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Utilization of Genomic Information to Augment Chemotherapy Decision-making for People With Incurable Malignancies

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ClinicalTrials.gov Identifier: NCT01802905
Recruitment Status : Completed
First Posted : March 4, 2013
Last Update Posted : February 5, 2015
BC Cancer Foundation
Information provided by (Responsible Party):
British Columbia Cancer Agency

Brief Summary:
Most systemic therapies are chosen on the basis of large randomized clinical trials; however, tumour heterogeneity means that cancers with similar histological features may have substantially different underlying biological drivers. The investigators propose that applying personal genomic information prospectively obtained in a clinically realistic timeframe to assist in chemotherapy decision-making could result in more effective and efficient cancer treatment. This study will investigate this approach in a cross section of advanced cancers to examine timeliness, deliverability, rate of actionable targets identified, and our ability to expand this approach into a larger clinical trial setting.

Condition or disease Intervention/treatment
Advanced Incurable Cancers Genetic: in depth genomic sequencing

Detailed Description:

It is clear that carcinogenesis is an immensely complex process and that even within a histologic cancer subtype - such as adenocarcinoma of the lung or breast - there is significant heterogeneity in cancer behaviour and response to therapy. Recognizing genetic mutations that promote disease facilitates targeted treatment; this has been demonstrated in several small subgroups of cancers in which specific genetic mutations or translocations have been successfully treated with targeted chemotherapy agents.

Analyses of individual patients demonstrate unique molecular signatures for every cancer examined. Frequently, multiple different pathways are involved in disease growth and progression and the dominant process varies from person to person and perhaps even within different sites of disease within one person. As well these variations evolve in response to treatment. With many recognized mutations personalized evaluation of the genetic signature encoded in DNA and RNA may enable directed therapy to the appropriate oncologic pathway thereby providing information to help guide chemotherapy choices.

Study Type : Interventional  (Clinical Trial)
Actual Enrollment : 100 participants
Intervention Model: Single Group Assignment
Masking: None (Open Label)
Official Title: Utilization of Genomic Information to Augment Chemotherapy Decision-making for People With Incurable Malignancies
Study Start Date : June 2012
Primary Completion Date : February 2015
Study Completion Date : February 2015

Arm Intervention/treatment
Experimental: Sequenced patients
Patients enrolled on the study who have successful sequencing of their cancers will be closely monitored for: what chemotherapy agents are next used, what response and toxicity do they have, is there any early sign of response detected on PET-CT, overall did the genomic information change treatment decision-making.
Genetic: in depth genomic sequencing
Fresh tumour biopsies and matched normal specimens (blood and surrounding tissue) and when possible archival pretreatment specimens, will undergo in depth DNA and RNA sequencing and analysis on an oncogene panel.

Primary Outcome Measures :
  1. Frequency of actioanble genomic abnormalites detected that modify treatment [ Time Frame: up to 24 months ]
    What is the frequency of "actionable" results in this varied tumour population ?

Secondary Outcome Measures :
  1. What is the frequency with which these actionable results actually result in a subject receiving a drug(s) related to this test [ Time Frame: up to 24 months ]
    What is the frequency with which these actionable results actually result in a subject receiving a drug(s) related to this test.

Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Senior)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No

Inclusion Criteria:

  1. Subjects must have histologically or cytologically confirmed diagnosis of cancer
  2. This cancer must be incurable, as defined by their treating oncologist (generally because of advanced stage).
  3. Subjects must agree to provide archival tissue and agree to undergo a study specific biopsy and blood test for genetic analysis. All subjects would have a biopsy and blood samples at progression if it could be done safely.
  4. ECOG PS 0 or 1.
  5. Age > 18 years of age.
  6. Subject consent must be obtained according to the BCCA requirements.
  7. Subject must be accessible for treatment and follow-up. Subjects must be registered at the BCCA Vancouver site.

Exclusion Criteria:

  1. Unable or unwilling to undergo tumour biopsy(s) and/or blood/skin samples for normal DNA.
  2. Significant medical condition that in the opinion of the treating oncologist renders the subject not suitable for participation.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT01802905

Canada, British Columbia
BC Cancer Agency
Vancouver, British Columbia, Canada
Sponsors and Collaborators
British Columbia Cancer Agency
BC Cancer Foundation
Principal Investigator: Janessa J. Laskin, MD FRCPC British Columbia Cancer Agency
Principal Investigator: Marco Marra, PhD FRSC Genome Sciences Centre, BC Cancer Agency

Peixoto RD; Li Y; Pleasance E; Yip S; et al. A case of the utilization of genomic information in the management of metastatic colorectal cancer. J Clin Oncol 30: 2012 (suppl 34; abstr 444)

Responsible Party: British Columbia Cancer Agency
ClinicalTrials.gov Identifier: NCT01802905     History of Changes
Other Study ID Numbers: BCCA POG 01
First Posted: March 4, 2013    Key Record Dates
Last Update Posted: February 5, 2015
Last Verified: February 2013

Keywords provided by British Columbia Cancer Agency:
metastatic cancer
cancer genome
genomic analysis