Fumagalli et al. BMC Cancer 2010, 10:101 http://www.biomedcentral.com/1471-2407/10/101 samples. Sanger sequencing would require amplification of at least 60 different fragments per sample, and many reactions would require optimization, thus adding con- siderable time and expense. Multiplexing and the use of the OncoCarta panel allowed us to skip this time con- suming step. Thus, conservatively, Sanger sequencing would be 40 times more expensive, and require at least 2 times more DNA. Other sequencing technologies, which employ differential melting of mutant and wt sequences, such as HRMA, still require that the PCR product be sequenced. This would add significant cost and time to the procedure because 60% of the colon samples contained one or more mutations. In addition the Sequenom platform is more sensitive than Sanger sequencing in that it was able to detect mutations that represented only 5% of the DNA. Pyrosequencing repre- sented a potential alternative to the Sequenom platform, but in our hands assays needed to be optimized, and the lack of multiplexing made the procedure more time consuming and demanded more DNA. The Sequenom methodology also focuses on only those nucleotides that are known to be cancer mutations and thus makes review of the sequence information considerably faster than Sanger. Next-Generation sequencing was cost pro- hibitive and has not been shown to work with DNAs isolated from FFPET. Thus, the Sequenom platform and the OncoCarta Panel provided the simplest, most rapid, sensitive and cost-effective method for detecting hot spot cancer mutations in degraded DNAs isolated from archival and routinely processed FFPET. The ColoCarta panel provides a more specific panel for colon cancer mutation detection and greatly reduces the amount of DNA needed for mutation profiling. The frequencies and specific amino acid mutations detected here were similar to the COSMIC database and other publications [6]. The small variation in frequency between our data and other reports may be attributed to differences in the stage of the samples analyzed, the number of samples considered, and the sensitivity of the technology [18]. These observations, combined with the perfect match that we obtained between the expected and the detected mutations in our control cell lines, both fresh and FFPE, and the fact that mutations detected with OncoCarta and ColoCarta were identical, suggest that the technology is reliable and reproducible in DNAs isolated from FFPE samples. In our study, the majority of tumors (60.3%) had one or more mutations in KRAS, PIK3CA, and BRAF. Muta- tions in these genes are likely to perturb many different and overlapping signaling pathways, including PI3K/ AKT, ERK/MAPK, SAPK/JNK, NFKb, and others. We were also able to detect other less frequent mutations that are likely to perturb the same pathways and these may cause resistance to EGFR-targeted therapies, as Page 12 of 14 reported for KRAS, PIK3CA and BRAF. For example, AKT1 and NRAS are molecules that are downstream mediators of the EGFR signaling pathway, and muta- tions in these genes are likely to affect the response to drugs that target EGFR. Mutations in ABL, AKT1, and MET were detected here but were not listed in COSMIC, probably due to the small number of samples analyzed. The AKT1-E17K mutation was initially identified as a SNP, rs34409589, but in a recent publication it was found to be a somatic mutation and was found in 3 of 51 colon cancers [27]. The frequency of these mutations in this small study (51 samples) was 6% and is much greater than in the C0-7 samples (0.4%). This difference in frequencies may be because the Carpten et al [27] samples were from more advanced stages than those from the C-07 trial. More- over, they selected large tumors (>100 mg) and contain- ing more than 60% tumor cells. No such selection was done for our study, and samples were from stages II and III exclusively. The significance of ABL1 and AKT1 muta- tions for patient prediction and prognosis in our study is questionable given that they each were found in only in one sample and represented only 0.4% of the cases. To our knowledge, this is the first report of MET mutations in the primary colon cancer, but a different MET mutation (N1118Y) was found in a lung metastasis of the large intestine [28]. The MET mutations, R970C and T992I, were detected in 8 out of 239 C-07 colon cancers. These mutations correspond to MET-R988C and MET-T1010I, respectively, in the long form of MET which is the isoform referred to in the COSMIC data- base [29]. The R970C and T992I mutations are located in the juxtamembrane segment of the protein and were detected in lung carcinoma [30]. These mutations, when introduced into a lung cell line, increased focus forma- tion, formation of colonies in soft agar, cell motility, and migration. These mutations also resulted in constitutive tyrosine phosphorylation on several cellular proteins including paxillin at key tyrosine residues and may account for the increased motility of cells with this mutation. Another critical amino acid in this location is a Ser 985, which, when phosphorylated, has been found to diminish MET signaling [31]. If phosphorylation at Thr residue 992 (1010) reduces signaling, then the R992I mutation would inhibit this negative feedback and may result in constitutive signaling [30]. If MET mutations confer an alternative activated sig- naling pathway, then these mutations could also confer resistance to anti-EGFR-based therapies or provide a new target for directed therapies. Therapeutic drugs have been developed to specifically target MET, includ- ing small molecule kinase inhibitors, anti-MET mono- clonal antibodies, and inhibitors of HGF, the MET ligand. Invitro assays have demonstrated that a number