Actin-Binding LIM 1 (ABLIM1) Inhibits Glioblastoma Progression and Serves as a Novel Prognostic Biomarker

Liu, Danping; Wang, Xiaoping; Liu, Ying; Li, Chunliu; Zhang, Zhen; Lv, Peng

doi:https://doi.org/10.1155/2022/9516808

Disease Markers

On this page

Abstract Introduction Methods Results Discussion Conclusions Data Availability Conflicts of Interest Authors’ Contributions References Copyright Related Articles

Research Article | Open Access

Volume 2022 | Article ID 9516808 | https://doi.org/10.1155/2022/9516808

Actin-Binding LIM 1 (ABLIM1) Inhibits Glioblastoma Progression and Serves as a Novel Prognostic Biomarker

Danping Liu,¹Xiaoping Wang,¹Ying Liu,¹Chunliu Li,²Zhen Zhang,³and Peng Lv⁴

Academic Editor: Jie Mei

Received14 Oct 2022

Revised07 Dec 2022

Accepted08 Dec 2022

Published20 Dec 2022

Abstract

Background. Glioma is the most prevalent malignant brain tumor in adult humans, and glioblastoma (GBM) is the most malignant type. The actin-binding LIM 1 (ABLIM1) protein can modulate actin polymerization, which is essential for the cell proliferation and migration. We aim to investigate ABLIM1 expression, function, and clinical significance in GBM. Methods. The ABLIM1 mRNA level was extracted from the TCGA and GTEx online databases. The ABLIM1 protein expression level was explored using immunohistochemistry staining in a GBM cohort enrolled in our hospital (). The patient survival and prognostic factors were determined using the Kaplan-Meier method and multivariate Cox hazard proportional analysis, respectively. Two human GBM cell lines, U87 and U251 cells, were utilized for ABLIM1 overexpression and cell proliferation analyses. A subcutaneous xenograft model was generated using nude mice to validate the tumor-related effect of ABLIM1 in vivo. Results. ABLIM1 exhibited a significantly lower mRNA level in GBM than in other glioma or normal brain tissues. Higher ABLIM1 protein level was correlated with smaller GBM tumor size and better cancer-specific survival (CSS). Multivariate analysis identified ABLIM1 as a novel independent prognostic factor for GBM prognosis. ABLIM1 overexpression significantly inhibits U87 and U251 cell proliferation and colony formation. Consistently, ABLIM1 exerted tumor-suppressing functions in mice models. Conclusion. ABLIM1 plays antitumor roles in GBM progression and could be served as a novel biomarker to help predict GBM prognosis.

1. Introduction

Glioma is the most prevalent malignant brain tumor in adult humans. According to the World Health Organization (WHO), glioblastoma (GBM) is classified as grade IV glioma, highlighting its highly aggressive phenotype. The current treatment for GBM is surgical resection followed by radiochemotherapy [1]. Considering most GBM patients suffer from self-care difficulty, careful hospital nursing is critical for better life quality and prognosis. The Karnofsky score is a significant prognostic factor for GBM; the GBM prognosis is unsatisfactory. The five-year survival time of GBM is 5.5%, with a median survival time of less than 15 months [2, 3]. The intrinsic molecular characteristic of GBM in different patients is the predominant factor that results in distinct outcomes [4]. Therefore, GBM-related biomarker identification and their functional mechanism elucidation are urgently needed to improve disease prognosis.

The LIM domain refers to a cysteine-rich sequence motif that functions as a protein-binding interface and mediates specific protein-protein interactions. The actin-binding LIM (ABLIM) protein family members consist of four amino-terminal LIM domains and a carboxyl-terminal dematin-like domain, including a villin headpiece (VHP) domain that binds to actin filaments [5]. Currently, three subtypes, ABLIM1, ABLIM2, and ABLIM3, have been reported in mammals [6]. Actin-binding LIM 1 (ABLIM1) is a novel protein identified by Roof et al. in 1997 [7]. ABLIM1 can bind F-actin and thus mediates interactions between actin and other proteins. ABLIMs can synergistically stimulate the striated muscle activator of Rho signaling- (STARS-) dependent activation of the serum-response factor (SRF) through binding tightly with F-actin [8].

Dysregulated ABLIM1 is correlated with various diseases. ABLIM1 can construct actin networks to prevent mechanical tension-induced blebbing [9]. ABLIM1 abnormal splicing is identified in skeletal muscles of myotonic dystrophy type 1 patients and the corresponding mouse model [10]. The ablation of a retina-specific isoform of ABLIM1 results in the absence of morphological and functional defects in retinal neurons [11]. Similarly, ABLIM1-rs7099208 is associated with severe spermatogenic failure [12]. ABLIM1 polymorphisms are also associated with personality traits and alcohol dependence [13], implying its significant role as an axon development-related protein [14]. An in silico study suggests that hypermethylated and lowly expressed ABLIM1 is present in gestational diabetes mellitus [15]. Meanwhile, ABLIM1 participates in osteoclast differentiation and migration, depending on the NF-κB ligand (RANKL)-mediated signaling pathway [6, 16].

ABLIM1 maps to human chromosome 10q25, a frequently deleted region in human cancers [17]. According to microarray data, ABLIM1-mRNA is downregulated in adrenocortical carcinomas compared to nontumorous tissues [18]. The tumor-related role of ABLIM1 has also been reported in hepatocellular [19] and nasopharyngeal carcinoma [20]. However, whether ABLIM1 modulates GBM progression is unknown. Here, we aim to investigate the ABLIM1 expression profile in GBM for the first time. Additionally, correlations between ABLIM1 with patients’ clinicopathological characteristics and survival will be analyzed. Finally, functional mechanisms of ABLIM1 in GBM will be explored using in vitro and in vivo assays.

2. Methods

2.1. Online Dataset

The clinical information and mRNA gene expression data were obtained from the TCGA (https://cancergenome.nih.gov/) and GTEx (https://gtexportal.org/home/) databases. The survival information was retrieved from Liu et al.’s publication [21].

2.2. Cohort Enrollment

GBM tissues were collected from Yantai Yuhuangding Hospital (). Patients with pathologically confirmed non-GBM and patients with incomplete clinical features were excluded. The study was conducted with all participants’ informed consent and approved by the Ethics Committee of Yantai Yuhuangding Hospital (No. 2022-280).

2.3. Immunohistochemistry (IHC)

ABLIM1 protein expression was detected in GBM tissues using IHC. Briefly, the sections were heated at 60°C overnight, dewaxed with water, and heated for antigen retrieval. Then, sections were incubated with 1% H₂O₂ to inactivate endogenous enzymes for 10 min at room temperature. The sections were incubated with anti-ABLIM1 primary antibody (1 : 50, #MBS2518798, MyBioSource, USA) overnight in the cold room, then with the secondary antibody for 30 min at room temperature the following day. The 3,3-diaminobenzidine (DAB) was used for color staining, followed by hematoxylin incubation for 5 min. The stained IHC sections were observed under a light microscope (400x magnification). The staining was assessed based on staining intensity and percentage of positively stained cells by two independent pathologists blinded to patients’ information. Sections with greater than 50% positively stained cells (dark yellow or brown) were considered high-ABLIM1 expression. Otherwise, sections were considered low-ABLIM1 expressions.

2.4. Cell Culture and Transfection

Two human GBM cell lines, U87 (wild-type TP53) and U251 (mutant TP53), were used in our study. Both cell lines were maintained in DMEM supplied with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin. All cells were cultured at 37°C in a humidified atmosphere containing 5% CO₂. Human ABLIM1 cDNA was cloned into pcDNA3.1 plasmids for overexpressing transfection serving as a negative control, according to the manufacturer’s instructions.

2.5. Western Blot

After lysing cultured cells with radioimmunoprecipitation assay (RIPA) buffer (Beyotime, China), equal amounts of proteins were separated by sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene difluoride (PVDF) membranes (Millipore, USA). Then, transferred membranes were blocked with 5% BSA and incubated for 1 h at 4°C. The blocked PVDF membranes were incubated with primary antibodies, including anti-ABLIM1 (1 : 1000, #MBS2518798, MyBioSource, USA) and anti-beta-actin (1 : 3000; Proteintech, USA) antibodies, at 4°C overnight. On the next day, membranes were washed three times and incubated with the secondary antibody at room temperature for 1 h. The immunoblotting signals were visualized with an enhanced chemiluminescence (ECL) reagent (Thermo Fisher Scientific, USA).

2.6. Cell-Counting Kit 8 (CCK-8) Assays

The CCK-8 kit was used to evaluate cell proliferation activity according to the manufacturer’s procedure. Briefly, 1,000 transfected cells were seeded into each well of a 96-well plate. Then, the cell proliferation capacity was measured at 0, 1, 2, 3, and 4 days. At designated time points, the culture medium was removed, and the cells were washed with phosphate-buffered saline (PBS) to remove dead cells. Then, CCK-8 reagents were added to the 96-well plates (100 μL/well) and incubated at 37°C for 90 min. Finally, the absorption was measured at 450 nm using a microplate reader.

2.7. Colony Formation

Transfected cells were seeded into six-well plates 200 cells/well density cell and cultured for two weeks. Then, the colonies were fixed with methanol for 10 min, followed by staining with crystal violet for 20 min. The number of colonies was counted under a light microscope.

2.8. Mice Model

Four-week-old nude mice were injected subcutaneously with transfected cells to establish a xenograft model and examine the in vivo effect of ABLIM1 on GBM progression. The tumor size was monitored every week using the Vernier caliper. The tumor volume was calculated using the following formula: ( and ). All mice were sacrificed after four weeks. The xenografts were isolated and weighted. The study was approved by the Ethics Committee of Yantai Yuhuangding Hospital.

2.9. Statistics

Statistical analyses were conducted using SPSS (Version 20.0) and GraphPad Prism (Version 5.0) software. The correlations between ABLIM1 and clinic-pathological variables were tested using the chi-square test. Cancer-specific survival (CSS) was defined as the interval between the surgery and tumor-related death or the last follow-up. Univariate log-rank test and multivariate Cox regression model were used for survival analyses. Statistical differences between the two groups were assessed using Student’s -test. Independent experiments were repeated at least three times for each experiment and exhibited as (SD). was considered statistically significant [22].

3. Results

3.1. ABLIM1 Expression and Clinical Relevance on mRNA Level Using Online Databases

We discovered that ABLIM1 exhibits distinct levels in glioma tissues with different WHO grades by extracting the microarray data from the TCGA database (Figure 1(a)). GBM tissues (WHO grade IV) had significantly lower ABLIM1 levels than low-grade gliomas (WHO grade II-III). ABLIM1 level comparison based on histological types revealed that GBM has the lowest ABLIM1 level than astrocytoma or oligodendroglioma (Figure 1(b), ). Notably, glioma patients with a lower ABLIM1 level had shorter overall survival than those with a higher ABLIM1 level (Figure 1(c), ). We investigated ABLIM1’s detailed role in GBM due to its significantly lower level than other glioma types. As expected, TCGA and GTEx datasets revealed a significantly lower ABLIM1-mRNA level in GBM than in normal brain tissues (Figure 1(d)).

(a)

(b)

(c)

(d)

(e)

(f)

Figure 1

The ABLIM1 mRNA and protein expression in GBM. (a) The ABLIM1 mRNA level in glioma tissues with different WHO grades from the TCGA database was compared, indicating the lowest level in WHO grade IV glioma, namely the glioblastoma (GBM). The y-axis was plotted according to the transcripts per million (TPM) and converted to log₂ (TPM+1). (b) The ABLIM1 mRNA level in glioma tissues with different histological types from the TCGA database was compared, showing the lowest level in glioblastoma compared with other histological types. (c) We conducted a Kaplan-Meier survival analysis to compare the survival difference of glioma patients with low or high ABLIM1 mRNA levels using the data from the TCGA database. (d) The ABLIM1 mRNA level was compared between GBM and normal brain tissues using TCGA and GTEx databases (). Each red dot indicates a specific mRNA level in a GBM sample, while each green dot indicates normal brain tissue. (e) Representative low ABLIM1 protein expression in GBM as reflected using IHC, demonstrating almost negative expression in specific GBM samples. (f) Representative high ABLIM1 protein expression in GBM tissues using IHC, exhibiting a positive expression in the cytoplasm. , ; ns: no significance. Magnification: 400x.

3.2. Enrolled Patients’ Characteristics

Table 1 displays that the median age of our enrolled cohort () is 62 years old. The GBM cohort included 51 females and 53 males. The median tumor size was 4.0 cm, recorded by the largest diameter. Among the 104 cases, 55 underwent local resection, 20 underwent radical resection, and the remaining 29 underwent lobectomy. Only 19 cases received definite chemotherapy, while the other 85 did not accept chemotherapy or were unsure. The median follow-up time was seven months, ranging from 1 to 132 months.

3.3. Protein Expression and Clinical Significance of ABLIM1 in GBM

According to IHC (Figures 2(a) and 2(b)), different GBM tissues exhibited remarkable ABLIM1 protein expression levels. Accordingly, we divided enrolled GBM patients into low-ABLIM1 () and high-ABLIM1 () groups. The correlations between ABLIM1 and GBM characteristics were analyzed using the chi-square test (Table 1). ABLIM1 level was negatively correlated with tumor size (), indicating that ABLIM1 may exert tumor-suppressive effects in GBM. However, ABLIM1 presented no significant correlation between patient age, sex, surgery, and chemotherapy ().

(a)

(b)

(c)

(d)

(e)

(f)

The Kaplan-Meier method and log-rank test were conducted to assess patient prognosis (Table 2). Survival curves indicated that a lower ABLIM1 was correlated with a worse prognosis (Figure 2(a)), consistent with its prognostic significance of mRNA level (Figure 1(c)). The three-year CSS rate was 54.7% in the high-ABLIM1 group, while it decreased to 12.4% in the low-ABLIM1 group. Meanwhile, elderly patients had a poor prognosis (Figure 2(b), ), highlighting the importance of careful nursing, while sex has no significant effect on patient survival (Figure 2(c), ). Larger tumor size was significantly correlated with unfavorable survival as a conventional prognostic factor (Figure 2(d), ). Nevertheless, neither the resection pattern nor chemotherapy had a prognostic effect in our cohort (Figures 2(e)–2(f), ).

We applied patients’ age, tumor size, and ABLIM1 level into a Cox hazard regression model to identify independent prognostic factors (Table 2). Consequently, elder age was an independent unfavorable prognostic factor (, 95% CI 1.6–4.6, ). Higher ABLIM1 protein expression was also determined as an independent favorable prognostic factor (, 95% CI 0.2–0.6, ), indicating that patients with higher ABLIM1 expression have better survival.

3.4. ABLIM1 Exerts an Anti-Proliferation Effect in GBM In Vitro and In Vivo

The cellular experiments were conducted to evaluate the detailed function of ABLIM1 in GBM. Immunoblotting revealed that ABLIM1 was detectable in U87 and U251 cell lines. The transfection of ABLIM1 plasmids significantly increased its protein level (Figure 3(a)). The CCK-8 proliferation assay reflected an attenuated proliferation capacity in the ABLIM1-overexpressed group (Figure 3(b)). Consistently, ABLIM1 transfection impaired the colony formation ability in both cell lines (Figure 3(c)).

(a)

(b)

(c)

Finally, we established a subcutaneous xenograft model as an in vivo strategy to validate the role of ABLIM1 during GBM progression. Subcutaneous injection of different GBM cells had no significant effect on mice weight (Figure 4(a)). However, xenografts generated by ABLIM1-overexpressed cells exhibit decreased growth compared to those generated by vector-overexpressed cells (Figure 4(b)). After tumor excision and weighting, ABLIM1 xenografts were lighter and smaller than vector xenografts (Figures 4(c) and 4(d)). Therefore, we concluded that ABLIM1 might play antitumor roles by inhibiting GBM growth.

(a)

(b)

(c)

(d)

Figure 4

High ABLIM1 suppressed GBM growth in vivo. (a) The mice weight was recorded since the date of subcutaneous tumor cell injection, showing no statistically significant difference between vector and ABLIM1 groups. (b) Subcutaneous tumor growth was monitored weekly after tumor cell injection according to the tumor volume. The tumor volume was calculated using the formula: ( and ). (c) Four weeks after tumor cell injection, the xenografts were isolated and weighted to compare their differences. (d) Isolated xenografts were photographed, and visual size differences can be observed between vector and ABLIM1 groups. by Student’s -test.

4. Discussion

Initially, we determined ABLIM1 expression and clinical significance in GBM. According to our data, decreased ABLIM1 was associated with larger tumor size, whereas ABLIM1 overexpression resulted in impaired GBM growth. Besides its total protein expression level, ABLIM1 phosphorylation has been previously reported to participate in hepatocellular carcinoma (HCC) progression. According to Dong et al.’s data, dominant negative mutations of Ser 214 and Ser 431 residues of ABLIM1 inhibited actin polymerization and affected cellular migration [19]. However, we cannot map the ABLIM1 phosphorylation level in GBM specimens due to lack of specific phosphorylation antibodies. Considering the importance of posttranslational modifications [23], whether its phosphorylation is dysregulated in tumors and the corresponding mechanism deserves further investigation.

Several studies revealed upstream regulators of ABLIM1. The lncRNA ZNF667-AS1 promoted ABLIM1 expression by adsorbing miR-1290, subsequently attenuating nasopharyngeal carcinoma progression [20]. Meanwhile, microarray data implied that miR-129-3p potentially targeted ABLIM1 in retinal pigment epithelial cells, thus inhibiting ciliation in proliferating cells and impairing cilia elongation [24]. The hsa-miR-6165 is another upstream microRNA of ABLIM1 in NT2 neural cells. The hsa-miR-6165 overexpression can downregulate ABLIM1, attenuate NT2 differentiation, and affect the cell cycle and apoptosis [25].

Nevertheless, we did not identify a statistically significant alteration in ABLIM1 expression after transfecting the above microRNAs in GBM cells (data not shown). The cell-type-specific signatures of microRNAs may explain this on target mRNA expression [26]. Additionally, ABLIM1 may interact with GSK-3β signaling pathways. A recent study demonstrated that GSK-3β could bind ABLIM1 and modulate its function in cardiovascular cells [27]. Since the Wnt-GSK-3β signaling pathway is well known for its tumor-related function, GSK-3 and ABLIM1 probably interact with malignancies. The upstream and downstream mechanisms of ABLIM1 in tumors must be systematically elucidated using high-throughput techniques, such as next-generation sequencing and mass spectrometry.

According to our clinical data, ABLIM1 expression in GBM tissues could be an independent prognostic factor. GBM patients with low or negative ABLIM1 expression have worse CSS. The important point is that elder age patients had a worse prognosis. Therefore, high-quality nursing is critical for GBM prognosis. However, our data were retrospectively collected from a single medical center with a limited case number, which may have a regional bias. Although we used an online database to verify our findings, further validation may be necessary. Nevertheless, we provided initial evidence regarding the tumor-related role of ABLIM1 in GBM from clinical, cellular, and in vivo aspects.

5. Conclusions

ABLIM1 is decreased in GBM, and its lower expression is correlated with poor prognosis. High ABLIM1 expression can inhibit GBM growth in vitro and in vivo.

Data Availability

Data is available upon requirement.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Authors’ Contributions

Danping Liu conducted statistical assays. Xiaoping Wang helped with data collection. Ying Liu and Chunliu Li performed cellular experiments. Zhen Zhang performed in vivo assays. Peng Lv designed this project and wrote this paper. Danping Liu and Xiaoping Wang contributed equally to this work.

References

O. L. Chinot, W. Wick, W. Mason et al., “Bevacizumab plus radiotherapy–temozolomide for newly diagnosed glioblastoma,” The New England Journal of Medicine, vol. 370, no. 8, pp. 709–722, 2014.
View at: Publisher Site | Google Scholar
T. Jiang, D. H. Nam, Z. Ram et al., “Clinical practice guidelines for the management of adult diffuse gliomas,” Cancer Letters, vol. 499, pp. 60–72, 2021.
View at: Publisher Site | Google Scholar
N. Sanai, J. Li, J. Boerner et al., “Phase 0 trial of AZD1775 in first-recurrence glioblastoma patients,” Clinical Cancer Research, vol. 24, no. 16, pp. 3820–3828, 2018.
View at: Publisher Site | Google Scholar
H. Shi and S. Zhang, “Expression and prognostic role of orphan receptor GPR110 in glioma,” Biochemical and Biophysical Research Communications, vol. 491, no. 2, pp. 349–354, 2017.
View at: Publisher Site | Google Scholar
B. J. Koch, J. F. Ryan, and A. D. Baxevanis, “The diversification of the LIM superclass at the base of the metazoa increased subcellular complexity and promoted multicellular specialization,” PLoS One, vol. 7, no. 3, article e33261, 2012.
View at: Publisher Site | Google Scholar
S. H. Jin, H. Kim, D. R. Gu et al., “Actin-binding LIM protein 1 regulates receptor activator of NF-κB ligand-mediated osteoclast differentiation and motility,” BMB Reports, vol. 51, no. 7, pp. 356–361, 2018.
View at: Publisher Site | Google Scholar
D. J. Roof, A. Hayes, M. Adamian, A. H. Chishti, and T. Li, “Molecular characterization of abLIM, a novel actin-binding and double zinc finger protein,” The Journal of Cell Biology, vol. 138, no. 3, pp. 575–588, 1997.
View at: Publisher Site | Google Scholar
T. Barrientos, D. Frank, K. Kuwahara et al., “Two novel members of the ABLIM protein family, ABLIM-2 and -3, associate with STARS and directly bind F-actin,” The Journal of Biological Chemistry, vol. 282, no. 11, pp. 8393–8403, 2007.
View at: Publisher Site | Google Scholar
G. Li, S. Huang, S. Yang et al., “abLIM1 constructs non-erythroid cortical actin networks to prevent mechanical tension-induced blebbing,” Cell Discovery, vol. 4, no. 1, pp. 1–14, 2018.
View at: Publisher Site | Google Scholar
N. Ohsawa, M. Koebis, H. Mitsuhashi, I. Nishino, and S. Ishiura, “ABLIM1 splicing is abnormal in skeletal muscle of patients with DM1 and regulated by MBNL, CELF and PTBP1,” Genes to Cells, vol. 20, no. 2, pp. 121–134, 2015.
View at: Publisher Site | Google Scholar
C. Lu, X. Huang, H. F. Ma et al., “Normal retinal development and retinofugal projections in mice lacking the retina-specific variant of actin-binding LIM domain protein,” Neuroscience, vol. 120, no. 1, pp. 121–131, 2003.
View at: Publisher Site | Google Scholar
M. Cerván-Martín, L. Bossini-Castillo, R. Rivera-Egea et al., “Effect and in silico characterization of genetic variants associated with severe spermatogenic disorders in a large Iberian cohort,” Andrology, vol. 9, no. 4, pp. 1151–1165, 2021.
View at: Publisher Site | Google Scholar
K.-S. Wang, X. Liu, N. Aragam et al., “Polymorphisms in ABLIM1 are associated with personality traits and alcohol dependence,” Journal of Molecular Neuroscience, vol. 46, no. 2, pp. 265–271, 2012.
View at: Publisher Site | Google Scholar
K. Choi, J. Lee, and H. J. Kang, “Myelination defects in the medial prefrontal cortex of Fkbp5 knockout mice,” The FASEB Journal, vol. 35, no. 2, article e21297, 2021.
View at: Publisher Site | Google Scholar
M. Chen, J. Yan, Q. Han, J. Luo, and Q. Zhang, “Identification of hub-methylated differentially expressed genes in patients with gestational diabetes mellitus by multi-omic WGCNA basing epigenome-wide and transcriptome-wide profiling,” Journal of Cellular Biochemistry, vol. 121, no. 5-6, pp. 3173–3184, 2020.
View at: Publisher Site | Google Scholar
H. Narahara, E. Sakai, Y. Yamaguchi et al., “Actin binding LIM 1 (abLIM1) negatively controls osteoclastogenesis by regulating cell migration and fusion,” Journal of Cellular Physiology, vol. 234, no. 1, pp. 486–499, 2019.
View at: Publisher Site | Google Scholar
A. C. Kim, L. L. Peters, J. H. M. Knoll et al., “Limatin (LIMAB1), an actin-binding LIM protein, maps to mouse chromosome 19 and human chromosome 10q25, a region frequently deleted in human cancers,” Genomics, vol. 46, no. 2, pp. 291–293, 1997.
View at: Publisher Site | Google Scholar
P. Soon, A. J. Gill, D. E. Benn et al., “Microarray gene expression and immunohistochemistry analyses of adrenocortical tumors identify IGF2 and Ki-67 as useful in differentiating carcinomas from adenomas,” Endocrine-Related Cancer, vol. 16, no. 2, pp. 573–583, 2009.
View at: Publisher Site | Google Scholar
X. Dong, M. Feng, H. Yang et al., “Rictor promotes cell migration and actin polymerization through regulating ABLIM1 phosphorylation in hepatocellular carcinoma,” International Journal of Biological Sciences, vol. 16, no. 15, pp. 2835–2852, 2020.
View at: Publisher Site | Google Scholar
X. Chen, Y. Huang, D. Shi et al., “LncRNA ZNF667-AS1 promotes ABLIM1 expression by adsorbing microRNA-1290 to suppress nasopharyngeal carcinoma cell progression,” Oncotargets and Therapy, vol. Volume 13, pp. 4397–4409, 2020.
View at: Publisher Site | Google Scholar
J. Liu, T. Lichtenberg, K. A. Hoadley et al., “An integrated TCGA pan-cancer clinical data resource to drive high-quality survival outcome analytics,” Cell, vol. 173, no. 2, pp. 400–416.e11, 2018, e11.
View at: Publisher Site | Google Scholar
Q. Zhang, H. Hu, H. Liu et al., “RNA sequencing enables systematic identification of platelet transcriptomic alterations in NSCLC patients,” Biomedicine & Pharmacotherapy, vol. 105, pp. 204–214, 2018.
View at: Publisher Site | Google Scholar
Q. Zhang, K. Xiao, J. M. Paredes et al., “Parathyroid hormone initiates dynamic NHERF1 phosphorylation cycling and conformational changes that regulate NPT2A-dependent phosphate transport,” Journal of Biological Chemistry, vol. 294, no. 12, pp. 4546–4571, 2019.
View at: Publisher Site | Google Scholar
J. Cao, Y. Shen, L. Zhu et al., “miR-129-3p controls cilia assembly by regulating CP110 and actin dynamics,” Nature Cell Biology, vol. 14, no. 7, pp. 697–706, 2012.
View at: Publisher Site | Google Scholar
M. Hassanlou, B. M. Soltani, and S. J. Mowla, “Expression and function of hsa-miR-6165 in human cell lines and during the NT2 cell neural differentiation process,” Journal of Molecular Neuroscience, vol. 63, no. 2, pp. 254–266, 2017.
View at: Publisher Site | Google Scholar
P. Sood, A. Krek, M. Zavolan, G. Macino, and N. Rajewsky, “Cell-type-specific signatures of microRNAs on target mRNA expression,” Proceedings of the National Academy of Sciences, vol. 103, no. 8, pp. 2746–2751, 2006.
View at: Publisher Site | Google Scholar
M. J. Stachowski-Doll, M. Papadaki, T. G. Martin et al., “GSK-3β localizes to the cardiac Z-disc to maintain length dependent activation,” Circulation Research, vol. 130, no. 6, pp. 871–886, 2022.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2022 Danping Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

385

Downloads

415

Citations