Detalhe da pesquisa
1.
Feasibility of monitoring peripheral blood to detect emerging clones in children with acute lymphoblastic leukemia.
Pediatr Blood Cancer
; 67(7): e28306, 2020 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-32391957
2.
SETD2 mutations do not contribute to clonal fitness in response to chemotherapy in childhood B cell acute lymphoblastic leukemia.
Leuk Lymphoma
; 65(1): 78-90, 2024 Jan.
Artigo
em Inglês
| MEDLINE | ID: mdl-37874744
3.
NSD2 E1099K drives relapse in pediatric acute lymphoblastic leukemia by disrupting 3D chromatin organization.
Genome Biol
; 24(1): 64, 2023 04 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-37016431
4.
Altered BAF occupancy and transcription factor dynamics in PBAF-deficient melanoma.
Cell Rep
; 39(1): 110637, 2022 04 05.
Artigo
em Inglês
| MEDLINE | ID: mdl-35385731
5.
Oncogenic deubiquitination controls tyrosine kinase signaling and therapy response in acute lymphoblastic leukemia.
Sci Adv
; 8(49): eabq8437, 2022 12 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-36490346
6.
Surface antigen-guided CRISPR screens identify regulators of myeloid leukemia differentiation.
Cell Stem Cell
; 28(4): 718-731.e6, 2021 04 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-33450187
7.
Mutations associated with human neural tube defects display disrupted planar cell polarity in Drosophila.
Elife
; 92020 04 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-32234212
8.
Evolution of the Epigenetic Landscape in Childhood B Acute Lymphoblastic Leukemia and Its Role in Drug Resistance.
Cancer Res
; 80(23): 5189-5202, 2020 12 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-33067268
9.
The NSD2 p.E1099K Mutation Is Enriched at Relapse and Confers Drug Resistance in a Cell Context-Dependent Manner in Pediatric Acute Lymphoblastic Leukemia.
Mol Cancer Res
; 18(8): 1153-1165, 2020 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-32332049
10.
Targeting Mitochondrial Structure Sensitizes Acute Myeloid Leukemia to Venetoclax Treatment.
Cancer Discov
; 9(7): 890-909, 2019 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-31048321
11.
A Deep Learning Framework for Predicting Response to Therapy in Cancer.
Cell Rep
; 29(11): 3367-3373.e4, 2019 12 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-31825821
12.
Machine learning and data mining frameworks for predicting drug response in cancer: An overview and a novel in silico screening process based on association rule mining.
Pharmacol Ther
; 203: 107395, 2019 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-31374225