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  • Review Article
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Biomarker development in the precision medicine era: lung cancer as a case study

Nature Reviews Cancer volume 16, pages 525–537 (2016)Cite this article

Subjects

Key Points

  • Precision medicine seeks to identify and classify individual patients so that optimal treatment decisions can be made. Nations are recognizing this area of research by developing national cohorts from which to collect data and developing regulatory guidelines on biomarkers.

  • The cost of genetic sequencing and other 'omics' technologies has decreased while the quality of data they generate has increased. Thus, immense amounts of molecular data are being derived from cohort studies to begin developing new biomarkers to classify patients into subtypes.

  • The development of biomarkers is largely limited by the following factors: low statistical power in rare subtypes; risk of false-positive findings in studies that do not validate their findings in a separate cohort and/or conduct concomitant mechanistic experiments; and technical reproducibility concerns.

  • Genomics and protein immunohistochemistry have led the way for developing biomarkers. Other molecular measurements (for example, metabolomics and microbiomics) are still in preliminary stages and are often not validated in another cohort.

  • Integrating different types of molecules into a biomarker panel, along with other patient data, is the future of precision medicine; however, the sheer number of potential combinations of data types complicates the concerns about statistical power and reproducibility.

  • Currently, improved biomarkers are needed to differentiate lung nodules identified by new US national screening recommendations into non-cancer, cancer with poor survival probability and cancer with higher survival probability subtypes, to provide thousands of individuals with precise treatment decisions.

Abstract

Precision medicine relies on validated biomarkers with which to better classify patients by their probable disease risk, prognosis and/or response to treatment. Although affordable 'omics'-based technology has enabled faster identification of putative biomarkers, the validation of biomarkers is still stymied by low statistical power and poor reproducibility of results. This Review summarizes the successes and challenges of using different types of molecule as biomarkers, using lung cancer as a key illustrative example. Efforts at the national level of several countries to tie molecular measurement of samples to patient data via electronic medical records are the future of precision medicine research.

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Figure 1: Classifying patients into new, specific taxa.
Figure 2: A precision medicine research strategy.
Figure 3: Knowledge of non-small cell lung adenocarcinoma has evolved in recent decades.
Figure 4: The lung exposome.
Figure 5: Use of precision medicine to classify patients with early-stage lung cancer into subclasses to provide appropriate treatment.

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Acknowledgements

This work was supported by funding from the Intramural Program of the Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA, and the Cancer Prevention Fellowship Program, National Cancer Institute, Rockville, Maryland, USA.

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  1. Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Room 3068A, MSC 425, 837 Convent Drive, Bethesda, 20892-4258, Maryland, USA

    Ashley J. Vargas & Curtis C. Harris

  2. Division of Cancer Prevention, National Cancer Institute, Rockville, 20850, Maryland, USA

    Ashley J. Vargas

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Vargas, A., Harris, C. Biomarker development in the precision medicine era: lung cancer as a case study. Nat Rev Cancer 16, 525–537 (2016). https://doi.org/10.1038/nrc.2016.56

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