Integrated Analysis of Single-Cell and Bulk RNA-Sequencing Based on EcoTyper Machine Learning Framework Identifies Cell-State-Specific M2 Macrophage Markers Associated with Gastric Cancer Prognosis
A-Kao Zhu, Guang-Yao Li, Fang-Ci Chen, Jia-Qi Shan, Yu-Qiang Shan, Chen-Xi Lv, Zhi-Qiang Zhu, Yi-Ren He, Lu-Lu Zhai · 2024
Read Integrated Analysis of Single-Cell and Bulk RNA-Sequencing Based on EcoTyper Machine Learning Framework Identifies Cell-State-Specific M2 Macrophage Markers Associated with Gastric Cancer Prognosis by A-Kao Zhu, Guang-Yao Li, Fang-Ci Chen, Jia-Qi Shan, Yu-Qiang Shan, Chen-Xi Lv, Zhi-Qiang Zhu, Yi-Ren He, Lu-Lu Zhai (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11646439.txt.
Description
A-Kao Zhu and co-authors search for marker genes of a tumor-friendly immune cell state in stomach cancer. Their study appeared in 2024. Tumors grow inside a busy neighborhood of cells, and macrophages are key residents. One flavor of macrophage, called M2, helps tumors rather than fighting them. The team joined single-cell gene data with bulk gene data and ran them through a learning framework called EcoTyper.
The framework sorted tumor macrophages into states and neighborhoods. It yielded 168 marker genes tied to the M2 state. Those markers split patients into two groups with different outlooks, linking the cell state to prognosis. The authors say the markers could guide prognosis and, in time, treatments that re-educate tumor macrophages.
Catalog record
| CREATOR | A-Kao Zhu, Guang-Yao Li, Fang-Ci Chen, Jia-Qi Shan, Yu-Qiang Shan, Chen-Xi Lv, Zhi-Qiang Zhu, Yi-Ren He, Lu-Lu Zhai |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 31 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |