Publications

Abstract

Loss of AZGP1 expression is a biomarker associated with progression to castration resistance, development of metastasis, and poor disease-specific survival in prostate cancer. However, high expression of AZGP1 cells in prostate cancer has been reported to increase proliferation and invasion. The exact role of AZGP1 in prostate cancer progression remains elusive.AZGP1 knockout and overexpressing prostate cancer cells were generated using a lentiviral system. The effects of AZGP1 under- or over-expression in prostate cancer cells were evaluated by in vitro cell proliferation, migration, and invasion assays. Heterozygous AZGP1± mice were obtained from European Mouse Mutant Archive (EMMA), and prostate tissues from homozygous knockout male mice were collected at 2, 6 and 10 months for histological analysis. In vivo xenografts generated from AZGP1 under- or over-expressing prostate cancer cells were used to determine the role of AZGP1 in prostate cancer tumor growth, and subsequent proteomics analysis was conducted to elucidate the mechanisms of AZGP1 action in prostate cancer progression. AZGP1 expression and microvessel density were measured in human prostate cancer samples on a tissue microarray of 215 independent patient samples.Neither the knockout nor overexpression of AZGP1 exhibited significant effects on prostate cancer cell proliferation, clonal growth, migration, or invasion in vitro. The prostates of AZGP1-/- mice initially appeared to have grossly normal morphology; however, we observed fibrosis in the periglandular stroma and higher blood vessel density in the mouse prostate by 6 months. In PC3 and DU145 mouse xenografts, over-expression of AZGP1 did not affect tumor growth. Instead, these tumors displayed decreased microvessel density compared to xenografts derived from PC3 and DU145 control cells, suggesting that AZGP1 functions to inhibit angiogenesis in prostate cancer. Proteomics profiling further indicated that, compared to control xenografts, AZGP1 overexpressing PC3 xenografts are enriched with angiogenesis pathway proteins, including YWHAZ, EPHA2, SERPINE1, and PDCD6, MMP9, GPX1, HSPB1, COL18A1, RNH1, and ANXA1. In vitro functional studies show that AZGP1 inhibits human umbilical vein endothelial cell proliferation, migration, tubular formation and branching. Additionally, tumor microarray analysis shows that AZGP1 expression is negatively correlated with blood vessel density in human prostate cancer tissues.AZGP1 is a negative regulator of angiogenesis, such that loss of AZGP1 promotes angiogenesis in prostate cancer. AZGP1 likely exerts heterotypical effects on cells in the tumor microenvironment, such as stromal and endothelial cells. This study sheds light on the anti-angiogenic characteristics of AZGP1 in the prostate and provides a rationale to target AZGP1 to inhibit prostate cancer progression.

View details for DOI 10.1186/s12967-024-05183-x

View details for PubMedID 38659028

View details for PubMedCentralID 321763

Abstract

Men diagnosed with prostate cancer (PC) have an increased risk of depression; however, it is unclear to what extent depression affects long-term survival. A better understanding of such effects is needed to improve long-term care and outcomes for men with PC.To determine the associations between major depression and mortality in a national cohort of men with PC.A national cohort study was conducted of all 180 189 men diagnosed with PC in Sweden during 1998-2017. Subsequent diagnoses of major depression were ascertained from nationwide outpatient and inpatient records through 2018.Deaths were identified from nationwide records through 2018. Cox regression was used to compute hazard ratios (HRs) for all-cause mortality associated with major depression, adjusting for sociodemographic factors and comorbidities. Subanalyses assessed differences by PC treatment during 2005-2017. PC-specific mortality was examined using competing risks models.In 1.3 million person-years of follow-up, 16 134 (9%) men with PC were diagnosed with major depression and 65 643 (36%) men died. After adjusting for sociodemographic factors and comorbidities, major depression was associated with significantly higher all-cause mortality in men with high-risk PC (HR, 1.50; 95% confidence interval [CI], 1.44-1.55) or low- or intermediate-risk PC (1.64; 1.56-1.71). These risks were elevated regardless of PC treatment or age at PC diagnosis, except for youngest men (<55 yr) in whom the risks were nonsignificant. Major depression was also associated with increased PC-specific mortality in men with either high-risk PC (HR, 1.35; 95% CI, 1.28-1.43) or low- or intermediate-risk PC (1.42; 1.27-1.59). This study was limited to Sweden and will need replication in other countries when feasible.In this national cohort of men with PC, major depression was associated with ∼50% higher all-cause mortality. Men with PC need timely detection and treatment of depression to support their long-term outcomes and survival.In this report, we examined the effects of depression on survival in men with prostate cancer. We found that among all men with prostate cancer, those who developed depression had a 50% higher risk of dying than those without depression. Men with prostate cancer need close monitoring for the detection and treatment of depression to improve their long-term health outcomes.

View details for DOI 10.1016/j.euo.2024.03.012

View details for PubMedID 38575410

Abstract

Image registration can map the ground truth extent of prostate cancer from histopathology images onto MRI, facilitating the development of machine learning methods for early prostate cancer detection. Here, we present RAdiology PatHology Image Alignment (RAPHIA), an end-to-end pipeline for efficient and accurate registration of MRI and histopathology images. RAPHIA automates several time-consuming manual steps in existing approaches including prostate segmentation, estimation of the rotation angle and horizontal flipping in histopathology images, and estimation of MRI-histopathology slice correspondences. By utilizing deep learning registration networks, RAPHIA substantially reduces computational time. Furthermore, RAPHIA obviates the need for a multimodal image similarity metric by transferring histopathology image representations to MRI image representations and vice versa. With the assistance of RAPHIA, novice users achieved expert-level performance, and their mean error in estimating histopathology rotation angle was reduced by 51% (12 degrees vs 8 degrees), their mean accuracy of estimating histopathology flipping was increased by 5% (95.3% vs 100%), and their mean error in estimating MRI-histopathology slice correspondences was reduced by 45% (1.12 slices vs 0.62 slices). When compared to a recent conventional registration approach and a deep learning registration approach, RAPHIA achieved better mapping of histopathology cancer labels, with an improved mean Dice coefficient of cancer regions outlined on MRI and the deformed histopathology (0.44 vs 0.48 vs 0.50), and a reduced mean per-case processing time (51 vs 11 vs 4.5 min). The improved performance by RAPHIA allows efficient processing of large datasets for the development of machine learning models for prostate cancer detection on MRI. Our code is publicly available at: https://github.com/pimed/RAPHIA.

View details for DOI 10.1016/j.compbiomed.2024.108318

View details for PubMedID 38522253

Abstract

Prostate cancer pathology plays a crucial role in clinical management but is time-consuming. Artificial intelligence (AI) shows promise in detecting prostate cancer and grading patterns. We tested an AI-based digital twin of a pathologist, vPatho, on 2603 histological images of prostate tissue stained with hematoxylin and eosin. We analyzed various factors influencing tumor grade discordance between the vPatho system and six human pathologists. Our results demonstrated that vPatho achieved comparable performance in prostate cancer detection and tumor volume estimation, as reported in the literature. The concordance levels between vPatho and human pathologists were examined. Notably, moderate to substantial agreement was observed in identifying complementary histological features such as ductal, cribriform, nerve, blood vessel, and lymphocyte infiltration. However, concordance in tumor grading decreased when applied to prostatectomy specimens (κ = 0.44) compared to biopsy cores (κ = 0.70). Adjusting the decision threshold for the secondary Gleason pattern from 5 to 10% improved the concordance level between pathologists and vPatho for tumor grading on prostatectomy specimens (κ from 0.44 to 0.64). Potential causes of grade discordance included the vertical extent of tumors toward the prostate boundary and the proportions of slides with prostate cancer. Gleason pattern 4 was particularly associated with this population. Notably, the grade according to vPatho was not specific to any of the six pathologists involved in routine clinical grading. In conclusion, our study highlights the potential utility of AI in developing a digital twin for a pathologist. This approach can help uncover limitations in AI adoption and the practical application of the current grading system for prostate cancer pathology.

View details for DOI 10.1038/s41598-024-55228-w

View details for PubMedID 38438436

View details for PubMedCentralID 2995775

Abstract

National Comprehensive Cancer Network guidelines include prostate-specific membrane antigen (PSMA)-targeted PET for detection of biochemical recurrence of prostate cancer. However, targeting a single tumour characteristic might not be sufficient to reflect the full extent of disease. Gastrin releasing peptide receptors (GRPR) have been shown to be overexpressed in prostate cancer. In this study, we aimed to evaluate the diagnostic performance of the GRPR-targeting radiopharmaceutical 68Ga-RM2 in patients with biochemical recurrence of prostate cancer.This single-centre, single-arm, phase 2/3 trial was done at Stanford University (USA). Adult patients (aged ≥18 years) with biochemical recurrence of prostate cancer, a Karnofsky performance status of 50 or higher, increasing prostate-specific antigen concentration 0·2 ng/mL or more after prostatectomy or 2 ng/mL or more above nadir after radiotherapy, and non-contributory conventional imaging (negative CT or MRI, and bone scan) were eligible. All participants underwent 68Ga-RM2 PET-MRI. The primary outcome was the proportion of patients with PET-positive findings on 68Ga-RM2 PET-MRI compared with MRI alone after initial therapy, at a per-patient and per-lesion level. The primary outcome would be considered met if at least 30% of patients had one or more lesions detected by 68Ga-RM2 PET-MRI and the detection by 68Ga-RM2 PET-MRI was significantly greater than for MRI. Each PET scan was interpreted by three independent masked readers using a standardised evaluation criteria. This study is registered with ClinicalTrials.gov, NCT02624518, and is complete.Between Dec 12, 2015, and July 27, 2021, 209 men were screened for eligibility, of whom 100 were included in analyses. Median follow-up was 49·3 months (IQR 36·7-59·2). The primary endpoint was met; 68Ga-RM2 PET-MRI was positive in 69 (69%) patients and MRI alone was positive in 40 (40%) patients (p<0·0001). In the per-lesion analysis 68Ga-RM2 PET-MRI showed significantly higher detection rates than MRI alone (143 vs 96 lesions; p<0·0001). No grade 1 or worse events were reported.68Ga-RM2 PET-MRI showed better diagnostic performance than MRI alone in patients with biochemical recurrence of prostate cancer. Further prospective comparative studies with PSMA-targeted PET are needed to gain a better understanding of GRPR and PSMA expression patterns in these patients.The US Department of Defense.

View details for DOI 10.1016/S1470-2045(24)00069-X

View details for PubMedID 38423030

Abstract

Glycoproteins in urine have the potential to provide a rich class of informative molecules for studying human health and disease. Despite this promise, the urine glycoproteome has been largely uncharacterized. Here, we present the analysis of glycoproteins in human urine using LC-MS/MS-based intact glycopeptide analysis, providing both the identification of protein glycosites and characterization of the glycan composition at specific glycosites. Gene enrichment analysis reveals differences in biological processes, cellular components, and molecular functions in the urine glycoproteome versus the urine proteome, as well as differences based on the major glycan class observed on proteins. Meta-heterogeneity of glycosylation is examined on proteins to determine the variation in glycosylation across multiple sites of a given protein with specific examples of individual sites differing from the glycosylation trends in the overall protein. Taken together, this dataset represents a potentially valuable resource as a baseline characterization of glycoproteins in human urine for future urine glycoproteomics studies.

View details for DOI 10.1038/s41598-024-53299-3

View details for PubMedID 38355753

View details for PubMedCentralID PMC10866872

View details for DOI 10.1093/jnci/djae033

View details for PubMedID 38341661

Abstract

Neuroendocrine carcinomas, such as neuroendocrine prostate cancer and small-cell lung cancer, commonly have a poor prognosis and limited therapeutic options. We report that ubiquitin carboxy-terminal hydrolase L1 (UCHL1), a deubiquitinating enzyme, is elevated in tissues and plasma from patients with neuroendocrine carcinomas. Loss of UCHL1 decreases tumor growth and inhibits metastasis of these malignancies. UCHL1 maintains neuroendocrine differentiation and promotes cancer progression by regulating nucleoporin, POM121, and p53. UCHL1 binds, deubiquitinates, and stabilizes POM121 to regulate POM121-associated nuclear transport of E2F1 and c-MYC. Treatment with the UCHL1 inhibitor LDN-57444 slows tumor growth and metastasis across neuroendocrine carcinomas. The combination of UCHL1 inhibitors with cisplatin, the standard of care used for neuroendocrine carcinomas, significantly delays tumor growth in pre-clinical settings. Our study reveals mechanisms of UCHL1 function in regulating the progression of neuroendocrine carcinomas and identifies UCHL1 as a therapeutic target and potential molecular indicator for diagnosing and monitoring treatment responses in these malignancies.

View details for DOI 10.1016/j.xcrm.2023.101381

View details for PubMedID 38244540

Abstract

Distinguishing indolent from clinically significant localized prostate cancer is a major clinical challenge and influences clinical decision-making between treatment and active surveillance. The development of novel predictive biomarkers will help with risk stratification, and clinical decision-making, leading to a decrease in over or under-treatment of patients with prostate cancer. Here, we report that Trop2 is a prognostic tissue biomarker for clinically significant prostate cancer by utilizing the Canary Prostate Cancer Tissue Microarray (CPCTA) cohort composed of over 1100 patients from a multi-institutional study. We demonstrate that elevated Trop2 expression is correlated with worse clinical features including Gleason score, age, and pre-operative PSA levels. More importantly, we demonstrate that elevated Trop2 expression at radical prostatectomy predicts worse overall survival in men undergoing radical prostatectomy. Additionally, we detect shed Trop2 in urine from men with clinically significant prostate cancer. Our study identifies Trop2 as a novel tissue prognostic biomarker and a candidate non-invasive marker for prostate cancer.

View details for DOI 10.1038/s41598-023-50215-z

View details for PubMedID 38177207

View details for PubMedCentralID 7983799

Abstract

BACKGROUND: A diagnosis of prostate cancer (PC) may cause psychosocial distress not only in a man but also his intimate partner. However, long-term risks of depression, anxiety, or suicide in partners of men with PC are largely unknown.METHODS: A national cohort study was conducted of 121,530 partners of men diagnosed with PC during 1998-2017 and 1,093,304 population-based controls in Sweden. Major depression, anxiety disorder, and suicide death were ascertained through 2018. Cox regression was used to compute hazard ratios (HRs) while adjusting for sociodemographic factors.RESULTS: Partners of men with high-risk PC had increased risks of major depression (adjusted HR, 1.34; 95% CI, 1.30-1.39) and anxiety disorder (1.25; 1.20-1.30), which remained elevated ≥10 years later. Suicide death was increased in partners of men with distant metastases (adjusted HR, 2.38; 95% CI, 1.08-5.22) but not other high-risk PC (1.14; 0.70-1.88). Among partners of men with high-risk PC, risks of major depression and anxiety disorder were highest among those aged ≥80 years (adjusted HR, 1.73; 95% CI, 1.53-1.96; and 1.70; 1.47-1.96, respectively), whereas suicide death was highest among those aged <60 years (7.55; 2.20-25.89). In contrast, partners of men with low- or intermediate-risk PC had modestly or no increased risks of these outcomes.CONCLUSIONS: In this large cohort, partners of men with high-risk PC had increased risks of major depression and anxiety disorder, which persisted for ≥10 years. Suicide death was increased 2-fold in partners of men with distant metastases. Partners as well as men with PC need psychosocial support and close follow-up for psychosocial distress.

View details for DOI 10.1093/jnci/djad257

View details for PubMedID 38060258