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Harvey-Jones E, Raghunandan M, Robbez-Masson L, Magraner-Pardo L, Alaguthurai T, Yablonovitch A, Yen J, Xiao H, Brough R, Frankum J, Song F, Yeung J, Savy T, Gulati A, Alexander J, Kemp H, Starling C, Konde A, Marlow R, Cheang M, Proszek P, Hubank M, Cai M, Trendell J, Lu R, Liccardo R, Ravindran N, Llop-Guevara A, Rodriguez O, Balmana J, Lukashchuk N, Dorschner M, Drusbosky L, Roxanis I, Serra V, Haider S, Pettitt SJ, Lord CJ, Tutt ANJ. Longitudinal profiling identifies co-occurring BRCA1/2 reversions, TP53BP1, RIF1 and PAXIP1 mutations in PARP inhibitor-resistant advanced breast cancer. Ann Oncol 2024; 35:364-380. [PMID: 38244928 DOI: 10.1016/j.annonc.2024.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND Resistance to therapies that target homologous recombination deficiency (HRD) in breast cancer limits their overall effectiveness. Multiple, preclinically validated, mechanisms of resistance have been proposed, but their existence and relative frequency in clinical disease are unclear, as is how to target resistance. PATIENTS AND METHODS Longitudinal mutation and methylation profiling of circulating tumour (ct)DNA was carried out in 47 patients with metastatic BRCA1-, BRCA2- or PALB2-mutant breast cancer treated with HRD-targeted therapy who developed progressive disease-18 patients had primary resistance and 29 exhibited response followed by resistance. ctDNA isolated at multiple time points in the patient treatment course (before, on-treatment and at progression) was sequenced using a novel >750-gene intron/exon targeted sequencing panel. Where available, matched tumour biopsies were whole exome and RNA sequenced and also used to assess nuclear RAD51. RESULTS BRCA1/2 reversion mutations were present in 60% of patients and were the most prevalent form of resistance. In 10 cases, reversions were detected in ctDNA before clinical progression. Two new reversion-based mechanisms were identified: (i) intragenic BRCA1/2 deletions with intronic breakpoints; and (ii) intragenic BRCA1/2 secondary mutations that formed novel splice acceptor sites, the latter being confirmed by in vitro minigene reporter assays. When seen before commencing subsequent treatment, reversions were associated with significantly shorter time to progression. Tumours with reversions retained HRD mutational signatures but had functional homologous recombination based on RAD51 status. Although less frequent than reversions, nonreversion mechanisms [loss-of-function (LoF) mutations in TP53BP1, RIF1 or PAXIP1] were evident in patients with acquired resistance and occasionally coexisted with reversions, challenging the notion that singular resistance mechanisms emerge in each patient. CONCLUSIONS These observations map the prevalence of candidate drivers of resistance across time in a clinical setting, information with implications for clinical management and trial design in HRD breast cancers.
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Affiliation(s)
- E Harvey-Jones
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK; The Breast Cancer Now Research Unit, Guy's Hospital Cancer Centre, King's College London, UK; The City of London Cancer Research UK Centre at King's College London, UK
| | - M Raghunandan
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - L Robbez-Masson
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - L Magraner-Pardo
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - T Alaguthurai
- The Breast Cancer Now Research Unit, Guy's Hospital Cancer Centre, King's College London, UK
| | | | - J Yen
- Guardant Health Inc., Redwood City, USA
| | - H Xiao
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - R Brough
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - J Frankum
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - F Song
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - J Yeung
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - T Savy
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - A Gulati
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - J Alexander
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - H Kemp
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - C Starling
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - A Konde
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - R Marlow
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - M Cheang
- Clinical Trials and Statistics Unit, The Institute of Cancer Research, London, UK
| | - P Proszek
- Clinical Genomics, The Royal Marsden Hospital, London, UK
| | - M Hubank
- Clinical Genomics, The Royal Marsden Hospital, London, UK
| | - M Cai
- Guardant Health Inc., Redwood City, USA
| | - J Trendell
- The Breast Cancer Now Research Unit, Guy's Hospital Cancer Centre, King's College London, UK
| | - R Lu
- The Breast Cancer Now Research Unit, Guy's Hospital Cancer Centre, King's College London, UK
| | - R Liccardo
- The Breast Cancer Now Research Unit, Guy's Hospital Cancer Centre, King's College London, UK
| | - N Ravindran
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | | | - O Rodriguez
- Vall d'Hebron Institute of Oncology, Barcelona, Spain
| | - J Balmana
- Vall d'Hebron Institute of Oncology, Barcelona, Spain
| | | | | | | | - I Roxanis
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - V Serra
- Vall d'Hebron Institute of Oncology, Barcelona, Spain
| | - S Haider
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - S J Pettitt
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
| | - C J Lord
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
| | - A N J Tutt
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK; The Breast Cancer Now Research Unit, Guy's Hospital Cancer Centre, King's College London, UK; The City of London Cancer Research UK Centre at King's College London, UK.
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Rubio-Guivernau JL, Luengo-Oroz MA, Duloquin L, Savy T, Peyrieras N, Bourgine P, Santos A. Combining sea urchin embryo cell lineages by error-tolerant graph matching. Annu Int Conf IEEE Eng Med Biol Soc 2009; 2009:5918-21. [PMID: 19965057 DOI: 10.1109/iembs.2009.5334851] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Obtaining the complete cell lineage tree of an embryo's development is a very appealing and ambitious goal, but fortunately recent developments both in optical imaging and digital image processing are bringing it closer. However, when imaging the embryos (sea urchin embryos for this work) with high enough spatial resolution and short enough time-step to make cell segmentation and tracking possible, it is currently not possible to image the specimen throughout its all embryogenesis. For this reason it is interesting to explore how cell lineage trees extracted from two different embryos of the same species and imaged for overlapping periods of time can be concatenated, resulting in a single lineage tree covering both embryos' development time frames. To achieve this we used an error-tolerant graph matching strategy by selecting a time point at which both lineage trees overlap, and representing the information about each embryo at that time point as a graph in which nodes stand for cells and edges for neighborhood relationships among cells. The expected output of the graph matching algorithm is the minimal-cost correspondence between cells of both specimens, allowing us to perform the lineage combination.
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Affiliation(s)
- J L Rubio-Guivernau
- Biomedical Image Technologies Lab, DIE-ETSIT, Universidad Politécnica de Madrid, Madrid, Spain.
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