qBiomarker Somatic Mutation PCR Arrays

We recommend using the QIAGEN QIAamp DNA Mini Kit for DNA isolation, with the recommended RNase step. For sample quality, we recommend assaying for DNA concentration & purity with a UV Spectrophotometer; for DNA Integrity, an agarose gel should be run; and DNA quality and consistency can be checked on the Somatic Mutations QC plate that measures 7 reference genes by RT-PCR.

For pathway-focused arrays, we included assays for detecting the most frequent and functionally verified mutations for multiple genes within a specific pathway implicated in a variety of cancers. Additional assays are also available for each gene to allow array customization. For disease-focused arrays, we selected top somatic mutations for that disease type covering between 4,000 and 40,000 published tumor samples for each disease type.

The pathways covered include major receptor tyrosine kinase pathways, non-receptor kinase pathways, as well as additional oncogene and tumor suppressor pathways; and the targeted diseases include all major cancer types. In addition, a collection of more than 800 pre-validated somatic mutation assays enables researchers to study single mutations or to customize the mutation panels or collections according to their research needs.

Real-time PCR is the most sensitive and reliable method for the detection of DNA mutations. By combining allele specific amplification and hydrolysis probe detection, we have developed real-time PCR assays that detects as low as 1% somatic mutations in the background of wild-type genomic DNA. Allele specific amplification is achieved by Amplification Refractory Mutation System (ARMS@) technology, which is based on the ability of Taq polymerase to discriminate between a match and a mismatch at the 3' end of the PCR primer.

Depending on the qBiomarker Somatic Mutation PCR Array that is chosen, one can profile between 40 and 360 mutations per sample in one PCR run.

Sanger sequencing and pyrosequencing can be used to validate the mutations identified on the arrays. However, one needs to bear in mind that the detection sensitivity of Sanger sequencing is around 20%, and the detection sensitivity of pyrosequencing is around 5%, while RT-PCR based arrays can detect 1% or lower mutations. Therefore, mutations occurring below the detection limit of Sanger sequencing and pyrosequencing will not be verified by these two methods.

The content for the Somatic Mutations PCR Array is derived from the COSMIC database, established by the Sanger Institute of the Wellcome Trust. (http://www.sanger.ac.uk/genetics/CGP/cosmic/)

The basic principle behind the data analysis is that we compare the Ct value of a mutation assay in a test sample with the Ct value of the same assay in a wildtype sample. When there is a significant difference (a preset value of 4 Cts) between the Ct values, the test sample is concluded to contain the mutation. The Ct values used for comparison can either be raw Ct (in average Ct method) or normalized Ct (in delta delta Ct case). When the Ct difference falls between 3 and 4, we give a borderline mutation call, which means that the mutation may be present at low percentage. When the Ct difference is smaller than 3, we give a negative mutation call (i.e. the mutation percentage is beyond the detection limit of the array). The wildtype sample can be either a genuine wildtype sample that is tested in the same experiment, or it could be a "virtual" wildtype sample that is computed from all test samples. For detailed description of the data analysis principle, refer to (link to white paper).

Each array contains gene copy reference assays for each gene represented by the array. These assays target non-variable regions of the genes and measure input DNA quality and amount. In addition, these assays sensitively measure gene dosage to normalize mutation assay data against the gene copy number. Each array also contains positive PCR controls (SMPC) to test for the presence of inhibitors in the sample or the efficiency of the polymerase chain reaction itself using a pre-dispensed artificial DNA sequence and the primer set that detects it.

The main advantages are qPCR-based superior detection sensitivity and straightforward data analysis procedure. Additional major advantages over other currently available mutation detection platforms/methods are: (1) The workflow is very simple, involving only one setup step. No multi-step handling is involved, and hands-on time is less than any other method available. (2) Reactions involved are all closed-tube reactions avoiding sample contamination. (3) The DNA sample input is low. (4) The hardware involved in analysis using the mutation detection arrays and assays is highly accessible, enabling such analysis for any laboratory with access to real-time PCR instruments.

The assays were validated to have at least 1% sensitivity (i.e. able to detect 1% mutation on a wildtype background), but the sensitivity is usually higher. On average, the assay sensitivity is 0.03%.

There are currently 13 different pathway-focused and 10 disease-focused Somatic Mutation PCR Arrays available, with each array assaying from 3 to 19 genes, and on average 5-30 mutations within each gene. Please refer to the individual product sheets/ product webpage for a full listing.

Poor quality samples tend to give higher Cts in all assays (mutation assays and gene copy number assays) and there are two possible consequences:

 (1) if using average Ct method for data analysis, even real mutations in poor quality samples will not be called, because the mutation locus Ct will be pushed to a high Ct region; (2) if using delta delta Ct method for data analysis, there will be a number of false positives in low quality samples.

We recommend using the average Ct value for gene copy number assays on the array to gauge the sample quality (or run the sample on a DNA QC plate before running samples on an array). For FFPE samples, we recommend the average Ct to be below 32 to allow sensitive detection of mutations. Samples that meet this criterion perform robustly on the arrays.

The choice between one of two data analysis methods depends on the experimental setup and sample type.

1. ΔΔCt Method Recommended for experiments using: Small (four or less) number of fresh, frozen samples Large number of samples with similar DNA quality

2. Average Ct Method Recommended for experiments using: FPPE samples, large number of samples or without wild-type control samples

Data analysis can either be performed on the somatic mutation data analysis web portal or by downloading the Excel data analysis templates at http://www.sabiosciences.com/somaticmutationdataanalysis.php

Each array contains a panel of assays bench-validated for hydrolysis probe based real-time RT-PCR detection. These assays are optimized to work under standard cycling conditions enabling a large number of assays to be analyzed simultaneously.