Fibroblast activation and abnormal extracellular matrix remodelling as common hallmarks in three cancer-prone genodermatoses.

BACKGROUND: Recessive dystrophic epidermolysis bullosa (RDEB), Kindler syndrome (KS) and xeroderma pigmentosum complementation group C (XPC) are three cancer-prone genodermatoses whose causal genetic mutations cannot fully explain, on their own, the array of associated phenotypic manifestations. Recent evidence highlights the role of the stromal microenvironment in the pathology of these disorders. OBJECTIVES: To investigate, by means of comparative gene expression analysis, the role played by dermal fibroblasts in the pathogenesis of RDEB, KS and XPC. METHODS: We conducted RNA-Seq analysis, which included a thorough examination of the differentially expressed genes, a functional enrichment analysis and a description of affected signalling circuits. Transcriptomic data were validated at the protein level in cell cultures, serum samples and skin biopsies. RESULTS: Interdisease comparisons against control fibroblasts revealed a unifying signature of 186 differentially expressed genes and four signalling pathways in the three genodermatoses. Remarkably, some of the uncovered expression changes suggest a synthetic fibroblast phenotype characterized by the aberrant expression of extracellular matrix (ECM) proteins. Western blot and immunofluorescence in situ analyses validated the RNA-Seq data. In addition, enzyme-linked immunosorbent assay revealed increased circulating levels of periostin in patients with RDEB. CONCLUSIONS: Our results suggest that the different causal genetic defects converge into common changes in gene expression, possibly due to injury-sensitive events. These, in turn, trigger a cascade of reactions involving abnormal ECM deposition and underexpression of antioxidant enzymes. The elucidated expression signature provides new potential biomarkers and common therapeutic targets in RDEB, XPC and KS. What's already known about this topic? Recessive dystrophic epidermolysis bullosa (RDEB), Kindler syndrome (KS) and xeroderma pigmentosum complementation group C (XPC) are three genodermatoses with high predisposition to cancer development. Although their causal genetic mutations mainly affect epithelia, the dermal microenvironment likely contributes to the physiopathology of these disorders. What does this study add? We disclose a large overlapping transcription profile between XPC, KS and RDEB fibroblasts that points towards an activated phenotype with high matrix-synthetic capacity. This common signature seems to be independent of the primary causal deficiency, but reflects an underlying derangement of the extracellular matrix via transforming growth factor-ß signalling activation and oxidative state imbalance. What is the translational message? This study broadens the current knowledge about the pathology of these diseases and highlights new targets and biomarkers for effective therapeutic intervention. It is suggested that high levels of circulating periostin could represent a potential biomarker in RDEB.

Accurate quantification methods to evaluate cervical cord atrophy in multiple sclerosis patients.

OBJECT: Automatic accurate measurement techniques are needed to increase reproducibility in the quantification of cervical cord area (CCA) with magnetic resonance (MR) imaging in the assessment of central nervous system (CNS) atrophy in multiple sclerosis (MS) patients. MATERIALS AND METHODS: Two segmentation methods were implemented: (1) spatial mean brightness level estimation (SMBLE), and (2) partial-volume modeling (PVM). These were evaluated with the inclusion of spinal cord inclination and/or partial-volume-effect corrections. An averaged manually segmented set was considered as reference. Thirty MR studies were used to compare the different methods. A set of 15 MS patients and 15 control subjects within a two-year longitudinal study were used to evaluate cord atrophy with the best method. Statistical evaluation was made by using an intraclass correlation coefficient and Bland-Altman comparisons. RESULTS: Partial-volume modeling with spinal cord inclination correction and partial-volume spinal-cord contour contribution estimation was the most accurate method. The longitudinal test showed a 4% decrease in CCA in MS patients with no significant reduction in control subjects. CONCLUSION: The automatic PVM cord-segmentation approach, taking into consideration the spinal-cord inclination and partial-volume treatment, provides reproducibility and increased accuracy in the evaluation of cord atrophy, allowing the monitoring of changes in MS patients.