001     156955
005     20240229123123.0
024 7 _ |a 10.1016/j.annonc.2020.05.019
|2 doi
024 7 _ |a pmid:32473302
|2 pmid
024 7 _ |a 0923-7534
|2 ISSN
024 7 _ |a 1569-8041
|2 ISSN
024 7 _ |a altmetric:83144282
|2 altmetric
037 _ _ |a DKFZ-2020-01260
041 _ _ |a eng
082 _ _ |a 610
100 1 _ |a Millstein, J.
|b 0
245 _ _ |a Prognostic gene expression signature for high-grade serous ovarian cancer.
260 _ _ |a Oxford
|c 2020
|b Oxford Univ. Press
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 1598879791_25230
|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 2020 Sep;31(9):1240-1250
520 _ _ |a Median overall survival (OS) for women with high-grade serous ovarian cancer (HGSOC) is ∼4 years, yet survival varies widely between patients. There are no well-established, gene expression signatures associated with prognosis. The aim of this study was to develop a robust prognostic signature for OS in patients with HGSOC.Expression of 513 genes, selected from a meta-analysis of 1455 tumours and other candidates, was measured using NanoString technology from formalin-fixed paraffin-embedded tumour tissue collected from 3769 women with HGSOC from multiple studies. Elastic net regularization for survival analysis was applied to develop a prognostic model for 5-year OS, trained on 2702 tumours from 15 studies and evaluated on an independent set of 1067 tumours from six studies.Expression levels of 276 genes were associated with OS (false discovery rate < 0.05) in covariate-adjusted single-gene analyses. The top five genes were TAP1, ZFHX4, CXCL9, FBN1 and PTGER3 (P < 0.001). The best performing prognostic signature included 101 genes enriched in pathways with treatment implications. Each gain of one standard deviation in the gene expression score conferred a greater than twofold increase in risk of death [hazard ratio (HR) 2.35, 95% confidence interval (CI) 2.02-2.71; P < 0.001]. Median survival [HR (95% CI)] by gene expression score quintile was 9.5 (8.3 to -), 5.4 (4.6-7.0), 3.8 (3.3-4.6), 3.2 (2.9-3.7) and 2.3 (2.1-2.6) years.The OTTA-SPOT (Ovarian Tumor Tissue Analysis consortium - Stratified Prognosis of Ovarian Tumours) gene expression signature may improve risk stratification in clinical trials by identifying patients who are least likely to achieve 5-year survival. The identified novel genes associated with the outcome may also yield opportunities for the development of targeted therapeutic approaches.
536 _ _ |a 313 - Cancer risk factors and prevention (POF3-313)
|0 G:(DE-HGF)POF3-313
|c POF3-313
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed,
700 1 _ |a Budden, T.
|b 1
700 1 _ |a Goode, E. L.
|b 2
700 1 _ |a Anglesio, M. S.
|b 3
700 1 _ |a Talhouk, A.
|b 4
700 1 _ |a Intermaggio, M. P.
|b 5
700 1 _ |a Leong, H. S.
|b 6
700 1 _ |a Chen, S.
|b 7
700 1 _ |a Elatre, W.
|b 8
700 1 _ |a Gilks, B.
|b 9
700 1 _ |a Nazeran, T.
|b 10
700 1 _ |a Volchek, M.
|b 11
700 1 _ |a Bentley, R. C.
|b 12
700 1 _ |a Wang, C.
|b 13
700 1 _ |a Chiu, D. S.
|b 14
700 1 _ |a Kommoss, S.
|b 15
700 1 _ |a Leung, S. C. Y.
|b 16
700 1 _ |a Senz, J.
|b 17
700 1 _ |a Lum, A.
|b 18
700 1 _ |a Chow, V.
|b 19
700 1 _ |a Sudderuddin, H.
|b 20
700 1 _ |a Mackenzie, R.
|b 21
700 1 _ |a George, J.
|b 22
700 1 _ |a Group, AOCS
|b 23
|e Collaboration Author
700 1 _ |a Fereday, S.
|b 24
700 1 _ |a Hendley, J.
|b 25
700 1 _ |a Traficante, N.
|b 26
700 1 _ |a Steed, H.
|b 27
700 1 _ |a Koziak, J. M.
|b 28
700 1 _ |a Köbel, M.
|b 29
700 1 _ |a McNeish, I. A.
|b 30
700 1 _ |a Goranova, T.
|b 31
700 1 _ |a Ennis, D.
|b 32
700 1 _ |a Macintyre, G.
|b 33
700 1 _ |a Silva De Silva, D.
|b 34
700 1 _ |a Ramón Y Cajal, T.
|b 35
700 1 _ |a García-Donas, J.
|b 36
700 1 _ |a Hernando Polo, S.
|b 37
700 1 _ |a Rodriguez, G. C.
|b 38
700 1 _ |a Cushing-Haugen, K. L.
|b 39
700 1 _ |a Harris, H. R.
|b 40
700 1 _ |a Greene, C. S.
|b 41
700 1 _ |a Zelaya, R. A.
|b 42
700 1 _ |a Behrens, S.
|0 P:(DE-He78)6b04712f3afe72044d496a25505cb1ea
|b 43
|u dkfz
700 1 _ |a Fortner, R. T.
|0 P:(DE-HGF)0
|b 44
700 1 _ |a Sinn, P.
|b 45
700 1 _ |a Herpel, E.
|b 46
700 1 _ |a Lester, J.
|b 47
700 1 _ |a Lubiński, J.
|b 48
700 1 _ |a Oszurek, O.
|b 49
700 1 _ |a Tołoczko, A.
|b 50
700 1 _ |a Cybulski, C.
|b 51
700 1 _ |a Menkiszak, J.
|b 52
700 1 _ |a Pearce, C. L.
|b 53
700 1 _ |a Pike, M. C.
|b 54
700 1 _ |a Tseng, C.
|b 55
700 1 _ |a Alsop, J.
|b 56
700 1 _ |a Rhenius, V.
|b 57
700 1 _ |a Song, H.
|b 58
700 1 _ |a Jimenez-Linan, M.
|b 59
700 1 _ |a Piskorz, A. M.
|b 60
700 1 _ |a Gentry-Maharaj, A.
|b 61
700 1 _ |a Karpinskyj, C.
|b 62
700 1 _ |a Widschwendter, M.
|b 63
700 1 _ |a Singh, N.
|b 64
700 1 _ |a Kennedy, C. J.
|b 65
700 1 _ |a Sharma, R.
|b 66
700 1 _ |a Harnett, P. R.
|b 67
700 1 _ |a Gao, B.
|b 68
700 1 _ |a Johnatty, S. E.
|b 69
700 1 _ |a Sayer, R.
|b 70
700 1 _ |a Boros, J.
|b 71
700 1 _ |a Winham, S. J.
|b 72
700 1 _ |a Keeney, G. L.
|b 73
700 1 _ |a Kaufmann, S. H.
|b 74
700 1 _ |a Larson, M. C.
|b 75
700 1 _ |a Luk, H.
|b 76
700 1 _ |a Hernandez, B. Y.
|b 77
700 1 _ |a Thompson, P. J.
|b 78
700 1 _ |a Wilkens, L. R.
|b 79
700 1 _ |a Carney, M. E.
|b 80
700 1 _ |a Trabert, B.
|b 81
700 1 _ |a Lissowska, J.
|b 82
700 1 _ |a Brinton, L.
|b 83
700 1 _ |a Sherman, M. E.
|b 84
700 1 _ |a Bodelon, C.
|b 85
700 1 _ |a Hinsley, S.
|b 86
700 1 _ |a Lewsley, L. A.
|b 87
700 1 _ |a Glasspool, R.
|b 88
700 1 _ |a Banerjee, S. N.
|b 89
700 1 _ |a Stronach, E. A.
|b 90
700 1 _ |a Haluska, P.
|b 91
700 1 _ |a Ray-Coquard, I.
|b 92
700 1 _ |a Mahner, S.
|b 93
700 1 _ |a Winterhoff, B.
|b 94
700 1 _ |a Slamon, D.
|b 95
700 1 _ |a Levine, D. A.
|b 96
700 1 _ |a Kelemen, L. E.
|b 97
700 1 _ |a Benitez, J.
|b 98
700 1 _ |a Chang-Claude, J.
|0 P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253
|b 99
|u dkfz
700 1 _ |a Gronwald, J.
|b 100
700 1 _ |a Wu, A. H.
|b 101
700 1 _ |a Menon, U.
|b 102
700 1 _ |a Goodman, M. T.
|b 103
700 1 _ |a Schildkraut, J. M.
|b 104
700 1 _ |a Wentzensen, N.
|b 105
700 1 _ |a Brown, R.
|b 106
700 1 _ |a Berchuck, A.
|b 107
700 1 _ |a Chenevix-Trench, G.
|b 108
700 1 _ |a deFazio, A.
|b 109
700 1 _ |a Gayther, S. A.
|b 110
700 1 _ |a García, M. J.
|b 111
700 1 _ |a Henderson, M. J.
|b 112
700 1 _ |a Rossing, M. A.
|b 113
700 1 _ |a Beeghly-Fadiel, A.
|b 114
700 1 _ |a Fasching, P. A.
|b 115
700 1 _ |a Orsulic, S.
|b 116
700 1 _ |a Karlan, B. Y.
|b 117
700 1 _ |a Konecny, G. E.
|b 118
700 1 _ |a Huntsman, D. G.
|b 119
700 1 _ |a Bowtell, D. D.
|b 120
700 1 _ |a Brenton, J. D.
|b 121
700 1 _ |a Doherty, J. A.
|b 122
700 1 _ |a Pharoah, P. D. P.
|b 123
700 1 _ |a Ramus, S. J.
|b 124
773 _ _ |a 10.1016/j.annonc.2020.05.019
|g p. S0923753420398410
|0 PERI:(DE-600)2003498-2
|n 9
|p 1240-1250
|t Annals of oncology
|v 31
|y 2020
|x 0923-7534
909 C O |o oai:inrepo02.dkfz.de:156955
|p VDB
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 43
|6 P:(DE-He78)6b04712f3afe72044d496a25505cb1ea
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 44
|6 P:(DE-HGF)0
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 99
|6 P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253
913 1 _ |a DE-HGF
|l Krebsforschung
|1 G:(DE-HGF)POF3-310
|0 G:(DE-HGF)POF3-313
|2 G:(DE-HGF)POF3-300
|v Cancer risk factors and prevention
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
|b Gesundheit
914 1 _ |y 2020
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2020-01-11
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2020-01-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2020-01-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
|d 2020-01-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0320
|2 StatID
|b PubMed Central
|d 2020-01-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2020-01-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2020-01-11
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
|d 2020-01-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2020-01-11
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
|d 2020-01-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2020-01-11
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b ANN ONCOL : 2018
|d 2020-01-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2020-01-11
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2020-01-11
915 _ _ |a IF >= 10
|0 StatID:(DE-HGF)9910
|2 StatID
|b ANN ONCOL : 2018
|d 2020-01-11
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


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21