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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.
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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.
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100 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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