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In order to develop a practical model of breast cancer, with in vitro and syngeneic,immune-intact, in vivo growth capacity, we established a primary cell line derived from a mammary carcinoma in the transgenic FVB/N-Tg(MMTV-ErbB2*)NDL2-5Mul mouse, referred to as "NDLUCD". The cellline is adapted to standard cell culture and can be transplanted into syngeneic FVB/N mice. The line maintains a stable phenotype over multiple in vitro passages and rounds of in vivo transplantation. NDLUCD tumors in FVB/N mice exhibit high expression of ErbB2 and ErbB3 and signaling molecules downstream of ErbB2. The syngeneic transplant tumors elicit an immune reaction in the adjacent stroma, detected and characterized using histology, immunophenotyping, and gene expression. NDLUCD cells also express PD-L1 in vivo and in vitro, and in vivo transplants are reactive to anti-immune checkpoint therapy with responses conducive to immunotherapy studies. This new NDLUCD cell line model is a practical alternative to the more commonly used 4T1 cells, and our previously described FVB/N-Tg(MMTV-PyVT)634Mul derived Met-1fvb2 and FVB/NTg(MMTV-PyVTY315F/Y322F) derived DB-7fvb2 cell lines. The NDLUCD cells have, so far, remained genetically and phenotypically stable over many generations, with consistent and reproducible results in immune intact preclinical cohorts.

Background Stat1 gene-targeted knockout mice (129S6/SvEvTac-Stat1 tm1Rds) develop estrogen receptor-positive (ER+), luminal-type mammary carcinomas at an advanced age. There is evidence for both host environment as well as tumor cell-intrinsic mechanisms to initiate tumorigenesis in this model. In this report, we summarize details of the systemic and mammary pathology at preneoplastic and tumor-bearing time points. In addition, we investigate tumor progression in the 129:Stat1 −/− host compared with wild-type 129/SvEv, and we describe the immune cell reaction to the tumors. Methods Mice housed and treated according to National Institutes of Health guidelines and Institutional Animal Care and Use Committee-approved methods were evaluated by histopathology, and their tissues were subjected to immunohistochemistry with computer-assisted quantitative image analysis. Tumor cell culture and conditioned media from cell culture were used to perform macrophage (RAW264.7) cell migration assays, including the 129:Stat1 −/−-derived SSM2 cells as well as control Met1 and NDL tumor cells and EpH4 normal cells. Results Tumorigenesis in 129:Stat1 −/− originates from a population of FoxA1+ large oval pale cells that initially appear and accumulate along the mammary ducts in segments or regions of the gland prior to giving rise to mammary intraepithelial neoplasias. Progression to invasive carcinoma is accompanied by a marked local stromal and immune cell response composed predominantly of T cells and macrophages. In conditioned media experiments, cells derived from 129:Stat1 −/− tumors secrete both chemoattractant and chemoinhibitory factors, with greater attraction in the extracellular vesicular fraction and inhibition in the soluble fraction. The result appears to be recruitment of the immune reaction to the periphery of the tumor, with exclusion of immune cell infiltration into the tumor. Conclusions 129:Stat1 −/− is a unique model for studying the critical origins and risk reduction strategies in age-related ER+ breast cancer. In addition, it can be used in preclinical trials of hormonal and targeted therapies as well as immunotherapies. Electronic supplementary material The online version of this article (doi:10.1186/s13058-017-0892-8) contains supplementary material, which is available to authorized users.

Mechanisms for the progression of ductal carcinoma in situ (DCIS) to invasive breast carcinoma remain unclear. Previously we showed that the transition to invasiveness in the mammary intraepithelial neoplastic outgrowth (MINO) model of DCIS does not correlate with its serial acquisition of genetic mutations. We hypothesized instead that progression to invasiveness depends on a change in the microenvironment and that precancer cells might create a more tumor-permissive microenvironment secondary to changes in glucose uptake and metabolism. Immunostaining for glucose transporter 1 (GLUT1) and the hypoxia marker carbonic anhydrase 9 (CAIX) in tumor, normal mammary gland and MINO (precancer) tissue showed differences in expression. The uptake of the fluorescent glucose analog dye, 2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl) amino]-2-deoxy-D-glucose (2-NBDG), reflected differences in the cellular distributions of glucose uptake in normal mammary epithelial cells (nMEC), MINO and Met1 cancer cells, with a broad distribution in the MINO population. The intracellular pH (pHi) measured using the fluorescent ratio dye 2’,7’-bis(2-carboxyethyl)-5(6)-155 carboxyfluorescein-AM (BCECF-AM) revealed expected differences between normal and cancer cells (low and high, respectively), and a mixed distribution in the MINO cells, with a subset of cells in the MINO having an increased rate of acidification when proton efflux was inhibited. Invasive tumor cells had a more alkaline baseline pHi with high rates of proton production coupled with higher rates of proton export, compared with nMEC. MINO cells displayed considerable variation in baseline pHi that separated into two distinct populations: MINO high and MINO low. MINO high had a noticeably higher mean acidification rate compared with nMEC, but relatively high baseline pHi similar to tumor cells. MINO low cells also had an increased acidification rate compared with nMEC, but with a more acidic pHi similar to nMEC. These findings demonstrate that MINO is heterogeneous with respect to intracellular pH regulation which may be associated with an acidified regional microenvironment. A change in the pH of the microenvironment might contribute to a tumor-permissive or tumor-promoting progression. We are not aware of any previous work showing that a sub-population of cells in in situ precancer exhibits a higher than normal proton production and export rate.

Patient tailored therapy will serve the fundamentals of future cancer treatment. For this it will be imperative to characterize the tumor and to acquire precise predictive and prognostic information. We can achieve this by using not only monogenic (like ER, PR, HER-2, Ki-67) but also multigene assays, which can provide answers to several diagnostic questions simultaneously. We present a summary of currently available RT-PCR and microarray based multigene tests including MammaPrint, Oncotype DX, BLN Assay, Theros Breast Cancer Index SM, MapQuant DX, ARUP Breast Bioclassifier, Celera Metastatic Score, eXagen BCtm, Invasive Gene Signature, Wound Response Indicator and Mammostrat. Two of these (Oncotype DX and MammaPrint) are already incorporated in several diagnostic protocols. However, multiple unsolved issues deteriorate the value of these tests: generally the validation is poor, the gene sets do not confirm each other, the associated costs are high and the necessary bioinformatics is highly complex.

Background Primary systemic treatment for ovarian cancer is surgery, followed by platinum based chemotherapy. Platinum resistant cancers progress/recur in approximately 25% of cases within six months. We aimed to identify clinically useful biomarkers of platinum resistance. Methods A database of ovarian cancer transcriptomic datasets including treatment and response information was set up by mining the GEO and TCGA repositories. Receiver operator characteristics (ROC) analysis was performed in R for each gene and these were then ranked using their achieved area under the curve (AUC) values. The most significant candidates were selected and in vitro functionally evaluated in four epithelial ovarian cancer cell lines (SKOV-3-, CAOV-3, ES-2 and OVCAR-3), using gene silencing combined with drug treatment in viability and apoptosis assays. We collected 94 tumor samples and the strongest candidate was validated by IHC and qRT-PCR in these. Results All together 1,452 eligible patients were identified. Based on the ROC analysis the eight most significant genes were JRK, CNOT8, RTF1, CCT3, NFAT2CIP, MEK1, FUBP1 and CSDE1. Silencing of MEK1, CSDE1, CNOT8 and RTF1, and pharmacological inhibition of MEK1 caused significant sensitization in the cell lines. Of the eight genes, JRK (p = 3.2E-05), MEK1 (p = 0.0078), FUBP1 (p = 0.014) and CNOT8 (p = 0.00022) also correlated to progression free survival. The correlation between the best biomarker candidate MEK1 and survival was validated in two independent cohorts by qRT-PCR (n = 34, HR = 5.8, p = 0.003) and IHC (n = 59, HR = 4.3, p = 0.033). Conclusion We identified MEK1 as a promising prognostic biomarker candidate correlated to response to platinum based chemotherapy in ovarian cancer. Electronic supplementary material The online version of this article (doi:10.1186/1471-2407-14-837) contains supplementary material, which is available to authorized users.

Epithelial ovarian cancer (EOC) is the most deadly tumor of the female reproductive system. Despite improvements in understanding the biology of EOC, therapeutic strategies still depend on surgery and combination of taxane and platinum agents. Here, we provide a summary of clinically tested biomarkers potentially useful to predict drug response. Resistance against platinum derivatives can result from lower drug concentrations, alterations in the target molecule and changes in the cellular signal transduction pathways. Taxane resistance can develop due to decreased intracellular drug concentration, alterations in microtubuli structure and changes in the cellular response including ERBB2 (epidermal growth factor receptor 2). A few key genes have been suggested as biomarkers for hormonal therapy. Currently, the only targeted therapy agent approved for ovarian cancer is the VEGF (vascular endothelial growth factor) inhibitor bevacizumab. Response to bevacizumab is correlated with VEGF-A levels and hypertension. The primary problems in identifying reliable biomarkers for EOC are the usage of different clinical endpoints, multivariate analysis for a panel of clinical parameters and the lack of published comprehensive clinical information of patients enrolled in these studies. The future lies in adding targeted agents to the taxane/platinum gold standard and in a more detailed stratification of patients into sub-cohorts enabling a more effective therapy. In conclusion, a large-scale coordinated effort is needed for the robust validation of the numerous biomarker candidates available in EOC therapy.

Patient tailored therapy will serve the fundamentals of future cancer treatment. For this it will be imperative to characterize the tumor and to acquire precise predictive and prognostic information. We can achieve this by using not only monogenic (like ER, PR, HER-2, Ki-67) but also multigene assays, which can provide answers to several diagnostic questions simultaneously. We present a summary of currently available RT-PCR and microarray based multigene tests including MammaPrint, Oncotype DX, BLN Assay, Theros Breast Cancer Index SM, MapQuant DX, ARUP Breast Bioclassifier, Celera Metastatic Score, eXagen BCtm, Invasive Gene Signature, Wound Response Indicator and Mammostrat. Two of these (Oncotype DX and MammaPrint) are already incorporated in several diagnostic protocols. However, multiple unsolved issues deteriorate the value of these tests: generally the validation is poor, the gene sets do not confirm each other, the associated costs are high and the necessary bioinformatics is highly complex.

Drug combinations are highly efficient in systemic treatment of complex multigene diseases such as cancer, diabetes, arthritis and hypertension. Most currently used combinations were found in empirical ways, which limits the speed of discovery for new and more effective combinations. Therefore, there is a substantial need for efficient and fast computational methods. Here, we present a principle that is based on the assumption that perturbations generated by multiple pharmaceutical agents propagate through an interaction network and can cause unexpected amplification at targets not immediately affected by the original drugs. In order to capture this phenomenon, we introduce a novel Target Overlap Score (TOS) that is defined for two pharmaceutical agents as the number of jointly perturbed targets divided by the number of all targets potentially affected by the two agents. We show that this measure is correlated with the known effects of beneficial and deleterious drug combinations taken from the DCDB, TTD and Drugs.com databases. We demonstrate the utility of TOS by correlating the score to the outcome of recent clinical trials evaluating trastuzumab, an effective anticancer agent utilized in combination with anthracycline- and taxane- based systemic chemotherapy in HER2-receptor (erb-b2 receptor tyrosine kinase 2) positive breast cancer.

5557 Background: Primary systemic treatments for ovarian cancer are paclitaxel and carboplatin chemotherapy. Platinum resistant cancers progress/recur in approximately 25% of cases within six month...

e21005 Background: Clinical studies show low overall response rates of 10-47% to targeted cancer therapeutics. Our aim was to identify new biomarkers for predicting sensitivity against five already approved tyrosine kinase inhibitors. Methods: Sensitivity to sunitinib, erlotinib, lapatinib, sorafenib and gefitinib were tested in 45 cancer cell lines, and a resistance index was calculated for each cell line. The gene expression profiles (data were obtained by interrogating the raw microarray data of the caArray database) in the subset of resistant vs. sensitive cell lines were compared for each drug. Feature selection was carried out using significance analysis of microarrays and rank products. The results were validated by qPCR in the cell lines and - in case of four sunitinib resistance associated genes - in clinical samples by immunohistochemistry. Results: A set of 63 genes was identified as associated with resistance against the examined drugs. Overall classification accuracy of the prediction was 92.8% in a leave-one-out cross validation using prediction analysis of microarrays. The expression of the genes was validated by qPCR in the cell lines. The results confirmed 45/63 of the microarray-based resistance associated genes and 7/32 of literature based genes. All together 48 sunitinib-treated metastatic renal cell carcinomas were collected. The immunohistochemical analysis in these confirmed the correlation of the expression of RAB17, LGALS8, and EPCAM with overall survival. Conclusions: We identified new predictive biomarker candidates for five tyrosine kinase inhibitors, and validated a set of sunitinib resistance associated genes in an independent patient cohort.

BackgroundDeveloping chemotherapy resistant cell lines can help to identify markers of resistance. Instead of using a panel of highly heterogeneous cell lines, we assumed that truly robust and convergent pattern of resistance can be identified in multiple parallel engineered derivatives of only a few parental cell lines.MethodsParallel cell populations were initiated for two breast cancer cell lines (MDA-MB-231 and MCF-7) and these were treated independently for 18 months with doxorubicin or paclitaxel. IC50 values against 4 chemotherapy agents were determined to measure cross-resistance. Chromosomal instability and karyotypic changes were determined by cytogenetics. TaqMan RT-PCR measurements were performed for resistance-candidate genes. Pgp activity was measured by FACS.ResultsAll together 16 doxorubicin- and 13 paclitaxel-treated cell lines were developed showing 2-46 fold and 3-28 fold increase in resistance, respectively. The RT-PCR and FACS analyses confirmed changes in tubulin isofom composition, TOP2A and MVP expression and activity of transport pumps (ABCB1, ABCG2). Cytogenetics showed less chromosomes but more structural aberrations in the resistant cells.ConclusionWe surpassed previous studies by parallel developing a massive number of cell lines to investigate chemoresistance. While the heterogeneity caused evolution of multiple resistant clones with different resistance characteristics, the activation of only a few mechanisms were sufficient in one cell line to achieve resistance.