Clinical implications of the cancer genome - PubMed (original) (raw)

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Clinical implications of the cancer genome

Laura E Macconaill et al. J Clin Oncol. 2010.

Abstract

Cancer is a disease of the genome. Most tumors harbor a constellation of structural genomic alterations that may dictate their clinical behavior and treatment response. Whereas elucidating the nature and importance of these genomic alterations has been the goal of cancer biologists for several decades, ongoing global genome characterization efforts are revolutionizing both tumor biology and the optimal paradigm for cancer treatment at an unprecedented scope. The pace of advance has been empowered, in large part, through disruptive technological innovations that render complete cancer genome characterization feasible on a large scale. This article highlights cardinal biologic and clinical insights gleaned from systematic cancer genome characterization. We also discuss how the convergence of cancer genome biology, technology, and targeted therapeutics articulates a cohesive framework for the advent of personalized cancer medicine.

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Conflict of interest statement

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

Figures

Fig 1.

Fig 1.

The major classes of genomic alterations that give rise to cancer. TS, tumor suppressor; CML, chronic myelogenous leukemia.

Fig 2.

Fig 2.

Interrogating molecular alterations in cancer. Genomic alterations that give rise to cancers occur at both the RNA and DNA level. Interrogation of the many types of changes and consequent pathway dysregulation has been restricted to date, in part as a result of limiting technologies. Massively parallel sequencing is one emerging technology that enables the myriad cancer-causing alterations to be interrogated on a tumor-by-tumor basis. FISH, fluorescent in situ hybridization; PCR, polymerase chain reaction.

Fig 3.

Fig 3.

Advances in massively parallel technologies have dramatically reduced the cost of sequencing. The blue line shows the exponential decrease in cost (US dollars) of sequencing as a function of time. The extrapolated timeline represents human whole-genome sequencing for US$100. The yellow line represents Moore's law—the doubling of computer instructions-per-second (IPS) per dollar every 18 months—indicated as a decrease in cost as a function of time (US$/IPS).

Fig 4.

Fig 4.

Schema of personalized medicine. A genome-based vision for personalized cancer medicine will require a paradigm shift in both diagnosis and treatment. Traditionally, tumors are classified by site of origin. In the future, tumor nucleic acid will be profiled for a wide array of genomic alterations with a view to specific, tailored treatment options for each individual patient.

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