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(Chest. 2005;128:1069-1071.)
© 2005 American College of Chest Physicians

Patterns of Melanoma Antigen-A Expression in Lung Cancer Patients

Timothy P. Hutchinson, PhD

University of Adelaide Adelaide, SA, Australia

Correspondence to: Timothy P. Hutchinson, PhD, Centre for Automotive Safety Research, University of Adelaide, Adelaide, SA 5005, Australia; e-mail: paul{at}casr.adelaide.edu.au

To the Editor:

Table 1 , part (a) lists the combinations of melanoma antigen (MAGE) markers giving positive results occurring in 37 lung cancer patients (information from Tables 1 and 2 of the study by Mecklenburg et al1). Unless we are sure the different markers are independent of each other, the dependencies among them may be of interest.


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Table 1.. Data and Interpretation as Ordered Lists*

 
In one sense, there seems to be a lot of variability, as any of the five markers might be the sole positive one. On the other hand, of the 32 possible patterns of positive and negative markers, only 12 were observed. These viewpoints can be reconciled by listing the results as combinations of negative results (Table 1, part [b]), and reasoning as follows. One simple form of dependence is a "negative-implies-negative" rule (ie, a single ordered list such that if there is a negative result for any marker, there is also a negative result for all markers to its left). Such a list cannot be constructed for this data set. Both BE and DE occur as combinations of negative results. Now suppose there are two ordered lists of the markers (Table 1, part [c]), that each patient has a position in both lists, and that markers to the left of the patient in either list have negative results. This pair of lists generates all except one of the observed patterns, the exception being that one patient has negative results for C and D.

It is chance that the lists are the reverse of each other.

As a concise description of the data, Table 1 (part c) is not unique. The positioning of E is ambiguous, as it could be first in the first list and last in the second list.

An alternative analysis might start from part (a) of Table 1 and employ a "positive-implies-positive" rule. This is not successful for this data set, as so many of the markers occur as the only positive result, in one patient or another.

If the lists in part (c) of Table 1 are taken seriously, they might be considered a theory and interpreted as resiliencies of the different MAGE markers, with a patient’s positions reflecting the strengths of the two systems for suppressing them. I have used the same method of summarizing data in the context of which patients do or do not succeed at various neuropsychological tests,2 and which chemicals do or do not kill various microorganisms.3 Interpretations could be made in terms of systems damaged to lesser or greater degrees, with a rule either saying both components are needed or saying one component is sufficient for a certain outcome. The method has disadvantages, admittedly. It is silent about degrees of response, dealing only with a 0/1 dichotomy, and there is no random element.

Reservations About the Data
Treating Tables 1 and 2 of the study by Mecklenburg et al1 as a single data set is questionable. They refer to induced sputum and BAL fluid, respectively. Moreover, the level of MAGE expression is reported as being much higher in Table 2. It is arguable that marker C should have been excluded from consideration, since it is a conflation of MAGE-3 and MAGE-6 (see page 253 of the article by Kufer et al4). Repeated observations from the same patient are not available, so allowance cannot be made for possible errors.

I hope that part (c) of Table 1 is thought-provoking despite the preceding paragraph, and that the proposed method of summarizing patterns of expression may be useful with other data sets.

Footnotes

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (e-mail: www.chestjournal.org/misc/reprints.shtml).

References

  1. Mecklenberg, I, Stratakis, DF, Huber, RM, et al (2004) Detection of melanoma antigen-A expression in sputum and bronchial lavage fluid of patients with lung cancer. Chest 125,164S-166S
  2. Hutchinson, TP A notation for the structure of cognitive processes, with application to patterns of verb-processing impairment. Lang Cognitive Proc 2003;18,165-174[CrossRef]
  3. Hutchinson, TP Analysis of datasets showing which compounds kill which organisms: inferring two systems. Eur J Med Chem 2004;39,107-111[Medline]
  4. Kufer, P, Zippelius, A, Lutterbuse, R, et al Heterogeneous expression of MAGE-A genes in occult disseminated tumor cells: a novel multimarker reverse transcription-polymerase chain reaction for diagnosis of micrometastatic disease. Cancer Res 2002;62,251-261[Abstract/Free Full Text]

Ingo Mecklenburg, MD and Peter Kufer, MD

{ddagger} Ludwig-Maximilians-University Munich, Germany

Correspondence to: Ingo Mecklenburg, MD, Institut für Immunologie, Goethestrasse 31, 80336 Munich, Germany; e-mail: ingo.mecklenburg{at}med.uni-muenchen.de

To the Editor:

We thank Dr. Hutchinson for his detailed statistical review of our described melanoma antigen (MAGE) expression profiles in sputum and bronchial fluid of lung cancer patients.1 We definitely agree to his notion that different MAGE expression patterns need further attention, as the distinct expression of individual markers might have particular prognostic impact or may be used for further subclassification of disease.

However, comprehensive analysis of large cohorts of patients with different types of cancers have not yielded any transparent order of distribution yet. Moreover, the additional quantitative assessment of MAGE expression by real-time polymerase chain reaction displays a rather arbitrary gene activity of individual markers in different types of tumors (unpublished data), and the sensitivity threshold of the utilized assay markedly affects the formation of the expression pattern.

The biological function and the physiologic role of individual cancer/testis antigens is still obscure23; therefore, we are currently tracking prospective data for a correlation of the course of disease with the MAGE expression profile in primary tumor tissue, venous blood, and bone marrow aspirates of cancer patients in several cohorts. Subsequently, a detailed statistical assessment of the data sets has to be done, and the proposed method for summarizing the patterns of MAGE expression may be helpful for the generation of a later decision model. However, far more clinical experience is needed with this approach, and quantitative data will have to be included in the final analysis as relevant carrier of additional information.

References

  1. Mecklenburg, I, Stratakis, DF, Huber, RM, et al Detection of melanoma antigen-A expression in sputum and bronchial lavage fluid of patients with lung cancer. Chest 2004;125,164S-166S
  2. Ohman Forslund, K, Nordqvist, K The melanoma antigen genes: any clues to their functions in normal tissues? Exp Cell Res 2001;265,185-194[CrossRef][ISI][Medline]
  3. Xiao, J, Chen, HS Biological functions of melanoma-associated antigens. World J Gastroenterol 2004;10,1849-1853[Medline]




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