Refining the clinical interpretation of GLUT1 in non-small cell lung cancer

We read with great interest the recent article by Hantzsch-Kuhn et al., who reported that high glucose transporter 1 (GLUT1) protein expression is associated with unfavorable tumor features and poor prognosis in non-small cell lung cancer (NSCLC) (1). Using a large tissue microarray cohort, the authors showed that GLUT1 staining was markedly more prevalent and intense in squamous cell carcinoma (SCC) than in adenocarcinoma (AC), and that high GLUT1 expression correlated with adverse clinicopathological parameters and/or worse overall survival. Notably, however, GLUT1 was not retained as an independent prognostic factor in multivariable analysis.

We commend the authors for assembling a substantial cohort and for separately analyzing AC and SCC, which is a strength of the study. Nevertheless, we believe that several biological and methodological issues deserve further discussion before GLUT1 can be viewed as a robust prognostic biomarker or a plausible therapeutic stratification marker in NSCLC.

First, although GLUT1 is canonically regarded as a key glucose transporter and a surrogate of enhanced glycolytic activity, its biological interpretation in tumors may be more complex than tumor-cell-intrinsic glucose uptake alone (2). Increasing evidence suggests that, within the tumor microenvironment, immune cells—particularly activated effector immlung SCC, whereas no clear prognostic association was observed in lung ACune subsets—can be highly glucose-avid, whereas many tumor cells also exhibit substantial dependence on alternative nutrients, especially glutamine. In this context, GLUT1 immunoreactivity observed in bulk tumor sections should not automatically be interpreted as a direct reflection of malignant epithelial metabolic dependence. Rather, the immune contexture of the tumor and the cell populations in which GLUT1 is predominantly enriched should also be considered. This is especially relevant because the present study relied on immunohistochemistry in tissue microarrays, which provides limited resolution for defining the principal GLUT1-positive cellular compartment. Accordingly, we believe that single-cell transcriptomic or spatially resolved analyses would be highly informative in this setting (3,4). Such approaches could help clarify whether GLUT1 is mainly enriched in malignant epithelial cells, hypoxic tumor-border populations, stromal elements, or metabolically active immune subsets, and whether its prognostic implication differs according to the dominant expressing compartment. Without this level of cellular resolution, the translational interpretation of GLUT1 positivity in NSCLC remains incomplete.

Second, the prognostic significance of GLUT1 may differ substantially across histological subtypes and independent datasets. In our own interrogation of the Gene Expression Profiling Interactive Analysis (GEPIA) platform, GLUT1 appeared to be more closely associated with poor prognosis in lung SCC, whereas no clear prognostic association was observed in lung AC (Figure 1A) (5). This pattern is not fully concordant with the results reported by Hantzsch-Kuhn et al., who observed survival associations in both AC and SCC on univariable analysis. Such discrepancies suggest that the role of GLUT1 is unlikely to be uniform across NSCLC subtypes and instead warrants deeper subtype-specific investigation. Differences in cohort composition, staging structure, cutoff selection, treatment background, and analytic strategy may all contribute to these divergent observations.

Figure 1 Heterogeneous prognostic and functional relevance of SLC2A1/GLUT1 in lung cancer. (A) Kaplan-Meier survival analyses of SLC2A1 expression in lung squamous cell carcinoma (upper panel) and lung adenocarcinoma (lower panel) based on the GEPIA database. Patients were stratified into low- and high-expression groups according to the median SLC2A1 transcript level. (B) Distribution of SLC2A1 dependency scores across lung cancer cell line subtypes in the DepMap database. Each dot represents one cell line. Lower Chronos scores indicate stronger dependency on SLC2A1, whereas scores near zero or above indicate weak dependency or potential context-dependent growth-suppressive effects. (C) Correlation between SLC2A1 expression and CRISPR dependency (Chronos score) in lung cancer cell lines from the DepMap database. Each dot represents one cell line and is colored by subtype. The fitted line and shaded area indicate the overall trend and 95% confidence interval. CRISPR, clustered regularly interspaced short palindromic repeats; DepMap, Cancer Dependency Map; GEPIA, Gene Expression Profiling Interactive Analysis; GLUT1, glucose transporter 1; HR, hazard ratio; SLC2A1, solute carrier family 2 member 1; TPM, transcripts per million.

Third, functional dependency data also argue against a simplistic interpretation of GLUT1 as a universal therapeutic target in lung cancer. Our analysis of DepMap data suggests that the effect of GLUT1 is heterogeneous across lung cancer cell lines; in some models, its dependency is modest or inconsistent, and in a subset of contexts, GLUT1-related effects may even be compatible with tumor-suppressive behavior (Figure 1B,1C) (6). These observations imply that GLUT1-directed strategies may not exert uniform antitumor activity across lung cancers. Therefore, if GLUT1-targeted therapeutics are to be considered in the future, more precise preclinical assessment will be essential, ideally using biologically stratified systems such as patient-derived xenograft models, organoids, or other platforms that better preserve metabolic heterogeneity and tumor-microenvironment interactions than conventional cell lines.

In addition to these biological considerations, the methodological limitations of the current study should also temper interpretation. The analysis was performed on tissue microarrays using a single 0.6-mm core per tumor, an efficient design for large-scale screening but one that may insufficiently capture intratumoral heterogeneity, particularly for a metabolism-related membrane protein potentially influenced by regional hypoxia and microenvironmental variation. Moreover, while high GLUT1 expression was associated with poorer overall survival in univariable analyses, the marker did not remain independently prognostic in multivariable models. Thus, the current data may more convincingly support an association between GLUT1 and aggressive tumor phenotype than establish GLUT1 as an independent prognostic biomarker or therapeutic selection marker.

Taken together, this important study reinforces the relevance of GLUT1 in NSCLC biology, but we suggest that its clinical interpretation should be further refined. Future studies should aim to define the specific GLUT1-enriched cellular compartments, integrate immune-metabolic context, validate subtype-specific prognostic effects in external cohorts, and evaluate therapeutic relevance in more representative precision models such as PDX systems. Such efforts will be essential to determine whether GLUT1 is merely a correlate of aggressive disease or a truly actionable vulnerability in selected subsets of lung cancer.

Acknowledgments

The authors acknowledge that an AI language model (ChatGPT 5) was used to assist with English language polishing and style editing of this manuscript. The authors take full responsibility for the scientific content and the accuracy of all statements.

Footnote

Provenance and Peer Review: This article was a standard submission to the journal. 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://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0417/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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