Tu et al. present a systematic analysis of the tumor microenvironment across 14,837 breast cancers, identifying distinct cellular patterns that predict disease-specific survival independently of genom...

Introduction The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK. Methods Using the Eastern Cancer Registration and Information Centre (ECRIC) dataset, information was collated for 5,694 women who had surgery for invasive breast cancer in East Anglia from 1999 to 2003. Breast cancer mortality models for oestrogen receptor (ER) positive and ER negative tumours were derived from these data using Cox proportional hazards, adjusting for prognostic factors and mode of cancer detection (symptomatic versus screen-detected). An external dataset of 5,468 patients from the West Midlands Cancer Intelligence Unit (WMCIU) was used for validation. Results Differences in overall actual and predicted mortality were <1% at eight years for ECRIC (18.9% vs. 19.0%) and WMCIU (17.5% vs. 18.3%) with area under receiver-operator-characteristic curves (AUC) of 0.81 and 0.79 respectively. Differences in breast cancer specific actual and predicted mortality were <1% at eight years for ECRIC (12.9% vs. 13.5%) and <1.5% at eight years for WMCIU (12.2% vs. 13.6%) with AUC of 0.84 and 0.82 respectively. Model calibration was good for both ER positive and negative models although the ER positive model provided better discrimination (AUC 0.82) than ER negative (AUC 0.75). Conclusions We have developed a prognostication model for early breast cancer based on UK cancer registry data that predicts breast cancer survival following surgery for invasive breast cancer and includes mode of detection for the first time. The model is well calibrated, provides a high degree of discrimination and has been validated in a second UK patient cohort.

New legal duties on universities and colleges come into force, as government delivers Plan for Change to restore integrity of higher education.

In this Perspective, attendees of the Herrenhausen Tumour Heterogeneity meeting discuss the challenges in understanding tumour heterogeneity and propose ways forward for overcoming these hurdles.

Nature Genetics - Frequent somatic mutations and homozygous deletions of the p16 (MTS1) gene in pancreatic adenocarcinoma

Abstract. Pancreatic adenocarcinoma is the fifth leading cause of cancer death in the United States. Mutations in the K-ras oncogene occur in 85% of pancreatic adenocarcinomas and have also been ident...

Find a way of mapping tumours at the molecular and cellular level. This challenge was taken on by teams IMAXT and Rosetta.