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BackgroundAngiosarcoma is an uncommon endothelial malignancy and a highly aggressive soft tissue sarcoma. Due to its infiltrative nature, successful management of localized angiosarcoma is often challenging. Systemic chemotherapy is used in the metastatic setting and occasionally in patients with high-risk localized disease in neoadjuvant or adjuvant settings. However, responses tend to be short-lived and most patients succumb to metastatic disease. Novel therapies are needed for patients with angiosarcomas.MethodsWe performed a retrospective analysis of patients with locally advanced or metastatic angiosarcoma, who were treated with checkpoint inhibitors at our institution. We collected their clinical information and outcome measurements. In one patient with achieved complete response, we analyzed circulating and infiltrating T cells within peripheral blood and tumor tissue.ResultsWe have treated seven angiosarcoma (AS) patients with checkpoint inhibitors either in the context of clinical trials or off label [Pembrolizumab + Axitinib (NCT02636725; n = 1), AGEN1884, a CTLA-4 inhibitor (NCT02694822; n = 2), Pembrolizumab (n = 4)]. Five patients had cutaneous angiosarcoma, one primary breast angiosarcoma and one radiation-associated breast angiosarcoma. At 12 weeks, 5/7 patients (71%) had partial response of their lesions either on imaging and/or clinical exam and two (29%) had progressive disease. 6/7 patients are alive to date and, thus far, 3/7 patients (43%) have progressed (median 3.4 months)- one achieved partial response after pembrolizumab was switched to ongoing Nivolumab/Ipilimumab, one died of progressive disease at 31 weeks (primary breast angiosarcoma) and one was placed on pazopanib. One patient had a complete response (CR) following extended treatment with monotherapy AGEN1884. No patient experienced any ≥ grade 2 toxicities.ConclusionsThis case series underscores the value of targeted immunotherapy in treating angiosarcoma. It also identifies genetic heterogeneity of cutaneous angiosarcomas and discusses specific genetic findings that may explain reported benefits from immunotherapy.

Following publication of the original article [1], the authors have reported that the following sentence "While of the same IgG1 class as ipilimumab, preclinical data suggests this molecule may have enhanced activity against T regulatory cells".

Glioblastoma multiforme (GBM) is the most aggressive brain tumor with poor prognosis to most patients. Immunotherapy of GBM is a potentially beneficial treatment option, whose optimal implementation may depend on familiarity with tumor specific antigens, presented as HLA peptides by the GBM cells. Further, early detection of GBM, such as by a routine blood test, may improve survival, even with the current treatment modalities. This study includes large-scale analyses of the HLA peptidome (immunopeptidome) of the plasma-soluble HLA molecules (sHLA) of 142 plasma samples, and the membranal HLA of GBM tumors of 10 of these patients' tumor samples. Tumor samples were fresh-frozen immediately after surgery and the plasma samples were collected before, and at multiple visits after surgery. In total, this HLA peptidome analysis involved 52 different HLA allotypes and resulted in the identification of more than 35,000 different HLA peptides. Strong correlations were observed in the signal intensities and in the repertoires of identified peptides between the tumors and plasma-soluble HLA peptidomes of the individual patients, whereas low correlations were observed between these HLA peptidomes and the tumors' proteomes. HLA peptides derived from Cancer/Testis Antigens (CTAs) were selected based on their presence among the HLA peptidomes of the patients and absence of expression of their source genes from any healthy and essential human tissues, except from immune-privileged sites. Additionally, peptides were selected as potential biomarkers if their levels in the plasma-sHLA peptidome were significantly reduced after the removal of tumor mass. The CTAs identified among the analyzed HLA peptidomes provide new opportunities for personalized immunotherapy and for early diagnosis of GBM.

Immune checkpoint blockade (ICB) is currently evaluated in patients with glioblastoma (GBM), based on encouraging clinical data in other cancers, and results from studies with the methylcholanthrene-induced GL261 mouse glioma. In this paper, we describe a novel model faithfully recapitulating some key human GBM characteristics, including low mutational load, a factor reported as a prognostic indicator of ICB response. Consistent with this observation, SB28 is completely resistant to ICB, contrasting with treatment sensitivity of the more highly mutated GL261. Moreover, SB28 shows features of a poorly immunogenic tumor, with low MHC-I expression and modest CD8+ T-cell infiltration, suggesting that it may present similar challenges for immunotherapy as human GBM. Based on these key features for immune reactivity, SB28 may represent a treatment-resistant malignancy likely to mirror responses of many human tumors. We therefore propose that SB28 is a particularly suitable model for optimization of GBM immunotherapy.

Background/Aim: Clotting factors promote cancer development. We investigated if coagulation proteins promote proliferation and migration in colorectal cancer (CRC) cell lines and whether their direct inhibitors can attenuate these effects. Materials and Methods: DLD‐1 and SW620 cells were treated with tissue factor (0, 50, 100 and 500 pg/mL ± 10 μg/mL 10H10 [anti‐tissue factor antibody]), thrombin (0.0, 0.1, 1.0 and 10.0 U/mL ± 0.5 μM dabigatran [thrombin inhibitor]) and Factor Xa, FXa (0.0, 0.1, 1.0 and 10.0 U/mL ± 100 ng/mL rivaroxaban [FXa inhibitor]) and their effects on proliferation and migration were quantified using the PrestoBlue® and transwell migration assays, respectively. Results: Thrombin increased proliferation from 48 h treatment compared to its control (48 h 6.57 ± 1.36 u vs. 2.42 ± 0.13 u, p = 0.001, 72 h 9.50 ± 1.54 u vs. 4.50 ± 0.47 u, p = 0.004 and 96 h 10.77 ± 1.72 u vs. 5.57 ± 0.25 u, p = 0.008). This increase in proliferation was attenuated by dabigatran at 72 h (2.23 ± 0.16 u vs. 3.26 ± 0.43 u, p = 0.04). Tissue factor (0 pg/mL 20.7 ± 1.6 cells/view vs. 50 pg/mL 32.4 ± 1.9 cells/view, p = 0.0002), FXa (0.0 U/mL 8.9 ± 1.1 cells/view vs. 10.0 U/mL 17.7 ± 1.7 cells/view, p < 0.0001) and thrombin (0.0 U/mL 8.9 ± 1.3 cells/view vs. 10.0 U/mL 20.2 ± 2.0 cells/view, p < 0.0001) all increased migration compared to their controls. However, their direct inhibitors did not attenuate these increases. Conclusion: Thrombin, FXa and TF all increase migration in CRC in vitro. Thrombin induced increase in proliferation is abrogated by dabigatran. Dabigatran may have potential as an anti‐cancer therapy in CRC. [ABSTRACT FROM AUTHOR]

Malaria caused by Plasmodium falciparum results in approximately 1 million annual deaths worldwide, with young children and pregnant mothers at highest risk. Disease severity might be related to parasite virulence factors, but expression profiling studies of parasites to test this hypothesis have been hindered by extensive sequence variation in putative virulence genes and a preponderance of host RNA in clinical samples. We report here the application of RNA sequencing to clinical isolates of P. falciparum, using not-so-random (NSR) primers to successfully exclude human ribosomal RNA and globin transcripts and enrich for parasite transcripts. Using NSR-seq, we confirmed earlier microarray studies showing upregulation of a distinct subset of genes in parasites infecting pregnant women, including that encoding the well-established pregnancy malaria vaccine candidate var2csa. We also describe a subset of parasite transcripts that distinguished parasites infecting children from those infecting pregnant women and confirmed this observation using quantitative real-time PCR and mass spectrometry proteomic analyses. Based on their putative functional properties, we propose that these proteins could have a role in childhood malaria pathogenesis. Our study provides proof of principle that NSR-seq represents an approach that can be used to study clinical isolates of parasites causing severe malaria syndromes as well other blood-borne pathogens and blood-related diseases., Introduction Malaria is endemic in over 100 countries, and 3.3 billion people are at risk of contracting this disease (1). While only a small percentage of clinical cases are fatal, [...]

Rett syndrome (RTT) is a postnatal neurodevelopmental disorder characterized by the loss of acquired motor and language skills, autistic features, and unusual stereotyped movements. RTT is caused by mutations in the X-linked gene encoding methyl-CpG binding protein 2 (MeCP2). Mutations in MECP2 cause a variety of neurodevelopmental disorders including X-linked mental retardation, psychiatric disorders, and some cases of autism. Although MeCP2 was identified as a methylation-dependent transcriptional repressor, transcriptional profiling of RNAs from mice lacking MeCP2 did not reveal significant gene expression changes, suggesting that MeCP2 does not simply function as a global repressor. Changes in expression of a few genes have been observed, but these alterations do not explain the full spectrum of Rett-like phenotypes, raising the possibility that additional MeCP2 functions play a role in pathogenesis. In this study, we show that MeCP2 interacts with the RNA-binding protein Y box-binding protein 1 and regulates splicing of reporter minigenes. Importantly, we found aberrant alternative splicing patterns in a mouse model of RTT. Thus, we uncovered a previously uncharacterized function of MeCP2 that involves regulation of splicing, in addition to its role as a transcriptional repressor. Rett syndrome | Y box-binding protein 1

In the spring of i993, a previously undescribed disease emerged in the Southwest, killing 10 people during an 8-week period in May and June. Early during an infection, victims experienced [...]

Abstract Background Peptide microarrays offer an enormous potential as a screening tool for peptidomics experiments and have recently seen an increased field of application ranging from immunological studies to systems biology. By allowing the parallel analysis of thousands of peptides in a single run they are suitable for high-throughput settings. Since data characteristics of peptide microarrays differ from DNA oligonucleotide microarrays, computational methods need to be tailored to these specifications to allow a robust and automated data analysis. While follow-up experiments can ensure the specificity of results, sensitivity cannot be recovered in later steps. Providing sensitivity is thus a primary goal of data analysis procedures. To this end we created rapmad (Robust Alignment of Peptide MicroArray Data), a novel computational tool implemented in R. Results We evaluated rapmad in antibody reactivity experiments for several thousand peptide spots and compared it to two existing algorithms for the analysis of peptide microarrays. rapmad displays competitive and superior behavior to existing software solutions. Particularly, it shows substantially improved sensitivity for low intensity settings without sacrificing specificity. It thereby contributes to increasing the effectiveness of high throughput screening experiments. Conclusions rapmad allows the robust and sensitive, automated analysis of high-throughput peptide array data. The rapmad R-package as well as the data sets are available from http://www.tron-mz.de/compmed.

Abstract Background DNA copy number variations occur within populations and aberrations can cause disease. We sought to develop an improved lab-automatable, cost-efficient, accurate platform to profile DNA copy number. Results We developed a sequencing-based assay of nuclear, mitochondrial, and telomeric DNA copy number that draws on the unbiased nature of next-generation sequencing and incorporates techniques developed for RNA expression profiling. To demonstrate this platform, we assayed UMC-11 cells using 5 million 33 nt reads and found tremendous copy number variation, including regions of single and homogeneous deletions and amplifications to 29 copies; 5 times more mitochondria and 4 times less telomeric sequence than a pool of non-diseased, blood-derived DNA; and that UMC-11 was derived from a male individual. Conclusion The described assay outputs absolute copy number, outputs an error estimate (p-value), and is more accurate than array-based platforms at high copy number. The platform enables profiling of mitochondrial levels and telomeric length. The assay is lab-automatable and has a genomic resolution and cost that are tunable based on the number of sequence reads.

Abstract Background mRNA profiling has become an important tool for developing and validating prognostic assays predictive of disease treatment response and outcome. Archives of annotated formalin-fixed paraffin-embedded tissues (FFPET) are available as a potential source for retrospective studies. Methods are needed to profile these FFPET samples that are linked to clinical outcomes to generate hypotheses that could lead to classifiers for clinical applications. Methods We developed a two-color microarray-based profiling platform by optimizing target amplification, experimental design, quality control, and microarray content and applied it to the profiling of FFPET samples. We profiled a set of 50 fresh frozen (FF) breast cancer samples and assigned class labels according to the signature and method by van 't Veer et al 1 and then profiled 50 matched FFPET samples to test how well the FFPET data predicted the class labels. We also compared the sorting power of classifiers derived from FFPET sample data with classifiers derived from data from matched FF samples. Results When a classifier developed with matched FF samples was applied to FFPET data to assign samples to either "good" or "poor" outcome class labels, the classifier was able to assign the FFPET samples to the correct class label with an average error rate = 12% to 16%, respectively, with an Odds Ratio = 36.4 to 60.4, respectively. A classifier derived from FFPET data was able to predict the class label in FFPET samples (leave-one-out cross validation) with an error rate of ~14% (p-value = 3.7 × 10-7). When applied to the matched FF samples, the FFPET-derived classifier was able to assign FF samples to the correct class labels with 96% accuracy. The single misclassification was attributed to poor sample quality, as measured by qPCR on total RNA, which emphasizes the need for sample quality control before profiling. Conclusion We have optimized a platform for expression analyses and have shown that our profiling platform is able to accurately sort FFPET samples into class labels derived from FF classifiers. Furthermore, using this platform, a classifier derived from FFPET samples can reliably provide the same sorting power as a classifier derived from matched FF samples. We anticipate that these techniques could be used to generate hypotheses from archives of FFPET samples, and thus may lead to prognostic and predictive classifiers that could be used, for example, to segregate patients for clinical trial enrollment or to guide patient treatment.

Abstract Background Housekeeping genes (HKG) are constitutively expressed in all tissues while tissue-enriched genes (TEG) are expressed at a much higher level in a single tissue type than in others. HKGs serve as valuable experimental controls in gene and protein expression experiments, while TEGs tend to represent distinct physiological processes and are frequently candidates for biomarkers or drug targets. The genomic features of these two groups of genes expressed in opposing patterns may shed light on the mechanisms by which cells maintain basic and tissue-specific functions. Results Here, we generate gene expression profiles of 42 normal human tissues on custom high-density microarrays to systematically identify 1,522 HKGs and 975 TEGs and compile a small subset of 20 housekeeping genes which are highly expressed in all tissues with lower variance than many commonly used HKGs. Cross-species comparison shows that both the functions and expression patterns of HKGs are conserved. TEGs are enriched with respect to both segmental duplication and copy number variation, while no such enrichment is observed for HKGs, suggesting the high expression of HKGs are not due to high copy numbers. Analysis of genomic and epigenetic features of HKGs and TEGs reveals that the high expression of HKGs across different tissues is associated with decreased nucleosome occupancy at the transcription start site as indicated by enhanced DNase hypersensitivity. Additionally, we systematically and quantitatively demonstrated that the CpG islands' enrichment in HKGs transcription start sites (TSS) and their depletion in TEGs TSS. Histone methylation patterns differ significantly between HKGs and TEGs, suggesting that methylation contributes to the differential expression patterns as well. Conclusion We have compiled a set of high quality HKGs that should provide higher and more consistent expression when used as references in laboratory experiments than currently used HKGs. The comparison of genomic features between HKGs and TEGs shows that HKGs are more conserved than TEGs in terms of functions, expression pattern and polymorphisms. In addition, our results identify chromatin structure and epigenetic features of HKGs and TEGs that are likely to play an important role in regulating their strikingly different expression patterns.

Abstract Background Spontaneous tumors in dog have been demonstrated to share many features with their human counterparts, including relevant molecular targets, histological appearance, genetics, biological behavior and response to conventional treatments. Mammary tumors in dog therefore provide an attractive alternative to more classical mouse models, such as transgenics or xenografts, where the tumour is artificially induced. To assess the extent to which dog tumors represent clinically significant human phenotypes, we performed the first genome-wide comparative analysis of transcriptional changes occurring in mammary tumors of the two species, with particular focus on the molecular pathways involved. Results We analyzed human and dog gene expression data derived from both tumor and normal mammary samples. By analyzing the expression levels of about ten thousand dog/human orthologous genes we observed a significant overlap of genes deregulated in the mammary tumor samples, as compared to their normal counterparts. Pathway analysis of gene expression data revealed a great degree of similarity in the perturbation of many cancer-related pathways, including the 'PI3K/AKT', 'KRAS', 'PTEN', 'WNT-beta catenin' and 'MAPK cascade'. Moreover, we show that the transcriptional relationships between different gene signatures observed in human breast cancer are largely maintained in the canine model, suggesting a close interspecies similarity in the network of cancer signalling circuitries. Conclusion Our data confirm and further strengthen the value of the canine mammary cancer model and open up new perspectives for the evaluation of novel cancer therapeutics and the development of prognostic and diagnostic biomarkers to be used in clinical studies.

Abstract Background Studies have shown that genetic and sex differences strongly influence gene expression in mice. Given the diversity and complexity of transcripts produced by alternative splicing, we sought to use microarrays to establish the extent of variation found in mouse strains and genders. Here, we surveyed the effect of strain and sex on liver gene and exon expression using male and female mice from three different inbred strains. Results 71 liver RNA samples from three mouse strains – DBA/2J, C57BL/6J and C3H/HeJ – were profiled using a custom-designed microarray monitoring exon and exon-junction expression of 1,020 genes representing 9,406 exons. Gene expression was calculated via two different methods, using the 3'-most exon probe ("3' gene expression profiling") and using all probes associated with the gene ("whole-transcript gene expression profiling"), while exon expression was determined using exon probes and flanking junction probes that spanned across the neighboring exons ("exon expression profiling"). Widespread strain and sex influences were detected using a two-way Analysis of Variance (ANOVA) regardless of the profiling method used. However, over 90% of the genes identified in 3' gene expression profiling or whole transcript profiling were identified in exon profiling, along with 75% and 38% more genes, respectively, showing evidence of differential isoform expression. Overall, 55% and 32% of genes, respectively, exhibited strain- and sex-bias differential gene or exon expression. Conclusion Exon expression profiling identifies significantly more variation than both 3' gene expression profiling and whole-transcript gene expression profiling. A large percentage of genes that are not differentially expressed at the gene level demonstrate exon expression variation suggesting an influence of strain and sex on alternative splicing and a need to profile expression changes at sub-gene resolution.