American Association for Cancer Research
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Supplemental Tables 1 - 3 and Figures 1 - 2 from Pharmacogenomic Modeling of Circulating Tumor and Invasive Cells for Prediction of Chemotherapy Response and Resistance in Pancreatic Cancer

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journal contribution
posted on 2023-03-31, 18:25 authored by Kenneth H. Yu, Mark Ricigliano, Manuel Hidalgo, Ghassan K. Abou-Alfa, Maeve A. Lowery, Leonard B. Saltz, Joseph F. Crotty, Kristen Gary, Brandon Cooper, Rena Lapidus, Mariola Sadowska, Eileen M. O'Reilly

Supplementary Table 1: List of genes used for PGx modeling Supplementary Table 2: Correlation of PGx model prediction in tumor tissue to CTICs, soft tissue sarcoma. Supplementary Table 3. Normalized Enrichment Scores for chemotherapeutic agents modeled in three pancreatic cancer derived xenografts, referenced in (Figure 2). Supplementary Figure 1. Correlation of PGx model prediction in tumor tissue to CTICs, soft tissue sarcoma. Supplementary Figure 2. Correlation of Treatment Score to (A) PFS and (B) OS.



Purpose: Despite a challenging prognosis, modern cytotoxic therapy can induce tumor responses and extend life in pancreatic adenocarcinoma (PDAC). Pharmacogenomic (PGx) modeling of tumor tissue can predict the efficacy of chemotherapeutic agents in preclinical cancer models. We hypothesized that PGx profiling of circulating tumor and invasive cells (CTIC) isolated from peripheral blood could predict tumor response, progression, and resistance.Experimental Design: A PGx model was created and validated in preclinical models. A prospective clinical trial was conducted. Fifty patients with advanced PDAC were enrolled. Before treatment, 10 mL of peripherally drawn blood was collected. CTICs isolated from this blood sample were expression profiled and the PGx model was used to predict effective and ineffective chemotherapeutic agents. The treating physicians were blinded to PGx prediction.Results: We found that CTICs could be reliably isolated, total RNA extracted and profiled from 10 mL of peripheral blood from patients with unresectable PDAC before chemotherapy treatment and at disease progression. Using previously created PGx models to predict chemotherapy sensitivity, we found that clinical benefit was seen for study participants treated with chemotherapy regimens predicted to be effective versus chemotherapy regimens predicted to be ineffective with regard to progression-free (10.4 mo vs. 3.6 mo; P < 0.0001; HR, 0.14) and overall survival (17.2 mo vs. 8.3 mo; P < 0.0249; HR, 0.29).Conclusions: These findings suggest that PGx profiling of CTICs can predict treatment response. Clin Cancer Res; 20(20); 5281–9. ©2014 AACR.