Dr Gavin Harris, Canterbury District Health Board
Using deep learning and digital pathology to intrinsically subtype breast cancer
24 months: $249,650
Digital pathology is the reviewing of tissue slides on a computer monitor rather than using microscopes. It is gaining momentum with anatomical pathology laboratories transitioning to this technology. In addition to increasing efficiency of pathologists to generate reports for clinicians treating breast cancer, digital pathology allows the application of computer algorithms that objectively quantify and standardise results. Studies have found that algorithms applied to digitally scanned slides can provide molecular data from breast cancer cases. This would otherwise require molecular testing, which not all patients can access due to cost. We wish to develop advanced machine-learning algorithms to automatically identify digital signatures of genomic changes in invasive breast cancers from tissue slides. This will be used to improve equity of access to testing and improve prediction of prognosis and response to treatment. The ultimate goal is to allow more tailored patient therapies to give the best clinical outcome possible.
Dr Annette Lasham, The University of Auckland
Validation of a liquid biopsy to predict recurrence in NZ breast cancer patients
18 months, $244,095
Early detection of breast cancer recurrence is critical for saving lives. We have identified two molecules, found in the blood of 250 patients at the time of surgery for breast cancer, that were very good at predicting which of these women would have a relapse before five years. We now want to validate these molecules on a new group of 400 NZ breast cancer patients, to see whether these molecules could be used as a blood test to predict disease recurrence. We also want to see if we can combine information from this blood test with existing clinical and pathological tests, to give doctors and patients greater knowledge about their prognosis. We will use advanced statistics to determine what information to include in order to generate the best prognostic test. This information could guide treatment decisions or suggest a requirement for closer surveillance of patients following surgery for breast cancer.
Barbara Lipert, The University of Auckland
Validation of predictive biomarkers for T-DM1 activity in HER2+ breast cancer
24 months, $195,571
The antibody-drug conjugate trastuzumab emtansine (T-DM1; Kadcyla) extends the survival of HER2-positive metastatic breast cancer patients. However, both acquired and intrinsic resistance limit its effectiveness and there are no reliable biomarkers for predicting the tumour response to T-DM1. Applying advanced genetic methods, we have identified a panel of 612 genes that we hypothesise to be involved in T-DM1 resistance. Here, we propose to validate the pre-selected candidate genes to select those with the highest potential to modify T-DM1 activity. We will apply cellular and animal models to check how inactivation of these genes influences the response to T-DM1. Finally, we will correlate their activity with the oncologic response of breast cancer patients to T-DM1 therapy. In the long term, our work could be applied to identify breast cancer patients most likely to benefit from T-DM1 or those patients who are most likely to develop resistance.
Dr Logan Walker, University of Otago
Analysis of full-length transcripts for variant classification in breast cancer
24 months, $186,149
(Funded fully by Breast Cancer Cure)
The future of successful genetic screening in New Zealand requires increased sensitivity and specificity of tests, and informed clinical management for high-risk breast cancer families.
To date a lot of attention has gone on BRCA1/2 and that focus remains, however for this study the focus is on other high-risk breast cancer genes which currently do not reliably have the specificity that we need as we often identify variants of unknown significance. Using the latest technology (nanopore sequencing – a world first) which involves splicing the full length of the isoforms for BARD1, CDH1, CHEK2, PTEN, PALB2 and TP3, we expect to more reliably identify the necessary mutations. This will ensure that clinicians, the individuals affected and their families will be more likely to be able to take actions to reduce the likelihood of developing disease. How – through better surveillance techniques, treatments, surgery all in the hope of reducing the risk of advanced breast cancer. Two of the research team are members of an international expert panel (https://clinicalgenome.org/affiliation/50039/) who have been charged with developing rules for doctors so they can interpret genetic results. It is because of these linkages that their findings will be applied within clinical diagnostic settings around the world.
Identification of cancer-causing mutations in breast cancer susceptibility genes has well-defined and actionable implications for disease prevention. Of added value, outcomes from this research will also be integrated into international guidelines and as a result people globally will benefit. In the future this work can be extended to moderate and high-risk genes and also to better understand potential differences across Maori and Pasifika for whom there are currently no reliable norms.
Phillipa Green, CEO of Breast Cancer Cure comments, “Funding these distinctly different, but equally compelling research submissions is our reason for being. All the fundraising events, the networking, the conferences and the meetings comes down to this – putting money into the scientists and laboratories that are working hard to find ways to beat the devasting effects of breast cancer. We are delighted to announce these successful recipients co-funded with BCFNZ and HRC, but equally thrilled to announce an additional recipient who we will fund entirely through our own organisation. We believe this research will put us on a path to making breast cancer a survivable disease.