Development of metastatic brain disease involves progression through lung metastases in EGFR mutated non-small cell lung cancer

Abstract

Lung cancer is often classified by the presence of oncogenic drivers, such as epidermal growth factor receptor (EGFR), rather than patterns of anatomical distribution. While metastatic spread may seem a random and unpredictable process, we explored the possibility of using its quantifiable nature as a measure of describing and comparing different subsets of disease. We constructed a database of 664 non-small cell lung cancer (NSCLC) patients treated at the University of Southern California Norris Comprehensive Cancer Center and the Los Angeles County Medical Center. Markov mathematical modeling was employed to assess metastatic sites in a spatiotemporal manner through every time point in progression of disease. Our findings identified a preferential pattern of primary lung disease progressing through lung metastases to the brain amongst EGFR mutated (EGFR ^m) NSCLC patients, with exon 19 deletions or exon 21 L858R mutations, as compared to EGFR wild type (EGFR ^wt). The brain was classified as an anatomic "sponge", with a higher ratio of incoming to outgoing spread, for EGFR ^m NSCLC. Bone metastases were more commonly identified in EGFR ^wt patients. Our study supports a link between the anatomical and molecular characterization of lung metastatic cancer. Improved understanding of the differential biology that drives discordant patterns of anatomic spread, based on genotype specific profiling, has the potential to improve personalized oncologic care.

Figure 1

Kaplan-Meier curves depict survival of NSCLC patients with EGFR^m and EGFR^wt tumors (all stages)

Figure 2

Histogram showing the frequency of most common metastatic sites among non-small cell lung cancer patients with EGFR mutations and EGFR wild type

Figure 3

Spatiotemporal progression diagrams over a 5 year period for (a) EGFR^m and (b) EGFR^wt lung cancer. Innermost to outermost ring illustrates progression patterns from primary lung (inner golden ring) through formation of metastases (subsequent rings). The circular arc length of each ring represents the percentage of patients that progressed to that particular metastasis.

Figure 4

Markov chain network diagrams for (a) EGFR^m and (b) EGFR^wt lung cancer shown as circular chord diagrams with primary located at the 12:00 position. Metastatic sites are ordered clockwise from the primary in decreasing transition probability. Chord widths at their respective starting locations represent one-step transition probabilities between two sites.

Figure 5

Reduced Markov diagrams showing the top 30 two-step pathways emanating from primary lung cancer (outer golden ring) for (a) EGFR^m and (b) EGFR^wt. The bottom value indicates the percentage of all two-step pathways that the figure represents. Nodes are classified as a “spreader” (red) or “sponge” (blue) based on the ratio of their outgoing and incoming probabilities. Two-step probabilities as well as P_in and P_out values can be found under Supplemental Figures.