Prognosis Of Prostate Cancer Research Articles

Allelic variants and immunostaining profile in CXCL12/CXCR4 axis: An investigation of association with prognosis in prostate cancer

Prostate cancer (PCa) is the malignant neoplasm that most commonly affects men and is an important cause of death. It can be detected by changes in serum levels of Prostate Specific Antigen (PSA) and digital rectal examination, but often symptoms do not appear until advanced stages and metastases. The C-X-C Motif Chemokine Ligand 12/C-X-C Motif Chemokine Receptor 4 (CXCL12/CXCR4) axis acts in cell migration and may be involved in the metastatic process. In this context, the aim of this study was to evaluate the allelic variants rs1801157 (CXCL12) and rs2228014 (CXCR4) and the immunostaining of CXCR4 protein as candidates for prognostic markers in PCa. Samples (n = 60) were divided according to prognostic parameters (with and without metastasis at diagnosis) in tree groups: better prognosis, worse prognosis with metastasis at diagnosis and worse prognosis without metastasis at diagnosis, and immunostaining was evaluated by indirect immunohistochemistry, considering tumoral and adjacent tissues from the same patient (n = 120). A significant association was found between the C allele of rs2228014 (CXCR4) and the extraprostatic extension. For CXCR4 immunostaining a weak labeling and a cytoplasmic localization predominated, as well as a significant difference between malignant versus adjacent tissue, with higher protein expression in the malignant tissue. A significant association was found between CXCR4 tumor immunostaining with TNM staging (T2b-T2c) and PSA level (> 20 ng/mL). None of the allelic variants affected CXCR4 immunostaining. Prognostic groups did not differ in allelic variant frequency or immunostaining profile. Findings suggest that CXCR4 receptor may be one of the ways to worsen the prognosis of prostatic cancer.

Prognostic value of cell division cycle-associated protein-3 in prostate cancer.

The study was aimed to explore cell division cycle-associated protein-3 (CDCA3) expression and its correlation with clinicopathological characteristics, and identification of co-expressed genes of CDCA3 in prostate cancer (PCa). Data for CDCA3 mRNA expression in PCa were obtained from The Cancer Genome Atlas database. Furtherly, CDCA3 protein expression was examined by immunohistochemistry in 80 cases, including 20 normal prostate samples and 60 PCa samples. Then we used "survival" package to obtain the differentially expressed CDCA3 mRNA associated with prognosis of PCa patients. "pROC" package was used to analyze receiver operating characteristic of CDCA3. We used chi-square test, Kruskal-Wallis test and Wilcoxon rank sum test to identify clinicopathological parameters that correlated with CDCA3 expression. In order to determine the effects of CDCA3 expression and clinicopathological parameters on survival, univariate cox regression analysis was performed. Finally, the co-expressed genes of CDCA3 in PCa were explored by search tool for the retrieval of interacting genes, Kyoto encyclopedia of genes and genomes enrichment analysis and Spearman correlation analysis. In this study, we found that CDCA3 expression was increased in PCa. PCa patients with higher CDCA3 expression had poor outcomes. In terms of receiver operating characteristic, CDCA3 had an area under the curve of 0.857. High CDCA3 expression was positively correlated with advanced T stage, N stage, Gleason score, and served as an independent predictor of progress free interval in PCa patients. Then 20 proteins closely related to CDCA3 were screened through STRING website. Functional enrichment analysis revealed that, Kyoto encyclopedia of genes and genomes pathway was mainly enriched in cell cycle, including 6 genes, BUB1, CCNA2, CDK1, CDC20, TTK, and CCNB2. CDCA3 is significantly associated with the prognosis of PCa, which may be an indicator of the diagnosis and prognosis of PCa and a new therapeutic target.

The SGLT2 inhibitor canagliflozin suppresses growth and enhances prostate cancer response to radiotherapy

Radiotherapy is a non-invasive standard treatment for prostate cancer (PC). However, PC develops radio-resistance, highlighting a need for agents to improve radiotherapy response. Canagliflozin, an inhibitor of sodium-glucose co-transporter-2, is approved for use in diabetes and heart failure, but is also shown to inhibit PC growth. However, whether canagliflozin can improve radiotherapy response in PC remains unknown. Here, we show that well-tolerated doses of canagliflozin suppress proliferation and survival of androgen-sensitive and insensitive human PC cells and tumors and sensitize them to radiotherapy. Canagliflozin blocks mitochondrial respiration, promotes AMPK activity, inhibits the MAPK and mTOR-p70S6k/4EBP1 pathways, activates cell cycle checkpoints, and inhibits proliferation in part through HIF-1α suppression. Canagliflozin mediates transcriptional reprogramming of several metabolic and survival pathways known to be regulated by ETS and E2F family transcription factors. Genes downregulated by canagliflozin are associated with poor PC prognosis. This study lays the groundwork for clinical investigation of canagliflozin in PC prevention and treatment in combination with radiotherapy.

The Prognosis-Predictive and Immunoregulatory Role of SUMOylation Related Genes: Potential Novel Targets in Prostate Cancer Treatment.

SUMOylation is an important part of post-translational protein modifications and regulates thousands of proteins in a dynamic manner. The dysregulation of SUMOylation is detected in many cancers. However, the comprehensive role of SUMOylation in prostate cancer (PCa) remains unclear. Using 174 SUMOylation-related genes (SRGs) from the MigDSB database and the transcript data of PCa from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we constructed a SUMOylation-related risk score and correlated it with prognosis, tumor mutation burden (TMB), tumor microenvironment (TME) infiltration, and response to chemotherapy and immunotherapy. Moreover, we validated two vital SRGs by RT-qPCR, western blotting, and immunohistochemistry. Two vital SRGs (DNMT3B and NUP210) were finally selected. The risk score based on these genes exhibited excellent predictive efficacy in predicting the biochemical recurrence (BCR) of PCa. A nomogram involving the risk score and T stage was established to further explore the clinical value of the risk score. We found the high-score group was correlated with worse prognosis, higher TMB, a more suppressive immune microenvironment, and a better response to Docetaxel but worse to PD-1/CTLA-4 blockade. Meanwhile, we validated the significantly higher expression level of NUP210 in PCa at mRNA and protein levels. This study elucidated the comprehensive role of SUMOylation-related genes in PCa. Importantly, we highlighted the role of an important SRG, NUP210, in PCa, which might be a promising target in PCa treatment. A better understanding of SUMOylation and utilizing the SUMOylation risk score could aid in precision medicine and improve the prognosis of PCa.

Development of a novel, clinically relevant anoikis-related gene signature to forecast prognosis in patients with prostate cancer.

Introduction: Anoikis is a specific form of programmed cell death and is related to prostate cancer (PC) metastasis. This study aimed to develop a reliable anoikis-related gene signature to accurately forecast PC prognosis. Methods: Based on anoikis-related genes and The Cancer Genome Atlas (TCGA) data, anoikis-related molecular subtypes were identified, and their differences in disease-free survival (DFS), stemness, clinical features, and immune infiltration patterns were compared. Differential expression analysis of the two subtypes and weighted gene co-expression network analysis (WGCNA) were employed to identify clinically relevant anoikis-related differentially expressed genes (DEGs) between subtypes, which were then selected to construct a prognostic signature. The clinical utility of the signature was verified using the validation datasets GSE116918 and GSE46602. A nomogram was established to predict patient survival. Finally, differentially enriched hallmark gene sets were revealed between the different risk groups. Results: Two anoikis-related molecular subtypes were identified, and cluster 1 had poor prognosis, higher stemness, advanced clinical features, and differential immune cell infiltration. Next, 13 clinically relevant anoikis-related DEGs were identified, and five of them (CKS2, CDC20, FMOD, CD38, and MSMB) were selected to build a prognostic signature. This gene signature had a high prognostic value. A nomogram that combined Gleason score, T stage, and risk score could accurately predict patient survival. Furthermore, gene sets closely related with DNA repair were differentially expressed in the different risk groups. Conclusion: A novel, clinically relevant five-anoikis-related gene signature was a powerful prognostic biomarker for PC.

The Prognostic Nutritional Index (PNI): A New Biomarker for Determining Prognosis in Metastatic Castration-Sensitive Prostate Carcinoma.

Prognostic nutritional index (PNI), which is calculated using the albumin level reflecting nutritional status and lymphocyte count reflecting immune status, is useful in showing nutritional and immunological status related to survival and prognosis in many cancers. In this study, we aimed to evaluate the biomarker potential and effect of PNI in determining the prognosis of metastatic castration-sensitive prostate cancer (mCSPC). This retrospective observational study included the complete data of 108 patients with mCPSC who were treated for at least three months between 1 January 2010, and 1 June 2021. The relationships between cancer-specific survival (CSS), overall survival (OS), progression-free survival (PFS), and PNI were evaluated. The Kaplan-Meier method for OS, PFS, and CSS, as well as univariate and multivariate Cox regression models, were used for the statistical analyses. The median age of 108 patients included in the study was 68.54 (61.05-74.19) years. A value of 49.75 was determined to be the best cut-off point for the PNI. OS (months) was found to be significantly lower in patients with low PNI (median: 34.93, 95% CI: 21.52-48.34) than in patients with high PNI (median: 65.60, 95% CI: 39.36-91.83) (p = 0.016). Patients with high PNI (median: 48.20, 95% CI: 34.66-61.73) had significantly better CSS (months) than patients with low PNI (median: 27.86, 95% CI: 24.16-31.57) (p = 0.001). There was no statistically significant difference in PFS between patients with high PNI values (median: 24.60, 95% CI: 10.15-39.05) and patients with low PNI values (median: 20.03, 95% CI: 11.06-29.03) (p = 0.092). The PNI is a good predictor of OS and CSS in patients with mCSPC. The prediction of PFS, albeit showing a trend towards significance, was not statistically significant, probably due to the small number of cases.

A Prognostic Model for Prostate Cancer Patients Based on Two DNA Damage Response Mutation-Related Immune Genes.

Background: DNA damage response (DDR) mutation-related genes and composition of immune cells are core factors affecting the effectiveness of immune checkpoint inhibitor therapy. The aim of this study is to combine DDR with immune-related genes to screen the prognostic signature for prostate cancer (PCa). Methods: Gene expression profile and somatic mutation were downloaded from The Cancer Genome Atlas (TCGA). DDR-related genes were obtained from published study. After identification of prognostic-related DDR genes, samples were divided into mutation and nonmutation groups. Differentially expressed genes between these two groups were screened, followed by selection of immune-related DDR genes. Univariate and multivariate Cox analyses were performed to screen genes for constructing prognostic model. Nomogram model was also developed. The expression level of signature was detected by quantitative real-time PCR (qPCR). Results: Two genes (MYBBP1A and PCDHA9) were screened to construct the prognostic model, and it showed good risk prediction of PCa prognosis. Survival analysis showed that patients in high-risk group had worse overall survival than those in low-risk group. Cox analyses indicated that risk score could be used as an independent prognostic factor for PCa. qPCR results indicated that MYBBP1A was upregulated, whereas PCDHA9 was downregulated in PCa cell lines. Conclusions: A prognostic model based on DDR mutation-related genes for PCa was established, which serves as an effective tool for prognostic differentiation in patients with PCa.

An anoikis-related gene signature for prediction of the prognosis in prostate cancer.

This study presents a novel approach to predict postoperative biochemical recurrence (BCR) in prostate cancer (PCa) patients which involves constructing a signature based on anoikis-related genes (ARGs). In this study, we utilised data from TCGA-PARD and GEO databases to identify specific ARGs in prostate cancer. We established a signature of these ARGs using Cox regression analysis and evaluated their clinical predictive efficacy and immune-related status through various methods such as Kaplan-Meier survival analysis, subject work characteristics analysis, and CIBERSORT method. Our findings suggest that these ARGs may have potential as biomarkers for prostate cancer prognosis and treatment. To investigate the biological pathways of genes associated with anoikis, we utilised GSVA, GO, and KEGG. The expression of ARGs was confirmed by the HPA database. Furthermore, we conducted PPI analysis to identify the core network of ARGs in PCa. Based on analysis of the TCGA database, a set of eight ARGs were identified as prognostic signature genes for prostate cancer. The reliability and validity of this signature were well verified in both the TCGA and GEO codifications. Using this signature, patients were classified into two groups based on their risk for developing BCR. There was a significant difference in BCR-free time between the high and low risk groups (P < 0.05).This signature serves as a dependable and unbiased prognostic factor for predicting biochemical recurrence (BCR) in prostate cancer (PCa) patients. It outperforms clinicopathological characteristics in terms of accuracy and reliability. PLK1 may play a potential regulatory role as a core gene in the development of prostate cancer. This signature suggests the potential role of ARGs in the development and progression of PCa and can effectively predict the risk of BCR in PCa patients after surgery. It also provides a basis for further research into the mechanism of ARGs in PCa and for the clinical management of patients with PCa.

Prostate Cancer: Genetics, Epigenetics and the Need for Immunological Biomarkers.

Epidemiological data highlight prostate cancer as a significant global health issue, with high incidence and substantial impact on patients' quality of life. The prevalence of this disease is associated with various factors, including age, heredity, and race. Recent research in prostate cancer genetics has identified several genetic variants that may be associated with an increased risk of developing the disease. However, despite the significance of these findings, genetic markers for prostate cancer are not currently utilized in clinical practice as reliable indicators of the disease. In addition to genetics, epigenetic alterations also play a crucial role in prostate cancer development. Aberrant DNA methylation, changes in chromatin structure, and microRNA (miRNA) expression are major epigenetic events that influence oncogenesis. Existing markers for prostate cancer, such as prostate-specific antigen (PSA), have limitations in terms of sensitivity and specificity. The cost of testing, follow-up procedures, and treatment for false-positive results and overdiagnosis contributes to the overall healthcare expenditure. Improving the effectiveness of prostate cancer diagnosis and prognosis requires either narrowing the risk group by identifying new genetic factors or enhancing the sensitivity and specificity of existing markers. Immunological biomarkers (both circulating and intra-tumoral), including markers of immune response and immune dysfunction, represent a potentially useful area of research for enhancing the diagnosis and prognosis of prostate cancer. Our review emphasizes the need for developing novel immunological biomarkers to improve the diagnosis, prognosis, and management of prostate cancer. We highlight the most recent achievements in the identification of biomarkers provided by circulating monocytes and tumor-associated macrophages (TAMs). We highlight that monocyte-derived and TAM-derived biomarkers can enable to establish the missing links between genetic predisposition, hormonal metabolism and immune responses in prostate cancer.

Single-cell and bulk RNA sequencing reveal cancer-associated fibroblast heterogeneity and a prognostic signature in prostate cancer.

Cancer-associated fibroblasts (CAFs), the central players in the tumor microenvironment (TME), can promote tumor progression and metastasis via various functions. However, the properties of CAFs in prostate cancer (PCa) have not been fully assessed. Therefore, we aimed to examine the CAF characteristics in PCa and construct a CAF-derived signature to predict PCa prognosis. CAFs were identified using single-cell RNA sequencing (scRNA-seq) data from 3 studies. We performed the FindAllMarkers function to extract CAF marker genes and constructed a signature to predict the biochemical relapse-free survival (bRFS) of PCa in the Cancer Genome Atlas (TCGA) cohort. Subsequently, different algorithms were applied to reveal the differences of the TME, immune infiltration, treatment responses in the high- and low-risk groups. Additionally, the CAF heterogeneity was assessed in PCa, which were confirmed by the functional enrichment analysis, gene set enrichment analysis (GSEA), and AUCell method. The scRNA-seq analysis identified a CAF cluster with 783 cells and determined 183 CAF marker genes. Cell-cell communication revealed extensive interactions between fibroblasts and immune cells. A CAF-related prognostic model, containing 7 genes (ASPN, AEBP1, ALDH1A1, BGN, COL1A1, PAGE4 and RASD1), was developed to predict bRFS and validated by 4 independent bulk RNA-seq cohorts. Moreover, the high-risk group of the signature score connected with an immunosuppressive TME, such as a higher level of M2 macrophages and lower levels of plasma cells and CD8+ T cells, and a reduced reaction rate for immunotherapy compared with low-risk group. After re-clustering CAFs via unsupervised clustering, we revealed 3 biologically distinct CAF subsets, namely myofibroblast-like CAFs (myCAFs), immune and inflammatory CAFs (iCAFs) and antigen-presenting CAFs (apCAFs). In conclusion, the CAF-derived signature, the first of its kind, can effectively predict PCa prognosis and serve as an indicator for immunotherapy. Furthermore, our study identified 3 CAF subpopulations with distinct functions in PCa.

Comprehensively analysis of splicing factors to construct prognosis prediction classifier in prostate cancer.

Splicing factors (SFs) are proteins that control the alternative splicing (AS) of RNAs, which have been recognized as new cancer hallmarks. Their dysregulation has been found to be involved in many biological processes of cancer, such as carcinogenesis, proliferation, metastasis and senescence. Dysregulation of SFs has been demonstrated to contribute to the progression of prostate cancer (PCa). However, a comprehensive analysis of the prognosis value of SFs in PCa is limited. In this work, we systematically analysed 393 SFs to deeply characterize the expression patterns, clinical relevance and biological functions of SFs in PCa. We identified 53 survival-related SFs that can stratify PCa into two de nove molecular subtypes with distinct mRNA expression and AS-event expression patterns and displayed significant differences in pathway activity and clinical outcomes. An SF-based classifier was established using LASSO-COX regression with six key SFs (BCAS1, LSM3, DHX16, NOVA2, RBM47 and SNRPN), which showed promising prognosis-prediction performance with a receiver operating characteristic (ROC) >0.700 in both the training and testing datasets, as well as in three external PCa cohorts (DKFZ, GSE70769 and GSE21035). CRISPR/CAS9 screening data and cell-level functional analysis suggested that LSM3 and DHX16 are essential factors for the proliferation and cell cycle progression in PCa cells. This study proposes that SFs and AS events are potential multidimensional biomarkers for the diagnosis, prognosis and treatment of PCa.

Low-dose antimony exposure promotes prostate cancer proliferation by inhibiting ferroptosis via activation of the Nrf2-SLC7A11-GPX4 pathway

Antimony (Sb) is a typical environmental pollutant. With the development of industrialization, antimony is widely used in daily life and enters the human body through the food chain, water source, air pollution, and other channels. The risk of antimony exposure has emerged as one of the public's major health concerns. Current research on antimony shows that antimony has certain biological toxicity, and antimony exposure may be one of the carcinogenic risk factors for bladder cancer, prostate cancer (PCa), and other cancers. But the molecular mechanism of antimony exposure in PCa is still unclear. Our results showed that serum antimony levels were significantly higher in PCa patients than in benign prostatic hyperplasia (BPH), and high levels of serum antimony were associated with poorer prognosis in PCa. We demonstrate that antimony exposure promotes PCa progression in vivo and in vitro. In addition, our results also showed that low-dose antimony exposure resulted in increased GSH, increased GPX4 expression, and decreased Fe2+. Since GPX4 and Fe2+ are important molecular features in the mechanism of ferroptosis, we further found that low-dose antimony exposure can inhibit RSL3-induced ferroptosis and promote PCa proliferation. Finally, our study demonstrates that low-dose antimony exposure promotes Nrf2 expression, increases the expression level of SLC7A11, and then increases the expression of GPX4, inhibits ferroptosis, and promotes PCa progression. Taken together, our experimental results suggest that low-dose antimony exposure promotes PCa cell proliferation by inhibiting ferroptosis through activation of the Nrf2-SLC7A11-GPX4 pathway. These findings highlight the link between low-dose antimony exposure and the Nrf2-SLC7A11-GPX4 ferroptosis pathway, providing a new potential direction for the prevention and treatment of PCa.

Two cases of prostate cancer with disseminated carcinomatosis of the bone marrow treated with novel hormonal agents

IntroductionDisseminated carcinomatosis of the bone marrow in prostate cancer is rare and has a poor prognosis. Although strong evidence suggests that novel hormonal agents improve the prognosis of metastatic prostate cancer, their effectiveness in cases of disseminated carcinomatosis of the bone marrow remains unclear.Case presentationWe encountered two cases of prostate cancer with disseminated carcinomatosis of the bone marrow at the time of initial diagnosis. One patient was treated with enzalutamide, abiraterone, docetaxel, cabazitaxel, denosumab, and radium‐223 and died 38 months after the initial diagnosis. The other patient was treated with apalutamide and denosumab, and had progression‐free survival for 17 months after the initial diagnosis.ConclusionThese results suggest that novel hormonal agents may improve the prognosis of prostate cancer even in patients with disseminated carcinomatosis of the bone marrow.

The Relationship Between Lymphocyte Subtypes with Clinicopathological Features and Prognosis of Prostate Cancer in Patients Undergoing Radical Prostatectomy.

The immune system has an essential role in the development of cancer by showing both anti-tumor and pro-tumor activities. Understanding the immune func- tion of patients with malignancy is of clinical importance for the evaluation, treatment, and prognosis of the disease. We aimed to evaluate lymphocyte subtypes in peripheral blood samples of prostate cancer patients and their relationship with clinicopathologi- cal features and prognosis. One hundred thirty-seven patients who underwent open radical prosta- tectomy were included in our study. The percentages of CD3+T lymphocyte, CD19+ B lymphocyte, CD16/56 natural killer cells, CD4+ helper T lymphocyte, CD8+ cytotoxic T lymphocyte, and CD45 total lymphocyte were evaluated for each patient using the blood sample taken into a hemogram tube before surgery. The pathological stage was T2 for 64 of the cases and T3 for 73. The mean follow-up period of the patients was 12.81 ± 6.20 months. The CD3+/CD4+ counts of the patients with pathological stage T2 were found to be statistically significantly higher than stage T3. There was a statistically significant negative correlation between the prostate-specific antigen levels and CD3+/CD4+ percentages of the patients. There was no statistical significance between the percentages of lymphocyte subtypes and the presence of surgical margin, biochemical recurrence, adjuvant therapy, and cancer upgrade. We consider that the increase in the pathological stage and prostate-spe- cific antigen value and the decrease in the number of CD4+ T lymphocyte subtypes may be prognostic markers in prostate cancer patients.

Peripheral Blood CD8+ T-Lymphocyte Subsets Are Associated with Prognosis in Prostate Cancer Patients

Background: Various studies have reported associations between frequencies of total peripheral blood lymphocytes and prostate cancer prognosis, but none so far has addressed the prognostic role of CD8+ T-lymphocyte subsets. Methods: A total of 43 prostate cancer patients with metastatic disease and 81 patients with non-metastatic disease were included in this study. Flow cytometry analyses were employed for determining the frequencies of peripheral CD8+ T-lymphocyte subsets. Results: Statistically significant lower levels of terminally differentiated effector (TEMRA) cells in patients with non-metastatic disease vs. patients with metastatic disease were observed. Central memory (CM) and effector memory (EM) CD8+ subsets, were found to be significantly higher in patients with non-metastatic disease vs. patients with metastatic disease. A similar profile was revealed when these CD8+ subsets were analyzed based on the patients’ Gleason scores, as well as by combined disease stage (i.e., non-metastatic vs. metastatic disease) and Gleason score. Conclusions: Peripheral blood-derived CD8+ T-lymphocyte memory subsets could function as biomarkers for the prognosis of PCa.

Environmental explanation of prostate cancer progression based on the comprehensive analysis of perfluorinated compounds

Perfluorinated compounds (PFCs) are man-made chemicals used in the manufacture of many products with water and dirt repellent properties. Many diseases have been proved to be related to the exposure of PFCs, including breast fibroadenoma, hepatocellular carcinoma, breast cancer and leydig cell adenoma. However, whether the PFCs promote the progression of prostate cancer remains unclear. In this work, through comprehensive bioinformatics analysis, we discovered the correlation between the prostate cancer and five PFCs using Comparative Toxicogenomics Database (CTD), Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. In addition, further analysis showed that several PFCs-related genes demonstrated strong prognostic value for prostate cancer patients. The survival analysis and receiver operating characteristic (ROC) curves revealed that PFCs-related genes based prognostic model held great predictive value for the prognosis of prostate cancer, which could potentially serve as an independent risk factor in the future. In vitro experiments verified the promotive role of perfluorooctanoic acid (PFOA) and perfluorononanoic acid (PFNA) in the growth of prostate cancer cells. This study provided novel insights into understanding the role of PFCs in prostate cancer and brought attention to the environmental association with cancer risks and progression.

Identification of a novel stemness-related signature with appealing implications in discriminating the prognosis and therapy responses for prostate cancer

PurposeCancer stemness represents the tumor-initiation and self-renewal potentials of cancer stem cells. It is involved in prostate cancer progression and resistance to therapy. Herein, we aimed to unveil the stemness features, establish a novel prognostic model, and identify potential therapeutic targets. Methods26 stemness-related signatures were obtained from StemChecker. The expression profiles and clinical traits of TCGA-PRAD were obtained from TCGA and cBioPortal, respectively. GSE5446 and GSE70769 cohorts were acquired from GEO. PRAD_MSKCC cohort was also retrieved via the cBioPortal. The consensus clustering method was used for stemness subclusters classification. WGCNA was used to identify hub genes related to the stemness subcluster. The most important feature was explored in vitro. ResultsProstate cancer patients of TCGA-PRAD were divided into two subclusters (C1 and C2) based on the enrichment scores of the 26 stemness-related signatures. C1 was characterized by decreased survival, rich infiltrations of M0 macrophages and regulatory T cells, minimum sensitivity to chemotherapy, and a low response to immunotherapy. Hub genes of the red module with the highest correlation with C1 were subsequently identified by WGCNA and subjected to stemness-related risk model construction based on the machine-learning framework. Prostate cancer patients with high stemness scores had unfavorable prognosis, immunosuppressive tumor microenvironment, minimum sensitivity to chemotherapy, and a low response to immunotherapy. MXD3, the most important factor of the model, can regulate the stemness traits of prostate cancer cells. ConclusionsOur study depicted the stemness landscapes of prostate cancer and characterized two subclusters with diverse prognoses and tumor immune microenvironments. A stemness-risk signature was developed and demonstrated prospective implications in predicting prognosis and precision medicine.

C reactive protein/Albumin ratio as predictor of prognosis in castration resistant metastatic prostate cancer.

To assess the association of C reactive protein/Albumin ratio (CAR) with progression free survival (PFS) and overall survival (OS) in castration resistant metastatic prostate cancer (mCRPC) patients. A transversal study was conducted, including all patients diagnosed with mCRPC within a Central Hospital Urological Oncology consultation between December 2019 and December 2021 (n = 178) and that were submitted to systemic therapy. CRP and albumin results were collected at the beginning of the systemic treatment for mCRPC in 103 patients and, in 75 patients already under treatment at the start of the study, on that occasion (December 2019). All patients were then followed. CAR was correlated with PFS and OS. OS and PFS were measured from the day the CRP and Alb were collected until the event of interest or the final date of follow-up. The sample was divided in two groups according to an optimal cutoff point found in a ROC curve. The sample showed a median age of 75.76 ± 9.17 years old. Using a cut-off point of 0.22, patients with a CAR ≤ 0.22 (63.2%) showed, compared to CAR > 0.22, longer PFS (15.92 vs. 9.46 months, r = -0.13, p < 0.05) and OS (p = < 0.05, 25,72 vs. 15.79 months, r = -0,24, p < 0.05). Better OS in patients with CAR ≤ 0.22 vs > 0.22 was detected on both the group evaluated at the beginning of systemic treatment (26.96 vs 17.63 months, p < 0.05) and the group of patients already under treatment (23.90 vs 11.54 months, p < 0.05). Dividing the sample according to the first line treatment chosen, we found OS of 26.25 vs 5.9 months (p < 0.05), 27.71 vs 22.57 months (p < 0.05) and 27.36 vs 23.75 months (p = 0.12), for docetaxel, abiraterone and enzalutamide, respectively. According to this study, higher values of CAR are associated with lower PFS and OS in mCRPC patients. We found a cut-off value of 0.22 providing the best discrimination for prognosis. CAR is a good prognosis biomarker, irrespective of the moment of evaluation and chosen treatment option.

High SLC20A1 Expression Indicates Poor Prognosis in Prostate Cancer.

High expression of solute carrier family 20 member 1 (SLC20A1) indicates poor clinical outcomes for patients with breast cancer subtypes treated with endocrine therapy and radiotherapy. However, the association between SLC20A1 expression and clinical outcomes in prostate cancer remains to be determined. Open-source datasets (The Cancer Genome Atlas prostate, Stand Up to Cancer-Prostate Cancer Foundation Dream Team, and The Cancer Genome Atlas PanCancer Atlas) were downloaded and analyzed. SLC20A1 expression was analyzed in prostate cancer and normal prostate tissue. Survival analysis using Kaplan-Meier curves and Cox regression analysis were performed to examine patient prognosis, as well as the effects of endocrine therapy and radiotherapy on high SLC20A1 expression in patients with prostate cancer. SLC20A1 was higher in prostate cancer than in normal prostate tissues. High SLC20A1 expression predicted poor disease-free and progression-free survival. Following endocrine therapy, no significant difference in prognosis was observed between patients with high SLC20A1 and those with low SLC20A1 expression. However, following radiotherapy, high SLC20A1 expression tended to be associated with a poor clinical outcome. SLC20A1 may serve as a prognostic biomarker for prostate cancer, and the recommended treatment for patients with high SLC20A1 expression is endocrine therapy.

A novel carboxyl polymer-modified upconversion luminescent nanoprobe for detection of prostate-specific antigen in the clinical gray zonebase by flow immunoassay strip.

Prostate specific antigen (PSA) is a widely-used biomarker for the diagnosis, screening, and prognosis of prostate cancer (PCa). It is critical to develop a rapid and convenient method to accurately detect PSA levels, especially when the PSA levels are in the clinical gray area of 4-10ng/mL. We developed a novel upconversion nanoparticle (UCNP)-based fluorescence lateral flow test strip for qualitatively and quantitatively detecting PSA. The carboxyl group-modified UCNPs (UCNP-COOH) were labeled with anti-PSA antibodies via 1-ethyl-3-(3-(dimethylamino)propyl) carbodiimide (EDC) and N-hydroxysuccinimide (NHS) as labeling probes to recognize PSA. The fluorescence intensity of the UCNP-probe was then measured with a laser fluorescence scanner. A total of 1397 serum and 20 fingertip blood samples were collected to validate the UCNP strip. A reliable correlation between the area ratio (TC), reflecting the fluorescence intensity of the test/control line, and the PSA concentration was observed (r=0.9986). The dose-dependent luminescence enhancement showed good linearity in the PSA concentration range from 0.1 to 100.0ng/mL with a detection limit of 0.1ng/mL. Our UCNP POCT strip demonstrated excellent accuracy, anti-interference and stability in the gray zone (4-10ng/mL) of PSA clinical application and outperformed other PSA test strips. The UCNP strip showed good consistency with the Roche chemiluminescence assay in 1397 serum samples. It also showed good performance for PSA detection using fingertip blood samples. This novel UCNP-based test strip could be a sensitive and reliable POCT assay to detect PSA, facilitating the diagnosis and surveillance of PCa.