Single-cell transcriptomics reveal DHX9 in mature B cell as a dynamic network biomarker before lymph node metastasis in CRC.
Single-cell transcriptomics reveal DHX9 in mature B cell as a dynamic network biomarker before lymph node metastasis in CRC.
复制标题
单细胞转录组学揭示成熟 B 细胞中的 DHX9 作为 CRC 淋巴结转移前的动态网络生物标志物
DOI:
10.1016/j.omto.2021.06.004
复制
发表时间:
2021-09-24
期刊:
影响因子:
--
通讯作者:
Ling F
中科院分区:
文献类型:
--
作者:
Liu H;Zhong J;Hu J;Han C;Li R;Yao X;Liu S;Chen P;Liu R;Ling F
Increasing evidence indicates that mature B cells in the adjacent tumor tissue, both as an intermediate state, are vital in advanced colorectal cancer (CRC), which is associated with a low survival rate. Developing predictive biomarkers that detect the tipping point of mature B cells before lymph node metastasis in CRC is critical to prevent irreversible deterioration. We analyzed B cells in the adjacent tissues of CRC samples from different stages using the dynamic network biomarker (DNB) method. Single-cell profiling of 725 CRC-derived B cells revealed the emergence of a mature B cell subtype. Using the DNB method, we identified stage II as a critical period before lymph node metastasis and that reversed difference genes triggered by DNBs were enriched in the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway involving B cell immune capability. DHX9 (DEAH-box helicase 9) was a specific para-cancerous tissue DNB key gene. The dynamic expression levels of DHX9 and its proximate network genes involved in B cell-related pathways were reversed at the network level from stage I to III. In summary, DHX9 in mature B cells of CRC-adjacent tissues may serve as a predictable biomarker and a potential immune target in CRC progression. Based on single-cell transcriptomics, we used a novel method named dynamic network biomarkers to quantify the immune function of mature B cells in colorectal cancer (CRC)-adjacent tissues at regulatory networks and thus to predict the critical period before CRC metastasis as well as to uncover specific biomarkers.
登录
查看更多内容
影响因子:
46.9
作者:
Becht, Etienne;McInnes, Leland;Newell, Evan W.
通讯作者:
Newell, Evan W.
影响因子:
16.6
作者:
Aran D;Camarda R;Odegaard J;Paik H;Oskotsky B;Krings G;Goga A;Sirota M;Butte AJ
通讯作者:
Butte AJ
DOI:
10.3410/b2-87
发表时间:
2010-12-17
期刊:
F1000 biology reports
影响因子:
--
作者:
Harwood NE;Batista FD
通讯作者:
Batista FD
影响因子:
--
作者:
Guo, Fei Fei;Cui, Jiu Wei
通讯作者:
Cui, Jiu Wei
DOI:
10.1093/bioinformatics/btp101
发表时间:
2009-04-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Bindea G;Mlecnik B;Hackl H;Charoentong P;Tosolini M;Kirilovsky A;Fridman WH;Pagès F;Trajanoski Z;Galon J
通讯作者:
Galon J