Potential pitfalls in MitoChip detected tumor-specific somatic mutations: a call for caution when interpreting patient data

Published entire mitochondrial genomes from head and neck, adenoid cystic carcinoma, sessile serrated adenoma, and lung primary tumor from clinical patients were examined in a phylogenetic context and compared with known, naturally occurring mutations which characterize different populations.The phylogenetic linkage analysis of whole arrays of mtDNA mutations from patient cancerous and non-cancerous tissue confirmed that artificial recombination events occurred in studies of head and neck, adenoid cystic carcinoma, sessile serrated adenoma, and lung primary tumor. Our phylogenetic analysis of these tumor and control leukocyte mtDNA haplotype sequences shows clear cut evidence of mixed ancestries found in single individuals.Our study makes two prescriptions: both in the clinical situation and in research 1. more care should be taken in maintaining sample identity and 2. analysis should always be undertaken with respect to all the data available and within an evolutionary framework to eliminate artifacts and mix-ups.Mitochondrial DNA technology plays an exciting role in medical research especially the high throughput MitoChip for mtDNA mutation detection in cancer. In the past few years the MitoChip technique has uncovered a large number of mtDNA mutations in human head and neck, adenoid cystic carcinoma, sessile serrated adenoma, and lung primary tumors [1-6]. The majority of the MitoChip detected mutations were somatic (dominant in tumor cells) and it has been suggested that these mutations may be used as markers for the early diagnosis of cancer [2]. However, many of these early stages MitoChip detected cancer mutations require accurate validation before put into routine clinical practice. Many recorded mtDNA mutations in cancer samples are not fully reliable. Employing a phylogenetic analysis of mtDNA tumor profiles taken from a specific example in the literature, we demonstrate the pitfalls of using MitoChip identified mitochondrial mutations for clinical diagnos