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1805 Highly Sensitive Chip-Based Digital PCR Platform for Quantitative Detection of BCR::ABL1 Transcripts throughout CML Treatment

Program: Oral and Poster Abstracts
Session: 632. Chronic Myeloid Leukemia: Clinical and Epidemiological: Poster I
Hematology Disease Topics & Pathways:
Research, clinical trials, Clinical Research, Technology and Procedures, Minimal Residual Disease , molecular testing
Saturday, December 9, 2023, 5:30 PM-7:30 PM

Hyun-Woo Song1*, Sung-Hyun Kim, MD2*, Young Rok Do, PhD, MD3, Kyung-Mi Ki, MS4*, Soo Hyun Kim, MS4*, Min-Sik Song, PhD5*, Seung-Shick Shin, PhD5* and Dong-Wook Kim, MD, PhD6

1Optolane, Seongnam-Si, South Korea
2Dong-A University Hospital, Busan, Korea, Republic of (South)
3Dongsan Medical Center, Keimyung University, Daegu, Korea, Republic of (South)
4Uijeongbu Eulji Medical Center, Uijeoungbu, Korea, Republic of (South)
5Optolane Technologies, Seongnam, Korea, Republic of (South)
6Uijeongbu Eulji Medical Center, Uijeoungbu-si, Korea, Republic of (South)

Introduction: With various BCR::ABL1 tyrosine kinase inhibitors (TKIs), chronic myeloid leukemia (CML) has become a manageable disease and current therapeutic goal is treatment-free remission (TFR). To achieve a successful TFR in more patients, a precise assessment of minimal residual disease (MRD) is one of the prerequisite requirements.

Since undetectable BCR::ABL1 fusion transcripts by conventional Taqman™-based quantitative polymerase chain reaction (qPCR) is not an indicator for complete eradication of the CML clone, it requires the development of more sensitive technologies.

Currently, to overcome some limitations of conventional qPCR, such as rigorous standardization process and variations in sensitivity between laboratories, digital quantitative-PCR (dqPCR) methods have been developed for accurate and precise detection and its use in the routine clinical practice is gradually expanding.

However, current dqPCR methods require the inclusion of one or more negative partitions to calculate the concentration using Poisson distribution. Consequently, this leads to a more than a 10-fold decrease in the maximum detectable concentration in a single test compared to conventional qPCR.

Therefore, we have developed a novel technology, High Dynamic Range Digital Real-time PCR (so called HDR-drPCR) to achieve wider dynamic range, which allows more stable, accurate and sensitive monitoring of BCR::ABL1 in a timely manner.

Methods: For linearity assessment, we used BCR::ABL1 positive (e14a2) K562 cell line diluted to 7 points by 10-fold serial dilutions from 25 to 2.5x10-5 %IS with BCR::ABL1 negative HL60 cells.

In HDR-drPCR, the GUSB gene was employed as a control gene to determine %IS values. For this purpose, the 1st WHO international genetic reference panel was utilized to calculate the correction factor (CF).

With the results from cell lines, we also evaluated equivalence between conventional qPCR and HDR-drPCR using 219 clinical specimens. Among them, 100 samples were determined as DMR (<0.01%IS) based on the qPCR test results

In detail, conventional qPCR was performed using Transcriptor First Strand cDNA Synthesis Kit (Roche, USA) for cDNA synthesis and Real-Q BCR-ABL Quantification Kit (Biosewoom, South Korea) for qPCR.

For HDR-drPCR (1-step reverse transcriptase PCR), 106 to 107 copies per reaction of GUSB gene were applied to disposable cartridges of Genotizer™ HDR BCR::ABL1 Major IS detection kit (Optolane Technologies, South Korea) with LOAA platform (Optolane Technologies, Korea).

Based on the results, correlation analysis between qPCR and HDR-drPCR was performed using correlation graphs and Blend-Altman plots.

Results: Linearity was assessed by the dilution of RNA of K562 with RNA of HL60 using 10-fold serial dilution of up to - 7 log. The result showed accurate linearity (R2 = 0.9972) at the range of BCR::ABL1/GUSB ratio of 101 to 10-5(%). Notably, HDR-drPCR technology allowed to detect the level of BCR::ABL1 transcript of MR 6.34 (0.00005 %IS) (Figure 1A).

The correlation analysis for 209 clinical samples showed that measured values from both qPCR and HDR-drPCR were closely correlated with the R2 of 0.9731 (Figure 1B). The Bland-Altman plot showed a mean bias of 0.159, and the limit of agreement at the 95% confidence interval (LOA95) was calculated as -0.387 to 0.705. Furthermore, the concordance rate between the two methods was 96.17%, as measured by the proportion of samples in which the difference between the two methods was within a factor of 5. This indicates a strong concordance between the two methods.

HDR-drPCR reliably detected BCR::ABL1 transcripts in all 90 clinical specimens measured below 0.01%IS (DMR) using qPCR. Additionally, HDR-drPCR detected trace amounts of BCR::ABL1 transcripts in 6 out of 10 specimens that were not detected by qPCR, showcasing its improved sensitivity compared to the conventional qPCR method.

Conclusion: Taken together, we believe our high dynamic range real-time digital PCR(HDR-drPCR) may minimize false positive results and maximize the analytical sensitivity of detecting BCR::ABL1 fusion transcripts and thus, would be useful for accurately assessing treatment in routine clinical practice and facilitating the application of treatment-free remission (TFR). We will include these results in further intensive studies focusing on DMR clinical specimens

Study support: Funded by Korea Research Foundation

Disclosures: Song: Optolane: Current Employment. Song: Optolane: Current Employment. Shin: Optolane: Current Employment.

*signifies non-member of ASH