The performance of MTAP homozygous deletion detection based on next-generation sequencing technology.

L Lu Meng Y Yan Zhang X Xinhua Du (Geneplus-Beijing Institute, Beijing, China) S Shicheng Feng (Geneplus-Beijing Institute, Beijing, China) H Heyu Sheng (Geneplus-Beijing Institute, Beijing, China) Y Yun Xing (MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering) Y Yadi Cheng (Geneplus-Beijing Institute, Beijing, China) Y Yanfang Guan (Geneplus-Beijing Institute, Beijing, China) X Xin Yi (Key Laboratory of Crop Integrated Pest Management in South China, Ministry of Agriculture, Department of Pesticide Science, College of Plant Protection, South China Agricultural University)

Abstract

e14571 Background: Homozygous deletion of the MTAP occurs in 10-15% of all human cancers. MTAP catalyzes the conversion of MTA (S-adenosylmethionine) into methionine, playing a role in cellular energy metabolism and protein synthesis. Currently, numerous PRMT5 inhibitor drugs are being developed. Accurately detecting the status of MTAP is particularly important. Until recently, fluorescence in situ hybridization (FISH) served as the gold standard for detection of 9p21 loss. However, there is an increasing demand for NGS-based of MTAP deletion detection due to its ease of application and cost-effectiveness. Therefore, we have developed a panel-based detection method that can accurately determine deletion status of MTAP. Methods: In this study, we utilized a NGS panel that covers more than 2000 SNP loci within the genome. The sequencing depth was greater than 500X. To obtain the absolute copy number of the tumor, an algorithm was employed to correct the log2Ratio for each bin by utilizing the offset between tumor purity and log2Ratio. To validate the accuracy of this method, clinical samples from 41 cases were selected for simultaneous FISH testing and the NGS panel detection mentioned above. An additional 1260 clinical samples were selected for NGS testing to confirm the incidence of all exon deletions and partial loss. Results: All samples were successfully detected. Among 41 cases, FISH and NGS accurately identified 28 homozygous deletions and 11 heterozygous deletions; 2 samples incorrectly identified. The overall consistency in status determination reached 95% (39/41). Using the above algorithm to evaluation additional samples, 17% of the deletions can be accurately identified, including 60.7% of homozygous deletion. The detection rates of MTAP homozygous deletion in different cancer types are similar to the TCGA data. Specifically, it was observed that non-small cell lung cancer had a frequency of 16.7%, head and neck cancer of 17.3%, urothelial carcinoma of 40.4%, colorectal of 3.0%, pancreatic of 18.0%, glioma of 21.0%, and esophageal of 19.5%. The algorithm can accurately categorize all identified deletions into two groups: 13.8% complete gene deletions and 3.2% partial exon deletions. The multiple exon loss frequcies inclued exon 5-8 loss in 2.8% , exon 6-8 loss in 1.4%, exon 7-8 loss in 4.7% , exon 8 loss in 7.5% and other less common multi-exon losses. Conclusions: The NGS-based method established in this study for detecting MTAP deletion demonstrates a high consistency of 95% with FISH. Furthermore, it shows superior performance to FISH in detecting partial exon loss. This research method holds potential for application in companion diagnostics for drug therapy. Frequency of homozygous deletion in different cancers. Cancer Complete exons loss Partial exons loss NSCLC 15.5% 1.2% HNC 5.8% 11.5% UC 38.6% 1.8% CRC 0.7% 2.3% PAAD 14.0% 4.0% GBM 14.3% 6.7% ESCA 15.2% 4.3%

Article Details

Volume / Issue Vol. 43, Issue 16_suppl
Published June 01, 2025
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (9)

L

Lu Meng

Y

Yan Zhang

X

Xinhua Du

Geneplus-Beijing Institute, Beijing, China

S

Shicheng Feng

Geneplus-Beijing Institute, Beijing, China

H

Heyu Sheng

Geneplus-Beijing Institute, Beijing, China

Y

Yun Xing

MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering

Y

Yadi Cheng

Geneplus-Beijing Institute, Beijing, China

Y

Yanfang Guan

Geneplus-Beijing Institute, Beijing, China

X

Xin Yi

Key Laboratory of Crop Integrated Pest Management in South China, Ministry of Agriculture, Department of Pesticide Science, College of Plant Protection, South China Agricultural University