CDK6 is upregulated and may be a potential therapeutic target in enzalutamide-resistant castration- resistant prostate cancer by bioinformatic analysis

doi:10.21203/rs.3.rs-1501682/v1

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CDK6 is upregulated and may be a potential therapeutic target in enzalutamide-resistant castration- resistant prostate cancer by bioinformatic analysis

https://doi.org/10.21203/rs.3.rs-1501682/v1

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Background

Androgen deprivation therapy (ADT) is still the first line treatment of prostate cancer (PCa). However, after a certain period of therapy, primary PCa inevitably progresses into castration-resistant PCa (CRPC). Enzalutamide (MDV3100) is an androgen receptor (AR) signal inhibitor which can delay the progression of CRPC and increase survival of patients with metastatic CRPC. However, the mechanisms involved in enzalutamide-resistant (EnzR) CRPC are still controversial.

Methods

We collected RNA-seq data of the EnzR CRPC cell line LNCaP (EnzR LNCaP) from GSE44905, GSE78201, and GSE150807. We found the hub genes from the three datasets. Then we tested the expression of the hub genes in the Cancer Genome Atlas (TCGA) database and the potential drugs that affect the hub genes. Finally, we verified the hub gene expression and drug function.

Results

From GSE44905, GSE78201 and GSE150807, we found 45 differently expressed genes (DEGs) between LNCaP and EnzR LNCaP. Ten hub genes were found in the protein-protein interaction (PPI) network. The hub genes expression and survival analysis were analyzed by GEPIA depend on the TCGA database. We found that cyclin-dependent kinase 6 (CDK6) was highly expressed in both the EnzR LNCaP cell and PCa patients. Ten potential small molecules could suppress CDK6 expression as per CMap findings. Finally, we found the expression of CDK6 increased in both PCa patients’ samples, CRPC cell lines and EnzR PCa cell lines. Three potential CDK6 inhibitors, namely apigenin, chrysin and fisetin, can decrease cell proliferation.

Conclusions

The study proved that CDK6 mutation may be a reason behind EnzR CRPC occurrence and suppression CDK6 expression may help treat EnzR CRPC.

Differently expressed genes

castration-resistant prostate cancer

enzalutamide

hub gene

cyclin-dependent kinase 6

therapeutic target

Prostate cancer（PCa）has the highest incidence among all types of cancers in older men in America and its incidence is rapidly increasing. The estimated incidence rate of PCa is 174,650 in the United States in 2019, which amounts to a 20% incidence of all new cancer diagnoses in men. In addition, the mortality rate associated with PCa has risen in recent years. In America, the greatest number of deaths in men are from lung, prostate, and colorectal cancers[1]. Furthermore, PCa also has increasing incidence and death rates in China. According to the National Cancer Center of China, 72000 new patients were diagnosed as having PCa in China in 2015, with an estimated incidence ratio of 10.23/100 000 in men [2]. Androgen deprivation therapy (ADT) is still the first-line therapy for treating locally advanced and even metastatic PCa [3]. As an important method for treating PCa, ADT can effectively release patients’ clinical symptoms and prolong survival time [4]. However, after a certain period of treatment, nearly all patients will inevitably develop castration-resistant PCa (CRPC) [5]. CRPC refers to the disease will progress when serum testosterone level has reached castration level. When patients relapse into CRPC stage, the median survival rate of patients is less than 20 months [6]. The treatment of CRPC is still a difficult problem.

Enzalutamide (Enz) as a second-generation androgen receptor (AR) inhibitor is approved by the Food and Drug Administration (FDA) to treat CRPC [7]. It inhibits the activated AR nuclear translocation and prevents its combination of androgen response elements (ARE) and coactivator recruitment, which promotes apoptosis while suppresses proliferation of the CRPC cells [8, 9]. Enz can effectively prolong the survival time of CRPC patients than both placebo and bicalutamide [3, 10]. However, after a period of therapy, patients will resistant to Enz. There are still no effective treatment regimens for Enz-resistant (EnzR) CRPC.

Genetic mutations may play an important role in the occurrence of EnzR CRPC. Bioinformatic analysis has been widely used for finding potential gene mutations in this process. In this study, we found differently expressed genes (DEGs) in EnzR PCa cell line LNCaP (EnzR LNCaP) using the GEO database. Then, we analyzed the significant functional modules, and pathways which enriched by the DEGs. The hub genes were found in protein-protein interaction (PPI) network. The hub genes expression and clinical value were analyzed by using the Cancer Genome Atlas (TCGA) and Chinese Prostate Cancer Genome and Epigenome Atlas (CPGEA) database. A hub gene, Cyclin dependent kinase 6 (CDK6), was higher expression in both EnzR LNCaP and PCa samples. Finally, we validated the expression of CDK6 in clinical samples and EnzR PCa cell lines. Furthermore, we found three CDK6 inhibitors, namely apigenin, chrysin, and fisetin, can suppress CDK6 expression and cell proliferation ability.

Data Source

The GEO database (http://www.ncbi.nlm.nih.gov/geo/) at the National Center for Biotechnology Information (NCBI) is a public database that provides a genomics data repository of gene expression, chip, and microarray data[11]. Since it was different to collect clinical samples, we downloaded RNA-seq data of EnzR LNCaP. Three gene expression datasets, GSE44905, GSE78201, and GSE150807, were downloaded from the GEO database. These datasets were included in the high-throughput sequencing of EnzR LNCaP cells and normal control LNCaP cells. GSE44905 included three control LNCaP samples and six EnzR LNCaP samples. GSE78201 included four untreated LNCaP samples and four EnzR LNCaP samples. GSE150807 included three parental LNCaP samples and three EnzR LNCaP samples. In addition, two datasets, GSE151083 and GSE136130, which have the RNA-seq data of EnzR C4-2 samples were downloaded, too.

Identification of DEGs

Raw microarray expression data of mRNAs downloaded as Series Matrix files from the GEO database were mapped to the corresponding genes according to the SOFT-formatted family files from the GEO database. The primary data were normalized by R software Limma package [12]. The genes with an adjusted P-value<0.05 and |log2fold change (FC)|>1 were considered as DEGs [13]. Then, we used an online web tool, bioinformatic (http://www.bioinformatics.com.cn/), to draw a Venn map and find the DEGs. The upregulated and downregulated DEGs were saved for further analysis.

GO and KEGG analysis

GO terms included a frame of biological processes (BP), molecular functions (MF) and cellular components (CC). In addition, KEGG pathways are widely used to analyze biological pathways associated with DEGs. Both GO annotation and KEGG pathway enrichment analyses were performed using Metascape (http://metascape.org/). Then, scatter plots were drawn using an online web tool, bioinformatic (http://www.bioinformatics.com.cn/). P value < 0.05 was considered statistically significant.

Construction PPI network and identify hub gene

To evaluate the potential PPIs among the identified DEGs, the STRING online database (http://string-db.org/) was used to build a PPI network. Then, Cytoscape software was used to find the correlation among DEGs. The hub gene was defined as the gene that has a connection with other genes.

Detection of hub gene expression

TCGA is one of the largest tumor databases including 499 PCa samples and 52 normal prostate samples [14]. A website tool, GEPIA (http://www.gepia.cancer-pku.cn/), identify the expression of the hub gene in TCGA samples and Genotype-Tissue Expression (GTEx). Then, Chinese patients’ data from CPGEA (http://www.cpgea.com/) were downloaded and the expression of the hub gene was analyzed in Chinese population, as well.

Survival and Clinical value analysis

Besides expression data, GEPIA website can help with survival analysis as well. We performed survival analysis based on GEPIA. The expression of the hub gene on overall survival (OS) and disease-free survival (DFS) was analyzed. To assess hub gene expression at different tumor stages, we downloaded the clinical data of PCa patients from TCGA. Combined with the gene expression and clinical data. We analyzed the hub gene expression in different Tumor-Node-Metastasis (TNM) tumor classification of malignance tumors.

Screening of potential small molecules

CMap (https://portals.broadinstitute.org/cmap/) has the genome-wide transcriptional expression data that can help find functional connection among drugs, genes, and diseases [15]. We downloaded all potential small molecules that may affect the function of the hub gene.

Tissue samples

Fourteen paired PCa samples and para-cancerous samples were collected at Tongji Hospital, School of Medicine, Tongji University. The methods used for collecting samples were approved by the Ethics Committee of the hospital. Patients who provided samples knew the process of the experiment and provided written informed consent.

Cell culture and drug treating

The human normal prostate epithelial cell line RWPE-1 and PCa cells LNCaP,C4-2, and 22Rv1 were cultured in Roswell Park Memorial Institute (RPMI) 1640 (Sigma Darmstadt, Germany) with 10% fetal bovine serum (FBS) (Gibco, Thermo Fisher Scientific, Waltham, MA, USA). All cell lines were cultured in a humid environment containing 5% CO₂ and 95% air at 37 °C. The EnzR LNCaP and C4-2 cell lines were treated with Enz at 10, 20, 30, and then 40 µM until 20 days. Then, 10-µM Enz was used to maintain cell resistant ability to Enz. When EnzR cell culture was completed, we treated the cell lines with apigenin, chrysin, and fisetin. We added these small molecules to the culture medium of PCa and EnzR PCa cells according to the manufacturer's instructions.

RNA extraction and qRT-PCR

Total tissue and cell RNA was isolated using a TRIzol reagent (Sigma Darmstadt, Germany) in accordance with the manufacturer’s instructions. The mRNA was reverse transcribed to cDNA using the transcription kit (Advantage^® RT-for-PCR Kit, Takara Bio Inc., Kusatsu, Japan). The reverse transcription procedure was performed according to the manufacturer’s instructions. The qRT-PCR was performed using the Applied Biosystems 7500 Sequence Detection system. The volume of cDNA was detected by using qRT-PCR reagents and a kit (TB Green® Premix Ex Taq™ II, Takara Bio Inc.) according to the manufacturer’s instructions. β-tubulin was used as the normal control. The expression of RNA was calculated according to the 2^−ΔΔCt method. The following primers were used: cyclin-dependent kinases 6 (CDK6)（Forward: 5′-CAAGGTCAGGTCTACTCAAAGTCTCAC-3′, Reverse: 5′-CTGCCAACGATTGAATGCCAGAATG-3′）and β-tubulin (Forward:5′- TGGACTCTGTTCGCTCAGGT -3′ , Reverse: 5′- TGCCTCCTTCCGTACCACAT -3′ ).

Western blot

Clinical sample and cell line proteins were extracted using RIPA lysis buffer. Protein samples were treated with Dual Color Protein Loading Buffer (Thermo Fisher Scientific, Waltham, MA, USA). SDS–PAGE gels (10%) were used to separate proteins, and then transferred to nitrocellulose membranes (NC) (Merck KGaA, Darmstadt, Germany). Protein-Free Rapid Blocking Buffer (Thermo Fisher Scientific) was used to block the membranes. Then the membranes were incubated at 4°C overnight with primary antibodies against CDK6 (1:1000) and β-tubulin (1:1000) (Abcam UK, Cambridge, UK). On the second day, the membranes were washed by 1×TBST three times (10 min. each). Then, the membranes were incubated at normal temperature for 1.5 h with a matched secondary antibody [HRP-labeled Goat Anti-Human IgG (H+L), Beyotime Biotechnology, Shanghai, China]. Finally, the membranes were exposed to X-ray film.

Cell proliferation assay

Cell proliferation ability was detected using the CCK-8 kit (Dojindo, Japan). In brief, the cells were put in 96-well plates (3000 cells/well), cultured with 200µL 1640+10%FBS for 0h, 24h, 48h, or 72h. After culture, cells were detected using the CCK-8 kit according to the manufacturer’s illustration and absorbance at 450 nm was measured using a spectrophotometer (LD942, Beijing, China).

Statistical analysis

Experiment data represents all repeated at least three times. The data were represented as meaning ± standard deviation (SD). Data were analyzed using Student's t-test for two groups and one-way analysis of variance for three or more groups. The chip data from GEO and CPGEA database were analyzed by R software with different packages (R Version 4.0.3). A P value of≤0.05 was considered statistically significant.

DEGs identification

We detected GEO database to find EnzR PCa samples. Finally, cell samples treated by Enz were included in the study. To find DEGs, we analyzed three gene expression datasets: GSE44905, GSE78201 and GSE150807, which overall included 10 untreated LNCaP cell samples and 13 EnzR LNCaP cell samples. In these samples we identified 43 upregulated DEGs (Figure 1A) and 2 downregulated DEGs (Figure 1B). In total, there were 45 DEGs in all 3 datasets.

Functional and enrichment analysis

To identify the biological function of DEGs, we used Metascape to construct KEGG pathways and GO functional analysis. Then, we used a webtool, bioinformatic, to draw a scatter plot map. GO enrichment suggested that the DEGs were primarily involved in negative regulation of cell differentiation and cell morphogenesis, which are involved in cell differentiation. KEGG pathway enrichment shown that most enrichment pathways were pathways associated with cancer development and cytokine–cytokine receptor interaction. The significant KEGG pathways which DEGs enriched are shown in scatter plot map (Figure 2A). In addition, BP, MF and CC pathways were also shown in the scatter plot map (Figure 2B).

PPI network construction and hub gene finding

Next, we used STRING to draw the PPI network of DEGs. We drew the network to find the connection among DEGs and identify the hub gene (Figure 3). We defined the hub gene as the gene which had connection with other genes. We found that GRIP2, EPHB2, CDK6, PAX6, BMP7, ITGA1, LAMB1, IGFBP5, LY6K, and MDGA2 had connection with other genes and considered these as hub genes.

Hub gene expression in prostate cancer samples from public database

Due to the finding of the hub gene depending on the EnzR PCa cell line LNCaP, we tested the hub gene expression on TCGA data. We used GEPIA, which had sequencing information of all the 492 PCa patients’ samples and 152 normal control samples’ from TCGA and GTEx. We found that the expression of EPHB2, PAX6, LY6K, and MDGA2 did not differ, whereas all other genes were expressed differently in patients’ tissues. However, only CDK6 was expressed highly in cancer tissues, which is in agreement with the results obtained from cell line samples (Figure 4). Other genes, which were highly expressed in the EnzR LNCaP cell line, were expressed lower in cancer tissues. In addition, we also collected the RNA-sequence data from Chinese PCa patients. We found that except LY6K and MDGA2, all other hub genes were expressed differently between PCa tissues and para-carcinoma tissues. Like the results from TCGA, CDK6 was expressed highly in PCa tissues (Figure S1). These results indicated that CDK6 may be a potential cause of PCa. Moreover, we analyzed CDK6 expression at different tumor stages (TNM tumor stages) in PCa patients from the TCGA database. However, we found that the expression change of CDK6 was not reflective of disease progression (Figure S2).

CDK6 expression in EnzR CRPC cell line

As the LNCaP PCa cell line is from hormone sensitive PCa, it cannot reflect the CRPC model perfectly. Therefore, we further tested CDK6 expression in other PCa cell lines. As both C4-2 and 22Rv1 cell lines can independent growth without androgens., they can serve as CRPC cell lines[16, 17]. We collected RNA-sequence data from two datasets, GSE151083 and GSE136130, which included the RNA-sequence data from the C4-2 cell line and EnzR C4-2 cell line. We found that CDK6 showed a higher expression with EnzR C4-2 cell line (Figure S3A-B). These results indicated that CDK6 may be a reason behind the occurrence of EnzR CRPC.

Survival analysis

To find whether the hub gene can affect patients’ survival status, we further used GEPIA to identify the effect of the hub gene on the survival status. The OS and DFS were detected in the study. As the sample size was insufficient, we did not analyze MDGA2. We found that the hub genes, ITGA1 and LAMB1 affected the DFS (Figure 5). However, these gene could not affect the OS (Figure S4). The results suggested that ITGA1 and LAMB1 play a key role in PCa occurrence and may affect the disease progression.

Screening of potential small molecule drugs

According to the abovementioned results, we tried to identity drugs that may treat EnzR CRPC by inhibiting the function of CDK6. From CMap, we identified 10 compounds that could inhibit the activity of CDK6 (Figure S5). Three of them have been clinically used to treat breast cancer. Two compounds are currently in the preclinical phase, two in the phase II, and three in the phase I. The detailed information of the 10 compounds is shown in Table 1. We found that apigenin, chrysin, and fisetin affect only CDK6, whereas other compounds affect other CDK genes as well. So, we selected these three compounds for further study.

Table 1

The detailed information of 10 CDK6 inhibitors from CMap

Name	Mechanism of Action (MOA)	Target	Phase
Abemaciclib	CDK inhibitor	CDK4, CDK6	Launched
Alvocidib	CDK inhibitor	CDK1, CDK2, CDK4, CDK5, CDK,6 CDK7, CDK8, CDK9, EGFR, PYGM	Phase2
AMG-925	CDK inhibitor, FLT3 inhibitor	CDK4, CDK6, FLT3	Phase1
Apigenin	Casein kinase inhibitor, cell proliferation inhibitor	AKR1B1, AR,CDK6, CFTR, CYP19A1, CYP1B1, HSD17B1	Preclinical
AT-7519	CDK inhibitor	CDK1, CDK2, CDK4, CDK5, CDK6, CDK9	Phase2
Chrysin	Breast cancer resistance protein inhibitor	AKR1B1, CDK6, CYP19A1, CYP1B1	Phase1
Fisetin	Aurora kinase inhibitor	CDK6, FASN	Preclinical
Palbociclib	CDK inhibitor	CDK4, CDK6	Launched
RGB-286638	CDK inhibitor	CDK1, CDK2, CDK3, CDK4, CDK5, CDK6, CDK7, CDK9, FLT3, GSK3B, JAK2, MAP3K7, MAPK9	Phase 1
Ribociclib	CDK inhibitor	CDK4, CDK6	Launched

Validation of CDK6 expression in clinical PCa samples and EnzR PCa cell lines

As CDK6 may be important in the appearance of PCa and EnzR CRPC, we collected PCa patients’ tumor tissues and para-cancerous tissues and EnzR PCa cell lines to compare the CDK6 expression among them. We found the expression of CDK6 was high in PCa tissues at mRNA and protein levels (Figure 6A-B). In addition, CDK6 expression higher in the PCa cell lines LNCaP and C4-2 than in RWPE-1(Figure 6C-D). Further, CDK6 expression was higher in EnzR LNCaP and C4-2 cell lines than in normal LNCaP and C4-2 cell lines (Figure 6E-F). Due to the expression of AR splice variants, 22Rv1 cell can resistant to Enz [18]. We chose the 22Rv1 cell line to add Enz to check if CDK6 expression changes when Enz is added in this cell line. We found that CDK6 was expressed higher in the 22Rv1 cell which added Enz (Figure S3C-D). The results suggest that CDK6 plays a critical role in the occurrence of PCa and even EnzR CRPC.

CDK6 inhibitors’ function in PCa, CRPC, and EnzR CRPC cell model

To determine whether the abovementioned drugs, apigenin, chrysin, and fisetin, can treat PCa, CRPC, and even EnzR CRPC, we treated LNCaP, C4-2, EnzR LNCaP and EnzR C4-2 cell lines with these compounds. We found that when treated with CDK6 inhibitors, the expression of CDK6 truly downregulated at both mRNA and protein levels in PCa cell lines (Figure 7A-D). The result suggests that these drugs can suppress CDK6. In addition, when treated with these CDK6 inhibitors, the progression of PCa and EnzR PCa cell lines will decrease. (Figure 7E-F). As the LNCaP cell line cannot serve as a CRPC cell line, we further tested the expression of CDK6 in the 22Rv1 cell line which is considered an EnzR CRPC cell line. We found that these CDK6 inhibitors can suppress the expression and CDK6 and cell proliferation ability in 22Rv1 cell line (Figure S6A-C). The results prove that CDK6 inhibitors have the ability to treat EnzR CRPC in vivo and may be a protein drug to treat PCa, CRPC, and even EnzR CRPC in the future.

Millions of elderly men in the world suffer from PCa. In America, PCa has the highest incidence in men among all cancers. The incidence of PCa is nearly 20% of new patients diagnosed with cancer. In addition, PCa-related mortality has increased rapidly as well [1]. Similarly, PCa incidence has been increasing in Chinese population and has become a serious threat to patients’ healthy [2]. The current treatment methods for localized PCa are comprise surgical prostatectomy, chemotherapy, immune therapy, and a ADT [19]. Until now, ADT is still the first line therapy for treating localized advanced and metastatic PCa [3]. ADT has effectively improved patients survival [20]. However, after a period of therapy less than 2 years, the primary PCa inevitably relapsed into CRPC [5]. As a second-generation AR inhibitor, Enz can prolong the survival time of CRPC patients about 4.8 months when patients progressed in CRPC stage [21]. However, patients will resistant to Enz finally. Therefore, it is important to find effective methods to treat EnzR CRPC.

Genetic changes are suggested to be a key factor leading to EnzR CRPC. Study have proven that AR is expressed and is transcriptionally active in EnzR CRPC [22]. Some genes, such as kallikrein-related peptidase 3 (KLK3) and transmembrane protease serine 2 (TMPRSS2), which can activate AR show increased expression in EnzR CRPC. The changes in the expression of AR target genes can be a reason behind EnzR CRPC [23]. AR will change into splice variants in CRPC patients. AR can carry out selective shear to form hypotypes that consist of exons 1-3 with LBD deletion. The AR without LBD will fail to respond to Enz [24]. Many gene expressions will change and increase the expression of AR-Vs, which mainly refers to AR-V7 in EnzR CRPC. The splicing factor hnRNPA1, the long non-coding RNA Malat1 (LncRNA Malat1), arginine vasopressin receptor 1a (AVPR1A), and monoamine oxidase-A (MAO-A) will change and impact the expression of AR-V7 [25-27].In addition, some genes which regulate Wnt signaling, such as SOX9 and PRKAR2B can also cause EnzR CRPC [28-30]. All the results reflect that gene mutation is important in the occurrence of EnzR CRPC. Moreover, a review deems new methods like high-throughput next-generation sequencing can promote finding the drug-resistant genes and the mechanisms behind Enz resistance [31].

Bioinformatics analysis can comprehensively analyze the results of multiple high-throughput sequencing and more accurately find differential gene expression in the context of disease occurrence [32]. In this study, we used bioinformatics analysis to identify the key genes and their function in EnzR CRPC. We found 45 DEGs and 10 hub genes. We found a hub gene, CDK6, was highly expressed in EnzR PCa cell lines and PCa patients. Finally, we proved that three potential molecules, namely apigenin, chrysin, and fisetin, can truly decrease the expression of CDK6 and suppress cell proliferation.

CDK6 is a CDK comprising 13 different serine/threonine kinases that become periodically activated when bound to cyclins, their respective regulatory subunits. CDKs influence various important cellular processes, including cell-cycle progression and transcription. Abnormal kinase activation, leading to disordered cell regulation and causes uncontrolled cell proliferation. Therefore, CDKs can lead to cancer occurrence [33]. CDK6 and CDK4, which are highly homologous enzymes, are regarded as classic cell cycle kinases that promote cell proliferation by forming complexes with D-type cyclins at the early G1 phase of the cell cycle [34]. Thus far, it has been established that CDK6 is involved in the occurrence of many tumors. CDK6 malfunction can lead to the occurrence of hematologic malignancies such as acute myeloid leukemia (AML) and T-cell lymphoblastic lymphoma [35, 36]. In addition, CDK6 dysfunction can cause breast cancer and melanoma, as well [37, 38].

The function of CDK6 in PCa has been reported. A study found that baicalin can decrease PCa cell proliferation and this effect would reverse when the expression of CDK6 was upregulated, suggesting that CDK6 promotes proliferation [39]. Another study also found that CDK6 inhibitors (G1T28 and G1T38) had a role in treating CRPC [40]. In addition, CDK6 also reportedly may have a function in the occurrence of EnzR CRPC. The study found that a CDK6 inhibitor, palbociclib, can promote EnzR LNCaP cell death [41]. Although all these notions suggest that CDK6 can cause the occurrence and even the development of PCa, there is no direct evidence reflect the expression of CDK6 in PCa and EnzR CRPC. In our study, we found that CDK6 expression was indeed higher in tumor tissues than in normal tissues. At the same time, it is also expressed highly in EnzR LNCaP and C4-2 than in LNCaP and C4-2 cell lines. Furthermore, we found that three CDK6 inhibitors can decrease the expression of CDK6 and the cell proliferation. Our results directly illustrate that CDK6 mutation may be behind the occurrence of EnzR CRPC. Suppressing CDK6 expression can delay PCa progress. In addition, the result reflected that CDK6 inhibitors can be potential drugs to treat EnzR CRPC in the future.

However, our study had some shortcomings, as well. First, the DEGs and hub genes we found in EnzR CRPC were from EnzR LNCaP. Despite testing the expression of the hub genes in TCGA and CPGEA databases, the result may be different from EnzR CRPC patients’ samples. In addition, as LNCaP cell line cannot reflect as CRPC cell line, the results we found may have biases. Second, except CDK6, GRIP2, PREX2, ITGA1, and LAMB1 were expressed differently in cells samples and the database. However, as their expression showed an opposite trend between cell lines and clinical samples, we did not research their function. They may also be important factors leading to PCa and EnzR CRPC. Third we only verified the expression of the hub genes in one database: GEPIA. This may lead to the results we found not convincing enough. Fourth, the CDK6 inhibitor molecules also have other functions that may cause tumor occurrence. Their function in suppressing EnzR cell proliferation may come from other reasons to some extent. Therefore, further studies are need to verify our finding.

In conclusion, we found 45 DEGs and 10 hub genes in EnzR LNCaP. One hub gene, CDK6, maybe an important factor in the occurrence of PCa and even EnzR CRPC. Three small molecules, namely molecules, apigenin, chrysin, and fisetin, can decrease the expression of CDK6 in EnzR PCa cell lines and suppress cell proliferation. They may also be potential drugs in treating EnzR CRPC in the future.

PCa Prostate cancer

ADT Androgen deprivation therapy

DEGs Differentially expressed genes

AR Androgen receptor

CRPC Castration-resistant prostate cancer

GEO Gene Expression Omnibus

GO Gene oncology

KEGG Kyoto Encyclopedia of Genes and Genomes

PPI Protein-protein interaction

TCGA The Cancer Genome Atlas

GEPIA Gene Expression Profiling Interactive Analysis Platform

CPGEA Chinese Prostate Cancer Genome and Epigenome Atlas

OS Overall survival

DFS Disease-free survival

TNM Tumor-Node-Metastasis

CDK6 Cyclin-dependent kinases6

Ethic approval and consent participate

The study was approved by the ethic committee of Tongji Hospital, School of Medicine, Tongji University (SBKT-2021-220). Each participate volunteered to join and signed the informed consent form.

Consent for publication

Not applicable

Availability of data and materials

The datasets supporting the conclusions of this article are available in the TCGA-PRAD (https://portal.gdc.cancer.gov/) CPGEA (http://www.cpgea.com/) and CMap (https://portals.broadinstitute.org/cmap/) database. Another data can be collected from the corresponding author.

Competing interests

All authors declare that they have no conflict of interest regarding the publication of the paper.

Founding

This study was supported by Natural Science Foundation of Shanghai Municipal Science and Technology Committee (22ZR1456800, 21ZR1458300, 19ZR1448700). Clinical Research Plan of SHDC (NO. SHDC2020CR3074B) and New Frontier Technology Joint Research Project of Shanghai Municipal Hospital (No. SHDC12019112) and Clinical project of Shanghai Municipal Health Commission (NO.20184Y0263, NO.2018Y0105).

Authors’ contributions

Xi Chen and Yechen Wu put forward the idea of the article, wrote the manuscript and analyzed the data. Licheng Wangand Yicong Yao collected the data from public database. Xinan Wang and Chengdang Xu finished the RT-qPCR, Western blot and CCK-8 experiments. Denglong Wu and Gang Wu help collecting the clinical specimens and revised the manuscript.

Acknowledgments

Not applicable

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No competing interests reported.

FigS1.tif
Figure S1: The expression of hub genes in Chinese patients with prostate cancer. (The sequence data from CPGEA database)
FigS2.tif
Figure S2: The expression of CDK6 in different TNM tumor stages of PCa patients depend on TCGA data. (A) The expression of CDK6 in different Tumor (T) stage rely on TNM classification of malignant tumors. (B) The expression of CDK6 in different Node (N) stage rely on TNM classification of malignant tumors. (C) CDK6 expression in different T2 tumor stage patients. (D) CDK6 expression in different T3 tumor stage patients.
Figs3.tif
Figure S3: The overall survival (OS) of hub genes from GEPIA depend on TCGA data. (A) GRIP2 (B) EPHB2 (C) CDK6 (D) PAX6 (E) BMP7 (F) ITGA1 (G) LAMB1 (H) IGFBP5 (I) LY6K
FigS4.tif
Figure S4: The ten CDK6 inhibitors from CMap.
FigS5.tif
Figure S5: The expression of CDK6 in EnzR C4-2 (C4-2R) cell and 22Rv1 cell. (A) The expression of CDK6 in C4-2 and C4-2R cell from GSE151083. (B) The expression of CDK6 in C4-2 and C4-2R cell from GSE136130. (C) The mRNA expression of CDK6 in 22Rv1 cell treated or not treated by Enz. (D) The protein level of CDK6 after 22Rv1 cell treated or not treated by Enz. ** represents P<0.01, *** represents P<0.001. The qRT-PCR and Western blot using β-tubulin as inner control.
FigS6.tif
Figure S6: CDK6 inhibitors can decrease the expression of CDK6 and suppress 22Rv1 cell proliferation. (A) The mRNA expression of CDK6 after 22Rv1 cells treated by CDK6 inhibitors. (B) CDK6 protein level after CDK6 inhibitors treated 22Rv1 cells. (C) 22Rv1 cell proliferation ability after added CDK6 inhibitors. * represents P< 0.05, ** represents P<0.01. The qRT-PCR and Western blot using β-tubulin as inner control.

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CDK6 is upregulated and may be a potential therapeutic target in enzalutamide-resistant castration- resistant prostate cancer by bioinformatic analysis

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Abstract

Figures

Background

Methods

Data Source

Identification of DEGs

GO and KEGG analysis

Construction PPI network and identify hub gene

Detection of hub gene expression

Survival and Clinical value analysis

Screening of potential small molecules

Tissue samples

Cell culture and drug treating

RNA extraction and qRT-PCR

Western blot

Cell proliferation assay

Statistical analysis

Results

DEGs identification

Functional and enrichment analysis

PPI network construction and hub gene finding

Hub gene expression in prostate cancer samples from public database

CDK6 expression in EnzR CRPC cell line

Survival analysis

Screening of potential small molecule drugs

Validation of CDK6 expression in clinical PCa samples and EnzR PCa cell lines

CDK6 inhibitors’ function in PCa, CRPC, and EnzR CRPC cell model

Discussion

Conclusion

Abbreviations

Declarations

Ethic approval and consent participate

Consent for publication

Availability of data and materials

Competing interests

Founding

Authors’ contributions

Acknowledgments

References

Additional Declarations

Supplementary Files

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