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Primary cicatricial alopecias are characterized by dysregulation of shared gene expression pathways

ABSTRACT: Primary cicatricial alopecias are characterized by dysregulation of shared gene expression pathways

PROVIDER: PRJNA772282 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR16473800.fastq.gz	Fastqsanger.gz
	SRR16473801.fastq.gz	Fastqsanger.gz
	SRR16473715_1.fastq.gz	Fastqsanger.gz
	SRR16473715_2.fastq.gz	Fastqsanger.gz
	SRR16473716_1.fastq.gz	Fastqsanger.gz

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Primary cicatricial alopecias are characterized by dysregulation of shared gene expression pathways

Project description:To investigate the molecular signatures of the different sub-types of Primary cicatricial alopecia (PCA). We performed high-throughput RNA-sequencing on scalp biopsies of PCA patient. We developed gene expression-based signatures, trained into machine-learning based predictive models and pathways associated with dysregulated gene expression. We performed morphological and cytokine analysis to define the immune cell populations found in PCA sub types. Using bulk RNA sequencing, we identified a common PCA gene signature that was shared between LPP, FFA, and CCCA which revealed a significant over-representation of mast cell signature genes, as well as down regulation of cholesterogenic pathways and up regulation of fibrosis and immune cell signaling genes. Thw Immunohistological analyses revealed an increased presence of mast cells in PCAs lesions.

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Primary cicatricial alopecias are characterized by dysregulation of shared gene expression pathways.

Project description:The primary forms of cicatricial (scarring) alopecia (PCA) are a group of inflammatory, irreversible hair loss disorders characterized by immune cell infiltrates targeting hair follicles (HFs). Lichen planopilaris (LPP), frontal fibrosing alopecia (FFA), and centrifugal cicatricial alopecia (CCCA) are among the main subtypes of PCAs. The pathogenesis of the different types of PCAs are poorly understood, and current treatment regimens yield inconsistent and unsatisfactory results. We performed high-throughput RNA-sequencing on scalp biopsies of a large cohort PCA patients to develop gene expression-based signatures, trained into machine-learning-based predictive models and pathways associated with dysregulated gene expression. We performed morphological and cytokine analysis to define the immune cell populations found in PCA subtypes. We identified a common PCA gene signature that was shared between LPP, FFA, and CCCA, which revealed a significant over-representation of mast cell (MC) genes, as well as downregulation of cholesterogenic pathways and upregulation of fibrosis and immune signaling genes. Immunohistological analyses revealed an increased presence of MCs in PCAs lesions. Our gene expression analyses revealed common pathways associated with PCAs, with a strong association with MCs. The indistinguishable differences in gene expression profiles and immune cell signatures between LPP, FFA, and CCCA suggest that similar treatment regimens may be effective in treating these irreversible forms of hair loss.

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