Laura M. Arthur

Accurate Prediction and Validation of Response to Endocrine Therapy in Breast Cancer

PURPOSE Aromatase inhibitors (AIs) have an established role in the treatment of breast cancer. Response rates are only 50% to 70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy. PATIENTS AND METHODS Pretreatment and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 postmenopausal women who had estrogen receptor-alpha positive breast cancer and were receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed with use of three-dimensional ultrasound measurements. RESULTS The molecular response to letrozole was characterized and a four-gene classifier of clinical response was established (accuracy of 96%) on the basis of the level of two genes before treatment (one gene [IL6ST] was associated with immune signaling, and the other [NGFRAP1] was associated with apoptosis) and the level of two proliferation genes (ASPM, MCM4) after 2 weeks of therapy. The four-gene signature was found to be 91% accurate in a blinded, completely independent validation data set of patients treated with anastrozole. Matched 2-week on-treatment biopsies were associated with improved predictive power as compared with pretreatment biopsies alone. This signature also significantly predicted recurrence-free survival (P = .029) and breast cancer -specific survival (P = .009). We demonstrate that the test can also be performed with use of quantitative polymerase chain reaction or immunohistochemistry. CONCLUSION A four-gene predictive model of clinical response to AIs by 2 weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and cell proliferation that is not reduced 2 weeks after initiation of treatment are functional characteristics of breast tumors that do not respond to AIs.

Molecular Changes in Lobular Breast Cancers in Response to Endocrine Therapy

Invasive lobular carcinoma (ILC) accounts for approximately 10% to 15% of breast carcinomas, and although it responds poorly to neoadjuvant chemotherapy, it appears to respond well to endocrine therapy. Pre- and on-treatment (after 2 weeks and 3 months) biopsies and surgical samples were obtained from 14 postmenopausal women with estrogen receptor-positive (ER(+)) histologically confirmed ILC who responded to 3 months of neoadjuvant letrozole and were compared with a cohort of 14 responding invasive ductal carcinomas (IDC) matched on clinicopathologic features. RNA was extracted and processed for whole human genome expression microarray. Dynamic clinical response was assessed using periodic three-dimensional ultrasound measurements performed during treatment and defined as a reduction of >70% in tumor volume by 3 months. Pretreatment profiles of ILC and IDC tumors showed distinctive expression of genes associated with E-cadherin signaling, epithelial adhesion, and stromal rearrangement. The changes in gene expression in response to letrozole were highly similar between responding ILC and IDC tumors; genes involved in proliferation were downregulated and those involved with immune function and extracellular matrix remodeling were upregulated. However, molecular differences between the histologic subtypes were maintained upon treatment. This is the first study of molecular changes in ILC in response to endocrine therapy to date. The genes that change on letrozole are highly consistent between ILC and IDC. Differences in gene expression between ILC and IDC at diagnosis are maintained at each time point on treatment.

Tumour sampling method can significantly influence gene expression profiles derived from neoadjuvant window studies

Patient-matched transcriptomic studies using tumour samples before and after treatment allow inter-patient heterogeneity to be controlled, but tend not to include an untreated comparison. Here, Illumina BeadArray technology was used to measure dynamic changes in gene expression from thirty-seven paired diagnostic core and surgically excised breast cancer biopsies obtained from women receiving no treatment prior to surgery, to determine the impact of sampling method and tumour heterogeneity. Despite a lack of treatment and perhaps surprisingly, consistent changes in gene expression were identified during the diagnosis-surgery interval (48 up, 2 down; Siggenes FDR 0.05) in a manner independent of both subtype and sampling-interval length. Instead, tumour sampling method was seen to directly impact gene expression, with similar effects additionally identified in six published breast cancer datasets. In contrast with previous findings, our data does not support the concept of a significant wounding or immune response following biopsy in the absence of treatment and instead implicates a hypoxic response following the surgical biopsy. Whilst sampling-related gene expression changes are evident in treated samples, they are secondary to those associated with response to treatment. Nonetheless, sampling method remains a potential confounding factor for neoadjuvant study design.

Current treatment trends and the need for better predictive tools in the management of ductal carcinoma in situ of the breast

Ductal carcinoma in situ (DCIS) of the breast represents a group of heterogeneous non-invasive lesions the incidence of which has risen dramatically since the advent of mammography screening. In this review we summarise current treatment trends and up-to-date results from clinical trials studying surgery and adjuvant therapy alternatives, including the recent consensus on excision margin width and its role in decision-making for post-excision radiotherapy. The main challenge in the clinical management of DCIS continues to be the tailoring of treatment to individual risk, in order to avoid the over-treatment of low-risk lesions or under-treatment of DCIS with higher risk of recurring or progressing into invasion. While studies estimate that only about 40% of DCIS would become invasive if untreated, heterogeneity and complex natural history have prevented adequate identification of these higher-risk lesions. Here we discuss attempts to develop prognostic tools for the risk stratification of DCIS lesions and their limitations. Early results of a UK-wide audit of DCIS management (the Sloane Project) have also demonstrated a lack of consistency in treatment. In this review we offer up-to-date perspectives on current treatment and prediction of DCIS, highlighting the pressing clinical need for better prognostic indices. Tools integrating both clinical and histopathological factors together with molecular biomarkers may hold potential for adequate stratification of DCIS according to risk. This could help develop standardised practices for optimal management of patients with DCIS, improving clinical outcomes while providing only the amount of therapy required for each individual patient.

Abstract P5-11-02: Predicting local recurrence in patients treated for ductal carcinoma in situ of the breast (DCIS)

Background: Ductal carcinoma in situ (DCIS) of the breast represents a heterogeneous group of precursor, non-invasive breast lesions. Currently we lack accurate tools to stratify DCIS patients according to inherent risk of in breast tumour recurrence (IBTR) or progression to invasive breast cancer (IBC).Most DCIS patients are treated by breast-conversing surgery (BCS), followed by whole-breast radiotherapy (RT) for the majority of high-grade DCIS. The aim of this study was to identify novel biomarkers which predict recurrence after BCS +/- RT. Methods: A single institution study of 466 consecutive patients (median age 61, range 35-94) with DCIS treated by BCS between 2000 and 2010 was carried out. 271 patients with grade 3 DCIS received RT and 155 with grade 1/2 DCIS did not receive RT. For biomarker discovery, a case-control matched series of 200 patients (mean age = 61, range = 36-84) from the above audit that met the following criteria was selected: · 120 with low/intermediate-grade DCIS treated with BCS alone: 30 have recurred, 90 patients matched 3:1 have not recurred by 10 years. · 80 with high-grade DCIS treated by BCS plus RT: 20 have recurred, 60 patients matched 3:1 have not recurred by 10 years. Median follow-up was 7.4 years. RNA has been extracted and Affymetrix Clariom S whole-genome analysis has been performed and is currently being analysed. Results: In the cohort of 466 patients, 271 patients with high grade DCIS had BCS plus RT. Actuarial IBTR and IBC-IBTR in this group were 10% and 4% at 5 years and 18% and 6% at 10 years, respectively. 155 patients with low/intermediate grade DCIS had BCS alone. Actuarial overall IBTR and IBC-IBTR in this group were 6% and 2% at 5 years and 13% and 2% at 10 years respectively. In the high-grade, RT treated group, lesion size (P Full genomic analysis of the 240 patient case-control matched cohort is underway and will be presented. Discussion: · This is the first DCIS biomarker discovery study using whole genome analysis and the matched cohort design looking separately at BCS + RT for high-grade DCIS and BCS only for low/intermediate grade DCIS. · Clinical parameters alone may have insufficient sensitivity to identify high-grade, RT-treated patients at risk of developing IBC-IBTR. · While recurrence rates in the low/intermediate grade DCIS group are lower than in the high-grade group, some patients do recur and there is a need to develop new tools which can identify low grade patients with a sufficiently high risk of recurrence to warrant additional treatment. Citation Format: Martinez-Perez C, Turnbull AK, Ekatah GE, Arthur LM, Fernando A, Sims AH, Thomas JS, Dixon JM. Predicting local recurrence in patients treated for ductal carcinoma in situ of the breast (DCIS) [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-11-02.

Abstract P1-06-04: Molecular characterisation, subtype concordance and prognostic group assignment between patient-matched primary breast tumours and axillary lymph node metastases

Introduction Currently the primary breast tumour is used for prognostic profiling and as a monitor of response to therapy but how often does the molecular profile of the primary cancer reflect the molecular profile of nodal metastases? No previous study has investigated in detail the genomic profile of matched primary breast cancer (P) and nodal metastases (N) and correlated these with outcome. The aim of this study was to investigate whether the mRNA profiles of matched P and N differ significantly. Methods RNA was extracted from core biopsies from primary breast tumours and paired metastatic axillary lymph node samples from both FFPE blocks and fresh frozen samples. RNA was labelled and hybridised to Illumina HT-12 BeadChips to create a dataset consisting of one primary and one or two matched nodal metastasis, totalling 68 samples from 31 patients. Data was processed and corrected for batch effects, then analysed using the statistical programming language R. Clinical data on progression free and overall survival was collected from electronic and medical case note review. Results Unsupervised hierarchical clustering of the 500 most variable genes in each sample grouped only 12 of 31 PN PGR 19% and ERBB2 16%. Conclusions This study of gene expression change in matched primary breast cancers and synchronous metastatic paired axillary lymph nodes shows that molecular subtype differs in 39%. 50% of nodes had a poorer prognostic subtype than their primary. Expression of ESR, PGR and ERBB2 differs in up to 32% Classifying cancer molecular phenotype and estimating prognosis based only on the primary cancer misclassifies significant numbers of patients. Classification of prognosis, and treatment based on the nodal metastasis may provide better information on which to base treatment. Citation Format: Arthur LM, Turnbull AK, Pearce DA, Renshaw L, Thomas JS, Sims AH, Dixon JM. Molecular characterisation, subtype concordance and prognostic group assignment between patient-matched primary breast tumours and axillary lymph node metastases [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 P1-06-04.

Abstract P6-09-27: The EA2clin test significantly predicts response and survival in both pre and post-menopausal women with ER-positive breast cancers

Background Identifying breast cancer (BC) patients likely to recur on endocrine therapy (ET) is a challenge. Several methods and tests based on clinical parameters and multi-gene or protein classifiers have been shown to predict those likely to recur. Tests that incorporate baseline and on-treatment markers are likely to be more accurate than tests based on baseline characteristics alone. 4 genes were identified by microarray that predicted for to ET: 2 at diagnosis and 2 at 14 days. The EndoAdjuvant2 (EA2) test uses 2 of these genes: IL6ST at diagnosis and on-treatment MCM4 at transcript level or by graded immunohistochemistry (IHC). The aim of this study was to compare EA2 with currently used clinical parameters in 4 different cohorts of pre and postmenopausal women. Patients The cohorts are (1) 73 post-menopausal women (PMW) with ER+ BC treated with neoadjuvant letrozole (L) then surgery, (2) 39 PMW with ER+ BC treated with neoadjuvant anastrozole (A) then surgery, (3) 108 PMW who received 2-weeks of A or L prior to surgery (4) 25 preMW with ER+ BC who received one 750mg dose of fulvestrant prior to surgery. All had adjuvant ET and 5-10 years follow up. Neoadjuvant response was assessed by periodic 3D ultrasound. Results The 4 gene assay had 96% (training; cohort 1) and 93% (validation; cohort 2) accuracy of response prediction to neoadjuvant L or A. In cohort 1, clinical parameters were available. On univariate regression analysis intrinsic subtype (luminal A/B; defined using PAM50) (P=0.002), histological grade (P=0.033) and HER2 status (P=0.001) significantly predicted clinical response. EA2 out-performed all these in both univariate (P EA2 predicted recurrence free in cohorts 1 and 3 combined: RFS (P=0.0004, HR=17.63 95%CI: 4.95-17.6), BCSS (P=0.0007, HR=16.60: 3.36-45.7). The Nottingham Prognostic Index (NPI) also predicted RFS (P=0.0002) and BCSS (P=0.0017) in univariate analysis but in the Cox analysis NPI was not found to be significant, although in the low risk group there were only 1/46 events compared to 19/62 in the moderate/high risk group. Histological grade (P Conclusions • EA2 predicts clinical response, RFS and BCSS • EA2clin combines NPI and EA2, outperforms either alone and predicts outcome in a new validation cohort of preMW treated with Fulvestrant • EA2clin works in preM and PM women regardless of ET. Citation Format: Turnbull AK, Pearce DA, Arthur LM, Martinez-Perez C, Thomas JS, Fernando A, Renshaw L, Sims AH, Dixon JM. The EA2clin test significantly predicts response and survival in both pre and post-menopausal women with ER-positive breast cancers [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 P6-09-27.

Abstract P3-07-20: A validated test for neoadjuvant clinical response to endocrine therapy in breast cancer that estimates accurately recurrence-free and overall survival

Background: Aromatase inhibitors (AIs) have an established role in the treatment of estrogen receptor alpha positive post-menopausal breast cancer. Recently we have developed and validated a microarray-derived 4-gene test (Edinburgh EndoResponse4) to predict response to AIs in the neoadjuvant setting. We have also demonstrated the translational potential of this test in predicting accurately clinical response when mRNA is measured for these genes by polymerase chain reaction (PCR) or the gene protein is measured by immunohistochemistry (IHC). There is a major clinical need for biomarkers to predict which patients are likely to recur on adjuvant endocrine therapy so alternative or additional treatments can be provided to reduce recurrence and improve outcome. The aim of this study was to determine if Endoresponse4 and IHC of these gene proteins could do this. Methods: The original microarray assay used pre- and on-treatment (14-days) biopsies from 73 post-menopausal women with ER-rich breast cancer receiving 3 months of neoadjuvant letrozole prior to surgery with 10 years follow-up after adjuvant letrozole. Matched formalin-fixed paraffin embedded (FFPE) tissue sections from 42 of these patients were used for IHC and antibodies were optimised against 3 of the 4 proteins (where validated antibodies were available) using Envision technology. The ability of our test to estimate recurrence-free (RFS) and breast cancer specific overall survival (OS) using both PCR and IHC was then tested in a unique validation cohort of 140 post-menopausal women with ER-rich breast cancer treated with 2 weeks of neoadjuvant letrozole or anastrozole prior to surgery followed by adjuvant endocrine therapy and 10 years of follow up.. Results: Within our training cohort (n=73) using Kaplan-Meier analysis our 4-gene test predicted neoadjuvant clinical response and demonstrated a significant association with both RFS (P=0.029) and OS (P=0.009). This approach predicts outcomes within 2-weeks rather than 4-months of treatment required in other studies such as P024. Using IHC in the training cohort (n=42), two gene markers in combination (IL6ST at diagnosis and MCM4 after 2-weeks treatment) predicted both RFS (P=0.017) and OS (P=0.009) with great accuracy. The 140 patient group is being analysed and the findings are so far are consistent with the initial training cohort and indicate a significant association with outcomes. Conclusion: • A 4 gene model with clinical potential has been developed and validated to predict response to neoadjuvant aromatase inhibitors. • This 4 gene model predicts for response and also predicts relapse free and overall survival. • Proteins encoded by 2 of these 4 genes measured by IHC in an initial test set of 42 patients predict accurately both EFS and OS • A validation cohort (n=140) with over 10-years of follow-up will be available at SABCS 2015 to determine if this 2 biomarker test can predict outcome on adjuvant endocrine therapy. Citation Format: Turnbull AK, Arthur LM, Webber V, Thomas J, Uddin S, Webb H, Dunbier A, Dowsett M, Renshaw L, Sims AH, Dixon JM. A validated test for neoadjuvant clinical response to endocrine therapy in breast cancer that estimates accurately recurrence-free and overall survival. [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 P3-07-20.

Abstract P3-06-35: Association of estrogen receptor (ER) levels and prediction of antiproliferative effect of hormone therapy (HT) in lower ER-expressing tumors

Intro Accurate measurement of ER in early stage invasive breast cancer (EBC) is important to identify patients likely to benefit from HT. While immunohistochemistry (IHC) is the most common method to quantify ER, other methods can also accurately measure ER, such as RT-PCR. ER is one of the genes included in the RT-PCR based 21-gene Recurrence Score assay (Onco type DX ® , Genomic Health, Redwood City, CA) and is also reported separately as a single gene expression. Additionally, the association between ER expression by RT-PCR (ER-PCR) and tamoxifen benefit has been reported by Kim, et al (2011). A recent study reported that patients with ER levels Aim The study aims are: (1) To correlate quantification of ER in EBC as assessed by Allred Score (AS) and ER as measured by RT-PCR in the 21-gene assay; (2) To describe changes in ER, Recurrence Score, and measures of proliferation after 2wks of an aromatase inhibitor (AI); (3) To perform exploratory analyses of factors associated with changes in proliferation. Methods 55 postmenopausal EBC patients with lower ER (AS 2-7) were treated with 2wks of an AI followed by wide excision. All patients had a 21-gene assay on a pre-and post-treatment (Tx) sample. Proliferation was measured by both Ki67 by IHC (in 45 patients) and by the proliferation gene group score (PGS) in the RT-PCR based 21-gene assay (in all patients). Proliferation response was defined by a 20% relative decrease in Ki67 or a decrease in PGS. Changes in proliferation were correlated with AS, ER-PCR and Recurrence Score result. Results The Table shows the correlation of AS with ER-PCR measured in the pre-Tx (r=0.83) samples. 94% of AS (2-3) patients and 56% of AS (4-5) were ER(-) by RT-PCR There was a significant change (pre to post) in the average Ki67 level (18% to 11%; p Conclusions • Results confirm earlier reports showing substantial disagreement in ER measured by IHC vs RT-PCR in patients with lower ER-expressing tumors • The clinical implications are that a substantial number of patients with low ER by IHC may have little to no benefit from HT • The 21-gene assay may be useful in selecting patients likely to benefit from HT • Further studies in larger cohorts are required to confirm these findings. Citation Format: J Michael Dixon, Arran Turnbull, Lorna Renshaw, Megan P Rothney, Cynthia A Loman, Laura Arthur, Jeremy S Thomas, Oliver Young, Juliette Murray, Linda Williams, Amy P Sing, David Cameron. Association of estrogen receptor (ER) levels and prediction of antiproliferative effect of hormone therapy (HT) in lower ER-expressing tumors [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-35.

Abstract P3-05-01: Development for clinical utility of a validated predictive test of clinical response to aromatase inhibitors

Background: Aromatase inhibitors (AIs) have an established role in the treatment of estrogen receptor alpha positive post-menopausal breast cancer. Response rates are only 50-70% even in patients with ER-rich cancers in the neoadjuvant setting and are lower in advanced disease. Recently we developed and validated a microarray-derived 4-gene test to predict response to AIs in the neoadjuvant setting. Whole-genome expression analysis is impractical for clinical utility. There is a need to translate and validate any test utilising clinically accessible and reproducible material and technologies such as polymerase chain reaction (PCR) and immunohistochemistry (IHC). Methods: The original microarray experiment used pre- and on-treatment (at 14 days and 3-months) biopsies from 89 post-menopausal women with ER-rich breast cancer receiving 3 months of neoadjuvant letrozole. Dynamic response was based on periodic 3D ultrasound measurements performed during treatment. The derived 4-gene model was independently validated in a cohort of 44 post-menopausal women with ER-rich breast cancer treated with neoadjuvant anastrozole [table 1]. RNA was extracted from the original biopsies for RT-qPCR analysis using validated primers for the 4 genes with SYBR-green technology normalised to the geometric mean of 3 housekeeping genes. Matched formalin-fixed paraffin embedded (FFPE) tissue sections were used for IHC with optimised antibodies against 3 of the 4 proteins (where validated antibodies were available) using Envision technology. Results: PCR: Microarray and PCR expression levels for each of the four genes were well correlated (Pearson r=0.87-0.65, p Conclusion: •A 4 gene model has been developed and validated to predict response to neoadjuvant aromatase inhibitors. •This model has been shown to work with a high degree of accuracy using both PCR and IHC technologies. Further independent validation is currently underway. •This new test has the potential to predict accurately the benefit of endocrine therapy and has huge potential clinical value. Citation Format: Arran K Turnbull, Laura Arthur, Victoria Webber, Jeremy Thomas, Charlotte Heerlyn, Phoebe Thornton, Anita Dunbier, Mitch Dowsett, Lorna Renshaw, Andrew H Sims, J Michael Dixon. Development for clinical utility of a validated predictive test of clinical response to aromatase inhibitors [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-05-01.