Prediction of Postprostatectomy Biochemical Recurrence Using Quantitative Ultrasound Shear Wave Elastography Imaging

Development of a ferroptosis-based molecular markers for predicting RFS in prostate cancer patients

The goal of this study was to develop a ferroptosis-based molecular signature that can predict recurrence-free survival (RFS) in patients with prostate cancer (PCa). In this study, we obtained ferroptosis-related genes (FRGs) in FerrDb database and clinical transcriptome data in TCGA database and GEO database. Consensus cluster analysis was used to identify three molecular markers of ferroptosis in PCa with differential expression of 40 FRGs, including PD-L1 expression levels. We conducted a new ferroptosis-related signature for PCa RFS using four FRGs identified through univariate and multivariate Cox regression analyses. The signature was validated in the training, testing, and validation cohorts, and it demonstrated remarkable results in the area under the time-dependent receiver operating characteristic (ROC) curve of 0.757, 0.715, and 0.732, respectively. Additionally, we observed that younger patients, those with stage T III and stage T IV, stage N0, cluster 1, and cluster 2 PCa were more accurately predicted by the signature as independent predictors of RFS. DU-145 and RWPE-1 cells were successfully analyzed by qRT-PCR and Western blot for ASNS, GPT2, RRM2, and NFE2L2. In summary, we developed a novel ferroptosis-based signature for RFS in PC, utilizing four FRGs identified through univariate and multivariate Cox regression analyses. This signature was rigorously validated across training, testing, and validation cohorts, demonstrating exceptional performance as evidenced by its ROC curves. Notably, our findings indicate that this signature is particularly effective as an independent predictor of RFS in younger patients or those with stage T III and T IV, stage N0, and in clusters 1 and 2. Finally, we confirmed the expression of these four FRGs in DU-145 and RWPE-1 cell lines.

Comparative Assessment of Different Ultrasound Technologies in the Detection of Prostate Cancer: A Systematic Review and Meta-Analysis

The present study aimed to assess the diagnostic test accuracy of different ultrasound scanning technologies in the detection of prostate cancer. A systematic search was conducted using the Cochrane Guidelines for Screening and Diagnostic Tests. We performed a systematic search in the international databases PubMed, Medline, Ovid, Embase and Cochrane Library. Searches were designed to find all studies that evaluated Micro-US, mpUS, SWE and CEUS as the main detection modalities for prostate cancer. This study was registered with Research Registry of systematic review and meta-analysis. The QUADAS-2 tool was utilized to perform quality assessment and bias analysis. The literature search generated 1376 studies. Of these, 320 studies were screened for eligibility, with 1056 studies being excluded. Overall, 26 studies with a total of 6370 patients met the inclusion criteria. The pooled sensitivity for grayscale, CEUS, SWE, Micro-US and mpUS modalities were 0.66 (95% CI 0.54-0.73) 0.73 (95% CI 0.58-0.88), 0.82 (95% CI 0.75-0.90), 0.85 (95% CI 0.76-0.94) and 0.87 (95% CI 0.71-1.03), respectively. Moreover, the pooled specificity for grayscale, CEUS, SWE, Micro-US and mpUS modalities were 0.56 (95% CI 0.21-0.90), 0.78 (95% CI 0.67-0.88), 0.76 (95% CI 0.65-0.88), 0.43 (95% CI 0.28-0.59) and 0.68 (95% CI 0.54-0.81), respectively. In terms of sensitivity, substantial heterogeneity between studies was detected (I2 = 72%, p = 0.000 < 0.05). In relation to specificity, extreme heterogeneity was detected (I2 = 93%, p = 0.000 < 0.05). Some studies proved that advanced ultrasound modalities such as mpUS, Micro-US, shear-wave elastography, contrast enhanced and micro-ultrasound are promising methods for the detection of prostate cancer.

Multimodality Characterization of Cancer-Associated Fibroblasts in Tumor Microenvironment and Its Correlation With Ultrasound Shear Wave-Measured Tissue Stiffness in Localized Prostate Cancer

Introduction

Growing evidence suggests that the tumor microenvironment (TME) represented by cellular and acellular components plays a key role in the multistep process of metastases and response to therapies. However, imaging and molecular characterization of the TME in prostate cancer (PCa) and its role in predicting aggressive tumor behavior and disease progression is largely unexplored. The study explores the PCa TME through the characterization of cancer-associated fibroblasts (CAFs) using both immunohistochemistry (IHC) and genomics approaches. This is then correlated with transrectal ultrasound shear wave elastography (USWE)-measured tissue stiffness.

Patients and Methods

Thirty patients with clinically localized PCa undergoing radical prostatectomy for different risk categories of tumor (low, intermediate, and high) defined by Gleason score (GS) were prospectively recruited into this study. Prostatic tissue stiffness was measured using USWE prior to surgery. The CAFs within the TME were identified by IHC using a panel of six antibodies (FAP, SMAα, FSP1, CD36, PDGFRα, and PDGFRβ) as well as gene expression profiling using TempO-sequence analysis. Whether the pattern and degree of immunohistochemical positivity (measured by Quick score method) and expression of genes characterizing CAFs were correlated with USWE- and GS-measured tissue stiffnesses were tested using Spearman's rank correlation and Pearson correlation.

Results

There was a statistically significant correlation between GS of cancers, the pattern of staining for CAFs by immunohistochemical staining, and tissue stiffness measured in kPa using USWE (p < 0.001). Significant differences were also observed in immunohistochemical staining patterns between normal prostate and prostatic cancerous tissue. PDGFRβ and SMAα immunostaining scores increased linearly with increasing the USWE stiffness and the GS of PCa. There was a significant positive correlation between increasing tissue stiffness in tumor stroma and SMAα and PDGFRβ gene expression in the fibromuscular stroma (p < 0.001).

Conclusion

USWE-measured tissue stiffness correlates with increased SMAα and PDGFRβ expressing CAFs and PCa GSs. This mechanistic correlation could be used for predicting the upgrading of GS from biopsies to radical surgery and response to novel treatments.

A Novel Ferroptosis-Based Molecular Signature Associated with Biochemical Recurrence-Free Survival and Tumor Immune Microenvironment of Prostate Cancer

Objective: To identify ferroptosis-related molecular clusters, and to develop and validate a ferroptosis-based molecular signature for predicting biochemical recurrence-free survival (BCRFS) and tumor immune microenvironment of prostate cancer (PCa). Materials and Methods: The clinical data and transcriptome data of PCa were downloaded from TCGA and GEO database. Ferroptosis-related genes (FRGs) were obtained from FerrDb database. We performed consensus clustering analysis to identify ferroptosis-related molecular subtypes for PCa. Univariate and multivariate Cox regression analysis were used to establish a ferroptosis-based signature for predicting BCRFS. Internal verification, external verification and subgroup survival analysis were then successfully performed. Results: There was a total of 40 differentially expressed FRGs in PCa. We then identified three ferroptosis-related molecular clusters of PCa, which have significantly different immune infiltrating cells, tumor immune microenvironment and PD-L1 expression level. More importantly, a novel ferroptosis-based signature for predicting BCRFS of PCa based on four FRGs (including ASNS, GPT2, NFE2L2, RRM2) was developed. Internal and external verifications were then successfully performed. Patients with high-risk score were associated with significant poor BCRFS compared with those with low-risk score in training cohort, testing cohort and validating cohort, respectively. The area under time-dependent Receiver Operating Characteristic (ROC) curve were 0.755, 0.705 and 0.726 in training cohort, testing cohort and validating cohort, respectively, indicating the great performance of this signature. Independent prognostic analysis indicated that this signature was an independent predictor for BCRFS of PCa. Subgroup analysis revealed that this signature was particularly suitable for younger or stage T III-IV or stage N0 or cluster 1-2 PCa patients. Patients with high-risk score have significantly different tumor immune microenvironment in comparison with those with low-risk score. The results of qRT-PCR successfully verified the mRNA expression levels of ASNS, GPT2, RRM2 and NFE2L2 in DU-145 and RWPE-1 cells while the results of IHC staining exactly verified the relative protein expression levels of ASNS, GPT2, RRM2 and NFE2L2 between PCa and BPH tissues. Conclusions: This study successfully identified three ferroptosis-related molecular clusters. Besides, we developed and validated a novel ferroptosis-based molecular signature, which performed well in predicting BCRFS and tumor immune microenvironment of PCa.

Prostate Cancer Gleason Score From Biopsy to Radical Surgery: Can Ultrasound Shear Wave Elastography and Multiparametric Magnetic Resonance Imaging Narrow the Gap?

Objectives

To investigate the impact of ultrasound shear wave elastography (USWE) and multiparametric magnetic resonance imaging (mpMRI) in predicting a change in biopsy-assigned Gleason Score (GS) after radical surgery for localised prostate cancer (PCa).

Method

A total of 212 men opting for laparoscopic radical prostatectomy (LRP) between September 2013 and June 2017 were recruited into this study. All the participants had 12-core transrectal ultrasound (TRUS) biopsies and imaging using USWE and mpMRI before radical surgery. The predictive accuracy for imaging modalities was assessed in relation to upgrading and downgrading of PCa GS between the biopsies and radical prostatectomy using Student's t-test and multivariable logistic regression analyses. A decision analysis curve was constructed assessing the impact of nomogram on clinical situations using different thresholds of upgrading probabilities.

Results

Most GS 6 diseases on biopsies were upgraded on radical surgery (37/42, 88.1%). Major downgrading was seen in GS 8 category of disease (14/35; 37.1%), whereas no alteration was observed in GS 7 on biopsies in most men (55/75; 73.3%). In univariate analysis, higher preoperative prostate-specific antigen (PSA) (p = 0.001), higher prostate-specific antigen density (PSAD) (p = 0.002), stiffer USWE lesions (p = 0.009), and higher prostate imaging-reporting and data system (PIRADS) (p = 0.002) on mpMRI were significant predictors of upgrading. In multivariate logistic regression analyses, only PSA (p = 0.016) and USWE-measured tissue stiffness (p = 0.029) showed statistical significance in predicting upgrading.

Conclusions

Measurement of tissue stiffness using USWE in clinically localised PCa can predict upgrading of GS and has the potential to improve patient management options.

Causal contributors to tissue stiffness and clinical relevance in urology

Mechanomedicine is an emerging field focused on characterizing mechanical changes in cells and tissues coupled with a specific disease. Understanding the mechanical cues that drive disease progression, and whether tissue stiffening can precede disease development, is crucial in order to define new mechanical biomarkers to improve and develop diagnostic and prognostic tools. Classically known stromal regulators, such as fibroblasts, and more recently acknowledged factors such as the microbiome and extracellular vesicles, play a crucial role in modifications to the stroma and extracellular matrix (ECM). These modifications ultimately lead to an alteration of the mechanical properties (stiffness) of the tissue, contributing to disease onset and progression. We describe here classic and emerging mediators of ECM remodeling, and discuss state-of-the-art studies characterizing mechanical fingerprints of urological diseases, showing a general trend between increased tissue stiffness and severity of disease. Finally, we point to the clinical potential of tissue stiffness as a diagnostic and prognostic factor in the urological field, as well as a possible target for new innovative drugs.

Quantitative ultrasound shear wave elastography (USWE)-measured tissue stiffness correlates with PIRADS scoring of MRI and Gleason score on whole-mount histopathology of prostate cancer: implications for ultrasound image-guided targeting approach

OBJECTIVE

To correlate quantitative tissue stiffness measurements obtained by transrectal ultrasound shear wave elastography (USWE) with PI-RADS scoring of multiparametric magnetic imaging resonance (mpMRI) using Gleason scores of radical prostatectomy as a reference standard.

PATIENTS AND METHODS

196 men with localised prostate cancer were prospectively recruited into the study and had quantitative prostate tissue stiffness measurements in kilopascals (kPa) using transrectal USWE prior to radical prostatectomy. PI-RADS scores of mpMRI were also obtained in all the men. Imaging and histopathology of radical prostatectomy specimen were oriented to each other using patient specific customised 3D moulds to guide histopathology grossing of radical prostatectomy specimens. All included patients had confirmed PCa on TRUS-guided biopsies, had both USWE and mpMRI imaging data, and underwent radical prostatectomy. Chi-square test with 95% confidence interval was used to assess the difference between Gleason score (GS) of radical prostatectomy and PI-RADS classification, as well as GS of radical prostatectomy and stiffness (in Kpa) using USWE. The correlation coefficient (r) was calculated in order to investigate relation between PI-RADS classification and tissue stiffness in kPa.

RESULTS

There was a statistically significant correlation between USWE-measured tissue stiffness and GS (χ2 (2, N = 196) = 23.577, p < 0.001). Also, there was a statistically significant correlation between Gleason score and PI-RADS score (χ2 (2, N = 196) = 12.838, p = 0.002). High PIRADS on MRI and high stiffness on USWE (> 100 kPa) detected more than 80% and 90% high risk prostate cancer disease. However, a weak correlation coefficient of 0.231 was observed between PI-RADS score and level of tissue stiffness measured in kPa.

CONCLUSION

Quantitative USWE and mpMRI using PI-RADS classification provide a good degree of prediction for Gleason score of clinically significant prostate cancer (csPCa). Stiffer lesions on ultrasound showed a weak correlation with PI-RADS scoring system. USWE could be used to target suspected prostate cancer.

Characterisation of Prostate Lesions Using Transrectal Shear Wave Elastography (SWE) Ultrasound Imaging: A Systematic Review

BACKGROUND

ultrasound-based shear wave elastography (SWE) can non-invasively assess prostate tissue stiffness. This systematic review aims to evaluate SWE for the detection of prostate cancer (PCa) and compare diagnostic estimates between studies reporting the detection of all PCa and clinically significant PCa (csPCa).

METHODS

a literature search was performed using the MEDLINE, EMBASE, Cochrane Library, ClinicalTrials.gov, and CINAHL databases. Studies evaluating SWE for the detection of PCa using histopathology as reference standard were included.

RESULTS

16 studies including 2277 patients were included for review. Nine studies evaluated SWE for the detection of PCa using systematic biopsy as a reference standard at the per-sample level, with a pooled sensitivity and specificity of 0.85 (95% CI = 0.74-0.92) and 0.85 (95% CI = 0.75-0.91), respectively. Five studies evaluated SWE for the detection of PCa using histopathology of radical prostatectomy (RP) specimens as the reference standard, with a pooled sensitivity and specificity of 0.71 (95% CI = 0.55-0.83) and 0.74 (95% CI = 0.42-0.92), respectively. Sub-group analysis revealed a higher pooled sensitivity (0.77 vs. 0.62) and specificity (0.84 vs. 0.53) for detection of csPCa compared to all PCa among studies using RP specimens as the reference standard.

CONCLUSION

SWE is an attractive imaging modality for the detection of PCa.