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A 7 gene expression score predicts for radiation response in cancer cervix

BACKGROUND: Cervical cancer is the most common cancer among Indian women. The current recommendations are to treat the stage IIB, IIIA, IIIB and IVA with radical radiotherapy and weekly cisplatin based chemotherapy. However, Radiotherapy alone can help cure more than 60% of stage IIB and up to 40% o...

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Autores principales: Rajkumar, Thangarajan, Vijayalakshmi, Neelakantan, Sabitha, Kesavan, Shirley, Sundersingh, Selvaluxmy, Ganesharaja, Bose, Mayil Vahanan, Nambaru, Lavanya
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2768747/
https://www.ncbi.nlm.nih.gov/pubmed/19832977
http://dx.doi.org/10.1186/1471-2407-9-365
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author Rajkumar, Thangarajan
Vijayalakshmi, Neelakantan
Sabitha, Kesavan
Shirley, Sundersingh
Selvaluxmy, Ganesharaja
Bose, Mayil Vahanan
Nambaru, Lavanya
author_facet Rajkumar, Thangarajan
Vijayalakshmi, Neelakantan
Sabitha, Kesavan
Shirley, Sundersingh
Selvaluxmy, Ganesharaja
Bose, Mayil Vahanan
Nambaru, Lavanya
author_sort Rajkumar, Thangarajan
collection PubMed
description BACKGROUND: Cervical cancer is the most common cancer among Indian women. The current recommendations are to treat the stage IIB, IIIA, IIIB and IVA with radical radiotherapy and weekly cisplatin based chemotherapy. However, Radiotherapy alone can help cure more than 60% of stage IIB and up to 40% of stage IIIB patients. METHODS: Archival RNA samples from 15 patients who had achieved complete remission and stayed disease free for more than 36 months (No Evidence of Disease or NED group) and 10 patients who had failed radical radiotherapy (Failed group) were included in the study. The RNA were amplified, labelled and hybridized to Stanford microarray chips and analyzed using BRB Array Tools software and Significance Analysis of Microarray (SAM) analysis. 20 genes were selected for further validation using Relative Quantitation (RQ) Taqman assay in a Taqman Low-Density Array (TLDA) format. The RQ value was calculated, using each of the NED sample once as a calibrator. A scoring system was developed based on the RQ value for the genes. RESULTS: Using a seven gene based scoring system, it was possible to distinguish between the tumours which were likely to respond to the radiotherapy and those likely to fail. The mean score ± 2 SE (standard error of mean) was used and at a cut-off score of greater than 5.60, the sensitivity, specificity, Positive predictive value (PPV) and Negative predictive value (NPV) were 0.64, 1.0, 1.0, 0.67, respectively, for the low risk group. CONCLUSION: We have identified a 7 gene signature which could help identify patients with cervical cancer who can be treated with radiotherapy alone. However, this needs to be validated in a larger patient population.
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spelling pubmed-27687472009-10-28 A 7 gene expression score predicts for radiation response in cancer cervix Rajkumar, Thangarajan Vijayalakshmi, Neelakantan Sabitha, Kesavan Shirley, Sundersingh Selvaluxmy, Ganesharaja Bose, Mayil Vahanan Nambaru, Lavanya BMC Cancer Research Article BACKGROUND: Cervical cancer is the most common cancer among Indian women. The current recommendations are to treat the stage IIB, IIIA, IIIB and IVA with radical radiotherapy and weekly cisplatin based chemotherapy. However, Radiotherapy alone can help cure more than 60% of stage IIB and up to 40% of stage IIIB patients. METHODS: Archival RNA samples from 15 patients who had achieved complete remission and stayed disease free for more than 36 months (No Evidence of Disease or NED group) and 10 patients who had failed radical radiotherapy (Failed group) were included in the study. The RNA were amplified, labelled and hybridized to Stanford microarray chips and analyzed using BRB Array Tools software and Significance Analysis of Microarray (SAM) analysis. 20 genes were selected for further validation using Relative Quantitation (RQ) Taqman assay in a Taqman Low-Density Array (TLDA) format. The RQ value was calculated, using each of the NED sample once as a calibrator. A scoring system was developed based on the RQ value for the genes. RESULTS: Using a seven gene based scoring system, it was possible to distinguish between the tumours which were likely to respond to the radiotherapy and those likely to fail. The mean score ± 2 SE (standard error of mean) was used and at a cut-off score of greater than 5.60, the sensitivity, specificity, Positive predictive value (PPV) and Negative predictive value (NPV) were 0.64, 1.0, 1.0, 0.67, respectively, for the low risk group. CONCLUSION: We have identified a 7 gene signature which could help identify patients with cervical cancer who can be treated with radiotherapy alone. However, this needs to be validated in a larger patient population. BioMed Central 2009-10-15 /pmc/articles/PMC2768747/ /pubmed/19832977 http://dx.doi.org/10.1186/1471-2407-9-365 Text en Copyright ©2009 Rajkumar et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Rajkumar, Thangarajan
Vijayalakshmi, Neelakantan
Sabitha, Kesavan
Shirley, Sundersingh
Selvaluxmy, Ganesharaja
Bose, Mayil Vahanan
Nambaru, Lavanya
A 7 gene expression score predicts for radiation response in cancer cervix
title A 7 gene expression score predicts for radiation response in cancer cervix
title_full A 7 gene expression score predicts for radiation response in cancer cervix
title_fullStr A 7 gene expression score predicts for radiation response in cancer cervix
title_full_unstemmed A 7 gene expression score predicts for radiation response in cancer cervix
title_short A 7 gene expression score predicts for radiation response in cancer cervix
title_sort 7 gene expression score predicts for radiation response in cancer cervix
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2768747/
https://www.ncbi.nlm.nih.gov/pubmed/19832977
http://dx.doi.org/10.1186/1471-2407-9-365
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