The single-cell pathology landscape of breast cancer

Many genes and signalling pathways controlling cell proliferation, death and differentiation, as well as genomic integrity, are involved in cancer development. New techniques, such as serial analysis of gene expression and cDNA microarrays, have enabled measurement of the expression of thousands of genes in a single experiment, revealing many new, potentially important cancer genes. These genome screening tools can comprehensively survey one tumor at a time; however, analysis of hundreds of specimens from patients in different stages of disease is needed to establish the diagnostic, prognostic and therapeutic importance of each of the emerging cancer gene candidates. Here we have developed an array-based high-throughput technique that facilitates gene expression and copy number surveys of very large numbers of tumors. As many as 1000 cylindrical tissue biopsies from individual tumors can be distributed in a single tumor tissue microarray. Sections of the microarray provide targets for parallel in situ detection of DNA, RNA and protein targets in each specimen on the array, and consecutive sections allow the rapid analysis of hundreds of molecular markers in the same set of specimens. Our detection of six gene amplifications as well as p53 and estrogen receptor expression in breast cancer demonstrates the power of this technique for defining new subgroups of tumors.

The 14th St Gallen International Breast Cancer Conference (2015) reviewed new evidence on locoregional and systemic therapies for early breast cancer. This manuscript presents news and progress since the 2013 meeting, provides expert opinion on almost 200 questions posed to Consensus Panel members, and summarizes treatment-oriented classification of subgroups and treatment recommendations.

Single-cell, spatially resolved ‘omics analysis of tissues is poised to transform biomedical research and clinical practice. We have developed an open-source, computational multiplex image cytometry analysis toolbox (miCAT) to enable interactive, quantitative, and comprehensive exploration of individual cell phenotypes, cell-to-cell interactions, microenvironments, and morphological structures within intact tissues. We highlight the unique abilities of miCAT by analysis of highly multiplexed mass cytometry images of human breast cancer tissues.