Preneoplastic Breast Disease and the Promise of Proteomic Analysis
Roy A. Jensen
Vanderbilt University Medical Center
What impact will the application of modern techniques of molecular biology, the sequencing of the
human genome, and the development of proteomics have on diagnostic pathology? Will "labs on a chip"
replace traditional methods of histopathologic analysis? The short answer is not any time soon, but
these revolutionary advances cannot be ignored and indeed should be embraced if we are to increase our
understanding of molecular pathogenesis, improve patient care, and enhance the quality of information
that we can provide to our clinical colleagues by optimizing disease classification.
To understand the role that pathology will play in this process it is helpful to review the role that
diagnostic pathology has traditionally and currently plays in patient care. There is little doubt that
he development of modern medicine had its basis in the rise of diagnostic pathology in the mid-nineteenth
century . Until we understood how to recognize specific patterns of disease, understand their
pathogenesis, and develop classification schemes we had little or no hope of developing appropriate
therapies for the vast majority of disorders that afflict the human condition. In addition, pathology
has always played a critical role in establishing the prognosis of particular diseases and in predicting
which forms of therapy might be most effective. Unfortunately, while routine diagnostic pathology
represents the gold standard for evaluating prognosis and predicting the response to therapy for groups
of like patients, the application of these techniques often falls short in evaluating individual
Thus, the promise of adding molecular techniques to our armamentarium is that we will be able to
greatly increase our predictive and prognostic power and enable individual tailoring of therapy for
cancer patients . Ideally, this would occur on an ongoing basis such that at any particularly point
the therapeutic susceptibilities of the predominant subclone within the tumor could be identified and
appropriate therapy could be administered. Later, as resistant subclones emerge the patient could be
given alternative treatments selected for their efficacy against the new set of markers. In this model
cancer would be viewed as a chronic disease with continual monitoring necessary to stay even or one step
ahead of emergent clones.
A major question that remains is whether these techniques will be integrated into traditional
pathology or will these developments mean that pathology as traditionally practiced will become
obsolete? For solid tumors I see no diminution in role of pathology as long as surgical therapy
continues to be the primary and most effect form of treatment. With rare exceptions, surgical
extirpation of cancer prior to its metastatic spread provides the best chance of cure, and local control
often represents an important aspect of achieving this end. Routine histopathologic examination has
consistently been shown to be an excellent predictor of negative disease margins and while there have
been some attempts to examine margin status via molecular methods, no currently available molecular
method demonstrates sufficient specificity or sensitivity to challenge its supremacy in this regard .
There has been important progress regarding the utility of gene expression analysis in providing
improved prognostic information. Two groups, one from Stanford  and the second from the Netherlands
Cancer Institute  have published important papers regarding the molecular analysis of breast tumors
that would suggest that gene expression data can identify important prognostic subgroups not previously
recognized by traditional means of assessment. Interestingly, the molecular subgroups identified by the
different investigative groups do not appear to correspond exactly and the genes determined to be
critical in defining these different subset groups do not perfectly coincide. Thus, the exact pattern of
gene expression that best defines the most useful prognostic subgroups has yet to be defined. For
example in the Netherlands study, it should be noted that despite the improvement in selecting
appropriate groups for treatment in comparison to traditional means, ~10 % of patients who should
have received adjuvant chemotherapy would not have received it had that choice been made on the basis of
their tumor's molecular profile. In addition, nearly 30% of patients who would have been selected for
chemotherapy by molecular methods did not need it. Still, this represents a considerable improvement
over current means of selection whereby 70% of patients that would have been selected for chemotherapy by
traditional means in the Netherlands study wound up not needing it.
While the application of microarrays to measure gene expression in tumors to derive prognostic
information is in its early adolescence, the application of protemics to this end is in the blastula
stage. However, recent technological advances in protemics suggest that this line of investigation
offers tremendous potential for advancing our understanding of molecular pathogenesis, particularly in
regards to the role of protein modification and pathway elucidation . Although a number of exciting
techniques are under development this presentation will focus on the potential of matrix-assisted laser
desorption ionization time of flight (MALDI-TOF MS) mass spectroscopy to impact diagnostic pathology.
MALDI-TOF MS is a highly specific and sensitive analysis technique that is capable of detecting
attamoles of specific molecular species in complex mixtures. In addition, MALDI-TOF MS is capable of
analyzing very small clusters of cells and in conjunction with laser capture microdissection can analyze
single cells without any requirement to amplify the material . MALDI-TOF MS can also detect specific
protein modifications such as phosphorylation, glycosylation, and myristylation. The assays are
relatively fast, the reagents are either reusable or extremely cheap, and perhaps most importantly,
spatial and anatomic relationships are maintained in the analysis so that so that the complex interaction
between tumor cells and their environment can be studied at the molecular level.
The potential for this type of analysis is particularly exciting for imaging mass spectroscopy in
which specific molecular species can be mapped throughout a tumor and adjacent normal tissue. While this
capability is routinely available for individual proteins via immunohistochemistry, imaging mass
spectroscopy offers the potential for extending this analysis to all molecule species present in the
tumor simultaneously regardless of the availability of specific antibodies. This technology is
potentially extremely powerful and when coupled with the rapid advances in informatics offers the
capacity for entirely new ways of analyzing tumors. For example, with continued advances in optics,
processor speed, and knowledge of molecular pathogenesis it should be possible to determine the proteomic
profile of a tumor within the time frame currently utilized for frozen sections. With this information
it should then be possible to decide the optimal course of therapy for that particular tumor before the
patient even leaves the operating room. As a demonstration of the power inherent in this technology we
have chosen to analyze tumor samples for estrogen receptor expression via mass spectroscopy and compare
the results to those obtained via standard immunhistochemistry.
Estrogen receptor expression is a powerful predictive factor for response to tamoxifen and other
endocrine therapies and is the most widely utilized predictive factor in the selection of therapy for
breast cancer. While there is no current need for an accelerated determination of estrogen receptor
expression, this presentation will illustrate the potential for this technology and provide insight into
how mass spectroscopy and bioinformatics might be integrated to assess the selection of therapy by
examining the expression/activation state of literally hundreds if not thousands of individual markers.
- Malkin HM. Out of the Mist. Berkeley, California: Vesalius Books; 1993.
- Khan J, Bittner ML, Chen Y, Meltzer PS, Trent JM. DNA microarray technology: the anticipated impact on the study of human disease. Biochim Biophys Acta 1999;1423(2):M17-28.
- Wick MR, Mills SE. Evaluation of surgical margins in anatomic pathology: technical, conceptual, and clinical considerations. Semin Diagn Pathol 2002;19(4):207-18.
- Perou CM, Jeffrey SS, van de Rijn M, et al. Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc Natl Acad Sci U S A 1999;96(16):9212-7.
- van 't Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415(6871):530-6.
- Chaurand P, Schwartz SA, Caprioli RM. Imaging mass spectrometry: a new tool to investigate the spatial organization of peptides and proteins in mammalian tissue sections. Curr Opin Chem Biol 2002;6(5):676-81.
- Xu BJ, Caprioli RM, Sanders ME, Jensen RA. Direct analysis of laser capture microdissected cells by MALDI mass spectrometry. J Am Soc Mass Spectrom 2002;13(11):1292-7.