Limitations of Prostate-specific Antigen Testing After a Prostate Cancer Diagnosis

Synthesis and preclinical evaluation of 68Ga-labeled PSMA tracers with improved pharmacological properties

Prostate cancer (PCa) is one of the most common tumors in men, with the overexpression of prostate-specific membrane. In this study, we developed four new 68Ga-labeled PSMA-targeting tracers by introducing quinoline, phenylalanine and decanoic acid groups to enhance their lipophilicity, strategically limiting their metabolic pathway through the urinary system. Four radiotracers were synthesized with radiochemical purity >95 %, and exhibited high stability in vivo and in vitro. The inhibition constants (Ki) of SDTWS01-04 to PSMA were in the nanomolar range (<10 nM). Micro PET/CT imaging and biodistribution analysis revealed that 68Ga-SDTWS01 enabled clear tumor visualization in PET images at 1.5 h post-injection, with excellent pharmacokinetic properties. Notably, the kidney uptake of 68Ga-SDTWS01 significantly reduced, with higher tumor-to-kidney ratio (0.36 ± 0.02), tumor-to-muscle ratio (24.31 ± 2.10), compared with 68Ga-PSMA-11 (T/K: 0.15 ± 0.01; T/M: 14.97 ± 1.40), suggesting that 68Ga-SDTWS01 is a promising radiotracer for the diagnosis of PCa. Moreover, SDTWS01 with a chelator DOTA could also label 177Lu and 225Ac, which could be used for the treatment of PCa.

Aberrant expression of GATA3 in metastatic adenocarcinoma of the prostate: an important pitfall

AIMS

The distinction of high-grade prostate cancer (PCa) from poorly differentiated urothelial carcinoma (UC) can be somewhat challenging on clinical and morphological grounds alone, yet it is of great importance for prognostication and choice of treatment. GATA3 is a useful immunohistochemical marker to confirm urothelial origin. However, recent works report strong GATA3 immunoexpression in primary high-grade PCa. The aim of this study was to explore GATA3 expression specifically in metastatic PCa.

METHODS AND RESULTS

The pathology databases of four tertiary institutions were queried for cases of metastatic PCa. Available slides and clinical records were reviewed by experienced genitourinary pathologists. Prostatic markers (PSA, PSAP, NKX3.1) and GATA3 immunohistochemistry were performed. A total of 163 metastatic PCa cases were included. At least one prostate marker was positive in each case of non-regional distant metastasis, confirming prostatic origin. GATA3 strong staining was found in four (2.5%) cases: two liver, one bone and one non-regional lymph-node metastases. All four patients had Grade Group 5 PCa at the initial diagnosis. The metastatic prostatic adenocarcinomas were solid, either with no gland formation (n = 3) or with only focal cribriforming (n = 1).

CONCLUSIONS

To our knowledge, this is the first study exploring GATA3 expression specifically in metastatic PCa. Despite being infrequent, GATA3 positivity in high-grade PCa may lead to misdiagnosis, with clinical implications. We recommend a panel of immunohistochemical markers, both prostatic and urothelial, for ruling out UC, either in primary tumour samples or in the event of metastases of unknown primary, when a genitourinary origin is suspected.

Portable and Rapid Dual-Biomarker Detection Using Solution-Gated Graphene Field Transistors in the Accurate Diagnosis of Prostate Cancer

Prostate-specific antigen (PSA) is the common serum-relevant biomarker for early prostate cancer (PCa) detection in clinical diagnosis. However, it is difficult to accurately diagnose PCa in the early stage due to the low specificity of PSA. Herein, a new solution-gated graphene field transistor (SGGT) biosensor with dual-gate for dual-biomarker detection is designed. The sensing mechanism is that the designed aptamers immobilized on the surface of the gate electrodes can capture PSA and sarcosine (SAR) biomolecules and induce the capacitance changes of the electric double layers of SGGT. The limit of detections of PSA and SAR biomarkers can reach 0.01 fg mL-1 , which is three-to-four orders of magnitude lower than previously reported assays. The detection time of PSA and SAR is ≈4.5 and ≈13 min, which is significantly faster than the detection time (1-2 h) of conventional methods. The clinical serum samples testing demonstrates that the biosensor can distinguish the PCa patients from the control group and the diagnosis accuracy can reach 100%. The SGGT biosensor can be integrated into the portable platform and the diagnostic results can directly display on the smartphone/Pad. Therefore, the integrated portable platform of the biosensor can distinguish cancer types through the dual-biomarker detection.

Comprehensive Overview the Role of Glycosylation of Extracellular Vesicles in Cancers

Extracellular vesicles (EVs) are membranous structures secreted by various cells carrying diverse biomolecules. Recent advancements in EV glycosylation research have underscored their crucial role in cancer. This review provides a global overview of EV glycosylation research, covering aspects such as specialized techniques for isolating and characterizing EV glycosylation, advances on how glycosylation affects the biogenesis and uptake of EVs, and the involvement of EV glycosylation in intracellular protein expression, cellular metastasis, intercellular interactions, and potential applications in immunotherapy. Furthermore, through an extensive literature review, we explore recent advances in EV glycosylation research in the context of cancer, with a focus on lung, colorectal, liver, pancreatic, breast, ovarian, prostate, and melanoma cancers. The primary objective of this review is to provide a comprehensive update for researchers, whether they are seasoned experts in the field of EVs or newcomers, aiding them in exploring new avenues and gaining a deeper understanding of EV glycosylation mechanisms. This heightened comprehension not only enhances researchers' knowledge of the pathogenic mechanisms of EV glycosylation but also paves the way for innovative cancer diagnostic and therapeutic strategies.

A Novel Secreted Protein-Related Gene Signature Predicts Overall Survival and Is Associated With Tumor Immunity in Patients With Lung Adenocarcinoma

Secreted proteins are important proteins in the human proteome, accounting for approximately one-tenth of the proteome. However, the prognostic value of secreted protein-related genes has not been comprehensively explored in lung adenocarcinoma (LUAD). In this study, we screened 379 differentially expressed secretory protein genes (DESPRGs) by analyzing the expression profile in patients with LUAD from The Cancer Genome Atlas database. Following univariate Cox regression and least absolute shrinkage and selection operator method regression analysis, 9 prognostic SPRGs were selected to develop secreted protein-related risk score (SPRrisk), including CLEC3B, C1QTNF6, TCN1, F2, FETUB, IGFBP1, ANGPTL4, IFNE, and CCL20. The prediction accuracy of the prognostic models was determined by Kaplan–Meier survival curve analysis and receiver operating characteristic curve analysis. Moreover, a nomogram with improved accuracy for predicting overall survival was established based on independent prognostic factors (SPRrisk and clinical stage). The DESPRGs were validated by quantitative real-time PCR and enzyme-linked immunosorbent assay by using our clinical samples and datasets. Our results demonstrated that SPRrisk can accurately predict the prognosis of patients with LUAD. Patients with a higher risk had lower immune, stromal, and ESTIMATE scores and higher tumor purity. A higher SPRrisk was also negatively associated with the abundance of CD8⁺ T cells and M1 macrophages. In addition, several genes of the human leukocyte antigen family and immune checkpoints were expressed in low levels in the high-SPRrisk group. Our results provided some insights into assessing individual prognosis and choosing personalized treatment modalities.

Small Extracellular Vesicle-Derived microRNAs Stratify Prostate Cancer Patients According to Gleason Score, Race and Associate with Survival of African American and Caucasian Men

Simple Summary

Novel biomarkers are needed to guide prognosis and treatment of aggressive forms of prostate cancer (PCa). In this study, small extracellular vesicles (sEVs)-derived microRNAs (miRs) are used to predict aggressive phenotypes and ancestral background of PCa patients. Two cohorts was used to study the diagnostic and prognostic utility of sEV-associated miRs in predicting aggressive forms of PCa in African American (AA) and Caucasian (CA) men. In training cohort, miR profiling was performed and top-ranked sEV-associated miRs were then validated in two independent confirmatory cohorts comprising 150 plasma samples. Results revealed that sEV-associated miR-6068 and miR-1915-3p were enriched in PCa patients compared to healthy subjects. sEV-associated miR-6716-5p and miR-3692-3p distinguished AA from CA men and low from high Gleason score. However, miR-1915-3p was the only studied miR associated with longer recurrence-free survival as independent prognostic marker.

Abstract

The utility of small extracellular vesicles (sEVs)-derived microRNAs (miRs) to segregate prostate cancer (PCa) patients according to tumor aggressiveness and ancestral background has not been fully investigated. Thus, we aimed to determine the diagnostic and prognostic utility of sEV-associated miRs in identifying aggressive PCa in African American (AA) and Caucasian (CA) men. Using a training cohort, miR profiling was performed on sEVs isolated from plasma of PCa patients. Top-ranked sEV-associated miRs were then validated in 150 plasma samples (75 AA and 75 CA) collected from two independent cohorts; NIH (n = 90) and Washington University (n = 60) cohorts. Receiver operating characteristic (ROC) curve, Kaplan–Meier and Cox proportional hazards regression were used to assess these miRs as clinical biomarkers. Among nine top-ranked sEV-associated miRs, miR-6068 and miR-1915-3p were enriched in sEVs collected from PCa patients compared to healthy volunteers. Moreover, miR-6716-5p and miR-3692-3p segregated AA from CA men and low from high Gleason score (GS), respectively. Upregulation of sEV-associated miR-1915-3p, miR-3692-3p and miR-5001-5p was associated with improved survival time, and only miR-1915-3p was associated with longer recurrence-free survival (RFS) as an independent prognostic marker. Taken together, we identified novel sEV-associated miRs that can differentiate PCa patients from normal, AA from CA and high from low GS and predicts RFS.

Transmembrane and Tetratricopeptide Repeat Containing 4 Is a Novel Diagnostic Marker for Prostate Cancer with High Specificity and Sensitivity

The histopathologic diagnosis of prostate cancer (PCa) from biopsies is a current challenge if double or triple staining is needed. Therefore, there is an urgent need for development of a new reliable biomarker to diagnose PCa patients. We aimed to explore and compare the expression of TMTC4 in PCa cells and tissue specimens and evaluate its sensitivity and specificity. The expression of TMTC4 in PCa and normal prostate epithelial cells was determined by real-time PCR and Western blot analyses. Immunohistochemical (IHC) staining of TMTC4 was performed on tissues collected from PCa and benign prostatic hyperplasia (BPH). Our results show a high expression of TMTC4 on mRNA and protein levels in PCa versus BPH1 and normal cells (p < 0.05). IHC results show strong cytoplasmic expressions in PCa cases (p < 0.001) as compared to BPH cases. The overall accuracy as measured by the AUC was 1.0 (p < 0.001). The sensitivity and specificity of the protein were 100% and 96.6%, respectively. Taken together, we report a high TMTC4 expression in PCa cells and tissues and its ability to differentiate between PCa and BPH with high sensitivity and specificity. This finding can be carried over to clinical practice after its confirmation by further studies.

Four Novel Prognostic Genes Related to Prostate Cancer Identified Using Co-expression Structure Network Analysis

Prostate cancer (PCa) is one of the most common malignancies for males, but very little is known about its pathogenesis. This study aimed to identify novel biomarkers associated with PCa prognosis and elucidate the underlying molecular mechanism. First, The Cancer Genome Atlas (TCGA) RNA-sequencing data were utilized to identify differentially expressed genes (DEGs) between tumor and normal samples. The DEGs were then applied to construct a co-expression and mined using structure network analysis. The magenta module that was highly related to the Gleason score (r = 0.46, p = 3e-26) and tumor stage (r = 0.38, p = 2e-17) was screened. Subsequently, all genes of the magenta module underwent function annotation. From the key module, CCNA2, CKAP2L, NCAPG, and NUSAP1 were chosen as the four candidate genes. Finally, internal (TCGA) and external data sets (GSE32571, GSE70770, and GSE141551) were combined to validate and predict the value of real hub genes. The results show that the above genes are up-regulated in PCa samples, and higher expression levels show significant association with higher Gleason scores and tumor T stage. Moreover, receiver operating characteristic curve and survival analysis validate the excellent value of hub genes in PCa progression and prognosis. In addition, the protein levels of these four genes also remain higher in tumor tissues when compared with normal tissues. Gene set enrichment analysis and gene set variation analysis for a single gene reveal the close relation with cell proliferation. Meanwhile, 11 small molecular drugs that have the potential to treat PCa were also screened. In conclusion, our research identified four potential prognostic genes and several candidate molecular drugs for treating PCa.

Radiomics Improves Cancer Screening and Early Detection

Imaging is a key technology in the early detection of cancers, including X-ray mammography, low-dose CT for lung cancer, or optical imaging for skin, esophageal, or colorectal cancers. Historically, imaging information in early detection schema was assessed qualitatively. However, the last decade has seen increased development of computerized tools that convert images into quantitative mineable data (radiomics), and their subsequent analyses with artificial intelligence (AI). These tools are improving diagnostic accuracy of early lesions to define risk and classify malignant/aggressive from benign/indolent disease. The first section of this review will briefly describe the various imaging modalities and their use as primary or secondary screens in an early detection pipeline. The second section will describe specific use cases to illustrate the breadth of imaging modalities as well as the benefits of quantitative image analytics. These will include optical (skin cancer), X-ray CT (pancreatic and lung cancer), X-ray mammography (breast cancer), multiparametric MRI (breast and prostate cancer), PET (pancreatic cancer), and ultrasound elastography (liver cancer). Finally, we will discuss the inexorable improvements in radiomics to build more robust classifier models and the significant limitations to this development, including access to well-annotated databases, and biological descriptors of the imaged feature data.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Increased expression of CD81 is associated with poor prognosis of prostate cancer and increases the progression of prostate cancer cells in vitro

CD81, a member of the tetraspanin family, has been revealed to be upregulated and associated with prognosis in several types of cancer; however, this relationship has not been explored in prostate cancer. The present study aimed to investigate the prognostic significance and functional role of CD81 in prostate cancer. The expression of CD81 in prostate cancer tissues and cell lines was evaluated using qRT-PCR analysis. Kaplan-Meier survival analysis and Cox regression analysis were conducted to explore the prognostic significance of CD81. Cell experiments were used to explore the effects of CD81 on cell proliferation, migration, and invasion in prostate cell lines in vitro. The expression of CD81 was increased in both prostate cancer tissues and cell lines. Upregulation of CD81 was significantly associated with lymph node metastasis and TNM stage. Moreover, patients with high CD81 levels had poorer overall survival than those with lower levels. Additionally, tumor cell proliferation, migration, and invasion were inhibited by knockdown of CD81. The present results indicated that CD81 plays an oncogenic role in prostate cancer. Overexpression of CD81 may serve as a prognostic biomarker and therapeutic target and is involved in the progression of prostate cancer.

Downregulation of ARID4A and ARID4B promote tumor progression and directly regulated by microRNA-30d in patient with prostate cancer

AT-rich interaction domain 4A (ARID4A) and AT-rich interaction domain 4B (ARID4B), which are both the AT-rich interaction domain (ARID) family, have been reported to be oncogene or tumor suppressor gene in various human malignances, but there is no involvement about their functions in prostate cancer (PCa). Our previous study has reported that microRNA-30d (miR-30d) expression can predicted poor clinical prognosis in PCa, however, the underlying mechanisms of miR-30d have not been fully described. The aim of our study is to investigate the expression relevance between miR-30d and ARID4A or ARID4B, and examine the clinical significance and biological function of ARID4A and AIRD4B in PCa. In this study, both ARID4A and ARID4B were identified as the target genes of miR-30d. In addition, the mRNA expression of miR-30d in PCa tissues were significantly negative correlated with ARID4A (Pearson correlation coefficient = -0.313, P = 0.001) and ARID4B (Pearson correlation coefficient = -0.349, P < 0.001), while there was a positive correlation between ARID4A and ARID4B (Pearson correlation coefficient = 0.865, P < 0.001). Moreover, both ARID4A and ARID4B were significantly downregulated in PCa tissues with high Gleason scores (P = 0.005, P = 0.033), PSA failure (P = 0.012, P = 0.05) and short biochemical recurrent-free survival (P = 0.033, P = 0.031). Furthermore, the knockout expression of ARID4A and ARID4B promoted PCa cell proliferation, migration and invasion in vitro. In conclusion, our results indicated that ARID4A and ARID4B may serve as tumor suppressor in PCa progression, suggesting that they might be the potential therapeutic targets in prostate cancer.