Purpose

Metabolic reprogramming is currently considered a hallmark of tumor and immune development. It is obviously of interest to identify metabolic enzymes that are associated with clinical prognosis in head and neck squamous cell carcinomas (HNSCC).

Methods

Candidate genes were screened to construct folate metabolism scores by Cox regression analysis. Functional enrichment between high- and low-folate metabolism groups was explored by GO, KEGG, GSVA, and ssGSEA. EPIC, MCPcounter, and xCell were utilized to explore immune cell infiltration between high- and low-folate metabolism groups. Relevant metabolic scores were calculated and visually analyzed by the “IOBR” software package.

Results

To investigate the mechanism behind metabolic reprogramming of HNSCC, 2886 human genes associated with 86 metabolic pathways were selected. Folate metabolism is significantly enriched in HNSCC, and that the six-gene (MTHFD1L, MTHFD2, SHMT2, ATIC, MTFMT, and MTHFS) folate score accurately predicts and differentiates folate metabolism levels. Reprogramming of folate metabolism affects CD8T cell infiltration and induces immune escape through the MIF signaling pathway. Further research found that SHMT2, an enzyme involved in folate metabolism, inhibits CD8T cell infiltration and induces immune escape by regulating the MIF/CD44 signaling axis, which in turn promotes HNSCC progression.

Conclusions

Our study identified a novel and robust folate metabolic signature. A folate metabolic signature comprising six genes was effective in assessing the prognosis and reflecting the immune status of HNSCC patients. The target molecule of folate metabolic reprogramming, SHMT2, probably plays a very important role in HNSCC development and immune escape.

中文翻译：

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用于预测 HNSCC 预后的叶酸代谢相关基因特征的构建和验证

目的

代谢重编程目前被认为是肿瘤和免疫发育的标志。鉴定与头颈鳞状细胞癌（HNSCC）临床预后相关的代谢酶显然很有意义。

方法

通过Cox回归分析筛选候选基因以构建叶酸代谢评分。通过 GO、KEGG、GSVA 和 ssGSEA 探索了高叶酸代谢组和低叶酸代谢组之间的功能富集。利用 EPIC、MCPcounter 和 xCell 来探索高叶酸代谢组和低叶酸代谢组之间的免疫细胞浸润。通过“IOBR”软件包计算并直观分析相关代谢评分。

结果

为了研究 HNSCC 代谢重编程背后的机制，选择了与 86 条代谢途径相关的 2886 个人类基因。叶酸代谢在 HNSCC 中显着富集，六基因（MTHFD1L、MTHFD2、SHMT2、ATIC、MTFMT 和 MTHFS）叶酸评分可准确预测和区分叶酸代谢水平。叶酸代谢的重编程影响 CD8T 细胞浸润并通过 MIF 信号通路诱导免疫逃逸。进一步研究发现，参与叶酸代谢的酶SHMT2通过调节MIF/CD44信号轴抑制CD8T细胞浸润并诱导免疫逃逸，进而促进HNSCC进展。

结论

我们的研究发现了一种新颖且强大的叶酸代谢特征。包含六个基因的叶酸代谢特征可有效评估 HNSCC 患者的预后并反映免疫状态。叶酸代谢重编程的靶分子 SHMT2 可能在 HNSCC 的发生和免疫逃逸中发挥着非常重要的作用。