Clinical trial NCT02078544: Integrated Molecular Analysis of Cancer (IMAC)
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Cancer
Keywords: Oncology
Lead sponsor: National University Hospital, Singapore
Sponsor class: OTHER
First posted: 2014-03-05
Enrollment: 1800
Sex: FEMALE
Minimum age (years): 21
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_ONLY
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Patients treated with cancers at National University Hospital.

Brief summary: 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:

* Analysis of tumour samples will allow us to identify novel and/or actionable molecular changes that may drive therapeutic strategies for the management of cancers.
* Molecular profiling will improve the outcome of novel targeted-agent treatment in clinical trials
* Molecular profiling of paired samples (primary/recurrent and primary/metastatic) will provide new insights into mechanisms underlying drug resistance and metastasis in cancers.

Detailed description: 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.

Eligibility criteria: Inclusion Criteria:

1. Patients with histological confirmation of cancers who are candidates for systemic therapy, including molecular-targeted therapy/ biomarker-driven clinical trials.
2. Patients must be ≥ 21 years old.
3. All patients must have signed and dated an informed consent form.
4. All patients must have sufficient tumour tissue for molecular profiling

Exclusion Criteria:

Unable to provide informed consent

Primary outcomes:
measure: 1. Characterization of identified biomarkers and potentially actionable mutations/ activated molecular pathways
timeFrame: 2 years
measure: 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.
timeFrame: 2 years
measure: 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.
timeFrame: 2 years
Secondary outcomes:
Other outcomes:
Locations:
city: Singapore
country: Singapore
facility: David Tan Shao Peng
Study officials:
References:
citation: 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.
citation: 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.