Gene expression signature and response to the use of leucovorin, fluorouracil and oxaliplatin in colorectal cancer patients View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2011-06-29

AUTHORS

Toshiaki Watanabe, Takashi Kobunai, Yoko Yamamoto, Keiji Matsuda, Soichiro Ishihara, Keijiro Nozawa, Hisae Iinuma, Tsuyoshi Konishi, Hisanaga Horie, Hiroki Ikeuchi, Kiyoshi Eshima, Tetsuichiro Muto

ABSTRACT

PurposeFOLFOX (a combination of leucovorin, fluorouracil and oxaliplatin) has achieved substantial success in the treatment of colorectal cancer (CRC) patients. However, about half of all patients show resistance to this regimen and some develop adverse symptoms such as neurotoxicity. In order to select patients who would benefit most from this therapy, we aimed to build a predictor for the response to FOLFOX using microarray gene expression profiles of primary CRC samples.Patients and methodsForty patients who underwent surgery for primary lesions were examined. All patients had metastatic or recurrent CRC and received modified FOLFOX6. Responders and nonresponders were determined according to the best observed response at the end of the first-line treatment. Gene-expression profiles of primary CRC were determined using Human Genome GeneChip arrays U133. We identified discriminating genes whose expression differed significantly between responders and nonresponders and then carried out supervised class prediction using the k-nearest-neighbour method.ResultsWe identified 27 probes that were differentially expressed between responders and nonresponders at significant levels. Based on the expression of these genes, we constructed a FOLFOX response predictor with an overall accuracy of 92.5%. The sensitivity, specificity, positive and negative predictive values were 78.6%, 100%, 100% and 89.7%, respectively.ConclusionThe present model suggests the possibility of selecting patients who would benefit from FOLFOX therapy both in the metastatic and the adjuvant setting. To our knowledge, this is the first study to establish a prediction model for the response to FOLFOX chemotherapy based on gene expression by microarray analysis. More... »

PAGES

419-425

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12094-011-0676-z

DOI

http://dx.doi.org/10.1007/s12094-011-0676-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1015715567

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/21680303


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31 schema:description PurposeFOLFOX (a combination of leucovorin, fluorouracil and oxaliplatin) has achieved substantial success in the treatment of colorectal cancer (CRC) patients. However, about half of all patients show resistance to this regimen and some develop adverse symptoms such as neurotoxicity. In order to select patients who would benefit most from this therapy, we aimed to build a predictor for the response to FOLFOX using microarray gene expression profiles of primary CRC samples.Patients and methodsForty patients who underwent surgery for primary lesions were examined. All patients had metastatic or recurrent CRC and received modified FOLFOX6. Responders and nonresponders were determined according to the best observed response at the end of the first-line treatment. Gene-expression profiles of primary CRC were determined using Human Genome GeneChip arrays U133. We identified discriminating genes whose expression differed significantly between responders and nonresponders and then carried out supervised class prediction using the k-nearest-neighbour method.ResultsWe identified 27 probes that were differentially expressed between responders and nonresponders at significant levels. Based on the expression of these genes, we constructed a FOLFOX response predictor with an overall accuracy of 92.5%. The sensitivity, specificity, positive and negative predictive values were 78.6%, 100%, 100% and 89.7%, respectively.ConclusionThe present model suggests the possibility of selecting patients who would benefit from FOLFOX therapy both in the metastatic and the adjuvant setting. To our knowledge, this is the first study to establish a prediction model for the response to FOLFOX chemotherapy based on gene expression by microarray analysis.
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38 CRC samples
39 FOLFOX
40 FOLFOX chemotherapy
41 FOLFOX therapy
42 FOLFOX6
43 MethodsForty patients
44 ResultsWe
45 U133
46 accuracy
47 adjuvant setting
48 adverse symptoms
49 analysis
50 cancer patients
51 chemotherapy
52 class prediction
53 colorectal cancer patients
54 end
55 expression
56 expression profiles
57 expression signatures
58 first study
59 first-line treatment
60 fluorouracil
61 gene expression
62 gene expression profiles
63 gene expression signatures
64 genes
65 half
66 k-nearest-neighbour method
67 knowledge
68 lesions
69 leucovorin
70 levels
71 metastatic
72 method
73 microarray analysis
74 microarray gene expression profiles
75 model
76 negative predictive value
77 neurotoxicity
78 nonresponders
79 observed response
80 order
81 overall accuracy
82 oxaliplatin
83 patients
84 possibility
85 prediction
86 prediction model
87 predictive value
88 predictors
89 present model
90 primary CRC
91 primary CRC samples
92 primary lesion
93 probe
94 profile
95 recurrent CRC
96 regimen
97 resistance
98 responders
99 response
100 response predictors
101 samples
102 sensitivity
103 setting
104 signatures
105 significant levels
106 specificity
107 study
108 substantial success
109 success
110 surgery
111 symptoms
112 therapy
113 treatment
114 use
115 use of leucovorin
116 values
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