Quantitative RTPCR

Technologically, quantitative RT-PCR has evolved from the initial use of competitive and limiting dilution RT-PCR methods to real-time RT-PCR methods. Competitive RT-PCR is labor-intensive, technically demanding, time-consuming and lacks standardization. Therefore, real-time RT-PCR is the most common method currently used (see chapter 2).

Real-time RT-PCR affords sensitive, rapid, and reproducible quantification of the BCR-ABL1 fusion transcripts. A closed-tube system is employed, which eliminates the need for post-PCR processing and minimizes the potential for contamination while simultaneously decreasing testing time.

Figure 35-6. Schematic representation of real-time RT-PCR. (a) Amplification plot with known BCR-ABL1 standards and an unknown patient sample. The increase in fluorescence intensity reflects the increase in PCR products generated during amplification. The initial template concentration dictates the cycle number at which fluorescence increases above the threshold level,CT. (B) Standard curve from which the unknown BCR-ABL1 copy number is determined.

Although the sensitivity of real-time RT-PCR methods is somewhat less than conventional or nested RT-PCR, the dynamic range of fluorescent detection is much broader, spanning 5 to 6 orders of magnitude, with a lower limit of detection of <0.01%.26 Most important, real-time RT-PCR has the precision required in clinical diagnostic applications.

Various fluorescent detection systems have been used to quantify BCR-ABL1 transcripts. The major chemistries employed are the Taqman31 or FRET probe32 methods. For both of these, RNA or complementary DNA (cDNA) standards of known concentration are used to generate a standard curve (log copy number versus threshold cycle [Ct]), from which the unknown sample quantity is determined (Figure 35-6) and then normalized against an internal reference (e.g., ABL1 transcripts). The final result is reported as a percentage ratio (e.g., BCR-ABL1/ABL1), although alternative methods of reporting include copy number or micrograms of RNA, or both. Other methods include molecular beacons and melting-curve analysis (see chapter 2).

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