ArticleBiomarker research2022
Prognostic and predictive biomarkers for response to neoadjuvant chemoradiation in esophageal adenocarcinoma.
Article in Biomarker research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 3 citations in OpenAlex.
- Review
- Prediction of Overall Survival in Patients With Oesophageal Cancer Using AI-Based 3D CT Body Composition Analysis.Journal of cachexia, sarcopenia and muscle · 2026Article
- Accuracy of Predicting Residual Disease and Disease Progression During Active Surveillance for Esophageal Cancer.Annals of surgical oncology · 2026Article
- EphA5 Expression Predicts Better Survival Despite an Association with Proliferative Activity in Endometrial Cancer.Journal of clinical medicine · 2025Article
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEsophageal adenocarcinoma is a lethal disease. For locally advanced patients, neoadjuvant chemoradiotherapy followed by surgery is the standard of care. Risk stratification relies heavily on clinicopathologic features, particularly pathologic response, which is inadequate, therefore establishing the need for new and reliable biomarkers for risk stratification.
methodsThirty four patients with locally advanced esophageal adenocarcinoma were analyzed, of which 21 received a CROSS regimen with carboplatin, paclitaxel, and radiation. Capture-based targeted sequencing was performed on the paired baseline and post-treatment samples. Differentially mutated gene analysis between responders and non-responders of treatment was performed to determine predictors of response. A univariate Cox proportional hazard regression was used to examine associations between gene mutation status and overall survival.
resultsA 3-gene signature, based on mutations in EPHA5, BCL6, and ERBB2, was identified that robustly predicts response to the CROSS regimen. For this model, sensitivity was 84.6% and specificity was 100%. Independently, a 9 gene signature was created using APC, MAP3K6, ETS1, CSF3R, PDGFRB, GATA2, ARID1A, PML, and FGF6, which significantly stratifies patients into risk categories, prognosticating for improved relapse-free (p = 4.73E-03) and overall survival (p = 3.325E-06). The sensitivity for this model was 73.33% and the specificity was 94.74%.
conclusionWe have identified a 3-gene signature (EPHA5, BCL6, and ERBB2) that is predictive of response to neoadjuvant chemoradiotherapy and a separate prognostic 9-gene classifier that predicts survival outcomes. These panels provide significant potential for personalized management of locally advanced esophageal cancer.
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