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- Buddenkotte, Thomas, et al.
(author)
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Deep learning-based segmentation of multisite disease in ovarian cancer
- 2023
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In: EUROPEAN RADIOLOGY EXPERIMENTAL. - : Springer Nature. - 2509-9280. ; 7:1
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Journal article (peer-reviewed)abstract
- Purpose: To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods.Methods: A deep learning model for the two most common disease sites of high-grade serous ovarian cancer lesions (pelvis/ovaries and omentum) was developed and compared against the well-established “no-new-Net” framework and unrevised trainee radiologist segmentations. A total of 451 CT scans collected from four different institutions were used for training (n = 276), evaluation (n = 104) and testing (n = 71) of the methods. The performance was evaluated using the Dice similarity coefficient (DSC) and compared using a Wilcoxon test.Results: Our model outperformed no-new-Net for the pelvic/ovarian lesions in cross-validation, on the evaluation and test set by a significant margin (p values being 4 × 10–7, 3 × 10–4, 4 × 10–2, respectively), and for the omental lesions on the evaluation set (p = 1 × 10–3). Our model did not perform significantly differently in segmenting pelvic/ovarian lesions (p = 0.371) compared to a trainee radiologist. On an independent test set, the model achieved a DSC performance of 71 ± 20 (mean ± standard deviation) for pelvic/ovarian and 61 ± 24 for omental lesions.Conclusion: Automated ovarian cancer segmentation on CT scans using deep neural networks is feasible and achieves performance close to a trainee-level radiologist for pelvic/ovarian lesions.Relevance statement: Automated segmentation of ovarian cancer may be used by clinicians for CT-based volumetric assessments and researchers for building complex analysis pipelines.Key points:The first automated approach for pelvic/ovarian and omental ovarian cancer lesion segmentation on CT images has been presented.Automated segmentation of ovarian cancer lesions can be comparable with manual segmentation of trainee radiologists.Careful hyperparameter tuning can provide models significantly outperforming strong state-of-the-art baselines. Graphical Abstract: [Figure not available: see fulltext.]
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| 2. |
- Coward, Jermaine, et al.
(author)
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Interleukin-6 as a Therapeutic Target in Human Ovarian Cancer
- 2011
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In: Clinical Cancer Research. - 1078-0432. ; 17:18, s. 6083-6096
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Journal article (peer-reviewed)abstract
- Purpose: We investigated whether inhibition of interleukin 6 (IL-6) has therapeutic activity in ovarian cancer via abrogation of a tumor-promoting cytokine network. Experimental Design: We combined preclinical and in silico experiments with a phase 2 clinical trial of the anti-IL-6 antibody siltuximab in patients with platinum-resistant ovarian cancer. Results: Automated immunohistochemistry on tissue microarrays from 221 ovarian cancer cases showed that intensity of IL-6 staining in malignant cells significantly associated with poor prognosis. Treatment of ovarian cancer cells with siltuximab reduced constitutive cytokine and chemokine production and also inhibited IL-6 signaling, tumor growth, the tumor-associated macrophage infiltrate and angiogenesis in IL-6-producing intraperitoneal ovarian cancer xenografts. In the clinical trial, the primary endpoint was response rate as assessed by combined RECIST and CA125 criteria. One patient of eighteen evaluable had a partial response, while seven others had periods of disease stabilization. In patients treated for 6 months, there was a significant decline in plasma levels of IL-6-regulated CCL2, CXCL12, and VEGF. Gene expression levels of factors that were reduced by siltuximab treatment in the patients significantly correlated with high IL-6 pathway gene expression and macrophage markers in microarray analyses of ovarian cancer biopsies. Conclusion: IL-6 stimulates inflammatory cytokine production, tumor angiogenesis, and the tumor macrophage infiltrate in ovarian cancer and these actions can be inhibited by a neutralizing anti-IL-6 antibody in preclinical and clinical studies. Clin Cancer Res; 17(18); 6083-96. (C) 2011 AACR.
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| 3. |
- Heinze, Karolin, et al.
(author)
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Validated biomarker assays confirm ARID1A loss is confounded with MMR deficiency, CD8 TIL infiltration, and provides no independent prognostic value in endometriosis-associated ovarian carcinomas.
- 2021
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In: The Journal of pathology. - : Wiley. - 1096-9896 .- 0022-3417. ; 256:4, s. 388-401
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Journal article (peer-reviewed)abstract
- ARID1A (BAF250a) is a component of the SWI/SNF chromatin modifying complex, plays an important tumour suppressor role, and is considered prognostic in several malignancies. However, in ovarian carcinomas there are contradictory reports on its relationship to outcome, immune response, and correlation with clinicopathological features. We assembled a series of 1,623 endometriosis-associated ovarian carcinomas, including 1,078 endometrioid (ENOC) and 545 clear cell (CCOC) ovarian carcinomas through combining resources of the Ovarian Tumor Tissue Analysis (OTTA) Consortium, the Canadian Ovarian Unified Experimental Resource (COEUR), local, and collaborative networks. Validated immunohistochemical surrogate assays for ARID1A mutations were applied to all samples. We investigated associations between ARID1A loss/mutation, clinical features, outcome, CD8+ tumour-infiltrating lymphocytes (CD8+ TIL), and DNA mismatch repair deficiency (MMRd). ARID1A loss was observed in 42% of CCOC and 25% of ENOC. We found no associations between ARID1A loss and outcomes, stage, age, or CD8+ TIL status in CCOC. Similarly, we found no association with outcome or stage in endometrioid cases. In ENOC, ARID1A loss was more prevalent in younger patients (p=0.012), and associated with MMRd (p<0.001), and presence of CD8+ TIL (p=0.008). Consistent with MMRd being causative of ARID1A mutations, in a subset of ENOC we also observed an association between ARID1A loss-of-function mutation as a result of small indels (p=0.035, versus single nucleotide variants). In ENOC, the association between ARID1A loss, CD8+ TIL, and age, appears confounded by MMRd status. Although this observation does not explicitly rule out a role for ARID1A influence on CD8+ TIL infiltration in ENOC, given current knowledge regarding MMRd, it seems more likely that effects are dominated by the hypermutation phenotype. This large dataset with consistently applied biomarker assessment now provides a benchmark for the prevalence of ARID1A loss-of-function mutations in endometriosis-associated ovarian cancers and brings clarity to the prognostic significance. This article is protected by copyright. All rights reserved.
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