ArticleDaru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences2015
Label-free LC-MS analysis of HER2+ breast cancer cell line response to HER2 inhibitor treatment.
Article in Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed, 25 citations in OpenAlex.
- Label-Free Quantitative Analysis of Pig Liver Proteome after Hepatitis E Virus Infection.Viruses · 2024Article
- Lapatinib-induced enhancement of mitochondrial respiration in HER2-positive SK-BR-3 cells: mechanism revealed by analysis of proteomic but not transcriptomic data.Frontiers in molecular biosciences · 2024Article
- Comparative Proteomics Analysis of Pig Muscle Exudate through Label-Free Liquid Chromatography-Mass Spectrometry.Animals : an open access journal from MDPI · 2023Article
- A Label-Free Quantitative Analysis for the Search of Proteomic Differences between Goat Breeds.Animals : an open access journal from MDPI · 2022Article
- Label-free quantitative proteomics and stress responses in pigs-The case of short or long road transportation.PloS one · 2022Article
- Review
- Differential proteomic comparison of breast cancer secretome using a quantitative paired analysis workflow.BMC cancer · 2019Article
- Increases in Tumor N-Glycan Polylactosamines Associated with Advanced HER2-Positive and Triple-Negative Breast Cancer Tissues.Proteomics. Clinical applications · 2019Article
- Article
- Application of sebomics for the analysis of residual skin surface components to detect potential biomarkers of type-1 diabetes mellitus.Scientific reports · 2017Article
- Oral squamous cell carcinoma patients can be differentiated from healthy individuals with label-free serum proteomics.British journal of cancer · 2017Article
- Comparative proteomic profiling of the serum differentiates pancreatic cancer from chronic pancreatitis.Cancer medicine · 2017Article
- Proteomic profiling of mdx-4cv serum reveals highly elevated levels of the inflammation-induced plasma marker haptoglobin in muscular dystrophy.International journal of molecular medicine · 2017Article
- Proteomic profiling of the dystrophin complex and membrane fraction from dystrophic mdx muscle reveals decreases in the cytolinker desmoglein and increases in the extracellular matrix stabilizers biglycan and fibronectin.Journal of muscle research and cell motility · 2017Article
- Article
- Human Spermatozoa Quantitative Proteomic Signature Classifies Normo- and Asthenozoospermia.Molecular & cellular proteomics : MCP · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHuman epidermal growth-factor receptor (HER)-2 is overexpressed in 25 % of breast-cancers and is associated with an aggressive form of the disease with significantly shortened disease free and overall survival. In recent years, the use of HER2-targeted therapies, monoclonal-antibodies and small molecule tyrosine-kinase inhibitors has significantly improved the clinical outcome for HER2-positive breast-cancer patients. However, only a fraction of HER2-amplified patients will respond to therapy and the use of these treatments is often limited by tumour drug insensitivity or resistance and drug toxicities. Currently there is no way to identify likely responders or rational combinations with the potential to improve HER2-focussed treatment outcome.
methodsIn order to further understand the molecular mechanisms of treatment-response with HER2-inhibitors, we used a highly-optimised and reproducible quantitative label-free LC-MS strategy to characterize the proteomes of HER2-overexpressing breast-cancer cell-lines (SKBR3, BT474 and HCC1954) in response to drug-treatment with HER2-inhibitors (lapatinib, neratinib or afatinib).
resultsFollowing 12 ours treatment with different HER2-inhibitors in the BT474 cell-line; compared to the untreated cells, 16 proteins changed significantly in abundance following lapatinib treatment (1 μM), 21 proteins changed significantly following neratinib treatment (150 nM) and 38 proteins changed significantly following afatinib treatment (150 nM). Whereas following 24 hours treatment with neratinib (200 nM) 46 proteins changed significantly in abundance in the HCC1954 cell-line and 23 proteins in the SKBR3 cell-line compared to the untreated cells. Analysing the data we found that, proteins like trifunctional-enzyme subunit-alpha, mitochondrial; heterogeneous nuclear ribonucleoprotein-R and lamina-associated polypeptide 2, isoform alpha were up-regulated whereas heat shock cognate 71 kDa protein was down-regulated in 3 or more comparisons.
conclusionThis proteomic study highlights several proteins that are closely associated with early HER2-inhibitor response and will provide a valuable resource for further investigation of ways to improve efficacy of breast-cancer treatment.
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.