Construction of a Wilms tumor risk model based on machine learning and identification of cuproptosis-related clusters
Jingru Huang, Yong Li, Xiaotan Pan, Jixiu Wei, Qiongqian Xu, Yin Zheng, Peng Chen, Jiabo Chen · 2024
Read Construction of a Wilms tumor risk model based on machine learning and identification of cuproptosis-related clusters by Jingru Huang, Yong Li, Xiaotan Pan, Jixiu Wei, Qiongqian Xu, Yin Zheng, Peng Chen, Jiabo Chen (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-11536559.txt.
Description
Jingru Huang and seven co-authors build a risk model for a child kidney tumor in a 2024 study. The tumor, called Wilms tumor, is the most common kidney cancer of childhood. A fresh-found form of cell death, set off by copper, may shape how the tumor grows, but its inner role was murky.
The team pulled four gene data sets from a shared bank and scanned genes tied to the copper death path. From 105 tumor samples they found groups with like gene marks. They then built a learning model to sort risk, and mapped immune cells in each group. The work may guide care picks.
Catalog record
| CREATOR | Jingru Huang, Yong Li, Xiaotan Pan, Jixiu Wei, Qiongqian Xu, Yin Zheng, Peng Chen, Jiabo Chen |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 42 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |