Ju Hye-Yeon, Youn Seo Yeon, Kang Jun, Whang Min Yeop, Choi Youn Jin, Han Mi-Ryung
Division of Life Sciences, College of Life Sciences and Bioengineering, Incheon National University, Incheon, 22012, Korea.
Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, 06591, Korea.
Biomark Res. 2024 Aug 12;12(1):80. doi: 10.1186/s40364-024-00632-7.
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.
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.
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.
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.
高级别浆液性卵巢癌（HGSOC）以其异质性、高复发率和转移而闻名，常在扩散至多个部位后才被诊断出来，约80%的患者会复发。尽管对其转移特性有了更好的理解，但HGSOC患者的生存率仍然很低。
我们的研究利用空间转录组学（ST）来解读肿瘤微环境，并利用计算机断层扫描（CT）来检查8例HGSOC患者的空间特征，这些患者被分为复发组（R）和难以采集的非复发组（NR）。
通过将ST数据与公共单细胞RNA测序数据、大量RNA测序数据和CT数据相结合，我们确定了与CT表型相关的特定细胞群富集和差异表达基因。重要的是，我们阐明了通过核因子κB的肿瘤坏死因子-α信号传导、氧化磷酸化、G2/M检查点、E2F靶点和MYC靶点可作为复发的指标（不良预后标志物），并且这些通路在R组和某些CT表型中均显著富集。此外，我们还确定了许多表明无复发的预后标志物（良好预后标志物）。在内部HGSOC样本以及公共HGSOC TCIA和TCGA样本中，前列腺素D合成酶（PTGDS）表达下调与更高数量的播散部位（≥3个）相关。此外，根据我们的ST数据，R组肿瘤和基质区域的PTGDS表达低于NR组。在我们的ST和放射基因组学分析中，趋化相关标志物（CXCL14和NTN4）以及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。
本研究证明了结合CT和ST的放射基因组学在识别HGSOC诊断和治疗靶点方面的潜力，标志着向个性化医学迈出了一步。
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