| Home > Publications database > SputOMICs identifies common and distinct markers in cystic fibrosis and chronic obstructive pulmonary disease. > print |
| 001 | 307446 | ||
| 005 | 20251231120304.0 | ||
| 024 | 7 | _ | |a 10.1038/s41598-025-32565-y |2 doi |
| 024 | 7 | _ | |a pmid:41436524 |2 pmid |
| 024 | 7 | _ | |a pmc:PMC12738762 |2 pmc |
| 037 | _ | _ | |a DKFZ-2025-03045 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 600 |
| 100 | 1 | _ | |a Frey, Dario |0 P:(DE-He78)928cfe90c9ba53a9d24391f31b14ce95 |b 0 |e First author |u dkfz |
| 245 | _ | _ | |a SputOMICs identifies common and distinct markers in cystic fibrosis and chronic obstructive pulmonary disease. |
| 260 | _ | _ | |a [London] |c 2025 |b Springer Nature |
| 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 1767096222_1386403 |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 #EA:B200#LA:B200# |
| 520 | _ | _ | |a Cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) are muco-obstructive lung diseases. Knowledge of molecular processes has much improved therapeutic options in CF, whereas much less is known for COPD, a disease affecting an increasing number of patients. Here, we report a multilayer workflow integrating microbiome, inflammation and proteome profiling with clinical data to identify disease specific characteristics in sputum. Our proof-of-concept study shows that CF sputum is dominated by Pseudomonas and Staphylococcus, exhibits heightened neutrophilic inflammation, and a severe protease-antiprotease imbalance. In contrast, COPD displays heterogeneous microbiome composition, eosinophilic inflammation, and altered extracellular matrix remodeling. Proteome-based cellular deconvolution identifies disease-specific immune cell signatures, underscoring the complexity, especially in COPD. Multi-omics factor analysis suggests that matrisome and nucleotide metabolism changes may act as disease discriminators, though future confirmation in larger cohorts is needed. These findings highlight the potential of our integrated approach to uncover sputum biomarkers as tools for patient stratification and personalized therapeutic strategies in CF and COPD. |
| 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 Biomarkers |2 Other |
| 650 | _ | 7 | |a COPD |2 Other |
| 650 | _ | 7 | |a Cystic fibrosis |2 Other |
| 650 | _ | 7 | |a Microbiome |2 Other |
| 650 | _ | 7 | |a Multi-omics |2 Other |
| 650 | _ | 7 | |a Proteomics |2 Other |
| 650 | _ | 7 | |a Biomarkers |2 NLM Chemicals |
| 650 | _ | 7 | |a Proteome |2 NLM Chemicals |
| 650 | _ | 2 | |a Cystic Fibrosis: metabolism |2 MeSH |
| 650 | _ | 2 | |a Cystic Fibrosis: microbiology |2 MeSH |
| 650 | _ | 2 | |a Humans |2 MeSH |
| 650 | _ | 2 | |a Pulmonary Disease, Chronic Obstructive: metabolism |2 MeSH |
| 650 | _ | 2 | |a Pulmonary Disease, Chronic Obstructive: microbiology |2 MeSH |
| 650 | _ | 2 | |a Sputum: microbiology |2 MeSH |
| 650 | _ | 2 | |a Sputum: metabolism |2 MeSH |
| 650 | _ | 2 | |a Biomarkers: metabolism |2 MeSH |
| 650 | _ | 2 | |a Biomarkers: analysis |2 MeSH |
| 650 | _ | 2 | |a Female |2 MeSH |
| 650 | _ | 2 | |a Male |2 MeSH |
| 650 | _ | 2 | |a Microbiota |2 MeSH |
| 650 | _ | 2 | |a Proteome |2 MeSH |
| 650 | _ | 2 | |a Proteomics: methods |2 MeSH |
| 650 | _ | 2 | |a Adult |2 MeSH |
| 700 | 1 | _ | |a Helm, Barbara |0 P:(DE-He78)1c49e2bc4134e93b5dc7d9845e30c039 |b 1 |u dkfz |
| 700 | 1 | _ | |a Guerra, Matteo |b 2 |
| 700 | 1 | _ | |a Hagner, Matthias |b 3 |
| 700 | 1 | _ | |a Lu, Junyan |b 4 |
| 700 | 1 | _ | |a Dittrich, A Susanne |b 5 |
| 700 | 1 | _ | |a Wege, Sabine |b 6 |
| 700 | 1 | _ | |a Eberhardt, Ralf |b 7 |
| 700 | 1 | _ | |a Herth, Felix J F |b 8 |
| 700 | 1 | _ | |a Sommerburg, Olaf |b 9 |
| 700 | 1 | _ | |a Schultz, Carsten |b 10 |
| 700 | 1 | _ | |a Dalpke, Alexander H |b 11 |
| 700 | 1 | _ | |a Klingmüller, Ursula |0 P:(DE-He78)860df4ab16c373fb28a815dcd81107a6 |b 12 |e Last author |u dkfz |
| 700 | 1 | _ | |a Mall, Marcus A |b 13 |
| 700 | 1 | _ | |a Boutin, Sébastien |b 14 |
| 773 | _ | _ | |a 10.1038/s41598-025-32565-y |g Vol. 15, no. 1, p. 44418 |0 PERI:(DE-600)2615211-3 |n 1 |p 44418 |t Scientific reports |v 15 |y 2025 |x 2045-2322 |
| 909 | C | O | |o oai:inrepo02.dkfz.de:307446 |p VDB |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 0 |6 P:(DE-He78)928cfe90c9ba53a9d24391f31b14ce95 |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 1 |6 P:(DE-He78)1c49e2bc4134e93b5dc7d9845e30c039 |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 12 |6 P:(DE-He78)860df4ab16c373fb28a815dcd81107a6 |
| 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 JCR |0 StatID:(DE-HGF)0100 |2 StatID |b SCI REP-UK : 2022 |d 2024-12-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2024-12-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2024-12-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0501 |2 StatID |b DOAJ Seal |d 2024-07-29T15:28:26Z |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0500 |2 StatID |b DOAJ |d 2024-07-29T15:28:26Z |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b DOAJ : Anonymous peer review |d 2024-07-29T15:28:26Z |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2024-12-18 |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2024-12-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2024-12-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1040 |2 StatID |b Zoological Record |d 2024-12-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1150 |2 StatID |b Current Contents - Physical, Chemical and Earth Sciences |d 2024-12-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2024-12-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2024-12-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2024-12-18 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2024-12-18 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2024-12-18 |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2024-12-18 |
| 915 | _ | _ | |a Article Processing Charges |0 StatID:(DE-HGF)0561 |2 StatID |d 2024-12-18 |
| 915 | _ | _ | |a Fees |0 StatID:(DE-HGF)0700 |2 StatID |d 2024-12-18 |
| 920 | 2 | _ | |0 I:(DE-He78)B200-20160331 |k B200 |l B200 Systembiologie der Signaltransduktion |x 0 |
| 920 | 1 | _ | |0 I:(DE-He78)B200-20160331 |k B200 |l B200 Systembiologie der Signaltransduktion |x 0 |
| 920 | 1 | _ | |0 I:(DE-He78)W120-20160331 |k W120 |l Proteomics |x 1 |
| 920 | 0 | _ | |0 I:(DE-He78)B200-20160331 |k B200 |l B200 Systembiologie der Signaltransduktion |x 0 |
| 920 | 0 | _ | |0 I:(DE-He78)W120-20160331 |k W120 |l Proteomics |x 1 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-He78)B200-20160331 |
| 980 | _ | _ | |a I:(DE-He78)W120-20160331 |
| 980 | _ | _ | |a UNRESTRICTED |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|