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Table of Contents
ORIGINAL ARTICLE
Year : 2020  |  Volume : 3  |  Issue : 3  |  Page : 135-142

Comprehensive RNAseq analysis reveals PIK3CD promotes glioblastoma tumorigenesis by mediating PI3K-Akt signaling pathway


1 Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China
2 Cardiovascular Research Institute, Xiamen Cardiovascular Hospital, Xiamen University, Xiamen, Fujian Province, China
3 Department of Anatomical Pathology, Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
4 Department of Neurosurgery/Neuro-Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong Province, China

Date of Submission07-Aug-2020
Date of Decision24-Aug-2020
Date of Acceptance01-Sep-2020
Date of Web Publication17-Oct-2020

Correspondence Address:
Dr. Shing-shun Tony To
Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong Special Administrative Region
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/glioma.glioma_23_20

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  Abstract 

Background and Aim: Glioblastoma (GBM) is the most common and aggressive form of primary malignant brain tumors. Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit delta (PIK3CD), which is overexpressed in GBM, is involved in GBM pathogenesis and drug resistance. However, the molecular mechanism by which PIK3CD drives its transcriptional program toward GBM favors remains elusive. Materials and Methods: Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated 9 technology was used to knock-out (KO) PIK3CD gene, and comprehensive RNAseq analysis was performed to investigate the underlying role of PIK3CD in GBM. Results: To minimize the off-target effects, two KO cell clones were used, and our data showed that PIK3CD KO altered the expression 306 genes in both KO cell clones compared with the parent U87 cell line. Gene set enrichment analysis revealed that genes involved in epithelial-mesenchymal (MES) transition-related biological processes were highly depressed in both KO cell clones in a similar fashion, suggesting PIK3CD's involvement in MES transformation/transition in GBM. Comprehensive pathway analysis by three different platforms confirmed that PIK3CD exerted its oncogenic function in GBM through phosphatidylinositol 3-kinase (PI3K)-Akt signaling pathway. In addition, other signaling pathways (integrin, cadherin, Wnt, and inflammation mediated by chemokine and cytokine signaling pathways) were found decreased in the KO cell clones. Further, The Cancer Genomic Atlas (TCGA) analysis of our PI3K-Akt pathway-related genes showed a similar pattern of expression. Conclusion: PIK3CD is involved in GBM pathogenesis, and this action probably mediated through the PI3K-Akt signaling pathway.

Keywords: Glioblastoma, integrin, mesenchymal transformation, phosphatidylinositol 3-kinase-akt, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit delta knock-out, RNAseq


How to cite this article:
Azam Z, Shao W, Ng Hk, Wang J, Chen Zp, To Ss. Comprehensive RNAseq analysis reveals PIK3CD promotes glioblastoma tumorigenesis by mediating PI3K-Akt signaling pathway. Glioma 2020;3:135-42

How to cite this URL:
Azam Z, Shao W, Ng Hk, Wang J, Chen Zp, To Ss. Comprehensive RNAseq analysis reveals PIK3CD promotes glioblastoma tumorigenesis by mediating PI3K-Akt signaling pathway. Glioma [serial online] 2020 [cited 2022 Nov 28];3:135-42. Available from: http://www.jglioma.com/text.asp?2020/3/3/135/298395


  Introduction Top


Gliomas are brain tumors, the most lethal of all pediatric solid tumors, accounting for over 80% of all fatal central nervous system malignancy.[1],[2] More than 70% of patients diagnosed with glioblastoma (GBM) – the most malignant and aggressive form of gliomas – survive <24 months from diagnosis despite surgical excision, radiotherapy, and high-dose chemotherapy.[3],[4] GBM frequently develops resistance to conventional chemo- and radiotherapy, and it is believed that unique features of the brain tumor (micro-environmental, genetic and epigenetic) often exacerbate this process.[5],[6] Moreover, the highly heterogeneous nature of GBM tumors and their associated diverse cellular and invasive phenotypes are equally responsible for treatment failure.[7]

The phosphatidylinositol 3-kinase (PI3K) pathway is one of the most highly deregulated cell signaling pathways in GBM,[8] that promotes metabolism, proliferation, cell survival, growth, and angiogenesis in response to extracellular signals.[9],[10] Based on the regulation, structure, and substrate binding capacity, the PI3K family is divided into four different classes: Class I to III.[10] Class I PI3K is further subdivided into two subclasses: Class IA, comprising a p110 catalytic subunit, namely p110α, β, or δ and a regulatory subunit p85, and Class IB consists of a catalytic p110 γ and a regulatory p101 subunit. Class II has three catalytic subunits, but no regulatory subunits, whereas Class III comprises a regulatory and a catalytic subunit.[11] A number of previous studies have shown the involvement of Class IA PI3K in GBM. Knockdown of PIK3CA significantly inhibits cell viability, migration, and invasion in medulloblastoma and GBM cells.[12] Another study showed that selective inhibition of p110 β by AZD6482 can inhibit glioma cell proliferation.[13] Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit delta (PIK3CD) primarily expresses in leukocytes and thus emerges as a promising target for hematological malignancies. However, recent studies suggest that p110 δ is also expressed in other solid tumors, including brain cancer.[14] Our research group has demonstrated that siRNA-mediated knock-down of PIK3CD is associated with reduced GBM cell migration, invasion, and proliferation.[15] In another study, the expression of PIK3CD is shown to be related to glioma cell resistance to erlotinib,[16] adding another layer of solid evidence that PIK3CD takes part in GBM pathogenesis.

We hypothesized that PI3KCD is involved in GBM pathogenesis and aims to address its role in GBM. To address our aim, we completely suppressed the PIK3CD gene activity by Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated 9 (Cas9) and analyzed the transcriptomes of parent and knockout (KO) cell clones using bulk RNAseq.


  Materials and Methods Top


Cell lines and cell culture

The human GBM cell line U87 and two PI3KCD knockout cell lines generated, designated as KO_1 and KO_2, were used for all experimental purposes. Cells were cultured in minimum essential medium alpha (Gibco, Invitrogen, UK) supplemented with 10% (v/v) fetal bovine serum (Gibco, Invitrogen, UK), and the cultured cells were maintained at 37°C with 5% CO2.

Protein extraction, quantification, and western blotting

Cell pellets were collected and washed twice with 1× PBS (Gibco, Invitrogen, UK). The collected cell pellet was lysed in RIPA buffer for 30 min in ice. The cellular lysate was clarified by centrifugation, and subsequent collect the clear supernatant for future use. The amount of protein in cell lysate was then measured by Pierce Protein Assay Kit (Thermo Fisher Scientific, 168 Third Avenue, Waltham, MA USA). Samples were mixed with 4× loading dye and separated on 12% polyacrylamide gel. The separated proteins then transfer on a PVDF membrane for 2 h at 250 mA. The membrane was blocked for 1 h by 5% nonfat milk in. 1% TBST and washed with 0.1% TBST thrice for 10 min. The blocked membrane then incubated with the appropriate dilution of primary antibody overnight at cold room (β-Actin (13E5) Rabbit mAb #4970, PI3 Kinase p110 δ (D1Q7R) Rabbit mAb #34050, Cell signaling, Danvers, MA, USA). After that, membrane washed with 0.1% TBST and incubate again with secondary antibody with conjugated HRP for 1 h at room temperature, washed and protein signals were visualized by ECL select Western blot detection reagent and recorded by chemiDoc MP imaging system (Bio-Rad, CA, USA).

RNA isolation and quality check

Total RNA was extracted using the RNeasy Kit (Qiagen, Germantown, MD, USA) combined with Trizol (Thermo Fisher Scientific, 168 Third Avenue, Waltham, MA USA) method from U87, KO_1 and KO_2 cells. Contaminant genomic DNA was removed by Dnase treatment (Qiagen). The purity of total RNA was evaluated by spectrophotometry (NanoDrop 2000, Thermo Scientific, Madison, WI, USA) and Bioanalyzer analysis. The purity of RNA was measured by the ratio of the absorbance at 260 and 280 nm (A260/280) and at 260 and 230 nm (A260/230), along with RNA integrity (RIN) value. Samples considered pure having A260/280 and A260/230 over 2 and RIN value over 9. The integrity of total RNA quality was also checked by 1% agarose gel electrophoresis.

RNA sequencing

cDNA libraries were prepared by KAPA Stranded mRNA-Seq Kit (Roche Molecular Biochemicals, Indianapolis, IN, USA). One μg of total RNA was used as starting material. The manufacturer's protocol was followed. In brief, Poly-A containing mRNA was collected by using poly-T oligo-attached magnetic beads. The purified mRNA was fragmented to 200–300 bp by incubating at 94°C for 6 min in the presence of magnesium ions. The fragmented mRNA was then applied as template to synthesize the first-strand cDNA by using random hexamer-primer and reverse transcriptase. In the second-strand cDNA synthesis, the mRNA template was removed, and a replacement strand was generated to form the blunt-end double-stranded (ds) cDNA. The ds cDNA underwent 3' adenylation and indexed adaptor ligation. The adaptor-ligated libraries were enriched by ten cycles of polymerase chain reaction. The libraries were denatured and diluted to optimal concentration. Illumina NovaSeq 6000 was used for Pair-End 151 bp sequencing. Sequencing reads were first filtered for adapter sequence and low-quality sequence followed by retaining only reads with read length ≥40 bp. Reads were mapped to the reference genome using STAR Version 2.5.2 (https://github.com/alexdobin/STAR) and quantify the expression using RSEM Version 1.2.31 (https://deweylab.github.io/RSEM/). Differential expression analysis was performed using EBSeq (http://bioconductor.org/packages/release/bioc/html/EBSeq.html).

Bioinformatics analysis

Morpheus software (https://software.broadinstitute.org/morpheus/) was used to quantify the expression pattern from whole RNA-Seq data. Venn diagram and volcano plot data were generated by FunRich (http://www.funrich.org/) and GraphPad Prism 8 (GraphPad Software, Inc., San Diego, CA, USA), respectively. Enrichr (https://amp.pharm.mssm.edu/Enrichr/) functional analysis tool was employed to identify the Gene Ontolology (GO) term and pathway identification from whole transcriptomic data. Gene set enrichment analysis (GSEA) software (https://www.gsea-msigdb.org/gsea/index.jsp) was used to identify the hallmark gene sets of our whole transcriptomic data. Functional protein enrichment analysis was determined by STRING (https://string-db. org/) software. GEPIA (http://gepia.cancer-pku. cn/about.html) interactive webserver was used to match our transcriptomic data with the TCGA dataset of GBM.


  Results Top


Overview of transcriptomic data

We employed CRISPR-Cas9 to completely KO PIK3CD gene (unpublished data). After screening, we successfully identified two KO clones (designated as KO_1 and KO_2) and Western blot analysis showed the activity of the PIK3CD gene was completely abrogated [Figure 1]A. Next, we used RNA-Seq to quantitatively compare the gene expression pattern between parent (U87) and KO cell clones. The sample analysis workflow is shown in [Figure 1]B. After filtering the ribosomal RNA (rRNA) reads and aligned to reference genome, 46,832,410, 41,079,948, and 41,187,770 filtered reads were mapped to reference genome for U87, KO_1 and KO_2, respectively. At the mRNA level, a total of 751 and 796 genes were found differentially expressed (DEGs) in U87 versus KO_1 and U87 versus KO_2 groups, respectively (false discovery rate (FDR) ≤0.05 and fold change ≥2) [Supplementary [Table 1][Additional file 1]. Volcano plot analysis of DEGs between groups is shown in [Figure 1]D and [Figure 1]E. Venn diagram of DEGs between two different clones data showed 329 DEGs are common [Figure 1]C, and among them, 306 DEGs have similar up or downregulated trend indicating that our KO and RNA-seq results are reliable [Supplementary [Table 2][Additional file 2]. Of the 306 DEGs, 57 genes were found significantly upregulated, whereas 249 genes were downregulated. Heat-map analysis of common DEGs demonstrated that the expression abundance between KO_1 and KO_2 are almost similar [Figure 1]F. This further indicates the reliability of our KO and RNA-seq results. We, therefore, further analyzed these 306 commonly DEGs.
Figure 1: Overview of transcriptomic data. (A) Western blot analysis of control and KO cell lines. (B) Overview of transcriptomic data analysis. (C) Venn-diagram analysis of DEGs in two knockout cell clones. (D) Volcano plot analysis of DEGs between control and KO_1. (E) Volcano plot analysis of DEGs between control and knock-out 2 (KO_2). (F) Heat-map analysis of common DEGs between two KO cell clones. Each row corresponds to one gene; green and red indicate downregulation and upregulation of corresponding genes, respectively. DEGs: Differentially expressed genes, KO: Knockout

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Functional analysis results of commonly expressed deregulated genes

We employed Enrichr,[17] a comprehensive resource for curated gene sets, and classified the commonly expressed DEGs according to their respective gene ontology (GO) terms. Jensen diseases of Enrichr showed the top 5 diseases related to gene sets are associated with cancer [Figure 2]A. The top 5 GO terms are shown in [Figure 2]B, [Figure 2]C, [Figure 2]D. At the biological process level, commonly expressed DEGs were enriched in extracellular matrix organization and regulation of cell migration [Figure 2]B. Collagen-binding and integrin-binding process among others were mainly enriched at the molecular function level [Figure 2]C. GO analysis of cellular components showed that most of the DEGs are an integral component of the plasma membrane [Figure 2]D. Next, we performed GSEA[18] to identify the hallmark genes in our dataset and the epithelial-mesenchymal transition (EMT) related biological process was found highly downregulated [Figure 2]E. String-based protein–protein interaction between genes associated with EMT depicted that they are highly linked to each other and 4 of them (PDGFRB, THBS1, LAMA2, and COL1A2) are linked with phosphoinoside 3 kinase (PI3K-Akt) signaling pathway [Figure 2]F. Heat-map analysis of EMT related genes showed that they were downregulated in both KO clones and showed a similar level of abundance [Figure 2]G.
Figure 2: Gene Ontology and GSEA of commonly expressed DEGs. (A) Jensen diseases (a web resource that integrates evidence on disease-gene associations from different sources), (B) GO analysis of biological process, (C) GO analysis of molecular function, (D) GO analysis of cellular component of commonly expressed DEGs, (E) GSEA of common DEGs data with hallmark gene sets. (F) String-based protein-protein interaction network of hallmark genes representing epithelial-mesenchymal transition. Color nodes indicate genes related to phosphatidylinositol 3-kinase-Akt signaling pathway. (G) Heat-map of hallmark genes representing epithelial-mesenchymal transition. DEGs: Differentially expressed genes, GO: Gene-ontology, GSEA: Gene-set enrichment analysis

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Pathway analysis results of commonly expressed deregulated genes

To dissect the molecular mechanisms associated with PIK3CD KO in GBM, we further analyzed our commonly expressed DEGs with three different pathway analysis platforms, namely Panther, KEGG, and Wiki pathway. Top 5 significant pathways for each platform are shown in [Figure 3]A, [Figure 3]B, [Figure 3]C, respectively. Analysis of the 306 identified genes revealed integrin, cadherin, Wnt and inflammation mediated by chemokine and cytokine signaling pathways are enriched in the Panther pathway analysis database [Figure 3]A. Whereas both KEGG and Wiki pathway analyses showed PI3K-Akt signaling remain among the top five pathways enriched in our DEGs dataset [Figure 3]B and [Figure 3]C. In fact, all the pathways are related to each other one way or another. Heat-map analysis of PI3K-Akt and integrin signaling related genes showed the most significant differences between parental and KO cell clones [Figure 3]D and [Figure 3]E. All the PI3K-Akt and integrin pathway-related genes in our dataset were downregulated in both KO cell clones except two (CREB3 L3 and PGF) in the PI3K-Akt signaling pathway. Moreover, heat-map analysis of Wnt, cadherin, and inflammation mediated by chemokine and cytokine pathway-related genes showed most of the genes were downregulated in our dataset [Figure 3]F, [Figure 3]G, [Figure 3]H.
Figure 3: Pathway analysis of commonly expressed DEGs indicate variations in expression between control and KO cell clones. (A) Panther pathway analysis, (B) KEGG pathway analysis, (C) Wiki pathway analysis, (D) Heat-map of PI3K-Akt signaling pathway related genes, (E) Heat-map of integrin signaling pathway related genes, (F) Heat-map of Wnt signaling pathway related genes, (G) Heat-map of Cadherin signaling pathway related genes, (H) Heat-map of inflammation mediated by chemokine and cytokine signaling pathway related genes. DEGs: Differentially expressed genes, KEGG: Kyoto Encyclopedia of Genes and Genomes, KO: Knock-out, PI3K: Phosphatidylinositol 3-kinase

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Cross-validation of phosphatidylinositol 3-kinase-Akt-related genes with TCGA dataset

PI3K-Akt signaling pathway plays significant roles in GBM pathogenesis, and activation of this pathway is associated with poor prognosis.[19] Therefore, we further analyzed the impact of PI3K-Akt related genes in our dataset. Literature search of our PI3K-Akt related downregulated genes showed that they are extensively associated with GBM pathogenesis and/or prognosis [Table 1].[20],[21],[22],[23],[24],[25],[26],[27],[28],[29],[30],[31],[32],[33],[34] To determine if changes of PI3K-Akt related gene expression in our dataset are similar to those in the TCGA dataset, we used GEPIA, an interactive web server for analyzing the RNA sequencing expression data.[35] Individual gene expression analysis showed that VWF, FN1, COL1A2, THBS1, LAMA2, KDR, and ITGA6 expression were significantly higher in GBM [Figure 4], all of them were found downregulated in our both KO cell clones. Other PI3K-Akt related downregulated genes (ITGA6, TNXB, PDGFRB, EREG, and COL4A6) in our dataset were also found upregulated in GEPIA but insignificantly. On the other hand, CREB3 L3 expression was upregulated in both GBM and in our dataset [Figure 4]. As we completely knockedout the PIK3CD gene, we further investigated if there is any correlation between PI3K-Akt related genes and PIK3CD. As expected, all the significantly downregulated PI3K-Akt related genes in our dataset have a strong and significant positive correlation with PIK3CD [Figure 5]. By contrast, CREB3 L3 is negatively and significantly correlated with PIK3CD, in completely consistent with our dataset. Taken together, these data identified reduced expression of PI3K-Akt related genes in PIK3CD KO cells suggesting its role in GBM pathogenesis.
Figure 4: Box-plot of key PIK3CD-Akt related genes obtained from published bulk RNAseq data. Number of tumor sample-163, number of control sample-207, match TCGA normal and GTEx data,*P = 0.01

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Figure 5: Scatter-plots between key PIK3CD-Akt related genes and PIK3CD indicate their strong relationship. P value was calculated based on Spearman's correlation coefficient

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  Discussion Top


GBM is the most common and prevalent form of glioma, leading invariably to death. Up to now, no effective treatment has been found for this aggressive cancer. As part of GBM pathogenesis, a number of pathways are deregulated, and among them, PI3K signaling pathway plays a very critical role.[36] However, PI3K catalytic subunits are not functionally dispensable, so determining their specific role in GBM may be an effective strategy to tackle GBM. In this sense, we and others previously reported that PIK3CD takes part in GBM pathogenesis and chemo-resistance.[15],[16] To get a broader view of PIK3CD's role in GBM, we analyzed the gene expression profile of control U87 cells and PIK3CD KO (KO_1 and KO_2) cell clones. Our data showed that KO of PIK3CD influenced gene sets collectively reduce tumor aggressiveness through PI3K-Akt signaling and epithelial to mesenchymal (MES) transition-related processes. To address the off-target issue, we used two KO cell clones and focus on genes that are consistently deregulated in both cell clones.

EMT, a process where tumor cells lose their epithelial characteristics (cell-cell adhesion and polarity) and possess more aggressive MES characteristics, play a significant role in tumor cell migration, invasion, metastasis, and resistance to conventional radio and chemotherapy.[37],[38] The same molecular events are also involved in MES transformation in GBM, leading to increased tumor aggressiveness and acquired drug resistance.[6] Our GSEA analysis demonstrated that a number of genes (PDGFRB, COL5A3, MEST, NID2, OXTR, FN1, COL1A2, LUM, RGS4, THBS1, PMEPA1, LAMA2, and LRRC15) in our dataset are associated with MES transformation and all EMT-related genes were downregulated in our dataset, indicating that on PIK3CD KO, infiltrating and invasion power of GBM are greatly reduced. Among those MES transformation-related genes, PDGFRB, FN1, THBS1, and LAMA2 are extensively studied in GBM and their involvement in GBM are summarized in [Table 1]. Moreover, our GO analysis showed that genes influenced by PIK3CD KO are mostly associated with cell migration, collagen, and integrin binding. Collectively, these data indicate that PIK3CD may control the MES transformation through collagen and integrin binding.
Table 1: Role of PI3K signaling pathway mediated genes in glioblastoma pathogenesis

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We identified at least five pathways by which PIK3CD exerts its effect in GBM and promotes tumor growth. First and most importantly, the expression of the PI3K-Akt signaling pathway-related genes was reduced in both KO cell clones. All the PI3K-Akt-related downregulated genes in our dataset are involved in GBM pathogenesis/prognosis [Table 1]. The involvement of PI3K-Akt pathway is well documented in previous studies.[36],[39] In response to external stimuli, the PI3K-Akt signaling pathway is activated and promotes GBM aggressiveness. Thus, increased activity of PIK3CD promotes tumor cell-external stimuli interaction and therefore enhances invasiveness and protects tumor cells from conventional chemo- and radiotherapy. A second group of transcriptional alterations is related to integrin signaling pathway. Integrin-mediated signaling pathways have been found to promote the invasiveness and survival of GBM cells by enhancing the tumor-stroma interaction.[40] Through activating multiple pathways, integrin molecules influence gene expression leading to tumor dissemination and invasiveness.[39] In this sense, PIK3CD may participate in GBM tumorigenesis by upregulating integrin-mediated interaction with the extracellular matrix and stromal cells as our dataset showed that all the integrin-related genes were downregulated after PIK3CD KO. Our results also demonstrated that Wnt, cadherin, and inflammation mediated by chemokine and cytokine-mediated pathways are greatly decreased on PIK3CD KO, all of which take part in GBM pathogenesis.[40],[41],[42] These data clearly demonstrated that PIK3CD enhances GBM's aggressiveness through regulating tumor interaction with external stimuli and the GBM microenvironment. As GBM is a highly heterogeneous tumor,in vitro cell culture results might not reflect thein vivo scenario. To address this issue, we compared our results with TCGA and found that their data support the conclusions obtained from our dataset.

The results presented here are solely based on bioinformatics analysis and all the data generated here based on one cell line. Hence, further studies with clinical samples, along with robust molecular biology techniques, are needed to confirm PI3KCD's role in GBM.


  Conclusion Top


We have demonstrated that PIK3CD promotes GBM tumorigenesis through enhancing tumor interaction with the GBM microenvironment. Collectively, our results open a new window to selectively target GBM through PIK3CD mediated signaling molecules.

Supplementary Material

Supplementary material is available at Glioma online (http://www.jglioma.com/).

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
 
 
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[Pubmed] | [DOI]



 

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