Kinome profiling of myxoid liposarcoma reveals NF-kappaB-pathway kinase activity and Casein Kinase II inhibition as a potential treatment option

<p>Abstract</p> <p>Background</p> <p>Myxoid liposarcoma is a relatively common malignant soft tissue tumor, characterized by a (12;16) translocation resulting in a FUS-DDIT3 fusion gene playing a pivotal role in its tumorigenesis. Treatment options in patients with inoperable or metastatic myxoid liposarcoma are relatively poor though being developed and new hope is growing.</p> <p>Results</p> <p>Using kinome profiling and subsequent pathway analysis in two cell lines and four primary cultures of myxoid liposarcomas, all of which demonstrated a FUS-DDIT3 fusion gene including one new fusion type, we aimed at identifying new molecular targets for systemic treatment. Protein phosphorylation by activated kinases was verified by Western Blot and cell viability was measured before and after treatment of the myxoid liposarcoma cells with kinase inhibitors. We found kinases associated with the atypical nuclear factor-kappaB and Src pathways to be the most active in myxoid liposarcoma. Inhibition of Src by the small molecule tyrosine kinase inhibitor dasatinib showed only a mild effect on cell viability of myxoid liposarcoma cells. In contrast, inhibition of the nuclear factor-kappaB pathway, which is regulated by the FUS-DDIT3 fusion product, in myxoid liposarcoma cells using casein kinase 2 inhibitor 4,5,6,7-tetrabromobenzotriazole (TBB) showed a significant decrease in cell viability, decreased phosphorylation of nuclear factor-kappaB pathway proteins, and caspase 3 mediated apoptosis. Combination of dasatinib and TBB showed an enhanced effect.</p> <p>Conclusion</p> <p>Kinases associated with activation of the atypical nuclear factor-kappaB and the Src pathways are the most active in myxoid liposarcoma <it>in vitro </it>and inhibition of nuclear factor-kappaB pathway activation by inhibiting casein kinase 2 using TBB, of which the effect is enhanced by Src inhibition using dasatinib, offers new potential therapeutic strategies for myxoid liposarcoma patients with advanced disease.</p

Histological response to radiotherapy is an early event in myxoid liposarcoma

Myxoid liposarcoma; Personalized medicine; RadiotherapyLiposarcoma mixoide; Medicina personalizada; RadioterapiaLiposarcoma mixoide; Medicina personalitzada; RadioteràpiaCompared to other sarcomas, myxoid liposarcoma (MLS) is exceptionally sensitive to radiation therapy, but the underlying mechanism remains unknown. The objective was to assess the tissue-based changes in MLS during and after neoadjuvant radiotherapy in 26 patients of the DOREMY trial. Morphological assessment was performed on biopsies pre-treatment, after 8 fractions, 16 factions, and after surgical resection and included percentage of viable tumor cells, hyalinization, necrosis, and fatty maturation. Furthermore, immunohistochemistry was performed for apoptosis (cleaved caspase-3), anti-apoptosis (Bcl-2), activity of mTOR signaling (phospho-S6), hypoxia (CAIX), proliferation (Ki67), inflammation (CD45 and CD68), and microvessel density (CD34 Chalkley count). A pronounced reduction in vital tumor cells was observed early with a drop to 32.5% (median) tumor cells (IQR 10–93.8%) after 8 fractions. This decreased further to 10% (IQR 5–30%) after 16 fractions and 7.5% (IQR 5–15%) in the surgical specimen. All but one patient had an excellent response with < 50% remaining tumor cells. Inversely, treatment response was mainly observed as hyalinization and less often as fatty maturation. Additionally, a decrease of inflammatory cells was noticed especially during the first eight fractions. Microvessel density remained stable over time. Immunohistochemical markers for apoptosis, anti-apoptosis, activity of mTOR signaling, proliferation, and hypoxia did not show any marked changes within the remaining tumor cells during and after radiotherapy. As a modest dose of neoadjuvant radiotherapy induces profound tissue changes in MLS, mainly during the first 8 fractions, current findings might suggest that in a carefully selected patient population further deintensification of radiotherapy might be explored

No preclinical rationale for IGF1R directed therapy in chondrosarcoma of bone

Background: Chondrosarcoma is a malignant cartilage forming bone tumour for which no effective systemic treatment is available. Previous studies illustrate the need for a better understanding of the role of the IGF pathway in chondrosarcoma to determine if it can be a target for therapy, which was therefore explored in this study. Methods: Expression of mediators of IGF1R signalling and phosphorylation status of IRS1 was determined in chondrosarcoma cell lines by qRT-PCR and western blot. The effect of activation and inhibition of IGF1R signalling on downstream targets was assessed by western blot. Ten chondrosarcoma cell lines were treated with OSI-906 (IGF1R and IR dual inhibitor) after which cell proliferation and migration were determined by a viability assay and the xCELLigence system, respectively. In addition, four chondrosarcoma cell lines were treated with a combination of doxorubicin and OSI-906. By immunohistochemistry, IGF1R expression levels were determined in tissue microarrays of 187 cartilage tumours and ten paraffin embedded cell lines. Results: Mediators of IGF1R signalling are heterogeneously expressed and phosphorylated IRS1 was detected in 67 % of the tested chondrosarcoma cell lines, suggesting that IGF1R signalling is active in a subset of chondrosarcoma cell lines. In the cell lines with phosphorylated IRS1, inhibition of IGF1R signalling decreased phosphorylated Akt levels and increased IGF1R expression, but it did not influence MAPK or S6 activity. In line with these findings, treatment with IGF1R/IR inhibitors did not impact proliferation or migration in any of the chondrosarcoma cell lines, even upon stimulation with IGF1. Although synergistic effects of IGF1R/IR inhibition with doxorubicin are described for other cancers, our results demonstrate that this was not the case for chondrosarcoma. In addition, we found minimal IGF1R expression in primary tumours in contrast to the high expression detected in chondrosarcoma cell lines, even if both were derived from the same tumour, suggesting that in vitro culturing upregulates IGF1R expression. Conclusions: The results from this study indicate that the IGF pathway is not essential for chondrosarcoma growth, migration or chemoresistance. Furthermore, IGF1R is only minimally expressed in chondrosarcoma primary tumours. Therefore, the IGF pathway is not expected to be an effective therapeutic target for chondrosarcoma of bone. Electronic supplementary material The online version of this article (doi:10.1186/s12885-016-2522-8) contains supplementary material, which is available to authorized users

Frequent mutated B2M, EZH2, IRF8, and TNFRSF14 in primary bone diffuse large B-cell lymphoma reflect a GCB phenotype

Primary bone diffuse large B-cell lymphoma (PB-DLBCL) is a rare extranodal lymphoma subtype. This retrospective study elucidates the currently unknown genetic background of a large clinically well-annotated cohort of DLBCL with osseous localizations (O-DLBCL), including PB-DLBCL. A total of 103 patients with O-DLBCL were included and compared with 63 (extra)nodal non-osseous (NO)-DLBCLs with germinal center B-cell phenotype (NO-DLBCL-GCB). Cell-of-origin was determined by immunohistochemistry and gene-expression profiling (GEP) using (extended)-NanoString/Lymph2Cx analysis. Mutational profiles were identified with targeted next-generation deep sequencing, including 52 B-cell lymphoma-relevant genes. O-DLBCLs, including 34 PB-DLBCLs, were predominantly classified as GCB phenotype based on immunohistochemistry (74%) and NanoString analysis (88%). Unsupervised hierarchical clustering of an extended-NanoString/Lymph2Cx revealed significantly different GEP clusters for PB-DLBCL as opposed to NO-DLBCL-GCB (P < .001). Expression levels of 23 genes of 2 different targeted GEP panels indicated a centrocyte-like phenotype for PB-DLBCL, whereas NO-DLBCL-GCB exhibited a centroblast-like constitution. PB-DLBCL had significantly more frequent mutations in four GCB-associated genes (ie, B2M, EZH2, IRF8, TNFRSF14) compared with NO-DLBCL-GCB (P = .031, P = .010, P = .047, and P = .003, respectively). PB-DLBCL, with its corresponding specific mutational profile, was significantly associated with a superior survival compared with equivalent Ann Arbor limited-stage I/II NO-DLBCL-GCB (P = .016). This study is the first to show that PB-DLBCL is characterized by a GCB phenotype, with a centrocyte-like GEP pattern and a GCB-associated mutational profile (both involved in immune surveillance) and a favorable prognosis. These novel biology-associated features provide evidence that PB-DLBCL represents a distinct extranodal DLBCL entity, and its specific mutational landscape offers potential for targeted therapies (eg, EZH2 inhibitors)

High-grade sarcoma diagnosis and prognosis: Biomarker discovery by mass spectrometry imaging

Molecular tumour pathology - and tumour geneticsMTG

Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas.

Based on morphology it is often challenging to distinguish between the many different soft tissue sarcoma subtypes. Moreover, outcome of disease is highly variable even between patients with the same disease. Machine learning on transcriptome sequencing data could be a valuable new tool to understand differences between and within entities. Here we used machine learning analysis to identify novel diagnostic and prognostic markers and therapeutic targets for soft tissue sarcomas. Gene expression data was used from the Cancer Genome Atlas, the Genotype-Tissue Expression project and the French Sarcoma Group. We identified three groups of tumors that overlap in their molecular profiles as seen with unsupervised t-Distributed Stochastic Neighbor Embedding clustering and a deep neural network. The three groups corresponded to subtypes that are morphologically overlapping. Using a random forest algorithm, we identified novel diagnostic markers for soft tissue sarcoma that distinguished between synovial sarcoma and MPNST, and that we validated using qRT-PCR in an independent series. Next, we identified prognostic genes that are strong predictors of disease outcome when used in a k-nearest neighbor algorithm. The prognostic genes were further validated in expression data from the French Sarcoma Group. One of these, HMMR, was validated in an independent series of leiomyosarcomas using immunohistochemistry on tissue micro array as a prognostic gene for disease-free interval. Furthermore, reconstruction of regulatory networks combined with data from the Connectivity Map showed, amongst others, that HDAC inhibitors could be a potential effective therapy for multiple soft tissue sarcoma subtypes. A viability assay with two HDAC inhibitors confirmed that both leiomyosarcoma and synovial sarcoma are sensitive to HDAC inhibition. In this study we identified novel diagnostic markers, prognostic markers and therapeutic leads from multiple soft tissue sarcoma gene expression datasets. Thus, machine learning algorithms are powerful new tools to improve our understanding of rare tumor entities