Integrated Molecular Profiling in Advanced Cancers Trial
NCT ID: NCT01505400
Last Updated: 2026-01-08
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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ACTIVE_NOT_RECRUITING
3026 participants
OBSERVATIONAL
2012-02-29
2027-01-31
Brief Summary
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Biomarkers are specific characteristics of the cancer that may help provide prognostic information (i.e. how well patients will be regardless of the treatments given) or help predict sensitivity or resistance to a specific treatment.
The study will collect archival tumor samples (previously collected biopsy or surgical tumor samples) to provide biomarker data about a patient's cancer, in order to help their physicians to identify which clinical trials of molecularly targeted therapies may be most appropriate for the patient in the future.
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Detailed Description
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The premises behind personalized cancer medicine include: i) genetic aberrations exist in human malignancies; ii) a subset of these aberrations, often present across multiple cancer types, have functional relevance as "hallmarks" or "drivers" for oncogenesis and tumor progression; iii) such genetic aberrations are potentially "druggable" targets; and iv) there are tolerable medicinal compounds that can effectively modulate such targets. A key requirement of this new, personalized approach to anti-cancer therapy is that specific patients must be matched to a particular drug or combination of drugs. Molecular profiling of tumors 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 present protocol seeks to provide molecular profiling data to the treating physician for patients with advanced breast, non-small cell lung, colorectal, genitourinary, pancreatobiliary gastrointestinal, upper aerodigestive tract, gynecological, melanoma, unknown primary, and rare carcinomas, as well as patients who are phase I trial candidates, in order to help identify which standard regimens or clinical trials of molecularly targeted therapies may be most appropriate for the individual patient.
Conditions
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Study Design
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COHORT
RETROSPECTIVE
Study Groups
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Advanced cancer
Advanced breast, non-small cell lung, colorectal, genitourinary, pancreatobiliary gastrointestinal, upper aerodigestive tract, gynecological, melanoma, unknown primary, and rare carcinomas; as well as patients who are phase I trial candidates
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* Patient must be ≥ 18 years old.
* Patient's ECOG performance status equal to 0 or 1.
* All patients must have signed and dated an informed consent form.
* All patients must have sufficient archived tumor tissue for molecular profiling.
Exclusion Criteria
18 Years
ALL
No
Sponsors
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Princess Margaret Hospital, Canada
OTHER
University Health Network, Toronto
OTHER
Responsible Party
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Principal Investigators
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Philippe Bedard, MD
Role: PRINCIPAL_INVESTIGATOR
Princess Margaret Hospital, Canada
Locations
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Princess Margaret Hospital
Toronto, Ontario, Canada
Countries
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References
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Ma LX, Espin-Garcia O, Bedard PL, Stockley T, Prince R, Mete O, Krzyzanowska MK. Clinical Application of Next-Generation Sequencing in Advanced Thyroid Cancers. Thyroid. 2022 Jun;32(6):657-666. doi: 10.1089/thy.2021.0542. Epub 2022 May 16.
Stockley TL, Oza AM, Berman HK, Leighl NB, Knox JJ, Shepherd FA, Chen EX, Krzyzanowska MK, Dhani N, Joshua AM, Tsao MS, Serra S, Clarke B, Roehrl MH, Zhang T, Sukhai MA, Califaretti N, Trinkaus M, Shaw P, van der Kwast T, Wang L, Virtanen C, Kim RH, Razak AR, Hansen AR, Yu C, Pugh TJ, Kamel-Reid S, Siu LL, Bedard PL. Molecular profiling of advanced solid tumors and patient outcomes with genotype-matched clinical trials: the Princess Margaret IMPACT/COMPACT trial. Genome Med. 2016 Oct 25;8(1):109. doi: 10.1186/s13073-016-0364-2.
Other Identifiers
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IMPACT-001
Identifier Type: -
Identifier Source: org_study_id
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