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

doi:10.21203/rs.3.rs-568302/v1

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

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

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Background: The study aimed to examine the molecular mechanism and clinical significance of A-kinase 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 genes (DEGs) by AKIP1 modification 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 efficiency in 22Rv1 and LNCaP cells. Reversely, AKIP1 knockdown exhibited the opposite effect in 22Rv1 and LNCaP cells. Further RNA sequencing analysis exhibited that AKIP1-modified 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.

Cancer Biology

Oncology

AKIP1

prostate cancer

RNA sequencing

mobility

viability

stemness

prognosis

Prostate cancer ranks as the second most frequently diagnosed cancer as well as the fifth 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 benefit 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 gene expressions [8]. In addition, in hepatocellular carcinoma, AKIP1 is upregulated, and its high expression increases the β-catenin induced by protein kinase A 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 profiles modified by AKIP1 via RNA sequencing (RNA-seq) assay in prostate cancer cells. Furthermore, clinical significance of AKIP1 was explored by detecting its correlation with clinicopathological features and prognosis in prostate cancer patients.

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 Modified 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 Modification 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 humidified 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

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 flow 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 flow 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. Briefly, 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 identified 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. Gene Ontology (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 Affiliated 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 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 Affiliated Hospital of Harbin Medical University, which were fixed by formalin and embedded by paraffin. Besides, prostate cancer patients’ clinical features including age, pathological T stage, pathological N stage, Gleason score, prostate-specific 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 Affiliated 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. Briefly, all tissue specimens were cut into 4 µm slices, then the tissue slices were processed with deparaffination, rehydration and antigen retrieval. Afterwards, the endogenous peroxidase activity of the tissue slices was blocked with the use of H₂O₂ (Sigma-Aldrich, USA), and nonspecific 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 classified 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 significant. For the figures of in vitro experiments, P > 0.05, P < 0.05, P < 0.01 and P < 0.001 were marked as non-significant (NS), *, ** and ***, respectively.

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-modified 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-modified 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 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 findings 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 modification in prostate cancer cells

RNA-seq assay was conducted following the construction of AKIP1-modified stably-infected 22Rv1 cells. The volcano plots exhibited that 640 upregulated and 901 downregulated DEGs were identified in the OE-AKIP1 group compared with OE-NC group, respectively (Fig. 7A). Meanwhile, 658 upregulated and 579 downregulated DEGs were identified 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 modification was shown in Table 1.

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
Gene ID	Symbol	log₂FC	P value	P_adj value	Trend	log₂FC	P value	P_adj value	Trend	Mean ABS log₂FC
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
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, identification; NC, negative control; OE, overexpression; FC, fold change; Sh, short hairpin; ABS, absolute.

3.7 Related signaling pathways by AKIP1 modification 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, specific 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.

Table 2

Top 30 pathways of KEGG enrichment with accordant DEGs
Pathway	Number of symbols	Proportion of symbols	Symbols	Fold enrichment	P value
Prostate cancer	20	0.12195122	CHUK, EP300, ERBB2, FOXO1, MTOR, HRAS, HSP90AB1, IGF1R, IKBKB, PDPK1, MAPK3, MAP2K2, RB1, BCL2, SOS1, BRAF, TCF7L2, TCF7L1, CCNE2, CREB5	9.6916964	6.1399E-14
PI3K-Akt signaling pathway	28	0.170731707	LAMC3, CHUK, COL1A1, COL6A6, FGF10, FGFR4, LPAR3, SGK3, MTOR, HRAS, HSP90AB1, TNC, IGF1R, IKBKB, IL6R, ITGB8, MYC, PCK2, PDPK1, MAPK3, MAP2K2, PRLR, BCL2, SOS1, THBS2, TNXB, CCNE2, CREB5	3.5309514	1.2695E-08
Pathways in cancer	30	0.182926829	LAMC3, ADCY8, CHUK, ADCY4, EP300, ERBB2, ETS1, FGF10, FOXO1, LPAR3, MTOR, HRAS, HSP90AB1, IGF1R, IKBKB, MMP1, MYC, MAPK3, MAP2K2, PTGER2, PTGS2, RB1, BCL2, SOS1, BRAF, TCF7L2, WNT2, WNT5B, TCF7L1, CCNE2	3.2590465	1.9924E-08
EGFR tyrosine kinase inhibitor resistance	13	0.079268293	ERBB2, MTOR, NRG1, HRAS, IGF1R, IL6R, SHC3, MAPK3, MAP2K2, BCL2, SOS1, BRAF, NRG2	6.9217856	2.3262E-07
Acute myeloid leukemia	11	0.067073171	CHUK, MTOR, HRAS, IKBKB, MYC, MAPK3, MAP2K2, SOS1, BRAF, TCF7L2, TCF7L1	8.3229568	4.5865E-07
mTOR signaling pathway	12	0.073170732	CHUK, MTOR, HRAS, IGF1R, IKBKB, PDPK1, MAPK3, MAP2K2, SOS1, BRAF, WNT2, WNT5B	3.3825921	7.301E-07
MAPK signaling pathway	15	0.091463415	CHUK, DUSP5, FGF10, FGFR4, HRAS, HSPA2, IKBKB, MYC, MAPK3, MAP2K2, MAP2K3, SOS1, BRAF, PTPN5, CACNA1G	2.536944	7.301E-07
Endometrial cancer	10	0.06097561	ERBB2, HRAS, MYC, PDPK1, MAPK3, MAP2K2, SOS1, BRAF, TCF7L2, TCF7L1	8.2938555	1.9531E-06
ErbB signaling pathway	12	0.073170732	ERBB2, EREG, MTOR, NRG1, HRAS, MYC, SHC3, MAPK3, MAP2K2, SOS1, BRAF, NRG2	5.8810976	4.2919E-06
FoxO signaling pathway	14	0.085365854	KLF2, CHUK, EP300, FOXO1, SGK3, HRAS, IGF1R, IKBKB, PCK2, PDPK1, MAPK3, MAP2K2, SOS1, BRAF	4.5059155	1.0445E-05
Bladder cancer	8	0.048780488	ERBB2, HRAS, MMP1, MYC, MAPK3, MAP2K2, RB1, BRAF	8.415229	2.9849E-05
Non-small cell lung cancer	9	0.054878049	ERBB2, ALK, HRAS, PDPK1, MAPK3, MAP2K2, RB1, SOS1, BRAF	6.9312936	3.2495E-05
Thyroid cancer	7	0.042682927	HRAS, MYC, MAPK3, MAP2K2, BRAF, TCF7L2, TCF7L1	10.410219	3.3827E-05
Chronic myeloid leukemia	10	0.06097561	CHUK, HRAS, IKBKB, MYC, SHC3, MAPK3, MAP2K2, RB1, SOS1, BRAF	5.9079519	3.6112E-05
Focal adhesion	16	0.097560976	LAMC3, COL1A1, COL6A6, ERBB2, HRAS, TNC, IGF1R, ITGB8, PDPK1, SHC3, MAPK3, BCL2, SOS1, BRAF, THBS2, TNXB	3.3992551	5.9059E-05
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, RB1, BCL2, CCNE2, CREB5	3.8401687	0.00011948
Axon guidance	14	0.085365854	EPHA7, EPHB1, SEMA3D, NTNG1, NGEF, HRAS, NFATC2, PLXNB3, MAPK3, RGS3, SEMA3F, WNT5B, PLXNA4, NTN1	3.4306402	0.00018591
Insulin signaling pathway	12	0.073170732	FOXO1, MTOR, HRAS, IKBKB, PCK2, PDPK1, SHC3, PPP1R3C, MAPK3, MAP2K2, SOS1, BRAF	3.7232848	0.00032023
Estrogen signaling pathway	10	0.06097561	ADCY8, ADCY4, HRAS, HSPA2, HSP90AB1, SHC3, MAPK3, MAP2K2, SOS1, CREB5	4.3563686	0.00040045
Melanogenesis	10	0.06097561	ADCY8, ADCY4, EP300, HRAS, MAPK3, MAP2K2, TCF7L2, WNT2, WNT5B, TCF7L1	4.3128049	0.00043194
Neurotrophin signaling pathway	10	0.06097561	HRAS, IKBKB, ARHGDIB, PDPK1, SHC3, MAPK3, MAP2K2, BCL2, SOS1, BRAF	3.5940041	0.00163109
Ras signaling pathway	14	0.085365854	CHUK, ETS1, FGF10, FGFR4, HRAS, HTR7, IGF1R, IKBKB, SHC3, MAPK3, MAP2K2, SOS1, RIN1, RAPGEF5	2.6482135	0.00216202
Proteoglycans in cancer	13	0.079268293	ERBB2, MTOR, HRAS, IGF1R, MYC, PDPK1, PLAUR, MAPK3, MAP2K2, SOS1, BRAF, WNT2, WNT5B	2.7349494	0.0025552
Longevity regulating pathway - multiple species	7	0.042682927	ADCY8, ADCY4, FOXO1, MTOR, HRAS, HSPA2, IGF1R	4.7171303	0.00313872
Rap1 signaling pathway	13	0.079268293	ADCY8, ADCY4, FGF10, FGFR4, LPAR3, HRAS, IGF1R, MAPK3, MAP2K2, MAP2K3, SIPA1L2, BRAF, RAPGEF5	2.6571784	0.00324367
Jak-STAT signaling pathway	11	0.067073171	EP300, MTOR, HRAS, IL6R, IL11, MYC, IL20RB, PRLR, BCL2, SOS1, TSLP	3.0025857	0.00327791
Small cell lung cancer	8	0.048780488	LAMC3, CHUK, IKBKB, MYC, PTGS2, RB1, BCL2, CCNE2	4.0119115	0.00332085
Insulin resistance	9	0.054878049	PPARGC1B, FOXO1, MTOR, IKBKB, PCK2, PDPK1, PPP1R3C, TRIB3, CREB5	3.5610316	0.00334879
Renal cell carcinoma	7	0.042682927	EP300, ETS1, HRAS, MAPK3, MAP2K2, SOS1, BRAF	4.5059155	0.00396637
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).

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-specific 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.

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 inflammatory 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 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 modification 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 verified 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 findings 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 profiles 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].

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.

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-significant; ZEB1, Zinc Finger E-box binding homeobox 1

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 Affiliated 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 final approval of the version to be published.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit 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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AKIP1 promotes cell proliferation, invasion, stemness and activates PI3K-Akt, MEK/ERK, mTOR signaling pathways in prostate cancer

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