _ | _ | |a Fees |0 StatID:(DE-HGF)0700 |2 StatID |d 2025-01-07 |
920 | 1 | _ | |0 I:(DE-He78)B450-20160331 |k B450 |l Künstl. Intelligenz in der Onkologie |x 0 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a I:(DE-He78)B450-20160331 |
980 | _ | _ | |a UNRESTRICTED |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|