ArticleNPJ precision oncology2021
Bayesian multi-source regression and monocyte-associated gene expression predict BCL-2 inhibitor resistance in acute myeloid leukemia.
Article in NPJ precision oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 31 citations in OpenAlex.
- Dynamic genetic and nongenetic RAS-pathway activation drives resistance to FLT3 and BCL2 inhibitor therapy.Blood · 2026Article
- m6A and NuRD complexes regulate monocytic differentiation and resistance to BCL2/BCL2L1 inhibitors in acute myeloid leukemia.Haematologica · 2026Article
- Bayesian machine learning enables discovery of risk factors for hepatosplenic multimorbidity related to schistosomiasis.Nature communications · 2026Article
- Discovery of predictive biomarkers for cancer therapy through computational approaches.Nature reviews. Clinical oncology · 2026Review
- Drivers of clinical resistance to venetoclax and hypomethylating agents in acute myeloid leukemia and strategies for improving efficacy.HemaSphere · 2026Article
- A Machine Learning-Based Strategy Predicts Selective and Synergistic Drug Combinations for Relapsed Acute Myeloid Leukemia.Cancer research · 2025Article
- Article
- A precision oncology-focused deep learning framework for personalized selection of cancer therapy.bioRxiv : the preprint server for biology · 2024Article
- Bayesian Simultaneous Factorization and Prediction Using Multi-Omic Data.Computational statistics & data analysis · 2024Article
- Monocytic Differentiation in Acute Myeloid Leukemia Cells: Diagnostic Criteria, Biological Heterogeneity, Mitochondrial Metabolism, Resistance to and Induction by Targeted Therapies.International journal of molecular sciences · 2024Review
- Overcoming limitations in current measures of drug response may enable AI-driven precision oncology.NPJ precision oncology · 2024Article
- Myelomonocytic and monocytic acute myeloid leukemia demonstrate comparable poor outcomes with venetoclax-based treatment: a monocentric real-world study.Annals of hematology · 2024Article
- Venetoclax Resistance in Acute Myeloid Leukemia.Cancers · 2024Review
- Venetoclax Combined with Intensive Chemotherapy: A New Hope for Refractory and/or Relapsed Acute Myeloid Leukemia?Journal of clinical medicine · 2024Review
- ATP1A1/BCL2L1 predicts the response of myelomonocytic and monocytic acute myeloid leukemia to cardiac glycosides.Leukemia · 2024Article
- Identification of hub genes and potential molecular mechanisms related to drug sensitivity in acute myeloid leukemia based on machine learning.Frontiers in pharmacology · 2024Article
- Clinical forecasting of acute myeloid leukemia using ex vivo drug-sensitivity profiling.Cell reports methods · 2023Article
- Bayesian predictive modeling of multi-source multi-way data.Computational statistics & data analysis · 2023Article
- Venetoclax response prediction in acute myeloid leukemia: are weHaematologica · 2023Article
- Immune cell proportions correlate with clinicogenomic features andFrontiers in oncology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 6 institutions in 5 countries.
Funding
Abstract
The FDA recently approved eight targeted therapies for acute myeloid leukemia (AML), including the BCL-2 inhibitor venetoclax. Maximizing efficacy of these treatments requires refining patient selection. To this end, we analyzed two recent AML studies profiling the gene expression and ex vivo drug response of primary patient samples. We find that ex vivo samples often exhibit a general sensitivity to (any) drug exposure, independent of drug target. We observe that this "general response across drugs" (GRD) is associated with FLT3-ITD mutations, clinical response to standard induction chemotherapy, and overall survival. Further, incorporating GRD into expression-based regression models trained on one of the studies improved their performance in predicting ex vivo response in the second study, thus signifying its relevance to precision oncology efforts. We find that venetoclax response is independent of GRD but instead show that it is linked to expression of monocyte-associated genes by developing and applying a multi-source Bayesian regression approach. The method shares information across studies to robustly identify biomarkers of drug response and is broadly applicable in integrative analyses.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.