Relapse In Early Breast Cancer Research Articles

Abstract P4-02-07: A large real-world study of circulating tumor DNA in early breast cancer patients

Abstract Background Around 30-40% of early breast cancer (EBC) patients relapse after curative surgery and systemic treatment. However, it is very difficult to identify the patients with high risks of relapse. Recently, circulating tumor DNA (ctDNA) is shown to be a sensitive method to evaluate the minimal residual disease (MRD) of solid tumors after surgery. Here, we explored the prognostic value of ctDNA in a large real-world study of EBC patients. Method 346 invasive EBC patients from three hospitals in China were enrolled in this study. All patients received radical surgery and were followed up for a median of 13.1 months from surgery. 17 patients developed local and/or distant relapse during the follow-up. Primary breast cancer samples (n=346) and plasma samples (n=1059) were subjected to deep targeted sequencing using a large next-generation sequencing panel that covers 1,021 cancer-related genes. Results Among the 346 patients, 153 patients had detectable ctDNA in at least one of the plasma samples and 15 of them relapsed. Only two of the 193 patients with consistent negative ctDNA relapsed, demonstrating the value of positive ctDNA in predicting RFS (p< 0.0001; HR=13.09; 95%CI: 2.98-57.45). Of 334 patients who had postoperative plasma samples tested, 108 patients with positive ctDNA in at least one of the postoperative plasma samples had 11 relapse during follow-up, which had a significantly worse RFS than the 226 patients with negative postoperative ctDNA and 4 relapse (p< 0.0005; HR=5.98; 95%CI: 1.90-18.79). In this study, 176 patients received neoadjuvant therapy (NAT) and 59 of them had twice or more ctDNA tests before surgery. Among them, 12 patients with negative ctDNA before NAT remained negative before surgery and had no relapse, 36 patients with positive ctDNA before NAT turned negative before surgery and had 4 relapse, while 11 patients kept positive ctDNA before surgery and had 2 relapse. 165 patients received NAT and had postoperative ctDNA tests. Of the 31 patients achieved pCR, 21 patients with negative postoperative ctDNA did not relapse and 10 patients with positive postoperative ctDNA had 1 relapse. Of the 134 non-pCR patients, 90 patients with negative postoperative ctDNA had 4 (4.4%) relapse, which is significantly better than the 44 patients with positive postoperative ctDNA and 8 (18.2%) relapse (p< 0.05), indicating the feasibility to further distinguish the real high-risk patients among the patients with non-pCR after NAT. Among the 17 patients with relapse or metastasis, 11 patients had positive ctDNA after surgery before relapse and the median lead time was 74 days and a maximum of 526 days. Four patients had negative ctDNA before relapse and two patients did not test after surgery. Conclusions Circulating tumor DNA is a sensitive assay to predict the relapse in early breast cancer, especially in the patients who received NAT and did not achieve pCR. This may provide a window of opportunity to personalize the escalated adjuvant treatment in patients with high relapse risk. Table 1. The association between patients’ characteristics and ctDNA positivity Citation Format: Qiang Liu, Mengzi Wu, Shunying Li, Yudong Li, Liang Jin, Qianfeng Shi, Yu Zhang, Chang Gong. A large real-world study of circulating tumor DNA in early breast cancer patients [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-02-07.

Mechanistic modeling of metastatic relapse in early breast cancer to investigate the biological impact of prognostic biomarkers

Background and objectiveEstimating the risk of metastatic relapse is a major challenge to decide adjuvant treatment options in early-stage breast cancer (eBC). To date, distant metastasis-free survival (DMFS) analysis mainly relies on classical, agnostic, statistical models (e.g., Cox regression). Instead, we propose here to derive mechanistic models of DMFS. MethodsThe present series consisted of eBC patients who did not receive adjuvant systemic therapy from three datasets, composed respectively of 692 (Bergonié Institute), 591 (Paoli-Calmettes Institute, IPC), and 163 (Public Hospital Marseille, AP-HM) patients with routine clinical annotations. The last dataset also contained expression of three non-routine biomarkers. Our mechanistic model of DMFS relies on two mathematical parameters that represent growth (α) and dissemination (μ). We identified their population distributions using mixed-effects modeling. Critically, we propose a novel variable selection procedure allowing to: (i) identify the association of biological parameters with either α, μ or both, and (ii) generate an optimal candidate model for DMFS prediction. ResultsWe found that Ki67 and Thymidine Kinase-1 were associated with α, and nodal status and Plasminogen Activator Inhibitor-1 with μ. The predictive performances of the model were excellent in calibration but moderate in discrimination, with c-indices of 0.72 (95% CI [0.48, 0.95], AP-HM), 0.63 ([0.44, 0.83], Bergonié) and 0.60 (95% CI [0.54, 0.80], IPC). ConclusionsOverall, we demonstrate that our novel method combining mechanistic and advanced statistical modeling is able to unravel the biological roles of clinicopathological parameters from DMFS data.

Risk assessment of disease recurrence in early breast cancer: A serum metabolomic study focused on elderly patients

BackgroundWe previously showed that metabolomics predicts relapse in early breast cancer (eBC) patients, unselected by age. This study aims to identify a “metabolic signature” that differentiates eBC from advanced breast cancer (aBC) patients, and to investigate its potential prognostic role in an elderly population. MethodsSerum samples from elderly breast cancer (BC) patients enrolled in 3 onco-geriatric trials, were retrospectively analyzed via proton nuclear magnetic resonance (1H NMR) spectroscopy. Three nuclear magnetic resonance (NMR) spectra were acquired for each serum sample: NOESY1D, CPMG, Diffusion-edited. Random Forest (RF) models to predict BC relapse were built on NMR spectra, and resulting RF risk scores were evaluated by Kaplan–Meier curves. ResultsSerum samples from 140 eBC patients and 27 aBC were retrieved. In the eBC cohort, median age was 76 years; 77% of patients had luminal, 10% HER2-positive and 13% triple negative (TN) BC. Forty-two percent of patients had tumors >2 cm, 43% had positive axillary nodes. Using NOESY1D spectra, the RF classifier discriminated free-from-recurrence eBC from aBC with sensitivity, specificity and accuracy of 81%, 67% and 70% respectively. We tested the NOESY1D spectra of each eBC patient on the RF models already calculated. We found that patients classified as "high risk" had higher risk of disease recurrence (hazard ratio (HR) 3.42, 95% confidence interval (CI) 1.58–7.37) than patients at low-risk. ConclusionsThis analysis suggests that a “metabolic signature”, identified employing NMR fingerprinting, is able to predict the risk of disease recurrence in elderly patients with eBC independently from standard clinicopathological features.

Definition of High-Risk Early Hormone-Positive HER2-Negative Breast Cancer: A Consensus Review.

Simple SummaryBreast cancer is one of the major causes of cancer-related morbidity and mortality in women worldwide. Despite recent improvements in adjuvant treatment of hormone receptor-positive/HER2−negative breast cancer, estimating the risk of relapse of breast cancer on an individual basis is still challenging. The IRIDE (high risk definition in breast cancer) working group was established with the aim of reviewing evidence from the literature to synthesize the current relevant features that predict hormone-positive/HER2−negative early breast cancer relapse. This work may guide clinicians in the practical management of hormone-positive/HER2−negative early breast cancers.Breast cancer is one of the major causes of cancer-related morbidity and mortality in women worldwide. During the past three decades, several improvements in the adjuvant treatment of hormone receptor-positive/HER2−negative breast cancer have been achieved with the introduction of optimized adjuvant chemotherapy and endocrine treatment. However, estimating the risk of relapse of breast cancer on an individual basis is still challenging. The IRIDE (hIGh Risk DEfinition in breast cancer) working group was established with the aim of reviewing evidence from the literature to synthesize the current relevant features that predict hormone-positive/HER2−negative early breast cancer relapse. A panel of experts in breast cancer was involved in identifying clinical, pathological, morphological, and genetic factors. A RAND consensus method was used to define the relevance of each risk factor. Among the 21 features included, 12 were considered relevant risk factors for relapse. For each of these, we provided a consensus statement and relevant comments on the supporting scientific evidence. This work may guide clinicians in the practical management of hormone-positive/HER2−negative early breast cancers.

Association of three single nucleotide polymorphisms of interleukin -35 for detection and prediction of women with breast cancer in Erbil city

Association of three single nucleotide polymorphisms of interleukin -35 for detection and prediction of women with breast cancer in Erbil city

Identifying and Validating of an Autophagy-Related Gene Signature for the Prediction of Early Relapse in Breast Cancer.

BackgroundCompelling evidence has demonstrated the pivotal role of autophagy in the prognosis of breast cancer. Breast cancer (BC) patients with early relapse consistently exhibited worse survival.MethodsThe autophagy-related genes were derived from the Human Autophagy Database (HADb) and high-sequencing data were obtained from The Cancer Genome Atlas (TCGA). Discrepantly expressed autophagy genes (DEAGs) between early relapse and long-term survival groups were performed using the Linear Models for Microarray data (LIMMA) method. Lasso Cox regression analysis was conducted for the selection of the 4-gene autophagy-related gene signature. GSE42568 and GSE21653 databases were enrolled in this study for the external validation of the signature. Then patients were divided into high and low-risk groups based on the specific score formula. GSEA was used to discover the related signaling pathway. The Kaplan-Meier curves and the receiver operating characteristic (ROC) curves were used to evaluate the discrimination and accuracy of the 4-gene signature.ResultsA signature composed of four autophagy-related mRNA including APOL1, HSPA8, SIRT1, and TP73, was identified as significantly associated with the early relapse in BC patients. Time-dependent receiver-operating characteristic at 1 year suggested remarkable accuracy of the signature [area under the curve (AUC = 0.748)]. The risk score model based on the autophagy-related signature showed favorable predicting value in 1-, 2-, and 3-year relapse-free survival (RFS) in training and two validating cohorts. The GSEA displayed gene sets were remarkably enriched in carcinogenic activation pathways and autophagy-related pathways. The nomogram involving three variables (progesterone receptor status, T stage, and 4-gene signature) exhibited relatively good discrimination with a C-index of 0.766.ConclusionsOur study establishes an autophagy-related 4-gene signature that can effectively stratify the high-risk and low-risk BC patients for early relapse. Combined with the clinicopathological variables, the signature could significantly help oncologists tailor more efficient treatment strategies for BC patients.

Abstract P2-01-06: Detection of circulating tumor DNA post neoadjuvant chemotherapy using a personalized assay is associated with disease relapse

Abstract Background: Approximately 30% of patients with early breast cancer present disease relapse after surgery, and technologies that enable the detection of circulating tumor DNA (ctDNA) were shown to identify them earlier than standard imaging. In the present study, we aimed to interrogate the value of the SignateraTM personalized ctDNA assay for early detection of disease relapse. Methods: The study included 52 early breast cancer patients undergoing neoadjuvant chemotherapy from an ongoing translational, single-center study at Jules Bordet Institute, Brussels, Belgium. From each patient, primary tumor tissue sections, blood sample for normal DNA, and serial plasma samples were sent to NATERA Inc for ctDNA detection using the SignateraTM assay. Plasma samples were collected before the initiation of neoadjuvant chemotherapy (baseline), after neoadjuvant chemotherapy, before surgery (pre-surgery), and at follow-up post-surgery. Whole exome sequencing (WES) was performed on the primary tumor tissue and matched normal DNA to design a patient-specific ctDNA assay. The unique set of SNV’s identified in WES were tracked in serial plasma samples. Associations between baseline ctDNA detection and standard clinicopathological characteristics and primary tumor point mutations or copy number aberrations were evaluated. Association between ctDNA detection, pathological complete response (pCR) and event-free survival (EFS) were explored. Fisher, Mann-Whitney and Kruskal-Wallis tests were used to compare variables. Log-rank tests and Cox regressions were used for survival analyses. Hazard ratios (HRs) and confidence intervals (CIs) were obtained from Cox regressions. For multivariable tests, logistic regressions were used for binary outcomes and Cox regressions for survival outcomes. P-values were obtained by comparing models with and without the variable of interest using Chi-square test in ANOVAs. Results: Forty-four out of 52 (85%) initially selected patients had the required tumor cellularity (≥ 20%) and adequate tumor DNA quantity and quality and had personalized ctDNA assays designed. In these 44 patients, 154 plasma samples were successfully processed including 38, 41, 75, 38 at baseline, pre-surgery, follow-up (any timepoint) and last follow-up timepoint, respectively. Twenty (45%) patients had hormone receptor positive/HER2-negative, 13 (30%) triple-negative and 11 (25%) HER2-positive breast cancers. Detection of ctDNA was observed in 22 of 38 (58%) patients at baseline and was significantly associated with Ki67>20% and MYC copy number gain in the primary tumor. ctDNA detection at pre-surgery and at last follow-up was observed in 2 of 41 (5%) and 2 of 38 (5%) patients respectively. All patients who achieved pCR were ctDNA-negative at the pre-surgical time point. With a median follow-up of 3.03 years (range 0.39 - 5.85), we observed 8 relapses (7 distant and 1 local, respectively). After adjusting for pCR, ctDNA detection was associated with shorter EFS at pre-surgery and at last follow-up time points (HR: 53, 95% CI: 4.5-624, p<0.01, and HR: 31, 95% CI: 2.7-352, p<0.01, respectively), but not at baseline (HR: 1.4, 95% CI: 0.3-5.9, p=0.67). Conclusions: The detection of ctDNA post neoadjuvant chemotherapy is associated with disease relapse in early breast cancer supporting interventional trials in this setting. Citation Format: Elisa Agostinetto, Frédéric Cailleux, Matteo Lambertini, Françoise Rothé, Hsin-Ta Wu, Mustafa Balcioglu, Himanshu Sethi, Delphine Vincent, Giulia Viglietti, Andrea Gombos, Andreas Papagiannis, Isabelle Veys, Ahmad Awada, Christos Sotiriou, Ekaterina Kalashnikova, Alexey Aleshin, Denis Larsimont, David Venet, Michail Ignatiadis. Detection of circulating tumor DNA post neoadjuvant chemotherapy using a personalized assay is associated with disease relapse [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-01-06.

Effects of systemic inflammation on relapse in early breast cancer

Chronic inflammation has been a proposed mechanism of resistance to aromatase inhibitors in breast cancer. Stratifying by HER2 status, a matched case-control study from the Wellness After Breast Cancer-II cohort was performed to assess whether or not elevated serum inflammatory biomarkers (C-Reactive protein [CRP], interleukin-6 [IL-6], and serum amyloid A [SAA]) and/or the presence of a high-risk IL-6 promoter genotype were associated with recurrence of hormone receptor positive (HR+) early breast cancer. Estrogen levels were also measured and correlated with biomarkers and disease outcomes. CRP and SAA were significantly associated with an increased risk of recurrence in the HR+/HER2− group, but not the HR+/HER2+ group. Mean serum estrogen levels were non-significantly elevated in patients who relapsed vs. non-relapsed patients. Surprisingly, high-risk IL-6 promoter polymorphisms were strongly associated with HER2+ breast cancer relapse, which has potential therapeutic implications, as elevated intracellular IL-6 has been associated with trastuzumab resistance in pre-clinical models.

Effect of CYP2C19 genotypes on tamoxifen metabolism and early-breast cancer relapse

CYP2C19*2 and CYP2C19*17 might influence tamoxifen metabolism and clinical outcome. Our aim was to investigate the effect of CYP2C19 genotypes on tamoxifen concentrations and metabolic ratios (MRs) and breast cancer recurrence in a large cohort of Caucasian women. Genetic variants (CYP2D6 and CYP2C19 genotypes), tamoxifen and metabolites concentrations, baseline characteristics, and breast cancer recurrence from the CYPTAM study (NTR1509) were used. CYP2C19*2 and CYP2C19*17 genotypes were evaluated as alleles and as groups based on CYP2D6 genotypes (high, intermediate and low activity). Log-rank test and Kaplan–Meier analysis were used to evaluate differences in recurrence defined as relapse-free survival (RFS). Classification tree analyses (CTAs) were conducted to assess the levels of interactions per polymorphism (CYP2D6 and CYP2C19 genotypes) on endoxifen concentrations. No differences in mean concentrations and MRs were observed when comparing CYP2C19 genotypes (CYP2C19*1/*1; CYP2C19*1/*2; CYP2C19*2/*2; CYP2C19*1/*17; CYP2C19*17/*17; CYP2C19*2/*17). Only significant differences (p value < 0.05) in mean concentrations and MRs were observed when comparing tamoxifen activity groups (high, intermediate and low activity). A log-rank test did not find an association across CYP2C19 genotypes (p value 0.898). CTAs showed a significant relationship between CYP2D6 and endoxifen (p value < 0.0001), but no association with CYP2C19 genotypes was found. CYP2C19 polymorphisms do not have a significant impact on tamoxifen metabolism or breast cancer relapse.

Abstract P1-05-07: microRNAs regulating tumor and immune cell interactions in the prediction of early relapse in breast cancer

Abstract Background: Metastasis remains the major lethal consequence in the progression of early breast cancer (BC). Effective immunosurveillance can inhibit metastasis, while a dysfunctional immune system can create a favorable environment for tumor spread. MicroRNAs (miRNAs) are involved in the regulation of immune response and there is evidence that they play an important role in immune escape. We investigated the effect of plasma miR-10b, miR-126, miR-19α, miR-20α and miR-155, which regulate the interaction between cancer and immune cells during immunosurveillance and immune evasion in patients with early BC. Methods: Blood samples were obtained from relapsed (n=52) and non-relapsed (n=100) patients with early BC before adjuvant chemotherapy. Plasma miRNA expression levels were assessed by qRT-PCR and expression was classified as high or low according to the median values. Receiver operating curves (ROC) were constructed to determine miRNA sensitivity and specificity. Results: miRNA expression was not correlated with patients’ characteristics or outcome. No differences in miRNA expression were observed between relapsed and non-relapsed patients. In multivariate analysis the number of infiltrated axillary lymph nodes and stage III disease independently predicted for shorter DFS (HR: 2.591; p=0.002) and OS (HR: 2.344; p=0.035), respectively. miR-126, miR-20a, miR-19a and miR-155 expression levels were lower in patients with early relapse (defined as relapse at ≤ 2 yrs; n=19) compared to those who either relapse later than 2 years (n=33) or those who remained disease-free during follow up (n=100). ROC curve analysis showed that miR-155 had the highest performance to discriminate patients with early relapse [AUC 0.825; sensitivity 90%, specificity 67% (p&amp;lt;0.001; 95% CI: 0.742-0.909)]. Multivariate analysis revealed that ER negative status and miR-155 low expression independently predicted for shorter DFS (HR: 2.616; p=0.039 and HR: 9.104; p=0.003, respectively). For the triple negative subgroup (n=31), low miR-155 expression was associated with both shorter DFS and OS (p=0.02 and p=0.032, respectively) and low miR-155 expression was an independent predictor of shorter DFS (HR: 5.056; p=0.037). Conclusions: Deregulated expression of circulating miRNAs involved in tumor and immune cell interactions evaluated before adjuvant chemotherapy is associated with early relapse in patients with primary BC. Low miR-155 expression has high accuracy in the prediction of early relapse in the whole group of patients and independently predicts for shorter DFS in the triple negative subgroup. The role of miR-155 in the pathogenesis and management of early relapse in BC merits further investigation. Citation Format: Konstantina Thomopoulou, Chara Papadaki, Alexia Monastirioti, George Koronakis, Lambros Vamvakas, Maria A Papadaki, Sofia Agelaki, Dimitrios Mavroudis. microRNAs regulating tumor and immune cell interactions in the prediction of early relapse in breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-05-07.

Abstract P2-01-01: Early relapses in breast cancer can be prevented by a perioperative NSAID, which would be a solution to a 2000 year old problem

Abstract A bimodal pattern of hazard of relapse among early stage breast cancer patients has been identified in multiple databases from US, Europe and Asia. We have been studying these data to determine if this can lead to new ideas on how to prevent relapse in breast cancer. Using computer simulation and access to a very high quality database from Milan for patients treated with mastectomy only, we proposed that relapses within 3 years of surgery are stimulated somehow by the surgical procedure. During the week post surgery, metastatic development is enhanced 100 fold according to the simulation. Most relapses in breast cancer are in this early category. Retrospective data from a Brussels anesthesiology group suggested a plausible mechanism. Use of ketorolac, a common NSAID analgesic used in surgery was associated with far superior disease-free survival in the first 5 years after surgery. The expected prominent early relapse events in months 9-18 are reduced 5-fold. Transient systemic inflammation accompanying surgery (identified by IL-6 in serum) could facilitate angiogenesis of dormant micrometastases, proliferation of dormant single cells, and seeding of circulating cancer stem cells resulting in early relapse and could have been effectively blocked by the perioperative anti-inflammatory agent. If this observation holds up to further scrutiny, it could mean that the simple use of this safe, inexpensive and effective anti-inflammatory agent at surgery might eliminate early relapses. Similar bimodal patterns have been identified in other cancers suggesting a general effect. Based on the writings of Galen and Celsus, metastatic development after breast tumors were removed was known to them 2000 years ago. This effect has been demonstrated recently in a mouse model by Krall et al Science Translational Medicine and reviewed in NEJM by Komaroff. In a series of experiments in 273 mice, aggressive mouse breast cancer cells were implanted in various locations. Initially, the tumor cells grew but then became dormant. This dormancy occurred only in mice with intact immunity, which suggests that the immune system can contain certain dormant metastases. Surgery of any type (including resection of a primary tumor) led to aggressive growth of metastases in 60% of animals, compared with 10% of control animals that did not undergo surgery. Surgical procedures caused systemic inflammatory responses. Activated monocytes from the marrow traveled to the sites of the dormant metastases and became tumor associated macrophages. These macrophages suppressed the immune system near the tumor, awakening the metastases from their dormancy. Treating the animals with NSAIDs before and immediately following surgery greatly attenuated growth of these metastases. Since this effect has by now been shown in two Belgian retrospective studies as well as a mouse model we suggest this be tested in one or more clinical trials. We also note that the bleeding potential from using NSAIDs before surgery can apparently be reduced with the use of Tranexamic Acid – currently being tested in a clinical trial for mastectomy. Citation Format: Retsky MW, Baum M, Vaidya JS, Rogers RA, Hrushesky WJ, Demicheli R, Forget P. Early relapses in breast cancer can be prevented by a perioperative NSAID, which would be a solution to a 2000 year old problem [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 P2-01-01.

Disseminated Tumor Cells Predict Efficacy of Regional Nodal Irradiation in Early Stage Breast Cancer

Disseminated tumor cells (DTCs) collect in the bone marrow and indicate micrometastatic spread. We previously reported that DTCs could be a predictive factor for the efficacy of regional node irradiation (internal mammary nodes [IMNs]/supra- and infraclavicular nodes [SCNs]). In this article, we report the long-term results (>10years) on the impact of DTC status in early stage breast cancer. Patients with localized breast cancer were eligible for inclusion in this prospective cohort. DTCs were obtained from a medullary iliac crest sample performed before any primary therapy. DTC status was prospectively assessed by pathologists. Irradiation volumes were defined per standard of care. Cumulative incidence rates and hazard ratios were obtained using both Cox and Fine-Gray models. Interaction tests were performed to confirm the predictive value of DTC status in a multivariate analysis. Six hundred twenty patients with localized breast cancer were included. Overall, 94 patients (15.2%) were DTC-positive. After a median follow-up of 11.7years, 47 patients (7.6%) experienced locoregional relapse. DTC detection was associated with a higher risk of locoregional relapse in univariate and multivariate analyses (Cox hazard ratio, 3.26; 95% confidence interval, 1.6-5.7; P=.001). In the multivariate subgroup analysis, IMN/SCN irradiation significantly reduced locoregional relapse among DTC-positive patients compared with DTC-negative patients (interaction test: hazard ratio, 0.3; 95% confidence interval, 0.1-0.9; P=.02). IMN/SCN was the only irradiation volume with an impact on locoregional relapse in patients according to DTC status, and the predictive value of DTC status for the benefit of locoregional irradiation was independent of locoregional nodal status. This long-term analysis confirms the predictive impact of DTC status on the efficacy of regional radiation therapy for locoregional relapse in early breast cancer. After further studies, DTC status could be used as a decision tool to better tailor adjuvant radiation therapy in patients with early stage breast cancer.

Circulating microRNAs (miRNAs) as predictors of relapse in early breast cancer (BC).

e23030 Background: Disease relapse is usually a lethal development following treatment of early BC. Recurrence could arise from a state of tumour dormancy during which there is growth restriction of undetectable micrometastases. The expression of dormancy and metastasis related miRNAs was evaluated in the plasma of patients (pts) with early BC obtained before adjuvant therapy in order to discover novel biomarkers for the prediction of relapse. Methods: PlasmamiR-21, miR-23b, miR-190, miR-200b and miR-200c expression was assessed by qRT-PCR in 133 pts with early BC (non-relapsed, n = 84; relapsed, n = 49). Expression was classified as high or low according to the median values. Results: No correlation was observed between the expression of miRNAs and the clinicopathological characteristics of pts. After a median follow-up of 94 mo, median Disease Free Interval (DFI) was significantly lower in pts with high compared to low miR-21 [105.03 mo vs not reached (NR); p= 0.001], miR-200c (105.2 mo vs NR; p= 0.007), or both miR-21 and miR-200c expression (81.37 mo vs NR; p= 0.001). miR-21-high was also associated with decreased median Overall Survival (OS; p= 0.041). In multivariate analysis the number of infiltrated axillary lymph nodes (N3 vs N0-N2, HR: 2.86; p= 0.004) and miR-21 expression (high vs low, HR: 2.824; p= 0.001) were independent negative prognostic factors for DFI, whereas negative hormone receptor status (HR: 3.062; p= 0.024) and miR-21 high (HR: 3.545; p= 0.029) independently predicted for worse OS. Moreover, miR-21 expression was higher in pts with early relapse (defined as relapse at ≤ 3 yrs) compared to non-relapsed at 5 yrs ( p= 0.032). In addition, higher miR-21 ( p= 0.038), miR-23b ( p= 0.039), miR-200b ( p= 0.027) and miR-200c ( p&lt; 0.001) levels were observed in pts with late relapse (at ≥ 5 yrs) compared to those without relapse. Conclusions: Differential expression levels of metastasis and/or dormancy related circulating miRNAs are detectable before adjuvant therapy in pts with early BC presenting subsequent relapse compared to non-relapsed pts. Circulating miRNAs can predict for early or late recurrence years before clinical detection of metastases. These results merit prospective validation in an independent patient cohort.

Abstract P2-05-13: Negative progesterone receptor is associate early breast cancer relapse, even among good prognosis tumors

Abstract Background/objective: A minority of estrogen-receptor (ER) positive breast cancers lack progesterone receptor (PR) expression, but little is known of the clinical meaning of PR negativity (PR-). In the present study we sought to clarify the association between PR- and outcomes of ER+, human-epidermal growth factor (HER2)-negative breast cancers using a large, single institution database. Methods: We retrospectively analyzed consecutive, non-metastatic, unilateral HER2- invasive breast cancers diagnosed between 2000 and 2011. Records were reviewed for age at diagnosis, disease stage, tumor features, and histologically confirmed recurrence. ER+ and PR+ status was defined as ≥1% immunoreactive cells. We used Kaplan-Meier curves to determine the association between PR- and early (≤5 years) and late (&amp;gt;5 years) disease recurrence, defined as locoregional or distant breast cancer relapse &amp;gt;6 months after diagnosis. Results: We identified 1,933 patients with TN (n=337) or ER+/HER2- (n=1,596) breast cancer. Patients with ER+/PR- (n=107) vs. ER+/PR+ (n=1,489) tumors did not differ in age or disease stage at diagnosis; however, PR- tumors were more frequently high grade (37.9% vs. 17.8%, p&amp;lt;0.001), with higher median Ki67 indices (20.0% vs. 10.0%, p&amp;lt;0.001). Median ER expression was also lower in PR- as compared to PR+ tumors (80.0% vs. 90.0%, p&amp;lt;0.001). Over a median follow-up of 84 months, there were 119 early and 54 late locoregional or distant breast cancer relapses. Negative PR was strongly associated with early relapse, with PR- tumors demonstrating a 2.1-fold higher hazard of relapse in the first 5 years as compared to PR+ tumors (95% CI 1.0-4.2) Hazards of early (&amp;lt;5 years) breast cancer relapse by hormone status. Shown are univariable Cox proportional hazard ratios and 95% confidence intervals among all tumors, and in subsets defined by %ER, node status, Ki67, and grade. All tumors n=1,933High ER (80-100%) n=1,383TN3.9 (2.6-5.6)*--PR 0%2.1 (1.0-4.2)*1.7 (0.6-4.6)PR 1-100%ReferenceReference Node-negative n=1,299Node-positive n=634TN4.3 (2.5-7.5)*3.6 (2.1-6.0)*PR 0%2.7 (1.0-7.0)*1.6 (0.6-4.5)PR 1-100%ReferenceReference Ki67 &amp;lt;14% n=768Ki67 ≥14% n=997TN**2.4 (1.5-3.8)*PR 0%4.1 (1.2-14.1)*1.6 (0.7-3.8)PR 1-100%ReferenceReference Grade 1/2 n=1,337Grade 3 n=564TN3.4 (1.4-7.9)*1.9 (1.2-3.3)*PR 0%2.0 (0.7-5.7)1.2 (0.4-3.5)PR 1-100%ReferenceReference*p&amp;lt;0.05; **too few subjects/events for analysis. Negative PR remained significantly associated with a higher hazard of early relapse even in node-negative (HR 2.7, 95%CI 1.0-7.0) and low-proliferating tumors (Ki67&amp;lt;14%, HR 4.1, 95%CI 1.2-14.1). There was no significant association between PR- and late breast cancer relapse (HR 0.7, 95%CI 0.2-2.9). Conclusions: Compared to ER+/PR+ breast cancers, ER+/PR- breast cancers have a significantly greater risk of early recurrence, similar to triple-negative cancers. These results suggest that negative PR expression is importantly and independently associated with early breast cancer prognosis, and may be an indicator of unique tumor biology. Citation Format: Winner M, Rosman M, Mylander C, Jackson RS, Pozo ME, Wolff AC, Tafra L, Umbricht CB. Negative progesterone receptor is associate early breast cancer relapse, even among good prognosis tumors [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 P2-05-13.

The sialyl-glycolipid stage-specific embryonic antigen 4 marks a subpopulation of chemotherapy-resistant breast cancer cells with mesenchymal features

IntroductionChemotherapy resistance resulting in incomplete pathologic response is associated with high risk of metastasis and early relapse in breast cancer. The aim of this study was to identify and evaluate biomarkers of treatment-resistant tumor cells.MethodsWe performed a cell surface marker screen in triple-negative breast cancer patient-derived xenograft models treated with standard care genotoxic chemotherapy. Global expression profiling was used to further characterize the identified treatment-resistant subpopulations.ResultsHigh expression of sialyl-glycolipid stage-specific embryonic antigen 4 (SSEA4) was found in residual tumor cells surviving chemotherapy and in samples from metastatic patients who relapsed after neoadjuvant chemotherapy. Gene and microRNA (miRNA) expression profiling linked SSEA4 positivity with a mesenchymal phenotype and a deregulation of drug resistance pathways. Functional assays demonstrated a direct link between epithelial–mesenchymal transition (EMT) and SSEA4 expression. Interestingly, SSEA4 expression, EMT, and drug resistance seemed to be regulated posttranscriptionally. Finally, high expression of CMP-N-acetylneuraminate-β-galactosamide-α-2,3-sialyltransferase 2 (ST3GAL2), the rate-limiting enzyme of SSEA4 synthesis, was found to be associated with poor clinical outcome in breast and ovarian cancer patients treated with chemotherapy.ConclusionsIn this study, we identified SSEA4 as highly expressed in a subpopulation of tumor cells resistant to multiple commonly used chemotherapy drugs, as well as ST3GAL2, the rate-limiting enzyme of SSEA4 synthesis, as a predictive marker of poor outcome for breast and ovarian cancer patients undergoing chemotherapy. Both biomarkers and additionally identified regulatory miRNAs may be used to further understand chemoresistance, to stratify patient groups in order to avoid ineffective and painful therapies, and to develop alternative treatment regimens for breast cancer patients.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-015-0652-6) contains supplementary material, which is available to authorized users.

Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer.

The identification of early-stage breast cancer patients at high risk of relapse would allow tailoring of adjuvant therapy approaches. We assessed whether analysis of circulating tumor DNA (ctDNA) in plasma can be used to monitor for minimal residual disease (MRD) in breast cancer. In a prospective cohort of 55 early breast cancer patients receiving neoadjuvant chemotherapy, detection of ctDNA in plasma after completion of apparently curative treatment-either at a single postsurgical time point or with serial follow-up plasma samples-predicted metastatic relapse with high accuracy [hazard ratio, 25.1 (confidence interval, 4.08 to 130.5; log-rank P < 0.0001) or 12.0 (confidence interval, 3.36 to 43.07; log-rank P < 0.0001), respectively]. Mutation tracking in serial samples increased sensitivity for the prediction of relapse, with a median lead time of 7.9 months over clinical relapse. We further demonstrated that targeted capture sequencing analysis of ctDNA could define the genetic events of MRD, and that MRD sequencing predicted the genetic events of the subsequent metastatic relapse more accurately than sequencing of the primary cancer. Mutation tracking can therefore identify early breast cancer patients at high risk of relapse. Subsequent adjuvant therapeutic interventions could be tailored to the genetic events present in the MRD, a therapeutic approach that could in part combat the challenge posed by intratumor genetic heterogeneity.

Abstract 4317: The sialyl-glycolipid SSEA4 marks a subpopulation of chemotherapy-resistant breast cancer cells with mesenchymal features

Abstract Currently, the main option for systemic therapy of high-risk breast cancer is chemotherapy, with an overall poor efficacy and severe side effects. Chemotherapy-resistance and incomplete pathologic response associate with risk of metastasis and early relapse in breast cancer. In order to characterize treatment-resistant tumor cells, we performed a cell surface marker screen in 4 triple-negative breast cancer patient-derived xenograft (PDX) models that respond well to adriamycin/cyclophosphamide-based chemotherapy but fail to reach complete pathological response. We used multi-parameter flow cytometry to screen for the expression of a set of 45 cell surface markers during the course of chemotherapy. This set of markers represented both proteins involved in stem cell function and proteins known to be over-expressed in stem cells or cancer stem cell sub-populations. We identified the sialyl-glycolipid SSEA4 as a constant marker of chemotherapy-resistant cancer cells in all four models. In addition, SSEA4 expression was found higher in 3 out of 4 TNBC PDXs that are de novo resistant to neo-adjuvant chemotherapy compared to sensitive TNBC PDXs. Two cell populations with different percentage of SSEA4-positive (SSEA4+) cells and with different growth characteristics were identified in a PDX model. When treated with genotoxic compounds, the cell population with higher SSEA4+ expression showed increased resistance to chemotherapy, indicating this post-translational modification as potential marker of tumor resistance. Comparison of SSEA4+ and SSEA4-negative (SSEA4-) tumor cells from TNBC PDX models by global gene expression profiling showed overexpression of mesenchymal-associated genes in SSEA4+ tumor cells and a deregulation of drug resistance pathway-associated genes and miRNAs. In addition, high expression of ST3 beta-galactoside alpha-2,3-sialyltransferase 2 (ST3GAL2), the enzyme catalyzing the last step of SSEA4 synthesis, was found associated with poor outcome in breast and ovarian cancer patients treated with chemotherapy. Thus, we propose SSEA4 as a novel marker of epithelial-mesenchymal transition associated with chemoresistance, and ST3GAL2 expression as a predictive marker for tumor chemoresistance associated with poor outcome in breast and ovarian cancer patients. Both biomarkers and additionally identified regulatory miRNAs may be used to further understand chemoresistance and to develop alternative treatment regimens for breast and ovarian cancer patients. Citation Format: Andrea Aloia, Evgeniya Petrova, Stefan Tomiuk, Ute Bissels, Sophie Banis, Olivier Deas, Silvia Rüberg, Bernhard Gerstmayer, David Agorku, Jean-Gabriel Judde, Andreas Bosio, Stefano Cairo, Olaf T. Hardt. The sialyl-glycolipid SSEA4 marks a subpopulation of chemotherapy-resistant breast cancer cells with mesenchymal features. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4317. doi:10.1158/1538-7445.AM2015-4317

Abstract P4-02-01: High-depth sequencing of circulating tumor DNA to interrogate the genetics of residual micro-metastatic disease prior to relapse in early breast cancer

Abstract Background: The identification of early stage breast cancers that are at high risk of relapse after apparently curative treatment of the primary tumor would allow tailored adjuvant therapy approaches to prevent relapse. We sought to define whether high-depth targeted sequencing of circulating cell-free plasma DNA could be used to interrogate the genetics of residual micro-metastatic disease (RMD) persisting after neoadjuvant treatment in patients with early stage breast cancer. Methods: In a cohort of 31 patients with early breast cancer receiving neoadjuvant chemotherapy, with no evidence of metastasis at presentation, we collected tumor tissue at baseline with the metastatic relapse if it occurred, and serial plasma samples at baseline, post-surgery, and every 6 months in follow-up. Serial plasma samples were subject to digital PCR mutation tracking to examine for circulating tumor DNA (ctDNA). Four patients had ctDNA detectable prior to clinical relapse. Primary tumor-derived DNA (from 4 cases), serial plasma DNA samples (from 4 cases), and metastases derived DNA (from 2 cases) were subjected to massively parallel sequencing (Illumina HiSeq2000) targeting all exons of 273 genes frequently mutated in breast cancers and/ or a custom AmpliSeq cancer panel (IonTorrent). Results: Targeted sequencing revealed the presence of 1 to 20 somatic mutations in the early breast cancers at baseline, including 3 PIK3CA H1047L/R and 2 TP53 pathogenic mutations, all of which were detected in the subsequent plasma DNA samples taken prior to relapse. However, in one case an ESR1 E380Q mutation found in the baseline primary breast cancer was undetectable by targeted sequencing in all 3 subsequent plasma samples and in the metastasis; this mutation could not be identified in the metastasis by digital PCR. In two cases plasma DNA sequencing revealed no additional mutations to those identified in the primary tumor, whereas in the other two cases, plasma DNA targeted capture sequencing revealed divergence in the genetics of RMD. In these cases, 1 and 5 somatic mutations were found in the plasma DNA but were not detected in the respective baseline tumors. In particular, an activating FGFR1 K656E mutation, which was not detected by targeted capture sequencing in the primary breast cancer at 355x sequencing depth, was found at a mutant allele fraction (MAF) of 2.6% in the plasma 12 months post-surgery, and was subsequently detected in the distant metastasis at a MAF of 43.4% by targeted sequencing and digital PCR. Conclusions: Our results provide evidence of clonal shifts in response to neoadjuvant systemic therapy of early breast cancers. In addition, we demonstrate that high-depth targeted capture massively parallel sequencing analysis of plasma ctDNA may help predict the genotype of recurrence prior to the onset of clinically overt metastasis. Citation Format: Charlotte KY Ng, Britta Weigelt, Isaac Garcia-Murillas, Gaia Schiavon, Sarah Hrebien, Rosalind J Cutts, Peter Osin, Ashutosh Nerurkar, Iwanka Kozarewa, Javier Armisen Garrido, Mitch Dowsett, Ian E Smith, Jorge S Reis-Filho, Nicholas C Turner. High-depth sequencing of circulating tumor DNA to interrogate the genetics of residual micro-metastatic disease prior to relapse in early breast cancer [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 P4-02-01.

Prediction of early breast cancer metastasis from DNA microarray data using high-dimensional cox regression models.

BACKGROUNDDNA microarray studies identified gene expression signatures predictive of metastatic relapse in early breast cancer. Standard feature selection procedures applied to reduce the set of predictive genes did not take into account the correlation between genes. In this paper, we studied the performances of three high-dimensional regression methods – CoxBoost, LASSO (Least Absolute Shrinkage and Selection Operator), and Elastic net – to identify prognostic signatures in patients with early breast cancer.METHODSWe analyzed three public retrospective datasets, including a total of 384 patients with axillary lymph node-negative breast cancer. The Amsterdam van’t Veer’s training set of 78 patients was used to determine the optimal gene sets and classifiers using sensitivity thresholds resulting in mis-classification of no more than 10% of the poor-prognosis group. To ensure the comparability between different methods, an automatic selection procedure was used to determine the number of genes included in each model. The van de Vijver’s and Desmedt’s datasets were used as validation sets to evaluate separately the prognostic performances of our classifiers. The results were compared to the original Amsterdam 70-gene classifier.RESULTSThe automatic selection procedure reduced the number of predictive genes up to a minimum of six genes. In the two validation sets, the three models (Elastic net, LASSO, and CoxBoost) led to the definition of genomic classifiers predicting the 5-year metastatic status with similar performances, with respective 59, 56, and 54% accuracy, 83, 75, and 83% sensitivity, and 53, 52, and 48% specificity in the Desmedt’s dataset. In comparison, the Amsterdam 70-gene signature showed 45% accuracy, 97% sensitivity, and 34% specificity. The gene overlap and the classification concordance between the three classifiers were high. All the classifiers added significant prognostic information to that provided by the traditional prognostic factors and showed a very high overlap with respect to gene ontologies (GOs) associated with genes overexpressed in the predicted poor-prognosis vs. good-prognosis classes and centred on cell proliferation. Interestingly, all classifiers reported high sensitivity to predict the 4-year status of metastatic disease.CONCLUSIONSHigh-dimensional regression methods are attractive in prognostic studies because finding a small subset of genes may facilitate the transfer to the clinic, and also because they strengthen the robustness of the model by limiting the selection of false-positive predictive genes. With only six genes, the CoxBoost classifier predicted the 4-year status of metastatic disease with 93% sensitivity. Selecting a few genes related to ontologies other than cell proliferation might further improve the overall sensitivity performance.

A new 5-gene signature predictive of risk of relapse in early breast cancer.

546 Background: The aim of this study was look for the "core-genes" of published Signatures in order to find a simpler one Methods: To select candidate genes we used data of NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/) including 408 breast cancer cases. Raw intensity data of Affymetrix HU133A and HU133B arrays of the two datasets (GSE1456 and GSE3494) were preprocessed using R/Bioconductor and the supercomputer Michelangelo ( www.litbio.org ). The candidate genes were selected from the “70-gene signature” (van 't Veer, Nature 2002), the “21-gene recurrence score” (Paik, NEJM 2004), the “two-gene–ratio model” (Ma, Cancer Cell 2004) and the “15-gene Insuline Resistence” signature (Gennari , JCO, Vol 25, No 18S, 2007: 10597), for a total of 98 genes.The 20 mRNA more significantly related to DFS were evaluated by quantitative reverse transcriptase PCR on 261 consecutive breast cancer cases, from paraffin embedded sections, split into a training (n 137) and a validation set (n 124). Results: The signature was developed on the training set and a multivariate stepwise Cox analysis selected 5 genes independently associated with DFS: FGF18 (HR=1.13, p=0.05) , BCL2 (HR=0.57, p=0.001), PRC1 (HR=1.51, p=0.001), MMP9 (HR=1.11, p=0.08), SERF1a (HR=0.83, p=0.007). These 5 genes were combined into a linear score weighted according to the coefficients of the Cox model, (0.125 FGF18 - 0.560 BCL2 + 0.409 PRC1 + 0.104 MMP9 - 0.188 SERF1A). The linear score was highly associated with DFS (HR=2.7, 95%CI=1.9-4.0, p&lt;0.001). The signature was then evaluated on the validation set assessing the discrimination ability by a Kaplan Meier analysis, using the same cut offs classifying patients at low, medium or high risk of relapse as defined on the training set. The score resulted highly associated with DFS also in the validation set (p&lt;0.001). Conclusions: Overexpression of BCL2 and SERF1A are related to a higher probability of relapse; overexpression of FGF18, PRC1 and MMP9 to a higher probability of survival without recurrence. The signature has a good discriminating ability and a further clinical validation is planned.