A Syngeneic ErbB2 Mammary Cancer Model for Preclinical Immunotherapy Trials.

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 cell line 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.

Pathobiology of the 129:Stat1 -/- mouse model of human age-related ER-positive breast cancer with an immune infiltrate-excluded phenotype.

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.

Validation of RNAi Silencing Efficiency Using Gene Array Data shows 18.5% Failure Rate across 429 Independent Experiments.

No independent cross-validation of success rate for studies utilizing small interfering RNA (siRNA) for gene silencing has been completed before. To assess the influence of experimental parameters like cell line, transfection technique, validation method, and type of control, we have to validate these in a large set of studies. We utilized gene chip data published for siRNA experiments to assess success rate and to compare methods used in these experiments. We searched NCBI GEO for samples with whole transcriptome analysis before and after gene silencing and evaluated the efficiency for the target and off-target genes using the array-based expression data. Wilcoxon signed-rank test was used to assess silencing efficacy and Kruskal-Wallis tests and Spearman rank correlation were used to evaluate study parameters. All together 1,643 samples representing 429 experiments published in 207 studies were evaluated. The fold change (FC) of down-regulation of the target gene was above 0.7 in 18.5% and was above 0.5 in 38.7% of experiments. Silencing efficiency was lowest in MCF7 and highest in SW480 cells (FC = 0.59 and FC = 0.30, respectively, P = 9.3E-06). Studies utilizing Western blot for validation performed better than those with quantitative polymerase chain reaction (qPCR) or microarray (FC = 0.43, FC = 0.47, and FC = 0.55, respectively, P = 2.8E-04). There was no correlation between type of control, transfection method, publication year, and silencing efficiency. Although gene silencing is a robust feature successfully cross-validated in the majority of experiments, efficiency remained insufficient in a significant proportion of studies. Selection of cell line model and validation method had the highest influence on silencing proficiency.

Glucose Uptake and Intracellular pH in a Mouse Model of Ductal Carcinoma In situ (DCIS) Suggests Metabolic Heterogeneity.

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 (BCECF) 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.

A Network-Based Target Overlap Score for Characterizing Drug Combinations: High Correlation with Cancer Clinical Trial Results.

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.

MEK1 is associated with carboplatin resistance and is a prognostic biomarker in epithelial ovarian cancer.

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.

Biomarkers for systemic therapy in ovarian cancer.

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.

Identifying resistance mechanisms against five tyrosine kinase inhibitors targeting the ERBB/RAS pathway in 45 cancer cell lines.

Because of the low overall response rates of 10-47% to targeted cancer therapeutics, there is an increasing need for predictive biomarkers. We aimed to identify genes predicting response to five already approved tyrosine kinase inhibitors. We tested 45 cancer cell lines for sensitivity to sunitinib, erlotinib, lapatinib, sorafenib and gefitinib at the clinically administered doses. A resistance matrix was determined, and gene expression profiles of the subsets of resistant vs. sensitive cell lines were compared. Triplicate gene expression signatures were obtained from the caArray project. Significance analysis of microarrays and rank products were applied for feature selection. Ninety-five genes were also measured by RT-PCR. In case of four sunitinib resistance associated genes, the results were validated in clinical samples by immunohistochemistry. A list of 63 top genes associated with resistance against the five tyrosine kinase inhibitors was identified. Quantitative RT-PCR analysis confirmed 45 of 63 genes identified by microarray analysis. Only two genes (ANXA3 and RAB25) were related to sensitivity against more than three inhibitors. The immunohistochemical analysis of sunitinib-treated metastatic renal cell carcinomas confirmed the correlation between RAB17, LGALS8, and EPCAM and overall survival. In summary, we determined predictive biomarkers for five tyrosine kinase inhibitors, and validated sunitinib resistance biomarkers by immunohistochemistry in an independent patient cohort.

Parallel evolution under chemotherapy pressure in 29 breast cancer cell lines results in dissimilar mechanisms of resistance.

BACKGROUND: Developing 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. METHODS: Parallel 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. RESULTS: All 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. CONCLUSION: We 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.

[Gene expression based multigene prognostic and predictive tests in breast cancer]. / Génexpresszió mérésén alapuló multigénes prognosztikai és prediktív elorejelzés emlotumorokban.

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.