The C2/AC2 genes of monopartite/bipartite geminiviruses of the genera Begomovirus and Curtovirus encode important pathogenicity factors with multiple functions described so far. A novel function of Abutilon mosaic virus (AbMV) AC2 as a replication brake is described, utilizing transgenic plants with dimeric inserts of DNA B or with a reporter construct to express green fluorescent protein (GFP). Their replicational release upon AbMV superinfection or the individual and combined expression of epitope-tagged AbMV AC1, AC2, and AC3 was studied. In addition, the effects were compared in the presence and in the absence of an unrelated tombusvirus suppressor of silencing (P19). The results show that AC2 suppresses replication reproducibly in all assays and that AC3 counteracts this effect. Examination of the topoisomer distribution of supercoiled DNA, which indicates changes in the viral minichromosome structure, did not support any influence of AC2 on transcriptional gene silencing and DNA methylation. The geminiviral AC2 protein has been detected here for the first time in plants. The experiments revealed an extremely low level of AC2, which was slightly increased if constructs with an intron and a hemagglutinin (HA) tag in addition to P19 expression were used. AbMV AC2 properties are discussed with reference to those of other geminiviruses with respect to charge, modification, and size in order to delimit possible reasons for the different behaviors. IMPORTANCEThe (A)C2 genes encode a key pathogenicity factor of begomoviruses and curtoviruses in the plant virus family Geminiviridae. This factor has been implicated in the resistance breaking observed in agricultural cotton production. AC2 is a multifunctional protein involved in transcriptional control, gene silencing, and regulation of basal biosynthesis. Here, a new function of Abutilon mosaic virus AC2 in replication control is added as a feature of this protein in viral multiplication, providing a novel finding on geminiviral molecular biology.
Introduction: Quantitative measurements of transcripts and proteins are key to investigate the basal state of a biological system, while functional proteomics inform about the active state of regulatory networks. Here we describe how the integration of transcriptomics and kinase activity data lead to a better characterization of various cancer models. Methods: We performed RNA sequencing (RNAseq) and kinase activity profiling of 63 Patient Derived Xenograft (PDX) models from six tumor types (Breast, Ovarian, Colon, Melanoma, Lung and Acute Myeloid Leukemia, AML). RNAseq was performed on an Illumina NovaSeq platform. The data was DESeq2-normalized and log2-transformed. Protein Tyrosine Kinase and Serine-Threonine Kinase activities were profiled on PamChip® peptide microarray. To identify the role of kinase signaling related genes we defined a set of signaling-specific genes (n=2932), based on the elements from the reactome signal transduction pathway database (n=2560) and additional kinases (n=372) represented on Pamchip, that was used for further analysis. Integrated analysis of transcriptomics and kinase activity data was performed using Multi Omics Factor Analysis (MOFA). Results: Principal Component Analysis (PCA) of RNAseq data using all included genes or 2932 kinase signaling-specific genes showed clustering of the data according to cancer type, with ovarian cancer showing most heterogeneity, which indicates the importance of kinase signaling in these malignancies. Interestingly, with integrated RNAseq-Kinase activity data all except ovarian cancer show clustering of cancer types on the MOFA Factor 1 - Factor 3. Pathway analysis on the highest ranking 100 genes from principal component 1 of RNAseq data (capturing variation between AML and the other tumor types) resulted in 60 KEGG pathways. Importantly, highest ranking 50 genes and 47 peptides comprising MOFA Factor1 identified 115 significant KEGG pathways, and the statistical score of pathways identified by RNAseq alone was further improved. Finally, significant correlation between gene expression and kinase activity was found for selected PDX model per malignancy. Furthermore, ranking PDX models based on correlation score provided suitable tool to select PDX models for disease or pathway specific research question. Conclusion: Integrating transcriptomics with kinase activity data can be used to confirm transcriptomics findings on a functional level and provides deeper biological insights than transcriptomics alone. We show that integrative analysis leads to more significant and a higher number of enriched pathways. High correlation between two datasets allows for selecting animal models addressing specific research questions. Integrated analysis of transcriptomics and kinase activity data has great potential in improving diagnosis, prognosis and prediction of response to treatment. Citation Format: Dóra Schuller, Rik de Wijn, Dirk Pijnenburg, Tobias Deigner, Julia Schueler, Simar Pal Singh. Integrated analysis of transcriptomics and kinase activity data for better characterization of cancer models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB060.
Plinabulin (Plin) is a new chemical entity and a selective immunomodulating microtubule-targeting agent (SIMBA), which exerts immune-enhancing effects through increasing dendritic cell (DC) maturation and DC-dependent antigen presentation to CD4+ and CD8+ T-Cells. Here we evaluated whether Plin also exerts direct anti-cancer effects against approximately 80 patient derived (PDX) models. Plin was characterized for its ability to inhibit anchorage independent growth and ex vivo colony formation of PDX tumor cells in semi-solid medium. The compound was investigated in PDX models of various cancer types, using a 3D clonogenic assay in a 96-well format. Briefly, tumor cell suspensions were prepared from subcutaneous xenografts in NMRI nu/nu mice and seeded into 96 well ultra-low attachment plates within a layer of semi-solid medium. Plin was added to the assay plate at either day 2 or day 7 and tested at 9 concentrations in half-log increments up to a concentration of 3 µM. Supernatant was exchanged 24 h after dosing and cells were further incubated at 37°C and 7.5 % CO2 up to a total assay time of 8 or 13 days. Colony counts based on image analysis were utilized to evaluate efficacy. Plin inhibited tumor colony formation in a concentration-dependent manner. With Plin treatment beginning 2 days after PDX cell seeding, the most sensitive cancer types were small cell lung cancer (mean absolute IC70 = 0.035 μM; n = 7), bladder cancer (mean absolute IC70 = 0.038 μM; n = 9), and soft tissue sarcoma (mean absolute IC70 = 0.057 μM; n = 10). Melanoma models were observed to be the least sensitive to Plin monotherapy, with a mean absolute IC70 of 1.105 μM (n = 19). With Plin treatment beginning 7 days after PDX cell seeding, based on absolute IC70 values, 9 out of 68 tumor models were sensitive towards plinabulin. The most sensitive histotypes were gastric cancer (Asian, mean abs. IC70 = 0.319 µM, n = 3), small cell lung cancer (mean abs. IC70 = 0.385 µM, n = 7; 3 below 50 nM), osteosarcoma (mean abs. IC70 = 0.624 µM, n = 3), and central nervous system cancer (mean abs. IC70 = 1.521 µM, n = 6). Overall, the most responsive models based on IC70 were the small cell lung cancer models 2156 (abs. IC70 = 0.015 µM), 1129 (abs. IC70 = 0.032 µM) and 650 (abs. IC70 = 0.032 µM), and the osteosarcoma model 1186 (abs. IC70 = 0.027 µM). Soft tissue sarcoma models (n = 8), Her2-enriched breast cancer models (n = 6), melanoma models (n = 9), bladder cancer models (n = 6), and gastric cancer models (Caucasian, n = 3) were observed to be the least sensitive cancer types with a mean IC70 value > 3 µM. In conclusion, using patient-derived tumor models in a 3D clonogenic assay, SCLC tumor types were the most sensitive to Plin. These results provide mechanistic support for the preliminary positive results recently reported with Plin in combination with Nivolumab and Ipilimumab in SCLC patients (Malhotra ASCO 2021). Citation Format: George K. Lloyd, James Tonra, Claudia Goettlich, Tobias Deigner, Ramon Mohanlal, Lan Huang. Distinct and significant anti-cancer efficacy of plinabulin in patient derived small cell lung cancer (SCLC) 3D soft agar clonogenic assays [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P082.
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