Abstract

Traditionally, immunology has considered a meaningful antibody response to be marked by large amounts of high-affinity antibodies reactive with the specific inciting antigen; the detection of small amounts of low-affinity antibodies binding to seemingly unrelated antigens has been considered to be beneath the threshold of immunological meaning. A systems-biology approach to immunology, however, suggests that large-scale patterns in the antibody repertoire might also reflect the functional state of the immune system. To investigate such global patterns of antibodies, we have used an antigen-microarray device combined with informatic analysis. Here we asked whether antibody-repertoire patterns might reflect the state of an implanted tumor. We studied the serum antibodies of inbred C57BL/6 mice before and after implantation of syngeneic 3LL tumor cells of either metastatic or non-metastatic clones. We analyzed patterns of IgG and IgM autoantibodies binding to over 300 self-antigens arrayed on slides using support vector machines and genetic algorithm techniques. We now report that antibody patterns, but not single antibodies, were informative: 1) mice, even before tumor implantation, manifest both individual and common patterns of low-titer natural autoantibodies; 2) the patterns of these autoantibodies respond to the growth of the tumor cells, and can distinguish between metastatic and non-metastatic tumor clones; and 3) curative tumor resection induces dynamic changes in these low-titer autoantibody patterns. The informative patterns included autoantibodies binding to self-molecules not known to be tumor-associated antigens (including insulin, DNA, myosin, fibrinogen) as well as to known tumor-associated antigens (including p53, cytokeratin, carbonic anhydrases, tyrosinase). Thus, low-titer autoantibodies that are not the direct products of tumor-specific immunization can still generate an immune biomarker of the body-tumor interaction. System-wide profiling of autoantibody repertoires can be informative.

Highlights

  • Immunologists traditionally have focused their studies on strong immune reactivates to defined antigens induced by immunization or by disease

  • We have extended the study of global antibody patterns by exploiting microarray technology to devise antigen chips capable of measuring the patterns of antibody reactivity, low-level as well as high-level, to many hundreds of defined antigens simultaneously [1,3,12]. bioinformatics analysis of natural autoantibody reactivities makes it possible to characterize common patterns of reactivity, for example, in mice patterns predictive of a future autoimmune disease [1]

  • We have reported the presence of common patterns of IgM and IgA autoantibodies in the cord bloods of healthy newborn humans, apparently arising from self-reactive immune activation in utero [3]

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Summary

Introduction

Immunologists traditionally have focused their studies on strong immune reactivates to defined antigens induced by immunization or by disease. In contrast to the discrete immune specificity borne by individual T-cell or antibody-mediated immune reactions, recent attention has been directed to global patterns formed by collectives of low-titer antibody reactivities as indicative of immunesystem state in both health and disease [1,2,3,4,5,6]. These systemsimmunology studies of patterns of antibodies are directed to analyzing the general immune state of the body [7,8]; their aim is not focused exclusively on high-titer, demonstrably specific one-to-one antigenantibody binding reactions. Attention has been directed to cancer biomarker discovery using proteomic and immunomic techniques [15,16]

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