{
  "annotation_id": "643136f5-cc0d-4d54-9d5c-677ea2759221",
  "date_created": "2026-03-02T18:01:34.946000Z",
  "date_modified": "2026-03-02T18:01:34.946000Z",
  "file_hash": "8e4d7f11200df1eef66a8bf742b1122590353f0db665276eb1a9bd43de7e84e8",
  "private": false,
  "record": {
    "abstract": "Background: Radiotherapy outcomes are usually predicted using the Linear\nQuadratic model. However, this model does not integrate complex features of\ntumor growth, in particular cell cycle regulation.\n  Methods: In this paper, we propose a multiscale model of cancer growth based\non the genetic and molecular features of the evolution of colorectal cancer.\nThe model includes key genes, cellular kinetics, tissue dynamics, macroscopic\ntumor evolution and radiosensitivity dependence on the cell cycle phase. We\ninvestigate the role of gene-dependent cell cycle regulation in the response of\ntumors to therapeutic irradiation protocols.\n  Results: Simulation results emphasize the importance of tumor tissue features\nand the need to consider regulating factors such as hypoxia, as well as tumor\ngeometry and tissue dynamics, in predicting and improving radiotherapeutic\nefficacy.\n  Conclusion: This model provides insight into the coupling of complex\nbiological processes, which leads to a better understanding of oncogenesis.\nThis will hopefully lead to improved irradiation therapy.",
    "arxiv_id": "q-bio/0606035",
    "authors": [
      "Benjamin Ribba",
      "Thierry Colin",
      "Santiago Schnell"
    ],
    "categories": [
      "q-bio.TO",
      "q-bio.SC"
    ],
    "doi": "10.1186/1742-4682-3-7",
    "title": "A multiscale mathematical model of cancer, and its use in analyzing   irradiation therapies",
    "url": "https://arxiv.org/abs/q-bio/0606035"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "582ac40d-1ee6-40b3-bdc7-65132a74bb0f",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}