Abstract: The present invention provides a method for predicting the treatment response of a human gastroesophageal cancer patient, the method comprising: a) measuring the gene expression of at least 3 of the following genes: CDH1, CDK6, COX2, ELOVL5, GATA4, EGFR, TBCEL, FGF7, CDH17, FNBP1, PIP5K1B, TWIST, CD44, MET, CEACAM1, TOX3, GLIPR2, GSTP1, RON, TMEM136, MYB, BRCA2, FGF1, POU5F1, EPR, DPYD, ABL2 and SH3RF1 in a sample obtained from the gastroesophageal tumour of the patient to obtain a sample gene expression profile of at least said genes; and b) making a prediction of the treatment response and/or prognosis of the patient based on the sample gene expression profile. Also provided are related computer-implemented methods and methods of treatment of gastroesophageal cancer.

Abstract: The present invention provides a medicament for the treatment or prevention of a cell proliferative disorder, the medicament comprising as an active ingredient a compound represented by formula or a pharmaceutically acceptable salt thereof, wherein the medicament is used in such a manner that: (a) said compound or salt is administered twice weekly for 3 weeks, (b) administration of said compound or salt is paused for the following 1 week, and (c) steps (a) and (b) are subsequently repeated at least once.

Abstract: A method of producing a magnetic resonance (MR) image of a region of interest is provided. The method includes the steps of: acquiring an initial MR image of the region of interest, the initial MR image mapping values of an MR-sensitive, physical property at positions over the region; determining a corresponding map of the estimated uncertainties in the values of the MR-sensitive, physical property over the region; and calculating a weighted MR image of the region, the weighted MR image mapping values of a function which combines, at each position of the initial image, the respective value of the MR-sensitive, physical property and the respective estimated uncertainty, the function applying a higher weighting to positions with relatively low estimated uncertainties than to positions with relatively high estimated uncertainties.

Abstract: The present invention provides a method for predicting the treatment response of a human gastroesophageal cancer patient, the method comprising: a) measuring the gene expression of at least 3 of the following genes: CDH1, CDK6, COX2, ELOVL5, GATA4, EGFR, TBCEL, FGF7, CDH17, FNBP1, PIP5K1B, TWIST, CD44, MET, CEACAM1, TOX3, GLIPR2, GSTP1, RON, TMEM136, MYB, BRCA2, FGF1, POU5F1, EPR, DPYD, ABL2 and SH3RF1 in a sample obtained from the gastroesophageal tumour of the patient to obtain a sample gene expression profile of at least said genes; and b) making a prediction of the treatment response and/or prognosis of the patient based on the sample gene expression profile. Also provided are related computer-implemented methods and methods of treatment of gastroesophageal cancer.

Abstract: There is disclosed a method and apparatus for generating data for a two-dimensional image which identifies different classes of property of an imaged subject, this being done by separately rendering volumetric data classified into those different classes and, from all of those separate renderings, choosing one datum for use in the two-dimensional image as an image pixel. This being repeatable for each datum to be used in the two-dimensional image—thereby, for example, to selectively build-up the data for whole of the two-dimensional image as a mixture/combination of different classes of data. The data for the two-dimensional image may be color coded for visually distinguishing data of different classes. Thus when applied to the image enhancement of tissues subjected to contrast agent uptake in patients kinetic information may be incorporated into the volume renderings to enable tissues of different enhancement and kinetic characteristics to be identified as such.