Literature DB >> 18927307

Clinical determinants of response to irinotecan-based therapy derived from cell line models.

Wendy L Allen1, Vicky M Coyle, Puthen V Jithesh, Irina Proutski, Leanne Stevenson, Cathy Fenning, Daniel B Longley, Richard H Wilson, Michael Gordon, Heinz-Josef Lenz, Patrick G Johnston.   

Abstract

PURPOSE: In an attempt to identify genes that are involved in resistance to SN38, the active metabolite of irinotecan (also known as CPT-11), we carried out DNA microarray profiling of matched HCT116 human colon cancer parental cell lines and SN38-resistant cell lines following treatment with SN38 over time. EXPERIMENTAL
DESIGN: Data analysis identified a list of genes that were acutely altered in the parental cells following SN38 treatment as well as constitutively altered in the SN38-resistant cells.
RESULTS: Independent validation of 20% of these genes by quantitative reverse transcription-PCR revealed a strong correlation with the microarray results: Pearson's correlation was 0.781 (r(2) = 0.61, P < 0.000001) for those genes that were acutely altered in the parental setting following SN38 treatment and 0.795 (r(2) = 0.63, P < 0.000002) for those genes that were constitutively altered in the SN38-resistant cells. We then assessed the ability of our in vitro-derived gene list to predict clinical response to 5-fluorouracil/irinotecan using pretreatment metastatic biopsies from responding and nonresponding colorectal cancer patients using both unsupervised and supervised approaches. When principal components analysis was used with our in vitro classifier gene list, a good separation between responding and nonresponding patients was obtained, with only one nonresponding and two responding patients separating with the incorrect groups. Supervised class prediction using support vector machines algorithm identified a 16-gene classifier with 75% overall accuracy, 81.8% sensitivity, and 66.6% specificity.
CONCLUSIONS: These results suggest that in vitro-derived gene lists can be used to predict clinical response to chemotherapy in colorectal cancer.

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Year:  2008        PMID: 18927307     DOI: 10.1158/1078-0432.CCR-08-0452

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  8 in total

1.  Pharmacogenomic profiling and pathway analyses identify MAPK-dependent migration as an acute response to SN38 in p53 null and p53-mutant colorectal cancer cells.

Authors:  Wendy L Allen; Richard C Turkington; Leanne Stevenson; Gail Carson; Vicky M Coyle; Suzanne Hector; Philip Dunne; Sandra Van Schaeybroeck; Daniel B Longley; Patrick G Johnston
Journal:  Mol Cancer Ther       Date:  2012-06-04       Impact factor: 6.261

Review 2.  Implementing prognostic and predictive biomarkers in CRC clinical trials.

Authors:  Sandra Van Schaeybroeck; Wendy L Allen; Richard C Turkington; Patrick G Johnston
Journal:  Nat Rev Clin Oncol       Date:  2011-02-15       Impact factor: 66.675

3.  A systems biology approach identifies SART1 as a novel determinant of both 5-fluorouracil and SN38 drug resistance in colorectal cancer.

Authors:  Wendy L Allen; Leanne Stevenson; Vicky M Coyle; Puthen V Jithesh; Irina Proutski; Gail Carson; Michael A Gordon; Heinz-Josef D Lenz; Sandra Van Schaeybroeck; Daniel B Longley; Patrick G Johnston
Journal:  Mol Cancer Ther       Date:  2011-10-25       Impact factor: 6.261

4.  New benzimidazole acridine derivative induces human colon cancer cell apoptosis in vitro via the ROS-JNK signaling pathway.

Authors:  Kang Chen; Bi-zhu Chu; Feng Liu; Bin Li; Chun-mei Gao; Lu-lu Li; Qin-sheng Sun; Zhi-fa Shen; Yu-yang Jiang
Journal:  Acta Pharmacol Sin       Date:  2015-08-03       Impact factor: 6.150

5.  Three-gene predictor of clinical outcome for gastric cancer patients treated with chemotherapy.

Authors:  H K Kim; I J Choi; C G Kim; H S Kim; A Oshima; Y Yamada; T Arao; K Nishio; A Michalowski; J E Green
Journal:  Pharmacogenomics J       Date:  2010-12-21       Impact factor: 3.550

6.  The colorectal cancer disease-specific transcriptome may facilitate the discovery of more biologically and clinically relevant information.

Authors:  Wendy L Allen; Puthen V Jithesh; Gavin R Oliver; Irina Proutski; Daniel B Longley; Heinz-Josef Lenz; Vitali Proutski; Paul Harkin; Patrick G Johnston
Journal:  BMC Cancer       Date:  2010-12-20       Impact factor: 4.430

7.  Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post-chemotherapy tissues.

Authors:  Mengsha Tong; Weicheng Zheng; Xingrong Lu; Lu Ao; Xiangyu Li; Qingzhou Guan; Hao Cai; Mengyao Li; Haidan Yan; You Guo; Pan Chi; Zheng Guo
Journal:  Oncotarget       Date:  2015-12-01

8.  Identification of galanin and its receptor GalR1 as novel determinants of resistance to chemotherapy and potential biomarkers in colorectal cancer.

Authors:  Leanne Stevenson; Wendy L Allen; Richard Turkington; Puthen V Jithesh; Irina Proutski; Gail Stewart; Heinz-Josef Lenz; Sandra Van Schaeybroeck; Daniel B Longley; Patrick G Johnston
Journal:  Clin Cancer Res       Date:  2012-08-02       Impact factor: 12.531

  8 in total

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