Dan Liu
7 Papers
Dan Liu is an academic researcher. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 1, co-authored 1 publications.
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Papers
A multi‐analyte cell‐free DNA–based blood test for early detection of hepatocellular carcinoma
Nan Lin,Yongping Lin,Jianfeng Xu,Dan Liu,Diange Li,Hongyu Meng,Maxime A. Gallant,Naoto Kubota,Dhruvajyoti Roy,J. S. Li,Emmanuel C. Gorospe,Morris Sherman,Robert G. Gish,Ghassan K. Abou-Alfa,M. Hong Nguyen,David Taggart,Richard A. Van Etten,Yujin Hoshida,Wei Li +18 more
TL;DR: The HelioLiver Test showed superior performance for HCC detection compared to with both AFP and the GALAD score and warrants further evaluation in HCC surveillance settings.
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Genotyping of Circulating Tumor DNA Reveals the Clinically-actionable Mutation Landscape of Advanced Colorectal Cancer
Weiguo Cao,Yaping Xu,Lianpeng Chang,Yuhua Gong,Liren Li,Xianwei Mo,Xin Zhang,Guole Lin,Jiaolin Zhou,Dan Liu,Yuting Yi,Pingping Dai,Chenchen Zhu,Liu Tao,Yuxing Chu,Yanfang Guan,Yongsheng Chen,Jiayin Wang,Xuefeng Xia,Ling Yang,Xin Yi,Yong Cheng +21 more
TL;DR: Comprehensive ctDNA genotyping is a promising noninvasive alternative to biopsy-derived analysis for determining targeted therapy in advanced colorectal cancer and shows favorable concordance with tumor tissues in the authors' matched analysis.
Tumour mutational burden and immune-cell infiltration in cervical squamous cell carcinoma
TL;DR: A relationship between high TMB standards and the development of cervical squamous cell carcinoma was observed, but an immune prognostic model was not presented, and the survival curve was not clinically significant, but a correlation was observed betweenhigh TMB levels and tumour grade.
1
Plasma cell-free DNA integrative analysis for early detection of hepatocellular carcinoma.
Peiyao Nie,Fang Lv,Shuying He,Tiancheng Han,S. Yang,Li Suxing,Dan Liu,Ying Yang,Yulong Li,Yu S. Huang,Yuanyuan Hong,Weizhi Chen,Jianing Yu,Haidong Tan +13 more
TL;DR: A machine learning approach to comprehensively integrate multiple types of cancer genomic markers from enzyme-conversion-based low-pass whole-methylome sequencing of plasma cfDNA to non-invasively detect hepatocellular carcinoma is developed.
Sensitive detection of pancreatic adenocarcinoma using plasma cell-free DNA methylomes.
Peiyao Nie,Fang Lv,Shuying He,Tiancheng Han,S. Yang,Li Suxing,Dan Liu,Ying Yang,Yulong Li,Yu S. Huang,Yuanyuan Hong,Weizhi Chen,Jianing Yu,Yongjun Sun +13 more
TL;DR: A machine learning approach to comprehensively integrate multiple types of cancer genomic markers from enzyme-conversion-based low-pass whole-methylome sequencing of plasma cfDNA to non-invasively detect pancreatic adenocarcinoma is developed.