I. Roxanis
The significance of tumour microarchitectural features in breast cancer prognosis: a digital image analysis
Roxanis, I.; Colling, R.; Kartsonaki, C.; Green, A.R.; Rakha, E.A.
Authors
R. Colling
C. Kartsonaki
Dr Andy Green ANDREW.GREEN@NOTTINGHAM.AC.UK
ASSOCIATE PROFESSOR
Professor EMAD RAKHA Emad.Rakha@nottingham.ac.uk
PROFESSOR OF BREAST CANCER PATHOLOGY
Abstract
BACKGROUND: As only a minor portion of the information present in histological sections is accessible by eye, recognition and quantification of complex patterns and relationships among constituents relies on digital image analysis. In this study, our working hypothesis was that, with the application of digital image analysis technology, visually unquantifiable breast cancer microarchitectural features can be rigorously assessed and tested as prognostic parameters for invasive breast carcinoma of no special type.
METHODS: Digital image analysis was performed using public domain software (ImageJ) on tissue microarrays from a cohort of 696 patients, and validated with a commercial platform (Visiopharm). Quantified features included elements defining tumour microarchitecture, with emphasis on the extent of tumour-stroma interface. The differential prognostic impact of tumour nest microarchitecture in the four immunohistochemical surrogates for molecular classification was analysed. Prognostic parameters included axillary lymph node status, breast cancer-specific survival, and time to distant metastasis. Associations of each feature with prognostic parameters were assessed using logistic regression and Cox proportional models adjusting for age at diagnosis, grade, and tumour size.
RESULTS: An arrangement in numerous small nests was associated with axillary lymph node involvement. The association was stronger in luminal tumours (odds ratio (OR) = 1.39, p = 0.003 for a 1-SD increase in nest number, OR = 0.75, p = 0.006 for mean nest area). Nest number was also associated with survival (hazard ratio (HR) = 1.15, p = 0.027), but total nest perimeter was the parameter most significantly associated with survival in luminal tumours (HR = 1.26, p = 0.005). In the relatively small cohort of triple-negative tumours, mean circularity showed association with time to distant metastasis (HR = 1.71, p = 0.027) and survival (HR = 1.8, p = 0.02).
CONCLUSIONS: We propose that tumour arrangement in few large nests indicates a decreased metastatic potential. By contrast, organisation in numerous small nests provides the tumour with increased metastatic potential to regional lymph nodes. An outstretched pattern in small nests bestows tumours with a tendency for decreased breast cancer-specific survival. Although further validation studies are required before the argument for routine quantification of microarchitectural features is established, our approach is consistent with the demand for cost-effective methods for triaging breast cancer patients that are more likely to benefit from chemotherapy.
Citation
Roxanis, I., Colling, R., Kartsonaki, C., Green, A., & Rakha, E. (2018). The significance of tumour microarchitectural features in breast cancer prognosis: a digital image analysis. Breast Cancer Research, 20(11), https://doi.org/10.1186/s13058-018-0934-x
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 10, 2018 |
Publication Date | Feb 5, 2018 |
Deposit Date | Mar 27, 2018 |
Publicly Available Date | Mar 27, 2018 |
Journal | Breast Cancer Research |
Print ISSN | 1465-5411 |
Electronic ISSN | 1465-542X |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 20 |
Issue | 11 |
DOI | https://doi.org/10.1186/s13058-018-0934-x |
Keywords | Breast cancer; Digital image analysis; Prognosis; Microarchitecture; Tumour nests |
Public URL | https://nottingham-repository.worktribe.com/output/910210 |
Publisher URL | https://breast-cancer-research.biomedcentral.com/articles/10.1186/s13058-018-0934-x |
Contract Date | Mar 27, 2018 |
Files
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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0
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