A whole-genome sequence and transcriptome perspective on HER2-positive breast cancers.

HER2-positive breast cancer has long proven to be a clinically distinct class of breast cancers for which several targeted therapies are now available. However, resistance to the treatment associated with specific gene expressions or mutations has been observed, revealing the underlying diversity of these cancers. Therefore, understanding the full extent of the HER2-positive disease heterogeneity still remains challenging. Here we carry out an in-depth genomic characterization of 64 HER2-positive breast tumour genomes that exhibit four subgroups, based on the expression data, with distinctive genomic features in terms of somatic mutations, copy-number changes or structural variations. The results suggest that, despite being clinically defined by a specific gene amplification, HER2-positive tumours melt into the whole luminal-basal breast cancer spectrum rather than standing apart. The results also lead to a refined ERBB2 amplicon of 106 kb and show that several cases of amplifications are compatible with a breakage-fusion-bridge mechanism

A Machine Learning Approach to Waterbody Segmentation in Thermal Infrared Imagery in Support of Tactical Wildfire Mapping

Wildfire research is working toward near real-time tactical wildfire mapping through the application of computer vision techniques to airborne thermal infrared (IR) imagery. One issue hindering automation is the potential for waterbodies to be marked as areas of combustion due to their relative warmth in nighttime thermal imagery. Segmentation and masking of waterbodies could help resolve this issue, but the reliance on data captured exclusively in the thermal IR and the presence of real areas of combustion in some of the images introduces unique challenges. This study explores the use of the random forest (RF) classifier for the segmentation of waterbodies in thermal IR images containing a heterogenous wildfire. Features for classification are generated through the application of contextual and textural filters, as well as normalization techniques. The classifier’s outputs are compared against static GIS-based data on waterbody extent as well as the outputs of two unsupervised segmentation techniques, based on entropy and variance, respectively. Our results show that the RF classifier achieves very high balanced accuracy (>98.6%) for thermal imagery with and without wildfire pixels, with an overall F1 score of 0.98. The RF method surpassed the accuracy of all others tested, even with heterogenous training sets as small as 20 images. In addition to assisting automation of wildfire mapping, the efficiency and accuracy of this approach to segmentation can facilitate the creation of larger training data sets, which are necessary for invoking more complex deep learning approaches

Differential histone modifications mark mouse imprinting control regions during spermatogenesis

Only some imprinting control regions (ICRs) acquire their DNA methylation in the male germ line. These imprints are protected against the global demethylation of the sperm genome following fertilisation, and are maintained throughout development. We find that in somatic cells and tissues, DNA methylation at these ICRs is associated with histone H4-lysine-20 and H3-lysine-9 trimethylation. The unmethylated allele, in contrast, has H3-lysine-4 dimethylation and H3 acetylation. These differential modifications are also detected at maternally methylated ICRs, and could be involved in the somatic maintenance of imprints. To explore whether the post-fertilisation protection of imprints relates to events during spermatogenesis, we assayed chromatin at stages preceding the global histone-to-protamine exchange. At these stages, H3-lysine-4 methylation and H3 acetylation are enriched at maternally methylated ICRs, but are absent at paternally methylated ICRs. H4 acetylation is enriched at all regions analysed. Thus, paternally and maternally methylated ICRs carry different histone modifications during the stages preceding the global histone-to-protamine exchange. These differences could influence the way ICRs are assembled into specific structures in late spermatogenesis, and may thus influence events after fertilisation