Identification and validation of the nicotine metabolism-related signature of bladder cancer by bioinformatics and machine learning
Yating Zhan, Min Weng, Yangyang Guo, Dingfeng Lv, Feng Zhao, Zejun Yan, Junhui Jiang, Yanyi Xiao, Lili Yao · 2024
Read Identification and validation of the nicotine metabolism-related signature of bladder cancer by bioinformatics and machine learning by Yating Zhan, Min Weng, Yangyang Guo, Dingfeng Lv, Feng Zhao, Zejun Yan, Junhui Jiang, Yanyi Xiao, Lili Yao (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-11685211.txt.
Description
Yating Zhan and co-authors build a gene signature linking nicotine metabolism to outcomes in bladder cancer. Smoking is a major risk factor for bladder cancer, and genes of nicotine metabolism were suspected players. Mining public databases, they grouped tumors into three clusters with distinct outlooks and immune patterns. Ten machine learning methods then competed to build the signature.
A four-gene signature from a survival forest method predicted patient outcomes reliably across three cohorts. The score also tracked clinical features, the tissue around the tumor, and likely response to immune therapy. Lab tests on one signature gene confirmed effects on cancer cell growth, spread, and colony formation, grounding the computation in biology.
Catalog record
| CREATOR | Yating Zhan, Min Weng, Yangyang Guo, Dingfeng Lv, Feng Zhao, Zejun Yan, Junhui Jiang, Yanyi Xiao, Lili Yao |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 36 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |