A robust microsatellite instability detection model for unpaired colorectal cancer tissue samples.
10.1097/CM9.0000000000002216
- Author:
Zili ZHANG
1
;
Hua WAN
2
;
Bing XU
2
;
Hongyang HE
3
;
Guangyu SHAN
2
;
Jingbo ZHANG
2
;
Qixi WU
2
;
Tong LI
4
Author Information
1. Department of General Surgery, The Third Central Clinical College of Tianjin Medical University, The Third Central Hospital of Tianjin, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, Tianjin 300170, China.
2. Department of Medicine, Beijing USCI Medical Laboratory, Beijing 100195, China.
3. Department of General Surgery, The First Affiliated Hospital of Dali University, Dali, Yunnan 671013, China.
4. Department of Heart Center, The Third Central Clinical College of Tianjin Medical University, The Third Central Hospital of Tianjin, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, Tianjin 300170, China.
- Publication Type:Journal Article
- MeSH:
Humans;
Microsatellite Instability;
Colorectal Neoplasms/diagnosis*;
Microsatellite Repeats/genetics*;
DNA Mismatch Repair
- From:
Chinese Medical Journal
2023;136(9):1082-1088
- CountryChina
- Language:English
-
Abstract:
BACKGROUND:Microsatellite instability (MSI) is a key biomarker for cancer immunotherapy and prognosis. Integration of MSI testing into a next-generation-sequencing (NGS) panel could save tissue sample, reduce turn-around time and cost, and provide MSI status and comprehensive genomic profiling in single test. We aimed to develop an MSI calling model to detect MSI status along with the NGS panel-based profiling test using tumor-only samples.
METHODS:From January 2019 to December 2020, a total of 174 colorectal cancer (CRC) patients were enrolled, including 31 MSI-high (MSI-H) and 143 microsatellite stability (MSS) cases. Among them, 56 paired tumor and normal samples (10 MSI-H and 46 MSS) were used for modeling, and another 118 tumor-only samples were used for validation. MSI polymerase chain reaction (MSI-PCR) was performed as the gold standard. A baseline was built for the selected microsatellite loci using the NGS data of 56 normal blood samples. An MSI detection model was constructed by analyzing the NGS data of tissue samples. The performance of the model was compared with the results of MSI-PCR.
RESULTS:We first intersected the target genomic regions of the NGS panels used in this study to select common microsatellite loci. A total of 42 loci including 23 mononucleotide repeat sites and 19 longer repeat sites were candidates for modeling. As mononucleotide repeat sites are more sensitive and specific for detecting MSI status than sites with longer length motif and the mononucleotide repeat sites performed even better than the total sites, a model containing 23 mononucleotide repeat sites was constructed and named Colorectal Cancer Microsatellite Instability test (CRC-MSI). The model achieved 100% sensitivity and 100% specificity when compared with MSI-PCR in both training and validation sets. Furthermore, the CRC-MSI model was robust with the tumor content as low as 6%. In addition, 8 out of 10 MSI-H samples showed alternations in the four mismatch repair genes ( MLH1 , MSH2 , MSH6 , and PMS2 ).
CONCLUSION:MSI status can be accurately determined along the targeted NGS panels using only tumor samples. The performance of mononucleotide repeat sites surpasses loci with longer repeat motif in MSI calling.
