Metastatic castration-resistant prostate cancer (mCRPC) remains the primary cause of prostate cancer-related mortality. Despite the availability of treatments, the molecular mechanisms underlying tumor invasion and metastasis are not fully understood, highlighting the need for novel therapeutic strategies. In this study, we developed fully human monoclonal antibodies (mAbs) that prevent the proteolytic cleavage of the transforming growth factor-beta (TGFβ) type I receptor (TβRI) by steric hindrance. This cleavage, mediated by the metalloprotease ADAM17 (a disintegrin and metalloprotease domain 17; also known as TACE), results in the generation of a soluble intracellular domain (TβRI-ICD) that is translocated to the nucleus of castration-resistant prostate cancer (CRPC) cells and promotes epithelial-to-mesenchymal transition (EMT), invasion, and metastasis. High levels of TGFBR1 correlated with poor survival in two independent clinical cohorts of patients with mCRPC, and a strong positive correlation between TGFBR1 and ADAM17 expression was observed. In a preclinical human orthotopic mCRPC mouse model, treatment with therapeutic mAbs effectively prevented the nuclear accumulation of TβRI-ICD, inhibited EMT, and suppressed tumor growth, invasion, and metastasis. Notably, the therapeutic effect was comparable to that of docetaxel, a current standard-of-care chemotherapy, without noticeable side effects on body weight, proximal aorta or heart function detected in immune-deficient mice. These findings suggest that targeting TβRI cleavage using specific mAbs is a novel precision medicine approach for the treatment of mCRPC. By selectively blocking the prometastatic activity of TβRI-ICD without disrupting physiological TGFβ signaling, this strategy may provide a safer and more effective alternative to existing therapies for advanced prostate cancer.

Prostate cancer (PCa) is common world-wide. Current diagnostics based on testing for circulating levels of prostate specific antigen (PSA) is unspecific, and novel prognostic markers are needed for personalized therapeutic strategies. Pro-neuropeptide Y (pro-NPY) has been reported as a tissue marker for PCa related to poor prognosis. This study explored the prognostic value of circulating pro-NPY in PCa. Plasma samples were obtained from two patient cohorts: (1) men examined due to increased PSA levels in 2003-2011 (n = 796) and (2) patients treated for PCa in 2013-2016 (n = 92). Cohort 2 also provided plasma samples collected ~ 3 months after therapy. For plasma pro-NPY assessment, a sandwich immunoassay was developed. In cohort 1, 315 patients were diagnosed with PCa at the time for blood sampling, 137 were diagnosed during follow-up, and 344 remained disease-free. Plasma pro-NPY provided independent prognostic information from PSA regarding time to metastasis and PCa death. In cohort 2, high plasma pro-NPY levels were confirmed associated with metastatic disease and poor survival. Plasma pro-NPY levels were normalized after androgen-deprivation therapy, suggesting androgen-regulation. In conclusion, high circulating pro-NPY levels are associated with metastasis and poor outcome in PCa. Prospective validation is needed before suggesting pro-NPY for clinical use. The underlying biology and consequences of pro-NPY overexpression remain to be understood.

Novel treatments for metastatic prostate cancer (PC) are needed. Molecular subtypes of bone metastatic PC (MetA-C) were recently identified, with the proliferation-driven MetB subtype linked to very poor prognosis. Non-coding microRNAs (miRs) regulate gene expression and constitute potential therapeutic targets. This study aimed to explore miR profiles in bone metastases in relation to the MetA-C subtypes, with focus on the aggressive MetB subtype. Genome-wide microarray analysis of clinical bone metastasis samples (n = 96, 62 patients) identified miR-375 to be inversely associated with the MetB subtype. The metastatic C4-2B cell line was transduced to overexpress or sequester miR-375 and effects were evaluated by microarray analysis, cell proliferation/adhesion assays, and tumor growth in mice. miR-375 overexpression in C4-2B altered transcription profiles and shifted the phenotype from being MetB-like to becoming MetA-like. In cell culture, miR-375 overexpression reduced cell proliferation, increased adhesion, and downregulated YAP1 expression among other direct gene targets, while miR-375 inhibition had opposite effects. In mice, miR-375 overexpression reduced tumor establishment and growth. Our data link clinical and experimental findings of miR-375 being a potential inhibitor of the aggressive MetB subtype in PC.

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.

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.

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.

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.

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. 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

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.

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.

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.

Background and purpose Dose escalation in external radiotherapy of prostate cancer shows promising results in terms of biochemical disease-free survival. Boost volume delineation guidelines are sparse which may cause high interobserver variability. The aim of this research was to characterize gross tumor volume (GTV) delineations based on multiparametric magnetic resonance imaging (mpMRI) and prostate specific membrane antigen-positron emission tomography (PSMA-PET) in relation to histopathology-validated Gleason grade 4 and 5 regions. Material and methods The study participants were examined with [68Ga]PSMA-PET/mpMRI prior to radical prostatectomy. Four radiation oncologists delineated GTVs in 15 study participants, on four different image types; T2-weighted (T2w), diffusion weighted imaging (DWI), dynamic contrast enhanced (DCE) and PSMA-PET scans separately. The simultaneous truth and performance level estimation (STAPLE) algorithm was used to generate combined GTVs. GTVs were subsequently compared to histopathology. We analysed how Dice similarity coefficient (DSC) and lesion coverage are affected by using single versus multiple image types as well as by adding a clinical target volume (CTV) margin. Results Median DSC (STAPLE) for different GTVs varied between 0.33 and 0.52. GTVPSMA-PET/mpMRI generated the highest median lesion coverage at 0.66. Combining different image types achieved similar lesion coverage as adding a CTV margin to contours from a single image type, while reducing non-malignant tissue inclusion within the target volume. Conclusion The combined use of mpMRI or PSMA-PET/mpMRI shows promise, achieving higher DSC and lesion coverage while minimizing non-malignant tissue inclusion, in comparison to the use of a single image type with an added CTV margin.

Background and Objective: Diagnostic needle biopsies that miss clinically significant prostate cancers (PCa) likely sample benign tissue adjacent to cancer. Such samples may contain changes indicating the presence of cancer elsewhere in the organ. Our goal is to evaluate if artificial intelligence (AI) can identify morphological characteristics in benign biopsies of men with raised PSA that predict the future detection of clinically significant PCa during a 30-month follow-up. Methods: A retrospective cohort of 232 patients with raised PSA and benign needle biopsies, paired by age, year of diagnosis and PSA levels was collected. Half were diagnosed with PCa within 30 months, while the other half remained cancer-free for at least eight years. AI model performance was assessed using the area under the receiver operating characteristic curve (AUC) and attention maps were used to visualise the morphological patterns relevant for cancer diagnosis as captured by the model. Key findings and Limitations: The AI model could identify patients that were later diagnosed with PCa from their initial benign biopsies with an AUC of 0.82. Distinctive morphological patterns, such as altered stromal collagen and changes in glandular epithelial cell composition, were revealed. Conclusions and Clinical Implications: AI applied to standard haematoxylin-eosin sections identifies patients initially diagnosed as negative but later found to have clinically significant PCa. Morphological patterns offer insights into the long-ranging effects of PCa in the benign parts of the tumour-bearing organ. Patient Summary: Using AI, we identified subtle changes in normal prostate tissue suggesting the presence of tumours elsewhere in the prostate. This could aid in the early identification of potentially high-risk tumours, limiting overuse of prostate biopsies. ### Competing Interest Statement C.W. is on the advisory board of Navinci Diagnostics, Sweden. ### Funding Statement This research was funded by the European Research Council via ERC Consolidator grant CoG 682810 and Technology Development project from SciLifeLab to C.W and grant no 21-1856 from the Swedish Cancer Society to A.B. The computations were enabled by the Berzelius resource provided by the Knut and Alice Wallenberg Foundation at the National Supercomputer Centre. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethical approval was granted from Regionala etikprövningsnämnden i Umeå, DNR 2010/366-31M. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Alterations in deoxyribonucleoside triphosphate (dNTP) pools have been linked to increased mutation rates and genome instability in unicellular organisms and cell cultures. However, the role of dNTP pool changes in tumor development in mammals remains unclear. In this study, we present a mouse model with a point mutation at the allosteric specificity site of ribonucleotide reductase, RRM1-Y285A. This mutation reduced ribonucleotide reductase activity, impairing the synthesis of deoxyadenosine triphosphate (dATP) and deoxyguanosine triphosphate (dGTP). Heterozygous Rrm1+/Y285A mice exhibited distinct alterations in dNTP pools across various organs, shorter lifespans and earlier tumor onset compared with wild-type controls. Mutational spectrum analysis of tumors revealed two distinct signatures, one resembling a signature extracted from a human cancer harboring a mutation of the same amino acid residue in ribonucleotide reductase, RRM1Y285C. Our findings suggest that mutations in enzymes involved in dNTP metabolism can serve as drivers of cancer development.

Background and purpose:Dose escalation in external radiotherapy of prostate cancer shows promising results in terms of biochemical disease-free survival. Boost volume delineation guidelines are sparse which may cause high interobserver variability. The aim of this research was to characterize gross tumor volume (GTV) delineations based on multiparametric magnetic resonance imaging (mpMRI) and prostate specific membrane antigen-positron emission tomography (PSMA-PET) in relation to histopathology-validated Gleason grade 4 and 5 regions. Material and methods:The study participants were examined with [68Ga]PSMA-PET/mpMRI prior to radical prostatectomy. Four radiation oncologists delineated GTVs in 15 study participants, on four different image types; T2-weighted (T2w), diffusion weighted imaging (DWI), dynamic contrast enhanced (DCE) and PSMA-PET scans separately. The simultaneous truth and performance level estimation (STAPLE) algorithm was used to generate combined GTVs. GTVs were subsequently compared to histopathology. We analysed how Dice similarity coefficient (DSC) and lesion coverage are affected by using single versus multiple image types as well as by adding a clinical target volume (CTV) margin. Results:Median DSC (STAPLE) for different GTVs varied between 0.33 and 0.52. GTVPSMA-PET/mpMRI generated the highest median lesion coverage at 0.66. Combining different image types achieved similar lesion coverage as adding a CTV margin to contours from a single image type, while reducing non-malignant tissue inclusion within the target volume. Conclusion:The combined use of mpMRI or PSMA-PET/mpMRI shows promise, achieving higher DSC and lesion coverage while minimizing non-malignant tissue inclusion, in comparison to the use of a single image type with an added CTV margin.