ArticleOncology letters2015
Melanoma-associated antigen expression and the efficacy of tyrosine kinase inhibitors in head and neck cancer.
Article in Oncology letters, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 10 citations in OpenAlex.
- Vaccine therapies for glioma: clinical frontiers and potential breakthrough.Frontiers in oncology · 2025Review
- Melanoma Antigen Family A (MAGE A) as Promising Biomarkers and Therapeutic Targets in Bladder Cancer.Cancers · 2024Review
- 3, 3'- (3, 5-DCPBC) Down-Regulates Multiple Phosphokinase Dependent Signal Transduction Pathways in Malignant Melanoma Cells through Specific Diminution of EGFRMolecules (Basel, Switzerland) · 2022Article
- Epigenetic Upregulation of MAGE-A Isoforms Promotes Breast Cancer Cell Aggressiveness.Cancers · 2021Article
- Contrary melanoma-associated antigen-A expression at the tumor front and center: A comparative analysis of stage I and IV head and neck squamous cell carcinoma.Oncology letters · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Melanoma-associated antigen (MAGE) has been identified in a variety of types of cancer. The expression of several MAGE subgroups is correlated with poor prognosis and chemotherapeutic resistance. One target of chemotherapeutic treatment in head and neck cancer is the epidermal growth factor receptor (EGFR). The efficacy of tyrosine kinase inhibitors (TKI) in the context of melanoma-associated antigens is discussed in the present study. Five human squamous cell carcinoma cell lines were treated with the EGFR TKIs, erlotinib and gefitinib. The efficacy of these agents was measured using a crystal violet assay. Furthermore, the expression levels of MAGE-A1, -A5, -A8, -A9, -A11 and -A12 were determined by reverse transcription-quantitative polymerase chain reaction. The association between TKI efficacy and MAGE-A expression was analyzed by linear regression. The cell lines revealed inhomogeneous expression patterns for the MAGE-A subgroups. Four of the five cell lines demonstrated a good response to erlotinib and gefitinib. However, treatment with erlotinib induced better results than those of gefitinib, and revealed a concentration-dependent effect. The expression of MAGE-A5 and -A11 were significantly correlated with lower efficacy of erlotinib and gefitinib. By contrast, MAGE-A12 was associated with a superior response to these two drugs. One cell line, which expressed all investigated MAGE-A subgroups, was entirely resistant to the two TKIs. These results revealed a notable correlation between MAGE-A5 and -A11 and lower efficacy of EGFR TKIs. Pretreatment analysis of MAGE-A status may therefore aid improvement of chemoprevention using erlotinib and gefitinib in head and neck cancer.
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.