Mounting evidence has highlighted the multifunctional characteristics of glutamine metabolism (GM) in cancer initiation, progression and therapeutic regimens. However, the overall role of GM in the tumour microenvironment (TME), clinical stratification and therapeutic efficacy in patients with ovarian cancer (OC) has not been fully elucidated. Here, three distinct GM clusters were identified and exhibited different prognostic values, biological functions and immune infiltration in TME. Subsequently, glutamine metabolism prognostic index (GMPI) was constructed as a new scoring model to quantify the GM subtypes and was verified as an independent predictor of OC. Patients with low‐GMPI exhibited favourable survival outcomes, lower enrichment of several oncogenic pathways, less immunosuppressive cell infiltration and better immunotherapy responses. Single‐cell sequencing analysis revealed a unique evolutionary trajectory of OC cells from high‐GMPI to low‐GMPI, and OC cells with different GMPI might communicate with distinct cell populations through ligand‐receptor interactions. Critically, the therapeutic efficacy of several drug candidates was validated based on patient‐derived organoids (PDOs). The proposed GMPI could serve as a reliable signature for predicting patient prognosis and contribute to optimising therapeutic strategies for OC.

中文翻译：

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谷氨酰胺代谢预后指数预测卵巢癌肿瘤微环境特征和治疗效果

越来越多的证据强调了谷氨酰胺代谢 (GM) 在癌症发生、进展和治疗方案中的多功能特征。然而，GM在卵巢癌（OC）患者的肿瘤微环境（TME）、临床分层和治疗效果中的总体作用尚未完全阐明。在此，鉴定出三个不同的 GM 簇，并在 TME 中表现出不同的预后价值、生物学功能和免疫浸润。随后，构建了谷氨酰胺代谢预后指数（GMPI）作为量化 GM 亚型的新评分模型，并被验证为 OC 的独立预测因子。低 GMPI 患者表现出良好的生存结果、几种致癌途径的富集度较低、免疫抑制细胞浸润较少、免疫治疗反应较好。单细胞测序分析揭示了 OC 细胞从高 GMPI 到低 GMPI 的独特进化轨迹，并且具有不同 GMPI 的 OC 细胞可能通过配体受体相互作用与不同的细胞群进行通信。重要的是，几种候选药物的治疗效果是根据患者来源的类器官（PDO）进行验证的。所提出的 GMPI 可以作为预测患者预后的可靠特征，并有助于优化 OC 的治疗策略。