Tumor Classification of Six Common Cancer Types Based on Proteomic Profiling by MALDI Imaging

Citations Over TimeTop 10% of 2012 papers

Abstract

In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastatic tumor, especially if no apparent primary tumor is present. Tissue-based proteomics might allow correct tumor classification. As a result, we performed MALDI imaging to generate proteomic signatures for different tumors. These signatures were used to classify common cancer types. At first, a cohort comprised of tissue samples from six adenocarcinoma entities located at different organ sites (esophagus, breast, colon, liver, stomach, thyroid gland, n = 171) was classified using two algorithms for a training and test set. For the test set, Support Vector Machine and Random Forest yielded overall accuracies of 82.74 and 81.18%, respectively. Then, colon cancer liver metastasis samples (n = 19) were introduced into the classification. The liver metastasis samples could be discriminated with high accuracy from primary tumors of colon cancer and hepatocellular carcinoma. Additionally, colon cancer liver metastasis samples could be successfully classified by using colon cancer primary tumor samples for the training of the classifier. These findings demonstrate that MALDI imaging-derived proteomic classifiers can discriminate between different tumor types at different organ sites and in the same site.

Related Papers

• Clinicopathologic features and risk factors for hepatocellular carcinoma: results from a single center in southern Turkey.(2003)
• Spontaneous rupture of hepatocellular carcinoma.(2002)
• Pathology of hepatocellular carcinoma(2006)
• The medical management of hepatocellular carcinoma (HCC) in Japan: a review with implications for HCC seen in the west.(1997)
• Analysis of the influence factors of serum alpha-fetoprotein levels in patients with hepatocellular carcinoma(2001)