AKIP1 promotes cell proliferation, invasion, stemness and activates PI3K- Akt, MEK/ERK, mTOR signaling pathways in prostate cancer

Jiabin Zhao The First Afliated Hospital of Harbin Medical University Binjiahui Zhao Harbin Medical University Limin Hou (  [email protected] ) The First Afliated Hospital of Harbin Medical University

Research Article

Keywords: AKIP1, prostate cancer, RNA sequencing, mobility, viability, stemness, prognosis

Posted Date: June 9th, 2021

DOI: https://doi.org/10.21203/rs.3.rs-568302/v1

License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License

Page 1/18 Abstract

Background: The study aimed to examine the molecular mechanism and clinical signifcance of A- interacting protein 1 (AKIP1) in prostate cancer.

Methods: The effect of AKIP1 on cell proliferation, migration, invasion, apoptosis and stemness was determined by overexpressing and knocking down AKIP1 in LNCaP and 22Rv1 cells via lentivirus infection. Furthermore, differentially expressed (DEGs) by AKIP1 modifcation were determined using RNA sequencing. Besides, the correlation of AKIP1 with clinicopathological features and prognosis in 130 prostate cancer patients was assessed.

Results: AKIP1 expression was increased in VCaP, LNCaP, DU145 cells while similar in 22Rv1 cells compared with RWPE-1 cells. Furthermore, AKIP1 overexpression promoted 22Rv1 and LNCaP cell proliferation, invasion, but inhibited apoptosis; meanwhile, AKIP1 overexpression increased CD133+ cell rate and enhanced spheres formation efciency in 22Rv1 and LNCaP cells. Reversely, AKIP1 knockdown exhibited the opposite effect in 22Rv1 and LNCaP cells. Further RNA sequencing analysis exhibited that AKIP1-modifed DEGs were enriched in the oncogenic signaling pathways related to prostate cancer, such as PI3K-Akt, MEK/ERK, mTOR signaling pathways. The following western blot indicated that AKIP1 overexpression activated while its knockdown blocked PI3K-Akt, MEK/ERK, mTOR signaling pathways in prostate cancer cells. Clinically, AKIP1 was upregulated in the prostate tumor tissues compared with paired adjacent tissues, and its tumor high expression correlated with increased pathological T, pathological N stage and poor prognosis in prostate cancer patients.

Conclusion: AKIP1 promotes cell proliferation, invasion, stemness, activates PI3K-Akt, MEK/ERK, mTOR signaling pathways and correlates with worse tumor features and prognosis in prostate cancer.

1 Introduction

Prostate cancer ranks as the second most frequently diagnosed cancer as well as the ffth leading cause of cancer death among males [1–3]. As a highly heterogenous malignancy, the risk factors for prostate cancer including age, endogenous hormone balance, genetic factors and environment factors have been recognized to trigger the initiation and progression of prostate cancer [4, 5]. Owing to the advances in treatment applications, favorable prognosis are available for localized prostate cancer patients, however, for prostate cancer patients with metastasized stage, current therapeutic approaches show little beneft on their survival [6, 7]. Therefore, a deeper understanding of the molecular mechanisms underlying the progression of prostate cancer is essential to identify novel therapeutic targets, which could allow tailored treatment and further improve the clinical outcomes in prostate cancer patients.

A-kinase interacting protein 1 (AKIP1), as a nuclear protein, serves as a molecular determinant of cAMP-dependent protein kinase (PKA) involving in the activation of the NF-kappaB (NF-kB) signaling [8, 9]. Mechanically, AKIP1 is reported to act as a binding protein of NF-kB p65 subunit, and interact with the catalytic subunit of PKA, which augments the transcriptional competence of NF-kB [9]. Recent papers have indicated that AKIP1 is involved in the pathogenesis of several cancers, including hepatocellular carcinoma (HCC), non-small cell lung cancer (NSCLC), esophageal squamous cell carcinoma [8, 10–13]. For example, one study demonstrates that in breast cancer, when AKIP1 is abundant, the PKA signal is promoted to enhance NF-κB - dependent transcriptional activity, which further activate NF-κB-related cell proliferation and anti-apoptotic expressions [8]. In addition, in hepatocellular carcinoma, AKIP1 is upregulated, and its high expression increases the β-catenin induced by catalytic subunit (PKAc)- mediated phosphorylation and promotes the aggressive behaviors mediated by AKT and mTOR activation, contributing to the malignant progression of HCC [10, 11]. Moreover, NF-κB, AKT and mTOR signaling pathways are reported to promote metastasis and invasion of prostate cancer, and their activation is associated with increased resistance to androgen-deprivation therapy in prostate cancer patients [8, 14]. Based on the aforementioned evidence and considering our preliminary study that AKIP1 was upregulated in prostate cancer cells and tissues, we therefore hypothesized that AKIP1 might be involved in the pathology of prostate cancer, while, there was no related research until now.

The present study examined the regulatory role of AKIP1 in prostate cancer cell growth, mobility and stemness via overexpressing and knocking down AKIP1, and subsequently explored RNA profles modifed by AKIP1 via RNA sequencing (RNA-seq) assay in prostate cancer cells. Furthermore, clinical signifcance of AKIP1 was explored by detecting its correlation with clinicopathological features and prognosis in prostate cancer patients.

2 Materials And Methods

2.1 Cell cultureHuman prostate cancer cell lines VCaP, 22Rv1, DU145 and human normal prostate epithelial cell line RWPE-1 were purchased from American Type Cell Collection (ATCC, USA), and human prostate cancer cell line LNCaP was obtained from Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures (DSMZ, Germany). VCaP cells were cultured in Dulbecco's Modifed Eagle Medium (Sigma, USA) supplemented with 10% Fetal Bovine Serum (FBS) (Sigma, USA); LNCaP and 22Rv1 cells were cultured in Roswell Park Memorial Institute (RPMI) 1640 medium (Sigma, USA) supplemented with 10% FBS (Sigma, USA); DU145 cells were cultured in Kaighn's Modifcation of Ham's F-12 Medium (Sigma, USA) supplemented with 10% FBS (Sigma, USA). RWPE-1 cells were cultured in Keratinocyte Serum Free Medium (K-SFM) (Gibco, USA). All cells were maintained in a humidifed atmosphere with 95% air, 5% CO2 at 37℃. All methods were performed in accordance with the relevant guidelines and regulations.

2.2 AKIP1 expression in the cell lines

Page 2/18 Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR) and western blot were performed to detect AKIP1 mRNA and protein expression in the cell lines. 2.3 Lentivirus construction and infection The AKIP1 overexpression (OE-AKIP1) plasmid and negative control (NC) overexpression (OE-NC) plasmid were constructed with pLVEF1a/Puro vector (Hanbio, China). While the AKIP1 short hairpin RNA (shRNA) (Sh-AKIP1) plasmid and NC shRNA (Sh-NC) plasmid were constructed with pHBLV-U6-Puro vector (Hanbio, China). The OE-AKIP1 plasmid, OE-NC plasmid, Sh-AKIP1 plasmid and Sh-NC plasmid were respectively co-transfected into 293T cells (ATCC, USA) along with the packaging vectors (pVSVG-I and pCMVMR8.92) (Hanbio, China) by using HillyMax (Dojindo, Japan) according to the manufacturer’s instructions, and the supernatant was collected 48 hours (h) and 72h later to obtain OE-AKIP1 lentivirus, OE-NC lentivirus, Sh-AKIP1 lentivirus and Sh-NC lentivirus. After the lentivirus infected the 22RV1 cells (MOI = 30) and LNCaP cells (MOI = 35) for 24h, 2 µg/ml puromycin (Sigma, USA) was added to select the stably infected cells. The mRNA and protein expression of AKIP1 were evaluated by RT-qPCR and western blot. 2.4 RT-qPCR

Total RNA was extracted using TRIzol Reagent (Invitrogen, USA), and then reverse-transcribed into cDNA using PrimeScript™ RT Master Mix (Takara, Japan). Following that, RT-qPCR was performed using TB Green™ Fast qPCR Mix (Takara, Japan) to qualify the AKIP1 expression. The data was calculated using the 2−ΔΔCt method and normalized to the internal reference gene β-actin. The primer sequences (5’->3’) were as follows: AKIP1, forward, CCCAACCCTTAGTGCTTCCTTC; reverse, CGACTCGCCTCTGTGATAACG; β-actin, forward, TCGTGCGTGACATTAAGGAGAA; reverse, AGGAAGGAAGGCTGGAAGAGT. 2.5 Western blot

Total protein was extracted using RIPA Lysis Buffer (Sigma, USA) and the protein concentration in each sample was then measured using the Bicinchoninic Acid Kit for Protein Determination (Sigma, USA). Total protein (20 µg/lane) was separated with TruPAGE™ Precast Gels (Sigma, USA) and transferred onto a nitrocellulose membrane (Pall, USA). The membrane was blocked by incubating with the primary antibodies overnight at 4˚C. Following primary antibody incubation, the membrane was incubated with secondary antibodies for 1 h at room temperature. The protein bands were visualized using ECL Plus Western Blotting Substrate (Pierce, USA). The antibodies used in western blot were listed in Supplementary table 1. 2.6 Cell proliferation, apoptosis, migration and invasion assessment

Cell proliferation was assessed by Cell Counting Kit-8 (Dojindo, Japan) following the protocol of the kit. Cell apoptosis was determined using Annexin V Apoptosis Detection Kit (Thermo, USA) in accordance with the procedure of instructions. Wound scratch assay and Transwell assay were performed to evaluate the migration ability and invasion ability according to the methods described in previously study [15, 16]. 2.7 Flow cytometry

CD133 positive (CD133+) cell rate was evaluated with use of fow cytometry. In brief, after being harvested, cells were incubated with CD133 Rabbit mAb (at 1:50 dilution) at room temperature for 30 min. Then, incubation with Alexa Fluor® 488 Conjugated Anti-rabbit IgG (H + L) (at 1:500 dilution) at 37℃ in dark was performed. At last, a fow cytometer (BD, USA) was used to assess the CD133+ cell rate. 2.8 Sphere formation assay DMEM/F12 medium (Sigma, USA) supplemented with 2% B27 (Sigma, USA), 20 ng/ml EGF (Sigma, USA), 20 ng/ml bFGF (Sigma, USA) and 4 ug/ml heparin (Sigma, USA) was used to culture the stably-infected cells for 10 days. The number of cells with the diameter > 50µm was counted. 2.9 RNA-seq

Stably infected 22Rv1 cells (OE-AKIP1 cells, OE-NC cells, Sh-AKIP1 cells, Sh-NC cells) were collected for RNA-sEq. Briefy, after the total RNA was extracted with the application of TRIzol reagent (Invitrogen, USA), the concentration, purity and integrity assessment with Agilent 2100 Bioanalyzer (Agilent, USA) was followed. With the application of the methods described in previous study [17], the RNA-seq library was constructed and sequenced. 2.10 Bioinformatics analysis

The R packages (Version 3.3.3) were used for RNA-seq data analyses and visualization. The raw count of each gene was calculated by featurecount, and the expression normalization and differential expression analysis were performed using DESeq2. The mRNAs with a fold change (FC) ≥ 2.0 and an adjusted P value (BH multiple test correction) < 0.05 were identifed as differentially expressed genes (DEGs) and displayed using Volcano Plots. Cross analysis with Venn Diagram was performed with VennDiagram package, which represent the DEGs in OE-AKIP1 verse (vs.) OE-NC groups and Sh-AKIP1 vs. Sh-NC groups. (GO) and Kyoko Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of gene set, in which the DEGs in OE-AKIP1 vs. OE-NC groups and Sh-AKIP1 vs. Sh-NC groups were expressed in an accordant way, were performed using DAVID web servers [18]. Top 30

DEGs (15 upregulated and 15 downregulated) were selected by the rank of mean absolute value of Log2FC in OE-AKIP1 vs. OE-NC groups and Sh-AKIP1 vs. Sh-NC groups.

2.11 Candidate pathway validation

PI3K/AKT, MEK/ERK and mTOR pathway were selected from KEGG enrichment analysis by the rank of P value. Western blot was performed to detect the expressions of phoso-PI3K (pPI3K), phoso-AKT (pAKT), phoso-MEK1/2 (pMEK1/2), phoso-ERK1/2 (pERK1/2), mTOR and phoso-S6 (pS6) in 22RV1 cells and LNCaP cells.2.12 Patients and specimensA total of 130 prostate cancer patients underwent resection in The First Afliated Hospital of Harbin Medical University between January 2015 and December 2019 were retrospectively reviewed in this study. All patients were aged 18–80 years, newly conformed as primary prostate cancer by histopathology, received resection treatment, had available tumor tissue and paired adjacent tissue, and had

Page 3/18 complete clinical data. Patients had history of neoadjuvant therapy or had history of other cancers were excluded. A total of 130 prostate cancer tumor specimens and 130 paired adjacent specimens were collected from the Pathology Department of The First Afliated Hospital of Harbin Medical University, which were fxed by formalin and embedded by parafn. Besides, prostate cancer patients’ clinical features including age, pathological T stage, pathological N stage, Gleason score, prostate-specifc antigen (PSA) level, and surgical margin status were acquired from electronic medical record. The disease status and survival status of patients was acquired from follow-up data. The use of patients’ specimens and data for this study were approved by Institutional Review Board of The First Afliated Hospital of Harbin Medical University, and informed consents were collected from patients or their family members.

2.13 Immunohistochemistry (IHC) assay

The expression of AKIP1 in tumor tissue specimens and paired adjacent tissue specimens was detected using IHC assay. Briefy, all tissue specimens were cut into 4 µm slices, then the tissue slices were processed with deparafnation, rehydration and antigen retrieval. Afterwards, the endogenous peroxidase activity of the tissue slices was blocked with the use of H2O2 (Sigma-Aldrich, USA), and nonspecifc binding was prevented using 10% normal goat serum (Sigma-Aldrich, USA). Subsequently, the tissue slices were incubated with Rabbit Anti-C11orf17 antibody (1:100; Abcam, USA) at 4℃ overnight, followed by incubation with Goat Anti-Rabbit IgG H&L (HRP) antibody (1:10000; Abcam, USA) at 37℃ for 60 min. Finally, the tissue slices were stained with diaminobenzidine (DAB) (Dako, USA) and counterstained with hematoxylin (Sigma-Aldrich, USA). The staining results were viewed on a microscope (Leica, Germany) and assessed using a semi-quantitative scoring method [19]. According to the total IHC score, AKIP1 expression was classifed as high expression (total IHC score > 3) or low expression (total IHC score ≤ 3) [19].

2.14 Statistical analysis

SPSS software version 24.0 (IBM, USA) and GraphPad Prism Software version 7.01 (GraphPad Software Inc., USA) were used for data analysis and graph plotting, respectively. All data were expressed as mean ± standard deviation (SD) or count (percentage). One-way analysis of variance (ANOVA) followed by Dunnett's multiple comparisons test was used to determine comparisons among cell groups. Unpaired t test was used to demine the comparison between two cell groups. McNemar’s test was used to demine the comparison between tumor tissue and paired adjacent tissue. Spearman’s rank correlation test was used to analyze the correlation between tumor AKIP1 expression and clinical features. Disease-free survival (DFS) was calculated from surgery to disease relapse, disease progression or death. Overall survival (OS) was calculated from surgery to death. For the patients who lost follow-up before occurrence of disease relapse, disease progression or death, they were censored at the last recorded date. Kaplan–Meier curves were plotted to illustrate DFS and OS, and the differences of DFS and OS between tumor AKIP1 high expression patients and tumor AKIP1 low expression patients were determined by Log-rank test. P < 0.05 was considered as statistically signifcant. For the fgures of in vitro experiments, P > 0.05, P < 0.05, P < 0.01 and P < 0.001 were marked as non-signifcant (NS), *, ** and ***, respectively.

3 Results

3.1 Comparison of AKIP1 expression between human prostate cancer cells and normal prostate epithelial cells

AKIP1 mRNA relative expression was higher in VCaP (P < 0.05), LNCaP (P < 0.001), DU145 cells (P < 0.01) but similar in 22Rv1 cells (P > 0.05) compared with RWPE-1 cells (Fig. 1A). Furthermore, AKIP1 protein expression presented the similar trend as its mRNA expression in each-group cells (Fig. 1B). As the relatively highest AKIP1 expression was shown in LNCaP cell line and its lowest expression was displayed in 22Rv1 cell line among total human prostate cancer cell lines, therefore, these two cell lines were chosen for the following interventional experiments. 3.2 Construction of AKIP1-modifed stably-infected prostate cancer cells

In 22Rv1 cells, AKIP1 mRNA and protein expressions were increased in OE-AKIP1 group compared with OE-NC group; meanwhile, they were decreased in Sh-AKIP1 group compared with Sh-NC group (Fig. 2A, 2B). Furthermore, in LNCaP cells, AKIP1 mRNA and protein expressions were higher in OE-AKIP1 group compared with OE-NC group; additionally, they were reduced in Sh-AKIP1 group compared with Sh-NC group (Fig. 2C, 2D). These data indicated the successful construction of AKIP1-modifed stably-infected prostate cancer cells. 3.3 Effect of AKIP1 on prostate cancer cell proliferation and apoptosis

In 22Rv1 cells, cell proliferation was increased in OE-AKIP1 group compared with OE-NC group at 48h (P < 0.05) and 72h (P < 0.05), but was decreased in Sh-AKIP1 group compared with Sh-NC group at 72 h (P < 0.05) (Fig. 3A); cell apoptosis was reduced in OE-AKIP1 group compared with OE-NC group (P < 0.05) but was enhanced in Sh-AKIP1 group compared with Sh-NC group (P < 0.05) (Fig. 3B, 3C). In addition, in LNCaP cells, cell proliferation was enhanced in OE-AKIP1 group compared with OE-NC group at 72h (P < 0.05), while was reduced in Sh-AKIP1 group compared with Sh-NC group at 48h (P < 0.05) and 72h (P < 0.05) (Fig. 3D); cell apoptosis was similar between OE-AKIP1 group and OE-NC group, but was increased in Sh-AKIP1 group compared with Sh-NC group (P < 0.01) (Fig. 3E, 3F). These data implied that AKIP1 promoted proliferation but inhibited apoptosis of prostate cancer cells. 3.4 Effect of AKIP1 on prostate cancer cell migration and invasion

In both 22Rv1 (Fig. 4A, 4B) and LNCaP (Fig. 4C, 4D) cells, cell migration was similar between OE-AKIP1 group and OE-NC group, as well as between Sh- AKIP1 group and Sh-NC group (all P > 0.05). Furthermore, in both 22Rv1 (Fig. 5A, 5B) and LNCaP (Fig. 5C, 5D) cells, invasive cell number was increased in

Page 4/18 OE-AKIP1 group compared with OE-NC group, but was decreased in Sh-AKIP1 group compared with Sh-NC group (all P < 0.05). These fndings suggested that AKIP1 promoted invasion but had no effect on migration of prostate cancer cells. 3.5 Effect of AKIP1 on prostate cancer cell stemness

In 22Rv1 cells, CD133+ cell rate was increased in OE-AKIP1 group compared with OE-NC group (P < 0.05), but was decreased in Sh-AKIP1 group compared with Sh-NC group (P < 0.05) (Fig. 6A, 6B); the sphere formation ability was also increased in OE-AKIP1 group compared with OE-NC group (P < 0.05), while was similar between Sh-AKIP1 group and Sh-NC group (P > 0.05) (Fig. 6C). In LNCaP cells, CD133+ cell rate was higher in OE-AKIP1 group compared with OE-NC group (P < 0.01), but was reduced in Sh-AKIP1 group compared with Sh-NC group (P < 0.01) (Fig. 6D, 6E); Sphere formation ability was higher in OE-AKIP1 group compared with OE-NC group (P < 0.05), while was also lower in Sh-AKIP1 group compared with Sh-NC group (P < 0.05) (Fig. 6F). There data implied that AKIP1 promoted stemness of prostate cancer cells. 3.6 DEGs by AKIP1 modifcation in prostate cancer cells

RNA-seq assay was conducted following the construction of AKIP1-modifed stably-infected 22Rv1 cells. The volcano plots exhibited that 640 upregulated and 901 downregulated DEGs were identifed in the OE-AKIP1 group compared with OE-NC group, respectively (Fig. 7A). Meanwhile, 658 upregulated and 579 downregulated DEGs were identifed in the Sh-AKIP1 group compared with Sh-NC group, respectively (Fig. 7B). Cross analysis with Venn Diagram was performed to indicate the overlapping patterns of these DEGs in OE-AKIP1 vs. OE-NC groups and Sh-AKIP1 vs. Sh-NC groups (Fig. 7C). Totally, 147 consistent DEGs were upregulated in the OE-AKIP1 groups (vs. OE-NC groups) and downregulated in the Sh-AKIP1 groups (vs. Sh-NC groups); 205 consistent DEGs were downregulated in the OE-AKIP1 groups (vs. OE-NC groups) and upregulated in the Sh-AKIP1 groups (vs. Sh-NC groups). Furthermore, the number of consistent DEGs was much more than the number of inconsistent DEGs, suggesting the internal consistency. The information of top 60 accordant DEGs by AKIP1 modifcation was shown in Table 1.

Page 5/18 Table 1 Top 60 accordant DEGs by RNA-seq. Gene ID Symbol OE-AKIP1 vs. OE-NC Sh-AKIP1 vs. Sh-NC Mean ABS log2FC log2FC P value Padj Trend log2FC P value Padj Trend value value

ENSG00000196090 PTPRT -5.8088 1.7E-13 4.73E-12 DOWN 4.308355 3.54E-29 1.39E-26 UP 5.058578304

ENSG00000183760 PAPL -5.75194 2.61E-17 1.06E-15 DOWN 3.532459 6.81E-12 2.79E-10 UP 4.64220089

ENSG00000184599 FAM19A3 -4.98053 7.46E-27 6.6E-25 DOWN 3.218765 1.04E-12 4.77E-11 UP 4.099646174

ENSG00000101096 NFATC2 -4.37853 0.001799 0.007876 DOWN 3.807821 0.00687 0.027691 UP 4.093174596

ENSG00000124882 EREG -3.61689 1.22E-08 1.7E-07 DOWN 4.483705 6.83E-13 3.21E-11 UP 4.050298181

ENSG00000135437 RDH5 -3.99148 2.24E-28 2.34E-26 DOWN 3.469189 1.52E-18 1.68E-16 UP 3.730335199

ENSG00000070193 FGF10 -4.35677 1.47E-09 2.29E-08 DOWN 3.001614 4.34E-09 1.02E-07 UP 3.679189488

ENSG00000168546 GFRA2 -1.92686 0.01557 0.047879 DOWN 5.343486 1.43E-11 5.57E-10 UP 3.635171166

ENSG00000110786 PTPN5 -4.22945 9.18E-09 1.3E-07 DOWN 3.024552 1.23E-06 1.68E-05 UP 3.627001296

ENSG00000050555 LAMC3 -5.02506 2.41E-23 1.69E-21 DOWN 2.161219 1.51E-13 7.86E-12 UP 3.593141533

ENSG00000158089 GALNT14 -2.86665 0.000212 0.001228 DOWN 4.297297 8.48E-07 1.21E-05 UP 3.581975403

ENSG00000182870 GALNT9 -5.90731 5.37E-20 2.8E-18 DOWN 1.227376 0.009828 0.037124 UP 3.567343259

ENSG00000137441 FGFBP2 -4.62698 2.13E-05 0.000157 DOWN 2.431035 0.000821 0.004824 UP 3.529005029

ENSG00000196353 CPNE4 -5.61326 4.33E-12 1.01E-10 DOWN 1.404041 0.001154 0.00646 UP 3.508648407

ENSG00000113494 PRLR -3.10167 2.18E-20 1.19E-18 DOWN 3.887881 3.07E-11 1.1E-09 UP 3.494775843

ENSG00000135333 EPHA7 -3.10256 1.56E-07 1.76E-06 DOWN 3.876892 2.34E-16 1.91E-14 UP 3.489726991

ENSG00000066248 NGEF -5.32309 6.03E-11 1.21E-09 DOWN 1.564991 0.002399 0.011714 UP 3.444040197

ENSG00000164283 ESM1 -3.79475 2.3E-19 1.13E-17 DOWN 3.068701 1.05E-07 1.84E-06 UP 3.431726056

ENSG00000175513 TSGA10IP -4.05487 3.94E-07 4.14E-06 DOWN 2.76025 0.000117 0.000899 UP 3.407560439

ENSG00000014257 ACPP -3.7599 4.2E-20 2.24E-18 DOWN 3.000254 6.38E-16 4.86E-14 UP 3.380076785

ENSG00000112562 SMOC2 -2.64455 2.88E-08 3.74E-07 DOWN 4.115201 8.75E-19 1.02E-16 UP 3.379872928

ENSG00000115919 KYNU -5.41641 2.36E-22 1.52E-20 DOWN 1.283852 0.003992 0.017849 UP 3.350131839

ENSG00000101187 SLCO4A1 -4.18817 3.4E-07 3.6E-06 DOWN 2.509989 0.001011 0.005779 UP 3.349077466

ENSG00000148798 INA -3.05591 1.97E-23 1.4E-21 DOWN 3.38917 2.74E-28 9.85E-26 UP 3.222541174

ENSG00000073756 PTGS2 -3.13866 4.11E-06 3.52E-05 DOWN 3.293855 1.55E-06 2.06E-05 UP 3.216258637

ENSG00000095752 IL11 -2.36059 0.00363 0.0143 DOWN 4.037497 1.12E-06 1.55E-05 UP 3.199045049

ENSG00000157766 ACAN -3.58972 1.92E-08 2.57E-07 DOWN 2.795004 1.55E-08 3.21E-07 UP 3.192364439

ENSG00000108551 RASD1 -2.55728 6.83E-05 0.000447 DOWN 3.770871 4.27E-09 1.01E-07 UP 3.16407515

ENSG00000165269 AQP7 -4.58797 6.38E-06 5.27E-05 DOWN 1.664234 0.00504 0.021576 UP 3.126103103

ENSG00000114757 PEX5L -3.3325 7.11E-10 1.18E-08 DOWN 2.792627 2.72E-09 6.77E-08 UP 3.062563263

ENSG00000171791 BCL2 3.156693 0.000233 0.001333 UP -5.55402 1.18E-10 3.8E-09 DOWN 4.355356509

ENSG00000198793 MTOR 3.971844 4.37E-05 0.0003 UP -4.38733 3.52E-06 4.28E-05 DOWN 4.179586785

ENSG00000138449 SLC40A1 4.656144 1.11E-09 1.78E-08 UP -3.60843 1.34E-06 1.81E-05 DOWN 4.132286285

ENSG00000099953 MMP11 4.946335 6.7E-20 3.44E-18 UP -3.08185 8.47E-09 1.85E-07 DOWN 4.014090237

ENSG00000094963 FMO2 3.961277 0.001625 0.00722 UP -4.02253 0.000523 0.00331 DOWN 3.991902111

ENSG00000160097 FNDC5 3.617972 5.67E-09 8.33E-08 UP -4.048 6.89E-13 3.23E-11 DOWN 3.832988105

ENSG00000104365 IKBKB 2.105272 0.015495 0.0477 UP -5.32721 1.05E-09 2.87E-08 DOWN 3.716239106

DEGs, differentially expressing genes; RNA-seq, RNA sequencing; ID, identifcation; NC, negative control; OE, overexpression; FC, fold change; Sh, short hairpin; ABS, absolute.

Page 6/18 Gene ID Symbol OE-AKIP1 vs. OE-NC Sh-AKIP1 vs. Sh-NC Mean ABS log2FC log2FC P value Padj Trend log2FC P value Padj Trend value value

ENSG00000018408 WWTR1 2.335813 0.00585 0.021366 UP -4.61295 1.36E-07 2.32E-06 DOWN 3.474380003

ENSG00000103811 CTSH 3.008323 0.000242 0.001378 UP -3.52146 7.95E-06 8.83E-05 DOWN 3.264892157

ENSG00000152583 SPARCL1 4.273809 8.01E-11 1.57E-09 UP -2.1997 0.000314 0.002125 DOWN 3.236756377

ENSG00000206384 COL6A6 2.647055 0.000466 0.002447 UP -3.7219 6.01E-07 8.85E-06 DOWN 3.184478389

ENSG00000149294 NCAM1 2.423713 1.12E-06 1.08E-05 UP -3.9302 9.29E-15 5.78E-13 DOWN 3.176954074

ENSG00000111371 SLC38A1 4.140028 6.62E-27 5.9E-25 UP -2.18426 6.44E-09 1.44E-07 DOWN 3.162143568

ENSG00000128606 LRRC17 3.409145 1.68E-18 7.61E-17 UP -2.73535 7.61E-14 4.12E-12 DOWN 3.072247404

ENSG00000176595 KBTBD11 4.004241 2.03E-09 3.11E-08 UP -2.04505 0.000353 0.002355 DOWN 3.024645613

ENSG00000109265 KIAA1211 2.997062 7.05E-05 0.000458 UP -2.97613 3.15E-06 3.86E-05 DOWN 2.986595641

ENSG00000145819 ARHGAP26 2.909441 6.23E-16 2.2E-14 UP -3.00239 4.06E-18 4.35E-16 DOWN 2.955915446

ENSG00000175183 CSRP2 2.759614 0.002554 0.010553 UP -3.13926 0.000666 0.004044 DOWN 2.949439731

ENSG00000111348 ARHGDIB 1.890709 0.004766 0.017912 UP -3.87587 2.48E-13 1.24E-11 DOWN 2.883290121

ENSG00000153993 SEMA3D 3.970096 4.36E-18 1.91E-16 UP -1.7425 4.17E-08 8E-07 DOWN 2.85629688

ENSG00000105989 WNT2 3.827113 1.34E-26 1.16E-24 UP -1.80581 1.71E-07 2.84E-06 DOWN 2.81646125

ENSG00000048540 LMO3 2.184586 0.002035 0.008759 UP -3.42649 1.36E-06 1.84E-05 DOWN 2.805539206

ENSG00000167191 GPRC5B 2.487935 0.004859 0.01823 UP -3.03667 0.000579 0.003586 DOWN 2.762302513

ENSG00000170293 CMTM8 3.578718 4.32E-10 7.52E-09 UP -1.64145 0.002853 0.013473 DOWN 2.610083571

ENSG00000126861 OMG 2.317496 0.000896 0.004325 UP -2.7749 1.34E-06 1.81E-05 DOWN 2.546196714

ENSG00000196208 GREB1 2.811484 1.08E-05 8.45E-05 UP -2.05357 0.000299 0.002042 DOWN 2.432526389

ENSG00000138131 LOXL4 3.120827 7.79E-22 4.8E-20 UP -1.73393 8.57E-08 1.53E-06 DOWN 2.427378451

ENSG00000148082 SHC3 2.200171 1.91E-12 4.7E-11 UP -2.55069 5.24E-16 4.04E-14 DOWN 2.375428198

ENSG00000174775 HRAS 2.098945 8.56E-17 3.33E-15 UP -2.63583 5.39E-25 1.33E-22 DOWN 2.367389118

ENSG00000102882 MAPK3 3.56455 3.6E-27 3.31E-25 UP -1.1644 0.000181 0.00132 DOWN 2.364473833

DEGs, differentially expressing genes; RNA-seq, RNA sequencing; ID, identifcation; NC, negative control; OE, overexpression; FC, fold change; Sh, short hairpin; ABS, absolute.

3.7 Related signaling pathways by AKIP1 modifcation in prostate cancer cells

The accordant DEGs were enriched in the biological process (including positive regulation of transcription, cell proliferation, etc.), cellular component (including plasma membrane, extracellular region, etc.) and molecular function (including protein kinase binding, specifc DNA binding, etc.) (Fig. 8A). Notably, the accordant DEGs were enriched in oncogenic signaling pathways related to prostate cancer (such as PI3K-Akt signaling pathway, MEK/ERK signaling pathway, mTOR signaling pathway, etc.) (Fig. 8B). More detailed information of top 30 pathways that accordant DEGs were enriched in were presented in Table 2.

Page 7/18 Table 2 Top 30 pathways of KEGG enrichment with accordant DEGs Pathway Number Proportion of Symbols Fold P value of symbols enrichment symbols

Prostate cancer 20 0.12195122 CHUK, EP300, ERBB2, FOXO1, MTOR, HRAS, HSP90AB1, IGF1R, 9.6916964 6.1399E-14 IKBKB, PDPK1, MAPK3, MAP2K2, RB1, BCL2, SOS1, BRAF, TCF7L2, TCF7L1, CCNE2, CREB5

PI3K-Akt 28 0.170731707 LAMC3, CHUK, COL1A1, COL6A6, FGF10, FGFR4, LPAR3, SGK3, 3.5309514 1.2695E-08 signaling MTOR, HRAS, HSP90AB1, TNC, IGF1R, IKBKB, IL6R, ITGB8, MYC, pathway PCK2, PDPK1, MAPK3, MAP2K2, PRLR, BCL2, SOS1, THBS2, TNXB, CCNE2, CREB5

Pathways in 30 0.182926829 LAMC3, ADCY8, CHUK, ADCY4, EP300, ERBB2, ETS1, FGF10, FOXO1, 3.2590465 1.9924E-08 cancer LPAR3, MTOR, HRAS, HSP90AB1, IGF1R, IKBKB, MMP1, MYC, MAPK3, MAP2K2, PTGER2, PTGS2, RB1, BCL2, SOS1, BRAF, TCF7L2, WNT2, WNT5B, TCF7L1, CCNE2

EGFR tyrosine 13 0.079268293 ERBB2, MTOR, NRG1, HRAS, IGF1R, IL6R, SHC3, MAPK3, MAP2K2, 6.9217856 2.3262E-07 kinase inhibitor BCL2, SOS1, BRAF, NRG2 resistance

Acute myeloid 11 0.067073171 CHUK, MTOR, HRAS, IKBKB, MYC, MAPK3, MAP2K2, SOS1, BRAF, 8.3229568 4.5865E-07 leukemia TCF7L2, TCF7L1 mTOR signaling 12 0.073170732 CHUK, MTOR, HRAS, IGF1R, IKBKB, PDPK1, MAPK3, MAP2K2, SOS1, 3.3825921 7.301E-07 pathway BRAF, WNT2, WNT5B

MAPK signaling 15 0.091463415 CHUK, DUSP5, FGF10, FGFR4, HRAS, HSPA2, IKBKB, MYC, MAPK3, 2.536944 7.301E-07 pathway MAP2K2, MAP2K3, SOS1, BRAF, PTPN5, CACNA1G

Endometrial 10 0.06097561 ERBB2, HRAS, MYC, PDPK1, MAPK3, MAP2K2, SOS1, BRAF, TCF7L2, 8.2938555 1.9531E-06 cancer TCF7L1

ErbB signaling 12 0.073170732 ERBB2, EREG, MTOR, NRG1, HRAS, MYC, SHC3, MAPK3, MAP2K2, 5.8810976 4.2919E-06 pathway SOS1, BRAF, NRG2

FoxO signaling 14 0.085365854 KLF2, CHUK, EP300, FOXO1, SGK3, HRAS, IGF1R, IKBKB, PCK2, 4.5059155 1.0445E-05 pathway PDPK1, MAPK3, MAP2K2, SOS1, BRAF

Bladder cancer 8 0.048780488 ERBB2, HRAS, MMP1, MYC, MAPK3, MAP2K2, RB1, BRAF 8.415229 2.9849E-05

Non-small cell 9 0.054878049 ERBB2, ALK, HRAS, PDPK1, MAPK3, MAP2K2, RB1, SOS1, BRAF 6.9312936 3.2495E-05 lung cancer

Thyroid cancer 7 0.042682927 HRAS, MYC, MAPK3, MAP2K2, BRAF, TCF7L2, TCF7L1 10.410219 3.3827E-05

Chronic myeloid 10 0.06097561 CHUK, HRAS, IKBKB, MYC, SHC3, MAPK3, MAP2K2, RB1, SOS1, BRAF 5.9079519 3.6112E-05 leukemia

Focal adhesion 16 0.097560976 LAMC3, COL1A1, COL6A6, ERBB2, HRAS, TNC, IGF1R, ITGB8, PDPK1, 3.3992551 5.9059E-05 SHC3, MAPK3, BCL2, SOS1, BRAF, THBS2, TNXB

Glioma 9 0.054878049 MTOR, HRAS, IGF1R, SHC3, MAPK3, MAP2K2, RB1, SOS1, BRAF 5.971576 9.9072E-05

Hepatitis B 13 0.079268293 CHUK, EGR3, EP300, HRAS, IKBKB, MYC, NFATC2, MAPK3, MAP2K2, 3.8401687 0.00011948 RB1, BCL2, CCNE2, CREB5

Axon guidance 14 0.085365854 EPHA7, EPHB1, SEMA3D, NTNG1, NGEF, HRAS, NFATC2, PLXNB3, 3.4306402 0.00018591 MAPK3, RGS3, SEMA3F, WNT5B, PLXNA4, NTN1

Insulin signaling 12 0.073170732 FOXO1, MTOR, HRAS, IKBKB, PCK2, PDPK1, SHC3, PPP1R3C, MAPK3, 3.7232848 0.00032023 pathway MAP2K2, SOS1, BRAF

Estrogen 10 0.06097561 ADCY8, ADCY4, HRAS, HSPA2, HSP90AB1, SHC3, MAPK3, MAP2K2, 4.3563686 0.00040045 signaling SOS1, CREB5 pathway

Melanogenesis 10 0.06097561 ADCY8, ADCY4, EP300, HRAS, MAPK3, MAP2K2, TCF7L2, WNT2, 4.3128049 0.00043194 WNT5B, TCF7L1

Neurotrophin 10 0.06097561 HRAS, IKBKB, ARHGDIB, PDPK1, SHC3, MAPK3, MAP2K2, BCL2, 3.5940041 0.00163109 signaling SOS1, BRAF pathway

Ras signaling 14 0.085365854 CHUK, ETS1, FGF10, FGFR4, HRAS, HTR7, IGF1R, IKBKB, SHC3, 2.6482135 0.00216202 pathway MAPK3, MAP2K2, SOS1, RIN1, RAPGEF5

Proteoglycans in 13 0.079268293 ERBB2, MTOR, HRAS, IGF1R, MYC, PDPK1, PLAUR, MAPK3, MAP2K2, 2.7349494 0.0025552 cancer SOS1, BRAF, WNT2, WNT5B

KEGG, Kyoko Encyclopedia of Genes and Genomes; DEGs, differentially expressing genes.

Page 8/18 Pathway Number Proportion of Symbols Fold P value of symbols enrichment symbols

Longevity 7 0.042682927 ADCY8, ADCY4, FOXO1, MTOR, HRAS, HSPA2, IGF1R 4.7171303 0.00313872 regulating pathway - multiple species

Rap1 signaling 13 0.079268293 ADCY8, ADCY4, FGF10, FGFR4, LPAR3, HRAS, IGF1R, MAPK3, 2.6571784 0.00324367 pathway MAP2K2, MAP2K3, SIPA1L2, BRAF, RAPGEF5

Jak-STAT 11 0.067073171 EP300, MTOR, HRAS, IL6R, IL11, MYC, IL20RB, PRLR, BCL2, SOS1, 3.0025857 0.00327791 signaling TSLP pathway

Small cell lung 8 0.048780488 LAMC3, CHUK, IKBKB, MYC, PTGS2, RB1, BCL2, CCNE2 4.0119115 0.00332085 cancer

Insulin 9 0.054878049 PPARGC1B, FOXO1, MTOR, IKBKB, PCK2, PDPK1, PPP1R3C, TRIB3, 3.5610316 0.00334879 resistance CREB5

Renal cell 7 0.042682927 EP300, ETS1, HRAS, MAPK3, MAP2K2, SOS1, BRAF 4.5059155 0.00396637 carcinoma

KEGG, Kyoko Encyclopedia of Genes and Genomes; DEGs, differentially expressing genes.

3.8 Validation of AKIP1 effect on PI3K/AKT, MEK/ERK and mTOR signaling pathways

Three oncogenic candidate signaling pathways (PI3K/AKT, MEK/ERK and mTOR signaling pathway) were selected according to the results of the KEGG enrichment analysis. The following western blot was performed to detect the effect of AKIP1 overexpression and knockdown on PI3K/AKT, MEK/ERK and mTOR signaling pathway in 22Rv1 and LNCaP cells, which exhibited that pPI3K, pAKT, pMEK1/2, pERK1/2, mTOR, pS6 protein expressions were higher in OE-AKIP1 group compared with OE-NC group, while were lower in Sh-AKIP1 group compared with Sh-NC group in both of 22Rv1 (Fig. 9A) and LNCaP cells (Fig. 9B). These data suggested that AKIP1 could activate PI3K/AKT, MEK/ERK and mTOR signaling pathway in prostate cancer cells. 3.9 AKIP1 expression in prostate patients

In order to assess the clinical application of AKIP1 in prostate cancer patients, we further detected AKIP1 expression in tumor tissue and adjacent tissue of prostate cancer patients by IHC staining, with their clinical features shown in Table 3. Representative IHC staining images of AKIP1 high expression and low expression in adjacent tissue and prostate tumor tissue were shown in Fig. 10A. Further comparison indicated that AKIP1 expression was increased in tumor tissues compared with adjacent tissues (P < 0.001) (Fig. 10B).

Page 9/18 Table 3 Clinical features of prostate cancer patients Items Prostate cancer patients (N = 130)

Age (years), mean ± SD 62.2 ± 8.9

Pathological T stage, No. (%)

pT2a 42 (32.3)

pT2b 20 (15.4)

pT2c 21 (16.2)

pT3a 23 (17.7)

pT3b 22 (16.9)

pT4 2 (1.5)

Pathological N stage, No. (%)

pN0 95 (73.1)

pN1 35 (26.9)

Gleason score, No. (%)

≤ 6 26 (20.0)

7 77 (59.2)

≥ 8 27 (20.8)

PSA level, No. (%)

≤ 10 ng/mL 26 (20.0)

10–20 ng/mL 72 (55.4)

≥ 20 ng/mL 32 (24.6)

Surgical margin status, No. (%)

Negative 105 (80.8)

Positive 25 (19.2)

SD, standard deviation; PSA, prostate-specifc antigen.

3.10 Correlation of tumor AKIP1 expression with clinicopathological features and survival in prostate cancer patients

Tumor AKIP1 high expression was correlated with increased pathological T stage (P = 0.006) (Fig. 11B), pathological N stage (P = 0.015) (Fig. 11C), however, there was no correlation of AKIP1 expression with age (P = 0.190) (Fig. 11A), PSA level (P = 0.327) (Fig. 11D), Gleason score (P = 0.073) (Fig. 11E) or surgical margin status (P = 1.000) (Fig. 11F) in prostate patients. Furthermore, tumor AKIP1 expression was negatively associated with DFS (P = 0.047) (Fig. 12A), while there was no correlation of tumor AKIP1 expression with OS (P = 0.088) (Fig. 12B) in prostate cancer patients.

4 Discussion

AKIP1 is of critical physiological value in the nuclear translocation of p65 and further NF-kB transcription, therefore, with the regard to the role of AKIP1 in the activation of NF-κB signaling, AKIP1 is claimed to be involved in the NF-κB-mediated immune and infammatory responses, cell proliferation, survival, and have regulatory effect on the pathogenesis of diverse type of cancers [9–13]. For example, cellular experiments exhibit that AKIP1 is upregulated and promotes HCC cell invasion and colony outgrowth, and further in animal model of HCC, AKIP1 promotes intrahepatic and lung metastasis via mediating AKT, mTOR and NF-κB signal pathways, suggesting the regulator of AKIP1 in the metastatic progression of HCC [10, 11]. Another study reveals that, in nude mouse xenograft model of cervical cancer, tumor growth and angiogenesis is suppressed by implanting the cells transfected with AKIP1 knockdown plasmids, and meanwhile, cellular experiments reveal that AKIP1-induced chemokines promote cell proliferation via regulating NF- kB kinase subunit β [20]. In addition, AKIP1 transactivates Zinc Finger E-box binding homeobox 1 (ZEB1) expression, and results in the promotion effect of epithelial-mesenchymal transition, further promoting NSCLC cell migration and invasion [21]. As for the implication of AKIP1 in the prostate cancer, only

Page 10/18 one clinical study indicates that AKIP1 is correlated with advanced pathological stage and survival in patients with prostate cancer, however, the underlying mechanism of AKIP1 in prostate cancer progression is uncovered, which was explored in the present study [22].

In our present study, we found that AKIP1 was upregulated in prostate cancer cells compared with normal prostate epithelial cells. The possible reason might include that: according to the prior study, AKIP1 might promote the nuclear preservation and phosphorylation of NF-kB p65 subunit, further activating NF-κB signaling pathway and promoting the onset of prostate cancer, therefore, AKIP1 was upregulated in prostate cancer cells [8, 9]. Following that, we observed that AKIP1 promoted proliferation and invasion, but inhibited apoptosis of LNCaP and 22Rv1 cells. The possible reason might be as follows: considering the crosstalk of NF-κB signaling with several oncogenic signaling pathways (such as AKT, mTOR, MEK-ERK signaling pathways), AKIP1 might activate these NF-κB-dependent oncogenic signaling pathways, and further trigger aggressive proliferation, invasion of prostate cancer cells, which was further explored by the following RNA seq analysis [11, 23, 24]. In addition, we also observed that AKIP1 increased the common cancer stem cell markers (CD133+) cell rate and enhanced the sphere formation ability in LNCaP and 22Rv1 cells. The possible reasons might involve that (1) according to the prior study, β-catenin was a key role implicated in the cell viability, adhesion as well as motility, and integrated multiple signaling pathways which led to the generation of cancer stem cell traits, and meanwhile, AKIP1 was reported to regulate the stimulation of β-catenin, therefore, AKIP1 might activated β-catenin-induced stemness in prostate cancer [10, 25]. (2) In addition, AKIP1 might increase the expressions of mesenchymal markers and decrease the expressions of epithelial markers to promote epithelial-mesenchymal transition like that in NSCLC, which thereby contributed to cancer stem cell properties in prostate cancer [21, 26].

With the purpose to explore the potential molecular mechanism of AKIP1 in prostate cancer progression, an RNA seq analysis was performed to identify DEGs by AKIP1 modifcation in stably-infected prostate cancer cells, which revealed that 147 accordant DEGs were upregulated by AKIP1 overexpression and downregulated by AKIP1 knockdown, respectively; meanwhile, 205 accordant DEGs were downregulated by AKIP1 overexpression and upregulated by AKIP1 knockdown, respectively. The following enrichment analysis indicated that these accordant DEGs were enriched in oncogenic signaling pathways related to prostate cancer (PI3K/AKT, MEK/ERK and mTOR signaling pathway), which was verifed by further western blot assay. The possible reasons might include that (1) These DEGs might activate the transcription of their targeted genes, which served as the stimulator on the PI3K/AKT, MEK/ERK and mTOR signaling pathway, further activating these oncogenic pathways and facilitating the progression of prostate cancer. (2) Some upregulating DEGs (such as BCL-2, MTOR, MAPK3) might serve as the stimulators of PI3K/AKT, MEK/ERK and mTOR pathway, therefore, AKIP1 high expression might activate DEG-mediated PI3K/AKT, MEK/ERK and mTOR signaling pathways in prostate cancer. (3) These DEGs might lead to the activation of IκB kinase complex, which functioned as the intermediary between Akt and NF-kB, further stimulating the NF-kB-mediated PI3K/AKT/mTOR as well as MEK/ERK signaling pathways, and triggering prostate cancer growth and metastasis [27, 28].

Existing papers have demonstrated the correlation of AKIP1 with advanced tumor properties and unfavorable prognosis in several cancers [10–13, 20]. For example, one study reports that increased AKIP1 expression is observed in HCC clinical samples and correlated with early recurrence and poor prognosis of HCC [10]. Another study reveals that in NSCLC, AKIP1 is overexpressed in NSCLC specimens, and its overexpression is correlated with advanced TNM stage, lymph node metastasis as well as poor survival in NSCLC patients [21]. As for in prostate cancer, we observed that AKIP1 was upregulated in prostate tumor tissues compared with adjacent tissues, and its high expression was correlated with higher pathological T, pathological N stage, and poor prognosis in prostate cancer patients, suggesting its potential to be a biomarker for disease surveillance and prognosis in prostate cancer. The possible reasons might include that (1) According to the prior fndings of this study, AKIP1 high expression might enhance the interaction between p65 and PKAc, promoting NF-κB-induced cell proliferation, invasion as well as NF-κB-related oncogenic genes expression, which further led to prostate tumor growth and metastasis [9, 11]. Therefore, AKIP1 high expression was associated with deteriorative tumor features, and further contributed to undesirable survival profles in prostate cancer patients. (2) According to the prior study, cancer cells with the CD133+ phenotype exhibit properties of self-renewal and the ability to re-establish the heterogeneous tumor cell population, therefore AKIP1 high expression might promote stemness of prostate cancer cells, and further induce relapse, metastasize, and develop drug resistance in prostate cancer, resulting in poor treatment response as well as unfavorable prognosis [29, 30].

5 Conclusions

In summary, AKIP1 promotes prostate cancer cell proliferation, invasion, stemness, and activates oncogenic PI3K/AKT, MEK/ERK and mTOR signaling pathway, which also associates with aggravated tumor features and survival in prostate cancer patients, suggesting its potential as a treatment target for the prostate cancer management.

Abbreviations

AKIP1, A-kinase interacting protein 1; PKA, protein kinase; NF-Kb, NF-kappaB; HCC, hepatocellular carcinoma; NSCLC, non-small cell lung cancer; FBS, Fetal Bovine Serum; RPMI, Roswell Park Memorial Institute; RT-qPCR, Reverse Transcription quantitative Polymerase Chain Reaction; NC, negative control; shRNA, short hairpin RNA; Sh-AKIP1, AKIP1 shRNA; Sh-NC, NC shRNA; CD133+, CD133 positive; d DEGs, ifferentially expressed genes; GO, Gene Ontology; KEGG, Kyoko Encyclopedia of Genes and Genomes; pPI3K, phoso-PI3K, pAKT, phoso-AKT; pMEK1/2, phoso-MEK1/2; pERK1/2, phoso-ERK1/2; IHC, Immunohistochemistry; SD, standard deviation; ANOVA, One-way analysis of variance; DFS, Disease-free survival; OS, Overall survival; NS, non- signifcant; ZEB1, Zinc Finger E-box binding homeobox 1

Declarations

Page 11/18 Ethics approval and consent to participate

The use of patients’ specimens and data for this study were approved by Institutional Review Board of The First Afliated Hospital of Harbin Medical University, and informed consents were collected from patients or their family members.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests

Acknowledgements

None.

Authors’ Contributions

LH contributed to the conception and design. JZ contributed to the data acquisition. BZ contributed to the analysis and interpretation of data. All authors contributed to drafting/revising of article. All authors provided fnal approval of the version to be published.

Funding

This research did not receive any specifc grant from funding agencies in the public, commercial, or not-for-proft sectors.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Figures

Figure 1

AKIP1 expression in human prostate cancer cells and normal prostate epithelial cells. Comparison of AKIP1 mRNA (A) and protein (B) expressions between human prostate cancer cells (VAcP, LNCaP, 22Rv1, DU145 cell lines) and normal prostate epithelial cells (RWPE-1 cells). AKIP1, A-kinase interacting protein 1

Page 13/18 Figure 2

AKIP1 expression of stably-infected prostate cancer cells. In 22Rv1 cells, comparison of AKIP1 mRNA (A) and protein (B) expressions between OE-AKIP1 group and OE-NC group, between Sh-AKIP1 group and Sh-NC group; in LNCaP cells, AKIP1 mRNA (C) and protein (D) expressions between OE-AKIP1 group and OE-NC group, between Sh-AKIP1 group and Sh-NC group. AKIP1, A-kinase interacting protein 1; OE, overexpression; NC, negative control; Sh, short hairpin.

Figure 3

Page 14/18 Comparison of prostate cancer cell proliferation and apoptosis. Comparison of cell proliferation (A) and apoptosis (B, C) between OE-AKIP1 group and OE-NC group, between Sh-AKIP1 group and Sh-NC group in 22Rv1 cells; comparison of cell proliferation (D) and apoptosis (E, F) between OE-AKIP1 group and OE-NC group, between Sh-AKIP1 group and Sh-NC group in LNCaP cells. AKIP1, A-kinase interacting protein 1; OE, overexpression; NC, negative control; Sh, short hairpin.

Figure 4

Comparison of prostate cancer cell migration. Comparison of cell migration (A, B) between OE-AKIP1 group and OE-NC group, between Sh-AKIP1 group and Sh-NC group in 22Rv1 cells; comparison of cell migration (C, D) between OE-AKIP1 group and OE-NC group, between Sh-AKIP1 group and Sh-NC group in LNCaP cells. AKIP1, A-kinase interacting protein 1; OE, overexpression; NC, negative control; Sh, short hairpin.

Figure 5

Comparison of prostate cancer cell invasion. Comparison of invasive cell number between OE-AKIP1 group and OE-NC group, between Sh-AKIP1 group and Sh-NC group in 22Rv1 cells (A, B); comparison of invasive cell number between OE-AKIP1 group and OE-NC group, between Sh-AKIP1 group and Sh- NC group in LNCaP cells (C, D). AKIP1, A-kinase interacting protein 1; OE, overexpression; NC, negative control; Sh, short hairpin.

Page 15/18 Figure 6

Comparison of prostate cancer cell stemness. Comparison of CD133+ cell rate (A, B) and sphere formation ability (C) between OE-AKIP1 group and OE- NC group, between Sh-AKIP1 group and Sh-NC group in 22Rv1 cells; comparison of CD133+ cell rate (D, E) and sphere formation ability (F) between OE- AKIP1 group and OE-NC group, between Sh-AKIP1 group and Sh-NC group in LNCaP cells. AKIP1, A-kinase interacting protein 1; OE, overexpression; NC, negative control; Sh, short hairpin.

Figure 7

AKIP1-modifed DEGs in prostate cancer cells. Volcano plots in the group of OE-AKIP1 vs. OE-NC (A); Volcano plots in the group of Sh-AKIP1 vs. Sh-NC (B); Cross analysis (C). AKIP1, A-kinase interacting protein 1; OE, overexpression; NC, negative control; Sh, short hairpin; DEG, differentially expressed genes.

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Enrichment analyses. GO (A) and KEGG (B) enrichment analysis for accordant DEGs. DEGs, differentially expressed genes; GO, Gene Ontology; KEGG, Kyoko Encyclopedia of Genes and Genomes.

Figure 9

Validation of AKIP1 on candidate oncogenic signaling pathways. Validation of AKIP1 on PI3K/AKT, MEK/ERK and mTOR signaling pathways in 22Rv1 cells (A) and LNCaP cells (B). AKIP1, A-kinase interacting protein 1.

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AKIP1 expression in prostate tumor tissues and adjacent tissues. Representative IHC images of AKIP1 high/low expression in adjacent tissues and tumor tissues (A). Comparison of the percentage of AKIP1 low expression and the percentage of AKIP high expression between tumor tissue and adjacent tissue (B). AKIP1, A-kinase interacting protein 1; IHC, immunohistochemistry.

Figure 11

Comparison of clinicopathological features between tumor AKIP1 high patients and tumor AKIP1 low patients. Comparison of age (A), pT (B), pN (C), Gleason score (D), PSA level (E), surgical margin status (F) between tumor AKIP1 high patients and tumor AKIP1 low patients. AKIP1, A-kinase interacting protein 1; pT, pathological T stage; pN, pathological N stage; PSA, prostate-specifc antigen.

Figure 12

Comparison of survival between tumor AKIP1 high patients and tumor AKIP1 low patients. Comparison of DFS (A) and OS (B) between tumor AKIP1 high patients and tumor AKIP1 low patients. DFS, disease-free survival; OS, overall survival; AKIP1, A-kinase interacting protein 1.

Supplementary Files

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SupplementaryTable1.docx

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