Prostate Cancer Invasion Research Articles

Exosomal PSM-E inhibits macrophage M2 polarization to suppress prostate cancer metastasis through the RACK1 signaling axis.

It is well-established that understanding the mechanism of prostate cancer (PCa)-associated metastasis is paramount for improving its prognosis. Metastasis is known to involve the communication between tumor-associated macrophages (TAMs) and tumor cells. Exosomes are crucial in mediating this intercellular communication within the tumor microenvironment. Nonetheless, the role of exosomal proteins in PCa metastasis is not yet fully understood. Here, we investigated the mechanisms of prostate cancer-derived exosomal PSM-E on regulating macrophage M2 polarization to suppress tumor invasion and metastasis. PSM-E levels in exosomes were detected by transmission electron microscopy and Western blotting analysis. The diagnostic value of urine-derived exosomal PSM-E in PCa were evaluated by LC-MS/MS, correlation analysis, and ROC curves analysis. The mechanisms underlying the inhibitory effect of exosomal PSM-E on the M2 polarization of macrophages was investigated by co-IP, IHC staining, and PCa tumorigenesis model, etc. RESULTS: We revealed that exosomal PSM-E is upregulated in exosomes derived from the serum and urine of PCa patients. Clinically, an elevated exosomal PSM-E expression in urine is significantly correlated with an advanced pathological tumor stage and a high Gleason score. Our research also revealed that exosomal PSM-E inhibits prostate cancer cell proliferation, invasion, and metastasis by suppressing macrophage polarization in vitro and in vivo. Furthermore, we provided compelling evidence that exosomal PSM-E inhibits M2 polarization of macrophages by recruiting RACK1 and suppressing the FAK and ERK signaling pathways, consequently suppressing PCa invasion and metastasis. Furthermore, we found that the protease-associated domain of PSM-E and the fourth tryptophan-aspartate repeat of RACK1 are crucial for the interaction between PSM-E and RACK1. Notably, exosomes carrying PSM-E from PCa urine could potentially serve as a biomarker for PCa, and targeting exosomal PSM-E may represent a strategy for preventing tumor progression in this patient population.

Research progress on the role of lipoxygenase and its inhibitors in prostate cancer.

Prostate cancer (PCa) has become a common disease among middle-aged and elderly men. The lipoxygenase (LOX) pathway plays a crucial role in the occurrence, development, invasion and metastasis of PCa and is therefore considered a new target for the prevention and treatment of PCa. 5-LOX and 12-LOX have a promoting effect on the occurrence, development, invasion and metastasis of PCa. 15-LOX-2 has an inhibitory effect on PCa. LOX inhibitors can effectively inhibit the metabolic activity of LOX. The research aims to review the mechanism of action and inhibitors of LOX in PCa, in order to provide relevant references for the prevention and treatment of PCa.

EphA2 regulates vascular permeability and prostate cancer metastasis via modulation of cell junction protein phosphorylation.

Prostate cancer morbidity and mortality demonstrate a need for more effective targeted therapies. One potential target is EphA2, although paradoxically, pro- and anti-oncogenic effects have been shown to be mediated by EphA2. We demonstrate that unique activating and blocking EphA2-targeting monoclonal antibodies display opposing tumor-suppressive and oncogenic properties in vivo. To further explore this complexity, we performed detailed phosphoproteomic analysis following ligand-induced EphA2 activation. Our analysis identified altered phosphorylation of 73 downstream proteins related to the PI3K/AKT/mTOR and ERK/MAPK pathways, with the majority implicated in cell junction and cytoskeletal organization, cell motility, and tumor metastasis. We demonstrate that the adapter protein SHB is an essential component in mediating the inhibition of the ERK/MAPK pathway in response to EphA2 receptor activation. Furthermore, we identify the adherence junction protein afadin as an EphA2-regulated phosphoprotein which is involved in prostate cancer migration and invasion.

P022 Lymphovascular invasion in prostate cancer: The significance of PSMA PET/CT

P022 Lymphovascular invasion in prostate cancer: The significance of PSMA PET/CT

P071 The first external validation of the briganti nomogram to predict lymph node invasion in prostate cancer in the UK — updating the nomogram for uk clinical practice

P071 The first external validation of the briganti nomogram to predict lymph node invasion in prostate cancer in the UK — updating the nomogram for uk clinical practice

Characterizing adipocytokine-related signatures for prognosis prediction in prostate cancer.

Prostate cancer (PCa) is a prevalent malignant tumor in males, with a significant incidence of biochemical recurrence (BCR) despite advancements in treatment. Adipose tissue surrounding the prostate, known as periprostatic adipose tissue (PPAT), contributes to PCa invasion through adipocytokine production. However, the relationship between adipocytokine-related genes and PCa prognosis remains understudied. This study was conducted to provide a theoretical basis and serve as a reference for the use of adipocytokine-related genes as prognostic markers in PCa. Transcriptome and survival data of PCa patients from The Cancer Genome Atlas (TCGA) database were analyzed. Differential gene expression analysis was conducted using the DESeq2 and limma packages. Prognostic genes were identified through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. A prognostic model was developed and validated utilizing receiver operating characteristic (ROC) and Kaplan-Meier (K-M) curves. Assessments of immune cell infiltration and drug sensitivity were also carried out. Subsequently, the function of BNIP3L gene in PCa was verified. A total of 47 adipocytokine-related differentially expressed genes (DEGs) were identified. Five genes (PPARGC1A, APOE, BNIP3L, STEAP4, and C1QTNF3) were selected as prognostic markers. The prognostic model demonstrated significant predictive accuracy in both training and validation cohorts. Patients with higher risk scores exhibited poorer survival outcomes. Immune cell infiltration analysis revealed that the high-risk group had increased immune and ESTIMATE scores, while the low-risk group had higher tumor purity. In vitro experiments confirmed the suppressive effects of BNIP3L on PCa cell proliferation, migration, and invasion. The prognostic model independently predicts the survival of patients with PCa, aiding in prognostic prediction and therapeutic efficacy. It expands the study of adipocytokine-related genes in PCa, presenting novel targets for treatment.

Accuracy of MRI in detecting seminal vesicle invasion in prostate cancer: a systematic review and meta-analysis.

To determine the diagnostic test accuracy of multiparametric magnetic resonance imaging (mpMRI) in detecting seminal vesicle invasion (SVI). The Medical Literature Analysis and Retrieval System Online (MEDLINE), PubMed, the Excerpta Medica dataBASE (EMBASE) and Cochrane databases were search up to May 2023. We included studies that investigated the accuracy of mpMRI in detecting SVI when compared to radical prostatectomy specimens as the reference standard. Data extraction was performed by two independent reviewers to construct 2 × 2 tables, as well as patient and study characteristics. The methodological quality of the included studies was assessed with the Quality of Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity and specificity were pooled and presented graphically with summary receiver operator characteristic (SROC) plots. A total of 27 articles with 4862 patients were included for analysis. The summary sensitivity and specificity were 0.57 (95% confidence interval [CI] 0.45-0.68) and 0.95 (95% CI 0.92-0.99), respectively. Meta-regression indicated that there was no evidence that coil strength (P = 0.079), coil type (P = 0.589), year of publication (P = 0.503) or use of the Prostate Imaging-Reporting and Data System (P = 0.873) significantly influenced these results. The summary diagnostic odds ratio was 28.3 (95% CI 15.0-48.8) and the area under the curve for the SROC curve was 0.87. The I2 statistic was a modest 11.9%. In general, methodological quality was good. The use of mpMRI in detecting SVI has excellent specificity but poor sensitivity. Both endorectal coils and magnetic field strength do not significantly impact the accuracy of MRI. These findings suggest that mpMRI cannot reliably rule out SVI in patients with prostate cancer.

Liquiritigenin inhibits the migration, invasion, and EMT of prostate cancer through activating ER stress

Liquiritigenin (LQ) is a monomeric compound found in licorice, a leguminous plant, and has been reported to exhibit antitumor effects in various lines of cancer cells. However, the underlying molecular mechanisms by which LQ exerts its antitumor effects remain largely unknown. In this study, the effects of LQ on the migration, invasion, and epithelial-mesenchymal transition (EMT) of prostate cancer (PCa) cells were investigated. We found that LQ effectively inhibited the migration and invasion of PCa cells in vitro, and this effect was further confirmed in xenograft lung metastasis models. In addition, LQ was found to activate endoplasmic reticulum stress (ER stress) in PCa cells. Further studies found that LQ upregulated the expression of inositol-requiring enzyme type 1α (IRE1). When IRE1 was knocked down, we observed a weakened inhibitory effect of LQ treatment on the migration and invasion of PCa cells. This observation suggests that LQ may inhibit the migration, invasion and EMT of PCa cells through activating the IRE1 branch of ER stress. In conclusion, our research may provide a novel therapeutic strategy for PCa.

Application value of magnetic resonance spectroscopy imaging in the diagnosis of prostate cancer.

Magnetic resonance spectroscopy (MRSI) can distinguish between benign and malignant prostate diseases. This study investigated the potential of MRSI for diagnosing prostate cancer and guiding prostate biopsy. We retrospectively reviewed 234 patients with suspected prostate cancer who underwent MRSI with targeted prostate biopsy. Patients were divided into two groups according to their puncture pathology: prostate cancer (n = 103, 44.02%) and benign prostatic disease (n = 131, 55.98%). The t-test, Mann-Whitney U test, or chi-square test was used to compare the groups. The diagnostic abilities of MRSI, prostate-specific antigen level, digital rectal examination, and magnetic resonance imaging without contrast for prostate cancer were compared using the area under the receiver operating characteristic curve (AUC-ROC); the ARC-ROC values were 0.831, 0.768, 0.692, and 0.656, respectively. The AUC-ROC value for diagnosing prostate cancer using the CC/c ratio was 0.853. CC/c ratio > 0.97 was identified as the optimal threshold for diagnosing prostate cancer (sensitivity, 86.5%; specificity, 78.6%; Youden index, 0.651). Spearman correlation analysis revealed a correlation between the CC/c ratio and Gleason score (r = 0.737, p < 0.001). Using the CC/c ratio of MRSI as an adjunct to targeted prostate biopsy can improve the detection rate of positive biopsies and evaluate prostate cancer invasiveness.

Abstract A008: Proof-of-Concept: A machine learning classifier to impute nativity status in Hispanic/Latino/a/x cancer patients in the California Cancer Registry

Abstract Background: Cancer disparities exist within the Hispanic/Latino/a/x (H/L) population by nativity status. Non-US born H/L colorectal cancer (CRC) patients and Prostate Cancer (PCa) patients in California have a statistically significant lower risk of cancer-specific survival when compared to Non-Hispanic White patients after controlling for confounders. However, birthplace information is largely incomplete in population-based cancer registries. For example, more than 40% of H/L patients have missing information on nativity in the California Cancer Registry (CCR) database. With the goal of better imputing missing birthplace, we built a Machine Learning (ML) model to predict nativity among CCR H/L cancer patients. Methods: H/L cases with primary invasive CRC (n = 75,613) and PCa (n = 93,042) at least 18 years old, diagnosed between 1988 and 2021 contained in the CCR research file were analyzed (46.36% had missing birthplace). A binary indicator variable assigning cases with known birthplace to US-born vs. Non-US born was constructed as the target for prediction. A stratified split by levels of the outcome was used to generate training (70%, n = 63,323) and testing (30%, n = 27,139) datasets. We used a pruned classification tree to perform feature selection, with the 10 features with the highest importance (measured by the overall reduction in impurity for any split containing each feature) used to predict nativity. Missing observations of the quantitative and qualitative features were mean, or mode imputed, respectively. The classification methods considered were classification trees, Random Forest (RF), and Boosting. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and the rate of correctly classified observations. Results: The top three features with the highest importance were the NHIA (NAACCR Hispanic/Latino Identification Algorithm) label, the Hispanic/Spanish identity, and the year of social security number issuance (SSN); the latter is part of a current SSN-based algorithm used to impute nativity status in this population. Classification models showed similar prediction performance. The highest AUC was reported by the RF (AUC = 0.9822), followed by Boosting (AUC = 0.9785), and the pruned classification tree (AUC = 0.9647). A similar rate of correctly classified observations was reported for the Boosting and RF models (∼94%). The RF model ranked feature importance in a similar order as the pruned classification tree. Ultimately, the RF model was the best performing classifier with a sensitivity and specificity of 0.61 and 0.90, respectively. This classifier substantially outperforms the SSN-based algorithm, which reported a correct classification rate of 81%, a sensitivity = 0.54, and a specificity = 0.41 in this dataset. Conclusions: This proof-of-concept analysis showcases a potential for developing a ML model to overcome missing nativity status in H/L cancer patients to enable more accurate classification by nativity in future research using CCR data. Citation Format: Proof-of-Concept: A machine learning classifier to impute nativity status in Hispanic/Latino/a/x cancer patients in the California Cancer Registry. Joel Sanchez Mendez, Lihua Liu, Juan P. Lewinger, Laura Fejerman, Mariana C. Stern [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A008.

Role of contrast agent in evaluation of periprostatic invasion in prostate cancer.

Our study aims to demonstrate the detection of invasion by biparametric prostate MRI (bpMRI). The cases whose histopathological diagnosis was prostate cancer (PCa) and whose mpMRI report was reported as PIRADS 4 and 5 were evaluated retrospectively by two radiologists with different prostate imaging experiences. The images were grouped into two data sets. Dataset-1 was bpMRI, and dataset-2 was mpMRI. Two radiologists first evaluated dataset-1 independently of each other, and 1 month later, dataset-2. They recorded whether there was an invasion and where it was seen in the patients. Then, the results were compared. A total of 75 patients were included in the study. Periprostatic invasion was detected in 33 of the patients. Both the 1st reader and the 2nd reader image detected all the cases with invasion (100%) separately between dataset-1 and set-2. Compatibility for image dataset-1 and dataset-2 between both readers was observed to be excellent. There is no need to use contrast agent to evaluate periprostatic invasion and to have an idea about local staging in PCa patients.

Comprehensive scRNA-seq analysis to identify new markers of M2 macrophages for predicting the prognosis of prostate cancer

Background Prostate cancer (PCa) has become the highest incidence of malignant tumor among men in the world. Tumor microenvironment (TME) is necessary for tumor growth. M2 macrophages play an important role in many solid tumors. This research aimed at the role of M2 macrophages’ prognosis value in PCa. Methods Single-cell RNA-seq (scRNA-seq) data and mRNA expression data were obtained from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA). Quality control, normalization, reduction, clustering, and cell annotation of scRNA-seq data were preformed using the Seruat package. The sub-populations of the tumor-associated macrophages (TAMs) were analysis and the marker genes of M2 macrophage were selected. Differentially expressed genes (DEGs) in PCa were identified using limma and the immune infiltration was detected using CIBERSORTx. Then, a weighted correlation network analysis (WGCNA) was constructed to identify the M2 macrophage-related modules and genes. Integration of the marker genes of M2 macrophage from scRNA-seq data analysis and hub genes from WGCNA to select the prognostic gene signature based on Univariate and LASSO regression analysis. The risk score was calculated, and the DEGs, biological function, immune characteristics related to risk score were explored. And a predictive nomogram was constructed. CCK8, Transwell, and wound healing were used to verify cell phenotype changes after co-cultured. Results A total of 2431 marker genes of M2 macrophage and 650 hub M2 macrophage-related genes were selected based on scRNA-seq data and WGCNA. Then, 113 M2 macrophage-related genes were obtained by overlapping the scRNA-seq data and WGCNA results. Nine M2 macrophage-related genes (SMOC2, PLPP1, HES1, STMN1, GPR160, ABCG1, MAZ, MYC, and EPCAM) were screened as prognostic gene signatures. M2 risk score was calculated, the DEGs, Immune score, stromal score, ESTIMATE score, tumor purity, and immune cell infiltration, immune checkpoint expression, and responses of immunotherapy and chemotherapy were identified. And a predictive nomogram was constructed. CCK8, Transwell invasion, and wound healing further verified that M2 macrophages promoted the proliferation, invasion, and migration of PCa (p < 0.05). Conclusions We uncovered that M2 macrophages and relevant genes played key roles in promoting the occurrence, development, and metastases of PCa and played as convincing predictors in PCa.

Curcumin blunts epithelial-mesenchymal transition to alleviate invasion and metastasis of prostate cancer through the JARID1D demethylation

Prostate cancer (PCa) is one of the most common and prevalent cancers in men worldwide. The majority of PCa-related deaths result from metastasis rather than primary tumors. Several studies have focused on the relationship between male-specific genes encoded on the Y chromosome and PCa metastasis; however, the relationship between the male specific protein encoded on the Y chromosome and tumor suppression has not been fully clarified. Here, we report a male specific protein of this type, the histone H3 lysine 4 (H3K4) demethylase JARID1D, which has the ability to inhibit the gene expression program related to cell invasion, and can thus form a phenotype that inhibits the invasion of PCa cells. However, JARID1D exhibits low expression level in advanced PCa, and which is related to rapid invasion and metastasis in patients with PCa. Curcumin, as a multi-target drug, can enhance the expression and demethylation activity of JARID1D, affect the androgen receptor (AR) and epithelial-mesenchymal transition (EMT) signaling cascade, and inhibit the metastatic potential of castration resistant cancer (CRPC). These findings suggest that using curcumin to increase the expression and demethylation activity of JARID1D may be a feasible strategy to inhibit PCa metastasis by regulating EMT and AR.

Targeting PLOD2 suppresses invasion and metastatic potential in radiorecurrent prostate cancer

BackgroundMetastatic relapse of prostate cancer after radiotherapy is a significant cause of prostate cancer-related morbidity and mortality. PLOD2 is a mediator of invasion and metastasis that we identified as being upregulated in our highly aggressive radiorecurrent prostate cancer cell line.MethodsPatient dataset analysis was conducted using a variety of prostate cancer cohorts. Prostate cancer cell lines were treated with siRNA, or the drug PX-478 prior to in vitro invasion, migration, or in vivo chick embryo (CAM) extravasation assay. Protein levels were detected by western blot. For RNA analysis, RNA sequencing was conducted on PLOD2 knockdown cells and validated by qRT-PCR.ResultsPLOD2 is a negative prognostic factor associated with biochemical relapse, driving invasion, migration, and extravasation in radiorecurrent prostate cancer. Mechanistically, HIF1α upregulation drives PLOD2 expression in our radiorecurrent prostate cancer cells, which is effectively inhibited by HIF1α inhibitor PX-478 to reduce invasion, migration, and extravasation. Finally, the long non-coding RNA LNCSRLR acts as a promoter of invasion downstream of PLOD2.ConclusionsTogether, our results demonstrate for the first time the role of PLOD2 in radiorecurrent prostate cancer invasiveness, and point towards its potential as a therapeutic target to reduce metastasis and improve survival outcomes in prostate cancer patients.

Altered expression and localization of nuclear envelope proteins in a prostate cancer cell system

BackgroundThe nuclear envelope (NE), which is composed of the outer and inner nuclear membranes, the nuclear pore complex and the nuclear lamina, regulates a plethora of cellular processes, including those that restrict cancer development (genomic stability, cell cycle regulation, and cell migration). Thus, impaired NE is functionally related to tumorigenesis, and monitoring of NE alterations is used to diagnose cancer. However, the chronology of NE changes occurring during cancer evolution and the connection between them remained to be precisely defined, due to the lack of appropriate cell models.MethodsThe expression and subcellular localization of NE proteins (lamins A/C and B1 and the inner nuclear membrane proteins emerin and β-dystroglycan [β-DG]) during prostate cancer progression were analyzed, using confocal microscopy and western blot assays, and a prostate cancer cell system comprising RWPE-1 epithelial prostate cells and several prostate cancer cell lines with different invasiveness.ResultsDeformed nuclei and the mislocalization and low expression of lamin A/C, lamin B1, and emerin became more prominent as the invasiveness of the prostate cancer lines increased. Suppression of lamin A/C expression was an early event during prostate cancer evolution, while a more extensive deregulation of NE proteins, including β-DG, occurred in metastatic prostate cells.ConclusionsThe RWPE-1 cell line-based system was found to be suitable for the correlation of NE impairment with prostate cancer invasiveness and determination of the chronology of NE alterations during prostate carcinogenesis. Further study of this cell system would help to identify biomarkers for prostate cancer prognosis and diagnosis.

The Sensitivity and Specificity of Multiparametric Magnetic Resonance Imaging and Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography for Predicting Seminal Vesicle Invasion in Clinically Significant Prostate Cancer: A Multicenter Retrospective Study.

Background/Objectives: The presence of seminal vesicle invasion (SVI) in prostate cancer (PCa) is associated with poorer postoperative outcomes. This study evaluates the predictive value of magnetic resonance imaging (MRI) and prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) for SVI in PCa. Methods: This cohort study included consecutive robotic prostatectomy patients for PCa at three Australian tertiary referral centres between April 2016 and September 2022. MRI and PSMA PET/CT results, clinicopathological variables, including age, BMI, prostate-specific antigen (PSA), PSA density, DRE, Biopsy Gleason score, Positive biopsy cores, PIRADS v2.1 score, MRI volume and MRI lesion size were extracted. The sensitivity, specificity, and accuracy of MRI and PSMA PET/CT for predicting SVI were compared with the histopathological results by receiver operating characteristic (ROC) analysis. Subgroup univariate and multivariate analysis was performed. Results: Of the 528 patients identified, 86 had SVI on final pathology. MRI had a low sensitivity of 0.162 (95% CI: 0.088-0.261) and a high specificity of 0.963 (95% CI: 0.940-0.979). The PSMA PET/CT had a low sensitivity of 0.439 (95% CI: 0.294-0591) and a high specificity of 0.933 (95% CI: 0.849-0.969). When MRI and PSMA PET/CT were used in combination, the sensitivity and specificity improved to 0.514 (95%CI: 0.356-0.670) and 0.880 (95% CI: 0.813-0.931). The multivariate regression showed a higher biopsy Gleason score (p = 0.033), higher PSA (p < 0.001), older age (p = 0.001), and right base lesions (p = 0.003) to be predictors of SVI. Conclusions: MRI and PSMA PET/CT independently underpredicted SVI. The sensitivity and AUC improved when they were used in combination. Multiple clinicopathological factors were associated with SVI on multivariate regression and predictive models incorporating this information may improve oncological outcomes.

The SP1/SNHG16/GLUT1 axis promotes prostate cancer proliferation and invasion by regulating glucose metabolism

IntroductionThe SP1/SNHG16/GLUT1 is involved in diverse cancer-related process. This study was designed to study the role of SP1/SNHG16/GLUT1 axis in prostate cancer (PCa) via modulation of glucose metabolism.Material and methodsThe expression profile of SNHG16 in PCa tissues was obtained from the online public database GEPIA (http://gepia.cancer-pku.cn/). Real-time qPCR was used to ascertain the mRNA expression. To find cellular proliferation and invasion, respectively, CCK-8, transwell, and glycolysis were used to monitor proliferation, invasion, and glycolysis.ResultsAnalysis of GEPIA2 data revealed upregulation of SNHG16 in PCa tissues and a positive association between GLUT1 (SLC2A1) and SP1/SNHG16 expression in the correlation study. Consistently, SPI and SNHG16 were either overexpressed or knocked down in PCa cells to unveil the role of the SP1/SNHG16/GLUT1 axis. Results demonstrated that PC-3 and DU145 cell proliferation were promoted by the overexpression of either SPI or SNHG16. On the other hand, PC-3 and DU145 cell proliferation were reduced upon knockdown of SP1 or SNHG16. A real-time qPCR study revealed that GLUT1 mRNA was upregulated by SP1/SNHG16 overexpression and downregulated by SP1/SNHG16 knockdown. In PCa cells, overexpression of SNHG16/SP1 resulted in enhanced utilization of glucose, lactose, and ATP production, whereas SNHG16/SP1 knockdown had the reverse effect. Lastly, transwell assay results showed that overexpression of SNHG16/SP1 promoted, while knockdown of SNHG16/SP1 inhibited the invasiveness of PC-3 and DU145 PCa cells.ConclusionsCollectively, the SP1/SNHG16/GLUT1 axis regulates the proliferation of PCa cells via the glycolytic route and thus may act as a therapeutic target for PCa treatment.

GPC2 promotes prostate cancer progression via MDK-mediated activation of PI3K/AKT signaling pathway

Prostate cancer is a major medical problem for men worldwide. Advanced prostate cancer is currently incurable. Recently, much attention was paid to the role of GPC2 in the field of oncology. Nevertheless, there have been no investigations of GPC2 and its regulatory mechanism in prostate cancer. Here, we revealed a novel action of GPC2 and a tumor promoting mechanism in prostate cancer. GPC2 was upregulated in prostate cancer tissues and cell lines. Higher expression of GPC2 was correlated with higher Gleason score, lymphatic metastasis, and worse overall survival in prostate cancer patients. Decreased expression of GPC2 inhibited cell proliferation, migration, and invasion in prostate cancer, whereas GPC2 overexpression promoted these properties. Mechanistically, GPC2 promoted the activation of PI3K/AKT signaling pathway through MDK. The rescue assay results in prostate cancer cells demonstrated that overexpression of MDK could attenuate GPC2 knockdown induced inactivation of PI3K/AKT signaling and partly reverse GPC2 knockdown induced inhibition of cell proliferation, migration, and invasion. In all, our study identified GPC2 as an oncogene in prostate cancer. GPC2 promoted prostate cancer cell proliferation, migration, and invasion via MDK-mediated activation of PI3K/AKT signaling pathway. GPC2 might be a promising prognosis predictor and potential therapeutic target in prostate cancer.

Perineural invasion in prostate cancer is associated with Schwann cells and disruption of circadian rhythm-related gene expression: A bioinformatics approach

Schwann cells in the tumor microenvironment are reportedly involved in the production of several factors that benefit cancer cell growth. During this process, Schwann cells are dedifferentiated and facilitate cancer cellular proliferation. The cells then migrate to the region close to the tumor tissue and assist the development of the neoplastic cells. Accordingly, the present study was designed to evaluate the perineural invasion in prostate cancer, in association with disrupted circadian rhythm-related gene expression in Schwann cells. Initially, we identified a database reporting gene expression in Schwann cells in a neoplastic context from the GEO Datasets platform in the GEO repository. The database contains the expression results from experiments in which two factors produced by tumor cells were added to cell cultures. Comparisons were made between samples from the first and third passages. Then, these data were used in differential gene expression analysis and combined with differential expression data of genes upregulated in perineural invasion-negative and -positive prostate cancers. We observed that the &amp;ldquo;axon guidance&amp;rdquo; pathway was upregulated in perineural invasion-negative prostate cancers. Meanwhile, upregulated mRNAs activated the &amp;ldquo;axon guidance&amp;rdquo; pathway and, together with ROBO1 and MPZ upregulation, inhibited perineural invasion pathways. Both genes are also associated with inhibition of Schwann cell migration. PER3, NR3C1, PPARGC1A, TIMP3, ID2, PDE6B, and CAVIN1 were upregulated in perineural invasion-negative tumors, while SLC25A10 was upregulated. We also observed upregulated expression in perineural invasion-positive tumors for genes such as PPARGC1A, TIMP3, S100A8, ID2, DEFB1, AQP3, ASS1, PDE6B, NEFH, and CAVIN1. AQP3 and NEFH were upregulated only in perineural invasion-positive tumors and PER3 and NR3C1 were upregulated only in perineural invasion-negative samples. The findings revealed that circadian rhythm and/or melatonin disruption are associated with dedifferentiation of Schwann cells, which consequently produce a set of factors that drive tumor progression. These processes may also be involved in tumor invasion into the perineural tissue in prostate cancer.

GPCR-Gα13 Involvement in Mitochondrial Function, Oxidative Stress, and Prostate Cancer.

Gα13 and Gα12, encoded by the GNA13 and GNA12 genes, respectively, are members of the G12 family of Gα proteins that, along with their associated Gβγ subunits, mediate signaling from specific G protein-coupled receptors (GPCRs). Advanced prostate cancers have increased expression of GPCRs such as CXC Motif Chemokine Receptor 4 (CXCR4), lysophosphatidic acid receptor (LPAR), and protease activated receptor 1 (PAR-1). These GPCRs signal through either the G12 family, or through Gα13 exclusively, often in addition to other G proteins. The effect of Gα13 can be distinct from that of Gα12, and the role of Gα13 in prostate cancer initiation and progression is largely unexplored. The oncogenic effect of Gα13 on cell migration and invasion in prostate cancer has been characterized, but little is known about other biological processes such as mitochondrial function and oxidative stress. Current knowledge on the link between Gα13 and oxidative stress is based on animal studies in which GPCR-Gα13 signaling decreased superoxide levels, and the overexpression of constitutively active Gα13 promoted antioxidant gene activation. In human samples, mitochondrial superoxide dismutase 2 (SOD2) correlates with prostate cancer risk and prognostic Gleason grade. However, overexpression of SOD2 in prostate cancer cells yielded conflicting results on cell growth and survival under basal versus oxidative stress conditions. Hence, it is necessary to explore the effect of Gα13 on prostate cancer tumorigenesis, as well as the effect of Gα13 on SOD2 in prostate cancer cell growth under oxidative stress conditions.