Revisiting prognostic biomarkers in gastrointestinal stromal tumor: the potential role of ETV1 polymorphisms

Gastrointestinal stromal tumors (GISTs) represent an example in which precision oncology has significantly changed the course of the disease, with the drug imatinib substantially transforming the prognosis for patients with advanced disease and in the context of high clinical risk adjuvant therapy. Although this medication has proven effective, variability in clinical response and time to progression remains a major challenge in clinical practice (1-3).

Traditional risk factors such as tumor size, location, mitotic index, and mutational profile related to KIT proto-oncogene receptor tyrosine kinase (KIT) and platelet-derived growth factor receptor alpha (PDGFRA) adequately guide initial management; however, there is notable interindividual variability in response due to multiple mechanisms and signaling pathways (4-9). The biological rationale for this study stems from the fact that ETS variant transcription factor 1 (ETV1) is a central transcription factor in GIST biology, closely related to the KIT-ERK-ETV1 pathway, which plays an important role in GIST cell survival and proliferation (10). This occurs because activated KIT stabilizes the ETV1 protein (10). ETV1 expression is found to be very specific towards GIST, and its presence can even be observed in KIT-negative patients and has been used as a biomarker in diagnostically challenging situations, including after imatinib therapy when conventional immunohistochemical markers may be lost (10,11). Clinically, reduced ETV1 expression has been associated with an increased risk of recurrence and reduced recurrence-free survival, indicating it remains a potential prognostic biomarker (12). In these studies, ETV1 has also been implicated in the control of the tumor microenvironment, particularly in the direction of M2 polarization of tumor-associated macrophages that may contribute to GIST progression (13). Given its key roles in GIST pathogenesis and resistance to apoptosis, targeting ETV1 or its downstream pathways represents a promising therapeutic strategy (10,13).

The study conducted by Zhuang et al. included 75 patients with GIST treated with imatinib and explored nine tag-single nucleotide polymorphisms (SNPs) in the ETV1 gene, in addition to integrating clinical variables, somatic mutations, and plasma levels of imatinib in multivariate analysis. The main finding was the association of SNP rs3735343, located in the 3'-untranslated region (UTR) of ETV1, with progression-free survival (PFS). The authors demonstrated that the rs3735343 genotype was significantly associated with the outcome and that, in multivariate model, tumor size and rs3735343 remained independent predictors of PFS. It is important to highlight the authors’ consistency in integrating a clinical parameter already known and implemented in practice with innovative molecular testing. Another important finding of the study is that it explores a possible functional mechanism. The authors suggest that rs3735343 acts as a microRNA-related SNP (miR-SNP), interfering with interactions in the 3'-UTR of ETV1, with emphasis on miR-4311 as a potential allele-specific negative regulator. Experiments with a dual-luciferase system point to differential regulation associated with the risk allele, which increases the interest in the finding and positions it at a promising interface between pharmacogenomics, molecular biology, and therapeutic resistance. In a field where mechanisms of resistance to imatinib are multifactorial, the possibility of integration between germline variants and post-transcriptional regulation is relevant (14).

From a clinical perspective, this study seeks to address an important challenge by proposing a more sophisticated approach for risk stratification of GISTs beyond the conventional clinicopathologic models in this study. While the driver changes in KIT and PDGFRA are still essential for diagnosis, prognosis, and therapeutic regimens, this genotypic profile alone is insufficient to explain the interindividual differences in tumor kinetics and longitudinal clinical presentation. Additional biomarkers used by DNA- and RNA-based sequencing technologies may provide extensive risk modeling, individualized surveillance strategies and even contribute to treatment optimization in the future (6,15).

These findings, however, should be interpreted cautiously, in light of methodological limitations that may impact the external validation. This is a single-center retrospective analysis, influenced by the local population, the institutional treatment and diagnosis protocols, and more susceptible to selection bias. Moreover, even though the results related to PFS and tumor size show statistical significance, the small number of patients included (n=75) and consequently lower number of events on the different subgroups are related to a wide confidence interval, suggesting reduced reliability in the true magnitude of the effect. The analysis involved multiple tests; therefore, the probability of identifying false-positive associations by chance may increase. It is important to highlight that statistical analysis utilized false discovery rate (FDR) control to address this issue, and the results that remain significant after FDR adjustment offer a more appropriate level of statistical confidence (16).

Overall, this study provides an important contribution to the growing field of risk stratification in GIST and should be interpreted as hypothesis-generating. Future prospective, multicenter studies with larger cohorts and stratification by disease stage and treatment exposure will be essential to validate these findings and determine whether ETV1 polymorphisms may ultimately contribute to clinically actionable risk stratification.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Journal of Gastrointestinal Oncology. The article did not undergo external peer review.

Funding: None.

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-0273/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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