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JeongYun Choi Haeseung Lee EunJi Kwon HyeonJoon Kong OkSeon Kwon HyukJin Cha 《Molecular oncology》2021,15(2):679
The acquisition of chemoresistance remains a major cause of cancer mortality due to the limited accessibility of targeted or immune therapies. However, given that severe alterations of molecular features during epithelial‐to‐mesenchymal transition (EMT) lead to acquired chemoresistance, emerging studies have focused on identifying targetable drivers associated with acquired chemoresistance. Particularly, AXL, a key receptor tyrosine kinase that confers resistance against targets and chemotherapeutics, is highly expressed in mesenchymal cancer cells. However, the underlying mechanism of AXL induction in mesenchymal cancer cells is poorly understood. Our study revealed that the YAP signature, which was highly enriched in mesenchymal‐type lung cancer, was closely correlated to AXL expression in 181 lung cancer cell lines. Moreover, using isogenic lung cancer cell pairs, we also found that doxorubicin treatment induced YAP nuclear translocation in mesenchymal‐type lung cancer cells to induce AXL expression. Additionally, the concurrent activation of TGFβ signaling coordinated YAP‐dependent AXL expression through SMAD4. These data suggest that crosstalk between YAP and the TGFβ/SMAD axis upon treatment with chemotherapeutics might be a promising target to improve chemosensitivity in mesenchymal‐type lung cancer.
Abbreviations
- AUC
- area under the curve
- AXL
- AXL receptor tyrosine kinase
- BCL2
- B‐cell lymphoma 2
- CTD2
- cancer target discovery and development
- CTGF
- connective tissue growth factor
- DEG
- differentially expressed genes
- DOXO
- doxorubicin
- EMT
- epithelial–mesenchymal transition
- Eto
- etoposide
- FDA
- Food and Drug Administration
- ITGB3
- integrin beta‐3
- MAPK
- mitogen‐activated protein kinase
- MMP2
- matrix metalloproteinase‐2
- MMP9
- matrix metalloproteinase‐9
- mRNA
- messenger RNA
- NF‐κB
- nuclear factor kappa‐light‐chain‐enhancer of activated B cells
- SBE
- SMAD binding element
- SERPINE1
- serpin family E member 1
- siRNA
- small interfering RNA
- ssGSEA
- single‐sample gene set enrichment analysis
- TCGA
- The Cancer Genome Atlas
- TGFβ
- transforming growth factor beta
- YAP
- Yes‐associated protein
- YAP8SA
- mutants of inhibitory phosphorylation site at eight serine to Alanine of YAP
- ZEB1
- zinc finger E‐box binding homeobox 1
- ZEB2
- zinc finger E‐box‐binding homeobox 2
34.
目的 分析社区"5+1"糖尿病分阶段达标管理对2型糖尿病患者生存质量的干预效果及其影响因素,为提高患者生存质量提供依据。方法 采用分层整群抽样的方法在山西省、江苏省和宁夏回族自治区选择12个社区卫生服务中心,分别作为干预组(管理方式:社区"5+1"糖尿病分阶段达标管理)、对照组[管理方式:依据《国家基本公共卫生服务规范(2011年版)》的相关要求],进行为期2年的随访观察。采用面对面问卷调查的方式,收集患者的人口学信息等基本信息;采用健康调查简表(SF-36)对患者在干预前后测量生存质量。采用SAS 9.4软件进行双重差分法以及多重线性回归模型分析。结果 基线时共纳入2 467名研究对象,终末时共1 924人接受了为期2年完整的随访管理。干预后,干预组、对照组患者生理健康维度(PCS)、心理健康维度(MCS)评分变化净差值分别为13.6分、29.8分。多重线性回归分析结果显示,影响患者PCS得分的主要因素有年龄、医保类型、基线PCS得分以及所在地区,影响患者MCS得分的主要因素有年龄、医保类型、基线MCS得分、是否合并高血压以及所在地区。结论 社区"5+1"糖尿病分阶段达标管理对2型糖尿病患者生存质量的干预效果较好。 相似文献
35.
目的本研究立足于项目组前期研究的成果上,积极探索吉林辽宁两省目标设置水平的差异,并进一步探究受目标设置影响下的工作落实结果情况,探讨产生差异的原因。
方法以系统穷尽的方式收集吉林辽宁两省2000至2017年有关目标与工作落实情况的指标,利用Spearman相关和线性回归分析吉林辽宁两省目标设置对于突发应急工作落实情况的影响。
结果吉林辽宁两省突发应急领域的目标设置水平与工作落实情况总体均呈现上升趋势,截至2017年,吉林目标设置水平与工作落实情况分别为46%与60%,辽宁为60%与53.3%,且目标设置水平与工作落实呈正相关。
结论有公众需要为依据且定量可考的目标设置对于工作落实、推进、完善具有积极的正反馈作用,建立科学量化的突发应急目标设置评价体系是适宜可行的。 相似文献
36.
T. Wu L. G. Trahair M. J. Bound C. F. Deacon M. Horowitz C. K. Rayner K. L. Jones 《Diabetic medicine》2015,32(5):595-600
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N. S. Hari Narayana Moorthy Sergio F. Sousa Maria J. Ramos Pedro A. Fernandes 《Medicinal chemistry research》2016,25(7):1340-1357
Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets. 相似文献
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