探索作为乳腺癌重要预后标志物的 SALL4 及其与癌症发生过程中的进展途径的关联。

IF 2.6 4区 生物学 Q2 BIOLOGY
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引用次数: 0

摘要

乳腺癌是导致女性癌症死亡的首要因素。由于其固有的分子亚型众多,乳腺癌是一种极其多样化的疾病。在这些亚型中,人类表皮生长因子受体2(HER2)阳性亚型尤为突出,特别容易发生癌变和复发。胚胎干细胞的多能性和自我更新是由SALL4(Spalt样转录因子4)家族成员调控的。在转录、转录后和表观基因组水平上运行的众多分子途径调控着SALL4的表达。许多转录因子控制着 SALL4 的表达,其中 STAT3 是肝细胞癌(HCC)和乳腺癌的主要调节因子。此外,这种癌基因还与多种细胞功能有关,包括侵袭、凋亡、增殖和抗药性。患者生存率降低和预后恶化与 SALL4 水平升高有关。为了靶向乳腺癌中过表达的不可药用的 SALL4,我们研究了乳腺癌中 SALL4 的预后水平及其与各种相关蛋白的相互作用。我们使用 TIMER 2.0 分析方法研究了所有 TCGA 数据集中 SALL4 的表达模式。研究发现,SALL4 在各种癌症中的表达都有所升高。UALCAN 的研究结果表明,SALL4 在所有肿瘤样本中都有过表达,包括乳腺癌,尤其是 TNBC(三阴性乳腺癌)。我们利用基于网络的 ENRICHR 程序进行了基因本体分析,发现 SALL4 积极参与了神经系统的发育、干细胞增殖的正向调节、干细胞增殖的调节、激活素受体信号通路的调节、使用 DNA 模板的转录调节、miRNA 代谢过程以及 RNA 聚合酶 I 的转录调节。此外,我们还利用bc-GenExMiner研究了SALL4对不同乳腺癌亚型中突然激活的通路的影响,结果显示SALL4与WNT2B、NOTCH4、AKT3和PIK3CA高度相关。此外,为了靶向 SALL4,我们评估并分析了 CLP 及其类似物的影响,结果令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring SALL4 as a significant prognostic marker in breast cancer and its association with progression pathways involved in cancer genesis

Breast carcinoma is the leading factor in women's cancer-related fatalities. Due to its numerous inherent molecular subtypes, breast cancer is an extremely diverse illness. The human epidermal growth factor receptor 2 (HER2) positive subtypes stands out among these subtypes as being especially prone to cancer development and illness recurrence. The regulation of embryonic stem cells' pluripotency and self-renewal is carried out by the SALL4 (Spalt-like transcription factor 4) family member. Numerous molecular pathways operating at the transcriptional, post-transcriptional, and epigenomic levels regulate the expression of SALL4. Many transcription factors control the expression of SALL4, with STAT3 being the primary regulator in hepatocellular carcinoma (HCC) and breast carcinoma. Moreover, this oncogene has been connected to a number of cellular functions, including invasion, apoptosis, proliferation, and resistance to therapy. Reduced patient survival rates and a worse prognosis have been linked to higher levels of SALL4. In order to target the undruggable SALL4 that is overexpressed in breast carcinoma, we investigated the prognostic levels of SALL4 in breast carcinoma and its interaction with various related proteins. Using TIMER 2.0 analysis, the expression pattern of SALL4 was investigated across all TCGA datasets. The research revealed that SALL4 expression was elevated in various cancers. The UALCAN findings demonstrated that SALL4 was overexpressed in all tumor samples including breast cancer especially TNBC (Triple negative breast cancer). The web-based ENRICHR program was used for gene ontology analysis that revealed SALL4 was actively involved in the development of the nervous system, positive regulation of stem cell proliferation, regulation of stem cell proliferation, regulation of the activin receptor signaling pathway, regulation of transcription using DNA templates, miRNA metabolic processes, and regulation of transcription by RNA Polymerase I. Using the STRING database, we analyzed the interaction and involvement of SALL4 with other abruptly activated proteins and used Cytoscape 3.8.0 for visualization. Additionally, using bc-GenExMiner, we studied the impact of SALL4 on pathways abruptly activated in different breast cancer subtypes that revealed SALL4 was highly correlated with WNT2B, NOTCH4, AKT3, and PIK3CA. Furthermore, to target SALL4, we evaluated and analyzed the impact of CLP and its analogues, revealing promising outcomes.

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来源期刊
Computational Biology and Chemistry
Computational Biology and Chemistry 生物-计算机:跨学科应用
CiteScore
6.10
自引率
3.20%
发文量
142
审稿时长
24 days
期刊介绍: Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.
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