RESUMEN
Trans-differentiation from an adenocarcinoma to a small cell neuroendocrine state is associated with therapy resistance in multiple cancer types. To gain insight into the underlying molecular events of the trans-differentiation, we perform a multi-omics time course analysis of a pan-small cell neuroendocrine cancer model (termed PARCB), a forward genetic transformation using human prostate basal cells and identify a shared developmental, arc-like, and entropy-high trajectory among all transformation model replicates. Further mapping with single cell resolution reveals two distinct lineages defined by mutually exclusive expression of ASCL1 or ASCL2. Temporal regulation by groups of transcription factors across developmental stages reveals that cellular reprogramming precedes the induction of neuronal programs. TFAP4 and ASCL1/2 feedback are identified as potential regulators of ASCL1 and ASCL2 expression. Our study provides temporal transcriptional patterns and uncovers pan-tissue parallels between prostate and lung cancers, as well as connections to normal neuroendocrine cell states.
Asunto(s)
Carcinoma de Células Pequeñas , Neoplasias Pulmonares , Neoplasias de la Próstata , Carcinoma Pulmonar de Células Pequeñas , Masculino , Humanos , Neoplasias Pulmonares/genética , Carcinoma de Células Pequeñas/genética , Factores de Transcripción/genética , Neoplasias de la Próstata/genética , Neoplasias de la Próstata/patología , Transdiferenciación Celular/genética , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/genética , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/metabolismo , Regulación Neoplásica de la Expresión Génica , Línea Celular Tumoral , Carcinoma Pulmonar de Células Pequeñas/genéticaRESUMEN
To investigate the relationship between geometrical changes of retinal vessels and diabetic peripheral neuropathy (DPN), and to determine the effectiveness of retinal vascular geometry analysis and vibration perception threshold (VPT) for DPN assessment. Type 2 diabetes patients (n = 242) were categorized by stage of DPN. VPT and fundus photography was performed to obtain retinal vascular geometry parameters. The risk factors for DPN and the correlation between DPN stages were analyzed. The efficiency of the retinal vascular geometric parameters obtained with VPT as a diagnostic tool for DPN was examined. Stages of DPN showed a linear correlation with VPT (r = 0.818), central retinal vein equivalent (CRVE) (r = 0.716), and fractal dimension arterioles (DFa) (r = - 0.769). VPT, CRVE, DFa, and fractal dimension veins (DFv) showed high sensitivity (80%, 55%, 82%, and 67%, respectively) and specificity (92%, 93%, 82%, and 80%, respectively) for DPN diagnosis. Good agreement was observed between combined use of geometric parameters (CRVE, DFa and DFv) and VPT (Kappa value 0.430). The detection rate of DPN with combined use of geometric parameters of retinal vessels (64.88%) was significantly higher than that with use of VPT (47.52%). Retinal vascular geometry changes demonstrated significant correlation with DPN severity. VPT, CRVE, DFa, and DFv may provide insights for understanding DPN.