—  AMERICAN SOCIETY FOR INVESTIGATIVE PATHOLOGY   —

Preneoplastic Breast Disease and the Promise of Proteomic Analysis


Roy A. Jensen
Vanderbilt University Medical Center
Nashville, TN


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 [1]. 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 patients.

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 [2]. 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 [3].

There has been important progress regarding the utility of gene expression analysis in providing improved prognostic information. Two groups, one from Stanford [4] and the second from the Netherlands Cancer Institute [5] 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 [6]. 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 [7]. 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.

References

  1. Malkin HM. Out of the Mist. Berkeley, California: Vesalius Books; 1993.
  2. 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.
  3. Wick MR, Mills SE. Evaluation of surgical margins in anatomic pathology: technical, conceptual, and clinical considerations. Semin Diagn Pathol 2002;19(4):207-18.
  4. 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.
  5. 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.
  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.
  7. 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.