ArticleMolecular & cellular proteomics : MCP2011
Monitoring a nuclear factor-κB signature of drug resistance in multiple myeloma.
Article in Molecular & cellular proteomics : MCP, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed, 34 citations in OpenAlex.
- Genomic profiling enables personalized strategies to overcome drug resistance in multiple myeloma.Discover oncology · 2026Review
- Simultaneously Targeting Two Coupled Signalling Molecules in the Mesenchymal Stem Cell Support Efficiently Sensitises the Multiple Myeloma Cell Line H929 to Bortezomib.International journal of molecular sciences · 2023Article
- Metabolic Changes Are Associated with Melphalan Resistance in Multiple Myeloma.Journal of proteome research · 2021Article
- Article
- Multi-omics tumor profiling technologies to develop precision medicine in multiple myeloma.Exploration of targeted anti-tumor therapy · 2021Review
- Novel Small Molecular Compound AE-848 Potently Induces Human Multiple Myeloma Cell Apoptosis by Modulating the NF-κB and PI3K/Akt/mTOR Signaling Pathways.OncoTargets and therapy · 2020Article
- Proteometabolomics of Melphalan Resistance in Multiple Myeloma.Methods in molecular biology (Clifton, N.J.) · 2019Article
- Comparison of Quantitative Mass Spectrometry Platforms for Monitoring Kinase ATP Probe Uptake in Lung Cancer.Journal of proteome research · 2018Article
- Soluble and Cell-Cell-Mediated Drivers of Proteasome Inhibitor Resistance in Multiple Myeloma.Frontiers in endocrinology · 2018Review
- A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research.Frontiers in oncology · 2017Review
- Oncogenic KRAS and BRAF Drive Metabolic Reprogramming in Colorectal Cancer.Molecular & cellular proteomics : MCP · 2016Article
- Fibronectin induction abrogates the BRAF inhibitor response of BRAF V600E/PTEN-null melanoma cells.Oncogene · 2016Article
- Review
- Evaluating kinase ATP uptake and tyrosine phosphorylation using multiplexed quantification of chemically labeled and post-translationally modified peptides.Methods (San Diego, Calif.) · 2015Article
- Emerging proteomic technologies for elucidating context-dependent cellular signaling events: A big challenge of tiny proportions.Proteomics · 2015Review
- Evaluating melanoma drug response and therapeutic escape with quantitative proteomics.Molecular & cellular proteomics : MCP · 2014Article
- Drug resistance in multiple myeloma: latest findings and new concepts on molecular mechanisms.Oncotarget · 2013Review
- An inverse switch in DNA base excision and strand break repair contributes to melphalan resistance in multiple myeloma cells.PloS one · 2013Article
- The Making of a CYP3A Biomarker Panel for Guiding Drug Therapy.Journal of personalized medicine · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 4 institutions in 1 country.
Funding
Abstract
The emergence of acquired drug resistance results from multiple compensatory mechanisms acting to prevent cell death. Simultaneous monitoring of proteins involved in drug resistance is a major challenge for both elucidation of the underlying biology and development of candidate biomarkers for assessment of personalized cancer therapy. Here, we have utilized an integrated analytical platform based on SDS-PAGE protein fractionation prior to liquid chromatography coupled to multiple reaction monitoring mass spectrometry, a versatile and powerful tool for targeted quantification of proteins in complex matrices, to evaluate a well-characterized model system of melphalan resistance in multiple myeloma (MM). Quantitative assays were developed to measure protein expression related to signaling events and biological processes relevant to melphalan resistance in multiple myeloma, specifically: nuclear factor-κB subunits, members of the Bcl-2 family of apoptosis-regulating proteins, and Fanconi Anemia DNA repair components. SDS-PAGE protein fractionation prior to liquid chromatography coupled to multiple reaction monitoring methods were developed for quantification of these selected target proteins in amounts of material compatible with direct translation to clinical specimens (i.e. less than 50,000 cells). As proof of principle, both relative and absolute quantification were performed on cell line models of MM to compare protein expression before and after drug treatment in naïve cells and in drug resistant cells; these liquid chromatography-multiple reaction monitoring results are compared with existing literature and Western blots. The initial stage of a systems biology platform for examining drug resistance in MM has been implemented in cell line models and has been translated to MM cells isolated from a patient. The ultimate application of this platform could assist in clinical decision-making for individualized patient treatment. Although these specific assays have been developed to monitor MM, these techniques are expected to have broad applicability in cancer and other types of disease.
Indexed as
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.