DOI: 10.4103/ijno.ijno_2_26 ISSN: 2590-2652

Glutamine-glutamate-lactate transporters in IDH-mutant low-grade glioma: Signals from a multi-omic exploration

Tahreem Fatima
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Abstract

Background:

In isocitrate dehydrogenase (IDH)-mutant low-grade glioma (LGG), patients with similar histology and canonical markers (IDH, 1p/19q, methylguanine‑DNA methyltransferase) can follow divergent clinical trajectories in survival, seizures, and edema. Current risk tools partly explain this variability. Glutamine, glutamate, and lactate are central to both glioma metabolism and neuronal excitability. It is unclear whether IDH-associated hypermethylation coordinately regulates the transporters that handle these metabolites, or the transporter states have functional support from genetic dependency data.

Materials and Methods:

A pathway-driven strategy focusing on five solute carriers that were selected as a priority-SLC1A3 (EAAT1; glutamate uptake), SLC1A5 (ASCT2), SLC38A1 (SNAT1) and SLC38A3 (SNAT3; glutamine/neutral amino-acid import), and SLC16A3 (MCT4; lactate export)-was opted for. Using The Cancer Genome Atlas (TCGA)-LGG, we assessed methylation-survival associations for cytosine‑phosphate‑guanine dinucleotide (CpG) in these genes. Expression-based survival was examined in GEPIA2, GlioVis, and GliomaDB (TCGA-LGG). Associated signaling states were accessed using TCGA reverse-phase protein arrays (RPPAs) in GlioVis and co-expression networks in GliomaDB. SLC16A3 expression was further evaluated in IDH-mutant and IDH-wild-type LGG, which were explored separately. To place these findings in context, existing data on glutamate-mediated epilepsy, peritumoral edema, and metabolic therapeutics in glioma were reviewed. Multivariable Cox regression in TCGA-LGG (adjusted for age and histology) was used to identify transporters independently associated with overall survival. External validation used Chinese Glioma Genome Atlas (CGGA) mRNAseq_325 survival analyses and clustered regularly interspaced short palindromic repeats (CRISPR) gene-effect scores from the Cancer Dependency Map (DepMap; Project Achilles).

Results:

Genome-wide, CpG-level survival screening in MethSurv and the cSurvival platform first identified prognostic methylation signals across the five transporters in TCGA-LGG. Within TCGA-LGG, CpGs in all five transporters showed hypermethylation associated with longer overall survival (typical hazard ratio [HR]: 0.2-0.6, false discovery rate: <0.05). This is suggestive of an epigenetic down-tuning of this transporter set that tends to occur in clinically favorable tumors. SLC1A5 and SLC16A3 additionally exhibited adverse expression-based survival in independent tools, with high expression associated with poorer outcome in GEPIA2 (SLC1A5 HR ≈ 2.3, P ≈ 1 × 10⁻⁵; SLC16A3 HR ≈ 2.6, P ≈ 1.8 × 10⁻⁶). Similarly, in GlioVis, high-expression groups had shorter median survival. In CGGA, high SLC1A5 and SLC16A3 expression correlated with shorter overall survival across primary WHO grades II–IV gliomas and in selected recurrent strata, qualitatively recapitulating the adverse transporter state. RPPA analyses indicated that SLC1A5-high and SLC16A3-high tumors more often displayed phosphorylation patterns consistent with activation of RTK-PI3K-mechanistic (mammalian) target of Rapamycin and mitogen‑activated protein kinase/stress pathways, whereas SLC16A3-low tumors tended to retain higher PTEN/INPP4B/TSC1 and lipogenic enzymes such as ACC1 and fatty acid synthase. Co-expression networks placed SLC16A3 in an immune/adhesion module (e.g., VASP, IL4R, TNFRSF1B, and FERMT3) inversely related to neuronal/differentiation genes (e.g., MAP2 and LSAMP ), and high SLC16A3 was associated with worse survival in both IDH-wild-type and IDH-mutant LGG in GliomaDB (HR ≈ 1.8-1.9). SLC1A3, SLC38A1, and SLC38A3 showed strong methylation-survival associations but neutral or inconsistent expression–survival, indicating that they may mark specific epigenetic states not fully captured by bulk RNA. DepMap CRISPR data showed that SLC1A5 and SLC16A3 have strongly selective negative gene-effect scores in a subset of cancer cell lines and are classified as druggable membrane transporters, supporting context-specific requirement for tumor cell fitness. These patterns are consistent with former wet-lab studies showing that SLC1A5-mediated glutamine uptake and SLC16A3-mediated lactate export support tumor growth, mechanistic (mammalian) target of Rapamycin / receptor tyrosine kinase signaling, and immune-evasive metabolic reprogramming in experimental cancer models. We focused our subsequent analyses on this transporter set to determine whether a coherent prognostic and signaling pattern exists in glioma.

Conclusion:

This pathway-focused, multi-omic analysis suggests that, within IDH-mutant LGG, there may exist at least two transport-related states: a transporter-suppressed state with hypermethylation and low expression of glutamine and lactate transporters, and a transporter-activated state with high SLC1A5/SLC16A3 expression, multi-pathway signaling activation, and external support from CGGA survival and DepMap genetic dependency data. Although correlative, these patterns generate testable hypotheses that transporter states may contribute to heterogeneity in survival and potentially in glutamate-related seizures and edema, and that they could help prioritize patients and targets for trials of ASCT2/MCT4 and related metabolic interventions.

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