Molecular assessment of surgical-resection margins of gastric cancer by mass-spectrometric imaging

Significance Complete resection of a tumor is associated with an improved prognosis for most types of solid malignancies. In gastric-cancer surgery, surgical-margin evaluation is commonly performed intraoperatively by histopathologic evaluation of frozen sections. However, frozen-section results are subjective and can be unreliable in up to 30% of patients undergoing resection of gastrointestinal cancers. We used desorption electrospray ionization mass spectrometric imaging (DESI-MSI) and the statistical method of least absolute shrinkage and selection operator (Lasso) to classify tissue as cancer or normal based on molecular information obtained from tissue and also to select those mass-spectra features most indicative of disease state. The results obtained using margin samples from nine gastric-cancer operations suggest that DESI-MSI/Lasso may be a valuable tool for routine intraoperative assessment of surgical margins during gastric-cancer surgery. Surgical resection is the main curative option for gastrointestinal cancers. The extent of cancer resection is commonly assessed during surgery by pathologic evaluation of (frozen sections of) the tissue at the resected specimen margin(s) to verify whether cancer is present. We compare this method to an alternative procedure, desorption electrospray ionization mass spectrometric imaging (DESI-MSI), for 62 banked human cancerous and normal gastric-tissue samples. In DESI-MSI, microdroplets strike the tissue sample, the resulting splash enters a mass spectrometer, and a statistical analysis, here, the Lasso method (which stands for least absolute shrinkage and selection operator and which is a multiclass logistic regression with L1 penalty), is applied to classify tissues based on the molecular information obtained directly from DESI-MSI. The methodology developed with 28 frozen training samples of clear histopathologic diagnosis showed an overall accuracy value of 98% for the 12,480 pixels evaluated in cross-validation (CV), and 97% when a completely independent set of samples was tested. By applying an additional spatial smoothing technique, the accuracy for both CV and the independent set of samples was 99% compared with histological diagnoses. To test our method for clinical use, we applied it to a total of 21 tissue-margin samples prospectively obtained from nine gastric-cancer patients. The results obtained suggest that DESI-MSI/Lasso may be valuable for routine intraoperative assessment of the specimen margins during gastric-cancer surgery.