Tumour cell density quantified by artificial intelligence is associated with differential benefit from irinotecan-based chemo-radiotherapy in locally advanced rectal cancer: a post-hoc study of the phase 3 ARISTOTLE trial
Zhuoyan Shen, Douglas Brand, Mikaël Simard, Nicholas P. West, Andre Lopes, Rubina Begum, Ying Zhang, Gary Royle, David Sebag-Montefiore, Charles-Antoine Collins Fekete, Maria A. Hawkins · 2026
Read Tumour cell density quantified by artificial intelligence is associated with differential benefit from irinotecan-based chemo-radiotherapy in locally advanced rectal cancer: a post-hoc study of the phase 3 ARISTOTLE trial by Zhuoyan Shen, Douglas Brand, Mikaël Simard, Nicholas P. West, Andre Lopes, Rubina Begum, Ying Zhang, Gary Royle, David Sebag-Montefiore, Charles-Antoine Collins Fekete, Maria A. Hawkins (2026) 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/PMC13476900.txt.
Description
Zhuoyan Shen and co-authors count tumor cell density in 2026 with artificial intelligence to predict who gains from stronger chemoradiation in rectal cancer. Slides from 414 trial patients were scanned and scored by an automated framework. Density meant the share of tumor cells inside tumor and support tissue. Patients split at the halfway mark into dense and sparse groups.
Dense tumors gained clearly from adding a second drug to chemoradiation, with longer disease-free and overall survival. Sparse tumors showed no such edge in the analysis. The split held in formal interaction tests for both outcomes. A slide-based score could spare some patients extra drug harm.
Catalog record
| CREATOR | Zhuoyan Shen, Douglas Brand, Mikaël Simard, Nicholas P. West, Andre Lopes, Rubina Begum, Ying Zhang, Gary Royle, David Sebag-Montefiore, Charles-Antoine Collins Fekete, Maria A. Hawkins |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 47 KB |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |