Home > Publications database > Profiling the immune landscape in mucinous ovarian carcinoma. > print |
001 | 182555 | ||
005 | 20240229145722.0 | ||
024 | 7 | _ | |a 10.1016/j.ygyno.2022.10.022 |2 doi |
024 | 7 | _ | |a pmid:36368129 |2 pmid |
024 | 7 | _ | |a 0090-8258 |2 ISSN |
024 | 7 | _ | |a 1095-6859 |2 ISSN |
024 | 7 | _ | |a altmetric:138197071 |2 altmetric |
037 | _ | _ | |a DKFZ-2022-02736 |
041 | _ | _ | |a English |
082 | _ | _ | |a 610 |
100 | 1 | _ | |a Meagher, Nicola S |b 0 |
245 | _ | _ | |a Profiling the immune landscape in mucinous ovarian carcinoma. |
260 | _ | _ | |a Amsterdam [u.a.] |c 2022 |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 1668427471_7316 |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 Mucinous ovarian carcinoma (MOC) is a rare histotype of ovarian cancer, with low response rates to standard chemotherapy, and very poor survival for patients diagnosed at advanced stage. There is a limited understanding of the MOC immune landscape, and consequently whether immune checkpoint inhibitors could be considered for a subset of patients.We performed multicolor immunohistochemistry (IHC) and immunofluorescence (IF) on tissue microarrays in a cohort of 126 MOC patients. Cell densities were calculated in the epithelial and stromal components for tumor-associated macrophages (CD68+/PD-L1+, CD68+/PD-L1-), T cells (CD3+/CD8-, CD3+/CD8+), putative T-regulatory cells (Tregs, FOXP3+), B cells (CD20+/CD79A+), plasma cells (CD20-/CD79a+), and PD-L1+ and PD-1+ cells, and compared these values with clinical factors. Univariate and multivariable Cox Proportional Hazards assessed overall survival. Unsupervised k-means clustering identified patient subsets with common patterns of immune cell infiltration.Mean densities of PD1+ cells, PD-L1- macrophages, CD4+ and CD8+ T cells, and FOXP3+ Tregs were higher in the stroma compared to the epithelium. Tumors from advanced (Stage III/IV) MOC had greater epithelial infiltration of PD-L1- macrophages, and fewer PD-L1+ macrophages compared with Stage I/II cancers (p = 0.004 and p = 0.014 respectively). Patients with high epithelial density of FOXP3+ cells, CD8+/FOXP3+ cells, or PD-L1- macrophages, had poorer survival, and high epithelial CD79a + plasma cells conferred better survival, all upon univariate analysis only. Clustering showed that most MOC (86%) had an immune depleted (cold) phenotype, with only a small proportion (11/76,14%) considered immune inflamed (hot) based on T cell and PD-L1 infiltrates.In summary, MOCs are mostly immunogenically 'cold', suggesting they may have limited response to current immunotherapies. |
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 Immune infiltrate |2 Other |
650 | _ | 7 | |a Mucinous ovarian carcinoma |2 Other |
650 | _ | 7 | |a Rare histotype |2 Other |
700 | 1 | _ | |a Hamilton, Phineas |b 1 |
700 | 1 | _ | |a Milne, Katy |b 2 |
700 | 1 | _ | |a Thornton, Shelby |b 3 |
700 | 1 | _ | |a Harris, Bronwyn |b 4 |
700 | 1 | _ | |a Weir, Ashley |b 5 |
700 | 1 | _ | |a Alsop, Jennifer |b 6 |
700 | 1 | _ | |a Bisinoto, Christiani |b 7 |
700 | 1 | _ | |a Brenton, James D |b 8 |
700 | 1 | _ | |a Brooks-Wilson, Angela |b 9 |
700 | 1 | _ | |a Chiu, Derek S |b 10 |
700 | 1 | _ | |a Cushing-Haugen, Kara L |b 11 |
700 | 1 | _ | |a Fereday, Sian |b 12 |
700 | 1 | _ | |a Garsed, Dale W |b 13 |
700 | 1 | _ | |a Gayther, Simon A |b 14 |
700 | 1 | _ | |a Gentry-Maharaj, Aleksandra |b 15 |
700 | 1 | _ | |a Gilks, Blake |b 16 |
700 | 1 | _ | |a Jimenez-Linan, Mercedes |b 17 |
700 | 1 | _ | |a Kennedy, Catherine J |b 18 |
700 | 1 | _ | |a Le, Nhu D |b 19 |
700 | 1 | _ | |a Piskorz, Anna M |b 20 |
700 | 1 | _ | |a Riggan, Marjorie J |b 21 |
700 | 1 | _ | |a Shah, Mitul |b 22 |
700 | 1 | _ | |a Singh, Naveena |b 23 |
700 | 1 | _ | |a Talhouk, Aline |b 24 |
700 | 1 | _ | |a Widschwendter, Martin |b 25 |
700 | 1 | _ | |a Bowtell, David D L |b 26 |
700 | 1 | _ | |a Candido Dos Reis, Francisco J |b 27 |
700 | 1 | _ | |a Cook, Linda S |b 28 |
700 | 1 | _ | |a Fortner, Renée T |0 P:(DE-He78)74a6af8347ec5cbd4b77e562e10ca1f2 |b 29 |u dkfz |
700 | 1 | _ | |a García, María J |b 30 |
700 | 1 | _ | |a Harris, Holly R |b 31 |
700 | 1 | _ | |a Huntsman, David G |b 32 |
700 | 1 | _ | |a Karnezis, Anthony N |b 33 |
700 | 1 | _ | |a Köbel, Martin |b 34 |
700 | 1 | _ | |a Menon, Usha |b 35 |
700 | 1 | _ | |a Pharoah, Paul D P |b 36 |
700 | 1 | _ | |a Doherty, Jennifer A |b 37 |
700 | 1 | _ | |a Anglesio, Michael S |b 38 |
700 | 1 | _ | |a Pike, Malcolm C |b 39 |
700 | 1 | _ | |a Pearce, Celeste Leigh |b 40 |
700 | 1 | _ | |a Friedlander, Michael L |b 41 |
700 | 1 | _ | |a DeFazio, Anna |b 42 |
700 | 1 | _ | |a Nelson, Brad H |b 43 |
700 | 1 | _ | |a Ramus, Susan J |b 44 |
773 | _ | _ | |a 10.1016/j.ygyno.2022.10.022 |g Vol. 168, p. 23 - 31 |0 PERI:(DE-600)1467974-7 |p 23 - 31 |t Gynecologic oncology |v 168 |y 2022 |x 0090-8258 |
909 | C | O | |o oai:inrepo02.dkfz.de:182555 |p VDB |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 29 |6 P:(DE-He78)74a6af8347ec5cbd4b77e562e10ca1f2 |
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 2022 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2021-01-28 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2021-01-28 |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2021-01-28 |
915 | _ | _ | |a Nationallizenz |0 StatID:(DE-HGF)0420 |2 StatID |d 2022-11-16 |w ger |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2022-11-16 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2022-11-16 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2022-11-16 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2022-11-16 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2022-11-16 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |d 2022-11-16 |
915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b GYNECOL ONCOL : 2021 |d 2022-11-16 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2022-11-16 |
915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2022-11-16 |
915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b GYNECOL ONCOL : 2021 |d 2022-11-16 |
920 | 1 | _ | |0 I:(DE-He78)C020-20160331 |k C020 |l C020 Epidemiologie von Krebs |x 0 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a I:(DE-He78)C020-20160331 |
980 | _ | _ | |a UNRESTRICTED |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|