(word count: 239):Murine syngeneic tumor models are critical to novel immuno-based therapy development but the molecular and immunological features of these models are still not clearly defined. The translational relevance of differences between the models is not fully understood, impeding appropriate preclinical model selection for target validation, and ultimately hindering drug development. Across a panel of commonly-used murine syngeneic tumor models, we showed variable responsiveness to immunotherapies. We employed array comparative genomic hybridization, whole-exome sequencing, exon microarray analysis, and flow cytometry to extensively characterize these models, which revealed striking differences that may underlie these contrasting response profiles. We identified strong differential gene expression in immune-related pathways and changes in immune cell-specific genes that suggested differences in tumor immune infiltrates between models. Further investigation using flow cytometry showed differences in both the composition and magnitude of the tumor immune infiltrates, identifying models that harbor 'inflamed' and 'non-inflamed' tumor immune infiltrate phenotypes. We also found that immunosuppressive cell types predominated in syngeneic mouse tumor models that did not respond to immune-checkpoint blockade, whereas cytotoxic effector immune cells were enriched in responsive models. A cytotoxic cell-rich tumor immune infiltrate has been correlated with increased efficacy of immunotherapies in the clinic and these differences could underlie the varying response profiles to immunotherapy between the syngeneic models. This characterization highlighted the importance of extensive profiling and will enable investigators to select appropriate models to interrogate the activity of immunotherapies as well as combinations with targeted therapies in vivo.4

Comparative proteomic methods are rapidly being applied to many different biological systems including complex tissues. One pitfall of these methods is that in some cases, such as oncology and neuroscience, tissue complexity requires isolation of specific cell types and sample is limited. Laser microdissection (LMD) is commonly used for obtaining such samples for proteomic studies. We have combined LMD with sensitive thiol-reactive saturation dye labelling of protein samples and 2-D DIGE to identify protein changes in a test system, the isolated CA1 pyramidal neurone layer of a transgenic (Tg) rat carrying a human amyloid precursor protein transgene. Saturation dye labelling proved to be extremely sensitive with a spot map of over 5,000 proteins being readily produced from 5 mug total protein, with over 100 proteins being significantly altered at p < 0.0005. Of the proteins identified, all showed coherent changes associated with transgene expression. It was, however, difficult to identify significantly different proteins using PMF and MALDI-TOF on gels containing less than 500 mug total protein. The use of saturation dye labelling of limiting samples will therefore require the use of highly sensitive MS techniques to identify the significantly altered proteins isolated using methods such as LMD.

the MIAPE Gel Electrophoresis (MIAPE-GE) guidelines specify the minimum information that should be provided when reporting the use of n-dimensional gel electrophoresis in a proteomics experiment. Developed through a joint effort between the gel-based analysis working group of the Human Proteome Organisation's Proteomics Standards Initiative (HUPO-PSI; http://www.psidev.info/) and the wider proteomics community, they constitute one part of the overall Minimum Information about a Proteomics Experiment (MIAPE) documentation system published last August in Nature Biotechnolog

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Background: Early results from Phase II trials have shown that treatment with the PARP inhibitor olaparib (AZD2281, KU-0059436) can induce tumour specific synthetic lethality in patients with BRCA-mutated breast and ovarian cancer, with little effect on normal tissues. Pre-clinical studies have indicated that sensitivity can also result from other perturbations affecting homologous recombination (HR), suggesting broader patient populations may benefit from this drug. We aimed to generate pre-clinical hypotheses as to the key biological mechanisms regulating response to this drug; and identify associated biomarkers by which responding patient subsets could be stratified. Methods: A panel of 95 cell lines representing breast, ovarian, colorectal, lung, head & neck and pancreatic cancers was tested for sensitivity to olaparib using 2D-clonogenic survival assays. Baseline (untreated) gene expression profiles (Affymetrix U133A Plus2) were determined for each cell line, alongside protein expression and mutational status of core HR genes. Dynamic pathway gene expression signatures were collated from the literature, and additional signatures generated using RNAi against core HR components. Statistical and bioinformatic approaches were then applied to prioritise correlated networks of genes displaying consistent pathway overlay and predictive of response in cell line subsets. Results: 30 cell lines were highly sensitive to olaparib treatment (IC50 &lt;1 µM) and 36 were resistant (IC50 &gt;4 µM). Deleterious mutations in BRCA1 or BRCA2 genes were associated with only a small subset of highly sensitive cell lines, highlighting the presence of other factors able to modulate olaparib responsiveness. Transcriptome analysis revealed DNA repair and proliferation associated genes to be most consistently correlated with olaparib response. Based on these results, a candidate predictive baseline gene expression profile was established. Conclusions: By profiling a large panel of cell lines we have determined that factors in addition to BRCA mutation can be linked with olaparib sensitivity. A list of candidate gene transcripts predictive of in vitro sensitivity to olaparib were identified which may have utility as predictive biomarkers in the clinic. Although primarily linked to mechanisms expected to influence response (DNA repair, cell-cycle checkpoints and proliferation), novel roles were suggested for other pathways such as Aurora A kinase signalling. Analyses also highlighted that some classical HR pathway components may prove to be more robust mRNA markers of pathway activity than others. Studies are already underway to determine whether this baseline transcript tumour profile can be correlated with patient responses to olaparib. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3497.