Expression and role of CNIH2 in prostate cancer

doi:10.21203/rs.3.rs-4163567/v1

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Expression and role of CNIH2 in prostate cancer

https://doi.org/10.21203/rs.3.rs-4163567/v1

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published 21 Oct, 2024

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Prostate cancer is one of the most common cancers in men and poses a significant threat to global male health. Traditional prostate cancer assessment methods have certain limitations, necessitating the identification of new prognostic factors and treatment targets. Our study revealed that low expression of the CNIH2 gene was associated with a better progression-free survival rate in prostate cancer patients. The area under the ROC curve (AUC) showed that the prognostic ability of the CNIH2 gene was high at 1, 3, and 5 years. The gene was an independent prognostic factor according to multivariate analysis. Functional verification experiments showed that knocking down the CNIH2 gene could inhibit the proliferation, migration and invasion of prostate cancer cells and could also inhibit tumor growth in nude mice. Our study is the first to reveal the important role of the CNIH2 gene in prostate cancer. This discovery provides a new research direction for individualized treatment and prognostic evaluation of prostate cancer.

Biological sciences/Cancer

Health sciences/Medical research

Health sciences/Oncology

Health sciences/Urology

Prostate cancer

CNIH2

Prognosis

Invasion

Migration

Prostate cancer is currently the most common malignant tumor in men worldwide and is one of the most common types of cancer that leads to death ¹. Clinicians have always been committed to finding more effective treatments to help prolong the life of patients with prostate cancer and improve their prognosis. This is both a challenge and an opportunity. Over the past several decades, the treatment landscape for prostate cancer has evolved substantially, with metastatic hormone-sensitive prostate cancer and metastatic castration-resistant prostate cancer emerging as the focal points of ongoing research discussions. These discussions have led to the advent of various novel therapeutic approaches, such as genome-guided strategies, which present numerous possibilities for prostate cancer patients^2,3. Numerous studies have highlighted the pivotal role of the androgen receptor axis in the pathogenesis and progression of prostate cancer, corroborating the principle of androgen deprivation therapy as a fundamental treatment for early-stage metastatic prostate cancer ^4,5. Despite significant progress in prostate cancer treatment over the years, it remains one of the principal malignancies affecting men in the United States, with tens of thousands of people succumbing to the disease annually ¹. Given this scenario, it is essential to continually explore suitable treatment strategies to provide patients with greater hope of survival.

Notably, the primary cause of death from prostate cancer is increased drug resistance to chemotherapy ^6,7. Therefore, there is an urgent need to identify novel treatment strategies that can alleviate the suffering of prostate cancer patients and improve patient prognosis. Prostate cancer is a highly heterogeneous disease, and individualized treatment plans rely extensively on genetic testing. This provides a direction and a thought process to identify predictive biomarkers related to prostate cancer that are effective for specific treatments, with the goal of achieving "precision medicine", i.e., providing the best treatment plan for each patient.

Alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors are glutamate-gated ion channels that transmit signals at the fastest rate among excitatory synapses in mammalian brains. These receptors control signaling between neurons involved in reflexes, behavior, and cognition^8–10. Among the auxiliary subunits of the AMPA receptor (AMPAR), cornichon homolog 2 (CNIH2) significantly slows the inactivation and desensitization of AMPAR in the expression system and shares many other characteristics with transmembrane AMPAR regulatory proteins ^11–16. Dysregulation of AMPARs is associated with numerous disorders, including several neurodegenerative and psychiatric diseases¹⁷. Many AMPA receptor antagonists that block synaptic transmission have been used to treat epilepsy, neurodegenerative diseases, and neuropathic pain (20). These receptors are implicated in the onset of astrocytoma, glioblastoma, breast carcinoma, lung carcinoma, colon adenocarcinoma, and prostate carcinoma^18–22.

Although several studies have shown that CNIH2 plays a crucial role in regulating the expression of AMPA receptors and subsequently impacting the occurrence of neurologic and psychiatric diseases, its precise expression and role in prostate cancer remain largely undefined. In this study, we conducted a comprehensive analysis and systematic research on the expression of CNIH2 in prostate cancer to determine the correlation between CNIH2 and prostate cancer and analyzed its molecular function in prostate cancer, attempting to identify new therapeutic strategies for this disease.

2.1 Prognostic significance of CNIH2

Analysis of the TCGA dataset revealed that patients in the CNIH2-low subgroup exhibited longer PFS than did those in the CNIH2-high subgroup (Fig. 1A). The gene demonstrated robust predictive capability for patient prognosis, with area under the ROC curve (AUC) values of 0.813, 0.761, and 0.748 for 1-year, 3-year, and 5-year survival predictions, respectively (Fig. 1B). Additionally, compared with clinicopathological factors, CNIH2 had the highest predictive capability (Fig. 1C). These findings underscore the strong prognostic potential of CNIH2. According to the univariate Cox regression analysis, CNIH2, T stage, and N stage were significant predictors of patient prognosis (Fig. 1D). However, in the multivariate analysis, only CNIH2 and T stage retained statistical significance, establishing CNIH2 as an independent prognostic factor for patients (Fig. 1E).

2.2 External Validation of the CNIH2 Prognosis

As described in the methods section, the expression levels of the CNIH2 gene were obtained for each patient, and based on the median expression, patients were divided into CNIH2-high and CNIH2-low-expression groups (Table S2). The demographic and clinical characteristics of patients in both the high- and low-expression groups are presented in Table 1 and Table S3. Compared to those in the CNIH2-high subgroup, the T stage in the CNIH2-low subgroup was lower. Furthermore, the median PFS time was longer in the CNIH2-low subgroup (Fig. 2A).

2.3 Independent Prognostic Analysis of External CNIH2 Data

TimeROC curves were constructed, with CNIH2 gene AUC values of 0.823, 0.723, and 0.830 for 1-year, 3-year, and 5-year survival prediction, respectively (Fig. 2B). Additionally, the predictive accuracy of CNIH2 and significant clinicopathological factors were assessed using receiver operating characteristic (ROC) curve analysis, which revealed that CNIH2 had the highest predictive capability for prostate cancer patient prognosis (AUC = 0.803) (Fig. 2C). Subsequently, Cox regression models were used to assess whether the expression of the CNIH2 gene could serve as an independent predictor of prostate cancer prognosis. According to the univariate analysis, CNIH2 gene expression, PSA levels, T stage, Gleason score, and patient age were significantly associated with prognosis (Fig. 2D). However, in the multivariate analysis, only CNIH2 gene expression, T stage, and Gleason score were found to be independent prognostic factors (Fig. 2E). Hence, CNIH2 score emerged as a robust predictor of patient prognosis.

2.4 Functional Validation of CNIH2 In Vitro

The functional role of CNIH2 at the cellular level was investigated by suppressing its expression through shRNA transfection. In the human prostate cancer cell lines DU-145 and PC-3, CNIH2 gene expression was significantly reduced after shRNA transfection, as confirmed by Western blot analysis (Fig. 3A, B). Subsequently, the impact of CNIH2 on the proliferation of prostate cancer cells was explored. Notably, knockdown of the CNIH2 gene significantly inhibited the proliferation of the DU-145 and PC-3 cell lines (Fig. 3C, D). Finally, Transwell assays demonstrated that downregulation of the CNIH2 gene significantly suppressed the migration and invasion of both cell lines (Fig. 3E, F).

2.5 Functional Validation of CNIH2 In Vivo

Tumor formation experiments in nude mice were also conducted to assess the in vivo effect of CNIH2. Subcutaneous grafting models showed that, compared with those in the control group, the growth rate of the tumor tissue in the CNIH2 knockdown group was significantly lower (Fig. 4A, B). After 40 days, the mice were euthanized, and the tumors were dissected and weighed, revealing a significant decrease in tumor volume and weight in the sh-CNIH2 group (volume: 165.13mm³ ± 56.12 vs 336.06mm³ ± 42.28, P < 0.05; weight: 0.224g ± 0.08 vs 0.458g ± 0.06, P < 0.05) (Fig. 4C, D).

In this study, we comprehensively explored the in vitro and in vivo roles of CNIH2 in prostate cancer and its clinical significance; to our knowledge, this is the first systematic investigation of CNIH2 in prostate cancer. Prior to this research, the role of CNIH2 in prostate cancer and cancer in general remained largely unexplored. No prior studies have evaluated the functions of CNIH2 in the context of prostate cancer, both in vitro and in vivo, and none have evaluated its clinical relevance within patient cohorts. We demonstrated that high expression of CNIH2 was associated with poorer PFS using TCGA data and clinical cohorts of prostate cancer patients. Additionally, our study confirmed through cellular experiments that the downregulation of CNIH2 expression suppressed the proliferation, migration, and invasion of prostate cancer cells. Further confirmation of these findings was achieved through xenograft tumor experiments in nude mice, which demonstrated that knockdown of this gene significantly inhibited prostate cancer growth in vivo.

The protein encoded by the CNIH2 gene is a constituent of AMPA-type glutamate receptors, which play crucial roles in neurotransmitter signaling within the nervous system²³. In the context of cancer, these receptors have been implicated in the development of astrocytoma, glioblastoma, breast carcinoma, lung carcinoma, colon adenocarcinoma, and prostate carcinoma^18–22.

The activation of AMPARs is considered a procancer signal. It has been reported that, when activated by glutamate, AMPARs promote the invasion and migration of pancreatic cancer cells through the Kras-MAPK signaling pathway ²⁴. Moreover, AMPARs are expressed in six different small-cell lung cancer cell lines, and the inhibition of AMPARs, either in vivo or in vitro, results in suppressed cell proliferation and reduced MAPK phosphorylation ²⁵. In glioblastoma, AMPARs expressed in glioblastoma cells promote tumor cell proliferation and migration via beta1 integrin-dependent adhesion to the extracellular matrix ²⁶. Previous research has also identified cardiac glycosides as potential candidates for prostate cancer therapy, as these compounds exert anticancer effects. Interestingly, cardiac glycosides, including CNIH2, were found to downregulate the expression of 46 genes, suggesting an oncogenic role for this gene ²⁷. This study indirectly supports the reliability of our research findings. Therefore, one possible mechanism by which CNIH2 contributes to the adverse prognosis of prostate cancer is through its overexpression, which leads to an increase in the quantity or activity of AMPA receptors, thereby enhancing the activation of the AMPA receptor signaling pathway, ultimately resulting in excessive cell proliferation and migration and promoting cancer development and progression.

The androgen receptor axis plays a pivotal role in the pathogenesis and progression of prostate cancer²⁸. D-aspartate not only increases testosterone synthesis by acting on the hypothalamus-pituitary-testis axis but also by directly acting on Leydig cells^29–32. Studies have also shown the involvement of AMPARs in this process³³. Therefore, another potential mechanism by which CNIH2 expression leads to the progression of prostate cancer could be through an increase in AMPAR expression in testicular cells, subsequently leading to increased testosterone synthesis.

While our study unveiled the clinical significance of CNIH2 expression in prostate cancer for the first time, there are certain limitations to be acknowledged. First, despite validation at the gene expression level and in cellular experiments, a more in-depth investigation and elucidation of the detailed functional mechanisms of CNIH2 and its role in prostate cancer are warranted. Second, while a nude mouse xenograft model was used, it has inherent limitations and cannot fully replicate the complex biological environment of humans. Utilizing different types of animal models may enhance the reliability of the results. Future studies could further strengthen our understanding of the role of the CNIH2 gene in prostate cancer, expand the sample size, improve validation methods, and ultimately increase the credibility and clinical applicability of the research through prospective studies.

This study provides initial insights into the potential role and clinical significance of CNIH2 in prostate cancer. High expression of CNIH2 is associated with poorer prognosis, making it a potential biomarker for prognostic assessment in prostate cancer patients. Both in vitro and in vivo experiments confirmed that CNIH2 knockdown can inhibit the proliferation, migration, and invasion of prostate cancer cells, further supporting its potential role in cancer development. Additionally, the association between CNIH2 and AMPAR suggests potential signaling pathways that may influence the progression of prostate cancer. This research offers new insights for personalized treatment, with the potential to improve the therapeutic outcomes of prostate cancer patients. Despite some limitations, these preliminary findings provide a foundation for future in-depth research and clinical applications, bringing new hope to the management of prostate cancer patients.

4.1 Data Acquisition

Fragments per kilobase million gene expression data and corresponding clinical information for prostate cancer patients were obtained from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/). The dataset included a total of 543 individuals, comprising 492 tumor tissue samples and 51 adjacent normal tissue samples. After excluding patients with missing clinical information, a final cohort of 487 prostate cancer tumor patients was included in the study.

4.2 Patient prognostic analysis

Patients were stratified into two groups according to the median expression level of the CNIH2 gene: the CNIH2-high subgroup and the CNIH2-low subgroup. Survival analysis was initially conducted using the "survival" and "survminer" R packages to assess differences in overall survival (OS) between these two patient groups. Subsequently, the "timeROC" R package was used to evaluate the accuracy of CNIH2 in predicting 1-year, 3-year, and 5-year prognoses. Finally, both univariate and multivariate Cox regression analyses were carried out to determine whether CNIH2, when accounting for other clinical factors, served as an independent prognostic factor.

4.3 Clinical Samples

A total of 361 prostate cancer patients who underwent either laparoscopic radical prostatectomy or robot-assisted laparoscopic radical prostatectomy at Shanxi Medical University First Hospital from October 2019 to April 2023 were included in the study. The TNM staging system (8th edition) of the American Joint Committee on Cancer was used for prostate cancer staging. PFS represents the time period between the time after surgical treatment and the absence of biochemical recurrence of prostate cancer. The inclusion criteria for the study were as follows: 1. Patients with prostate cancer were diagnosed by histopathological examination and had no distant metastasis. 2. Complete clinical information, including clinical stage, Gleason score, and prostate-specific antigen (PSA) levels, was obtained. 3. Relevant prognostic information, such as recurrence status data, was obtained. The exclusion criteria were as follows: 1. The presence of other serious diseases, such as other cancers or advanced organ failure, may interfere with the study results. 2. Patient mortality within 30 days after surgery. 3. Poor-quality samples with low RNA extraction yields from paraffin-embedded tissues make accurate gene expression quantification unfeasible. All tumor tissue samples were formalin-fixed and paraffin-embedded. Written informed consent was obtained from all patients, and the study was approved by the Ethics Committee of Shanxi Medical University First Hospital. All experiments were performed in accordance with relevant guidelines and regulations. Our human study was performed following the Declaration of Helsinki.

4.4 Gene expression quantification in patient samples

RNA was extracted from formalin-fixed paraffin-embedded (FFPE) specimens using an FFPE RNA Kit (Omega, USA) following the manufacturer's instructions. Subsequently, the PrimeScript™ RT reagent Kit with gDNA Eraser (Takara, Japan) was used to synthesize cDNA from the extracted RNA. Real-time PCR was performed using the TB Green® Premix Ex Taq™ II (Tli RNaseH Plus) Kit (Takara, Japan) on an Applied Biosystems 7500 Fast Real-Time PCR System. The sequences of primers used for CNIH2 were as follows: forward primer 5'-TCCACCTTTGCAACAAGCTC-3' and reverse primer 5'-CCCAAGTCCTTCTGTGGGAT-3', resulting in a 40 bp product. For beta-actin, the sequences of primers used were as follows: forward primer 5'-CCTTTGCCGATCCGCCG-3' and reverse primer 5'-GATATCATCATCCATGGGGGAGCTGG-3', resulting in a 59 bp product. The 2-ΔΔCt method was used to determine the relative expression level of CNIH2 with respect to that of β-actin. ΔCt represents the difference in Ct values between CNIH2 and β-actin, while ΔΔCt represents the difference in ΔCt values between target samples and the normalized control sample.

4.5 Cell Lines and Culture

The human prostate cancer cell lines DU-145 and PC-3 were procured from Sunncell (Wuhan, China). DU-145 and PC-3 cells were cultured in DMEM supplemented with 10% fetal bovine serum (FBS) and 1% penicillin‒streptomycin. The cells were maintained at 37°C in a 5% CO2 humidified incubator.

4.6 Establishment of SCENIC Stable Knockdown Cell Lines

The lentiviral shRNA vector GV344 was obtained from Genechem (Shanghai, China). DU-145 and PC-3 cells were transfected with lentiviral shRNA and subsequently selected to establish stable DU-145 and PC-3 cell lines with CNIH2 gene knockdown. The shRNA sequences used are listed in Table S1.

4.7 Cell Proliferation Assay

Stable knockdown and control cell lines were routinely cultured. The cells were first suspended in serum-free BSA medium, after which the concentration was adjusted to approximately 5x10^4 cells/ml. Subsequently, the cells were seeded into 6-well cell culture plates and incubated in a 5% CO2 humidified incubator. Cell counts were manually performed at 0, 24, 48, 72, 96, and 120 hours.

4.8 Cell Migration and Invasion Assays

Transwell chambers (BD Biosciences, Franklin Lakes, NJ, USA) with 8 µm pores and Matrigel-coated or uncoated plates were used to conduct cell migration and invasion assays, respectively. Prior to the experiment, the cells were serum starved for 12–24 hours to eliminate the influence of the serum. The cells were then suspended in serum-free BSA culture medium and adjusted to a density of 2x10^4 cells. The upper and lower chambers of the transwell apparatus (24-well cell culture plate) were filled with 200 µL of cell suspension and 500 µL of culture medium containing 10% FBS, respectively. After 24 hours of incubation, the cells that had migrated to the lower surface of the membrane were fixed, stained, and counted under a microscope.

4.9 Tumor Formation Experiment in Nude Mice

Four-week-old BALB/c male nude mice were obtained from Vital River (Beijing, China). Ten mice were randomly assigned to different experimental groups according to the random number table method (n = 5/group). PC-3 cells (PC-3 sh-NC, sh-CNIH2) were suspended in PBS culture medium and adjusted to a concentration of 2x106 cells/ml. Each mouse was subcutaneously injected with 2x106 cells in the flank. Two groups of nude mice were divided into two cages and kept in a specific pathogen free environment by the breeder without knowing the group. Tumor growth was periodically monitored by measuring two perpendicular diameters. Tumor volume was calculated using the formula: volume = 0.52 * length * width^2. Measurements were taken every 4 days and continued until the end of the experiment. After 40 days of observation, the mice were euthanized according to the approved methods, and the tumors were carefully dissected and weighed. The purpose of this experiment was to explore the effect of gene CNIH2 on tumor growth in vivo.

4.10 Statistical analysis

The R (version = 4.2.2) software was used for statistical analysis. Survival rates were assessed using Kaplan‒Meier survival curves, and differences in survival were evaluated using the log-rank test. Single-factor and multiple-factor analyses were carried out using the Cox regression model. Baseline demographic data were subjected to either the chi-square test or Fisher's exact test for categorical variables. For continuous data, Student's t test or the Mann‒Whitney U test was used to determine significant differences. In the nude mouse experiment, the Wilcoxon rank sum test was used to compare the two groups. A p value < 0.05 was considered to indicate statistical significance.

Author Contributions

Study concept and design: XW, WZ, and Zf M. Acquisition of the data: Zh L, Ym Z, and SW. Analysis and interpretation of the data: XW, WZ, Zf M and Cy H. Drafting of the manuscript: WZ, Zh L, Ym Z, Yp M and SW. Statistical analysis: Cy H, XJ and Zf M. Technical support: Cy H, XJ and WZ. All the authors read and approved the final manuscript.

Funding

This work was supported by the Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province, under Grant [20210005]; Shanxi Provincial Basic Applied Research Project, under Grant [20210302124611]; Research Project Supported by Shanxi Scholarship Council of China, under Grant [2021-164]; and Shanxi Province Basic Research Program, under Grant [202303021221211].

Conflict of Interest

The authors declare that they have no competing interests. None of the authors of this manuscript is a current Editor or Editorial Board Member of Cancer Science.

Ethics Statement

Informed Consent: Written informed consent was obtained from all patients.

Registry and the Registration No. of the study/trial: The animal study was approved by the Shanxi Medical University First Hospital (NO.DWYJ-2023-129). Our animal study was reported in accordance with ARRIVE guidelines. The human study was approved by the Ethics Committee of Shanxi Medical University First Hospital (NO.KYYJ-2023-164).

Availability of data and material

The datasets for this study can be found in the https://portal.gdc.cancer.gov/.

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Table 1 is available in the Supplementary Files section.

No competing interests reported.

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Expression and role of CNIH2 in prostate cancer

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Journal Publication

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Abstract

Figures

1 Introduction

2 Results

2.1 Prognostic significance of CNIH2

2.2 External Validation of the CNIH2 Prognosis

2.3 Independent Prognostic Analysis of External CNIH2 Data

2.4 Functional Validation of CNIH2 In Vitro

2.5 Functional Validation of CNIH2 In Vivo

3 Discussion

4 Method

4.1 Data Acquisition

4.2 Patient prognostic analysis

4.3 Clinical Samples

4.4 Gene expression quantification in patient samples

4.5 Cell Lines and Culture

4.6 Establishment of SCENIC Stable Knockdown Cell Lines

4.7 Cell Proliferation Assay

4.8 Cell Migration and Invasion Assays

4.9 Tumor Formation Experiment in Nude Mice

4.10 Statistical analysis

Declarations

Author Contributions

Funding

Conflict of Interest

Ethics Statement

Availability of data and material

References

Tables

Additional Declarations

Supplementary Files

Status:

Journal Publication

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