bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract P5-04-17: From transcriptome meta-analysis to targeted therapies in triple negative breast cancer
Authors: Rozali E , Al-Ejeh F 
Published: May 2016

Abstract
Triple-Negative Breast Cancer (TNBC) is a subtype of breast cancer that urgently requires the identification and approval of novel targeted therapies. Even for breast cancer subtypes that have approved targeted therapies such as tamoxifen in ER+ and herceptin in HER2+ patients, there are a proportion of patients that do not respond to these therapies or develop resistance and succumb to metastatic recurrence. Thus, there is a clinical need to identify patients who do not benefit from current standard therapies and developing new strategies for therapy for non-responsive patients across all breast cancer subtypes.
We hypothesised a potential prognostic and drug discovery approach by meta-analysis of multiple global gene expression profiles of breast cancer studies to identify significantly over- and under-expressed genes that associate with clinical outcomes (metastatic and/or death events within five years). These genes were filtered through 3 methods to annotate their predicted functions (1). The third and most generalised method identified a 133-gene signature set that was prognostic in all subtypes of breast cancer. These signatures, particularly with the devised score calculated as the ratio of the average expression of the over-expressed genes to the under-expressed genes, were patented (2). Of the 133 genes, we selected a 21-gene list representing novel and new targets in breast cancer drug development. The 21 genes were selected through an unbiased ranking of least-published cancer and non-cancer studies in PubMed.
This poster reports the characterisation of these 21 genes as drug targets in TNBC. A siRNA screen measuring proliferation and viability (xCELLigence RTCA) was performed (2 siRNAs per gene) on 3 TNBC cell lines (MDAMB231, SUM159PT and BT549) and MCF10A. The top gene hits that show a dependence on cancer proliferation and viability were followed up with clonogenic assays, cell cycle profiles and apoptosis assays. Parallel to these experiments, a negative-selection clustered regularly interspaced short palindromic repeats (CRISPR) screen involving the 21 genes (6 constructs per gene) is currently underway on MDAMB231 cell line in vitro and in vivo to identify cancer dependence on these genes for survival and metastasis.
References
1. Al-Ejeh, F., Simpson, P.T., Saunus, J.M., Klein, K., Kalimutho, M., Shi, W., Miranda, M., Kutasovic, J., Raghavendra, A., Madore, J., et al. 2014. Meta-analysis of the global gene expression profile of triple-negative breast cancer identifies genes for the prognostication and treatment of aggressive breast cancer. Oncogenesis 3:e124.
2. Al-Ejeh, F. 2015. PCT/AU2015/050096 (SUBMITTED).
Citation Format: Rozali E, Al-Ejeh F. From transcriptome meta-analysis to targeted therapies in triple negative breast cancer. [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 P5-04-17.
Abstract P5-07-05: Development of individual adjuvant chemotherapy benefit estimating program for breast cancer patients management
Authors: Rouzier R , Stevens D , Bonneau C , Falcou M-C , Hequet D , Pierga J-Y , Lerebours F 
Published: May 2016

Abstract
Background
To predict the individual benefit of adjuvant chemotherapy (CT) is challenging especially in estrogen receptor tumors HER2 negative tumors. Existing tools are based on data from randomized trials or on genomic tests with benefit calculated for outmoded CT. The aim of this study was to develop an exportable model to predict from real life data the invidual benefit of adjuvant anthracyclines/taxanes based CT.
Patients and methods
Women with estrogen receptor-positive HER2-negative tumors without metastasis at the time of the diagnosis treated at the Institut Curie - Centre René Huguenin (St Cloud, France) between 2000 and 2008 were included. Clinical characteristics, pathological data and information concerning the treatments and outcomes had been prospectively registered. We divided the study population into 2 groups: patients who did not receive adjuvant CT and patients who did. Multivariate survival analysis and prediction were performed according to the Cox model (proportional hazard model). Non-informative variables in the Cox model were excluded from the final model. The individual benefit of CT was calculated by comparing predicted distant disease-free survival without chemotherapy (using a model constructed in patients treated without adjuvant CT) and modeled distant disease-free survival with CT. Benefit of chemotherapy was validated by cross validation and compared to Adjuvant online predictions.
Results
Data from 3385 women were available: 2137 treated without adjuvant chemotherapy and 1248 with. The models to predict survival without and with CT were based on tumor size, number of metastatic nodes, grade and KI67 (all patients had ER-positive-HER2 negative tumors). The discrimination and the calibration of the models were excellent: C-index were 0.81 and 0.76 for patients treated without and with CT. In this population, the mean 10-year benefit provided by CT was 6.2% (median: 1.5%, min: -4%, max: 35%). The accuracy of the model was internally validated and over-performed predictions of adjuvant online because Ki67 and HER2 status are included in our model (p&lt;.05). A web-based interface is available.
Conclusion
We constructed a tool to evaluate the benefit of adjuvant anthracycline / taxane at an individual level. This tool is based on a model that outperform currently availble methods.
Citation Format: Rouzier R, Stevens D, Bonneau C, Falcou M-C, Hequet D, Pierga J-Y, Lerebours F. Development of individual adjuvant chemotherapy benefit estimating program for breast cancer patients management. [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 P5-07-05.
Abstract P5-08-20: Breast cancer patient survival prediction based on the signature derived from DNA methylation and mRNA expression
Authors: Yang HH , Lee MP 
Published: May 2016

Abstract
We analyzed a subset in the TCGA breast cancer data set for the samples with both expression and methylation assays. We first used the three Immunohistochemistry (IHC) markers for ER, PR and HER2 to find methylation sites that showed significant association to the IHC markers with Bonferroni adjustments. We obtained 2616 methylation sites in 2148 genes in the union of these significant methylation sites. On the other hand, based on the gene expression of samples, we selected top one percent most variable genes (179 genes). Intersection of the 2616 methylation markers with the 179 genes resulted in 58 methylation markers in 43 genes. We found 339 samples which have both expression and methylation data from which we can compute the correlation between the expression of a gene and the methylation of a marker in this gene. We defined a methylation expression index (MEI) which was a weighted sum of the expression of the 43 genes using the negative Spearman correlations as the weights. The expression index was applied in the survival analysis in three independent data sets GSE6532, NKI and METABRIC using Kaplan-Meier method and found the significant difference between the patient groups with high and low MEI index. Compared to the signature derived from the first principal component, the MEI gave better survival prediction across different data sets. We used Cox proportional hazards regression model to evaluate the hazard ratio of the MEI with adjustment of the other variables including age, grade, tumor size, ER and node and found HR=1.58 for the MEI with 95% confidence interval [1.06, 2.35].
Citation Format: Yang HH, Lee MP. Breast cancer patient survival prediction based on the signature derived from DNA methylation and mRNA expression. [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 P5-08-20.
Abstract P5-08-22: DUSP4 is associated with increased resistance against anti-HER2 therapy in breast cancer
Authors: Györffy B , Munkacsy G , Esteva FJ , Miquel TP , Menyhart O 
Published: May 2016

Abstract
Background. The majority of patients develop resistance against suppression of HER2-mediated signaling by trastuzumab in HER2 positive breast cancer (BC). HER2 overexpression activates multiple signaling pathways, including the mitogen-activated protein kinase (MAPK) cascade. MAPK phosphatases (MKPs) are essential regulators of MAPKs and participate in many facets of cellular regulation, including proliferation and apoptosis. We aimed to identify whether differential MKPs are associated with resistance to targeted therapy in patients previously treated with trastuzumab.
Methods. Using Affymetrix HGU133plus2 gene chip data of 88 HER2-positive, trastuzumab treated BC patients, candidate MKPs were identified by Receiver Operator Characteristics analysis performed in R. Genes were ranked using their achieved area under the curve (AUC) values and were further constricted to those markers significantly associated to worse survival. Functional significance of the two strongest predictive biomarkers was evaluated in vitro experiments after gene silencing in the HER2 overexpressing, trastuzumab resistant breast cancer cell lines SKBR-3-TR and JIMT-1.
Results. Out of 10 investigated MKPs, the strongest predictive genes were DUSP4/MKP2 (AUC=0.75, p=0.0096) and DUSP6/MKP3 (AUC=0.77, p=5.29E-05). Furthermore, higher expression for these correlated to worse survival in 221 HER2 positive BC patients (DUSP4: HR=1.6, p=0.04 and DUSP6: HR=1.8, p=0.0053). Silencing of DUSP4 had significant sensitization effects - viability of DUSP4 siRNA transfected, trastuzumab treated cells decreased significantly compared to scramble-siRNA transfected, trastuzumab treated controls (SKBR-3-TR: p=0.016; JIMT-1: p=0.016). In contrast, simultaneous treatment with DUSP6 siRNA and trastuzumab did not alter cell proliferation.
Conclusions. Our findings suggest that DUSP4 is involved in the development of trastuzumab resistance in HER2 positive BC.
Citation Format: Györffy B, Munkacsy G, Esteva FJ, Miquel TP, Menyhart O. DUSP4 is associated with increased resistance against anti-HER2 therapy in breast cancer. [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 P5-08-22.
Abstract P5-08-23: Ki-67 expression is not a valuable predictive prognostic factor when progesterone receptor expression is high in estrogen receptor-positive breast cancer
Authors: Han JH , Kang YJ , Han W , Lee H-B , Kim Y , Yoo T-K , Moon H-G , Noh D-Y 
Published: May 2016

Abstract
Background
Immunohistochemistry markers are recognized as a predictive prognostic factor for women with breast cancer. Ki-67 and progesterone receptor (PgR) expression are reported to be independently associated with breast cancer prognosis. Some studies report high Ki-67 expression as a negative predictive marker. Whereas other studies report tendency of similar survival between high and low Ki67 cancers when PgR expression is high. In this study, we examined the prognostic significance of Ki-67 expression under PgR expression status.
Methods
The records of 2,366 patients were retrospectively reviewed. The patients underwent surgery for primary breast cancer from July 2009 to December 2012 at a single institution. We studied the prognostic significance of Ki-67 expression under PgR expression. We used 20% and 10% as the cut-off value for PgR and Ki-67, respectively. The end point was recurrence-free survival (RFS) evaluated by use of Kaplan-Meier analysis.
Result
Of the 2,366 analyzed patients, the median follow-up time was 43 months. During follow-up, 44 patients had recurrence, loco-regional recurrence developed in 23 patients and distant recurrence developed in 21 patients. In patients with low PgR expression, high Ki-67 expression group showed significantly worse prognosis compared to low Ki-67 expression group (p=0.005). On the other hand, no significant difference was shown between low and high Ki-67 expression group when PgR expression was high (p=0.637). Also multivariate analysis demonstrated that high Ki-67 expression was an independent prognostic factor only when PgR expression was low. (95% confidence interval [CI], 1.35-10.48; p=0.011)
Conclusion
This is the largest reported study that prognostic significance of Ki-67 expression is defined by PgR expression. Our study presents that high Ki-67 expression is inversely correlated with recurrence risk in early breast cancer patients only under low PgR expression. At high PgR expression, Ki-67 expression has no influence on breast cancer prognosis. Therefore, attention should be paid to correlation between PgR and Ki-67 expression.
Citation Format: Han JH, Kang YJ, Han W, Lee H-B, Kim Y, Yoo T-K, Moon H-G, Noh D-Y. Ki-67 expression is not a valuable predictive prognostic factor when progesterone receptor expression is high in estrogen receptor-positive breast cancer. [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 P5-08-23.
Abstract P5-08-25: CKAP2 (cytoskeleton associated protein 2) is a new prognostic marker in HER2-negative luminal breast cancer
Authors: Sim SH , Bae C-D , Kwon Y , Park IH , Lee KS , Jung S-Y , Lee S , Kang H-S , Lee ES , Kim H-S , Hong K-M , Ro J 
Published: May 2016

Abstract
Background: Ki-67 has been increasingly used as a prognostic marker in spite of debates on the evaluation methods and inconsistent results on its clinical values. CKAP2 is a microtubule-associated protein which plays key roles in microtubule assembly and disassembly. In the present study, the clinical significance of CKAP2-positive cells was evaluated and compared with the results of Ki-67 positive cells.
Methods: A total of 579 early breast cancer patients who underwent surgery at the National Cancer Center Hospital between 2001 and 2005 were accrued. The proliferation activity was measured by CKAP2-positive cell count (CPCC) and Ki-67 labeling index (Ki-67 LI) using CKAP2 and Ki-67 antibodies, respectively, by immunohistochemcial staining on FFPE tumor tissue. The correlation of CPCC or Ki-67 LI with recurrence free survival (RFS) was analyzed. The immunofluorescent staining was performed on HeLa cells after synchronization by double thymidine block to compare the patterns between CKAP2 and Ki-67.
Results: The CPCC (median, 8 with the range of 0- 170) and Ki-67 LI (median, 10.2 with the range of 0%- 91.7%) were highly correlated (R = 0.754, P &lt; 0.001). While CPCC was marginally significant in multivariate analysis for RFS in all cases, it was a significant variable for RFS in the subset analysis with HER2-negative luminal breast cancer patients (HR, 3.154; 95% CI, 1.154-10.693; P = 0.027). On the contrary, Ki-67 LI failed to show any correlation with RFS in all or any subgroups. In the analysis on HeLa cells, CKAP2 staining was more specific to cells in metaphase than Ki-67 staining.
Conclusions: CPCC can be an independent prognostic factor specifically in a HER2-negative luminal type of breast cancer. In addition, CPCC appears to be superior to Ki-67 LI as a survival indicator which may be related to the restricted expression pattern of CKAP2 in metaphase cells. Further study is warranted.
Citation Format: Sim SH, Bae C-D, Kwon Y, Park IH, Lee KS, Jung S-Y, Lee S, Kang H-S, Lee ES, Kim H-S, Hong K-M, Ro J. CKAP2 (cytoskeleton associated protein 2) is a new prognostic marker in HER2-negative luminal breast cancer. [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 P5-08-25.
Abstract P5-08-42: Development and validation of personalized ex vivo platform mimicking patient heterogeneous tumor microenvironment to enable personalized treatment for breast cancer
Authors: Majumder PK , Majumder B , Mehrotra DG , Radhakrishnan P , Baraneedharan U , Agarwal S , Sengupta S , Babu G 
Published: May 2016

Abstract
Tumour heterogeneity is emerging as a key driver of drug response. Understanding the heterogeneity is therefore a critical milestone towards the prediction of clinical outcome of anti-cancer drugs. There is a need for technology that can predict treatment outcome with high fidelity by contextually integrating tumor heterogeneity and phenocopying the tumor microenvironment.
Tumor grade-matched matrix support, activated immune compartments and autologous ligands from individual patients were used to engineer a novel personalized ex vivo platform named CANScript. We evaluated functional outcomes as a measure of response to a panel of anticancer drugs in this CANScript platform. Histopathological and molecular characterization of the tumor explants cultured in CANScript revealed a close approximation to the parental tumor at baseline as confirmed by tumor cell viability, proliferation, critical phosphoproteomic status, global transcriptomic profiles and balance in active components of tumor and stromal phenotypes (Majumder. B et al Nat. Commun, 2015). Using more than 100 patients clinical outcome of anticancer drugs (training set) we have further built a machine learning algorithm that takes all functional outcome data from the CANScript platform and provides outcome data in a linear scale showing clinical prediction. This algorithm when applied to the test cohort of more than 40 patients with refractory breast cancer assessed in the CANScript achieved more than 90% sensitivity while keeping specificity in a desired high range for predicting short term clinical outcome.
The high specificity and sensitivity observed in predicting clinical outcomes using the CANScript support the use of this novel platform to select treatment for patients with breast cancer.
Citation Format: Majumder PK, Majumder B, Mehrotra DG, Radhakrishnan P, Baraneedharan U, Agarwal S, Sengupta S, Babu G. Development and validation of personalized ex vivo platform mimicking patient heterogeneous tumor microenvironment to enable personalized treatment for breast cancer. [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 P5-08-42.
Abstract P5-08-47: Clinical outcome of pathological T1N0 breast cancer according to the hormone receptor and HER2 status and adjuvant therapy
Authors: Tokunaga E , Akiyoshi S , Koga C , Nakamura Y , Taguchi K , Ishida M , Ohno S 
Published: May 2016

Abstract
Background: The outcome of T1N0 breast cancer is relatively good, however, a subpopulation of this stage has a high population of relapse. It is important to clarify the factors associated with the outcome in order to determine the adequate adjuvant systemic therapy for T1N0 breast cancer.
Aims: To investigate the prognosis of pathological T1N0 (pT1N0) breast cancer by receptor (estrogen receptor; ER, progesterone receptor; PgR, human epidermal growth factor receptor 2; HER2) status and adjuvant systemic therapy, and thus to identify the factors associated with the outcome.
Methods: Among 2164 women who underwent surgery for primary breast cancer in our department, 925 had pathological T1N0 tumors (130 T1a, 234 T1b and 561 T1c). The associations between clinicopathological characteristics, adjuvant therapy and relapse-free survival (RFS) were examined
Results: Of 908 patients with known hormone receptor (HR; ER and PgR) and HER2 status, 675, 79, 64 and 90 had HR+/HER2-, HR+/HER2+, HR-/HER2+ and HR-/HER2- (triple negative; TN) tumors, respectively. The prognosis of patients with T1c tumors was significantly poorer than that of the patients with T1a and T1b tumors (5-year DFS of T1a, T1b and T1c: 97.5%, 97.9%, 94.5%, p=0.0201). HR+/HER2- subtype was significantly associated with better prognosis than other subtypes (5-year DFS: 96.9% vs. 93.6%, p=0.0194). Patients younger than 40 year old or older than 74 years old had significantly shorter PFS (p=0.0039). Lymphovessel invasion (ly), high histological grade (HG2, 3) were associated with poor outcome in all cohort (p=0.0026, p=0.0356). In HR-positive tumors, ly, high HG and omission of the adjuvant endocrine therapy were associated with shorter RFS (p=0.0009, p=0.0306 and p=0.0016, respectively). Adjuvant chemotherapy was not associated with RFS regardless of HR and HER2 status. However, in T1c with nuclear grade (NG) 3 tumors, use of the adjuvant chemotherapy was associated better prognosis. The prognosis of patients with HER2+ tumors was not significantly different among patients with or without trastuzumab in this cohort.
Conclusion: In spite of the excellent prognosis of pT1N0 breast cancer, adjuvant endocrine therapy is important for patients with HR+ tumors. However, the use of adjuvant chemotherapy or trastuzumab did not significantly improve the prognosis. Thus, the indication of chemotherapy or anti-HER2 therapy should be determined in consideration of the several prognostic factors for pT1N0 breast cancer.
Citation Format: Tokunaga E, Akiyoshi S, Koga C, Nakamura Y, Taguchi K, Ishida M, Ohno S. Clinical outcome of pathological T1N0 breast cancer according to the hormone receptor and HER2 status and adjuvant therapy. [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 P5-08-47.