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• Research Paper Volume 14, Issue 4 pp 1782-1796

  Long non-coding RNA Linc00205 promotes hepatoblastoma progression through regulating microRNA-154-3p/Rho-associated coiled-coil Kinase 1 axis via mitogen-activated protein kinase signaling

  Relevance score: 6.4710035

  Guoqing Liu, Qiang Zhu, Hao Wang, Jianfeng Zhou, Bin Jiang

  Keywords: hepatoblastoma, miR-154-3p, ROCK1, MAPK signalling pathway

  Published in Aging on February 17, 2022

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  Hepatoblastoma (HB) is the most common pediatric liver tumor. The significant tumor heterogeneity of HB leads to varied prognoses among children with the disease. Recent studies have suggested that long non-coding RNAs (lncRNAs) can serve as novel therapies for HB treatment. Thus, in this study, we aimed to reveal the function and mechanism of the lncRNA Linc00205 in HB. Our results exhibited that, in both HB tissues and cell lines, levels of Linc00205 were significantly increased. In addition, knockdown of Linc00205 led to suppression of HB development. Moreover, we identified that Linc00205 was able to directly bind to miR-154-3p, thus isolating miR-154-3p from its target Rho-associated coiled-coil Kinase 1 (ROCK1). Further cellular behavioral experiments elucidated that the miR-154-3p inhibitor and ROCK1 overexpression were able to reverse the effect of downregulated Linc00205 on proliferation, migration, invasion, and apoptosis of HB cells by rescue assays via mitogen-activated protein kinase (MAPK) signaling. Our results demonstrated that Linc00205 enhanced HB progression by regulating ROCK1 expression via sponging miR-154-3p through MAPK signaling, which suggests a novel potential therapeutic target for HB.

• Research Paper Volume 12, Issue 21 pp 21129-21146

  LINC00452 promotes ovarian carcinogenesis through increasing ROCK1 by sponging miR-501-3p and suppressing ubiquitin-mediated degradation

  Relevance score: 5.6226006

  Juan Yang, Wei-Gang Wang, Ke-Qiang Zhang

  Keywords: ovarian cancer, long non-coding RNA, LINC00452, miR-501-3p, ROCK1

  Published in Aging on November 9, 2020

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  Ovarian cancer refers to all sorts of cancerous growth that starts from the ovary. Dysregulation of long non-coding RNAs (lncRNAs) is associated with ovarian cancer development and progression. Cellular expression and localization of LINC00452 in ovarian cancer cells were detected by qPCR and FISH. The roles of LINC00452 in ovarian carcinogenesis were characterized by MTT, transwell and colony-formation assays in vitro as well as xenograft mouse model. The underlying mechanism was explored by microarray, RIP, Co-IP and luciferase reporter assays. This study identified a novel lncRNA LINC00452 being elevated in both ovarian cancer cells and tumor tissues in patients. Such aberrant expression of LINC00452 was negatively correlated with relapse-free survival of ovarian cancer patients. Overexpression of LINC00452 potentiated CaOV3 cell viability, migration and invasion in vitro as well as xenograft tumor growth in vivo. Evidence from the current study suggests that the carcinogenicity of LINC00452 is partially due to competitive sponging of miR-501-3p followed with release of repression on the ROCK1, a key effector in Rho signaling pathway. Irrespective of its miRNA sponge function, LINC00452 is capable of preventing ROCK1 protein from ubiquitin/proteasome-mediated degradation via their mutual physical interaction. Our study makes LINC00452 a potential therapeutic target for ovarian cancer.

• Research Paper Volume 12, Issue 20 pp 20127-20138

  Long non-coding RNA DLEUI promotes papillary thyroid carcinoma progression by sponging miR-421 and increasing ROCK1 expression

  Relevance score: 7.682593

  Rui Li, Taihu Wan, Jie Qu, Yang Yu, Ruipeng Zheng

  Keywords: DLEU1, miR-421, papillary thyroid carcinoma, ROCK1

  Published in Aging on September 10, 2020

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  We investigated the role of long non-coding RNA DLEU1 (deleted in lymphocytic leukemia 1) in the progression of papillary thyroid carcinoma (PTC). DLEU1 levels were higher in PTC cell lines (BHP5-16, TPC-1,8505C, and SW1736) and patient tissues (n=54) than in a human thyroid follicular epithelial cell line (Nthy-ori3-1) or adjacent normal thyroid tissues. High DLEU1 expression correlated positively with lymph node metastasis and advanced clinical stages in PTC patients. Bioinformatics, dual luciferase reporter, and RNA pulldown assays confirmed that DLEU1 directly binds to miR-421. Moreover, bioinformatics and dual luciferase reporter assays showed that miR-421 directly binds to the 3’untranslated region of the rho-related coiled-coil kinase 1 (ROCK1) in TPC-1 cells. PTC patient tissues and cell lines showed high ROCK1 mRNA and protein levels as well as low miR-421 levels. CCK-8, flow cytometry, wound healing, and Transwell invasion assays demonstrated that DLEU1 silencing decreases TPC-1 cell proliferation, survival and progression, but they can be rescued by miR-421 knockdown or ROCK1 overexpression. DLEU1 knockdown in TPC-1 cells decreased in vivo xenograft tumor size and weight compared to controls in nude mice. These findings demonstrate that DLEU1 promotes PTC progression by sponging miR-421 and increasing ROCK1 expression.

  

  DLEU1 is overexpressed in PTC tissues and cell lines. (A) QRT-PCR analysis shows the expression of DLEU1 in 54 paired PTC tissues and adjacent normal thyroid tissues. (B) QRT-PCR analysis shows the expression of DLEU1 in four PTC cell lines (BHP5-16, 8505C, TPC-1, and SW1736) and the human thyroid follicular epithelial cells, Nthy-ori3-1. (C) QRT-PCR analysis shows the expression of DLEU1 in the cytoplasmic and nuclear extracts of TPC-1 cells. Note: The data are shown as the means ± SD of at least three independent experiments. *P< 0.05 and **P< 0.01.

  
  
  

  

  DLEU1 knockdown inhibits proliferation, migration and invasion of TPC-1 cells. (A) QRT-PCR analysis shows DLEU1 levels in sh-NC- and sh-DLEU1-transfected TPC-1 cells. (B) CCK8 assay results show proliferation rates of sh-NC- and sh-DLEU1-transfected TPC-1 cells. (C) Flow cytometry analysis shows the percentage apoptosis in sh-NC- and sh-DLEU1-transfected TPC-1 cells based on Annexin-V staining. (D) Wound healing assay results show the migration efficiency of sh-NC- and sh-DLEU1-transfected TPC-1 cells. (E) Transwell invasion assay results show the invasiveness of sh-NC- and sh-DLEU1-transfected TPC-1 cells. Note: The data is represented as the means ± SD of at least three independent experiments. *P< 0.05 and **P< 0.01.

  
  
  

  

  DLEU1 sponges miR-421 in PTC cells. (A) The diagram shows the predicted miR-421 binding sites in the 3’UTR of DLEU1 and the mutations in the miR-421 binding sites. (B) Dual luciferase reporter assay shows the relative luciferase activity of TPC-1 cells co-transfected with miR-421 mimic or miR-NC plus luciferase reporter plasmid with the wild-type DLEU1 (WT-DLEU1) or mutant DLEU1 (MUT-DLEU1). The miR-421 binding sites are mutated in the mutant DLEU1. (C) QRT-PCR results show DLEU1 levels in the RNA pull down extracts using biotinylated wild-type or mutant miR-421. (D) QRT-PCR analysis shows miR-421 levels in control and DLEU1-silenced TPC-1 cells. (E) QRT-PCR analysis shows DLEU1 levels in control and miR-421 mimic-transfected TPC-1 cells. (F) QRT-PCR analysis shows miR-421 expression in 54 paired PTC and adjacent normal thyroid tissues.(G) QRT-PCR analysis shows the expression of miR-421 in four PTC cell lines (BHP5-16, 8505C, TPC-1, and SW1736) and the human thyroid follicular epithelial cell line, Nthy-ori3-1. (H) Spearman’s correlation analysis shows that DLEU1 expression is inversely related to miR-421 expression in PTC tissues (n=54). Note: The data are represented as the means ± SD of at least three independent experiments. *P< 0.05 and **P< 0.01.

  
  
  

  

  ROCK1 is a direct target of miR-421 in PTC cells. (A) The predicted miR-421 binding sites in the 3’UTR of ROCK1 and the mutated sequence are shown. (B) Dual luciferase reporter assay shows the relative luciferase activity in TPC-1 cells co-transfected with miR-421 mimic or miR-NC and luciferase reporter plasmid with wild-type ROCK1-3’-UTR (WT-ROCK1) or mutant ROCK1-3’-UTR (MUT-ROCK1). (C) QRT-PCR analysis shows the ROCK1 mRNA levels in miR-NC- and miR-421 mimic-transfected TPC-1 cells. (D) Western blot analysis shows ROCK1 protein levels in miR-NC- and miR-421 mimic-transfected TPC-1 cells. (E) QRT-PCR analysis shows ROCK1 mRNA expression in 54 paired PTC and adjacent normal thyroid tissues. (F) Spearman correlation analysis shows that ROCK1 expression is inversely related to miR-421 expression in PTC tissues (n=54). Note: The data are represented as the means ± SD of at least three independent experiments. *P< 0.05 and **P< 0.01.

  
  
  

  

  DLEU1 regulates PTC cell growth and progression through the miR-421/ROCK1 axis. (A) Western blot analysis shows ROCK1 protein levels in sh-NC-, sh-DLEU1- and sh-DLEU1 plus miR-421 inhibitor-transfected TPC-1 cells. (B) Spearman correlation analysis shows that ROCK1 mRNA expression is inversely related to DLEU1 expression in PTC tissues (n=54). (C) CCK-8 assay analysis shows proliferation rates of TPC-1 cells transfected with sh-NC, sh-DLEU1, sh-DLEU1 plus miR-421 inhibitor, and sh-DLEU1 plus ROCK1 overexpression plasmid. (D) Flow cytometry analysis shows percentage apoptosis (% Annexin-V⁺ cells) in TPC-1 cells transfected with sh-NC, sh-DLEU1, sh-DLEU1 plus miR-421 inhibitor, and sh-DLEU1 plus ROCK1 overexpression plasmid. (E) Wound healing assay results show the numbers of migrating cells in the TPC-1 cells transfected with sh-NC, sh-DLEU1, sh-DLEU1 plus miR-421 inhibitor, and sh-DLEU1 plus ROCK1 overexpression plasmid. (F) Transwell invasion assay results show the numbers of invading cells in the TPC-1 cells transfected with sh-NC, sh-DLEU1, sh-DLEU1 plus miR-421 inhibitor, and sh-DLEU1 plus ROCK1 overexpression plasmid. Note: The data is represented as the means ± SD of at least three independent experiments. *P< 0.05 and **P< 0.01.

  
  
  

  

  DLEU1 knockdown reduces in vivo growth of xenograft tumors in nude mice model. (A) The curve shows the rate of growth of xenograft tumors generated from subcutaneously injected control and DLEU1 knockdown TPC-1 cells in the nude mice (n=5 each). Tumor growth was measured every 7 days for 28 days. (B) The representative images show the xenograft tumors in nude mice that are subcutaneously injected with control and DLEU1 knockdown TPC-1 cells for 28 days. (C) The histogram plot shows the weight of xenograft tumors derived from nude mice subcutaneously injected with control and DLEU1 knockdown TPC-1 cells. (D) Representative images show IHC staining with the anti-Ki67 antibody of xenograft tumor tissue sections derived from nude mice subcutaneously injected with control and DLEU1 knockdown TPC-1 cells. (E–F) QRT-PCR analysis shows the levels of DLEU1 and miR-421 in the xenograft tumor tissues derived from nude mice subcutaneously injected with control and DLEU1 knockdown TPC-1 cells. (G) QRT-PCR analysis shows ROCK1 mRNA levels in the xenograft tumor tissues derived from nude mice subcutaneously injected with control and DLEU1 knockdown TPC-1 cells. (H) Western blot analysis shows ROCK1 protein levels in the xenograft tumor tissues derived from nude mice subcutaneously injected with control and DLEU1 knockdown TPC-1 cells. Note: The data are represented as the means ± SD of at least three independent experiments. *P< 0.05 and **P< 0.01.

  
  
  

• Research Paper Volume 12, Issue 12 pp 12160-12174

  ROCK1 knockdown inhibits non-small-cell lung cancer progression by activating the LATS2-JNK signaling pathway

  Relevance score: 7.8699956

  Ting Xin, Wei Lv, Dongmei Liu, Yongle Jing, Fang Hu

  Keywords: ROCK1, LATS2, JNK, NSCLC, apoptosis

  Published in Aging on June 17, 2020

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  Rho-associated kinase 1 (ROCK1) regulates tumor metastasis by maintaining cellular cytoskeleton homeostasis. However, the precise role of ROCK1 in non-small-cell lung cancer (NSCLC) apoptosis remains largely unknown. In this study, we examined the function of ROCK1 in NSCLS survival using RNA interference-mediated knockdown. Our results showed that ROCK1 knockdown reduced A549 lung cancer cell viability in vitro. It also inhibited A549 cell migration and proliferation. Transfection of ROCK1 siRNA was associated with increased expression of large tumor suppressor kinase 2 (LATS2) and c-Jun N-terminal kinase (JNK). Moreover, ROCK1 knockdown-induced A549 cell apoptosis and inhibition of proliferation were suppressed by LATS2 knockdown or JNK inactivation, suggesting that ROCK1 deficiency triggers NSCLC apoptosis in a LATS2-JNK pathway-dependent manner. Functional analysis further demonstrated that ROCK1 knockdown dysregulated mitochondrial dynamics and inhibited mitochondrial biogenesis. This effect too was reversed by LATS2 knockdown or JNK inactivation. We have thus identified a potential pathway by which ROCK1 downregulation triggers apoptosis in NSCLC by inducing LATS2-JNK-dependent mitochondrial damage.

  

  ROCK1 regulates A549 cell viability. (A) MTT assay for A549 cells. A549 cells were transfected with siRNA against ROCK1 (si/ROCK1) or control siRNA (si/Ctrl). (B) An LDH release assay was used to measure LDH levels in the medium of A549 cells transfected with siRNA against ROCK1 (si/ROCK1) or control siRNA (si/Ctrl). (C) ELISA was used to analyze Caspase-3 activity in response to si/ROCK1 or si/Ctrl transfection. (D) A qPCR assay was used to measure Caspase-3 transcription. (E, F) TUNEL staining was used to measure numbers of apoptotic cells in response to si/ROCK1 or si/Ctrl transfection. *p<0.05.

  
  
  

  

  ROCK1 knockdown decreases cell migration and proliferation. (A) A CCK-8 assay was used to quantify proliferation in A549 cells transfected with siRNA against ROCK1 (si/ROCK1) or control siRNA (si/Ctrl). (B, C) A qPCR assay was used to analyze Cyclin-D and Cyclin-E transcription. (D) Transwell assay for A549 cells. Numbers of migrated cells were quantified after si/ROCK1 or si/Ctrl transfection. (E, F) A qPCR assay was used to analyze CXCR-4 and CXCCR-7 transcription. *p<0.05.

  
  
  

  

  The LATS2-JNK pathway is activated after ROCK1 knockdown. (A) A qPCR assay was used to analyze LATS2 transcription. (B) Western blots were used to detect LATS2 protein levels in response to si/ROCK1 transfection. (C) An ELISA was used to measure JNK activity in response to siRNA-mediated ROCK1 knockdown. (D) A qPCR assay was used to analyze JNK transcription after si/ROCK1 transfection. *p<0.05.

  
  
  

  

  Inactivation of the LATS2-JNK pathway abolishes the tumor-suppressive effects of ROCK1 knockdown. (A) MTT assay of cell viability. siRNA against LATS2 (si/LATS2) and SP600125 were used inhibit LATS2 upregulation and JNK activation, respectively. (B) An LDH release assay was used to measure LDH levels in the medium. (C, D) TUNEL staining was used to quantify numbers of apoptotic cells after si/LATS2 transfection and SP600125 administration. *p<0.05.

  
  
  

  

  ROCK1 deficiency promotes mitochondrial apoptosis by activating the LATS2-JNK pathway. (A) ATP production was measured in A549 cells after transfection of siRNA against LATS2 (si/LATS2) and SP600125 administration that inhibited LATS2 upregulation and JNK activation, respectively. (B, C) qPCR was used to analyze COX-1 and COX-2 transcription. (D, E) Immunofluorescence was used to measure generation of ROS in A549 cells. (F–G) A qPCR assay was used to detect changes in Bax and Bad levels in A549 cells. *p<0.05.

  
  
  

  

  The ROCK1-LATS2-JNK pathway affects mitochondrial dynamics and mitochondrial biogenesis in A549 cells. (A–C) Immunofluorescence was used to observe mitochondrial morphology in A549 cells. siRNA against LATS2 (si/LATS2) and SP600125 were used inhibit LATS2 upregulation and JNK activation, respectively. Mitochondrial length and number of cells with fragmented mitochondria were recorded. (D–F) A qPCR assay was used to analyze Drp1, Fis1, and Mid49 transcription in A549 cells in response to ROCK1 knockdown, LATS2 knockdown, and JNK inhibition. (G) Double immunofluorescence was used to observe alterations in Sirt3 and PGC1α levels; relative immunofluorescence intensities were evaluated. *p<0.05.

  
  
  

• Research Paper Volume 12, Issue 11 pp 10614-10632

  Ursolic acid reverses liver fibrosis by inhibiting interactive NOX4/ROS and RhoA/ROCK1 signalling pathways

  Relevance score: 6.4710035

  Sizhe Wan, Fangyun Luo, Chenkai Huang, Cong Liu, Qingtian Luo, Xuan Zhu

  Keywords: ursolic acid, l iver fibrosis, NOX4, RhoA, ROCK1

  Published in Aging on June 3, 2020

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  Liver fibrosis is the reversible deposition of extracellular matrix (ECM) and scar formation after liver damage by various stimuli. The interaction between NOX4/ROS and RhoA/ROCK1 in liver fibrosis is not yet clear. Ursolic acid (UA) is a traditional Chinese medicine with anti-fibrotic effects, but the molecular mechanism underlying these effects is still unclear. We investigated the interaction between NOX4/ROS and RhoA/ROCK1 during liver fibrosis and whether these molecules are targets for the anti-fibrotic effects of UA. First, we confirmed that UA reversed CCl4-induced liver fibrosis. In the NOX4 intervention and RhoA intervention groups, related experimental analyses confirmed the decrease in CCl4-induced liver fibrosis. Next, we determined that the expression of NOX4 and RhoA/ROCK1 was decreased in UA-treated liver fibrotic mice. Furthermore, RhoA/ROCK1 expression was decreased in the NOX4 intervention group, but there was no significant change in the expression of NOX4 in the RhoA intervention group. Finally, we found that liver fibrotic mice showed a decline in their microbiota diversity and abundance, a change in their microbiota composition, and a reduction in the number of potential beneficial bacteria. However, in UA-treated liver fibrotic mice, the microbiota dysbiosis was ameliorated. In conclusion, the NOX4/ROS and RhoA/ROCK1 signalling pathways are closely linked to the development of liver fibrosis. UA can reverse liver fibrosis by inhibiting the NOX4/ROS and RhoA/ROCK1 signalling pathways, which may interact with each other.

  

  The effect of UA on CCl₄-induced liver injury and fibrosis is related to NOX4. (A) HE staining (100× magnification). (B) Masson’s trichrome staining (100× magnification). (C–D) Morphometrical analysis of the fibrotic score and fibrotic area. (E) Detection of the hydroxyproline content in the liver tissue by colorimetry. (F) Liver function indices in mouse sera. Data represent the mean ± SD for each group. *P < 0.05 and ***P < 0.001.

  
  
  

  

  The effect of UA on CCl₄-induced liver fibrosis-related indicators is related to NOX4. (A) Dual immunofluorescence staining of liver sections from mice in the control, CCl₄ and UA groups for nuclei (DAPI, blue), aHSCs (α-SMA, green), and apoptosis (TUNEL, red), and the merged images are shown. (B) Hepatic mRNA levels of collagen I, MMP-1, α-SMA, and TIMP-1 were measured by qRT-PCR. (C) Collagen I, MMP-1, α-SMA, and TIMP-1 protein expression was detected by a western blot. Data represent the mean ± SD of each group. *P < 0.05 and ***P < 0.001.

  
  
  

  

  Effect of UA on the expression of NOX4 in mice with liver fibrosis. (A) The effect of UA on NOX4 expression was determined by using IHC. (B) Hepatic mRNA levels of NOX4 were measured by qRT-PCR. (C) Hepatic protein levels of NOX4 were detected by a western blot. (D) Detection of MDA content in the liver by a commercial kit. Data represent the mean ± SD of each group. *P < 0.05 and ***P < 0.001.

  
  
  

  

  Effect of UA on the expression of RhoA/ROCK1 in liver fibrotic mice. (A) The effect of UA on RhoA/ROCK1 expression was determined by using IHC. (B) Hepatic mRNA levels of RhoA/ROCK1 were measured by qRT-PCR. (C) Hepatic protein levels of RhoA/ ROCK1 were detected by a western blot. Data represent the mean ± SD of each group. *P < 0.05 and ***P < 0.001.

  
  
  

  

  The effect of UA on CCl₄-induced liver injury and fibrosis is related to RhoA. (A) HE staining (100× magnification). (B) Masson’s trichrome staining (100× magnification). (C–D) Morphometrical analysis of the fibrotic score and fibrotic area. (E) Detection of the hydroxyproline content in liver tissue by colorimetry. (F) Liver function indices in mouse sera. Data represent the mean ± SD of each group. *P < 0.05 and ***P < 0.001.

  
  
  

  

  The effect of UA on CCl₄-induced liver fibrosis-related indicators is related to RhoA. (A) Dual immunofluorescence staining of liver sections from mice in the control, CCl₄, and UA groups stained for nuclei (DAPI, blue), aHSCs (α-SMA, green), and apoptosis (TUNEL, red), and the merged images are shown. (B) Hepatic mRNA levels of collagen I, MMP-1, α-SMA, and TIMP-1 were measured by qRT-PCR. (C) Collagen I, MMP-1, and TIMP-1 protein expression was detected by a western blot. Data represent the mean ± SD of each group. *P < 0.05 and ***P < 0.001.

  
  
  

  

  Interaction between NOX4/ROS and RhoA/ROCK1 in liver fibrotic mice. (A) In liver fibrotic mice in which NOX4 expression was inhibited, RhoA/ROCK1 expression was detected by IHC. (B) Dual immunofluorescence staining of liver sections from mice in the control, CCl₄, NOX4^-/- and AP groups stained for nuclei (DAPI, blue), aHSCs (α-SMA, green), and RhoA (red), and the merged images are shown. (C) Hepatic mRNA levels of RhoA/ROCK1 were measured by qRT-PCR. (D) In liver fibrotic mice in which RhoA expression was inhibited, NOX4 expression was detected by IHC. (E) Detection of the MDA content in the liver by a commercial kit. (F) Hepatic mRNA levels of NOX4 were measured by qRT-PCR. Data represent the mean ± SD of each group. *P < 0.05 and ***P < 0.001.

  
  
  

  

  Effect of UA on intestinal microbiota dysbiosis in mice with CCl₄-induced liver fibrosis. (A) Ileal mRNA levels of the TJ proteins ZO-1 and occludin were measured by qRT-PCR. (B) The alpha diversity of each group was assessed by determining the Shannon index and the Chao1 index. (C) PCoA to determine the weighted UniFrac distance of the intestinal microbiota. (D) Composition of the intestinal microbiota of each group at the phylum level. (E) Composition of the intestinal microbiota of each group at the genus level. (F) Linear discriminant analysis effect size (LEfSe) prediction was used to identify the bacteria in each group with the most differential abundance. (G) Linear discriminant analysis (LDA) scores showed significant differences in the bacteria in each group. Only the bacteria whose abundance met an LDA threshold value of >2 are shown. Data represent the mean ± SD of each group. *P < 0.05 and ***P < 0.001.

  
  
  

• Research Paper Volume 12, Issue 2 pp 1867-1887

  miR-106b-5p contributes to the lung metastasis of breast cancer via targeting CNN1 and regulating Rho/ROCK1 pathway

  Relevance score: 6.132061

  Zheng Wang, Tian-En Li, Mo Chen, Jun-Jie Pan, Kun-Wei Shen

  Keywords: breast cancer, CNN1, miR-106b-5p, Rho/ROCK1 pathway

  Published in Aging on January 27, 2020

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  Objectives: Breast cancer has been the second most prevalent and fatal malignancy due to its frequent metastasis to other organs. We aim to study the effects of a key miRNA-mRNA signaling in breast cancer.

  Results: CNN1 was identified as the key gene in breast cancer by the bioinformatics analysis, and the downregulation of CNN1 in breast cancer tissues and cell lines was observed. Upregulating CNN1 inhibited cell survival, migration, invasion, and adhesion, but enhanced cell apoptosis. miR-106b-5p not only bound to CNN1 mRNA 3’UTR, but also promoted lung metastasis in vivo. Besides, the miR-106b-5p mimic enhanced breast cancer canceration by targeting CNN1 and activating Rho/ROCK1 signaling pathway.

  Conclusion: Overall, our results proved that miR-106b-5p promoted the metastasis of breast cancer by suppressing CNN1 and activating Rho/ROCK1 pathway.

  Methods: Bioinformatics analysis was performed to select the key gene in breast cancer. The overexpression and knockdown of Calponin 1 (CNN1) in breast cancer cell lines were performed to conduct cell viability, migrating, invasion, proliferation, adhesion, and apoptosis experiments. To identify the role of miR-106b-5p and Rho/ROCK1 in CNN1-induced breast cancer, a dual-luciferase assay, tumor lung metastasis assay, transcript half-life assay, and Rho/ROCK1 inhibition assay were performed.

  

  CNN1 and STAT1 were the key genes in breast cancer. (A) 36 common genes were screened after analysis with the results of the microarray chips. GSE124646 and GSE71053 were downloaded from NCBI. The DEGs of breast cancer was obtained from the Cancer RNA-Seq Nexus (CRN). (B) ACOT7, STAT1, TYMP, and VOPP1 were upregulated in breast cancer, while ACTG2, CNN1, CDC14B, NFIB, RCN1, and TRIM2 were downregulated in breast cancer. (C) The biological processes and KEGG pathway for 36 genes were analyzed using Metascape. (D) The String was performed to construct the PPI network, and analyze biological processes and KEGG pathway for 36 genes. (E) The expression of CNN1 and STAT1 according to different subtypes and TNBC status of breast cancer. Breast Cancer Gene-Expression Miner v4.4 was used to conduct the analysis. All DNA microarray data in the database were used. IDC, invasive ductal carcinoma. ILC, invasive lobular carcinoma. TNBC, triple negative breast cancer.

  
  
  

  

  CNN1 played a key role in BRCA. (A) The mRNA expression of CNN1 was decreased in BRCA cells, while the mRNA expression of STAT1 was increased in BRCA cells. *P<0.05 vs. MCF-10A and **P<0.001 vs. MCF-10A. (B) The effects of CNN1 and STAT1 on the prognosis of breast cancer. (C) The effects of CNNA and STAT1 on the stage of breast cancer.

  
  
  

  

  The CNN1 expression was decreased in BRCA tissues and cells. (A) The downregulation of CNN1 in breast cancer tissues (n=20) compared with normal breast tissues (n=20). (B) The protein expression of CNN1 was decreased in BRCA cell lines compared with the healthy breast cell line. *P<0.05 vs. MCF-10A and **P<0.001 vs. MCF-10A. (C) The CNN1 expression was upregulated after CNN1 overexpression transfected MCF-7 and MDA-MB-231 cells. Control, the cells were cultured without any treatment. NC, the cells were treated with the negative control. CNN1 OE, the cells were treated with CNN1 overexpression. *P<0.05 vs. Control and **P<0.001 vs. Control. (D) The CNN1 expression was downregulated after CNN1 small interfering RNA (siRNA) transfected T47D and CAMA-1 cells. Control, the cells were cultured without any treatment. NC, the cells were treated with the negative control. si-CNN1, the cells were transfected with CNN1 siRNA. *P<0.05 vs. Control and **P<0.001 vs. Control.

  
  
  

  

  CNN1 inhibited cell proliferation and migration of breast cancer. (A) and (B) CNN1 overexpression inhibited cell proliferation in MCF-7 and MDA-MB-231 cells, while CNN1 knockdown promoted cell proliferation in T47D and CAMA-1 cells. CCK8 was performed to detect the ability of cell proliferation after the breast cancer cells (MCF-7, MDA-MB-231, T47D, and CAMA-1 cells) treated with negative control, CNN1 overexpression or CNN1 siRNA for 0 h, 24 h, 48 h, and 72 h. (C) and (D) CNN1 overexpression inhibited cell invasion in MCF-7 and MDA-MB-231 cells, while CNN1 knockdown promoted cell invasion in T47D and CAMA-1 cells. The cell invasion after CNN1 overexpression or CNN1 knockdown for 24 h was measured using transwell invasion assay. Control, the cells were cultured without any treatment. NC, the cells were treated with the negative control. CNN1 OE, the cells were treated with CNN1 overexpression. si-CNN1, the cells were transfected with CNN1 siRNA. *P<0.05 vs. Control and **P<0.001 vs. Control.

  
  
  

  

  CNN1 overexpression suppressed cell migration, colony formation, and cell adhesion, while CNN1 overexpression enhanced the abilities of cell apoptosis. (A) The role of CNN1 overexpression in cell migration was confirmed using wound healing assay. The MCF-7 and MDA-MB-231 cells were treated with CNN1 overexpression for 0 h, 24 h, and 48 h. (B) The ability of colony formation was confirmed using colony formation assay. The MCF-7 and MDA-MB-231 cells were treated with negative control or CNN1 overexpression for 14 days. (C) The ability of cell adhesion after CNN1 overexpression for 30 min and 60 min was assessed using the cell adhesion assay. (D) The flow cytometry was performed to measure the cell apoptosis rate after CNN1 overexpression. Control, the cells were cultured without any treatment. NC, the cells were treated with the negative control. CNN1 OE, the cells were treated with CNN1 overexpression. *P<0.05 vs. Control and **P<0.001 vs. Control.

  
  
  

  

  The Rho/ROCK1 pathway participated in CNN1-induced breast cancer. (A) The half-time of ROCK1 transcript after CNN1 overexpression was decreased using half-time assay. The MCF-7 and MDA-MB-231 cells after transfection with CNN1 overexpression were treated with Act D (8 μg/ml) for 0 h, 2 h, 4 h, 6 h, and 8 h. The ROCK1 mRNA remaining was detected by qRT-PCR. (B) The protein expressions of Rho and ROCK1 was decreased after CNN1 overexpression. The western blot assay was used to measure the protein expression after CNN1 overexpression for 24 h. Control, the cells were cultured without any treatment. NC, the cells were treated with the negative control. CNN1 OE, the cells were treated with CNN1 overexpression. *P<0.05 vs. Control and **P<0.001 vs. Control.

  
  
  

  

  CNN1 was the target gene of miR-106b-5p, and the miR-106b-5p promoted cell proliferation. (A) The CNN1 3’UTR contained a binding site of miR-106b-5p by miRDB prediction. (B) The dual-luciferase reporter assay revealed the interaction between CNN1 3’UTR and miR-106b-5p. The HEK293 cells were co-transfected with the miR-106b-5p mimic and CNN1, or miR-106b-5p mimic and mutated CNN1. 3’UTR, wild-type CNN1 containing 3’UTR binding site. mimic, miR-106b-5p mimic. MU, mutated CNN1 without the 3’UTR binding site. NC, negative control. **P<0.001 vs. 3’UTR+NC. (C) The qRT-PCR was performed to detect the transfection efficiency of miR-106b-5p mimic and inhibitor in MCF-7 and MDA-MB-231 cells. (D) The miR-106b-5p mimic successfully inhibited CNN1 expression, while the miR-106b-5p inhibitor successfully upregulated CNN1 expression. The CNN1 protein expression was examined by immunoblotting assay after upregulation or downregulation of miR-106b-5p. mimic, the cells were transfected with miR-106b-5p mimic. inhibitor, the cells were transfected with miR-106b-5p inhibitor. (E) The miR-106b-5p mimic enhanced cell proliferation, and the miR-106b-5p inhibitor suppressed cell proliferation. The CCK8 assay was performed to detect the cell proliferation after transfection of miR-106b-5p mimic or inhibitor for 0 h, 24 h, 48 h, and 72 h. *P<0.05 vs. Control and **P<0.001 vs. Control. (F) Representative live bioluminescence images from mice treated with MCF-7 cells transfected with negative control or miR-106b-5p inhibitor. (G) Representative hematoxylin and eosin (H&E)-stained lung sections from mice treated with MCF-7 cells transfected with negative control or miR-106b-5p inhibitor.

  
  
  

  

  miR-106b-5p mimic alleviated the role of CNN1 overexpression induced suppression of cell proliferation and invasion. (A) Co-transfection of miR-106b-5p mimic and CNN1 overexpression led to the downregulation of CNN1 and upregulation of miR-106b-5p both in MCF-7 and MDA-MB-231 cells. (B) Co-transfection of miR-106b-5p mimic and CNN1 overexpression resulted in the decrease of the protein level of CNN1 compared with transfection of CNN1 overexpression. OE, the cells were transfected with CNN1 overexpression. OE+mimic, the cells were co-transfected with miR-106b-5p mimic and CNN1 overexpression. *P<0.05 vs. Control and **P<0.001 vs. Control. (C) and (D) The co-transfection of miR-106b-5p mimic and CNN1 overexpression alleviated the inhibition of cell proliferation and invasion caused by CNN1 overexpression. The CCK8 assay and transwell assay respectively revealed the changes of cell proliferation and invasion. CNN1 OE, the cells were transfected with CNN1 overexpression. CNN1 OE+mimic, the cells were co-transfected with miR-106b-5p mimic and CNN1 overexpression. *P<0.05 vs. Control and **P<0.001 vs. Control. #P<0.05 vs. CNN1 OE. #P<0.001 vs. CNN1 OE.

  
  
  

  

  miR-106b-5p promoted the cell proliferation in T47D and CAMA-1 cells by targeting CNN1 and activating the Rho/ROCK1 signaling pathway. (A) The ZINC00881524 was successfully inhibited the protein expression of ROCK1 after the cells were treated with ZINC00881524 for 24 h. ZINC00881524 is the inhibitor of the Rho/ROCK1 pathway. The protein expression of ROCK1 was detected by immunoblotting assay. (B) The CCK8 assay demonstrated that Rho/ROCK1 inhibitor alleviated the cell proliferation compared with the treatment of CNN1 siRNA. si-CNN1, the cells were transfected with CNN1 siRNA. ZINC00881524+si-CNN1, the cells were co-transfected with ZINC00881524 and CNN1 siRNA. *P<0.05 vs. Control and **P<0.001 vs. Control. #P<0.05 vs. si-CNN1. #P<0.001 vs. si-CNN1. (C) The protein expression of ROCK1 was upregulated by transfection of miR-106b-5p mimic, but co-transfection of miR-106b-5p and ZINC00881524 could downregulate it. mimic, the cells were transfected with miR-106b-5p mimic. mimic+ ZINC00881524, the cells were co-transfected with miR-106b-5p mimic and ZINC00881524. *P<0.05 vs. Control and **P<0.001 vs. Control. (D) Co-transfection of miR-106b-5p and ZINC00881524 alleviated the postive effect of miR-106b-5p mimic on cell proliferation in T47D and CAMA-1 cells. mimic, the cells were transfected with miR-106b-5p mimic. mimic+ ZINC00881524, the cells were co-transfected with miR-106b-5p mimic and ZINC00881524. *P<0.05 vs. Control and **P<0.001 vs. Control. #P<0.05 vs. mimic. #P<0.001 vs. mimic. (E) The signaling cascade indicated that miR-106b-5p promoted breast cancer by targeting CNN1 and activating the Rho/ROCK1 signaling pathway.

  
  
  

• Research Paper Volume 11, Issue 18 pp 7859-7879

  Up regulation of Rho-associated coiled-coil containing kinase1 (ROCK1) is associated with genetic instability and poor prognosis in prostate cancer

  Relevance score: 6.4710035

  Stefan Steurer, Benjamin Hager, Franziska Büscheck, Doris Höflmayer, Maria Christina Tsourlakis, Sarah Minner, Till S. Clauditz, Claudia Hube-Magg, Andreas M. Luebke, Ronald Simon, Jakob R. Izbicki, Eike Burandt, Guido Sauter, Christoph Fraune, Sören Weidemann, Thorsten Schlomm, Hans Heinzer, Alexander Haese, Markus Graefen, Hartwig Huland, Asmus Heumann

  Keywords: ROCK1, prostate cancer, prognosis, immunohistochemistry, tissue micro array

  Published in Aging on September 25, 2019

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  Background and objectives: Overexpression of the cytoskeleton-modulating kinase ROCK1 has been associated with unfavorable outcome in many cancers, but its impact in prostate cancer is largely unknown.

  Results: A weak ROCK1 staining was found in >90% of normal, and cancerous prostate tissues, but was generally stronger in cancer cells as compared to adjacent normal glands. In cancer, ROCK1 staining was considered weak, moderate, and strong in 22%, 53%, and 18% of cases respectively. Higher ROCK1 expression levels were associated with tumor stage, and Gleason grade, positive nodal stage, positive surgical margin, accelerated cell proliferation and early PSA recurrence in multivariable analysis. ROCK1 up regulation was associated with androgen receptor (AR) expression, TMPRSS2:ERG fusion, genomic deletions of the PTEN tumor suppressor, as well as recurrent deletions at chromosomes 3p, 5q, 6q. Strong ROCK1 staining was found in 3% of AR-negative, but in 27% of strongly AR positive cancers, in 13% of ERG-negative but in 25% of ERG positive cancers, and in 12% of PTEN normal but in 26% of PTEN deleted cancers.

  Conclusions: This study identifies ROCK1 expression associated with prognosis in prostate cancer.

  Methods: We tested ROCK1 expression in 12 427 prostate cancer specimens and followed PSA recurrence after prostatectomy.

  

  Representative images of normal (A) and cancerous glands (B–E) with negative (B), weak (C), moderate (D), and strong (E) ROCK1 staining. Spot size is 600 μm at 100 / 400x of originals.

  
  
  

  

  Association between ROCK1 expression and biochemical recurrence in (A) all cancers, (B) ERG-fusion negative cancers, (C) ERG-fusion positive cancers, (D) PTEN deleted cancers.

  
  
  

  

  Association between positive ROCK1 staining and androgen-receptor (AR) status in all cancer, ERG fusion negative and ERG fusion positive cancers.

  
  
  

  

  Association between ROCK1 staining and 10q23 (PTEN), 5q21 (CHD1), 6q15 (MAP3K7), 3p13 (FOXP1) deletions in (A) all cancers, (B) ERG negative cancers and (C) in ERG positive cancers.

  
  
  

• Research Paper pp undefined-undefined

  Identification of ROCK1 as a novel biomarker for postmenopausal osteoporosis and pan-cancer analysis

  Relevance score: 6.132061

  Bowen Lai, Heng Jiang, Yuan Gao, Xuhui Zhou

  Keywords: postmenopausal osteoporosis, ROCK1, machined Learning, immune infiltration, pan-cancer

  Published in Aging on Invalid Date

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  Background: Postmenopausal osteoporosis (PMOP) is a prevalent bone disorder with significant global impact. The elevated risk of osteoporotic fracture in elderly women poses a substantial burden on individuals and society. Unfortunately, the current lack of dependable diagnostic markers and precise therapeutic targets for PMOP remains a major challenge.

  Methods: PMOP-related datasets GSE7429, GSE56814, GSE56815, and GSE147287, were downloaded from the GEO database. The DEGs were identified by “limma” packages. WGCNA and Machine Learning were used to choose key module genes highly related to PMOP. GSEA, DO, GO, and KEGG enrichment analysis was performed on all DEGs and the selected key hub genes. The PPI network was constructed through the GeneMANIA database. ROC curves and AUC values validated the diagnostic values of the hub genes in both training and validation datasets. xCell immune infiltration and single-cell analysis identified the hub genes’ function on immune reaction in PMOP. Pan-cancer analysis revealed the role of the hub genes in cancers.

  Results: A total of 1278 DEGs were identified between PMOP patients and the healthy controls. The purple module and cyan module were selected as the key modules and 112 common genes were selected after combining the DEGs and module genes. Five Machine Learning algorithms screened three hub genes (KCNJ2, HIPK1, and ROCK1), and a PPI network was constructed for the hub genes. ROC curves validate the diagnostic values of ROCK1 in both the training (AUC = 0.73) and validation datasets of PMOP (AUC = 0.81). GSEA was performed for the low-ROCK1 patients, and the top enriched field included protein binding and immune reaction. DCs and NKT cells were highly expressed in PMOP. Pan-cancer analysis showed a correlation between low ROCK1 expression and SKCM as well as renal tumors (KIRP, KICH, and KIRC).

  Conclusions: ROCK1 was significantly associated with the pathogenesis and immune infiltration of PMOP, and influenced cancer development, progression, and prognosis, which provided a potential therapy target for PMOP and tumors. However, further laboratory and clinical evidence is required before the clinical application of ROCK1 as a therapeutic target.

• Research Paper pp undefined-undefined

  Micro RNA 148a induces apoptosis and prevents angiogenesis with bevacizumab in colon cancer through direct inhibition of ROCK1/c-Met via HIF-1α under hypoxia

  Relevance score: 6.448463

  Hsiang-Lin Tsai, Yueh-Chiao Tsai, Yen-Cheng Chen, Ching-Wen Huang, Po-Jung Chen, Ching-Chun Li, Wei-Chih Su, Tsung-Kun Chang, Yung-Sung Yeh, Tzu-Chieh Yin, Jaw-Yuan Wang

  Keywords: apoptosis, anti-angiogenesis, miR-148a, bevacizumab, ROCK1/c-Met

  Published in Aging on Invalid Date

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  Angiogenesis and antiapoptosis effects are the major factors influencing malignancy progression. Hypoxia induces multiple mechanisms involving microRNA (miRNA) activity. Vascular endothelial growth factor (VEGF) is correlated with angiogenesis. An antiapoptotic factor, myeloid leukemia 1 (Mcl-1) is the main regulator of cell death. This study examined the role of miR-148a in inhibiting VEGF and Mcl-1 secretion by directly targeting ROCK1/c-Met by downregulating HIF-1α under hypoxia. The protein expression of ROCK1 or Met/HIF-1α/Mcl-1 in HCT116 and HT29 cells (all P < 0.05) was significantly reduced by MiR-148a. The tube-formation assay revealed that miR-148a significantly suppressed angiogenesis and synergistically enhanced the effects of bevacizumab (both P < 0.05). The MTT assay revealed the inhibitory ability of miR-148a in HCT116 and HT29 cells (both P < 0.05). miR-148a and bevacizumab exerted synergistic antitumorigenic effects (P < 0.05) in an animal model. Serum miR-148a expression of metastatic colorectal cancer (mCRC) patients with a partial response was higher than that of mCRC patients with disease progression (P = 0.026). This result revealed that miR-148a downregulated HIF-1α/VEGF and Mcl-1 by directly targeting ROCK1/c-Met to decrease angiogenesis and increase the apoptosis of colon cancer cells. Furthermore, serum miR-148a levels have prognostic/predictive value in patients with mCRC receiving bevacizumab.