Model Predicts Tumor Spread in Lung Cancer

Genetic characteristics of lung cancer can be used to predict likelihood of metastasis, a newly developed model shows.

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Lung cancer is generally classified by oncogenic drivers, such as epidermal growth factor receptor (EGFR), rather than patterns of anatomical distribution. Oncogenic drivers are clinically predictive and prognostic. While tumor metastasis usually involves the opposite lung and other sites—such as the liver bone, brain, and lymph nodes—the process of metastasis may seem random and unpredictable.

Jorge Nieva, MD, University of Southern California, and colleagues conducted a study to assess whether a mathematical model could determine a link between the molecular and anatomical properties of lung cancer metastases, and whether this has any influence on how metastases spreads through the body. Researchers used a retrospective database involving data from 664 patients with non-small cell lung cancer. Markov mathematical modeling was used to examine metastatic sites in a spatiotemporal manner, through every point in the progression of disease.

The study was published in Convergent Science Physical Oncology (published July 13, 2017; 3[3]).

Results of the study showed a preferential pattern of primary lung disease progressing through lung metastasis to the brain with EGFR exon 19 deletions and exon 21 L858R mutations. Researchers describe the brain in these cases as classifiable as an “anatomical sponge,” due to a higher ratio of incoming to outgoing tumor spread. On the contrary, patients with EGFR wild type were more likely to have their tumors spread from the lungs to the bone, researchers acknowledged.

"If the presence of these EGFR mutations, particularly in the setting of progressive lung disease, points to increased risk of brain metastases, these patients may benefit from intensified CNS specific imaging,” authors of the study wrote. “Multi-modality strategies to treat limited metastatic disease and limited relapse have shown the potential to improve survival in advanced disease, and may directly impact the biology of EGFR exon 19 and 21 mutation harboring lung cancer when combined with targeted therapy."

Researchers concluded that a definite link exists between the anatomical and molecular characterization of metastatic lung cancer. Further research is needed to understand the underlying mechanism of these anatomical differences in metastatic progression. This research could improve predictive and prognostic use in the management of personalized lung cancer.—Zachary Bessette