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Receptor Polymorphisms and Gene Clusters May Help Identify Individual Patients Most Likely to Benefit From Immunotherapy

Receptor Polymorphisms and Gene Clusters May Help Identify Individual Patients Most Likely to Benefit From Immunotherapy

PHILADELPHIA-Developing methods to determine which patients will benefit most from immunotherapy will allow physicians to better tailor therapy for individual patients. Such methods for predicting response to treatment will be particularly useful in indolent relapsing diseases such as follicular lymphoma, and may reduce the number of treatment regimens that patients receive during the course of their disease. Two presentations by investigators at Stanford University in California identified methods that may make it possible to predict patient responses to antibody therapy.[1,2] Fc Gamma RIIIa Polymorphisms Wen-Kai Weng, MD, PhD, Ronald Levy, MD, and colleagues investigated immunoglobulin G Fc receptor Fc gamma RIIIa polymorphisms in patients with relapsed follicular non- Hodgkin's lymphoma treated with rituximab (Rituxan) (ASH abstract 1368).[1] Rituximab antitumor effects are mediated, in part, by antibody- dependent cellular cytotoxicity. Recently, the Fc gamma RIIIa position 158 valine/valine genotype was demonstrated to correlate with improved clinical response to rituximab compared with valine/phenylalanine or phenylalanine/phenylalanine (phenylalanine carriers) in patients with previously untreated follicular lymphoma.[3] The Stanford University team sought to test this hypothesis in patients with relapsed follicular lymphoma. Patient demographics and baseline characteristics are detailed in Table 1.[1] Dr. Levy reported that an analysis of 60 patients revealed that Fc gamma RIIIa position 158 genotype did not influence rituximab response rate 1 to 3 months after treatment in patients with previously treated follicular lymphoma (see Table 2).[1] However, 12 months after rituximab treatment, patients with position 158 valine/valine genotype had a higher response rate (62%) than the phenylalanine carriers (23%; P = .039). Furthermore, the progression-free survival at 2 years was 41% for patients with position 158 valine/valine genotype vs 16% for phenylalanine carriers, although the difference did not achieve statistical significance. From these results, the investigators confirmed the predictive value of Fc gamma RIIIa polymorphisms in patients with previously treated follicular lymphoma and suggested that the efficacy of rituximab may be improved if its binding affinity for Fc gamma RIIIa can be enhanced. Gene Expression Patterns In addition to antibody-dependent cellular cytotoxicity, other proposed mechanisms of action for rituximab activity in CD20-expressing lymphomas are complement-mediated lysis and induction of apoptosis. In an effort to further define the mechanism of action of rituximab in patients with follicular lymphoma and to develop a method for predicting responses to rituximab, Sean Bohen, MD, PhD, and colleagues examined the expression of more than 20,000 genes by microarray (ASH abstract 1222).[2,4] An analysis of 16 patients revealed two clusters of gene expression patterns: patients who did not respond to rituximab displayed expression patterns more similar to normal tonsil and spleen lymphoid tissue, whereas patients responded to rituximab clustered in a second group (P = .002). Specifically, the genes identified in the nonresponders were those that play a role in cellular immunity. The authors speculated that differences in these genes suggest that the nonresponders may have a reduced capacity for eliciting an antilymphoma immune response. Further analysis of 24 patient samples identified more than 100 genes expressed at significantly different levels in rituximab responders vs nonresponders. More than one-third of these genes were involved in the cellular immune response. These genes and other cellular immunity genes were then compared with those known to be up-regulated by macrophages activated in vitro by bacterial pathogens. Once again, rituximab responders and nonresponders clustered into groups based on the expression of 136 macrophage activation genes (P < .013). These two analyses of receptor polymorphisms and gene clusters that correlate with responses with rituximab suggest that screening before therapy would allow the selection of patients who are most likely to benefit from immunotherapy. Furthermore, these analyses provide important new information regarding the mechanisms of action of antibody therapy and identify potential targets for antibody modification that may improve the number and intensity of patient responses to antibody therapy.

References

1. Weng WK, Levy R. Analysis of IgG Fc receptor Fc gamma IIIa polymorphism in relapsed follicular non- Hodgkin’s lymphoma patients treated with rituximab (abstract 1368). Blood 100:353a, 2002.
2. Bohen SP, Troyanskaya O, Alter O, et al: Predicting rituximab response of follicular lymphoma using cDNA microarray analysis (abstract 1222). Blood 100:316a, 2002.
3. Cartron G, Dacheux L, Salles G, et al: Therapeutic activity of humanized anti-CD20 monoclonal antibody and polymorphism in IgG Fc receptor Fc gamma RIIIa gene. Blood 99:754-758, 2002.
4. Bohen SP, Troyanskaya OG, Alter O, et al: Variations in gene expression patterns in follicular lymphoma and the response to rituximab. Proc Natl Acad Sci USA 100:1926-1930, 2003.
 
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