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1.
Blood ; 132(20): 2154-2165, 2018 11 15.
Article in English | MEDLINE | ID: mdl-30181174

ABSTRACT

Improving outcomes in multiple myeloma will involve not only development of new therapies but also better use of existing treatments. We performed RNA sequencing on samples from newly diagnosed patients enrolled in the phase 2 PADIMAC (Bortezomib, Adriamycin, and Dexamethasone Therapy for Previously Untreated Patients with Multiple Myeloma: Impact of Minimal Residual Disease in Patients with Deferred ASCT) study. Using synthetic annealing and the large margin nearest neighbor algorithm, we developed and trained a 7-gene signature to predict treatment outcome. We tested the signature in independent cohorts treated with bortezomib- and lenalidomide-based therapies. The signature was capable of distinguishing which patients would respond better to which regimen. In the CoMMpass data set, patients who were treated correctly according to the signature had a better progression-free survival (median, 20.1 months vs not reached; hazard ratio [HR], 0.40; confidence interval [CI], 0.23-0.72; P = .0012) and overall survival (median, 30.7 months vs not reached; HR, 0.41; CI, 0.21-0.80; P = .0049) than those who were not. Indeed, the outcome for these correctly treated patients was noninferior to that for those treated with combined bortezomib, lenalidomide, and dexamethasone, arguably the standard of care in the United States but not widely available elsewhere. The small size of the signature will facilitate clinical translation, thus enabling more targeted drug regimens to be delivered in myeloma.


Subject(s)
Antineoplastic Agents/therapeutic use , Bortezomib/therapeutic use , Lenalidomide/therapeutic use , Multiple Myeloma/drug therapy , Multiple Myeloma/genetics , Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Dexamethasone/therapeutic use , Doxorubicin/therapeutic use , Humans , Kaplan-Meier Estimate , Machine Learning , Mutation , Proportional Hazards Models , Sequence Analysis, RNA , Transcriptome , Treatment Outcome , United States
2.
Blood ; 101(4): 1558-65, 2003 Feb 15.
Article in English | MEDLINE | ID: mdl-12560242

ABSTRACT

Acute promyelocytic leukemia (APL) is associated with a reciprocal and balanced translocation involving the retinoic acid receptor-alpha (RARalpha). All-trans retinoic acid (ATRA) is used to treat APL and is a potent morphogen that regulates HOX gene expression in embryogenesis and organogenesis. HOX genes are also involved in hematopoiesis and leukemogenesis. Thirty-nine mammalian HOX genes have been identified and classified into 13 paralogous groups clustered on 4 chromosomes. They encode a complex network of transcription regulatory proteins whose precise targets remain poorly understood. The overall function of the network appears to be dictated by gene dosage. To investigate the mechanisms involved in HOX gene regulation in hematopoiesis and leukemogenesis by precise measurement of individual HOX genes, a small-array real-time HOX (SMART-HOX) quantitative polymerase chain reaction (PCR) platform was designed and validated. Application of SMART-HOX to 16 APL bone marrow samples revealed a global down-regulation of 26 HOX genes compared with normal controls. HOX gene expression was also altered during differentiation induced by ATRA in the PML-RARalpha(+) NB4 cell line. PML-RARalpha fusion proteins have been reported to act as part of a repressor complex during myeloid cell differentiation, and a model linking HOX gene expression to this PML-RARalpha repressor complex is now proposed.


Subject(s)
Gene Expression Regulation, Neoplastic , Homeodomain Proteins/genetics , Leukemia, Promyelocytic, Acute/genetics , Neoplasm Proteins/analysis , Oncogene Proteins, Fusion/analysis , Bone Marrow/chemistry , Cell Differentiation/drug effects , Cloning, Molecular , Gene Expression Profiling , Hematopoiesis/genetics , Humans , Leukemia, Promyelocytic, Acute/metabolism , Leukemia, Promyelocytic, Acute/pathology , Polymerase Chain Reaction , Sequence Analysis, DNA , Tretinoin/pharmacology , Tumor Cells, Cultured
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