GLI1-induced mammary gland tumours are transplantable and maintain major molecular features

Increased expression of GLI1, the main Hedgehog signalling pathway effector, is related to unfavourable prognosis and progressive disease of certain breast cancer subtypes. We used conditional transgenic mice induced to overexpress GLI1 in the mammary epithelium either alone or in combination with deletion of one Trp53 allele to address the role of elevated GLI1 expression in breast tumour initiation and progression. Induced GLI1 expression facilitates mammary gland tumour formation and this was further increased upon heterozygous deletion of Trp53. The GLI1-induced primary tumours were of different murine molecular subtypes, including Normal-like^Ex, Class8^Ex, Claudin-Low^Ex and Erbb2-like^Ex. The gene expression profiles of some of the tumours correlated well with the PAM50 subtypes for human breast cancer. Whole-exome sequencing revealed somatic mutation profiles with only little overlap between the primary tumours. Orthotopically serially transplanted GLI1-induced tumours maintained the main morphological characteristics of the primary tumours for ≥10 generations. Independent of Trp53 status and molecular subtype, the serially transplanted GLI1-induced tumours were able to grow both in the absence of transgenic GLI1 expression and in the presence of the GLI1 inhibitor GANT61. These data suggest that elevated GLI1 expression has a determinant role in tumour initiation; however, additional genetic events are required for tumour progression.     

Ultrasound-determined fetal subcutaneous tissue thickness for a birthweight prediction model

AIM: The aim of this study was to explore a birthweight prediction model using ultrasound determined tissue thickness (SCTT) parameters. METHODS: We measured routine ultrasonographic biometric parameters and in addition, fetal SCTT in 201 healthy singleton pregnancies. Mid-arm fat and lean mass, mid-thigh fat and lean mass, subscapular fat mass and abdominal fat mass (AFM) were measured in order to calculate a birthweight prediction model. Ultrasound measurements were analyzed using an 'anovarepeated measures model'. The growth rate (beta-slope) of the selected parameters was computed and the correlation coefficient with the birthweight and the Kendall rank correlation tau, were calculated. RESULTS: From the ultrasound determined SCTT parameters, only abdominal circumference (AC), AFM, and MTLM showed a statistically significant trend. The beta-slope of mid-thigh lean mass was excluded since it exhibited significant correlation with the beta-slope of AFM. The final regression model could be calculated as: birthweight (gr.) = intercept +alpha(1)(AFM beta-slope) + alpha(2)(AC beta-slope), where alpha(1), alpha(2) represent regression coefficients. CONCLUSIONS: We provide a graphical birthweight prediction model for clinical practice using conventional and specific ultrasound measurements of fetal subcutaneous tissue thickness. This model is based upon an overall analysis of the ultrasound estimated body components.