Seminars in Radiation Oncology
Volume 20, Issue 3 , Pages 149-155, July 2010

Radiogenomics Predicting Tumor Responses to Radiotherapy in Lung Cancer

  • Amit K. Das, PhD

      Affiliations

    • The University of Texas Southwestern Medical Center, The Hamon Center for Therapeutic Oncology Research, Dallas, TX
    • Corresponding Author InformationAddress reprint requests to Amit K. Das, PhD, The University of Texas Southwestern Medical Center, The Hamon Center for Therapeutic Oncology Research, 6000 Harry Hines Blvd., Dallas, TX 75390-8593
  • ,
  • Marcus H. Bell

      Affiliations

    • The University of Texas Southwestern Medical Center, The Hamon Center for Therapeutic Oncology Research, Dallas, TX
  • ,
  • Chaitanya S. Nirodi, PhD

      Affiliations

    • Department of Radiation Oncology, Division of Molecular Radiation Biology, The University of Texas Southwestern Medical center, Dallas, TX
  • ,
  • Michael D. Story, PhD

      Affiliations

    • Department of Radiation Oncology, Division of Molecular Radiation Biology, The University of Texas Southwestern Medical center, Dallas, TX
  • ,
  • John D. Minna, MD

      Affiliations

    • The University of Texas Southwestern Medical Center, The Hamon Center for Therapeutic Oncology Research, Dallas, TX

The recently developed ability to interrogate genome-wide data arrays has provided invaluable insights into the molecular pathogenesis of lung cancer. These data have also provided information for developing targeted therapy in lung cancer patients based on the identification of cancer-specific vulnerabilities and set the stage for molecular biomarkers that provide information on clinical outcome and response to treatment. In addition, there are now large panels of lung cancer cell lines, both non–small-cell lung cancer and small-cell lung cancer, that have distinct chemotherapy and radiation response phenotypes. We anticipate that the integration of molecular data with therapy response data will allow for the generation of biomarker signatures that predict response to therapy. These signatures will need to be validated in clinical studies, at first retrospective analyses and then prospective clinical trials, to show that the use of these biomarkers can aid in predicting patient outcomes (eg, in the case of radiation therapy for local control and survival). This review highlights recent advances in molecular profiling of tumor responses to radiotherapy and identifies challenges and opportunities in developing molecular biomarker signatures for predicting radiation response for individual patients with lung cancer.

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 Supported by NIH/NCI the University of Texas SPORE in Lung Cancer 5P50 CA 70907 (Dr John D. Minna) and NASA/DOE NASA Specialized Center of Research (NSCOR) NNJ05HD36G/DEAI0205ER64068 (Dr John D. Minna).

PII: S1053-4296(10)00010-X

doi:10.1016/j.semradonc.2010.01.002

Seminars in Radiation Oncology
Volume 20, Issue 3 , Pages 149-155, July 2010