癌症发病机制中炎症信号的解码系统生物学:来自12种常见癌症的泛癌见解。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-10-01 DOI:10.1089/omi.2023.0127
Beste Turanli
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引用次数: 0

摘要

慢性炎症是许多组织中肿瘤发生的重要因素。然而,在各种癌症中,肿瘤微环境中炎症信号传导的潜在机制尚不完全清楚。因此,本研究旨在揭示导致肿瘤发生的炎症相关蛋白的基因表达特征,并着眼于发现肿瘤学中潜在的系统生物标志物和新的候选药物。检索癌症基因组图谱中与12种常见癌症(如乳腺浸润癌、结肠癌、肝细胞癌和前列腺癌)相关的基因表达谱,并将其映射到炎症相关基因集。随后,确定了炎症相关差异表达基因(i-DEG)。在全癌分析后,提出了所有癌症中常见的i-DEG作为肿瘤炎症特征(TIS)。由45种蛋白质组成的TIS被评估为一种潜在的系统生物标志物,基于其在多种组织中的预后预测和分泌谱。此外,每种癌症类型的i-DEG被用作药物再利用的查询。Narciclasine、孤雌内酯和高三尖杉酯碱被确定为药物再利用的潜在候选药物。确定了与炎症相关的候选生物标志物,如KNG1、SPP1和MIF。总之,这些发现为精确诊断的发展提供了信息,以区分单个癌症类型,也可以为多种癌症的新预后决策工具和重新调整用途的药物铺平道路。这些新的发现和假设保证了肿瘤学中精确/个性化医学的进一步研究。炎症介质的泛癌分析可以为癌症诊断和治疗开辟新的创新途径。
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Decoding Systems Biology of Inflammation Signatures in Cancer Pathogenesis: Pan-Cancer Insights from 12 Common Cancers.

Chronic inflammation is an important contributor to tumorigenesis in many tissues. However, the underlying mechanisms of inflammatory signaling in the tumor microenvironment are not yet fully understood in various cancers. Therefore, this study aimed to uncover the gene expression signatures of inflammation-associated proteins that lead to tumorigenesis, and with an eye to discovery of potential system biomarkers and novel drug candidates in oncology. Gene expression profiles associated with 12 common cancers (e.g., breast invasive carcinoma, colon adenocarcinoma, liver hepatocellular carcinoma, and prostate adenocarcinoma) from The Cancer Genome Atlas were retrieved and mapped to inflammation-related gene sets. Subsequently, the inflammation-associated differentially expressed genes (i-DEGs) were determined. The i-DEGs common in all cancers were proposed as tumor inflammation signatures (TIS) after pan-cancer analysis. A TIS, consisting of 45 proteins, was evaluated as a potential system biomarker based on its prognostic forecasting and secretion profiles in multiple tissues. In addition, i-DEGs for each cancer type were used as queries for drug repurposing. Narciclasine, parthenolide, and homoharringtonine were identified as potential candidates for drug repurposing. Biomarker candidates in relation to inflammation were identified such as KNG1, SPP1, and MIF. Collectively, these findings inform precision diagnostics development to distinguish individual cancer types, and can also pave the way for novel prognostic decision tools and repurposed drugs across multiple cancers. These new findings and hypotheses warrant further research toward precision/personalized medicine in oncology. Pan-cancer analysis of inflammatory mediators can open up new avenues for innovation in cancer diagnostics and therapeutics.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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