Anti-PRKCA (aa 563-672) polyclonal antibody

The dermatofibrosarcoma protuberans family of tumors (DPFT) comprises cutaneous soft tissue neoplasms associated with aberrant PDGFBR signaling, typically through a COL1A1-PDGFB fusion. The aim of the present study was to obtain a better understanding of the chromosomal origin of this fusion and to assess the spectrum of secondary mutations at the chromosome and nucleotide levels. We thus investigated 42 tumor samples from 35 patients using chromosome banding, fluorescence in situ hybridization, single nucleotide polymorphism arrays, and/or massively parallel sequencing (gene panel, whole exome and transcriptome sequencing) methods. We confirmed the age-associated differences in the origin of the COL1A1-PDGFB fusion and could show that it in most cases must arise after DNA synthesis, i.e., in the S or G2 phase of the cell cycle. Whereas there was a non-random pattern of secondary chromosomal rearrangements, single nucleotide variants seem to have little impact on tumor progression. No clear genomic differences between low-grade and high-grade DPFT were found, but the number of chromosomes and chromosomal imbalances as well as the frequency of 9p deletions all tended to be greater among the latter. Gene expression profiling of tumors with COL1A1-PDGFB fusions associated with unbalanced translocations or ring chromosomes identified several transcriptionally up-regulated genes in the amplified regions of chromosomes 17 and 22, including TBX2, PRKCA, MSI2, SOX9, SOX10, and PRAME. (C) 2019 The Authors. Published by Elsevier Inc.

Background: There is growing evidence that emerging malignancies in solid tissues might be kept under control by physical intercellular contacts with normal fibroblasts. Methods: Here we characterize transcriptional landscapes of fibroblasts that confronted cancer cells. We studied four pairs of in vitro and ex vivo fibroblast lines which, within each pair, differed in their capacity to inhibit cancer cells. The natural process was modeled in vitro by confronting the fibroblasts with PC-3 cancer cells. Fibroblast transcriptomes were recorded by Affymetrix microarrays and then investigated using network analysis. Results: The network enrichment analysis allowed us to separate confrontation-and inhibition-specific components of the fibroblast transcriptional response. Confrontation-specific differences were stronger and were characterized by changes in a number of pathways, including Rho, the YAP/TAZ cascade, NF-kB, and TGF-beta signaling, as well as the transcription factor RELA. Inhibition-specific differences were more subtle and characterized by involvement of Rho signaling at the pathway level and by potential individual regulators such as IL6, MAPK8, MAP2K4, PRKCA, JUN, STAT3, and STAT5A. Conclusions: We investigated the interaction between cancer cells and fibroblasts in order to shed light on the potential mechanisms and explain the differential inhibitory capacity of the latter, which enabled both a holistic view on the process and details at the gene/protein level. The combination of our methods pointed to proteins, such as members of the Rho pathway, pro-inflammatory signature and the YAP1/TAZ cascade, that warrant further investigation via tools of experimental perturbation. We also demonstrated functional congruence between the in vitro and ex vivo models. The microarray data are made available via the Gene Expression Omnibus as GSE57199.