  MET is a proto-oncogene whose somatic activation in non-small cell lung
cancer leads to increased cell growth and tumor progression. The two major
classes of MET alterations are gene amplification and exon 14 deletion, both of
which are therapeutic targets and detectable using existing molecular assays.
However, existing tests are limited by their consumption of valuable tissue,
cost and complexity that prevent widespread use. MET alterations could have an
effect on cell morphology, and quantifying these associations could open new
avenues for research and development of morphology-based screening tools. Using
H&E-stained whole slide images (WSIs), we investigated the association of
distinct cell-morphological features with MET amplifications and MET exon 14
deletions. We found that cell shape, color, grayscale intensity and
texture-based features from both tumor infiltrating lymphocytes and tumor cells
distinguished MET wild-type from MET amplified or MET exon 14 deletion cases.
The association of individual cell features with MET alterations suggested a
predictive model could distinguish MET wild-type from MET amplification or MET
exon 14 deletion. We therefore developed an L1-penalized logistic regression
model, achieving a mean Area Under the Receiver Operating Characteristic Curve
(ROC-AUC) of 0.77 +/- 0.05sd in cross-validation and 0.77 on an independent
holdout test set. A sparse set of 43 features differentiated these classes,
which included features similar to what was found in the univariate analysis as
well as the percent of tumor cells in the tissue. Our study demonstrates that
MET alterations result in a detectable morphological signal in tumor cells and
lymphocytes. These results suggest that development of low-cost predictive
models based on H&E-stained WSIs may improve screening for MET altered tumors.
