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Poster display session

3898 - Large-scale DNA organization is a prognostic marker of breast cancer survival

Date

11 Sep 2017

Session

Poster display session

Presenters

Martial Guillaud

Citation

Annals of Oncology (2017) 28 (suppl_5): v22-v42. 10.1093/annonc/mdx363

Authors

M. Guillaud1, M. Keyes2, Q. Ye3, A. Carraro3, A. Harrison3, M. Hayes4, A. Nichol5, S. Leung6

Author affiliations

  • 1 Integrative Oncology, BC Cancer Agency, Vancouver General Hospital University of British Columbia, v5z1l3 - Vancouver/CA
  • 2 Radiation Oncology, BC Cancer Agency, v5z1l3 - v/CA
  • 3 Integrative Oncology, BC Cancer Research Centre, v5z1l3 - Vancouver/CA
  • 4 Department Of Pathology, BC Cancer Agency, v5z1l3 - Vancouver/CA
  • 5 Radiation Oncology, BC Cancer Agency, v5z1l3 - Vancouver/CA
  • 6 Department Of Pathology, University of British Columbia, V6H 3Z6 - Vancouver/CA
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Resources

Abstract 3898

Background

Breast cancer is the leading cause of cancer-related deaths among women worldwide. Current clinicopathological parameters only partially encompass and predict biological diversity and therefore limit our ability to make informed treatment decisions and predict outcomes. The successful future of oncology will rely on our ability to correctly select patients who would benefit from chemotherapy or benefit from treatment intensification, and spare the rest from unnecessary exposure to toxic and expensive therapies. Tumour biology and prognostic markers may be the key to achieving the above goal. We investigated whether changes in Large scale DNA Organization (LDO) of tumour epithelial nuclei is an indicator of the aggressiveness of the tumour.

Methods

We tested our algorithm on a set of 172 TMA cores samples, coming from 95 breast cancer patients. Thirty five patients died of breast cancer and 60 were still alive 0 years after surgery. This TMA slide was stained with Feulgen-thionin and imaged using an high-resolution Imaging system. Automated segmentation of cell nuclei followed by manual selection of intact, in-focus nuclei resulted in an average of 50 cell nuclei per sample. Approximately 60 features measuring Large-scale DNA organization were calculated.

Results

Forward stepwise Linear Discriminant analysis selected 6 features that, combined linearly, gave the best discrimination between nuclei from alive patients specimens and nuclei from deceased patients specimens. Patient LDO score was defined as the percentage of cell nuclei with a high cell LDO. LDO algorithm correctly classified 82.1% patients, with a specificity of 79% and a sensitivity of 88%. Furthermore, individuals with a high LDO score had a 9x fold increase in relative risk of death. In the multivariate Cox regression model, LDO, Node status and Tumor Grade were all significant predictors of cancer death.

Conclusions

This data suggests that LDO could be used to identify patients more likely to have an aggressive disease and thus select a candidate for more aggressive or novel adjuvant therapies.

Clinical trial identification

Legal entity responsible for the study

Martial Guillaud

Funding

None

Disclosure

All authors have declared no conflicts of interest.

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