Predictive and prognostic molecular markers for cancer medicine
Over the last 10 years there has been an explosion of information about the molecular biology of cancer. A challenge in oncology is to translate this information into advances in patient care. While there are well-formed routes for translating new molecular information into drug therapy, the routes...
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2010-03-01
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Series: | Therapeutic Advances in Medical Oncology |
Online Access: | https://doi.org/10.1177/1758834009360519 |
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doaj-462dc2877666490dbfec691ebd6630242020-11-25T03:16:32ZengSAGE PublishingTherapeutic Advances in Medical Oncology1758-83402010-03-01210.1177/1758834009360519Predictive and prognostic molecular markers for cancer medicineSunali MehtaAndrew ShellingAnita MuthukaruppanAnnette LashamCherie BlenkironGeorge LakingCristin PrintOver the last 10 years there has been an explosion of information about the molecular biology of cancer. A challenge in oncology is to translate this information into advances in patient care. While there are well-formed routes for translating new molecular information into drug therapy, the routes for translating new information into sensitive and specific diagnostic, prognostic and predictive tests are still being developed. Similarly, the science of using tumor molecular profiles to select clinical trial participants or to optimize therapy for individual patients is still in its infancy. This review will summarize the current technologies for predicting treatment response and prognosis in cancer medicine, and outline what the future may hold. It will also highlight the potential importance of methods that can integrate molecular, histopathological and clinical information into a synergistic understanding of tumor progression. While these possibilities are without doubt exciting, significant challenges remain if we are to implement them with a strong evidence base in a widely available and cost-effective manner.https://doi.org/10.1177/1758834009360519 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sunali Mehta Andrew Shelling Anita Muthukaruppan Annette Lasham Cherie Blenkiron George Laking Cristin Print |
spellingShingle |
Sunali Mehta Andrew Shelling Anita Muthukaruppan Annette Lasham Cherie Blenkiron George Laking Cristin Print Predictive and prognostic molecular markers for cancer medicine Therapeutic Advances in Medical Oncology |
author_facet |
Sunali Mehta Andrew Shelling Anita Muthukaruppan Annette Lasham Cherie Blenkiron George Laking Cristin Print |
author_sort |
Sunali Mehta |
title |
Predictive and prognostic molecular markers for cancer medicine |
title_short |
Predictive and prognostic molecular markers for cancer medicine |
title_full |
Predictive and prognostic molecular markers for cancer medicine |
title_fullStr |
Predictive and prognostic molecular markers for cancer medicine |
title_full_unstemmed |
Predictive and prognostic molecular markers for cancer medicine |
title_sort |
predictive and prognostic molecular markers for cancer medicine |
publisher |
SAGE Publishing |
series |
Therapeutic Advances in Medical Oncology |
issn |
1758-8340 |
publishDate |
2010-03-01 |
description |
Over the last 10 years there has been an explosion of information about the molecular biology of cancer. A challenge in oncology is to translate this information into advances in patient care. While there are well-formed routes for translating new molecular information into drug therapy, the routes for translating new information into sensitive and specific diagnostic, prognostic and predictive tests are still being developed. Similarly, the science of using tumor molecular profiles to select clinical trial participants or to optimize therapy for individual patients is still in its infancy. This review will summarize the current technologies for predicting treatment response and prognosis in cancer medicine, and outline what the future may hold. It will also highlight the potential importance of methods that can integrate molecular, histopathological and clinical information into a synergistic understanding of tumor progression. While these possibilities are without doubt exciting, significant challenges remain if we are to implement them with a strong evidence base in a widely available and cost-effective manner. |
url |
https://doi.org/10.1177/1758834009360519 |
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