Central Laboratory, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, 100026, China.
J Transl Med. 2021 Oct 30;19(1):454. doi: 10.1186/s12967-021-03123-7.
Ovarian cancer was one of the leading causes of female deaths. Patients with OC were essentially incurable and portends a poor prognosis, presumably because of profound genetic heterogeneity limiting reproducible prognostic classifications.
We comprehensively analyzed an ovarian cancer single-cell RNA sequencing dataset, GSE118828, and identified nine major cell types. Relationship between the clusters was explored with CellPhoneDB. A malignant epithelial cluster was confirmed using pseudotime analysis, CNV and GSVA. Furthermore, we constructed the prediction model (i.e., RiskScore) consisted of 10 prognosis-specific genes from 2397 malignant epithelial genes using the LASSO Cox regression algorithm based on public datasets. Then, the prognostic value of Riskscore was assessed with Kaplan-Meier survival analysis and time-dependent ROC curves. At last, a series of in-vitro assays were conducted to explore the roles of IL4I1, an important gene in Riskscore, in OC progression.
We found that macrophages possessed the most interaction pairs with other clusters, and M2-like TAMs were the dominant type of macrophages. C0 was identified as the malignant epithelial cluster. Patients with a lower RiskScore had a greater OS (log-rank P < 0.01). In training set, the AUC of RiskScore was 0.666, 0.743 and 0.809 in 1-year, 3-year and 5-year survival, respectively. This was also validated in another two cohorts. Moreover, downregulation of IL4I1 inhibited OC cells proliferation, migration and invasion.
Our work provide novel insights into our understanding of the heterogeneity among OCs, and would help elucidate the biology of OC and provide clinical guidance in prognosis for OC patients.
卵巢癌是女性死亡的主要原因之一。OC 患者基本上无法治愈，预后不良，这可能是由于深刻的遗传异质性限制了可重复的预后分类。
我们全面分析了一个卵巢癌单细胞 RNA 测序数据集 GSE118828，并鉴定了九个主要细胞类型。使用 CellPhoneDB 探索了簇之间的关系。通过伪时间分析、CNV 和 GSVA 确认了恶性上皮簇。此外，我们使用基于公共数据集的 LASSO Cox 回归算法从 2397 个恶性上皮基因中构建了由 10 个预后特异性基因组成的预测模型（即 RiskScore）。然后，通过 Kaplan-Meier 生存分析和时间依赖的 ROC 曲线评估 RiskScore 的预后价值。最后，进行了一系列体外实验来探索 Riskscore 中的重要基因 IL4I1 在 OC 进展中的作用。
我们发现巨噬细胞与其他簇具有最多的相互作用对，并且 M2 样 TAMs 是巨噬细胞的主要类型。C0 被鉴定为恶性上皮簇。RiskScore 较低的患者 OS 更高（对数秩 P<0.01）。在训练集中，RiskScore 的 AUC 在 1 年、3 年和 5 年生存率分别为 0.666、0.743 和 0.809。这在另外两个队列中也得到了验证。此外，下调 IL4I1 抑制了 OC 细胞的增殖、迁移和侵袭。
我们的工作为我们理解 OC 之间的异质性提供了新的见解，并将有助于阐明 OC 的生物学，并为 OC 患者的预后提供临床指导。
