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

Wendy L. Allen, 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

Research output: Contribution to journalArticle

18 Citations (Scopus)

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 r = 0.61, P < 0.000001) for those genes that were acutely altered in the parental setting following SN38 treatment and 0.795 (r r = 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 a16-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.

Original languageEnglish
Pages (from-to)6647-6655
Number of pages9
JournalClinical Cancer Research
Volume14
Issue number20
DOIs
Publication statusPublished - 15 Oct 2008
Externally publishedYes

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irinotecan
Cell Line
Genes
Therapeutics
Colorectal Neoplasms
DNA Fingerprinting

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

Cite this

Allen, W. L., Coyle, V. M., Jithesh, P. V., Proutski, I., Stevenson, L., Fenning, C., ... Johnston, P. G. (2008). Clinical determinants of response to irinotecan-based therapy derived from cell line models. Clinical Cancer Research, 14(20), 6647-6655. https://doi.org/10.1158/1078-0432.CCR-08-0452

Clinical determinants of response to irinotecan-based therapy derived from cell line models. / Allen, Wendy L.; Coyle, Vicky M.; Jithesh, Puthen V.; Proutski, Irina; Stevenson, Leanne; Fenning, Cathy; Longley, Daniel B.; Wilson, Richard H.; Gordon, Michael; Lenz, Heinz Josef; Johnston, Patrick G.

In: Clinical Cancer Research, Vol. 14, No. 20, 15.10.2008, p. 6647-6655.

Research output: Contribution to journalArticle

Allen, WL, Coyle, VM, Jithesh, PV, Proutski, I, Stevenson, L, Fenning, C, Longley, DB, Wilson, RH, Gordon, M, Lenz, HJ & Johnston, PG 2008, 'Clinical determinants of response to irinotecan-based therapy derived from cell line models', Clinical Cancer Research, vol. 14, no. 20, pp. 6647-6655. https://doi.org/10.1158/1078-0432.CCR-08-0452
Allen, Wendy L. ; Coyle, Vicky M. ; Jithesh, Puthen V. ; Proutski, Irina ; Stevenson, Leanne ; Fenning, Cathy ; Longley, Daniel B. ; Wilson, Richard H. ; Gordon, Michael ; Lenz, Heinz Josef ; Johnston, Patrick G. / Clinical determinants of response to irinotecan-based therapy derived from cell line models. In: Clinical Cancer Research. 2008 ; Vol. 14, No. 20. pp. 6647-6655.
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AU - Proutski, Irina

AU - Stevenson, Leanne

AU - Fenning, Cathy

AU - Longley, Daniel B.

AU - Wilson, Richard H.

AU - Gordon, Michael

AU - Lenz, Heinz Josef

AU - Johnston, Patrick G.

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N2 - 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 r = 0.61, P < 0.000001) for those genes that were acutely altered in the parental setting following SN38 treatment and 0.795 (r r = 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 a16-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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