BackgroundFormation of blood vessels requires the concerted regulation of an unknown number of genes in a spatial-, time- and dosage-dependent manner. Determining genes, which drive vascular maturation is crucial for the identification of new therapeutic targets against pathological angiogenesis.Methology/Principal FindingsWe accessed global gene regulation throughout maturation of the chick chorio-allantoic membrane (CAM), a highly vascularized tissue, using pan genomic microarrays. Seven percent of analyzed genes showed a significant change in expression (>2-fold, FDR<5%) with a peak occurring from E7 to E10, when key morphogenetic and angiogenic genes such as BMP4, SMO, HOXA3, EPAS1 and FGFR2 were upregulated, reflecting the state of an activated endothelium. At later stages, a general decrease in gene expression occurs, including genes encoding mitotic factors or angiogenic mediators such as CYR61, EPAS1, MDK and MYC. We identified putative human orthologs for 77% of significantly regulated genes and determined endothelial cell enrichment for 20% of the orthologs in silico. Vascular expression of several genes including ENC1, FSTL1, JAM2, LDB2, LIMS1, PARVB, PDE3A, PRCP, PTRF and ST6GAL1 was demonstrated by in situ hybridization. Up to 9% of the CAM genes were also overexpressed in human organs with related functions, such as placenta and lung or the thyroid. 21–66% of CAM genes enriched in endothelial cells were deregulated in several human cancer types (P<.0001). Interfering with PARVB (encoding parvin, beta) function profoundly changed human endothelial cell shape, motility and tubulogenesis, suggesting an important role of this gene in the angiogenic process.Conclusions/SignificanceOur study underlines the complexity of gene regulation in a highly vascularized organ during development. We identified a restricted number of novel genes enriched in the endothelium of different species and tissues, which may play crucial roles in normal and pathological angiogenesis.

PurposeThe transforming growth factor-beta (TGF-β) signaling pathway is known to play a critical role in promoting tumor growth. Consequently, blocking this pathway has been found to inhibit tumor growth. In order to achieve an optimal anti-tumor effect, however, it remains to be established whether blocking the TGF-β signaling pathway alone is sufficient, or whether the tumor microenvironment plays an additional, possibly synergistic, role.MethodsTo investigate the relevance of blocking TGF-β signaling in tumor cells within the context of their respective tissue microenvironments, we treated a panel of patient-derived xenografts (PDX) with the selective TGF-β receptor kinase inhibitor LY2157299 monohydrate (galunisertib) and assessed both the in vitro and in vivo effects.ResultsGalunisertib was found to inhibit the growth in an in vitro clonogenic assay in 6.3 % (5/79) of the examined PDX. Evaluation of the expression profiles of a number of genes, representing both canonical and non-canonical TGF-β signaling pathways, revealed that most PDX exhibited expression changes affecting TGF-β downstream signaling. Next, we subjected 13 of the PDX to an in vivo assessment and, by doing so, observed distinct response patterns. These results suggest that, next to intrinsic, also extrinsic or microenvironmental factors can affect galunisertib response. pSMAD2 protein expression and TGF-βRI mRNA expression levels were found to correlate with the in vivo galunisertib effects.ConclusionsFrom our data we conclude that intrinsic, tumor-dependent TGF-β signaling does not fully explain the anti-tumor effect of galunisertib. Hence, in vivo xenograft models may be more appropriate than in vitro clonogenic assays to assess the anti-tumor activity of TGF-β inhibitors such as galunisertib.Electronic supplementary materialThe online version of this article (doi:10.1007/s13402-014-0210-8) contains supplementary material, which is available to authorized users.

Experimental tumors raised in rodents represent an important preclinical tool to develop innovative anticancer compounds before clinical testing. Amongst others such models include solid tumors raised in syngeneic fully immunocompetent hosts and tumors spontaneously growing in genetically engineered mice (GEM) and derivate thereof. These model platforms have gained additional value since the manipulation of the immune system to fight cancer has led to tangible benefits for cancer patients. In the current study, we analyzed somatic mutation profiles from whole-exome sequencing (WES) data in a panel of 14 different mouse models covering 6 major cancer types. 4 models were GEM-derived, all other lines were developed by injection of established cell lines into the corresponding mouse strain. In parallel, these models were evaluated for their sensitivity towards checkpoint inhibitors (α-CTLA-4, α-PD-1 or α-PDL-1) in mono- or combined therapy with cytostatic and/or targeted agents.WES achieved an average-of-coverage of 165X in tumor models and normal DNA. A median mutation rate of 34 somatic mutations (m)/MB was detected, ranging from 7 m/MB (GEM derived NSCLC model KP) to 328 m/MB (syngeneic NSCLC line Lewis Lung) in exons. Mutation rates were markedly lower in GEM-derived models as in syngeneic lines (median of 9 vs 43 m/MB). This reflects very well the different underlying carcinogenic mechanism of these two types of models. The cross-comparison of tissue-transplants vs cell lines from GEM-derived model KP revealed that 75% of the mutations found in the primary KP could also be detected in the corresponding cell lines KP1 and KP4. Of note, the mutation count increased 1.3- (KP4) and 2.9-fold (KP1) during cell line establishment. Every model depicted a distinct profile against modulators of the immune system dividing the panel in responders and non-responders. In our hands no significant correlation could be determined between mutational load and sensitivity towards checkpoint inhibition in vivo. This might be related to the fact that the dataset was not broad enough and the number of models per entity was too small, rendering the subtype analysis within the panel not feasible. However, a strong tendency was observed when investigating the colon lines Colon26, CT26 and MC38 showing best response to the combination of PD-1+CTLA-4 inhibitors and in parallel the highest mutation rates (52, 64 and 59 m/MB, respectively) compared to non-responders B16-F10, CloudmanS91, 4T1 and KP1 (23 m/MB on average). Mouse models of cancer are a relevant tool for preclinical studies specifically for immuno-oncology. The molecular characterization of these models will help to optimize their use in drug discovery. They will support the development of innovative drugs and indentification of biomarkers to classify the patient cohort profiting the most from these new compounds. Citation Format: Bruno Zeitouni, Cordula Tschuch, Jason M. Davis, Anne-Lise Peille, Yana Raeva, Manuel Landesfeind, Sheri Barnes, Julia B. Schüler. Whole-exome somatic mutation analysis of mouse cancer models and implications for preclinical immunomodulatory drug development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1840. doi:10.1158/1538-7445.AM2017-1840

Soft tissue sarcomas (STS) are rare, complex tumors with a poor prognosis. The identification of new prognostic biomarkers is needed to improve patient management. Our aim was to determine the methylation status of the 118 CpG sites in the PLAGL1 tumor-suppressor gene P1 CpG island promoter and study the potential prognostic impact of PLAGL1 promoter methylation CpG sites in STS. Training cohorts constituted of 28 undifferentiated sarcomas (US) and 35 leiomyosarcomas (LMS) were studied. PLAGL1 mRNA expression was investigated by microarray analysis and validated by RT-qPCR. Pyrosequencing was used to analyze quantitative methylation of the PLAGL1 promoter. Associations between global promoter or specific CpG site methylation and mRNA expression were evaluated using Pearson’s product moment correlation coefficient. Cox univariate and multivariate proportional hazard models were used to assess the predictive power of CpG site methylation status. Sixteen CpG sites associated with PLAGL1 mRNA expression were identified in US and 6 in LMS. Statistical analyses revealed an association between CpG107 methylation status and both overall and metastasis-free survival in US, which was confirmed in a validation cohort of 37 US. The exhaustive study of P1 PLAGL1 promoter methylation identified a specific CpG site methylation correlated with mRNA expression, which was predictive for both metastasis-free and overall survival and may constitute the first US-specific biomarker. Such a biomarker may be relevant for identifying patients likely to derive greater benefit from treatment.