Clinical Review Abstract
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Use of pharmacogenomic modeling in pancreatic cancer for prediction of chemotherapy response and resistance.
Gastrointestinal (Noncolorectal) Cancer
2013 ASCO Annual Meeting
J Clin Oncol 31, 2013 (suppl; abstr 4017)
Author(s): Kenneth H. Yu, Vineet Sangar, Mark Ricigliano, Manuel Hidalgo, Ghassan K. Abou-Alfa, Maeve Aine Lowery, Leonard Saltz, Joseph F. Crotty, Kristen Gary, Jing Yin, Eun Yong Choi, Eileen Mary O'Reilly; Memorial Sloan-Kettering Cancer Center, New York, NY; Institute for Systems Biology, Seattle, WA; CellPath Therapeuthics, Inc, Baltimore, MD; Spanish National Cancer Research Center (CNIO), Madrid, Spain; University of Maryland, Marlene and Stewart Greenebaum Cancer Center, Baltimore, MD
Background: Pancreatic adenocarcinoma (PDAC) is uniformly lethal and is the 4th leading cause of cancer mortality. Despite this, modern cytotoxics (C) can induce tumor responses and extend life. Xenograft models have shown that pharmacogenomic (PGx) modeling of C can predict efficacy. Chemo-sensitivity and gene expression profiling of circulating tumor and invasive cells (CTICs) isolated from peripheral blood may predict tumor response, progression and resistance. Methods: A prospective MSKCC study has completed planned accrual of 50 patients. 10 mL of peripheral blood is collected from patients with unresectable PDAC prior to C and at disease progression. Clinical data is prospectively collected. CTICs are isolated (Vita-Cap, Vitatex Inc.), total RNA is extracted and gene-expression analysis is performed. PGx models for twelve chemotherapy drug combinations used in PDAC were created from the GI50 data obtained from the NCI-60 cell lines (CellPath Therapeutics, Inc., Baltimore, MD). Expression data were normalized through GCRMA then probed to identify expression differences between patients with short v long TTP and within patients at baseline v at time of progression. The analysis was performed at the pathway and individual gene level. Results: CTICs were isolated, and gene expression and chemo-sensitivity patterns were obtained in all 50 patients prior to initiating C and in 20 patients at 1st line disease progression. Preliminary analysis demonstrates clinical benefit for patients treated with C predicted to be effective versus ineffective (TTP 7.3 mo v 3.7 mo, p=0.017, HR 0.30). Changes in chemo-sensitivity patterns were evident at disease progression, reflecting treatment resistance. Pathway analysis revealed that E2F1 and NFκB pathways are associated with prognosis, PLC and RB1 pathways become disrupted with disease progression. Conclusions: Isolation and gene expression profiling of CTICs can be performed reliably in unresectable PDAC. Preliminary analysis suggests that C profiling can predict response. Repeat PGx profiling identifies key pathways associated with treatment resistance. Clinical trial information: NCT01474564.
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