Background/Objectives: Endometrial cancer (EC) is the most common malignancy of the female genital tract. In 2013, The Cancer Genome Atlas analyzed the molecular profile of endometrial tumors identifying four risk classes (POLE ultramutated, mismatch repair-deficient, copy-number low-microsatellite stable, and copy-number high-serous-like. This classification is reshaping the current understanding of EC, enabling more refined risk stratification and uncovering potential therapeutic targets tailored to specific molecular subgroups. In the context of these four categories, it is possible to identify different molecular alterations that correlate with different prognoses. Methods and Results: We retrospectively analyzed tissue samples from eighty-five EC patients, performing multigene profiling using a 50-gene next-generation sequencing (NGS) panel to categorize them into distinct molecular subtypes; we observed the following distribution: 5.9% POLE, 25.8% mismatch repair-deficient/microsatellite instability (MMRd/MSI), 11.8% p53abn/TP53mut, and 56.5% NSMP. A favorable concordance (97.6%) was shown in MSI NGS-based analysis and MMR IHC results, and the agreement rate of p53 IHC andTP53mutation was 92.3%. When we analyzed the correlation between molecular subtypes and clinicopathological features, we found that molecular subtypes significantly differentiated by grade, FIGO stage, and lymphovascular invasion (LVSI). These findings seem to support the effectiveness of our NGS-based classifier and its reliability in distinguishing both MSI and TP53 mutated cancers. This study also explored mutations inPIK3CA,PTEN,KRAS,ERBB2, andESR1genes, noting their potential as targets for treatments.PIK3CAmutations were linked to favorable features, such as early disease stage and absence of LVSI. Conclusions: Our study highlights the potential of a medium-complexity NGS panel for supporting the molecular classification of endometrial cancer, complementing the existing diagnostic algorithms. By identifying additional biomarkers, we provided valuable insights into the genomic landscape of EC. However, further exploration of the molecular profiles is needed to validate these findings and improve the identification of patients at a higher risk of unfavorable outcomes.
背景/目的：子宫内膜癌是女性生殖系统最常见的恶性肿瘤。2013年，癌症基因组图谱项目通过分析子宫内膜肿瘤的分子特征，确立了四种风险类别（POLE超突变型、错配修复缺陷型、拷贝数低-微卫星稳定型、拷贝数高-浆液样型）。这一分类体系正在重塑当前对子宫内膜癌的认知，有助于实现更精细的风险分层，并揭示针对特定分子亚群的潜在治疗靶点。基于这四类分型，可识别出与不同预后相关的分子变异特征。方法与结果：我们回顾性分析了85例子宫内膜癌患者的组织样本，采用包含50个基因的新一代测序（NGS）检测组合进行多基因谱分析，将其划分为不同分子亚型，观察到以下分布：POLE型5.9%、错配修复缺陷/微卫星不稳定型25.8%、p53异常/TP53突变型11.8%、非特异性分子谱型56.5%。基于NGS的微卫星不稳定检测与错配修复蛋白免疫组化结果具有良好一致性（97.6%），p53免疫组化与TP53突变检测符合率达92.3%。分析分子亚型与临床病理特征的相关性时，发现不同分子亚型在肿瘤分级、国际妇产科联盟分期及淋巴脉管间隙浸润方面存在显著差异。这些发现支持了基于NGS的分类体系在区分微卫星不稳定型和TP53突变型肿瘤方面的有效性与可靠性。本研究还探讨了PIK3CA、PTEN、KRAS、ERBB2和ESR1基因的突变情况，指出其作为治疗靶点的潜力。其中PIK3CA突变与早期疾病分期、无淋巴脉管间隙浸润等良好预后特征相关。结论：本研究证明中等通量NGS检测组合具有支持子宫内膜癌分子分型的潜力，可对现有诊断流程形成有效补充。通过识别更多生物标志物，我们为解析子宫内膜癌基因组特征提供了重要依据。然而，仍需进一步探索分子谱特征以验证这些发现，并提升对不良预后高风险患者的识别能力。
肿瘤(癌症)患者之家