Risk Of Biochemical Recurrence Research Articles

A bicentric retrospective study of the correlation of EAU BCR risk groups with 18F-PSMA-1007 PET/CT detection in prostate cancer biochemical recurrence

The European Association of Urology (EAU) has proposed a risk stratification for patients harboring biochemical recurrence (BCR) after radical prostatectomy: ISUP < 4 and PSA doubling time (PSAdt) > 12 months for low risk, and ISUP ≥ 4 or PSAdt ≤ 12 months for high risk. This dual-center retrospective study aims to investigate the correlation between the EAU risk stratification for BCR following radical prostatectomy and the detection rate of lesions using 18F-PSMA-1007 PET/CT. Among the 71 included patients (58 high-risk, 13 low-risk), with a median PSA level of 1.43 ng/ml, PET/CT demonstrated a significantly higher positivity in the high-risk group compared to the low-risk group (72.4% vs. 38.0%, p = 0.026). Analysis of recurrence sites revealed a similar proportion of pelvic-confined disease in both groups (24.1% vs. 23.1%, p = 0.935), but a significantly higher incidence of metastatic disease in the high-risk group (51.7% vs. 15.4%, p = 0.017), with detailed findings indicating an increased prevalence of bone metastases in the high-risk BCR group (37.8% vs. 7.7%, p = 0.048). Therefore, PSMA PET/CT offers valuable insights for treatment decisions, aligning with the evolving landscape of prostate cancer management.

Comprehensive Analysis of Perioperative Factors Influencing the Risk of Biochemical Recurrence in Patients with Radical Prostatectomy.

To analyze the perioperative factors that influence the risk of biochemical recurrence (BCR) in patients with localized PCa undergoing radical prostatectomy Materials and Methods: A total of 457 patients, operated by 2 surgeons in our high-volume oncological center were included in the initial database. Patients who underwent RP for clinically localized PCa in our clinic from 2016 to 2021 were included in the study. Perioperative data were retrospectively reviewed for this study. Follow-up data including post-operative PSA and adjuvant treatment was prospectively gathered by contacting the patients or from the follow-up consultation. Final database was composed of 366 patients who underwent open or 3D laparoscopic RP. Statistical analysis was performed to emphasize the most powerful parameters that influence the BCR. Results: Accounting for multivariable analysis, 4 parameters were statistically significant: initial PSA (iPSA), Gleason score, vascular involvement and positive surgical margins. For the group of patients with no positive margins, 3 parameters were statistically significant: iPSA above 10,98 ng/mL (AUC=0,71); lymph node involvement and Gleason score. Multivariable Cox regression showed that positive margins and iPSA had a significant impact on the time to BCR. Patients that received adjuvant therapy were excluded from the study. Out of the whole cohort, 27,3% of patients presented BCR. Perioperative factors need to be carefully analyzed and a detailed follow-up needs to be conducted in order to assess the risk of biochemical recurrence, resulting in the optimal time for adjuvant treatment implementation.

Time Kinetics and prognosis roles of calcitonin after surgery for medullary thyroid carcinoma

BackgroundMedullary thyroid carcinoma (MTC) is a malignant tumor with low incidence. Currently, most studies have focused on the prognostic risk factors of MTC, whatever, time kinetic and risk factors related to calcitonin normalization (CN) and biochemical persistence/recurrence (BP) are yet to be elucidated.MethodsA retrospective study was conducted for 190 MTC patients. Risk factors related to calcitonin normalization (CN) and biochemical persistence/recurrence (BP) were analyzed. The predictors of calcitonin normalization time (CNT) and biochemical persistent/recurrent time (BPT) were identified. Further, the prognostic roles of CNT and BPT were also demonstrated.ResultsThe 5- and 10-year DFS were 86.7% and 70.2%, respectively. The 5- and 10-year OS were 97.6% and 78.8%, respectively. CN was achieved in 120 (63.2%) patients, whereas BP was presented in 76 (40.0%) patients at the last follow up. After curative surgery, 39 (32.5%) and 106 (88.3%) patients achieved CN within 1 week and 1 month. All patients who failed to achieve CN turned to BP over time and 32/70 of them developed structural recurrence. The median time of CNT and BPT was 1 month (1 day to 84 months) and 6 month (3 day to 63months), respectively. LNR > 0.23 and male gender were independent predictors for CN and BP. LNR > 0.23 (Hazard ratio (HR), 0.24; 95% CI,0.13–0.46; P < 0.01) and male gender (HR, 0.65; 95% CI, 0.42–0.99; P = 0.045) were independent predictors for longer CNT. LNR > 0.23 (HR,5.10; 95% CI,2.15–12.11; P < 0.01) was still the strongest independent predictor followed by preoperative serum Ctn > 1400ng/L (HR,2.34; 95% CI,1.29–4.25; P = 0.005) for shorter BPT. In survival analysis, primary tumor size > 2 cm (HR, 5.81; 95% CI,2.20-15.38; P < 0.01), CNT > 1 month (HR, 5.69; 95% CI, 1.17–27.61; P = 0.031) and multifocality (HR, 3.10; 95% CI, 1.45–6.65; P = 0.004) were independent predictor of DFS.ConclusionEarly changes of Ctn after curative surgery can predict the long-term risks of biochemical and structural recurrence, which provide a useful real-time prognostic information. LNR significantly affect the time kinetic of biochemical prognosis. Tumor burden and CNT play a crucial role in MTC survival, the intensity of follow-up must be tailored accordingly.

Development and validation of [18F]-PSMA-1007 PET-based radiomics model to predict biochemical recurrence-free survival following radical prostatectomy.

Biochemical recurrence (BCR) following radical prostatectomy (RP) is a significant concern for patients with prostate cancer. Reliable prediction models are needed to identify patients at risk for BCR and facilitate appropriate management. This study aimed to develop and validate a clinical-radiomics model based on preoperative [18F]PSMA-1007 PET for predicting BCR-free survival (BRFS) in patients who underwent RP for prostate cancer. A total of 236 patients with histologically confirmed prostate cancer who underwent RP were retrospectively analyzed. All patients had a preoperative [18F]PSMA-1007 PET/CT scan. Radiomics features were extracted from the primary tumor region on PET images. A radiomics signature was developed using the least absolute shrinkage and selection operator (LASSO) Cox regression model. The performance of the radiomics signature in predicting BRFS was assessed using Harrell's concordance index (C-index). The clinical-radiomics nomogram was constructed using the radiomics signature and clinical features. The model was externally validated in an independent cohort of 98 patients. The radiomics signature comprised three features and demonstrated a C-index of 0.76 (95% CI: 0.60-0.91) in the training cohort and 0.71 (95% CI: 0.63-0.79) in the validation cohort. The radiomics signature remained an independent predictor of BRFS in multivariable analysis (HR: 2.48, 95% CI: 1.47-4.17, p < 0.001). The clinical-radiomics nomogram significantly improved the prediction performance (C-index: 0.81, 95% CI: 0.66-0.95, p = 0.007) in the training cohort and (C-index: 0.78 95% CI: 0.63-0.89, p < 0.001) in the validation cohort. We developed and validated a novel [18F]PSMA-1007 PET-based clinical-radiomics model that can predict BRFS following RP in prostate cancer patients. This model may be useful in identifying patients with a higher risk of BCR, thus enabling personalized risk stratification and tailored management strategies.

CYP7B1 as a Biomarker for Prostate Cancer Risk and Progression: Metabolic and Oncogenic Signatures (Diagnostic Immunohistochemistry Analysis by Tissue Microarray in Prostate Cancer Patients-Diamond Study).

We aimed to analyze the association between CYP7B1 and prostate cancer, along with its association with proteins involved in cancer and metabolic processes. A retrospective analysis was performed on 390 patients with prostate cancer (PC) or benign prostatic hyperplasia (BPH). We investigated the interactions between CYP7B1 expression and proteins associated with PC and metabolic processes, followed by an analysis of the risk of biochemical recurrence based on CYP7B1 expression. Of the 139 patients with elevated CYP7B1 expression, 92.8% had prostate cancer. Overall, no increased risk of biochemical recurrence was associated with CYP7B1 expression. However, in a non-diabetic subgroup analysis, higher CYP7B1 expression indicated a higher risk of biochemical recurrence, with an HR of 1.78 (CI: 1.0-3.2, p = 0.05). PC is associated with elevated CYP7B1 expression. In a subgroup analysis of non-diabetic patients, elevated CYP7B1 expression was associated with an increased risk of biochemical recurrence, suggesting increased cancer aggressiveness.

Investigating the Role of SNAI1 and ZEB1 Expression in Prostate Cancer Progression and Immune Modulation of the Tumor Microenvironment.

Prostate cancer (PCa) is an immunologically cold tumor and the molecular processes that underlie this behavior are poorly understood. In this study, we investigated a primary cohort of intermediate-risk PCa (n = 51) using two NanoString profiling panels designed to study cancer progression and immune response. We identified differentially expressed genes (DEGs) and pathways associated with biochemical recurrence (BCR) and clinical risk. Confirmatory analysis was performed using the TCGA-PRAD cohort. Noteworthy DEGs included collagens such as COL1A1, COL1A2, and COL3A1. Changes in the distribution of collagens may influence the immune activity in the tumor microenvironment (TME). In addition, immune-related DEGs such as THY1, IRF5, and HLA-DRA were also identified. Enrichment analysis highlighted pathways such as those associated with angiogenesis, TGF-beta, UV response, and EMT. Among the 39 significant DEGs, 11 (28%) were identified as EMT target genes for ZEB1 using the Harmonizome database. Elevated ZEB1 expression correlated with reduced BCR risk. Immune landscape analysis revealed that ZEB1 was associated with increased immunosuppressive cell types in the TME, such as naïve B cells and M2 macrophages. Increased expression of both ZEB1 and SNAI1 was associated with elevated immune checkpoint expression. In the future, modulation of EMT could be beneficial for overcoming immunotherapy resistance in a cold tumor, such as PCa.

The impact of telomere length on prostate cancer aggressiveness, genomic instability and health disparities

The telomere repetitive TTAGGG motif at the ends of chromosomes, serves to preserve genomic integrity and chromosomal stability. In turn, genomic instability is a hallmark of cancer—implicating telomere disturbance. Prostate cancer (PCa) shows significant ancestral disparities, with men of African ancestry at the greatest risk for aggressive disease and associated genomic instability. Yet, no study has explored the role of telomere length (TL) with respect to ancestrally driven PCa health disparities. Patient- and technically-matched tumour-blood whole genome sequencing data for 179 ancestrally defined treatment naïve PCa patients (117 African, 62 European), we assessed for TL (blood and tumour) associations. We found shortened tumour TL to be associated with aggressive PCa presentation and elevated genomic instabilities, including percentage of genome alteration and copy number gains, in men of African ancestry. For European patients, tumour TL showed significant associations with PCa driver genes PTEN, TP53, MSH2, SETBP1 and DDX11L1, while shorter blood TL (< 3200 base pairs) and tumour TL (< 2861 base pairs) were correlated with higher risk for biochemical recurrence. Concurring with previous studies linking TL to PCa diagnosis and/or prognosis, for the first time we correlated TL differences with patient ancestry with important implications for future treatments targeting telomere dysfunction.

Abstract 3420: Androgen receptor (CAG)n polymorphism: A genomic marker for prostate cancer prognosis independent of histopathological parameters

Abstract The androgen receptor (AR) serves as a pivotal transcription factor in prostate cancer (PCa) development. Its transcriptional activity is linked to the number of glutamines in the N-terminal domain. While current screening for PCa and prognostic biomarkers include serum prostate-specific antigen (PSA) levels and histopathological characteristics (specifically, ISUP grade and margin involvement), the heterogeneity of these tumors underscores the need for additional markers to enhance clinical management. Thus, this study aimed at characterizing an Argentinian PCa patient cohort based on the CAG polymorphism (CAG)n in AR and establish associations between genotypes and clinical-pathological characteristics to refine disease prognosis. We designed a hospital-based case-case study for PCa patients to determine the association between AR polymorphisms and PCa biochemical relapse after radical prostatectomy (RP). We retrospectively recruited 112 patients histologically diagnosed with PCa at the Hospital de Clínicas José de San Martín, Buenos Aires, Argentina. All patients underwent RP as their primary therapeutic strategy. All patients were, by definition, Hispanics, predominantly of Caucasian ancestry and, at a lesser extent, Amerindian or African. Written informed consent and institutional review board approval were acquired. Blood samples were collected post-RP for genomic DNA extraction using the CTAB method. (CAG)n in AR was genotyped by fluorescent PCR followed by capillary electrophoresis, and correlations between genotypes and clinical-pathological variables were analyzed using R. Results categorized patients into three subgroups based on the length of the CAG tandem repeat in AR: long (&amp;gt;23 repeats, n=29), medium (20-23 repeats, n=44), and short (&amp;lt;20 repeats, n=38). No associations were found between the length of the polymorphism and age of diagnosis, pre-RP PSA serum values, ISUP grade, and margin involvement. However, patients with family cancer history had a higher frequency of the intermediate-length allele (p=0.02). Moreover, among patients with pre-RP PSA &amp;lt;10 ng/ml and intermediate-length allele had 2.72-fold risk of biochemical recurrence (BCR) (HR=2.72, 95%CI=1.05-7.03, p=0.039). Furthermore, multivariable BCR analysis including the ISUP grade and margin involvement as co-variates showed that the (CAG)n in AR was independent of these histopathological parameters (HRadj=3.37, 95%IC=1.24-9.10, padj=0.017). Altogether, the AR polymorphism is associated with family history of cancer. Consequently, determining the number of CAG repetitions in AR through a blood sample could serve as an independent prognostic marker in patients with PSA &amp;lt;10 ng/ml prior to PR, independent of the histopathological features. Citation Format: Gastón Mario Pascual, Agustina Sabater, Juan Bizzotto, Rocio Seniuk, Pablo Sanchis, Carlos M. Roggero, Carlos Scorticati, Osvaldo Mazza, Elba Vazquez, Ayelen Toro, Geraldine Gueron, Javier Cotignola. Androgen receptor (CAG)n polymorphism: A genomic marker for prostate cancer prognosis independent of histopathological parameters [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3420.

Abstract 299: FAP/αSMA association with tumor visibility and progression in prostate cancer

Abstract Introduction Prostate cancer (PCa) ranks as the second most frequently diagnosed cancer in the male population worldwide. The challenge in effectively managing PCa is the absence of well-established biological markers, which often leads to both over and under treatment. To address this issue, a deeper understanding of the molecular alterations within PCa is essential for more accurate patient stratification. In this research, we embark on a comprehensive examination of how the presence of fibroblast activation protein (FAP) and alpha smooth muscle actin (αSMA) in PCa tissue associates with the visibility of the disease in Magnetic Resonance Imaging (MRI) and their impact on cancer progression. The objective of this study is to analyze cell compartmental expression of FAP and aSMA using an AI based image analysis method. We also study the role of FAP and αSMA expression in predicting disease progression and mortality. Materials and Methods We applied FAP (ab207178, Abcam)/αSMA (M0851, DAKO) double chromogen immunohistochemical (IHC) staining to three independent cohorts of formalin-fixed paraffin-embedded (FFPE) prostate cancer tissue microarrays. All together, we analyzed 835 patients’ samples. First cohort consists of 387 patients with preoperative multiparametric MRI and robot-assisted laparoscopic prostatectomy (RALP) as primary treatment. Second cohort was case vs control cohort of Grade group 2-4 localized PCa at radical prostatectomy (RP) with 168 patients. Third cohort consists PCa patents from continuous, population-based collection of radical prostatectomies of 319 patients. Image analysis was performed with Aiforia Create, which is cloud-based deep-learning artificial intelligence software that provides platform for training and validating automated image analysis pipelines using convolutional neural networks. Analysis algorithm in this project was based on semantic, pixel-level area segmentation. Results FAP expression was higher and αSMA lower in MRI-visible tumors compared with MRI-invisible tumors. Stromal and epithelial FAP expression associate with tumor progression. We could also see statistically significant differences in FAP positivity between clinically significant (GS ≥7) and insignificant (GS ≤6) tumors. Hazard ratios imply that FAP and αSMA have significant impact on risk of biochemical recurrence in patients with MRI-visible tumors. Conclusions FAP is closely linked to tumor MRI visibility, cancer progression, and Gleason scores, marking it as a valuable biomarker in PCa assessment. High stromal αSMA is primarily associated with MRI visibility. Our automated AI-based image analysis method has demonstrated reliability, aligning with our previous findings. This advances the potential for more accurate and efficient prostate cancer diagnosis and prognosis, offering a potential benefit to future patient care. Citation Format: Jenni Säilä, Timo-Pekka Lehto, Annabrita Schoonenberg, Katja Välimäki, Andrew Erickson, Antti Rannikko, Olli Kallioniemi, Tuomas Mirtti, Teijo Pellinen. FAP/αSMA association with tumor visibility and progression in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 299.

Abstract 3813: Relationship between race/ethnicity and oncologic outcomes in patients with biochemical recurrence after primary treatment for prostate cancer

Abstract Background: Prostate cancer (PC) is the most common form of cancer in men and accounts for ~35% and 24% of all new cancer diagnoses in Black and Hispanic men, respectively. Incidence rates of PC are higher and cancer is diagnosed at a younger age in Black compared to White men. The most frequently utilized primary treatment options are radical prostatectomy (with or without adjuvant radiotherapy) or radiotherapy. Despite the success of primary treatments for localized PC, many patients (pts) will eventually develop biochemical recurrence (BCR), defined as rising prostate-specific antigen (PSA) levels. Pts with BCR are at a higher risk of developing distant metastases and ultimately dying from PC. This targeted literature review aimed to assess the real-world (RW) relationship between race/ethnicity and BCR, and further identify any differences in oncologic outcomes (risk of metastases, PC-specific mortality, and overall survival). Methods: A targeted literature search was performed using Embase, PubMed, and the past 2 years of American Society of Clinical Oncology conference proceedings. Selected studies were limited to English-language articles focusing on BCR and race or ethnicity among US populations, published between 1/2010 and 7/2023. Results: Ten studies were selected after title and abstract review. Most studies had a White pt majority (83%-92%). Six studies reported no differences in BCR or oncologic outcomes when pts were stratified by race/ethnicity. Four studies reported a higher BCR risk for Black pts with low-risk PC after radical prostatectomy, but not for pts with high-risk PC. PSA and PSA doubling time (PSADT) were found to be strong predictors of oncologic outcomes. Conclusions: The FDA draft guidance on diversity plans recommends that clinical trials enroll an adequate number of participants from underrepresented racial and ethnic populations. This requires an understanding of the diversity of the population that will eventually use the treatment and of which race/ethnicity differences in outcomes should be expected and investigated. Based on this targeted review among pts with localized PC, most RW studies had a White pt majority, and the race distribution in these studies aligned with published census and epidemiology data. In addition, findings suggest that race/ethnicity differences were not pronounced among high-risk PC pts in the US when given equal access to care or treatment, and that oncologic outcomes and BCR risk were similar across Black, White, and Hispanic pt populations. Conversely, PSA and PSADT may be stronger prognostic markers for BCR and oncologic outcomes. Future clinical trials are needed to support these RW findings and should aim to actively enroll racial/ethnic minorities to identify potential differences in efficacy and safety, and to help advance the evidence base for pt PC management. Citation Format: Nasreen Khan, Vanessa Quintero, Clara Beck, Miryana Dimova-Dobreva, Binita Patel. Relationship between race/ethnicity and oncologic outcomes in patients with biochemical recurrence after primary treatment for prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3813.

Abstract 5561: Whole slide Imaging Mass Cytometry allows the rapid profiling of the immune landscape of histopathologically aggressive prostate tumors

Abstract Patients with Gleason pattern 4 or 5 prostate tumors have a high risk of biochemical recurrence and worse survival. Affected by their local environment, dynamic immune cell phenotypes can both hinder or drive cancer progression. To understand the proteomic environments that facilitate specific immune cell responses and interactions in advanced prostate cancer, we have spatially resolved the immune cell content and metabolic features of Gleason pattern 4 and 5 and subpatterns of prostate tumors. To scale quantitative multiplexed histopathology measurements to human disease, we have applied a new high-throughput whole slide modality of high-plex Imaging Mass CytometryTM to simultaneously quantify immune cells, metabolic states, prostate specific pathways, and biomarkers in 125 whole slide sections from 42 patients over 100 cm2 of tissue. It is essential to image whole slide sections in order to fully evaluate the complete heterogeneity of these cancer samples. In parallel, multi-region macrodissection shotgun proteomics and both glycan and extracellular matrix MALDI imaging mass spectrometry have quantified the proteome associated with specific immune cell environments. Together, we identify localized proteomic microenvironments associated with specific tumor supportive or inhibitory immune cell content in human tumors that may help differentiate which high-risk patients will have a rapid biochemical recurrence following radical prostatectomy. Citation Format: Jennifer L. Gorman, Lydia Y. Liu, Jordan P. Hartig, Nikesh Parsotam, Amanda Khoo, Vladimir Ignatchenko, Sarah Asbury, Somi Afiuni, Ricardo Gonzalez, Michael J. Geuenich, Caitlin F. Harrigan, Yuju Lee, Jianan Chen, Liang Lim, Qanber Raza, Peggi M. Angel, Kieran Campbell, Stanley K. Liu, Michelle R. Downes, Richard R. Drake, Thomas Kislinger, David King, Hartland W. Jackson. Whole slide Imaging Mass Cytometry allows the rapid profiling of the immune landscape of histopathologically aggressive prostate tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5561.

Abstract 7669: Use of computational pathology to predict biochemical recurrence in prostate cancer (Pca) (Rp) patients following radical prostatectomy: Evaluation in low decipher risk category

Abstract Background: Current tools for predicting prostate cancer biochemical recurrence (BCR) after RP often depend on parameters determined by pathologists, such as tumor grade, which is known to vary between reviewers. Genomic risk classifiers provide useful information but require substantial tissue, are costly, and are not commonly accessible in many medical centers. The study presents an artificial intelligence (AI) model for automated risk assessment of biochemical recurrence (BCR) by analyzing nuclear morphologic patterns from Pca archival H&amp;E slides. Nuclear morphometric features are essential for disease diagnosis and gaining insights into cellular functions. Specifically, we sought to evaluate whether the computational pathology approach could provide additional granular risk stratification within the low-risk group identified by Decipher. Methods: The study employed two cohorts from the University of Pennsylvania D1 and D2. D1 comprised 180 patients, while D2 comprised 175 patients, including 63 individuals from the Decipher low-risk group. None of the patients in either cohort had received any pre-operative treatments. Within the Decipher cohort, a tumor segmentation model was created using the U-net deep learning network. The HoVer-Net model was used to both segment and classify nuclei. The feature extracted included a combination of nuclear texture and quantitative measurements of the spatial arrangement of nuclei. The eleven most significant features, selected via the least absolute shrinkage and selection operator (LASSO), were utilized to build a Cox regression model for predicting the risk of BCR in D1. In D2, patients were classified as either low-risk or high-risk for BCR based on the median risk score derived from D1. Results: Patients from D1 identified as high risk by the AI model experienced shorter survival, with a median BCR time of 27 months, in contrast to 55 months for those classified as low risk. The AI model demonstrated significant prognostic value for BCR in both D1 (HR = 6.82, 95% confidence interval [CI]: 3.54-13.12, p &amp;lt; 0.0019), and D2 (HR = 2.72, 95% CI: 1.53-4.82, p &amp;lt; 0.0032). Furthermore, the model effectively stratified the Decipher low-risk group in D2 into distinct low and high-risk categories (HR = 4.52, 95% confidence interval [CI]: 1.70-12.05, p &amp;lt; 0.0085). The most prognostic features identified included five related to nuclei shape diversity (Minor Axis Length, Eccentricity, Equivalent Diameter, Solidity, and Circularity) in conjunction with nine nuclear texture features. Conclusions: The AI model's findings suggest that a digital image-based prognostic classifier for prostate cancer could serve as an alternative or complementary method to molecular-based companion risk tests. Additional, independent multi-site and prospective validation of these findings are warranted. Citation Format: Kamal Hammouda, Tilak Pathak, Tuomas Mirtti, Priti Lal, Shilpa Gupta, Anant Madabhushi. Use of computational pathology to predict biochemical recurrence in prostate cancer (Pca) (Rp) patients following radical prostatectomy: Evaluation in low decipher risk category [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7669.

Abstract 3516: AI-derived features of 3D glandular networks are associated with likelihood of biochemical recurrence post radical prostatectomy

Abstract Introduction: Prostate cancer is the most common cancer in American men and is mainly diagnosed from two-dimensional histology sections. Recently, three-dimensional (3D) prostate histopathology has emerged as a valuable strategy to enhance the understanding of the disease by increasing microscopic sampling of specimens. This strategy enhances the microscopic examination of specimens by facilitating the analysis of the volumetric shape of cells and glands, as well as the pathway structures through entire biopsies and other morphological features. These aspects hold the potential to be linked with biochemical recurrence (BCR) outcomes. This study highlights the potential of features derived from the 3D structure of glands in samples of patients with prostate cancer for identifying patients who are at higher risk of BCR. Methods: Radical prostatectomy specimens were collected from 50 patients along with 5-year postoperative BCR follow-up from the University of Washington. A total of 118 ex vivo whole-biopsy 3D pathology images were obtained from RP by an open-top light-sheet microscopy platform. Images were converted into a synthetic CK8 immunofluorescence dataset using an image-sequence translation model. From these 3D images, a glandular structure mask was generated by a computer-vision algorithm. The 3D structure of prostate glands was modeled through a Tree-structure Extraction Algorithm for Accurate and Robust Skeletons (TEASER), which provides a simplification of the length of the gland, its shape, and its pathway. 91 features were then extracted from the glandular skeleton architecture. A 3-fold cross-validation approach was used in which patients were divided into training (D1) and test (D2) sets of 33 and 17 patients, respectively. Fisher’s score, used to select features based on their correlation to the outcome, was applied to D1 to identify the top 5 features most correlated with BCR. We then utilized these features to train a K-Nearest Neighbors classifier on D1, aimed at predicting whether a patient would experience BCR. The model’s performance was evaluated on D2 and averaged across all folds. Results: The classifier was able to accurately differentiate between BCR+ and BCR- patients, achieving an average ROCAUC of 0.73 (±0.04) in D2. Significant differences in 3D skeletal features were observed between BCR+ and BCR- groups (p&amp;lt;0.05). Among the five selected features, three were related to the length and diameter of the gland, with the longest glands observed in BCR- patients. The remaining two features pertained to gland curvature and tortuosity, revealing more twisted glands in BCR+ patients. Conclusion: Features derived from a skeleton model of the 3D glandular structure of biopsies showed promise in identifying patients with prostate cancer who are at a higher risk of BCR. Additional, multi-site independent validation of these findings is warranted. Citation Format: Jennifer Salguero, Hisham Abdeltawab, Kamal Hammouda, German Corredor, Sarah Hawley, Pushkar Mutha, Rohan Dhamdhere, Sebastian Medina, Tilak Pathak, Kevin Bishop, Rob Serafin, Tuomas Mirtti, Priti Lal, Lawrence True, Jonathan Liu, Anant Madabhushi. AI-derived features of 3D glandular networks are associated with likelihood of biochemical recurrence post radical prostatectomy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3516.

Contemporary risk of biochemical recurrence after radical prostatectomy in the active surveillance era

ObjectivesTo assess whether contemporary risks of biochemical recurrence (BCR) after radical prostatectomy (RP) in the AS era differ from historical estimates due to changes in tumor risk case mix and improvements in risk stratification. Materials and methodsWe sampled 6,682 men who underwent RP for clinically localized disease between 2000 and 2017 from the VA SEARCH database. Kaplan Meier analysis was used to calculate incidence of BCR before and after 2010 overall and within tumor risk subgroups. Multivariable Cox proportional hazard regression analysis including an interaction term between era and tumor risk was used to compare risk of BCR before and after 2010 overall and across tumor risk subgroups. ResultsAbout 3,492 (52%) and 3,190 (48%) men underwent RP before and after 2010, respectively. In a limited multivariable model excluding tumor risk, overall BCR risk was higher post-2010 vs. pre-2010 (HR: 1.15, 95%CI: 1.05–1.25; 40% vs 36% at 8 years post-RP). However, this effect was eliminated after correcting for tumor risk (HR: 0.95, 95%CI: 0.87–1.04), suggesting that differences in tumor risk between eras mediated the change. Yet, within tumor-risk subgroups, BCR risk was significantly lower for favorable intermediate-risk (HR: 0.76, 95%CI:0.60–0.96) and unfavorable intermediate-risk PC (HR: 0.78, 95%CI: 0.67–0.90), but significantly higher for high-risk PC (HR: 1.22, 95%CI: 1.07–1.38) in the post-2010 era. 8-year risks of BCR in the post-2010 era were 21% (95%CI: 16%–25%), 25% (95%CI: 20%–30%), 41% (95%CI: 37%–46%), and 60% (95%CI: 56%–64%) for low-, FIR-, UIR-, and high-risk disease, respectively. Limitations include limited long-term follow-up in the post-2010 subgroup. ConclusionsOverall BCR risk has increased in the AS era, driven by a higher risk case mix and increased BCR risk among high-risk patients. Physicians should quote contemporary estimates of BCR when counseling patients.

How Can We Identify Extraprostatic Extension (EPE) Before Surgery? The Use of a Preoperative Prostate MRI EPE Scoring System to Assess Postprostatectomy Locally Advanced Prostate Cancer.

Background: Distinguishing between organ-confined disease and extraprostatic extension (EPE) is crucial for the treatment of patients with prostate cancer. EPE is associated with an increased risk of biochemical recurrence, positive surgical margins, and metastatic disease. An MRI-based EPE scoring system was developed by Mehralivand in 2019; however, it has not been adopted in the Urology community. The purpose of this study is to evaluate the association of MRI-based EPE scoring with the pathologic EPE (pEPE) after radical prostatectomy. Methods: We conducted a retrospective review on a prospectively collected database of male patients who underwent a prostate MRI with EPE scoring by a trained genitourinary radiologist and subsequent robotic radical prostatectomy at our institution from September 2020 to December 2022. The associations between MRI EPE (mEPE) score and the presence of EPE on surgical pathology (pEPE) were examined using multivariable logistic regression. Results: A total of 194 patients met inclusion criteria with a median age of 63 years and prostate specific antigen (PSA) 7 ng/mL. Among those with mEPE score 3, 96% had pEPE. Those patients with an mEPE score ≥2 had an increased risk of pEPE compared with those with mEPE score 0 (odds ratio 3.79; 95% confidence interval 1.28-11.3) Furthermore, those with an mEPE score 3 were significantly more likely to have pEPE compared with those with mEPE score 0, 1 and 2 independently. Conclusion: MRI EPE is a straightforward tool that strongly correlates with the presence of pEPE. If validated prospectively, this scoring system could assist in counseling patients regarding nerve-sparing approach.

Patterns of B-cell lymphocyte expression changes in pre- and post-malignant prostate tissue are associated with prostate cancer progression.

Inflammation characterized by the presence of T and B cells is often observed in prostate cancer, but it is unclear how T- and B-cell levels change during carcinogenesis and whether such changes influence disease progression. The study used a retrospective sample of 73 prostate cancer cases (45 whites and 28 African Americans) that underwent surgery as their primary treatment and had a benign prostate biopsy at least 1 year before diagnosis. CD3+, CD4+, and CD20+ lymphocytes were quantified by immunohistochemistry in paired pre- and post-diagnostic benign prostate biopsy and tumor surgical specimens, respectively. Clusters of similar trends of expression across two different timepoints and three distinct prostate regions-benign biopsy glands (BBG), tumor-adjacent benign glands (TAG), and malignant tumor glandular (MTG) regions-were identified using Time-series Anytime Density Peaks Clustering (TADPole). A Cox proportional hazards model was used to estimate the hazard ratio (HR) of time to biochemical recurrence associated with region-specific lymphocyte counts and regional trends. The risk of biochemical recurrence was significantly reduced in men with an elevated CD20+ count in TAG (HR = 0.81, p = 0.01) after adjusting for covariates. Four distinct patterns of expression change across the BBG-TAG-MTG regions were identified for each marker. For CD20+, men with low expression in BBG and higher expression in TAG compared to MTG had an adjusted HR of 3.06 (p = 0.03) compared to the reference group that had nominal differences in CD20+ expression across all three regions. The two CD3+ expression patterns that featured lower CD3+ expression in the BBG compared to the TAG and MTG regions had elevated HRs ranging from 3.03 to 4.82 but did not reach statistical significance. Longitudinal and spatial expression patterns of both CD3+ and CD20+ suggest that increased expression in benign glands during prostate carcinogenesis is associated with an aggressive disease course.

Significance of the cribriform morphology area ratio for biochemical recurrence in Gleason score 4 + 4 prostate cancer patients following robot-assisted radical prostatectomy.

In prostate cancer, histological cribriform patterns are categorized as Gleason pattern 4, and recent studies have indicated that their size and percentage are associated with the risk of biochemical recurrence (BCR). However, these studies included a mixture of cases with various Gleason scores (GSs). We therefore examined the prognostic value of the area and percentage of cribriform patterns in patients with GS 4 + 4 prostate cancer. We investigated 108 patients with GS 4 + 4 prostate cancer who underwent robot-assisted radical prostatectomy (RARP). After digitally scanning the hematoxylin and eosin-stained slides, we measured the area of the entire cancer and cribriform patterns. Predictive factors for BCR were explored using log-rank test and Cox proportional hazard model analyses. Sixty-seven (62.0%) patients had a cribriform pattern in RARP specimens, and 32 (29.6%) experienced BCR. The median total cancer area, cribriform pattern area, and percentage of cribriform pattern area (% cribriform) were 427.70 mm2 (interquartile range [IQR], 171.65-688.53 mm2 ), 8.85 mm2 (IQR, 0-98.83 mm2 ), and 2.44% (IQR, 0%-33.70%), respectively. Univariate analyses showed that higher preoperative serum prostate-specific antigen (PSA) levels, positive resection margins, advanced pathological T stage, extraprostatic extension, larger total cancer area, larger cribriform morphology area, and higher % cribriform values were significantly associated with BCR. A multivariate analysis demonstrated that the PSA level (hazard ratio [HR], 1.061; 95% confidence interval [CI], 1.011-1.113; p = 0.017) and % cribriform (HR, 1.018; 95% CI, 1.005-1.031; p = 0.005) were independent predictors of BCR. An increased % cribriform value was associated with BCR in patients with GS 4 + 4 prostate cancer following RARP.

Radical prostatectomy cancer grade and percentage of Gleason pattern 4 estimated by global vs individual tumor grading correlate differently with the risk of biochemical recurrence in Grade Group 2 and 3 cancers.

There are 2 grading approaches to radical prostatectomy (RP) in multifocal cancer: Grade Group (GG) and percentage of Gleason pattern 4 (GP4%). We investigated whether RP GG and GP4% generated by global vs individual tumor grading correlate differently with biochemical recurrence. We reviewed 531 RP specimens with GG2 or GG3 cancer. Each tumor was scored separately with assessment of tumor volume and GP4%. Global grade and GP4% were assigned by combining Gleason pattern 3 and 4 volumes for all tumors. Correlation of GG and GP4% generated by 2 methods with biochemical recurrence was assessed by Cox proportional hazard regression and receiver operating characteristic curves, with optimism adjustment using a bootstrap analysis. Median age was 63 (range, 42-79) years. Median prostate-specific antigen was 6.3 (range, 0.3-62.9) ng/mL. In total, the highest-grade tumor in 371 (36.9%) men was GG2 and in 160 (30.1%) men was GG3. Global grading was downgraded from GG3 to GG2 in 37 of 121 (30.6%) specimens with multifocal disease, and 145 of 404 (35.9%) specimens had GP4% decreased by at least 10%. Ninety-eight men experienced biochemical recurrence within a median of 13 (range, 3-119) months. Men without biochemical recurrence were followed up for a median of 47 (range, 12-205) months. Grade Group, GP4%, and margin status correlated with the risk of biochemical recurrence using highest-grade tumor and global grading, but the degrees of these correlations varied and were statistically significantly different between the 2 grading approaches. Grade Group, GP4%, and margin status derived by global vs individual tumor grading predict postoperative biochemical recurrence statistically significantly differently. This difference has important implications if results derived from cohorts graded using different methods are compared.

Stroma-specific gene expression signature identifies prostate cancer subtype with high recurrence risk

Current prognostic tools cannot clearly distinguish indolent and aggressive prostate cancer (PC). We hypothesized that analyzing individual contributions of epithelial and stromal components in localized PC (LPC) could improve risk stratification, as stromal subtypes may have been overlooked due to the emphasis on malignant epithelial cells. Hence, we derived molecular subtypes of PC using gene expression analysis of LPC samples from prostatectomy patients (cohort 1, n = 127) and validated these subtypes in two independent prostatectomy cohorts (cohort 2, n = 406, cohort 3, n = 126). Stroma and epithelium-specific signatures were established from laser-capture microdissection data and non-negative matrix factorization was used to identify subtypes based on these signatures. Subtypes were functionally characterized by gene set and cell type enrichment analyses, and survival analysis was conducted. Three epithelial (E1-E3) and three stromal (S1-S3) PC subtypes were identified. While subtyping based on epithelial signatures showed inconsistent associations to biochemical recurrence (BCR), subtyping by stromal signatures was significantly associated with BCR in all three cohorts, with subtype S3 indicating high BCR risk. Subtype S3 exhibited distinct features, including significantly decreased cell-polarity and myogenesis, significantly increased infiltration of M2-polarized macrophages and CD8 + T-cells compared to subtype S1. For patients clinically classified as CAPRA-S intermediate risk, S3 improved prediction of BCR. This study demonstrates the potential of stromal signatures in identification of clinically relevant PC subtypes, and further indicated that stromal characterization may enhance risk stratification in LPC and may be particularly promising in cases with high prognostic ambiguity based on clinical parameters.

Identification of a 9-gene signature to enhance biochemical recurrence prediction in primary prostate cancer: A benchmarking study using ten machine learning methods and twelve patient cohorts

Prostate cancer (PCa) is a prevalent malignancy among men worldwide, and biochemical recurrence (BCR) after radical prostatectomy (RP) is a critical turning point commonly used to guide the development of treatment strategies for primary PCa. However, the clinical parameters currently in use are inadequate for precise risk stratification and informing treatment choice. To address this issue, we conducted a study that collected transcriptomic data and clinical information from 1662 primary PCa patients across 12 multicenter cohorts globally. We leveraged 101 algorithm combinations that consisted of 10 machine learning methods to develop and validate a 9-gene signature, named BCR SCR, for predicting the risk of BCR after RP. Our results demonstrated that BCR SCR generally outperformed 102 published prognostic signatures. We further established the clinical significance of these nine genes in PCa progression at the protein level through immunohistochemistry on Tissue Microarray (TMA). Moreover, our data showed that patients with higher BCR SCR tended to have higher rates of BCR and distant metastasis after radical radiotherapy. Through drug target prediction analysis, we identified nine potential therapeutic agents for patients with high BCR SCR. In conclusion, the newly developed BCR SCR has significant translational potential in accurately stratifying the risk of patients who undergo RP, monitoring treatment courses, and developing new therapies for the disease.