Lijing Gao
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Lijing Gao has a total of 20 co-authors. Here are the top co-authors by number of shared publications:
Chao Qu
Department of Epidemiology, School of Public Health, Harbin Medical University, Harbin, P.R. China
1 shared publication- Da Pang
Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, 150081, China
1 shared publication - Fan Wang
Department of Epidemiology, School of Public Health, Harbin Medical University
1 shared publication Fang Fang
Department of Breast Surgery, Cancer Hospital of Harbin Medical University, Harbin Medical University, Harbin, P.R. China
1 shared publicationJinyin Liu
Department of Epidemiology, School of Public Health, Harbin Medical University, Harbin, P.R. China
1 shared publicationJunxiao Wu
Department of Epidemiology, School of Public Health, Harbin Medical University, Harbin, P.R. China
1 shared publication
Latest Publications
- Open Access
- 16 June 2025
- Published by Springer Nature in Breast Cancer Research
- Vol. 27 (1) , 1-13
Discovery and validation of cell-free DNA methylation markers for specific diagnosis, differentiation from benign tumors, and prognosis of breast cancer
Plasma cell-free DNA (cfDNA) methylation is emerging as a non-invasive marker for various cancers. We aimed to identify specific methylation markers for diagnosis, differentiation from benign tumors, and prognosis of breast cancer (BC), which are essential for clinical decision-making yet seldom examined together. BC-specific methylation markers were identified using an in-house 850K dataset combined with large-scale publicly available 450 or 850K datasets. Multiplex digital droplet PCR (mddPCR) assays were developed to detect methylation in cfDNA from 201 BC patients, 83 healthy donors, and 71 individuals harboring benign tumors. Diagnostic and prognostic performance were evaluated using logistic and Cox regression models, respectively. The basic mechanism of a selected gene was explored through in vitro experiments. We identified 21 BC-specific methylated CpG sites that distinguished BC from tumor-adjacent tissues with high diagnostic accuracy. In the cfDNA cohort, three mddPCR assays targeting eight markers achieved an area under the curve (AUC) of 0.856 (95% CI = 0.814–0.898) for distinguishing BC from healthy controls, and 0.742 (95% CI = 0.684–0.801) for differentiating BC from benign tumors. Notably, combining these methylation markers with mammography and ultrasound improved diagnostic performance, resulting in an AUC of 0.898 (95% CI = 0.858–0.938) for differentiating BC from benign tumors. In the TCGA-BC dataset, prognostic model based on six sites was associated with poor overall survival prognosis (hazard ratio = 2.826, 95%CI: 1.841–4.338, p < 0.0001). In vitro experiments elucidated that FAM126A overexpression regulates BC cells malignant phenotypes. Our study demonstrated potential values of methylation-based markers in the detection and prognosis of BC.
- 16 June 2025
- Published by Springer Nature in Breast Cancer Research
- Vol. 27 (1) , 1-13
Open AccessDiscovery and validation of cell-free DNA methylation markers for specific diagnosis, differentiation from benign tumors, and prognosis of breast cancer
Plasma cell-free DNA (cfDNA) methylation is emerging as a non-invasive marker for various cancers. We aimed to identify specific methylation markers for diagnosis, differentiation from benign tumors, and prognosis of breast cancer (BC), which are essential for clinical decision-making yet seldom examined together. BC-specific methylation markers were identified using an in-house 850K dataset combined with large-scale publicly available 450 or 850K datasets. Multiplex digital droplet PCR (mddPCR) assays were developed to detect methylation in cfDNA from 201 BC patients, 83 healthy donors, and 71 individuals harboring benign tumors. Diagnostic and prognostic performance were evaluated using logistic and Cox regression models, respectively. The basic mechanism of a selected gene was explored through in vitro experiments. We identified 21 BC-specific methylated CpG sites that distinguished BC from tumor-adjacent tissues with high diagnostic accuracy. In the cfDNA cohort, three mddPCR assays targeting eight markers achieved an area under the curve (AUC) of 0.856 (95% CI = 0.814–0.898) for distinguishing BC from healthy controls, and 0.742 (95% CI = 0.684–0.801) for differentiating BC from benign tumors. Notably, combining these methylation markers with mammography and ultrasound improved diagnostic performance, resulting in an AUC of 0.898 (95% CI = 0.858–0.938) for differentiating BC from benign tumors. In the TCGA-BC dataset, prognostic model based on six sites was associated with poor overall survival prognosis (hazard ratio = 2.826, 95%CI: 1.841–4.338, p < 0.0001). In vitro experiments elucidated that FAM126A overexpression regulates BC cells malignant phenotypes. Our study demonstrated potential values of methylation-based markers in the detection and prognosis of BC.