Mouse p53-deficient cancer models as platforms for obtaining genomic predictors of human cancer clinical outcomes

Mutations in the TP53 gene are very common in human cancers, and are associated with poor clinical outcome. Transgenic mouse models lacking the Trp53 gene or that express mutant Trp53 transgenes produce tumours with malignant features in many organs. We previously showed the transcriptome of a p53-deficient mouse skin carcinoma model to be similar to those of human cancers with TP53 mutations and associated with poor clinical outcomes. This report shows that much of the 682-gene signature of this murine skin carcinoma transcriptome is also present in breast and lung cancer mouse models in which p53 is inhibited. Further, we report validated gene-expression-based tests for predicting the clinical outcome of human breast and lung adenocarcinoma. It was found that human patients with cancer could be stratified based on the similarity of their transcriptome with the mouse skin carcinoma 682-gene signature. The results also provide new targets for the treatment of p53-defective tumours.

Optical detection of mealiness in apples using laser TDRS.

Mealiness is a textural attribute related to an internal fruit disorder that involves quality loss. It is characterised by the combination of abnormal softness of the fruit and absence of free juiciness in the mouth when eaten by the consumer. Recent research concluded with the development of precise instrumental procedure to measure a scale of mealiness based on the combination of several rheological properties and empirical magnitudes. In this line, time-domain laser reflectance spectroscopy (TDRS) is a new medical technology, used to characterise the optical properties of tissues, and to locate affected areas like tumours. Among its advantages compared to more traditional spectroscopic techniques, there is the feasibility to asses simultaneously and independently two optical parameters: the absorption of the light inside the irradiated body, and the scattering of the photons across the tissues, at each wavelength, generating two coefficients (µa, absorption coeff.; and µ's, transport scattering coeff.). If it is assumed that they are related respectively to chemical components and to physical properties of the sample, TDRS can be applied to the quantification of chemicals and the measurement of the rheological properties (i.e. mealiness estimation) at the same time. Using VIS & NIR lasers as light sources, TDRS was applied in this work to Golden Delicious and Cox apples (n=90), conforming several batches of untreated samples and storage-treated (20°C & 95%RH) to promote the development of mealiness. The collected database was clustered into different groups according to their instrumental test values (Barreiro et al, 1998). The optical coefficients were used as explanatory variables when building discriminant analysis functions for mealiness, achieving a classification score above 80% of correctly identified mealy versus fresh apples.