Clinical and molecular predictors of very late recurrence in oestrogen receptor-positive breast cancer patients.

BACKGROUND: Risk of recurrence from primary ER+ breast cancer continues for at least 20 years. We aimed to identify clinical and molecular features associated with risk of recurrence after 10 years. METHODS: ER+ breast cancers from patients with and without recurrence were analysed with the BC360 NanoString Panel and an 87 gene targeted-exome panel. Frequency of clinical, pathologic and molecular characteristics was compared between cases (recurred between 10 and 20 years) and controls (no recurrence by 20 years) in the Very Late Recurrence (VLR) cohort. Analogous data from METABRIC were examined to confirm or refute findings. RESULTS: VLR cases had larger tumours and higher node positivity. Both VLR and METABRIC cases had higher clinical treatment score at 5 years (CTS5). There was a trend for fewer GATA3 mutations in cases in both VLR and METABRIC but no statistically significant differences in mutation frequency. Cell cycle and proliferation genes were strongly expressed in VLR cases. Immune-related genes and cell cycle inhibitors were highly expressed in controls. Neither of these changes were significant after correction for multiple testing. CONCLUSIONS: Clinicopathologic features are prognostic beyond 10 years. Conversely, molecular features, such as copy number alterations, TP53 mutations and intrinsic subtype which have early prognostic significance, have little prognostic value after 10 years.

Molecular profiling of aromatase inhibitor sensitive and resistant ER+HER2- postmenopausal breast cancers.

Aromatase inhibitors (AIs) reduce recurrences and mortality in postmenopausal patients with oestrogen receptor positive (ER+) breast cancer (BC), but >20% of patients will eventually relapse. Given the limited understanding of intrinsic resistance in these tumours, here we conduct a large-scale molecular analysis to identify features that impact on the response of ER + HER2- BC to AI. We compare the 15% of poorest responders (PRs, n = 177) as measured by proportional Ki67 changes after 2 weeks of neoadjuvant AI to good responders (GRs, n = 190) selected from the top 50% responders in the POETIC trial and matched for baseline Ki67 categories. In this work, low ESR1 levels are associated with poor response, high proliferation, high expression of growth factor pathways and non-luminal subtypes. PRs having high ESR1 expression have similar proportions of luminal subtypes to GRs but lower plasma estradiol levels, lower expression of estrogen response genes, higher levels of tumor infiltrating lymphocytes and immune markers, and more TP53 mutations.

Relationship between ER expression by IHC or mRNA with Ki67 response to aromatase inhibition: a POETIC study.

BACKGROUND: In clinical practice, oestrogen receptor (ER) analysis is almost entirely by immunohistochemistry (IHC). ASCO/CAP recommends cut-offs of < 1% (negative) and 1-10% (low) cells positive. There is uncertainty whether patients with ER low tumours benefit from endocrine therapy. We aimed to assess IHC and mRNA cut-points for ER versus biological response of primary breast cancer to 2 weeks' aromatase inhibitor treatment as measured by change in Ki67. METHODS: Cases were selected from the aromatase inhibitor treatment group of POETIC. We selected the 15% with the poorest Ki67 response (PR, < 40% Ki67 suppression, n = 230) and a random 30% of the remainder categorised as intermediate (IR, 40-79% Ki67 suppression, n = 150) and good-responders (GR, ≥ 80% Ki67 suppression, n = 230) from HER2 - group. All HER2 + cases available were selected irrespective of their response category (n = 317). ER expression was measured by IHC and qPCR. RESULTS: ER IHC was available from 515 HER2 - and 186 HER2 + tumours and ER qPCR from 367 HER2 - and 171 HER2 + tumours. Ninety-one percentage of patients with ER IHC < 10% were PRs with similar rates in HER2 - and HER2 + cases. At or above ER IHC 10% substantial numbers of patients showed IR or GR. Similar proportions of patients were defined by cut-points of ER IHC < 10% and ER mRNA < 5 units. In addition, loss of PgR expression altered ER anti-proliferation response with 92% of PgR - cases with ER IHC < 40% being PRs. CONCLUSIONS: There was little responsiveness at IHC < 10% and no distinction between < 1% and 1-10% cells positive. Similar separation of PRs from IR/GRs was achieved by IHC and mRNA.

HER2-enriched subtype and novel molecular subgroups drive aromatase inhibitor resistance and an increased risk of relapse in early ER+/HER2+ breast cancer.

BACKGROUND: Oestrogen receptor positive/ human epidermal growth factor receptor positive (ER+/HER2+) breast cancers (BCs) are less responsive to endocrine therapy than ER+/HER2- tumours. Mechanisms underpinning the differential behaviour of ER+HER2+ tumours are poorly characterised. Our aim was to identify biomarkers of response to 2 weeks' presurgical AI treatment in ER+/HER2+ BCs. METHODS: All available ER+/HER2+ BC baseline tumours (n=342) in the POETIC trial were gene expression profiled using BC360™ (NanoString) covering intrinsic subtypes and 46 key biological signatures. Early response to AI was assessed by changes in Ki67 expression and residual Ki67 at 2 weeks (Ki672wk). Time-To-Recurrence (TTR) was estimated using Kaplan-Meier methods and Cox models adjusted for standard clinicopathological variables. New molecular subgroups (MS) were identified using consensus clustering. FINDINGS: HER2-enriched (HER2-E) subtype BCs (44.7% of the total) showed poorer Ki67 response and higher Ki672wk (p<0.0001) than non-HER2-E BCs. High expression of ERBB2 expression, homologous recombination deficiency (HRD) and TP53 mutational score were associated with poor response and immune-related signatures with High Ki672wk. Five new MS that were associated with differential response to AI were identified. HER2-E had significantly poorer TTR compared to Luminal BCs (HR 2.55, 95% CI 1.14-5.69; p=0.0222). The new MS were independent predictors of TTR, adding significant value beyond intrinsic subtypes. INTERPRETATION: Our results show HER2-E as a standardised biomarker associated with poor response to AI and worse outcome in ER+/HER2+. HRD, TP53 mutational score and immune-tumour tolerance are predictive biomarkers for poor response to AI. Lastly, novel MS identify additional non-HER2-E tumours not responding to AI with an increased risk of relapse. FUNDING: Cancer Research UK (CRUK/07/015).

Impact of Duration of Neoadjuvant Aromatase Inhibitors on Molecular Expression Profiles in Estrogen Receptor-positive Breast Cancers.

PURPOSE: Aromatase inhibitor (AI) treatment is the standard of care for postmenopausal women with primary estrogen receptor-positive breast cancer. The impact of duration of neoadjuvant endocrine therapy (NET) on molecular characteristics is still unknown. We evaluated and compared changes of gene expression profiles under short-term (2-week) versus longer-term neoadjuvant AIs. EXPERIMENTAL DESIGN: Global gene expression profiles from the PeriOperative Endocrine Therapy for Individualised Care (POETIC) trial (137 received 2 weeks of AIs and 47 received no treatment) and targeted gene expression from 80 patients with breast cancer treated with NET for more than 1 month (NeoAI) were assessed. Intrinsic subtyping, module scores covering different cancer pathways and immune-related genes were calculated for pretreated and posttreated tumors. RESULTS: The differences in intrinsic subtypes after NET were comparable between the two cohorts, with most Luminal B (90.0% in the POETIC trial and 76.3% in NeoAI) and 50.0% of HER2 enriched at baseline reclassified as Luminal A or normal-like after NET. Downregulation of proliferative-related pathways was observed after 2 weeks of AIs. However, more changes in genes from cancer-signaling pathways such as MAPK and PI3K/AKT/mTOR and immune response/immune-checkpoint components that were associated with AI-resistant tumors and differential outcome were observed in the NeoAI study. CONCLUSIONS: Tumor transcriptional profiles undergo bigger changes in response to longer NET. Changes in HER2-enriched and Luminal B subtypes are similar between the two cohorts, thus AI-sensitive intrinsic subtype tumors associated with good survival might be identified after 2 weeks of AI. The changes of immune-checkpoint component expression in early AI resistance and its impact on survival outcome warrants careful investigation in clinical trials.

Inactivating NF1 Mutations Are Enriched in Advanced Breast Cancer and Contribute to Endocrine Therapy Resistance.

PURPOSE: Advanced breast cancer (ABC) has not been subjected to the same degree of molecular scrutiny as early primary cancer. Breast cancer evolves with time and under the selective pressure of treatment, with the potential to acquire mutations with resistance to treatment and disease progression. To identify potentially targetable mutations in advanced breast cancer, we performed prospective molecular characterization of a cohort of patients with ABC. EXPERIMENTAL DESIGN: Biopsies from patients with advanced breast cancer were sequenced with a 41 genes targeted panel in the ABC Biopsy (ABC-Bio) study. Blood samples were collected at disease progression for circulating tumor DNA (ctDNA) analysis, along with matched primary tumor to assess for acquisition in ABC in a subset of patients. RESULTS: We sequenced 210 ABC samples, demonstrating enrichment compared with primary disease for potentially targetable mutations in HER2 (in 6.19% of samples), AKT1 (7.14%), and NF1 (8.10%). Of these enriched mutations, we show that NF1 mutations were frequently acquired in ABC, not present in the original primary disease. In ER-positive cancer cell line models, loss of NF1 resulted in endocrine therapy resistance, through both ER-dependent and -independent mechanisms. NF1 loss promoted ER-independent cyclin D1 expression, which could be therapeutically targeted with CDK4/6 inhibitors in vitro. Patients with NF1 mutations detected in baseline circulating tumor DNA had a good outcome on the CDK4/6 inhibitor palbociclib and fulvestrant. CONCLUSIONS: Our research identifies multiple therapeutic opportunities for advanced breast cancer and identifies the previously underappreciated acquisition of NF1 mutations.

Genomic Instability and TP53 Genomic Alterations Associate With Poor Antiproliferative Response and Intrinsic Resistance to Aromatase Inhibitor Treatment.

PURPOSE: Although aromatase inhibitor (AI) treatment is effective in estrogen receptor-positive postmenopausal breast cancer, resistance is common and incompletely explained. Genomic instability, as measured by somatic copy number alterations (SCNAs), is important in breast cancer development and prognosis. SCNAs to specific genes may drive intrinsic resistance, or high genomic instability may drive tumor heterogeneity, which allows differential response across tumors and surviving cells to evolve resistance to treatment rapidly. We therefore evaluated the relationship between SCNAs and intrinsic resistance to treatment as measured by a poor antiproliferative response. PATIENTS AND METHODS: SCNAs were determined by single nucleotide polymorphism array in baseline and surgery core-cuts from 73 postmenopausal patients randomly assigned to receive 2 weeks of preoperative AI or no AI in the Perioperative Endocrine Therapy-Individualizing Care (POETIC) trial. Fifty-six samples from the AI group included 28 poor responders (PrRs, less than 60% reduction in protein encoded by the MKI67 gene [Ki-67]) and 28 good responders (GdRs, greater than 75% reduction in Ki-67). Exome sequencing was available for 72 pairs of samples. RESULTS: Genomic instability correlated with Ki-67 expression at both baseline (P < .001) and surgery (P < .001) and was higher in PrRs (P = .048). The SCNA with the largest difference between GdRs and PrRs was loss of heterozygosity observed at 17p (false discovery rate, 0.08), which includes TP53. Nine of 28 PrRs had loss of wild-type TP53 as a result of mutations and loss of heterozygosity compared with three of 28 GdRs. In PrRs, somatic alterations of TP53 were associated with higher genomic instability, higher baseline Ki-67, and greater resistance to AI treatment compared with wild-type TP53. CONCLUSION: We observed that primary tumors with high genomic instability have an intrinsic resistance to AI treatment and do not require additional evolution to develop resistance to estrogen deprivation therapy.

Molecular characterisation of aromatase inhibitor-resistant advanced breast cancer: the phenotypic effect of ESR1 mutations.

BACKGROUND: Several thousand breast cancer patients develop resistance to aromatase inhibitors (AIs) each year in the UK. Rational treatment requires an improved molecular characterisation of resistant disease. MATERIALS AND METHODS: The mutational landscape of 198 regions in 16 key breast cancer genes and RNA expression of 209 genes covering key pathways was evaluated in paired biopsies before AI treatment and at progression on AI from 48 patients. Validity of findings was assessed in another five ESR1-mutated tumours progressing on AI. RESULTS: Eighty-nine mutations were identified in 41 matched pairs (PIK3CA in 27%; CDH1 in 20%). ESR1 (n = 5), ERBB2 (n = 1) and MAP2K4 (n = 1) had mutations in the secondary sample only. There was very high heterogeneity in gene expression between AI-resistant tumours with few patterns apparent. However, in the ESR1-mutated AI-resistant tumours, expression of four classical oestrogen-regulated genes (ERGs) was sevenfold higher than in ESR1 wild-type tumours, a finding confirmed in the second set of ESR1-mutated tumours. In ESR1 wild-type AI-resistant tumours ERG expression remained suppressed and was uncoupled from the recovery seen in proliferation. CONCLUSIONS: Major genotypic and phenotypic heterogeneity exists between AI-resistant disease. ESR1 mutations appear to drive oestrogen-regulated processes in resistant tumours.

Impact of aromatase inhibitor treatment on global gene expression and its association with antiproliferative response in ER+ breast cancer in postmenopausal patients.

BACKGROUND: Endocrine therapy reduces breast cancer mortality by 40%, but resistance remains a major clinical problem. In this study, we sought to investigate the impact of aromatase inhibitor (AI) therapy on gene expression and identify gene modules representing key biological pathways that relate to early AI therapy resistance. METHODS: Global gene expression was measured on pairs of core-cut biopsies taken at baseline and at surgery from 254 patients with ER-positive primary breast cancer randomised to receive 2-week presurgical AI (n = 198) or no presurgical treatment (control n = 56) from the POETIC trial. Data from the AI group was adjusted to eliminate artefactual process-related changes identified in the control group. The response was assessed by changes in the proliferation marker, Ki67. RESULTS: High baseline ESR1 expression associated with better AI response in HER2+ tumours but not HER2- tumours. In HER2- tumours, baseline expression of 48 genes associated with poor antiproliferative response (p < 0.005) including PERP and YWHAQ, the two most significant, and the transcription co-regulators (SAP130, HDAC4, and NCOA7) which were among the top 16 most significant. Baseline gene signature scores measuring cell proliferation, growth factor signalling (ERBB2-GS, RET/GDNF-GS, and IGF-1-GS), and immune activity (STAT1-GS) were significantly higher in poor AI responders. Two weeks of AI caused downregulation of genes involved in cell proliferation and ER signalling, as expected. Signature scores of E2F activation and TP53 dysfunction after 2-week AI were associated with poor AI response in both HER2- and HER2+ patients. CONCLUSIONS: There is a high degree of heterogeneity in adaptive mechanisms after as little as 2-week AI therapy; however, all appear to converge on cell cycle regulation. Our data support the evaluation of whether an E2F signatures after short-term exposure to AI may identify those patients most likely to benefit from the early addition of CDK4/6 inhibitors. TRIAL REGISTRATION: ISRCTN, ISRCTN63882543, registered on 18 December 2007.

Tumor PIK3CA Genotype and Prognosis in Early-Stage Breast Cancer: A Pooled Analysis of Individual Patient Data.

Purpose Phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit alpha ( PIK3CA) mutations are frequently observed in primary breast cancer. We evaluated their prognostic relevance by performing a pooled analysis of individual patient data. Patients and Methods Associations between PIK3CA status and clinicopathologic characteristics were tested by applying Cox regression models adjusted for age, tumor size, nodes, grade, estrogen receptor (ER) status, human epidermal growth factor receptor 2 (HER2) status, treatment, and study. Invasive disease-free survival (IDFS) was the primary end point; distant disease-free survival (DDFS) and overall survival (OS) were also assessed, overall and by breast cancer subtypes. Results Data from 10,319 patients from 19 studies were included (median OS follow-up, 6.9 years); 1,787 patients (17%) received chemotherapy, 4,036 (39%) received endocrine monotherapy, 3,583 (35%) received both, and 913 (9%) received none or their treatment was unknown. PIK3CA mutations occurred in 32% of patients, with significant associations with ER positivity, increasing age, lower grade, and smaller size (all P < .001). Prevalence of PIK3CA mutations was 18%, 22%, and 37% in the ER-negative/HER2-negative, HER2-positive, and ER-positive/HER2-negative subtypes, respectively. In univariable analysis, PIK3CA mutations were associated with better IDFS (HR, 0.77; 95% CI, 0.71 to 0.84; P < .001), with evidence for a stronger effect in the first years of follow-up (0 to 5 years: HR, 0.73; 95% CI, 0.66 to 0.81; P < .001; 5 to 10 years: HR, 0.82; 95% CI, 0.68 to 0.99; P = .037); > 10 years: (HR, 1.15; 95% CI, 0.84 to 1.58; P = .38; P heterogeneity = .02). In multivariable analysis, PIK3CA genotype remained significant for improved IDFS ( P = .043), but not for the DDFS and OS end points. Conclusion In this large pooled analysis, PIK3CA mutations were significantly associated with a better IDFS, DDFS, and OS, but had a lesser prognostic effect after adjustment for other prognostic factors.

Major Impact of Sampling Methodology on Gene Expression in Estrogen Receptor-Positive Breast Cancer.

To investigate the impact of sampling methodology on gene expression data from primary estrogen receptor-positive (ER+) breast cancer biopsies, global gene expression was measured in core-cut biopsies at baseline and surgery from patients randomly assigned to receive either two weeks of presurgical aromatase inhibitor (AI; n = 157) or no presurgical treatment (n = 56). Those genes most markedly altered in the AI group (eg, FOS, DUSP1, RGS1, FOSB) were similarly altered in the no treatment group; some widely investigated genes that were apparently unaffected in the AI group (eg, MYC) were counter-altered in the control group, masking actual AI-dependent changes. In the absence of a control group, these artefactual changes would likely lead to the most affected genes being the erroneous focus of research. The findings are likely relevant to all archival collections of ER+ breast cancer.

Impact of a Panel of 88 Single Nucleotide Polymorphisms on the Risk of Breast Cancer in High-Risk Women: Results From Two Randomized Tamoxifen Prevention Trials.

Purpose At least 94 common single nucleotide polymorphisms (SNPs) are associated with breast cancer. The extent to which an SNP panel can refine risk in women who receive preventive therapy has not been directly assessed previously. Materials and Methods A risk score on the basis of 88 SNPs (SNP88) was investigated in a nested case-control study of women enrolled in the International Breast Intervention Study (IBIS-I) or the Royal Marsden study. A total of 359 women who developed cancer were matched to 636 controls by age, trial, follow-up time, and treatment arm. Genotyping was done using the OncoArray. Conditional logistic regression and matched concordance indices (mC) were used to measure the performance of SNP88 alone and with other breast cancer risk factors assessed using the Tyrer-Cuzick (TC) model. Results SNP88 was predictive of breast cancer risk overall (interquartile range odds ratio [IQ-OR], 1.37; 95% CI, 1.14 to 1.66; mC, 0.55), but mainly for estrogen receptor-positive disease (IQ-OR, 1.44; 95% CI, 1.16 to 1.79; P for heterogeneity = .10) versus estrogen receptor-negative disease. However, the observed risk of SNP88 was only 46% (95% CI, 19% to 74%) of expected. No significant interaction was observed with treatment arm (placebo IQ-OR, 1.46; 95% CI, 1.13 to 1.87; tamoxifen IQ-OR, 1.25; 95% CI, 0.96 to 1.64; P for heterogeneity = .5). The predictive power was similar to the TC model (IQ-OR, 1.45; 95% CI, 1.21 to 1.73; mC, 0.55), but SNP88 was independent of TC (Spearman rank-order correlation, 0.012; P = .7), and when combined multiplicatively, a substantial improvement was seen (IQ-OR, 1.64; 95% CI, 1.36 to 1.97; mC, 0.60). Conclusion A polygenic risk score may be used to refine risk from the TC or similar models in women who are at an elevated risk of breast cancer and considering preventive therapy. Recalibration may be necessary for accurate risk assessment.

Impact of mutational profiles on response of primary oestrogen receptor-positive breast cancers to oestrogen deprivation.

Pre-surgical studies allow study of the relationship between mutations and response of oestrogen receptor-positive (ER+) breast cancer to aromatase inhibitors (AIs) but have been limited to small biopsies. Here in phase I of this study, we perform exome sequencing on baseline, surgical core-cuts and blood from 60 patients (40 AI treated, 20 controls). In poor responders (based on Ki67 change), we find significantly more somatic mutations than good responders. Subclones exclusive to baseline or surgical cores occur in ∼30% of tumours. In phase II, we combine targeted sequencing on another 28 treated patients with phase I. We find six genes frequently mutated: PIK3CA, TP53, CDH1, MLL3, ABCA13 and FLG with 71% concordance between paired cores. TP53 mutations are associated with poor response. We conclude that multiple biopsies are essential for confident mutational profiling of ER+ breast cancer and TP53 mutations are associated with resistance to oestrogen deprivation therapy.

Heterogeneity in global gene expression profiles between biopsy specimens taken peri-surgically from primary ER-positive breast carcinomas.

BACKGROUND: Gene expression is widely used for the characterisation of breast cancers. Variability due to tissue heterogeneity or measurement error or systematic change due to peri-surgical procedures can affect measurements but is poorly documented. We studied the variability of global gene expression between core-cuts of primary ER+ breast cancers and the impact of delays to tissue stabilisation due to sample X-ray and of diagnostic core cutting. METHODS: Twenty-six paired core-cuts were taken immediately after tumour excision and up to 90 minutes delay due to sample X-ray; 57 paired core-cuts were taken at diagnosis and 2 weeks later at surgical excision. Whole genome expression analysis was conducted on extracted RNA. Correlations and differences were assessed between the expression of individual genes, gene sets/signatures and intrinsic subtypes. RESULTS: Twenty-three and 56 sample pairs, respectively, were suitable for analysis. The range of correlations for both sample sets were similar with the majority being >0.97 in both. Correlations between pairs for 18 commonly studied genes were also similar between the studies and mainly with Pearson correlation coefficients >0.6 except for a small number of genes, which had a narrow-dynamic range (e.g. MKI67, SNAI2). There was no systematic difference in intrinsic subtyping between the first and second sample of either set but there was c.15 % discordance between the subtype assignments between the pairs, mainly where the subtyping of individual samples was less certain. Increases in the expression of several stress/early-response genes (e.g. FOS, FOSB, JUN) were found in both studies and confirmed findings in earlier smaller studies. Increased expression of IL6, IGFBP2 and MYC (by 17 %, 14 % and 44 %, respectively) occurred between the samples taken 2 weeks apart and again confirmed findings from an earlier study. CONCLUSIONS: There is generally good correlation in gene expression between pairs of core-cuts except where genes have a narrow dynamic range. Similar correlation coefficients to the average gene expression profiles of intrinsic subtype, particularly LumA and LumB, can lead to discordances between assigned subtypes. Substantial changes in expression of early-response genes occur within an hour after surgery and in IL6, IGFB2 and MYC as a result of diagnostic core-cut biopsy. TRIAL REGISTRATION: Trial number CRUK/07/015 . Study start date September 2008.

Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170.

We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.

Analysis of ESR1 mutation in circulating tumor DNA demonstrates evolution during therapy for metastatic breast cancer.

Acquired ESR1 mutations are a major mechanism of resistance to aromatase inhibitors (AIs). We developed ultra high-sensitivity multiplex digital polymerase chain reaction assays for ESR1 mutations in circulating tumor DNA (ctDNA) and investigated the clinical relevance and origin of ESR1 mutations in 171 women with advanced breast cancer. ESR1 mutation status in ctDNA showed high concordance with contemporaneous tumor biopsies and was accurately assessed in samples shipped at room temperature in preservative tubes. ESR1 mutations were found exclusively in estrogen receptor-positive breast cancer patients previously exposed to AI. Patients with ESR1 mutations had a substantially shorter progression-free survival on subsequent AI-based therapy [hazard ratio, 3.1; 95% confidence interval (CI), 1.9 to 23.1; P = 0.0041]. ESR1 mutation prevalence differed markedly between patients who were first exposed to AI during the adjuvant and metastatic settings [5.8% (3 of 52) versus 36.4% (16 of 44), respectively; P = 0.0002]. In an independent cohort, ESR1 mutations were identified in 0% (0 of 32; 95% CI, 0 to 10.9) tumor biopsies taken after progression on adjuvant AI. In a patient with serial sampling, ESR1 mutation was selected during metastatic AI therapy to become the dominant clone in the cancer. ESR1 mutations can be robustly identified with ctDNA analysis and predict for resistance to subsequent AI therapy. ESR1 mutations are rarely acquired during adjuvant AI but are commonly selected by therapy for metastatic disease, providing evidence that mechanisms of resistance to targeted therapy may be substantially different between the treatment of micrometastatic and overt metastatic cancer.

Estrogen Receptor Expression in 21-Gene Recurrence Score Predicts Increased Late Recurrence for Estrogen-Positive/HER2-Negative Breast Cancer.

PURPOSE: To identify the individual genes or gene modules that lead to the OncoptypeDx 21-gene recurrence score's reduced performance after 5 years and thereby identify indices of residual risk that may guide selection of patients for extended adjuvant therapy. EXPERIMENTAL DESIGN: We conducted a retrospective assessment of the relationship between (i) the individual genes and gene modules of the Recurrence Score and (ii) early (0-5 years) and late (5-10 years) recurrence rates in 1,125 postmenopausal patients with primary estrogen receptor-positive breast cancer treated with anastrozole or tamoxifen in the Arimidex, Tamoxifen, Alone or Combined (ATAC) randomized clinical trial. RESULTS: In the HER2-negative population (n = 1,009), estimates of recurrence risk were similar between years 0-5 and 5-10 for proliferation and invasion modules but markedly different for the estrogen module and genes within it (all split at the median): for low estrogen module, annual recurrence rates were similar across the two time windows (2.06% vs. 2.46%, respectively); for high estrogen module, annual rates were 1.14% versus 2.72%, respectively (P interaction = 0.004). Estrogen receptor transcript levels showed inverse prediction across the time windows: HR, 0.88 (0.73-1.07) and 1.19 (0.99-1.43), respectively (P interaction = 0.03). Similar time-, module-, and estrogen-dependent relationships were seen for distant recurrence. CONCLUSIONS: Patients with tumors with high estrogen receptor transcript levels benefit most from 5 years' endocrine therapy but show increased recurrence rates after 5 years and may benefit from extended therapy. Improved prognostic profiles may be created by considering period of treatment and follow-up time.

Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer.

INTRODUCTION: Aromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach. METHODS: Samples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n=84), gene expression profiling (n=47), matched pre- and post-AI aCGH (n=19 pairs) and Ki67-based AI-response analysis (n=39). RESULTS: Integrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1). CONCLUSIONS: These data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response.

Prediction of late distant recurrence after 5 years of endocrine treatment: a combined analysis of patients from the Austrian breast and colorectal cancer study group 8 and arimidex, tamoxifen alone or in combination randomized trials using the PAM50 risk of recurrence score.

PURPOSE: We have previously shown that the PAM50-based risk of recurrence (ROR) score is significantly correlated with distant recurrence in both the translational research cohort within the Arimidex, Tamoxifen Alone or in Combination (ATAC) trial (TransATAC) and Austrian Breast and Colorectal Cancer Study Group 8 (ABCSG 8) randomized trials. Here, we focus on the ROR score for predicting distant recurrence after 5 years of follow-up in a combined analysis of these two randomized trials. METHODS: Long-term follow-up data and tissue samples were obtained from 2,137 postmenopausal women with hormone receptor-positive early-stage breast cancer from the ABCSG 8 and TransATAC trials. We used Cox proportional hazard regression models to determine the prognostic value of ROR for distant recurrence beyond 5 years in the combined data set. RESULTS: A total of 2,137 women who did not have a recurrence 5 years after diagnosis were included in the combined analyses. The Clinical Treatment Score (CTS) was the strongest prognostic factor 5 years after diagnosis (univariable: likelihood ratio [LR] χ(2) = 94.12, bivariable: LR χ(2) = 61.43). The ROR score was significantly prognostic by itself in years 5 to 10. In the node-negative/human epidermal growth factor receptor 2-negative subgroup, more prognostic value for late distant recurrence was added by the ROR score compared with the CTS. CONCLUSION: The ROR score added clinically meaningful prognostic information to the CTS in all patients and all subgroups in the late follow-up period. These results suggest that the ROR score may be helpful for separating patients into risk groups who could be spared or potentially benefit from extended hormonal therapy beyond 5 years of treatment.

Relationship of PIK3CA mutation and pathway activity with antiproliferative response to aromatase inhibition.

INTRODUCTION: PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit α) somatic mutations are the most common genetic alteration in breast cancer (BC). Their prognostic value and that of the phosphatidylinositol 3-kinase (PI3K) pathway in BC remains only partly defined. The effect of PIK3CA mutations and alterations of the PI3K pathway on the antiproliferative response to aromatase inhibitor treatment was determined. METHODS: The Sequenom MassARRAY System was used to determine the presence of 20 somatic mutations across the PIK3CA gene in 85 oestrogen receptor-positive (ER+) BC patients treated with 2 weeks of anastrozole before surgery. Whole-genome expression profiles were used to interrogate gene signatures (GSs) associated with the PI3K pathway. Antiproliferative activity was assessed by the change in Ki67 staining between baseline and surgery. Three GSs representing the PI3K pathway were assessed (PIK3CA-GS (Loi), PI3K-GS (Creighton) and PTEN-loss-GS (Saal)). RESULTS: In our study sample, 29% of tumours presented with either a hotspot (HS, 71%) or a nonhotspot (non-HS, 29%) PIK3CA mutation. Mutations were associated with markers of good prognosis such as progesterone receptor positivity (PgR+) (P=0.006), low grade (P=0.028) and luminal A subtype (P=0.039), with a trend towards significance with degree of ER positivity (P=0.051) and low levels of Ki67 (P=0.051). Non-HS mutations were associated with higher PgR (P=0.014) and ER (P<0.001) expression than both wild-type (WT) and HS-mutated samples, whereas neither biomarker differed significantly between WT and HS mutations or between HS and non-HS mutations. An inverse correlation was found between the Loi signature and both the Creighton and Saal signatures, and a positive correlation was found between the latter signatures. Lower pretreatment Ki67 levels were observed in mutation compared with WT samples (P=0.051), which was confirmed in an independent data set. Mutation status did not predict change in Ki67 in response to 2 weeks of anastrozole treatment; there was no significant difference between HS and non-HS mutations in this regard. CONCLUSIONS: PIK3CA mutations are associated with classical markers of good prognosis and signatures of PI3K pathway activity. The presence of a PIK3CA mutation does not preclude a response to neoadjuvant anastrozole treatment.