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R. Pithadia



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    P1.06 - Poster Session 1 - Prognostic and Predictive Biomarkers (ID 161)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Biology
    • Presentations: 1
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      P1.06-051 - Development of a serum biomarker panel predicting clinical outcome of chemotherapy with pemetrexed in patients with NSCLC (ID 3355)

      09:30 - 16:30  |  Author(s): R. Pithadia

      • Abstract

      Background
      Pemetrexed disodium is a novel folate antimetabolite approved for first-line treatment in combination with a platinum doublet, for second-line treatment as a single agent and, more recently, as maintenance treatment after first-line chemotherapy in patients with non-squamous non-small cell lung cancer (NSCLC). Circulating factors associated with folate metabolism and/or phenotypic plasticity (e.g. the epithelial-to-mesenchymal transition (EMT)) may have predictive value in selecting advanced NSCLC for first-line pemetrexed. The objective of this study was to identify serum biomarkers capable of predicting improved outcomes for pemetrexed added to first-line platinum based chemotherapy relative to standard platinum doublet.

      Methods
      Pretreatment serum from a total of 72 patients with non-squamous stage IV NSCLC was evaluated with 76 biomarkers using Luminex immunobead assays. Patients were treated either with platinum combined with pemetrexed (P: n= 26) or with other agents (O; n=51) at the discretion of the treating physician. Patients were evaluated for disease progression using RECIST criteria. Biomarker data was processed using Ingenuity Pathway Analysis (IPA) Suite to identify interactions with folate metabolism. Cox Proportional Hazard (PH) regression model was used to assess the association between H-scores and progression-free/overall survival (PFS/OS) distribution estimated by the Kaplan-Meier method. PH interaction model was used to capture the differential effects of the biomarkers on the O vs. P treatment groups.

      Results
      Univariate PH regression analysis identified 10 biomarkers that were negatively associated (p<0.05) with progression-free survival (PFS) in either the O (sTNF-RI, sTNF-RII, Tenascin C, sIL-2Rα, spg130, sIL-6R, CA-125, and CA 19-9) or the P subgroups (total PSA, amphiregulin). Four other biomarkers (MMP-1, MMP-2, sVEGFR2, and PDGF-B) were all significantly (p<0.05) positively associated with PFS in the P group. Similarly, seven biomarkers were strongly negatively associated (p<0.01) with overall survival (OS) in the O group, including osteopontin, sTNF-RI, sTNF-RII, CA 15-3, sIL-2Rα, CYFRA 21.1, and IL-6; whereas the P group possessed both negative (osteopontin and amphiregulin) and positive (sVEGFR2, MMP-1, MMP-2, and sRAGE) associations (P<0.05) with OS. In our assessment of differential association with PFS, we found two serum biomarkers (PSA (total) and amphiregulin) with significant positive interaction terms, thus indicating differentially increased hazard of progression in the P group with higher level of the biomarker. MMP-1, HGF, and Tenascin C, sVEGFR2 were similarly noted to have significant negative interaction terms for PFS. Evaluations of the differential associations with respect to OS, demonstrated five biomarkers with significant (MMP-1, MMP-2, sVEGFR2, sTNF-RI, and Tenascin C; p≤0.05) and three strongly associated (osteopontin, HGF, s-IL-6R; p≤0.01) negative interaction terms, demonstrating a decreased hazard of progression in the P group.

      Conclusion
      Serum biomarkers with potential predictive (PFS, OS) value for selecting patients most likely to benefit from pemetrexed have been identified. Pathway analysis demonstrates interactions of biomarker candidates identified with folate metabolism. This study is currently being expanded with additional front-line patients (P=90; n=56) from our institutional archives to further evaluate their potential predictive value.