高级别浆液性卵巢癌（HGSOC）由于其异质性和晚期诊断而面临重大挑战。使用单细胞和空间转录组学来阐明 HGSOC 的复杂景观，以了解其潜在机制。我们的分析揭示了显着的肿瘤间和肿瘤内多样性，这通过不同的细胞亚群和不同的微环境生态位表现出来。值得注意的是，我们的研究结果强调了广泛的免疫抑制环境，其特征是复杂的细胞间相互作用网络，在转移样本中肿瘤细胞密度升高的区域尤其明显。我们确定了转移标本中仅存在 COL14A1 肿瘤细胞，同时 CD8A NKT 细胞与不良预后之间存在很强的相关性，并且 HGSOC 转移组织中 CHODL 表达升高。此外，针对 CHODL 的敲除实验证明了其在降低 HGSOC 细胞迁移和侵袭能力方面的作用。我们研究的一个关键发现是描绘与不良后果相关的特定细胞特征，特别是 CHODL 肿瘤细胞的子集，其特征是具有独特的代谢表型，且倾向于脂质代谢。利用现有抑制剂以这种代谢途径为靶标进行治疗似乎有望抑制肿瘤增殖。这些发现增强了我们对 HGSOC 异质性的理解，并揭示了潜在的治疗靶点，有望为这种侵袭性癌症亚型提供更有效的管理策略。版权所有 © 2024 Luo、Wang 和 Li。

High-grade serous ovarian cancer (HGSOC) presents significant challenges due to its heterogeneity and late-stage diagnoses. Using single-cell and spatial transcriptomics to elucidate the complex landscape of HGSOC to understand its underlying mechanism. Our analysis reveals significant inter- and intra-tumoral diversity, manifested through distinct cellular subpopulations and varied microenvironmental niches. Notably, our findings highlight a widespread immunosuppressive environment, marked by complex networks of cell-cell interactions, particularly evident in areas of elevated tumor cell density within metastatic samples. We identify the exclusive presence of COL14A1+ neoplastic cells in metastatic specimens, alongside a strong correlation between CD8A+ NKT cells and poor prognosis, and elevated CHODL expression in HGSOC metastasis tissues. Furthermore, knockdown experiments targeting CHODL demonstrate its role in reducing migration and invasion abilities in HGSOC cells. A pivotal discovery of our study is the delineation of specific cellular signatures correlated with adverse outcomes, notably a subset of CHODL+ neoplastic cells characterized by a distinct metabolic phenotype with a predilection for lipid metabolism. The therapeutic targeting of this metabolic pathway with existing inhibitors appears promising in curbing tumor proliferation. These findings enhance our understanding of HGSOC heterogeneity and reveal potential therapeutic targets, promising more effective management strategies for this aggressive cancer subtype.Copyright © 2024 Luo, Wang and Li.