ArticleCancer genomics & proteomics
Proteomics-based Predictive Model for the Early Detection of Metastasis and Recurrence in Head and Neck Cancer.
Article in Cancer genomics & proteomics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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.
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Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Inositol monophosphatase 1 (IMPA1) promotes triple-negative breast cancer progression through regulating mTOR pathway and EMT process.Cancer medicine · 2023Article
- Article
- The Prediction of a 3-Protein-Based Model on the Prognosis of Head and Neck Squamous Cell Carcinoma.Computational and mathematical methods in medicine · 2022Article
- Proteomics Analysis Identified ASNS as a Novel Biomarker for Predicting Recurrence of Skull Base Chordoma.Frontiers in oncology · 2021Article
- Applications of Multi-omics Approaches for Exploring the Molecular Mechanism of Ovarian Carcinogenesis.Frontiers in oncology · 2021Review
- Proteomics analysis identified TPI1 as a novel biomarker for predicting recurrence of intrahepatic cholangiocarcinoma.Journal of gastroenterology · 2020Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimHead and neck squamous cell carcinoma (HNSCC) presents high morbidity, an overall poor prognosis and survival, and a compromised quality of life of the survivors. Early tumor detection, prediction of its behavior and prognosis as well as the development of novel therapeutic strategies are urgently needed for a more successful HNSCC management. MATERIALS AND
methodsIn this study, a proteomics analysis of HNSCC tumor and non-tumor samples was performed and a model to predict the risk of recurrence and metastasis development was built.
resultsThis predictive model presented good accuracy (>80%) and comprises as variables the tumor staging along with DHB12, HMGB3 and COBA1 proteins. Differences at the intensity levels of these proteins were correlated with the development of metastasis and recurrence as well as with patient's survival.
conclusionThe translation of proteomic predictive models to routine clinical practice may contribute to a more precise and individualized clinical management of the HNSCC patients, reducing recurrences and improving patients' quality of life. The capability of generalization of this proteomic model to predict the recurrence and metastases development should be evaluated and validated in other HNSCC populations.
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