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Background The pathogenesis of Cushing’s disease (CD) is still not adequately understood despite the identification of somatic driver mutations in USP8, BRAF and USP48. In this multiomics study, we combined RNA sequencing (RNA-seq) with Sanger sequencing to depict transcriptional dysregulation under different gene mutation backgrounds. Furthermore, we evaluated the potential of achaete-scute complex homolog 1 (ASCL1), a pioneer transcription factor, as a novel therapeutic target for treatment of CD and its possible downstream pathway. Methods RNA-seq was adopted to investigate the gene expression profile of CD, and Sanger sequencing was adopted to detect gene mutations. Bioinformatics analysis was used to depict transcriptional dysregulation under different gene mutation backgrounds. The function of ASCL1 in hormone secretion, cell proliferation and apoptosis were studied in vitro. The effectiveness of a ASCL1 inhibitor was evaluated in primary CD cells, and the clinical relevance of ASCL1 was examined in 68 patients with CD. RNA-seq in AtT-20 cells upon Ascl1 knockdown combined with published ChIp-seq data and dual luciferase assays were used to explore downstream pathways. Results ASCL1 was exclusively overexpressed in USP8-mutant and wild type tumors. Ascl1 promoted adrenocorticotrophin hormone overproduction and tumorigenesis and directly regulated Pomc in AtT-20 cells. A ASCL1 inhibitor presented promising efficacy in both AtT-20 and primary CD cells. ASCL1 overexpression was associated with a larger tumor volume and higher adrenocorticotrophin secretion in patients with CD. Conclusion Our findings help to clarify the pathogenesis of CD and suggest that ASCL1 is a potential therapeutic target for treatment of CD.

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Today, in the multimedia encoding technology, fractal image coding is an effective coding method without resolution. The effectiveness is because of the high compressing ratio of fractal image coding. But the computational complexity of this coding method is so high that it needs long encoding time. In this paper, a novel fast fractal coding method is constructed to decrease the coding time by the capture of primary additional error values. This method is a universal algorithm, which is independent of image types. First, we abstract the additional error values from classic image coding. Then, we present a method to abstract the primary error values with a given rule of weight. Moreover, the encoding and decoding processes are reformed to store the primary additional error values. Finally, experimental results shows the improved fractal image coding method has higher compressing ratio and better effectiveness (signal to noise ratio) than the classic algorithm.