Associated Papers
Mutation Patterns Predict Drug Sensitivity in Acute Myeloid Leukemia.
Qin G et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research, 2024
38619278 (PubMed )
Supplement: ccr-23-1674_supplementary_table_s1-s14_suppts1.xlsx › TableS2_Var_AF0.01
Development and validation of a mutation-based model to predict immunotherapeutic efficacy in NSCLC.
He P et al.
Frontiers in Oncology, 2023
36910641 (PubMed )
Supplement: DataSheet_1.xlsx › Table_S8
Patient-derived models recapitulate heterogeneity of molecular signatures and drug response in pediatric high-grade glioma.
He C et al.
Nature Communications, 2021
34215733 (PubMed )
Supplement: 41467_2021_24168_MOESM5_ESM.xlsx › SD2c
RUNX1 mutations in blast-phase chronic myeloid leukemia associate with distinct phenotypes, transcriptional profiles, and drug responses.
Adnan Awad S et al.
Leukemia, 2021
32782381 (PubMed )
Supplement: 41375_2020_1011_MOESM5_ESM.xlsx › Mutation_in_Australian_cohort
Aggressive natural killer-cell leukemia mutational landscape and drug profiling highlight JAK-STAT signaling as therapeutic target.
Dufva O et al.
Nature Communications, 2018
29674644 (PubMed )
Supplement: 41467_2018_3987_MOESM5_ESM.xlsx › ANKL4
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