背景:高级别浆液性卵巢癌(HGSOC),以其异质性而闻名,复发率高,和转移,通常在分散在几个地点后被诊断出来,约80%的患者经历复发。尽管对其转移性有了更好的了解,HGSOC患者的生存率仍然很低。
方法:我们的研究利用空间转录组学(ST)来解释肿瘤微环境,并利用计算机断层扫描(CT)来检查8例HGSOC患者的空间特征,这些患者分为复发(R)和具有挑战性的非复发(NR)组。
结果:通过整合ST数据与公共单细胞RNA测序数据,批量RNA测序数据,和CT数据,我们鉴定了与CT表型相关的特定细胞群富集和差异表达基因.重要的是,我们阐明了肿瘤坏死因子-α通过NF-κB,氧化磷酸化,G2/M检查点,E2F目标,和MYC目标作为复发的指标(不良预后标志物),这些途径在R组和某些CT表型中均显着富集。此外,我们确定了许多提示无复发的预后标志物(良好的预后标志物).在内部HGSOC样品以及公共HGSOCTCIA和TCGA样品中,PTGDS的表达下调与较高数量的接种位点(≥3个)有关。此外,根据我们的ST数据,R组肿瘤区和间质区的PTGDS表达低于NR组.在我们的ST和放射基因组学分析中,趋化性相关标志物(CXCL14和NTN4)和与免疫调节相关的标志物(DAPL1和RNASE1)也被发现是良好的预后标志物。
结论:这项研究证明了放射性基因组学的潜力,结合CT和ST,用于确定HGSOC的诊断和治疗靶标,标志着个性化医疗迈出了一步。
BACKGROUND: High-grade serous ovarian cancer (HGSOC), which is known for its heterogeneity, high recurrence rate, and metastasis, is often diagnosed after being dispersed in several sites, with about 80% of patients experiencing recurrence. Despite a better understanding of its metastatic nature, the survival rates of patients with HGSOC remain poor.
METHODS: Our study utilized spatial transcriptomics (ST) to interpret the tumor microenvironment and computed tomography (CT) to examine spatial characteristics in eight patients with HGSOC divided into recurrent (R) and challenging-to-collect non-recurrent (NR) groups.
RESULTS: By integrating ST data with public single-cell RNA sequencing data, bulk RNA sequencing data, and CT data, we identified specific cell population enrichments and differentially expressed genes that correlate with CT phenotypes. Importantly, we elucidated that tumor necrosis factor-α signaling via NF-κB, oxidative phosphorylation, G2/M checkpoint, E2F targets, and MYC targets served as an indicator of recurrence (poor prognostic markers), and these pathways were significantly enriched in both the R group and certain CT phenotypes. In addition, we identified numerous prognostic markers indicative of nonrecurrence (good prognostic markers). Downregulated expression of PTGDS was linked to a higher number of seeding sites (≥ 3) in both internal HGSOC samples and public HGSOC TCIA and TCGA samples. Additionally, lower PTGDS expression in the tumor and stromal regions was observed in the R group than in the NR group based on our ST data. Chemotaxis-related markers (CXCL14 and NTN4) and markers associated with immune modulation (DAPL1 and RNASE1) were also found to be good prognostic markers in our ST and
radiogenomics analyses.
CONCLUSIONS: This study demonstrates the potential of
radiogenomics, combining CT and ST, for identifying diagnostic and therapeutic targets for HGSOC, marking a step towards personalized medicine.