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The purpose of the study is to identify biomarkers and potentially actionable mutations/ activated molecular pathways and evaluate the impact of molecular profiling information on patients with cancer.
The hypothesis of the study are:
Advances in our understanding of cancer biology has led to a rapid expansion of molecularly targeted therapeutics in pre-clinical and clinical development over the last decade. The systematic sequencing of cancer genomes has revealed that individual tumours frequently harbor multiple "driver" somatic mutations that confer growth advantage and positive selection. Importantly, many of the altered proteins resulting from the mutations identified by these studies are in fact actionable, i.e. "druggable", targets. Hence, evaluating drug efficacy in tumours selected by a combination of histopathology and molecular analysis has the potential to result in a greater therapeutic gain. The premises behind personalised cancer medicine include: i) genetic aberrations exist in human malignancies; ii) a subset of these aberrations frequently exist across multiple tumour types and have functional relevance as drivers for oncogenesis and tumour progression; iii) the molecular effects of these genetic aberrations are potentially actionable targets; and iv) there are medicinal compounds that can safely and effectively modulate such targets in patients with these tumours. The key challenge to optimising this personalised approach to cancer therapy is to ensure that patients with tumours harbouring specific molecular/ genetic aberrations are specifically matched to a particular drug or combination of drugs. In this respect, molecular analysis of tumours to identify somatic mutations and/or other genetic aberrations are examples of enrichment strategies to assist in matching patients to drugs or treatments that have gained increasing interest in the oncology community. The ability to characterise the unique genetic features of each patient's tumour will be a critical step to identifying the optimal therapeutic strategy for the individual.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| All cancer |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Integrated Molecular Analysis | Other |
|
| Measure | Description | Time Frame |
|---|---|---|
| 1. Characterization of identified biomarkers and potentially actionable mutations/ activated molecular pathways | By identifying biomarkers and actionable mutations/molecular pathways in patients and characterizing them, we can evaluate the impact of molecular profiling information on patients with cancer. The spectrum and development of molecularly targeted agents is rapidly expanding, and it is increasingly likely that the future of cancer management will require the molecular and histological subtype of one's tumor to be defined in order to decide on the most appropriate treatment strategy. | 2 years |
| To compare progression free survival (PFS) on matched therapy vs non-matched therapy in cancer patients enrolled into molecular targeted therapy/ biomarker-driven clinical trials. | Progression free survival (PFS) on matched targeted therapy based on molecular profiling compared with PFS on previous non-targeted therapy will be compared to assess the clinical impact of molecular profiling in these patients. | 2 years |
| To compare overall response rates (ORR) on matched therapy vs non-matched therapy in cancer patients enrolled into molecular targeted therapy/ biomarker-driven clinical trials. | Overall response rates (ORR) on matched targeted therapy based on molecular profiling versus non-matched therapy will be compared to assess the clinical impact of molecular profiling in these patients. | 2 years |
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Inclusion Criteria:
Exclusion Criteria:
Unable to provide informed consent
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Patients treated with cancers at National University Hospital.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Shao peng David Tan, MBBS, MRCP, PHD | Contact | (65) 6779 5555 | david_sp_tan@nuhs.edu.sg |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| David Tan Shao Peng | Recruiting | Singapore | 119074 | Singapore |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 15286737 | Background | Kola I, Landis J. Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov. 2004 Aug;3(8):711-5. doi: 10.1038/nrd1470. No abstract available. | |
| 19064964 | Background | Stewart DJ, Kurzrock R. Cancer: the road to Amiens. J Clin Oncol. 2009 Jan 20;27(3):328-33. doi: 10.1200/JCO.2008.18.9621. Epub 2008 Dec 8. No abstract available. |
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| ID | Term |
|---|---|
| D009369 | Neoplasms |
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I. Tumour samples from patients with a diagnosis of cancer from year 1995 to 31 July 2013 will be obtained from the pathology archives and tissue repository.
II. Blood, tumour and ascitic and pleural fluid samples will be prospectively collected.