Anti-AP2A1 (aa 824-923) polyclonal antibody

Despite its modest capacity for regeneration, peripheral nervous system injury often results in significant long-term disability. Supplementing peripheral nervous system injury with autologous Schwann cells (SCs) may serve to rejuvenate the postinjury environment to enhance regeneration and ultimately improve functional outcomes. However, human nerve-derived SC (hN-SC) collection procedures require invasive surgical resection. Here, we describe the characterization of SCs from adult human skin (hSk-SCs) of four male donors ranging between 27 and 46 years old. Within five weeks of isolating and culturing adherent mixed skin cells, we were able to obtain 3-5 million purified SCs. We found that hSk-SCs appeared transcriptionally indistinguishable from hN-SCs with both populations exhibiting expression of SC genes including: SOX10, SOX9, AP2A1, CDH19, EGR1, ETV5, PAX3, SOX2, CX32, DHH, NECL4, NFATC4, POU3F1, S100B, and YY1. Phenotypic analysis of hSk-SCs and hN-SCs cultures revealed highly enriched populations of SCs indicated by the high percentage of NES vertical bar ve, SOX10(vertical bar ve), s100(vertical bar ve) and p75(vertical bar ve) cells, as well as the expression of a battery of other SC-associated proteins (PAX3, CDH19, ETV5, SOX2, POU3F1, S100B, EGR2, and YY1). We further show that both hSk-SCs and hN-SCs are capable of promoting axonal growth to similar degrees and that a subset of both associate with regenerating axons and form myelin following transplantation into the injured mouse sciatic nerve. Interestingly, although the majority of both hSk-SCs and hN-SCs maintained SOX10 immunoreactivity following transplant, only a subset of each activated the promyelinating factor, POU3F1, and were able to myelinate. Taken together, we demonstrate that adult hSk-SCs are genetically and phenotypically indistinguishable to hN-SCs.

Background: The immune system is a key player in fighting cancer. Thus, we sought to identify a molecular 'immune response signature' indicating the presence of epithelial ovarian cancer (EOC) and to combine this with a serum protein biomarker panel to increase the specificity and sensitivity for earlier detection of EOC. Methods: Comparing the expression of 32,000 genes in a leukocytes fraction from 44 EOC patients and 19 controls, three uncorrelated shrunken centroid models were selected, comprised of 7, 14, and 6 genes. A second selection step using RT-qPCR data and significance analysis of microarrays yielded 13 genes (AP2A1, B4GALT1, C1orf63, CCR2, CFP, DIS3, NEAT1, NOXA1, OSM, PAPOLG, PRIC285, ZNF419, and BC037918) which were finally used in 343 samples (90 healthy, six cystadenoma, eight low malignant potential tumor, 19 FIGO I/II, and 220 FIGO III/IV EOC patients). Using new 65 controls and 224 EOC patients (thereof 14 FIGO I/II) the abundances of six plasma proteins (MIF, prolactin, CA125, leptin, osteopondin, and IGF2) was determined and used in combination with the expression values from the 13 genes for diagnosis of EOC. Results: Combined diagnostic models using either each five gene expression and plasma protein abundance values or 13 gene expression and six plasma protein abundance values can discriminate controls from patients with EOC with Receiver Operator Characteristics Area Under the Curve values of 0.998 and bootstrap .632+ validated classification errors of 3.1% and 2.8%, respectively. The sensitivities were 97.8% and 95.6%, respectively, at a set specificity of 99.6%. Conclusions: The combination of gene expression and plasma protein based blood derived biomarkers in one diagnostic model increases the sensitivity and the specificity significantly. Such a diagnostic test may allow earlier diagnosis of epithelial ovarian cancer.