Network propagation-based identification of oligometastatic biomarkers in metastatic colorectal cancer

IF 2.4 3区 生物学 Q3 BIOCHEMICAL RESEARCH METHODS
Qing Jin, Kexin Yu, Xianze Zhang, Diwei Huo, Denan Zhang, Lei Liu, Hongbo Xie, Binhua Liang, Xiujie Chen
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引用次数: 0

Abstract

Background: The oligometastatic disease has been proposed as an intermediate state between primary tumor and systemically metastatic disease, which has great potential curable with locoregional therapies. However, since no biomarker for the identification of patients with true oligometastatic disease is clinically available, the diagnosis of oligometastatic disease remains controversial. Objective: We aim to identify potential biomarkers of colorectal cancer patients with true oligometastatic states, who will benefit most from local therapy. Methods: This study retrospectively analyzed the transcriptome profiles and clinical parameters of 307 metastatic colorectal cancer patients. A novel network propagation method and network-based strategy were combined to identify oligometastatic biomarkers to predict the prognoses of metastatic colorectal cancer patients. Results: We defined two metastatic risk groups according to twelve oligometastatic biomarkers, which exhibit distinct prognoses, clinicopathological features, immunological characteristics, and biological mechanisms. The metastatic risk assessment model exhibited a more powerful capacity for survival prediction compared to traditional clinicopathological features. The low-MRS group was most consistent with an oligometastatic state, while the high-MRS might be a potential polymetastatic state, which leads to the divergence of their prognostic outcomes and response to treatments. We also identified 22 significant immune check genes between the high-MRS and low- MRS groups. The difference in molecular mechanism between the two metastatic risk groups was associated with focal adhesion, nucleocytoplasmic transport, Hippo, PI3K-Akt, TGF-β, and EMCreceptor interaction signaling pathways. Conclusion: Our study provided a molecular definition of the oligometastatic state in colorectal cancer, which contributes to precise treatment decision-making for advanced patients.
基于网络传播的转移性结直肠癌低转移性生物标志物鉴定
背景:寡转移性疾病被认为是介于原发肿瘤和全身转移性疾病之间的一种中间状态,通过局部治疗具有很大的治愈潜力。然而,由于临床上没有识别真正的少转移性疾病患者的生物标志物,因此对少转移性疾病的诊断仍然存在争议。目的:我们的目标是确定具有真正少转移状态的结直肠癌患者的潜在生物标志物,这些患者将从局部治疗中获益最多。方法:回顾性分析307例转移性结直肠癌患者的转录组谱和临床参数。结合一种新的网络传播方法和基于网络的策略来识别低转移性生物标志物,以预测转移性结直肠癌患者的预后。结果:我们根据12个低转移性生物标志物定义了两个转移风险组,这些生物标志物表现出不同的预后、临床病理特征、免疫学特征和生物学机制。与传统的临床病理特征相比,转移性风险评估模型显示出更强大的生存预测能力。低mrs组最符合低转移状态,而高mrs组可能是潜在的多转移状态,这导致了他们的预后结果和对治疗的反应的差异。我们还在高MRS组和低MRS组之间鉴定了22个显著的免疫检查基因。两个转移风险组的分子机制差异与局灶黏附、核质转运、Hippo、PI3K-Akt、TGF-β和emc受体相互作用信号通路有关。结论:我们的研究提供了结直肠癌低转移状态的分子定义,有助于晚期患者的精确治疗决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Current Bioinformatics
Current Bioinformatics 生物-生化研究方法
CiteScore
6.60
自引率
2.50%
发文量
77
审稿时长
>12 weeks
期刊介绍: Current Bioinformatics aims to publish all the latest and outstanding developments in bioinformatics. Each issue contains a series of timely, in-depth/mini-reviews, research papers and guest edited thematic issues written by leaders in the field, covering a wide range of the integration of biology with computer and information science. The journal focuses on advances in computational molecular/structural biology, encompassing areas such as computing in biomedicine and genomics, computational proteomics and systems biology, and metabolic pathway engineering. Developments in these fields have direct implications on key issues related to health care, medicine, genetic disorders, development of agricultural products, renewable energy, environmental protection, etc.
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