Abstract

1119 Background: There are limited options for selecting an optimal treatment regimen for ABC patients (pts). DRIT is a platform technology that provides a profile of a patient's tumor's sensitivity or resistance to commonly used chemotherapeutic, hormonal, or biological agents as a basis for individualized anticancer treatment approach. DRIT may allow physicians to choose more effective drug treatments before initiation of therapy and improve the efficacy and toxicity profile of cancer therapies. Methods: DRIT analysis is based on fluorescent dye-labeled monoclonal antibody staining followed by computer-assisted microscopy to quantitatively measure expression levels in tumor sections. The interpretation of DRI expression levels results in classification of tumors as sensitive or resistant to treatment with a mechanistically related drug. This study utilized the following drug/DRI combinations: hormonal therapy/estrogen receptor; capecitabine/thymidylate synthase; docetaxel, paclitaxel, abraxane/β-tubulin isoform III; trastuzumab/HER-2; gemcitabine/ribonucleotide reductase. DRIT was performed on the tumor tissue of consented study participants with ABC who were then deemed to be sensitive or resistant to a given agent/agents. We then analyzed retrospectively clinical treatment outcomes (clinically sensitive to therapy defined as-stable disease+partial response+complete response or resistant to therapy-no response to therapy) for 91 treatment interventions in 71 pts with the DRIT tissue data. Results: We found that the DRIT sensitivity was 0.99, with specificity of 0.59, positive predictive value of 0.88, negative predictive value of 0.93 and overall predictive value of 88% for treatment outcomes for this cohort of ABC pts. Conclusions: This study suggests that DRIT can provide more accurate prediction of treatment outcomes for ABC pts than the standard of care approach and therefore has a potential to avoid unnecessary ineffective drug treatment exposure. Prospective study in ABC pts is currently conducted at the UMGCC. [Table: see text]

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