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Prostate cancer treatment depends on whether the cancer exists only inside the gland or within the prostate capsule or on the outside surface of the gland. The presence on the outside surface indicates migration of the cancer to adjacent organs. This study presents a novel method for detecting prostate cancer (PCa) on the surface of excised prostate glands using Raman spectroscopy and stiffness measurements. The workflow involves assessing the location and extent of PCa via MRI before surgery, followed by 3D scanning of the excised prostate. Key positions on ten excised prostates, 211 positions with 56 deemed as cancer, are measured using Raman spectroscopy and stiffness probes. The results are mapped onto a digital representation of the prostate to aid surgical decision-making. Statistical analysis of the Raman data indicates that spectra could be divided into two components, one more related to cancer and one more related to normal tissue. A stiffness parameter was calculated from resonance measurements from the stiffness probe. The Raman components and stiffness parameters were converted to z-scores. Logistic generalized linear mixed modelling revealed that the stiffness parameter was statistically associated with cancer presence in prostate regions (p = 0.009). The scanning equipment is easy to handle and makes further larger studies possible. This method holds promise for providing real-time support during surgery, reducing the need for post-surgical therapies and minimizing patient distress.

Prostate cancer is a heterogeneous disease showing variability both among individuals and within a patient. While most cases are indolent, aggressive tumors require early intervention. Accurately predicting tumor behavior is challenging, contributing to overdiagnosis but also undertreatment. Current imaging methods may miss the most malignant areas, leading to biopsies often capturing non-malignant prostate tissue even if cancer is present elsewhere in the organ. This non-malignant tissue, however, holds potential as a source for novel diagnostic and prognostic markers. Our clinical dataset comprises men with raised prostate-specific antigen but whose initial prostate needle biopsies only contained benign tissue. Half of the paired patients remained cancer-free for over eight years, while the others were diagnosed with prostate cancer within 30 months of follow-up. We share these initial benign biopsies to enable the exploration of morphological changes in non-malignant tissue and the potential for improved diagnostic accuracy in the early identification of patients with prostate cancer.

Metastatic prostate cancer is incurable, and new therapeutic targets and drugs are urgently needed. Viral infections are associated with several cancer types, but a link between viruses and prostate oncogenesis has not been established. Only recently, an association between human cytomegalovirus (CMV) seropositivity and increased risk of prostate cancer mortality was demonstrated. Here, we show that CMV infection is common in the normal prostate epithelium and in prostate tumor tissue, with 70–92% of tumors being infected. Additionally, we report that commonly studied prostate cancer cell lines are CMV infected. Loss-of-function experiments demonstrate that CMV promotes cell survival, proliferation, and androgen receptor signaling, identifying it as a therapeutic target in castration-sensitive and castration-resistant prostate cancer. Several anti-CMV pharmaceutical compounds in clinical use inhibited cell expansion in prostate cancer models both in vitro and in vivo. We conclude that CMV is common in prostate cancer, promotes core prostate cancer cell programs, and can be inhibited by well-tolerated drugs. These findings motivate investigation into potential clinical benefits of CMV inhibition in the treatment of prostate cancer.

Diagnostic needle biopsies that miss clinically significant prostate cancer (PCa) often sample benign tissue near hidden cancers. Such benign samples might still display subtle morphological signs of cancer elsewhere in the prostate. This study examined if artificial intelligence (AI) could detect these morphological clues in benign biopsies from men with elevated prostate-specific antigen (PSA) levels to predict subsequent diagnosis of clinically significant PCa within 30 months. We analysed biopsies from 232 men initially diagnosed as benign, matched for age, diagnosis year, and PSA levels-half were later diagnosed with PCa, while the rest remained cancer-free for at least eight years. The AI model accurately predicted future PCa diagnosis from initial benign biopsies (AUC = 0.82), highlighting patterns such as changes in stromal collagen and altered glandular epithelial cells. This demonstrates that AI analysis of routine haematoxylin-eosin biopsy sections can detect subtle signs indicating clinically significant PCa before it becomes histologically apparent. Such morphological patterns shed light on the broader tissue alterations induced by prostate cancer, even in benign tissue, potentially enhancing early detection and clinical decision-making.

Background: Accurate diagnosis and staging are essential for optimal treatment planning of prostate cancer. By combining functional and anatomical imaging, PSMA-PET/mpMRI offers a potential to improve lesion detection and enhance staging accuracy. This study aimed to evaluate the diagnostic performance of lesion detection and local staging of prostate cancer using combined PSMA-PET/mpMRI compared to standalone mpMRI or PSMA-PET.

Results: Fifty-five patients with intermediate- to high-risk prostate cancer scheduled for robot-assisted laparoscopic radical prostatectomy were included. All patients underwent [68Ga]PSMA-PET/mpMRI prior to surgery. Whole-mount histopathology and surgical report served as reference standard. Two radiologists independently evaluated mpMRI, while two nuclear medicine physicians assessed PSMA-PET. For the PSMA-PET/mpMRI analysis, a consensus evaluation was performed by a new set of readers in two teams, each comprising one radiologist and one nuclear medicine physician. Lesion localization was reported based on the PI-RADS v2.1 sector map and compared to histopathology. Among 130 histopathologically confirmed lesions, mean detection rates were 38% (49.5/130) for PSMA-PET/mpMRI, 32% (41/130) for mpMRI and 32% (41/130) for PSMA-PET. For clinically significant prostate cancer (csPC) (≥0.5 ml, ≥ISUP 2; 42 lesions), mean detection rates were 85% (35.5/42) for PSMA-PET/mpMRI, 75% (31.5/42) for mpMRI and 70% (29.5/42) for PSMA-PET. The mean false discovery rates were 8% (PSMA-PET/mpMRI), 15% (mpMRI) and 12% (PSMA-PET). The likelihood of extraprostatic extension (EPE) and seminal vesicle invasion (SVI) were scored using a 5-point Likert scale, where scores of 1–3 were classified as negative and scores of 4–5 were considered positive. Sensitivity for EPE was 32% for PSMA-PET/mpMRI, 37% for mpMRI and 7% for PSMA-PET, with a specificity of 100%, 96% and 98%, respectively. For SVI, sensitivity was 50% for PSMA-PET/mpMRI and 38% for mpMRI and PSMA-PET, with a specificity of 100%, 95% and 97% respectively.

Conclusions: PSMA-PET/mpMRI provided higher and a more consistent performance in localized prostate cancer detection and staging without increasing false-positive findings.

Introduction: Prostate cancer (PC) diagnosis relies on histopathological examination of prostate biopsies, which is restricted by insufficient sampling of all tumors present. Including samples from non-PC but tumor instructed normal tissues (TINT) may increase the diagnostic power by displaying the adaptive responses in benign tissues near tumors.

Methods: Here, we applied high-resolution magic angle spinning nuclear magnetic resonance (HR MAS NMR) to identify metabolomic biomarkers of possible diagnostic value in benign prostate tissues near low/high-grade tumors.

Results: Benign samples near high-grade tumors (B ISUP 3 + 4) exhibited altered metabolic profiles compared to those close to low-grade tumors (B ISUP 1 + 2). The levels of six metabolites differentiated between the two groups; myo-inositol, lysine, serine and combined signal of lysine/leucine/arginine were increased in benign samples near high-grade tumors (B ISUP 3 + 4) compared to near low-grade tumors (B ISUP 1 + 2), while levels of ethanolamine and lactate were decreased. Additionally, we revealed metabolic differences in non-cancer tissues as a function of their distance to the nearest tumor. Eight metabolites (glutathione, glutamate, combined signal of glutamate/glutamine - glx, glycerol, inosine, ethanolamine, serine and arginine) differentiated between benign tissue located close to the tumor (d ≤ 5 mm) compared to those far away (d ≥ 1 cm).

Conclusion: Our HR MAS NMR-based approach identified metabolic signatures in prostate biopsies that reflect the response of benign tissues to the presence of nearby located tumors in the same prostate and confirmed the power of the TINT concept for improved PC diagnostics and understanding of tumor-tissue interactions.

We previously identified three molecular subtypes of prostate cancer (PC) bone metastases, MetA-C, with MetB linked to poor prognosis after androgen deprivation therapy (ADT). This study analyzed epithelial and stromal markers using immunohistochemistry, focusing on their relationship to MetA-C subtypes, spatial heterogeneities, and clinical outcomes after ADT. High tumor proliferation and low PSA expression were associated with MetB and poor outcomes after ADT. Most metastases contained tumor epithelial subclones with different morphologies. In the metastasis stroma, blood vessels and fibroblast-like cells expressed smooth muscle actin (SMA), platelet-derived growth factor β, stroma-derived factor 1 (SDF1), periostin (POSTN), and decorin (DCN). Compared to each other, MetB metastases had higher SMA and ERG + endothelial cell densities, while MetA cases showed higher SDF1 and DCN levels. Accordingly, high POSTN and ERG + densities were associated with poor outcomes after ADT, whereas high DCN indicated favorable prognosis. Low levels of AR-positive stromal cells were linked to poor outcomes. Macrophage and T-lymphocyte densities showed no significant associations with metastases subtypes or outcome. Two stroma subtypes were identified: subtype 1 with higher bone content, lower vessel density, MetA-enrichment and better prognosis compared to subtype 2 that exhibited higher tumor proliferation and lower PSA expression. Most metastases contained regions of both stroma subtypes.

BACKGROUND AND PURPOSE: The study aims to evaluate dosimetric properties of hypofractionated treatment plans integrating focal boost, using registered whole-mount histopathology (WMHP) as reference standard.

METHODS: Fifteen men from the PAMP trial (EudraCT: 2015-005046-55) were included. Participants had ≥ 1 ISUP Grade group ≥ 4 lesion and underwent [⁶⁸Ga]prostate-specific membrane antigen (PSMA) positron emission tomography/multiparametric magnetic resonance imaging (PET/mpMRI) and [¹¹C]Acetate-PET/computed tomography before radical prostatectomy. Four radiation oncologists delineated gross tumor volumes (GTVs) on PSMA-PET/mpMRI. Sixty treatment plans were optimized, one per GTV and patient. Prostate planning target volumes were prescribed 42.7 Gy in seven fractions, with a simultaneous GTV boost up to 49.0 Gy, prioritizing organs at risk (OARs). Digital WMHP provided Gleason grading and was co-registered with in-vivo imaging. Target coverage for GTVs and voxels sharing Gleason patterns (GPs) was assessed via dose-volume histogram (DVH) analysis. Interobserver agreement in GTV-delineations was quantified with Fleiss' kappa.

RESULTS: The median GTV dose per plan (D50) ranged from 48.3 to 49.1 Gy. For voxels with the highest GP, D₅₀ was 42.9-49.2 Gy, exceeding 47.2 Gy in all except one plan. In lowest pattern voxels, D₅₀ was 42.5-49.3 Gy, and below 43.4 Gy in over half the plans. Significant positive correlations between Fleiss' kappa and DVH parameters appeared only for GP 5 regions, specifically for Fleiss' kappa and D₅₀ for two observers and the average D₅₀ across observers.

INTERPRETATION: The histologically confirmed tumor was only partially boosted. Regions with more aggressive disease received better coverage. These findings provide a rational for prioritizing OARs in treatment planning.

BACKGROUND: The delineation of intraprostatic lesions is vital for correct delivery of focal radiotherapy boost in patients with prostate cancer (PC). Errors in the delineation could translate into reduced tumour control and potentially increase the side effects. The purpose of this study is to compare PET-based delineation methods with histopathology.

MATERIALS AND METHODS: The study population consisted of 15 patients with confirmed high-risk PC intended for prostatectomy. [68Ga]-PSMA-PET/MR was performed prior to surgery. Prostate lesions identified in histopathology were transferred to the in vivo [68Ga]-PSMA-PET/MR coordinate system. Four radiation oncologists manually delineated intraprostatic lesions based on PET data. Various semi-automatic segmentation methods were employed, including absolute and relative thresholds, adaptive threshold, and multi-level Otsu threshold.

RESULTS: The gross tumour volumes (GTVs) delineated by the oncologists showed a moderate level of interobserver agreement with Dice similarity coefficient (DSC) of 0.68. In comparison with histopathology, manual delineations exhibited the highest median DSC and the lowest false discovery rate (FDR) among all approaches. Among semi-automatic approaches, GTVs generated using standardized uptake value (SUV) thresholds above 4 (SUV > 4) demonstrated the highest median DSC (0.41), with 0.51 median lesion coverage ratio, FDR of 0.66 and the 95th percentile of the Hausdorff distance (HD95%) of 8.22 mm.

INTERPRETATION: Manual delineations showed a moderate level of interobserver agreement. Compared to histopathology, manual delineations and SUV > 4 exhibited the highest DSC and the lowest HD95% values. The methods that resulted in a high lesion coverage were associated with a large overestimation of the size of the lesions.