Sha Zhilin, Gao Qingxiang, Wang Lei, An Ni, Wu Yingjun, Wei Dong, Wang Tong, Liu Chen, Shen Yang
Department I of Biliary Tract Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, People's Republic of China.
Department of General Surgery, Yancheng Hospital of Traditional Chinese Medicine, Yancheng, Jiang Su, People's Republic of China.
Onco Targets Ther. 2024 Apr 17;17:345-358. doi: 10.2147/OTT.S454295. eCollection 2024.
BACKGROUND: Colorectal cancer (CRC) is one of the deadliest causes of death by cancer worldwide. Liver metastasis (LM) is the main cause of death in patients with CRC. Therefore, identification of patients with the greatest risk of liver metastasis is critical for early treatment and reduces the mortality of patients with colorectal cancer liver metastases. METHODS: Initially, we characterized cell composition through single-cell transcriptome analysis. Subsequently, we employed copy number variation (CNV) and pseudotime analysis to delineate the cellular origins of LM and identify LM-related epithelial cells (LMECs). The LM-index was constructed using machine learning algorithms to forecast the relative abundance of LMECs, reflecting the risk of LM. Furthermore, we analyzed drug sensitivity and drug targeted gene expression in LMECs and patients with a high risk of LM. Finally, functional experiments were conducted to determine the biological roles of metastasis-related gene in vitro. RESULTS: Single-cell RNA sequencing analysis revealed different immune landscapes between primary CRC and LM tumor. LM originated from chromosomal variants with copy number loss of chr1 and chr6p and copy number gain of chr7 and chr20q. We identified the LMECs cluster and found LM-associated pathways such as Wnt/beta-catenin signaling and KRAS signaling. Subsequently, we identified ten metastasis-associated genes, including SOX4, and established the LM-index, which correlates with poorer prognosis, higher stage, and advanced age. Furthermore, we screened two drugs as potential candidates for treating LM, including Linsitinib_1510, Lapatinib_1558. Immunohistochemistry results demonstrated significantly elevated SOX4 expression in tumor samples compared to normal samples. Finally, in vitro experiments verified that silencing SOX4 significantly inhibited tumor cell migration and invasion. CONCLUSION: This study reveals the possible cellular origin and driving factors of LM in CRC at the single cell level, and provides a reference for early detection of CRC patients with a high risk of LM.
背景：结直肠癌（CRC）是全球癌症致死的主要原因之一。肝转移（LM）是CRC患者死亡的主要原因。因此，识别肝转移风险最高的患者对于早期治疗至关重要，并可降低结直肠癌肝转移患者的死亡率。 方法：首先，我们通过单细胞转录组分析来表征细胞组成。随后，我们采用拷贝数变异（CNV）和伪时间分析来描绘LM的细胞起源，并识别与LM相关的上皮细胞（LMECs）。使用机器学习算法构建LM指数，以预测LMECs的相对丰度，反映LM风险。此外，我们分析了LMECs和高LM风险患者的药物敏感性和药物靶向基因表达。最后，进行功能实验以确定转移相关基因在体外的生物学作用。 结果：单细胞RNA测序分析揭示了原发性CRC和LM肿瘤之间不同的免疫格局。LM起源于染色体变异，chr1和chr6p拷贝数丢失，chr7和chr20q拷贝数增加。我们识别出LMECs簇，并发现了与LM相关的信号通路，如Wnt/β-连环蛋白信号通路和KRAS信号通路。随后，我们识别出10个转移相关基因，包括SOX4，并建立了LM指数，该指数与较差的预后、更高的分期和高龄相关。此外，我们筛选出两种药物作为治疗LM的潜在候选药物，包括Linsitinib_1510、Lapatinib_1558。免疫组化结果显示，与正常样本相比，肿瘤样本中SOX4表达显著升高。最后，体外实验证实，沉默SOX4可显著抑制肿瘤细胞的迁移和侵袭。 结论：本研究在单细胞水平揭示了CRC中LM可能的细胞起源和驱动因素，并为早期检测高LM风险的CRC患者提供了参考。
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