Metastatic breast cancer (MBC) is considered incurable; therefore, palliative treatment is the only option. The biologic heterogeneity of the disease is reflected in its somewhat unpredictable clinical behavior. The presence of circulating tumor cells (CTCs) in patients with MBC about to start a new line of treatment has been shown to predict progression-free and overall survival. This prognostic value is independent of the line of therapy (eg, first or second line). Moreover, a multivariate analysis has shown the prognostic value of CTCs to be superior to that of site of metastasis, type of therapy, and length of time to recurrence after definitive primary surgery. These data suggest that the presence of CTCs may be used to modify the staging system for advanced disease. Larger studies are needed to confirm these data and evaluate the use of CTC detection in monitoring treatment and furthering our understanding of breast cancer biology when combined with other diagnostic technologies.

https://www.nejm.org/doi/pdf/10.1056/NEJMoa040766

Circulating Tumor Cells, Disease Progression, and Survival in Metastatic Breast Cancer

Proteomics, the large-scale analysis of proteins, will contribute greatly to our understanding of gene function in the post-genomic era. Proteomics can be divided into three main areas: (1) protein micro-characterization for large-scale identification of proteins and their post-translational modifications; (2) 'differential display' proteomics for comparison of protein levels with potential application in a wide range of diseases; and (3) studies of protein-protein interactions using techniques such as mass spectrometry or the yeast two-hybrid system. Because it is often difficult to predict the function of a protein based on homology to other proteins or even their three-dimensional structure, determination of components of a protein complex or of a cellular structure is central in functional analysis. This aspect of proteomic studies is perhaps the area of greatest promise. After the revolution in molecular biology exemplified by the ease of cloning by DNA methods, proteomics will add to our understanding of the biochemistry of proteins, processes and pathways for years to come.

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Proteomics to study genes and genomes

Molecular characterization of the tumor microenvironment in breast cancer

▪ Abstract A decade after the discovery of electrospray and matrix-assisted laser desorption ionization (MALDI), methods that finally allowed gentle ionization of large biomolecules, mass spectrometry has become a powerful tool in protein analysis and the key technology in the emerging field of proteomics. The success of mass spectrometry is driven both by innovative instrumentation designs, especially those operating on the time-of-flight or ion-trapping principles, and by large-scale biochemical strategies, which use mass spectrometry to detect the isolated proteins. Any human protein can now be identified directly from genome databases on the basis of minimal data derived by mass spectrometry. As has already happened in genomics, increased automation of sample handling, analysis, and the interpretation of results will generate an avalanche of qualitative and quantitative proteomic data. Protein-protein interactions can be analyzed directly by precipitation of a tagged bait followed by mass spectrometri...

Analysis of proteins and proteomes by mass spectrometry

Protein arrays are described for screening of molecular markers and pathway targets in patient matched human tissue during disease progression. In contrast to previous protein arrays that immobilize the probe, our reverse phase protein array immobilizes the whole repertoire of patient proteins that represent the state of individual tissue cell populations undergoing disease transitions. A high degree of sensitivity, precision and linearity was achieved, making it possible to quantify the phosphorylated status of signal proteins in human tissue cell subpopulations. Using this novel protein microarray we have longitudinally analysed the state of pro-survival checkpoint proteins at the microscopic transition stage from patient matched histologically normal prostate epithelium to prostate intraepithelial neoplasia (PIN) and then to invasive prostate cancer. Cancer progression was associated with increased phosphorylation of Akt (P<0.04), suppression of apoptosis pathways (P<0.03), as well as decreased phosphorylation of ERK (P<0.01). At the transition from histologically normal epithelium to PIN we observed a statistically significant surge in phosphorylated Akt (P<0.03) and a concomitant suppression of downstream apoptosis pathways which proceeds the transition into invasive carcinoma.

Reverse phase protein microarrays which capture disease progression show activation of pro-survival pathways at the cancer invasion front

Normal human luminal and myoepithelial breast cells separately purified from a set of 10 reduction mammoplasties by using a double antibody magnetic affinity cell sorting and Dynabead immunomagnetic technique were used in two-dimensional gel proteome studies. A total of 43,302 proteins were detected across the 20 samples, and a master image for each cell type comprising a total of 1,738 unique proteins was derived. Differential analysis identified 170 proteins that were elevated 2-fold or more between the two breast cell types, and 51 of these were annotated by tandem mass spectrometry. Muscle-specific enzyme isoforms and contractile intermediate filaments including tropomyosin and smooth muscle (SM22) alpha protein were detected in the myoepithelial cells, and a large number of cytokeratin subclasses and isoforms characteristic of luminal cells were detected in this cell type. A further 134 nondifferentially regulated proteins were also annotated from the two breast cell types, making this the most extensive study to date of the protein expression map of the normal human breast and the basis for future studies of purified breast cancer cells.

Proteomic definition of normal human luminal and myoepithelial breast cells purified from reduction mammoplasties.

In the current study, the protein expression maps (PEMs) of 26 breast cancer cell lines and three cell lines derived from normal breast or benign disease tissue were visualised by high resolution two-dimensional gel electrophoresis. Analysis of this data was performed with ChiClust and ChiMap, two analytical bioinformatics tools that are described here. These tools are designed to facilitate recognition of specific patterns shared by two or more (a series) PEMs. Both tools use PEMs that were matched by an image analysis program and locally written programs to create a match table that is saved in an object relational database. The ChiClust tool uses clustering and subclustering methods to extract statistically significant protein expression patterns from a large series of PEMs. The ChiMap tool calculates a differential value (either as percentage change or a fold change) and represents these graphically. All such differentials or just those identified using ChiClust can be submitted to ChiMap. These methods are not dependent on any particular commercial image analysis program, and the whole software package gives an integrated procedure for the comparison and analysis of a series of PEMs. The ChiClust tool was used here to order the breast cell lines into groups according to biological characteristics including morphology in vitro and tumour forming ability in vivo. ChiMap was then used to highlight eight major protein feature-changes detected between breast cancer cell lines that either do or do not proliferate in nude mice. Mass spectrometry was used to identify the proteins. The possible role of these proteins in cancer is discussed.

Luc Brusten

Papers

Proteomic definition of normal human luminal and myoepithelial breast cells purified from reduction mammoplasties.

Cluster analysis of an extensive human breast cancer cell line protein expression map database.