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Meta-Analysis
. 2020 Sep;31(9):1240-1250.
doi: 10.1016/j.annonc.2020.05.019. Epub 2020 May 28.

Prognostic gene expression signature for high-grade serous ovarian cancer

J Millstein  1 T Budden  2 E L Goode  3 M S Anglesio  4 A Talhouk  5 M P Intermaggio  6 H S Leong  7 S Chen  8 W Elatre  9 B Gilks  10 T Nazeran  11 M Volchek  12 R C Bentley  13 C Wang  14 D S Chiu  11 S Kommoss  15 S C Y Leung  11 J Senz  10 A Lum  11 V Chow  11 H Sudderuddin  11 R Mackenzie  11 J George  16 AOCS Group  17 S Fereday  18 J Hendley  18 N Traficante  18 H Steed  19 J M Koziak  20 M Köbel  21 I A McNeish  22 T Goranova  23 D Ennis  22 G Macintyre  23 D Silva De Silva  23 T Ramón Y Cajal  24 J García-Donas  25 S Hernando Polo  26 G C Rodriguez  27 K L Cushing-Haugen  28 H R Harris  29 C S Greene  30 R A Zelaya  31 S Behrens  32 R T Fortner  32 P Sinn  33 E Herpel  34 J Lester  35 J Lubiński  36 O Oszurek  36 A Tołoczko  36 C Cybulski  36 J Menkiszak  37 C L Pearce  38 M C Pike  39 C Tseng  40 J Alsop  41 V Rhenius  41 H Song  41 M Jimenez-Linan  42 A M Piskorz  23 A Gentry-Maharaj  43 C Karpinskyj  43 M Widschwendter  44 N Singh  45 C J Kennedy  46 R Sharma  47 P R Harnett  48 B Gao  48 S E Johnatty  49 R Sayer  50 J Boros  46 S J Winham  14 G L Keeney  51 S H Kaufmann  52 M C Larson  14 H Luk  53 B Y Hernandez  53 P J Thompson  54 L R Wilkens  53 M E Carney  55 B Trabert  56 J Lissowska  57 L Brinton  56 M E Sherman  58 C Bodelon  56 S Hinsley  59 L A Lewsley  59 R Glasspool  60 S N Banerjee  61 E A Stronach  62 P Haluska  63 I Ray-Coquard  64 S Mahner  65 B Winterhoff  66 D Slamon  67 D A Levine  68 L E Kelemen  69 J Benitez  70 J Chang-Claude  71 J Gronwald  36 A H Wu  40 U Menon  43 M T Goodman  54 J M Schildkraut  72 N Wentzensen  56 R Brown  73 A Berchuck  74 G Chenevix-Trench  49 A deFazio  46 S A Gayther  75 M J García  76 M J Henderson  77 M A Rossing  29 A Beeghly-Fadiel  78 P A Fasching  79 S Orsulic  35 B Y Karlan  35 G E Konecny  67 D G Huntsman  80 D D Bowtell  18 J D Brenton  23 J A Doherty  81 P D P Pharoah  82 S J Ramus  83
Collaborators, Affiliations
Meta-Analysis

Prognostic gene expression signature for high-grade serous ovarian cancer

J Millstein et al. Ann Oncol. 2020 Sep.

Abstract

Background: 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.

Patients and methods: 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.

Results: 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.

Conclusion: 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.

Keywords: formalin-fixed paraffin-embedded; gene expression; high-grade serous ovarian cancer; overall survival; prognosis.

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Conflict of interest statement

Disclosure BYK served on Invitae Corporation's Advisory Board from 2017 to 2018. IAM has acted on the Advisory Boards for AstraZeneca, Clovis Oncology, Tesaro, Carrick Therapeutics and Takeda. His institution receives funding from AstraZeneca. RG is on the Advisory Boards for AstraZeneca, Tesaro, Clovis and Immunogen and does consultancy work for SOTIO. She has received support to attend conferences from AstraZeneca, Roche and Tesaro. Her institution has received research funding from Boehringer Ingelheim and Lilly/Ignyta and she is the national co-ordinating investigator for the UK for trials sponsored by AstraZeneca and Tesaro and site principal investigator for trials sponsored by AstraZeneca, Tesaro, Immunogen, Pfizer, Lilly and Clovis. PAF has received grants from Novartis, BioNtech and Cepheid as well as personal fees from Novartis, Roche, Pfizer, Celgene, Daiichi-Sankyo, TEVA, Astra Zeneca, Merck Sharp & Dohme, Myelo Therapeutics, MacroGenics, Eisai and Puma during the conduct of the study. JDB has acted on Advisory Boards for AstraZeneca and has received support from GSK to attend conferences. His institution receives funding from AstraZeneca and Aprea. UM has shares in Abcodia Ltd. Sandra Orsulic and Beth Y. Karlan have patents on predictive gene signatures in ovarian cancer (US010253368 and EU2908913). All remaining authors have declared no conflicts of interest.

Figures

Figure 1.
Figure 1.. Schematic of study design.
*The TRI study was split across the training and validation sets due to 107 samples overlapping with the meta-analysis. GWAS, genome-wide association studies; HGSOC, high-grade serous ovarian cancer.
Figure 2.
Figure 2.. Receiver operator characteristic (ROC) curves for prognostic performance of the gene expression signature in independent high-grade serous ovarian cancer patients (testing data).
There was no overlap between studies or patient data used to develop models (training data) and construct ROC curves and calculate area under the curve (AUC) values shown here (testing data). All models included age and stage as described in Methods section. TP denotes the true positive rate (sensitivity) and FP denotes the false positive rate (1 − specificity).
Figure 3.
Figure 3.. KaplaneMeier curves of overall survival for patients (A) in the training and (B) testing sets.
Patients were assigned to quintiles (Q1–Q5) of the signature score including age and stage. Shaded areas indicate 95% confidence regions, only included for plots representing larger sample sizes. Because of limited sample size, the following plots represent all such patients in the entire dataset, training or testing: (C) no macroscopic residual disease after debulking surgery, (D) primary chemotherapy treatment ≥4 cycles of intravenous (IV) carboplatin area under the curve (AUC) 5 or 6 and paclitaxel 135 or 175 mg/m2 every 3 weeks (actual dose known or presumed), (E) BRCA1 or BRCA2 germline mutation and (F) CD8 > 19.

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