Prognostic Features of Biochemical Recurrence of Prostate Cancer Following Radical Prostatectomy Based on Multiparametric MRI and Immunohistochemistry Analysis of MRI-guided Biopsy Specimens

Investigating Intensity and Percentage of p53 Nuclear Expression in Prostate Cancer: Findings from a Cohort of U.S. Military Veterans

BACKGROUND

Next-generation sequencing has revealed TP53 alterations in localized prostate cancer (PCa), suggesting growing clinical potential for p53 immunohistochemistry (IHC). Prior research supports the use of IHC for the detection of p53 overexpression to predict the presence of TP53 alterations known to be associated with adverse outcomes. However, to reach a consensus definition of p53 overexpression in PCa, further insights are needed. This study aimed to compare two fundamental approaches of evaluating p53 expression across a variety of specimens regarding PCa progression.

METHODS

This study included 84 patients (75% self-identified as African American) diagnosed with PCa between 1996 and 2021 at the DC VA Medical Center. Representative sections of core biopsies, radical prostatectomies, transurethral prostate resections, and metastatic deposits were examined. p53 nuclear expression was scored according to the highest intensity observed (0, 1+, 2+, 3+) and the percentage (0%, <1%, 1-5%, >5%) of tumor cells expressing any level of intensity in the aggregate tumor area. All slides were reviewed by two independent pathologists. Pertinent clinical data were collected.

RESULTS

A total of 34 patients (40%) exhibited p53 nuclear expression, of which 18 (21%) showed the maximum (3+) intensity. The presence of maximum intensity, regardless of percentage, was found to be associated with Grade Group (p < 0.001), higher PSA at biopsy (p < 0.001), BCR (p < 0.001) and metastasis (p < 0.001). Importantly, maximum p53 intensity was identified only in patients who developed metastatic disease.

CONCLUSIONS

Maximum (3+) p53 nuclear intensity of any percentage is highly associated with disease progression in PCa, suggesting that optimal determination of p53 overexpression should incorporate intensity.

Multiparametric MRI for characterization of the tumour microenvironment

Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.

Comparison of MRI-Based Staging and Pathologic Staging for Predicting Biochemical Recurrence of Prostate Cancer After Radical Prostatectomy

BACKGROUND. Currently most clinical models for predicting biochemical recurrence (BCR) of prostate cancer (PCa) after radical prostatectomy (RP) incorporate staging information from RP specimens, creating a gap in preoperative risk assessment. OBJECTIVE. The purpose of our study was to compare the utility of presurgical staging information from MRI and postsurgical staging information from RP pathology in predicting BCR in patients with PCa. METHODS. This retrospective study included 604 patients (median age, 60 years) with PCa who underwent prostate MRI before RP from June 2007 to December 2018. A single genitourinary radiologist assessed MRI examinations for extraprostatic extension (EPE) and seminal vesicle invasion (SVI) during clinical interpretations. The utility of EPE and SVI on MRI and RP pathology for BCR prediction was assessed through Kaplan-Meier and Cox proportional hazards analyses. Established clinical BCR prediction models, including the University of California San Francisco Cancer of the Prostate Risk Assessment (UCSF-CAPRA) model and the Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) model, were evaluated in a subset of 374 patients with available Gleason grade groups from biopsy and RP pathology; two CAPRA-MRI models (CAPRA-S model with modifications to replace RP pathologic staging features with MRI staging features) were also assessed. RESULTS. Univariable predictors of BCR included EPE on MRI (HR = 3.6), SVI on MRI (HR = 4.4), EPE on RP pathology (HR = 5.0), and SVI on RP pathology (HR = 4.6) (all p < .001). Three-year BCR-free survival (RFS) rates for patients without versus with EPE were 84% versus 59% for MRI and 89% versus 58% for RP pathology, and 3-year RFS rates for patients without versus with SVI were 82% versus 50% for MRI and 83% versus 54% for RP histology (all p < .001). For patients with T3 disease on RP pathology, 3-year RFS rates were 67% and 41% for patients without and with T3 disease on MRI. AUCs of CAPRA models, including CAPRA-MRI models, ranged from 0.743 to 0.778. AUCs were not significantly different between CAPRA-S and CAPRA-MRI models (p > .05). RFS rates were significantly different between low- and intermediate-risk groups for only CAPRA-MRI models (80% vs 51% and 74% vs 44%; both p < .001). CONCLUSION. Presurgical MRI-based staging features perform comparably to postsurgical pathologic staging features for predicting BCR. CLINICAL IMPACT. MRI staging can preoperatively identify patients at high BCR risk, helping to inform early clinical decision-making. TRIAL REGISTRATION. ClinicalTrials.gov NCT00026884 and NCT02594202.

MR image quality in local staging of prostate cancer: Role of PI-QUAL in the detection of extraprostatic extension

PURPOSE

To assess the impact of prostate MRI image quality by means of the Prostate Imaging Quality (PI-QUAL) score, on the identification of extraprostatic extension of disease (EPE), predicted using the EPE Grade Score, Likert Scale Score (LSS) and a clinical nomogram (MSKCCn).

METHODS

We retrospectively included 105 patients with multiparametric prostate MRI prior to prostatectomy. Two radiologists evaluated image quality using PI-QUAL (≥4 was considered high quality) in consensus. All cases were also scored using the EPE Grade, the LSS, and the MSKCCn (dichotomized). Inter-rater reproducibility for each score was also assessed. Accuracy was calculated for the entire population and by image quality, considering two thresholds for EPE Grade (≥2 and = 3) and LSS (≥3 and ≥ 4) and using McNemar's test for comparison.

RESULTS

Overall, 66 scans achieved high quality. The accuracy of EPE Grade ranged from 0.695 to 0.743, while LSS achieved values between 0.705 and 0.733. Overall sensitivity for the radiological scores (range = 0.235-0.529) was low irrespective of the PI-QUAL score, while specificity was higher (0.775-0.986). The MSKCCn achieved an AUC of 0.76, outperforming EPE Grade (=3 threshold) in studies with suboptimal image quality (0.821 vs 0.564, p = 0.016). EPE Grade (=3 threshold) accuracy was also better in high image quality studies (0.849 vs 0.564, p = 0.001). Reproducibility was good to excellent overall (95 % Confidence Interval range = 0.782-0.924).

CONCLUSION

Assessing image quality by means of PI-QUAL is helpful in the evaluation of EPE, as a scan of low quality makes its performance drop compared to clinical staging tools.

Risk stratification for early biochemical recurrence of prostate cancer in the era of multiparametric magnetic resonance imagining-targeted biopsy

BACKGROUND

Multiparametric magnetic resonance imaging (MRI) and MRI-targeted biopsy are nowadays recommended in the prostate cancer (PCa) diagnostic pathway. Ploussard and Mazzone have integrated these tools into novel risk classification systems predicting the risk of early biochemical recurrence (eBCR) in PCa patients who underwent radical prostatectomy (RP). We aimed to assess available risk classification systems and to define the best-performing.

METHODS

Data on 1371 patients diagnosed by MRI-targeted biopsy and treated by RP between 2014 and 2022 at eight European tertiary referral centers were analyzed. Risk classifications systems included were the European Association of Urology (EAU) and National Comprehensive Cancer Network (NCCN) risk groups, the Cancer of the Prostate Risk Assessment (CAPRA) score, the International Staging Collaboration for Cancer of the Prostate (STAR-CAP) classification, the Ploussard and Mazzone models, and ISUP grade group. Kaplan-Meier analyses were used to compare eBCR among risk classification systems. Performance was assessed in terms of discrimination quantified using Harrell's c-index, calibration, and decision curve analysis (DCA).

RESULTS

Overall, 152 (11%) patients had eBCR at a median follow-up of 31 months (interquartile range: 19-45). The 3-year eBCR-free survival rate was 91% (95% confidence interval [CI]: 89-93). For each risk classification system, a significant difference among survival probabilities was observed (log-rank test p < 0.05) except for NCCN classification (p = 0.06). The highest discrimination was obtained with the STAR-CAP classification (c-index 66%) compared to CAPRA score (63% vs. 66%, p = 0.2), ISUP grade group (62% vs. 66, p = 0.07), Ploussard (61% vs. 66%, p = 0.003) and Mazzone models (59% vs. 66%, p = 0.02), and EAU (57% vs. 66%, p < 0.001) and NCCN (57% vs. 66%, p < 0.001) risk groups. Risk classification systems demonstrated good calibration characteristics. At DCA, the CAPRA score showed the highest net benefit at a probability threshold of 9%-15%.

CONCLUSIONS

The performance of risk classification systems using MRI and MRI-targeted information was less optimistic when tested in a contemporary set of patients. CAPRA score and STAR-CAP classification were the best-performing and should be preferred for treatment decision-making.

Role of magnetic resonance imaging for preoperative prediction of early biochemical failure in localized prostate cancer

Background

The purpose of our study was to assess preoperative clinical biological and Magnetic Resonance Imaging (MRI) predictive factors of early biochemical failure (BF), defined as persistence of significant post-operative plasmatic prostate specific antigen (PSA) level after radical prostatectomy (RP) in patients with localized prostate cancer (PCa).

Methods

In a retrospective cohort study we included 142 patients from our university hospital with newly diagnosed PCa, who underwent 3T multiparametric MRI prior to RP. Only the MRI target lesions [Prostate Imaging Reporting and Data System (PIRADS) ≥3] with histological correspondence were considered significant. Clinical, biological, MRI and pathological preoperative data were studied. We performed univariate and multivariate logistic regression analysis to identify significant parameters associated with early BF.

Results

Early BF occurred in 14% of patients (20/142). Patients with BF had higher PSA level at diagnosis, Gleason score, number of positive biopsies, size of the largest positive biopsy and higher National Comprehensive Cancer Network (NCCN) risk score (P<0.001 for all). According to MRI, they also had higher T stage and a higher size of capsular contact (P<0.001 for all). In contrast, there was no difference concerning neither ADC value, perfusion profile and zonal location of the index lesion. In multivariate analysis, the best combination of predictive factors of early BF was the association of preoperative Gleason score ≥4+3 [odds ratio (OR) =6.8 (1.4-32.5); P=0.002] and T stage ≥3 on preoperative MRI [OR =17.4 (3.2-94.9); P<0.001] with an area under the curve (AUC) of 0.89 [99% confidence interval (CI): 0.77-1], a negative predictive value of 94% and a positive predictive value of 75%.

Conclusions

Combination of simple preoperative biomarkers as Gleason score and T stage according to MRI accurately stratify the risk of early BF following RP. These results emphasize the pivotal role of preoperative MRI for the management of localized PCa.

The role of MRI in prostate cancer: current and future directions

There has been an increasing role of magnetic resonance imaging (MRI) in the management of prostate cancer. MRI already plays an essential role in the detection and staging, with the introduction of functional MRI sequences. Recent advancements in radiomics and artificial intelligence are being tested to potentially improve detection, assessment of aggressiveness, and provide usefulness as a prognostic marker. MRI can improve pretreatment risk stratification and therefore selection of and follow-up of patients for active surveillance. MRI can also assist in guiding targeted biopsy, treatment planning and follow-up after treatment to assess local recurrence. MRI has gained importance in the evaluation of metastatic disease with emerging technology including whole-body MRI and integrated positron emission tomography/MRI, allowing for not only better detection but also quantification. The main goal of this article is to review the most recent advances on MRI in prostate cancer and provide insights into its potential clinical roles from the radiologist's perspective. In each of the sections, specific roles of MRI tailored to each clinical setting are discussed along with its strengths and weakness including already established material related to MRI and the introduction of recent advancements on MRI.

Magnetic Resonance Imaging-Targeted Biopsy and Pretherapeutic Prostate Cancer Risk Assessment: a Systematic Review: Biopsie ciblée par Imagerie par résonance magnétique et évaluation pré-thérapeutique du risque de cancer de la prostate : revue systématique

INTRODUCTION

Multiparametric magnetic resonance imaging (MRI) has been included in prostate cancer (PCa) diagnostic pathway and may improve disease characterization. The aim of this systematic review is to assess the added value of MRI-targeted biopsy (TB) in pre-therapeutic risk assessment models over existing tools based on systematic biopsy (SB) for localized PCa.

EVIDENCE ACQUISITION

A systematic search was conducted using Pubmed (Medline), Scopus and ScienceDirect databases according to Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement. We included studies through October 2021 reporting on TB in pretherapeutic risk assessment models.

EVIDENCE SYNTHESIS

We identified 24 eligible studies including 24'237 patients for the systematic review. All included studies were retrospective and conducted in patients undergoing radical prostatectomy. Nine studies reported on the risk of extraprostatic extension, seven on the risk of lymph node invasion, three on the risk of biochemical recurrence and nine on the improvement of PCa risk stratification. Overall, the combination of TB with imaging, clinical and biochemical parameters outperformed current pretherapeutic risk assessment models. External validation studies are lacking for certain endpoints and the absence of standardization among TB protocols, including number of TB cores and fusion systems, may limit the generalizability of the results.

CONCLUSION

TB should be incorporated in pretherapeutic risk assessment models to improve clinical decision making. Further high-quality studies are required to determine models' generalizability while there is an urgent need to reach consensus on a standardized TB protocol. Long-term outcomes after treatment are also awaited to confirm the superiority of such models over classical risk classifications only based on SB. © 2022 Elsevier Masson SAS. All rights reserved.

Surface-enhanced Raman scattering (SERS) spectroscopy for prostate cancer diagnosis: A review

The present review focuses on the diagnosis of prostate cancer using surface enhanced Raman scattering (SERS) spectroscopy. On the basis of literature search, SERS-based analysis for prostate cancer detection of different sample types is reported in the present study. Prostate cancer is responsible for nearly one-tenth of all cell cancer deaths among men. Significant efforts have been dedicated to establish precise and sensitive monitoring techniques to detect prostate cancer biomarkers in different types of body samples. Among the various spectro-analytical techniques investigated to achieve this objective, SERS spectroscopy has been proven as a promising approach that provides noticeable enhancements of the Raman sensitivity when the target biomolecules interact with a nanostructured surface. The purpose of this review is to give a brief overview of the SERS-basedapproach and other spectro-analytical strategies being used for the detection and quantification of prostate cancer biomarkers. The revolutionary development of SERS methods for the diagnosis of prostate cancer has been discussed in more details based on the reported literature. It has been noticed that the SERS-based immunoassay presents reliable results for the prostate cancer quantification. The EC-SERS, which integrates electrochemistry with the SERS model, could also offer a potential ultrasensitive strategy, although its application in prostate cancer analysis has been still limited.

E-Cadherin, Integrin Alpha2 (Cd49b), and Transferrin Receptor-1 (Tfr1) Are Promising Immunohistochemical Markers of Selected Adverse Pathological Features in Patients Treated with Radical Prostatectomy

In patients treated for prostate cancer (PCa) with radical prostatectomy (RP), determining the risk of extraprostatic extension (EPE) and nodal involvement (NI) remains crucial for planning nerve-sparing and extended lymphadenectomy. The study aimed to determine proteins that could serve as immunohistochemical markers of locally advanced PCa. To select candidate proteins associated with adverse pathologic features (APF) reverse-phase protein array data of 498 patients was retrieved from The Cancer Genome Atlas. The analysis yielded 6 proteins which were then validated as predictors of APF utilizing immunohistochemistry in a randomly selected retrospective cohort of 53 patients. For univariate and multivariate analysis, logistic regression was used. Positive expression of TfR1 (OR 13.74; p = 0.015), reduced expression of CD49b (OR 10.15; p = 0.013), and PSA (OR 1.29; p = 0.013) constituted independent predictors of EPE, whereas reduced expression of e-cadherin (OR 10.22; p = 0.005), reduced expression of CD49b (OR 24.44; p = 0.017), and PSA (OR 1.18; p = 0.002) were independently associated with NI. Both models achieved high discrimination (AUROC 0.879 and 0.888, respectively). Immunohistochemistry constitutes a straightforward tool that might be easily utilized before RP. Expression of TfR1 and CD49b is associated with EPE, whereas expression of e-cadherin and CD49b is associated with NI. Since following immunohistochemical markers predicts respective APFs independently from PSA, in the future they might supplement existing preoperative nomograms or be implemented in novel tools.