Skip to content
DraconiticResearch
Search Sources API
194,161 studies31 sourcesUpdated 6 min ago
Peer-reviewedCC BYJournal for ImmunoTherapy of Cancer

179 Machine learning-based prediction of CAR-T cell therapy response in pediatric acute lymphoblastic leukemia patients using single-cell multi-omics features

  • Christopher Fisher1
  1. 1Good Manufacturing Practice Unit, Guy’s and St Thomas’ Biomedical Research Centre, Guy`s and St Thomas` NHS Foundation Trust, London, UK
Open at sourcePDFDOICite

Related

  1. Refining risk in historically high-risk pediatric B-cell acute lymphoblastic leukemia: response kinetics and outcomes
    Yasuo Kubota, Yasuhiro Okamoto, Toshihiko Imamura +7
    Blood NeoplasiaPeer-reviewedCC BY-NC-NDFull textEpidemiology & public healthDOAJEurope PMCEurope PMCPMC
  2. Resistance mechanisms and translational bottlenecks in CAR-T cell therapy for pediatric acute lymphoblastic leukemia: a perspective
    JiLi Xu, Lili Sui, Wenzhe Yang +2
    Frontiers in ImmunologyPeer-reviewedCC BY 4.0Full textOncologyCrossrefEurope PMC
  3. Impact of Obesity on Chemotherapy Pharmacokinetics, Toxicity, and Survival Outcomes in Pediatric Acute Lymphoblastic Leukemia.
    Arun Nair, Gillian Graifman, U Tahir +4
    CureusPeer-reviewedCC BYFull textEpidemiology & public healthEurope PMC
  4. Minor Myeloid Leukemic Populations in Pediatric Acute Lymphoblastic Leukemia: A Potentially Underrecognized Mixed-Phenotype Tumor?
    Alexandra Semchenkova, Polina Lavrova, Vladimir Kozeev +9
    International Journal of Molecular SciencesPeer-reviewedCC BY 4.0Full textEpidemiology & public healthCrossrefEurope PMC
  5. Genomic drivers of leukemia and blinatumomab response in adult acute lymphoblastic leukemia – the ECOG-ACRIN E1910 study
    Xiaoming Zhong, Kathryn G. Roberts, Huimei Wei +59
    BloodPeer-reviewedLicence not statedFull textGeneral medicinePMC

Cite

BibTeXRIS
BibTeX
@article{fisher2026machine,
  title = {{179 Machine learning-based prediction of CAR-T cell therapy response in pediatric acute lymphoblastic leukemia patients using single-cell multi-omics features}},
  author = {Christopher Fisher},
  journal = {Journal for ImmunoTherapy of Cancer},
  year = {2026},
  month = nov,
  doi = {10.1136/jitc-2026-sitc2026.0179},
  url = {https://doi.org/10.1136/jitc-2026-sitc2026.0179},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - 179 Machine learning-based prediction of CAR-T cell therapy response in pediatric acute lymphoblastic leukemia patients using single-cell multi-omics features
AU  - Christopher Fisher
PY  - 2026
DA  - 2026/11/06
JO  - Journal for ImmunoTherapy of Cancer
DO  - 10.1136/jitc-2026-sitc2026.0179
UR  - https://doi.org/10.1136/jitc-2026-sitc2026.0179
SN  - 2051-1426
ER  -