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583 Background: Immunotherapy is entering clinical practice as a promising new neoadjuvant therapeutic approach in triple-negative breast cancer, and it is important to identify biomarkers to focus this therapy on those patients that have the highest benefit. Interestingly, an improved survival outcome is observed in pCR and non-pCR patients, which raises the hypothesis that biomarkers might also be different for pCR prediction as well as prognosis. In this study, we investigated this hypothesis in the neoadjuvant GeparNuevo trial. Methods: A total of 174 patients were randomized to receive neoadjuvant chemotherapy with durvalumab vs. placebo. HTG EdgeSeq mRNA analysis was performed for a total of 2549 genes in 162 pretherapeutic core biopsies. In addition, tumor-infiltrating lymphocytes (stromal and intratumoural) as well as PD-L1 protein expression was evaluated by IHC. We systematically compared the distant disease-free survival (DDFS) of 5 predefined gene signatures (including the GeparSixto immune signature) as well as 12 single mRNA markers identified in previous projects between treatment arms using univariate Cox proportional-hazard regression analyses. In addition, exploratory biomarker analyses were performed. Results: The PSIP1 gene expression (per 1 unit hazard ratio [HR]: 0.58 95%CI 0.41-0.83; p=0.002), TAP1 (per 1 unit HR: 0.68 95%CI 0.48-0.95; p=0.025) as well as stromal TILs (sTILs) (per 10% HR: 0.73 95%CI 0.56-0.95; p=0.019) were significant for improved DDFS in the complete cohort. In the placebo arm PSIP1 (HR 0.50 95%CI 0.29-0.87; p=0.014) as well as sTILs (HR 0.73 95%CI 0.53-0.99; p=0.044) were significant for improved DDFS. In the durvalumab arm, the gene expression of PSIP1 (HR 0.54 95%CI 0.31-0.94; p=0.029), PD-L1/CD274 (per 1 unit HR: 0.41 95%CI 0.21-0.77; p=0.006), CD38 (per 1 unit: HR 0.52 95%CI 0.29-0.92; p=0.026) as well as the GeparSixto immune signature (per 1 unit HR: 0.51 95%CI 0.27-0.97; p=0.041) were significant for improved DDFS, with a positive test for interaction with treatment arm for PD-L1/CD274 (interaction p=0.020). Additional analyses, including multivariate Cox regressions for DDFS as well as systematic comparisons for biomarkers for DDFS and for pCR, will be presented. Conclusions: Our analysis suggests that biomarkers for immune response are linked to improved survival with neoadjuvant durvalumab therapy and that in this setting, survival biomarkers are not identical to pCR biomarkers. The results are a basis for a further dissection of the contribution of pCR to survival effects of immunotherapy.

581 Background: It is commonly anticipated that a high tumor mutational burden (TMB) is a predictor of response to immune checkpoint blockade (ICB). We previously showed that triple-negative breast cancer (TNBC) from the GeparNuevo study with high TMB displayed increased response both to neoadjuvant chemo-ICB with durvalumab but also to chemotherapy alone, with no significant interaction with treatment arm (Karn et al. Ann Oncol 2020). In contrast, we also observed that cases with very low TMB more often displayed a pCR after treatment with chemo-ICB than with chemotherapy alone. This may in fact suggest a benefit of ICB to those TNBC with rather low TMB. Methods: We have analyzed the distant disease-free survival (DDFS) of GeparNuevo patients according to TMB and treatment arm (neoadjuvant chemotherapy plus durvalumab or chemotherapy plus placebo). For TMB (mut/Mb) we applied the identical cutoff of the upper tertile as in our previous analysis. Results: The median follow-up of the time-to-event data was 43.7 months. Data of TMB was available in 149 of 174 patients. We found that within the high-TMB tumors (durvalumab: n=27; placebo: n=23), DDFS was similar between both arms of the trial (durvalumab vs. placebo: HR (hazard ratio) 0.95 [95%CI 0.19-4.69], p=0.95). Strikingly however, within the low-TMB group (durvalumab: n=47; placebo: n=52) we observed a significantly better DDFS in the durvalumab-chemotherapy combination arm, in contrast to the arm treated only with chemotherapy (durvalumab vs. placebo: HR 0.23 [95%CI 0.06-0.79], p=0.02; interaction test for TMB and treatment arm p=0.17). The observation was also robust to alternative TMB cutoffs. Similar results were obtained for invasive disease-free survival. Conclusions: Our results show, in contrast to other published data, that patients with early TNBC and low TMB/neoantigen counts may benefit from short-term neoadjuvant durvalumab treatment, while for those with high TMB, durvalumab plus chemotherapy does not improve efficacy over chemotherapy alone.

e18061 Background: Risk factors for invasive recurrence of borderline tumours (BOT) of the ovary are needed. The actin-bundling protein Fascin-1 (FSCN1) is involved in alteration of adhesion and cell motility and has been associated with invasion and metastasis in different cancers. Methods: We studied a retrospective cohort of 124 bordeline tumors of the ovary (BOT) with validated diagnosis by an independent pathologist for expression of FSCN1 as potential prognostic biomarker. Results: We found strong expression of the actin-bundling protein FSCN1 in 62 of these tumors. FSCN1 positive patients were slightly younger (46.9±2.2 vs. 53.3±2.3 years, P = 0.049). Expression of FSCN1 was more frequently detected in BOT with serous compared to mucinous histotype (58/78 [74.4%] vs. 3/41 [7.3%], p < 0.001), and in cases with micropapillary pattern (25/28 [89.3%] vs. 38/98 [38.8%], P < 0.001). In addition, a non significant trend was observed for more frequent expression of FSCN1 among cases with implants (8/10 [80.0%] vs. 55/116 [47.4%], P = 0.095). When we compared progression free survival of the patients we found numerical lower but not statistically significant PFS rates of 90.5±6.4% vs. 94.4±5.4% for 10 years, and 81.4±10.3% vs. 94.4±5.4% for 15 years, in BOT with FSCN1 expression compared to those tumors negative for FSCN1, respectively. Conclusions: Our analysis suggests an association of FSCN1 expression in BOT with micropapillary pattern and implants, which have been linked to inferior prognosis. Cases with FSCN1 expression in our cohort displayed numerical lower PFS rates prompting further studies of this marker.

509 Background: GeparNuevo (G9) showed a numerical increase in pCR rate of 53% vs 44%; p = 0.287 compared to placebo in TNBC with the addition of the anti-PD-L1 antibody durvalumab (D) to a neoadjuvant anthracycline-taxane containing chemotherapy (Loibl S et al. ASCO 2018). Somatic mutations in malignant cells manifest over the evolutionary history of a tumor. Reports in selected tumor types suggest that TMB may predict clinical outcomes on immune-checkpoint inhibitors (ICI). The clinical relevance of TMB in breast cancer has not been studied widely. Here, we investigated the hypothesis that TMB predicts response to ICI. Methods: Whole exome sequencing was conducted on patient-matched fresh-frozen core biopsies and blood samples with Illumina (n = 149/174). SNVs and indels were called with Mutect and pureCN was used for copy number calls. Mutational signatures were identified as described by Alexandrov et al. (Cell Rep. 3, 2013). Data from G9 were compared to The Cancer Genome Atlas (TCGA) TNBC cohort. Results: A similar genomic landscape was observed between G9 and TCGA with primary mutations in TP53 (69%), c-MYC (26%), BRCA1 (13%), BRCA2 (6%), PIK3CA (11%) and PTEN (11%). Median TMB was 1.52 mut/MB. TMB in G9 was slightly lower than TCGA TNBC. TMB correlated with older age, higher mutation rates in BRCA2, ARID1A, and TP53, and higher burden in variant signatures such as DDR, HRD, GFRs, APOBEC and Alexandrov’s signatures 3 and 6. Continuous TMB predicted pCR in univariate (OR = 1.62, 95%-CI: 1.20 - 2.20, p = 0.0018) and multivariate (OR = 2.06, 95%-CI: 1.33 - 3.20, p = 0.0012) logistic regression models, but did not predict a D effect. After dichotomisation of TMB at the top tertile, 50 patients had high TMB and 29 of these (58%) achieved a pCR, while 99 had low TMB and only 38 of these (38%) had a pCR (p = 0.0242). Conclusions: Results show that TMB may predict pCR in primary TNBC. The trial was financially supported by Astra Zeneca and Celgene. Clinical trial information: NCT02685059.

588 Background: The GeparNuevo trial is a randomized, double-blind, multi-center phase II trial of neoadjuvant therapy in patients with early-stage triple negative breast cancer (TNBC) investigating the role of durvalumab, an anti-PD-L1 antibody, which blocks PD-L1 binding to PD1 and CD80, in addition to standard chemotherapy with nab-Paclitaxel (nab-Pac) followed by Epirubicin plus Cyclophosphamid (EC; Loibl S et al. ASCO 2018). Since the tumor mutational burden (TMB) has been suggested to be associated with a better outcome of patients undergoing immunotherapy and an increased T cell response, we determined whether there exists a link between TMB and immune cell composition, frequency and function in patients of the GeparNuevo trial. Methods: In order to determine possible predictive and / or prognostic biomarkers, tumor biopsies taken at recruitment from 149 patients out of the 174 enrolled patients underwent deep sequencing in order to determine the TMB. In addition, for 120 patients blood samples were taken at recruitment and during different time points of treatment (after durvalumab pre-treatment, after Nab-Pac and at surgery after EC) and evaluated using multicolor flow cytometry by monitoring the absolute cell counts of T cells, B cells and NK cells as well as the frequency, composition and functionality of different immune cell populations. Results: The TMB of the GeparNuevo cohort was in line with published data with a mean of 1.8 mutations/MB (range 0.02 – 7.65), respectively. Preliminary evaluation demonstrated a significant correlation of TMB with blood parameters, in particular with subsets of CD8+ T cells. Interestingly, the data suggest a negative correlation of TMB with the frequency of effector cells while a positive correlation exists with the effector memory cells at recruitment. In depth analyses of a correlation with treatment arm and clinical responses are currently performed. Conclusions: Using this approach we hope to identify biomarkers, which will allow a better selection of TNBC patients undergoing specific immunotherapies. Clinical trial information: NCT02685059.

3075 Background: Hormone receptors, HER2 and Ki-67 are prognostic values typically determined for breast cancer (BC) outcome and prediction of therapy response. A RT-qPCR based system, the Xpert Breast Cancer STRAT4, can be used to classify BC tissues regarding their hormone receptor status, HER2 and proliferation via Ki-67. We compared mRNA expression analysis of ER, PR, HER2, and Ki-67 by this automated in-vitro diagnostic platform (GeneXpert) (GX) with central immunohistochemistry (IHC) in a large clinical trial cohort. Methods: BC patients from the prospective GBG neoadjuvant trial GeparX (NCT02682693) (still recruiting) were included in this biomarker project. We used formalin-fixed paraffin embedded (FFPE) pretherapeutical core biopsies with a tumor content > 10%. One 4 µm FFPE tissue section was first processed with the Xpert FFPE Lysis Kit, the sample lysate was placed in the STRAT4 cartridge system and then tested on the GX system in which the purification, amplification and real-time detection took place within two hours automatically. Results: A total of 503 (99%) of the 509 samples had a valid measurement of all four genes. 258 samples (51.3%) of the cohort were classified in central pathology as ER positive, 196 (39%) as PR positive and 78 (15.5%) as HER2-positive, and 421 samples (83.7%) were Ki-67-high ( > 20%). The simple kappa coefficient was for ER = 0.7938, PR = 0.6540, HER2 = 0.8172 and Ki-67 = 0.3655. This indicates, that the measurements for ER, PR and HER2 showed a high correlation between both methods, whereas the measurement of Ki-67 does not. The accuracy between the STRAT4 and IHC was 89.7% for ER, 83.3% for PR, 94.6% for HER2 and 86.7% for Ki-67. According to molecular subgroups, highest accuracy regarding Ki-67, was determined in TNBC (96.2%; luminal: 81.1%; HER2-positive: 76.9%). Conclusions: Our results show a high concordance between standardized central IHC and automated mRNA expression analysis for the most important BC biomarkers ER, PR and HER2. For the proliferation marker Ki-67, the concordance is slightly lower. The STRAT4 assay might offer additional option to conventional methods for BC biomarker assessment, in particular in settings where IHC is not feasible. To determine the clinical validity, additional outcome analyses are necessary. Clinical trial information: NCT02682693.

527Background: Immunogenic infiltrate in breast cancer (BC) may influence the prognosis and response to systemic therapies. The association and prognostic role of tumor infiltrating lymphocytes (TI...

11522 Background: Resistance towards anti-angiogenic therapy (AAT) still represents a substantial clinical challenge. As mast cell (MC) density is known to correlate with tumor angiogenesis, we analyzed if inhibition of MC holds potential to increase efficacy of AAT in mice and cancer patients. Methods: C57BL/6J (WT), NSG or MC-deficient KitW-sh(Wsh) mice were subcutaneously injected with Panc02, EL4 or BxPC3 cells with or without bone marrow-derived MC. Tumors were treated with 20 mg/kg of anti-VEGFR2 antibodies (DC101) or 25 mg/kg cromoglicic acid. Tissue microarrays from n = 299 breast cancer patients from the GeparQuinto Phase 3 clinical trial were stained for MC and MC numbers were correlated with clinical data. Results: We observed that absence of MC reduced tumor growth and increased the efficacy of AAT in different tumor models. Intriguingly, AAT only initially reduced microvessel proliferation but this was abrogated over time as a result of MC-mediated resistance. We show that MC secrete increased amounts of granzyme b upon therapy, which mobilizes alternative pro-angiogenic factors from the tumor matrix. These factors act beside the targeted VEGFA-VEGFR2-axis and reinduce angiogenesis despite the presence of AAT. Importantly, MC-mediated resistance could be overcome using the FDA-approved MC inhibitor cromoglicic acid. In line with our preclinical data, high intratumoral MC density correlated with disease progression in HR+ breast cancer patients when Bevacizumab was added to standard neodjuvant chemotherapy (HR 8.45, p = 0.006). Accordingly, Kaplan-Meier curves indicated that disease free survival of patients with high tumoral MC density was numerically shorter in the whole cohort and significantly shorter in the HR+ cohort upon addition of AAT to chemotherapy (p = 0.168 and p = 0.004, respectively). Conclusions: Here we unravel a novel resistance mechanism, by which MC hamper efficacy of AAT in mice and cancer patients. In preclinical models this effect could be overcome by combining AAT with an FDA-approved MC inhibitor indicating high clinical relevance. Thus, combination of FDA-approved MC inhibitors with AAT might be a suitable approach to increase efficacy of AAT in the clinic.

10068 Background: Women ≤45 years (yrs) treated with chemotherapy (CT) for EBC have a high risk of developing CIOF. Awareness of CIOF is essential for young women. Methods: 740 patients (pts) aged ≤45yrs treated with anthracycline or taxane-based CT for EBC from 4 German neoadjuvant/adjuvant trials were included. Blood samples were collected at baseline (N=740), end of treatment (EOT n=740), 6 (n=177), 12 (n=113), 18 (n=69), 24 (n=47) months (m) after EOT. Only samples collected in a time sequence were included. Estradiol (E2), Follicle-Stimulating Hormone (FSH) and Anti-Müllerian Hormone (AMH) were centrally assessed. CIOF was defined as FSH >12.4IU/l and E2

e13028 Background: African American (AA) women are more likely to be diagnosed with triple negative breast cancer (TNBC) compared to other races and have lower pathologic complete response rate to neoadjuvant therapy. Our goal was to assess differences in the immune microenvironment and genomic characteristics of TNBC by race using the TCGA data set. Methods: We compared the expression levels of 13 previously reported immune metagenes (CTL, Mphages, MHC1, Tregs, IF1, NK, STAT1, MHC2, Giam, Tfh, Tinh, Tstim, LCK), histologic tumor infiltrating lymphocyte (TIL) count and overall mutational load, neoantigen load, clonal heterogeneity assessed using the MATH score, amplification and deletion loads of between AA (n = 58) and non-AA TNBC (n = 114). Data was downloaded from the TCGA website, immune metagene expression and MATH scores were calculated as previously reported. Distributions between cohorts were compared using the Mann-Whitney U-test. Results: Among the immune metagenes only the cytotoxic T cell (CTL) metagene showed lower expression in AA patients (3.64 versus 4.08, unadjusted p = 0.046). TIL count was available in 51 of 58 AA and 91 of 114 of non-AA cases, and no significant difference was observed between the racial groups (p = 0.55). We also did not observe statistically significant differences in the mutational load (p = 0.36), neoantigen load (p = 0.38), clonal heterogeneity represented by the MATH score (p = 0.54), and amplification and deletion loads (p = 0.23 and 0.83 respectively) between the two TNBC race groups. We also assess the expression distribution of the immune signatures in an independent Affymetrix gene expression dataset including 40 AA and 323 non-AA patients with TNBC. Similar to the TCGA, there were no significant race differences in the immune signatures, including in the CTL metagene. Conclusions: These results suggest that the differences in prevalence and treatment response seen between TNBC in AA and non-AA patients are unlikely to be due to differences in the immune microenvironment and the genomic landscape of TNBC. However, more subtle comparison in the immune biology of these cancers can only be studies with more focused methods.

11505Background: Appropriate biomarkers to guide selection of patients for treatment with bevacizumab are still urgently needed. In this study, we analyzed serum levels of carbonic anhydrase IX (sC...

1081 Background: In HER2+ patients treated with HER2-targeted monoclonal antibodies in the NeoSphere trial, multivariate analysis showed a complex interplay between immune system and response (Gian...

530 Background: In ER+ tumors, a dentritic metagene (DM) predicts for lower risk of relapse (Bianchini G JCO 2010; Bianchini G ASCO 2012). We investigated if other immune metagenes provided additio...

1065 Background: To exceed prediction accuracy of previous multigene prognostic classifiers, we propose a new dynamic predictor. Our classifier does not use a single universal training cohort and a...

615 Background: Sphingolipids play important roles in apoptosis, senescence, cell proliferation and angiogenesis. Spingosine kinase 1 (SphK1) expression was shown to have prognostic impact in prima...

e15562 Background: Acid ceramidase (AC), a key enzyme of sphingolipid metabolism, plays an important role in cancer progression. Objective of this study was to explore the expression of AC in ovari...

e19647 Background: otally implanted venous access systems (portacath) are increasingly used in cancer patients in order to make the application of chemotherapy for patients more comfortable and saf...

661 Background: Several recent reports have linked the expression of SATB1, a genome organizer recruiting chromatin remodeling/modifying enzymes and transcription factors, to the potential for meta...

e21074 Background: Proteomic analyses has become a valuable tool in cancer research. The new tandem mass tag (TMT) technology was evaluated in breast cancer. Methods: Proteomic analysis was used to...

566 Background: The protein 63 (p63) represents a member of the p53 family (p53/p63/p73) located on chromosome 3q27. This gene family seems to play an important role in carcinogenesis and its members may act as oncogenes or tumor suppressor genes. P63 is overexpressed in many different tumors like head and neck cancer, lung cancers, uterine tumors and breast cancer, and has been associated with poor prognosis in some studies. P63 was found to be overexpressed in a subset of highly aggressive breast cancers that represent a basal and myoepithelial phenotype and have a poor clinical outcome. This protein seems to be a specific myoepithelial cell marker in normal breast tissue and might represent a prognostic factor in breast cancer. Methods: Large scale analysis was performed using Affymetrix microarray data from n=1581 breast cancer patients to evaluate p63 expression. Results: P63 expression showed a strong correlation with patient's age (χ2-test, p < 0.001), tumor size (p < 0.003), proliferation rate (p < 0.001), Topo2α expression (p = 0.001) and estrogen receptor expression (p = 0.017). Survival analysis of all patients with available follow up data (n = 1263) showed a significant difference due to high and low p63 expression (log rank p < 0.001). Patients with a low p63 expression had the worst prognosis. In univariate Cox regression analysis p63 showed a hazard ratio (HR) of 1.61 (95% CI 1.31–2.00, p < 0.001) for disease free survival. This prognostic impact remained significant when samples were stratified by estrogen receptor status. High expression of p63 was significantly associated with longer OS in both ER negative (n = 334, log rank p = 0.022) and ER positive (n = 929, log rank p < 0,001) breast cancer. The prognostic impact of p63 expression was independent of Ki67 expression (p = 0.011 and p = 0.001 for high and low Ki67, respectively). Moreover a worse prognosis of low p63 expressing tumors was found in both subgroups of ErbB2 positive tumors (p < 0.001) and ErbB2 negative tumors (p < 0.001). Conclusions: P63 expression is a prognostic factor in both ER positive and negative breast cancer and could be helpful for risk assessment in breast cancer patients. No significant financial relationships to disclose.

11015 Background: In vitro and in vivo data demonstrate that the expression of estrogen receptor (ER) in breast cancer is mainly associated with low proliferation. Gene expression profiling has recently been used to identify a group of high proliferating estrogen receptor positive breast cancers (the luminal B subtype), which are associated with a prognosis that is even worse than that of high proliferating estrogen receptor negative tumors. The analysis of those tumors might provide valuable information about breast cancer biology and could be helpful for adjuvant or neoadjuvant treatment decisions.Methods and Results: We analyzed microarray data from breast cancer specimens to gain insight into genes which play a role in estrogen receptor signalling. Genes were identified showing strong expression in high proliferating ER-positive tumors but no expression in either Ki67-/ER+ or Ki67+/ER- samples. Among these genes the Na+/H+ exchanger regulatory factor NHERF1 was found. We assessed the clinical relevance of NHERF1 transcript levels using a total of 2469 breast cancers. Analysis indicates that enhanced NHERF1 expression is associated with metastatic progression and poor prognosis of breast cancer patients. We found no correlation between NHERF1 and the nodal status as well as age, but positive correlations for tumor size (P No significant financial relationships to disclose.

11102 Background: Lymphocyte infiltration is often seen in breast cancer and has been suggested as a marker of host antitumor immune response but its importance remains controversial. Moreover, onl...

11109 Background: Beside their structural role for the cell membrane sphingolipids act as effector molecules in signal transduction with links to various aspects of cancer initiation, progression a...

10517 Background: Endocrine responsiveness is one of the most important characteristics of breast cancer. The negative association between expression of the estrogen receptor (ER) and proliferation detected in normal breast is frequently lost in breast cancers leading to receptor independent growth and poor patients’ prognosis. Methods: Microarray analysis of 171 breast cancer samples allowed the discrimination of a KIT+ tumor group by using a set of genes coregulated with the “stem cell factor” receptor KIT. Validation was performed on three independent datasets encompassing 637 samples. Furthermore the response to endocrine treatment only was analyzed in a dataset of 700 patients. Results: KIT+ tumors are transcriptionally related to proposed mammary stem cells. Two types of KIT+ tumors were identified which are characterized by their positive and negative ER status, respectively. The inverse link of ER expression and proliferation is perfectly conserved within the KIT+ tumor groups, while it is uncoupled among half of the KIT-Low ER positive tumors. Those “uncoupled” ER positive tumors with altered ER response are characterized by a prognosis inferior to the ER negative cancers despite an apparent positive ER status (hazard ratio for disease recurrence, 2.07; 95% CI 1.53–2.81; P+ tumors could allow a dissection of estrogen responsiveness giving crucial insights for prediction of response to endocrine therapy. No significant financial relationships to disclose.

622 Background: Expression of the proto-oncogene c-kit has been found in malignant tissue including a subset of breast cancers. c-Kit is also expressed in normal breast tissue and several authors found a loss of c-kit expression in breast carcinoma suggesting it might be involved in the growth control of mammary epithelium. Until now, only a few markers were described to be co-regulated with c-kit. To elucidate the possible role of c-kit in malignant transformation, we analyzed gene expression data of breast cancer patients. Methods: Tumor tissue of n=171 breast cancer patients were analyzed by gene expression profiling using Affymetrix Hg U133 Arrays (22,500 genes) and bioinformatic analyses. Tumor samples with high stromal and low epithelial cell content by gene expression profiling were excluded for further analysis. Validation was performed with n=100 independent samples. Results: A total of 10.5% of the tumors showed strong c-kit expression (2.5 fold above median). A careful dissection of global expression data revealed strong correlations of c-kit with the expression of a large cluster of genes containing several for whom c-kit coexpression was already described (HER1, CK-5/-17, PDGFR) as well as several members of the wnt signalling pathway, providing a possible novel link to mammary epithelial differentiation. Analysis of n=171 breast cancer samples according to this gene set allows the identification of putative “stem cell like” tumors (SCL) characterized by expression of several known stem cell markers. Surprisingly, a tight link of ER status and proliferation is restricted only to these SCL tumors but lost among non-SCL tumors. The clinical implications of our findings will be presented. Conclusions: For the first time these data bring together the description of two breast cancer subtypes identified by gene expression profiling with the actual stem cell model of the development of breast cancer. No significant financial relationships to disclose.

646 Background: Neoadjuvant administration of chemotherapy before surgery provides a unique opportunity to directly monitor response to treatment in breast cancer and excactly assess response. Goal...