Background: Recent studies have demonstrated that women with early stage ER-positive (ER+) and HER2-negative (HER2-) breast cancer have a persistent risk of recurrence and cancer related death up to 20 years post diagnosis, highlighting the chronic nature of ER+ breast cancer and critical need to identify tumor characteristics that are more predictive of risk of recurrence than standard clinical covariates. However, progress in delineating the dynamics of breast cancer relapse and biomarkers of late recurrence has been hindered by the lack of large cohorts with long-term clinical follow-up and molecular information. Methods: We report the results of a cohort of 3,240 breast cancer patients from the United Kingdom and Canada with 20 years of follow-up (median 9.75 years), including 1,980 with accompanying molecular data from the primary breast tumor. Information for each patient on loco-regional recurrence (LR), distant recurrence (DR), and site(s) of metastases was collected. We developed a non-homogenous Markov chain model that accounted for different clinical endpoints and timescales, as well as competing risks of mortality and the distinct baseline hazards that characterize different molecular subgroups. This approach enabled robust analysis of the spatio-temporal dynamics of breast cancer recurrence across the clinical subgroups, PAM50 subgroups and the integrative clusters, while also enabling individual risk of relapse predictions. Results: We employed our multistate model to compute the probability of experiencing a LR or DR, as well as the baseline transition probabilities from surgery, LR or DR at various time intervals for average individuals in each of the clinical/molecular subgroups. These analyses reveal four late-recurring ER+ (predominantly HER2-) subgroups, together accounting for 26% of all ER+ tumors, with high (median 42-55%) risk of recurrence up to 20 years post-diagnosis. Each of these four subgroups maps to one of the Integrative Clusters, defined based on genomic copy number alterations and gene expression, and is enriched for a characteristic copy number amplification events: 11q13 (CCND1, RSF1), 8p12 (FGFR1, ZNF703), 17q23 (RPS6KB1) and 8q24 (MYC). These four molecular subgroups are superior in predicting late DR than standard clinical variables. Conclusions: A detailed understanding of the rates and routes of metastasis and their variability across the distinct molecular subtypes is essential for devising personalized approaches to breast cancer care. We describe a molecularly characterized breast cancer cohort with long-term clinical follow-up and a statistical modeling framework, enabling delineation of the dynamics of breast cancer recurrence at unprecedented resolution. These analyses reveal four late recurring ER+ subgroups and accompanying biomarkers that collectively define the quarter of ER+ cases at highest risk of recurrence. Our findings highlight opportunities for improved patient stratification and biomarker-driven clinical trials directed at the subset of breast cancer patients with persistent risk of recurrence. Citation Format: Curtis C, Rueda OM, Sammut S-J, Chin S-F, Caswell-Jin JL, Seoane JA, Callari M, Batra R, Pereira B, Bruna A, Ali HR, Provenzano E, Liu B, Parisien M, Gillett C, McKinney S, Green A, Murphy L, Purushotham A, Ellis I, Pharoah P, Rueda C, Aparicio S, Caldas C. Dynamics of breast cancer relapse reveal molecularly defined late recurring ER-positive subgroups: Results from the METABRIC study [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr GS3-06.

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Background: The Rational Therapy for Breast Cancer (RATHER) Consortium aims to identify novel kinase targets for therapy in poor-prognosis subtypes of breast cancer for which there are currently no targeted therapies available. In this project, the focus is on invasive lobular carcinomas (ILC), which represent 10% of breast tumors. The main strength of the RATHER project is the unique combination of comprehensive molecular data together with detailed clinical information, which enables translation of state-of-the art genomics analyses to the clinic. Our main goal is to identify and validate novel kinase targets for breast cancer therapy in a comprehensive way using large-scale and complementary genomics data (DNA and RNA sequence, copy number variation, gene expression and protein expression). Integrated analysis of these molecular data is performed to define molecular subtypes of ILC with differential clinical outcome. Methods: One hundred and fifty ILC samples (fresh frozen) with >5 years follow-up were collected from two institutes (Cambridge, Netherlands Cancer Institute). All samples were processed following one standard operating protocol to isolate RNA, DNA and protein of high quality. We used a five-pronged approach to identify and validate novel kinase targets for therapy in ILC, namely i) direct re-sequencing of the kinome of 150 ILC breast tumors, ii) determination of abundance and activation status of kinases in these tumors by reverse phase protein lysate array (RPPA) technology, iii) determination of copy number variation (CNV) by genome-wide SNP arrays, iv) mRNA quantitation of both genome and kinome using DNA microarrays and v) RNAseq of a subset of ILC tumors. ILC are compared to triple negative, which allows us to highlight differences and/or similarities between these subtypes and provide clues for therapeutic targets. Results: Data from these independent genome-scale technologies were integrated, yielding a prioritized list of potential kinase targets for therapy in ILC breast cancer. Deep sequencing of the kinome has revealed somatic mutations characteristic of ILC, which are currently being validated via mass spectrometry-based genotyping technology and their possible effects confirmed with gene expression, protein expression and phosphorylation changes. In addition, on a subset of the ILC samples, RNA sequencing was performed to confirm expression of particular mutants. Known gene mutations in ILC such as loss of CDH1 were confirmed. Moreover, the PI3K pathway is found to be frequently altered (50% of the samples). Gene expression analysis, as well as integrative analysis of CNV and gene expression data revealed subsets of ILCs that significantly regulate alternate biological processes and show differential clinical outcome. Such biological subsets are currently being validated with clinical and follow-up data. Updated results will be presented at the meeting. Conclusion: The RATHER project aims to deliver proof-of-concept for novel therapeutic interventions, together with companion molecular diagnostic assays for patient stratification, for up to 10% of breast cancer patients, where current treatment options are unsatisfactory. Ongoing validation of a number of potential targets proves to be promising. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P6-04-02.

Background: BRCA1/2 mutation carriers (gBRCA) have a higher risk of breast or ovarian cancer, since BRCA1/2 mutation results in impaired high-fidelity DNA repair by homologous recombination (HR) and subsequently genetic instability. In non-gBRCA TNBC, HR deficiency occurs at the somatic level, by means of BRCA1 mutation, BRCA1 epigenetic loss or mutation in other HR-associated genes. Because PARP1/2 inhibitors (PARPi) are well-tolerated and active anti-cancer agents in the advanced setting of gBRCA tumors, we sought to expand their applicability by identifying response biomarkers in TNBC. Methods: We have assessed the antitumor response of the PARP1/2 inhibitor olaparib as single agent in a panel of 12 primary and advanced TNBC PDX models. On PDXs exhibiting primary sensitivity to olaparib, we have developed models of acquired resistance by continuous exposure to the drug and identifying progression on treatment. We have characterized the models through targeted sequencing and the analysis of the hypermethylation and expression levels of BRCA1 transcript to find potential correlates of drug-sensitivity. Results: Three out of 12 PDXs (25%) treated with single agent olaparib, exhibit tumor regression or disease stabilization. BRCA1 is hypermethylated in two of these PARPi-sensitive TNBC PDX models and is associated with loss of BRCA1 mRNA expression. The third PARPi-sensitive TNBC PDX harbors a frameshift, heterozygous PALB2 mutation, which is no longer detected in the acquired resistance PDX model. Acquired resistance in the hypermethylated PDXs is under study as well as the duration of response compared to gBRCA PDX models. Conclusions: Our study highlights that somatic HR-deficiency is frequent in TNBC and provides the basis of sensitivity to PARPi. Citation Format: Serra V, Cruz C, Bruna A, Ibrahim YH, Vivancos A, Vivancos A, Nuciforo P, Bellet M, Gómez P, Pérez JM, Saura C, Vidal M, Serres X, Rueda OM, Peg V, Caldas C, O'Connor MJ, Baselga J, Cortés J. PARP1/2 inhibition in a subset of triple negative breast cancer (TNBC) patient-derived tumor xenografts (PDX) identifies predictive biomarkers of response. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-07-04.

Backgound and Aim: The best test to guide the choice of systemic therapy for breast cancer (BC) has not yet been identified. We did this study to identify factors that drive proliferation features in BC and assess their association with clinical outcomes after systemic therapy. Methods: We applied an artificial neural network-based integrative data mining approach to three cohorts of patients with untreated lymph node (LN)-negative BC (Wang et al; n=286, Desmedt et al; n=198 and Schmidt et al; n=200). The results were validated in four cohorts of BC patients (the Nottingham discovery cohort (n=171), Uppsala cohort (n=249), The Cancer Genome Atlas-Breast Cancer project [TCGA-BRCA; n= 970] and Molecular Taxonomy of Breast Cancer International Consortium [METABRIC cohort; n=1980]. Genes that featured prominently in our interactome map of proliferation have been chosen to take them forward to investigate their clinicopathological relevance of their gene copy number aberrations (CNAs), mRNA transcript expression, and protein expression and their associations with breast cancer-specific survival (BCSS), distant relapse-free survival (DRFS) and pathological complete response (pCR) in ten international cohorts of BC (n>12000 patients). Findings: ESR1, SPAG5, EGFR, BCL2, and FOXA1 were among the 39 common gene probes that were predictive across most proliferation features and datasets. In TCGA-BRCA cohort, SPAG5 gene mutation, gain/amplification and loss at the Ch17q11.2 locus were detected in 43 (4.4%), 177 (18.2%) and 180 (18.8%) of 970 patients, respectively and 65 (31%) of 479 ER-positive /HER-positive patients showed gain/amplification of SPAG5 gene. In multivariable analysis, high SPAG5 transcript and SPAG5 protein expression were associated with reduced BCSS compared with lower expression (METABRIC: HR 1·27, 95% CI 1·02–1·58, p=0·034; untreated LN-negative cohort: 2·34, 1·24–4·42, p=0·0090; and Nottingham-cohort: 1·73, 1·23–2·46, p=0·0020). In patients with ER-negative/HER2-negative or ER-positive/HER2-negative BC, high SPAG5 transcript expression was associated with an increased pCR compared with low SPAG5 transcript expression after receiving anthracycline neoadjuvant chemotherapy (AC-NeoACT) [(Multicentre phase 2 clinical trial cohort; n=136; OR 2·47, 95% CI 1·17–5·21, p=0.016) and (MD Anderson- taxane+AC-NeoACT cohort; n=287; OR 3·16, 95% CI 1·46–6·84, p=0.003); respectively]. In patients with ER-positive/HER2-negative BC who received taxane+AC-NeoACT followed by adjuvant tamoxifen (Adj-Tam) for 5 years (MD Anderson- taxane+AC-NeoACT cohort; n=287), high and low SPAG5 transcript expression had similar DRFS (HR 1·40, 95% CI 0.76–2·58, p=0.282). Whereas in ER-positive/HER2-negative BC patients who received only adj-Tam (n=298), high SPAG5 transcript expression was associated with reduced DRF at 5 years compared with lower expression (HR 1.98, 95% CI 1.19–3.27, p=0.008). Interpretation: The transcript and protein products of SPAG5 are independent prognostic and predictive biomarkers that might have clinical utility as biomarkers for combination cytotoxic chemotherapy sensitivity in ER-positive/HER-negative BC. Citation Format: Abdel-Fatah TMA, Agarwal D, Zafeiris D, Pongor L, Györffy B, Rueda OM, Moseley PM, Green AR, Liu D-X, Pockley AG, Rees RC, Caldas C, Ellis IO, Ball GR, Chan SYT. Identification of proliferation related derivers and their roles in precision medicine for breast cancers: A retrospective multidimensional comparative, integrated genomic, transcriptomic, and protein analysis [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-09-16.