Biomarker For Prostate Cancer Research Articles

Investigating miR-6880-5p in extracellular vesicle from plasma as a prognostic biomarker in endocrine therapy-treated castration-resistant prostate cancer

BackgroundAdvancements in the diagnosis, treatment, and surveillance of castration-resistant prostate cancer (CRPC) have progressed considerably, but a new biomarker that combines existing clinical and pathological data could be useful for a more precise diagnosis and prognosis. Some investigations have found that extracellular vesicle (EV)-derived miRNAs play crucial roles in various types of malignant tumors. The objective of this study was to explore EV miRNA and identify its biologic function as a biomarker for the diagnosis and prognosis of CRPC.MethodsPlasma samples were collected from five healthy donors (Control, CT) and 17 CRPC patients, categorizing into two groups based on their endocrine treatment response: partial response (PR; n = 10) and progressive disease (PD; n = 7). Candidate extracellular vesicle (EV) miRNAs were identified using miRNA microarray and RT-qPCR. The biological functions of the selected miRNAs were evaluated using the MTT assay, wound healing assay, trans-well assay, and RNA sequencing in CRPC cells after transient miRNA expression.ResultsMicroarray analysis revealed a significant downregulation of EV-miR-6880-5p in the PD samples compared to both CT and PR samples (p < 0.01). The expression of EV-miR-6880-5p in CRPC patients was decreased compared with that CT group (p = 0.0336) using RT-qPCR. In the PR group, EV-miR-6880-5p was increased at follow-up compared with the baseline (p = 0.2803), while in the PD group, it decreased at follow-up compared with the baseline samples (p = 0.4356). Furthermore, overexpression of miR-6880-5p hampered cell proliferation, migration, and invasion, downregulated pathways associated with tumor progression, and simultaneously upregulated pathways associated with cell growth and apoptosis in CRPC cells.ConclusionsEV-miR-6880-5p shows promise as a prognostic biomarker in patients with CRPC. Further, prospective validations are necessary to evaluate the potential of these candidate miRNAs.

An electrochemical/SERS dual-mode immunosensor using TMB/Au nanotag and Au@2D-MoS2 modified screen-printed electrode for sensitive detection of prostate cancer biomarker

This study describes a novel dual-mode immunosensor that combines electrochemical (EC) and surface-enhanced Raman scattering (SERS) techniques for the detection of prostate-specific antigen (PSA), a biomarker associated with prostate cancer. The sensor consists of a nanocomposite of gold nanoparticles (AuNPs) deposited on two-dimensional (2D) molybdenum disulfide (Au@MoS2) modified on a working carbon electrode of a screen-printed electrode (SPE). Subsequently, the primary antibody (Ab1) is immobilized on the modified electrode, creating Ab1/Au@MoS2/SPE for specific recognition of the target PSA. In parallel, AuNPs are conjugated with a secondary antibody (Ab2) and a probe molecule, 3,3′,5,5′-tetramethylbenzidine (TMB), leading nanotags (TMB/Ab2/AuNPs) formation exhibiting strong SERS and EC responses. Upon the presence of the target, sandwich immunocomplexes can be formed through antigen-antibody interactions (Ab1-PSA-Ab2). The differential pulse voltammetry (DPV) technique is employed for EC detection mode, while a handheld Raman spectrometer with a 785 nm excitation laser is utilized to collect SERS signals. The developed system demonstrates excellent selectivity and sensitivity, with low limits of detection (LODs) of 3.58 pg mL−1 and 4.83 pg mL−1 for EC and SERS sensing, respectively. Importantly, the dual-mode immunosensor proves effective quantifying PSA protein in human serum samples with good recovery. Given its high sensitivity and proficiency in analyzing biological samples, this proposed immunosensor holds promise as an alternative tool for the early diagnosis of cancers.

Enzymatic cascade reactors on carbon nanotube transistor detecting trace prostate cancer biomarker

Biosensors based on carbon nanotube field-effect transistors (CNT-FETs) have shown great potential in biomarker detection due to their high sensitivity because of appreciable semiconducting electrical properties. However, background signal interferences in complex mediums may results in low signal-to-noise ratio, which may impose challenges for precise biomarker detection in physiological fluids. In this work, we develop an enzymatic CNT-FET, with scalable production at wafer scale, for detection of trace sarcosine that is a biopsy-correlated biomarker of prostate cancer. Enzymatic cascade rectors are constructed on the CNT to improve the reaction efficiency, thereby, enhancing the signal transduction. As such, a limit of detection as low as 105 zM is achieved in buffer solution. Owing to the enhanced reaction efficiency, the testing of clinical serum samples yields significant signal difference to discriminate the prostate cancer (PCa) samples from the benign prostatic hyperplasia (BPH) samples (P = 1.07 × 10−5), demonstrating immense potential in practical applications.

Stockholm3 in a Multiethnic Cohort for Prostate Cancer Detection (SEPTA): A Prospective Multicentered Trial.

Asian, Black, and Hispanic men are underrepresented in prostate cancer (PCa) clinical trials. Few novel prostate cancer biomarkers have been validated in diverse cohorts. We aimed to determine if Stockholm3 can improve prostate cancer detection in a diverse cohort. An observational prospective multicentered (17 sites) clinical trial (2019-2023), supplemented by prospectively recruited participants (2008-2020) in a urology clinic setting included men with suspicion of PCa and underwent prostate biopsy. Before biopsy, sample was collected for measurement of the Stockholm3 risk score. Parameters include prostate-specific antigen (PSA), free PSA, KLK2, GDF15, PSP94, germline risk (single-nucleotide polymorphisms), age, family history, and previous negative biopsy. The primary endpoint was detection of International Society of Urological Pathology (ISUP) Grade ≥2 cancer (clinically significant PCa, csPC). The two primary aims were to (1) demonstrate noninferior sensitivity (0.8 lower bound 95% CI noninferiority margin) in detecting csPC using Stockholm3 compared with PSA (relative sensitivity) and (2) demonstrate superior specificity by reducing biopsies with benign results or low-grade cancers (relative specificity). A total of 2,129 biopsied participants were included: Asian (16%, 350), Black or African American (Black; 24%, 505), Hispanic or Latino and White (Hispanic; 14%, 305), and non-Hispanic or non-Latino and White (White; 46%, 969). Overall, Stockholm3 showed noninferior sensitivity compared with PSA ≥4 ng/mL (relative sensitivity: 0.95 [95% CI, 0.92 to 0.99]) and nearly three times higher specificity (relative specificity: 2.91 [95% CI, 2.63 to 3.22]). Results were consistent across racial and ethnic subgroups: noninferior sensitivity (0.91-0.98) and superior specificity (2.51-4.70). Compared with PSA, Stockholm3 could reduce benign and ISUP 1 biopsies by 45% overall and between 42% and 52% across racial and ethnic subgroups. In a substantially diverse population, Stockholm3 significantly reduces unnecessary prostate biopsies while maintaining a similar sensitivity to PSA in detecting csPC.

High Sensitivity and Specificity Platform to Validate MicroRNA Biomarkers in Cancer and Human Diseases.

We developed a technology for detecting and quantifying trace nucleic acids using a bracketing protocol designed to yield a copy number with approximately ± 20% accuracy across all concentrations. The microRNAs (miRNAs) let-7b, miR-15b, miR-21, miR-375 and miR-141 were measured in serum and urine samples from healthy subjects and patients with breast, prostate or pancreatic cancer. Detection and quantification were amplification-free and enabled using osmium-tagged probes and MinION, a nanopore array detection device. Combined serum from healthy men (Sigma-Aldrich, St. Louis, MO, USA #H6914) was used as a reference. Total RNA isolated from biospecimens using commercial kits was used as the miRNA source. The unprecedented ± 20% accuracy led to the conclusion that miRNA copy numbers must be normalized to the same RNA content, which in turn illustrates (i) independence from age, sex and ethnicity, as well as (ii) equivalence between serum and urine. miR-21, miR-375 and miR-141 copies in cancers were 1.8-fold overexpressed, exhibited zero overlap with healthy samples and had a p-value of 1.6 × 10-22, tentatively validating each miRNA as a multi-cancer biomarker. miR-15b was confirmed to be cancer-independent, whereas let-7b appeared to be a cancer biomarker for prostate and breast cancer, but not for pancreatic cancer.

PSA, an outdated biomarker for prostate cancer: In search of a more specific biomarker, citrate takes the spotlight

The prevailing biomarker employed for prostate cancer (PCa) screening and diagnosis is the prostate-specific antigen (PSA). Despite excellent sensitivity, PSA lacks specificity, leading to false positives, unnecessary biopsies and overdiagnosis. Consequently, PSA is increasingly less used by clinicians, thus underscoring the imperative for the identification of new biomarkers. An emerging biomarker in this context is citrate, a molecule secreted by the normal prostate, which has been shown to be inversely correlated with PCa. Here, we discuss about PSA and its usage for PCa diagnosis, its lack of specificity, and the various conditions that can affect its levels. We then provide our vision about what we think would be a valuable addition to our PCa diagnosis toolkit, citrate. We describe the unique citrate metabolic program in the prostate and how this profile is reprogrammed during carcinogenesis. Finally, we summarize the evidence that supports the usage of citrate as a biomarker for PCa diagnosis, as it can be measured in various patient samples and be analyzed by several methods. The unique relationship between citrate and PCa, combined with the stability of citrate levels in other prostate-related conditions and the simplicity of its detection, further accentuates its potential as a biomarker.

Advances in multiparametric magnetic resonance imaging combined with biomarkers for the diagnosis of high-grade prostate cancer.

Clinical decisions based on the test results for prostate-specific antigen often result in overdiagnosis and overtreatment. Multiparametric magnetic resonance imaging (mpMRI) can be used to identify high-grade prostate cancer (HGPCa; Gleason score ≥3 + 4); however, certain limitations remain such as inter-reader variability and false negatives. The combination of mpMRI and prostate cancer (PCa) biomarkers (prostate-specific antigen density, Proclarix, TMPRSS2:ERG gene fusion, Michigan prostate score, ExoDX prostate intelliscore, four kallikrein score, select molecular diagnosis, prostate health index, and prostate health index density) demonstrates high accuracy in the diagnosis of HGPCa, ensuring that patients avoid unnecessary prostate biopsies with a low leakage rate. This manuscript describes the characteristics and diagnostic performance of each biomarker alone and in combination with mpMRI, with the intension to provide a basis for decision-making in the diagnosis and treatment of HGPCa. Additionally, we explored the applicability of the combination protocol to the Asian population.

Smartphone-assisted immunosensing of cancer biomarkers in human biofluids using poly (methyl methacrylate) decorated by triangular silver nanoparticles

This system utilizes an innovative platform consisting of a poly (methyl methacrylate) (PMMA) plate adorned with triangular silver nanoparticles, enabling the sensitive and specific detection of prostate-specific antigen (PSA), carcinoembryonic antigen (CEA), and cancer antigen 15–3 (CA 15.3). To achieve this, the PMMA polymer microarrays were precisely cut using a laser cutting machine to create an optimized number of micro-arrays. These designed wells were embellished with triangular silver nanoparticles (TA-AgNPs) featuring prism morphology. The antigens could be easily detected based on antigen–antibody-induced aggregation of TA-AgNPs and resulting in a visible color change due to the alteration of surface plasmon resonance properties. Consequently, utilizing the immunocomplex of antigen–antibody in the presence of the optical probe (TA-AgNPrs) and a portable photochemical sensor, candidate cancer biomarkers (PSA, CEA, and CA 15.3) were successfully identified with linear ranges of 1–60, 1–75, and 1–125 µg/mL, respectively. By employing digital image analysis using a smartphone, we achieved a highly favorable low limit of quantification of 1 µg/mL for PSA, CEA, and CA 15.3 as biomarkers for prostate, colon, and breast cancer, respectively. This groundbreaking research introduces a pioneering digital image-based colorimetry immunoassay, the first of its kind in the field, providing a transformative approach to the early-stage diagnosis of various cancer biomarkers through a single opto-device. To the best of our knowledge, no smartphone ambient light sensor has yet been specifically designed to identify PSA, CEA, and CA 15.3 proteins as cancer biomarkers. Therefore, a sensory micro-array was developed to open new possibilities for the rapid and simple colorimetric identification of PSA, CEA, and CA 15.3 antigens in real samples, offering a sensitive and specific monitoring strategy for these biomarkers through colorimetry.

Biological determinants of PSMA expression, regulation and heterogeneity in prostate cancer.

Prostate-specific membrane antigen (PSMA) is an important cell-surface imaging biomarker and therapeutic target in prostate cancer. The PSMA-targeted theranostic 177Lu-PSMA-617 was approved in 2022 for men with PSMA-PET-positive metastatic castration-resistant prostate cancer. However, not all patients respond to PSMA-radioligand therapy, in part owing to the heterogeneity of PSMA expression in the tumour. The PSMA regulatory network is composed of a PSMA transcription complex, an upstream enhancer that loops to the FOLH1 (PSMA) gene promoter, intergenic enhancers and differentially methylated regions. Our understanding of the PSMA regulatory network and the mechanisms underlying PSMA suppression is evolving. Clinically, molecular imaging provides a unique window into PSMA dynamics that occur on therapy and with disease progression, although challenges arise owing to the limited resolution of PET. PSMA regulation and heterogeneity - including intertumoural and inter-patient heterogeneity, temporal changes, lineage dynamics and the tumour microenvironment - affect PSMA theranostics. PSMA response and resistance to radioligand therapy are mediated by a number of potential mechanisms, and complementary biomarkers beyond PSMA are under development. Understanding the biological determinants of cell surface target regulation and heterogeneity can inform precision medicine approaches to PSMA theranostics as well as other emerging therapies.

Novel technetium-99m-labeled bivalent PSMA-targeting probe based on hydroxamamide chelate for diagnosis of prostate cancer.

Prostate-specific membrane antigen (PSMA) is a well-known biomarker of prostate cancer. Previously, our group reported that the succinimidyl-cystatin-urea-glutamate (SCUE) moiety has a high affinity for PSMA. In this study, we developed the novel technetium-99m-labeled PSMA-targeting probe "[99mTc]Tc-(Ham-SCUE)2" based on a hydroxamamide chelate with a bivalent SCUE and evaluated its potential as a SPECT imaging probe for the diagnosis of PSMA-expressing prostate cancer. Ham-SCUE was synthesized by a one-step reaction with Ham-Mal and cysteine-urea-glutamine. Then, Ham-SCUE was reacted with [99mTc]NaTcO4 for 10min at room temperature to obtain [99mTc]Tc-(Ham-SCUE)2. [99mTc]Tc-(Ham-SCUE)2 was added to LNCaP (high PSMA expression) cells or PC3 (low PSMA expression) cells, and their radioactivity was measured 60min after administration. The blocking study was performed by co-incubation of LNCaP cells with various concentrations of 2-PMPA (a PSMA inhibitor) for 15min before adding [99mTc]Tc-(Ham-SCUE)2. The biodistribution of [99mTc]Tc-(Ham-SCUE)2 in LNCaP/PC3 dual xenografted C.B.-17/Icr scid/scid Jcl mice was evaluated for 120min after intravenous injection. The blocking study was performed by pretreatment of mice with 2-PMPA (10mg/kg weight). [99mTc]Tc-(Ham-SCUE)2 was acquired at radiochemical yields of 56% with a radiochemical purity of over 95%. The cellular uptake level of [99mTc]Tc-(Ham-SCUE)2 by LNCaP cells was significantly higher than that by PC3 cells (LNCaP: 11.12 ± 0.71 vs. PC3: 1.40 ± 0.13%uptake/mg protein, p < 0.01), and the uptake was significantly suppressed by pretreatment with 2-PMPA (2.56 ± 0.37%uptake/mg protein, p < 0.05). IC50 of 2-PMPA was 245 ± 47nM. In the in vivo study, the radioactivity of LNCaP tumor tissue was significantly higher than that of PC3 tumor tissue at 120min after the administration of [99mTc]Tc-(Ham-SCUE)2 (LNCaP: 9.97 ± 2.79, PC3: 1.16 ± 0.23%ID/g, p < 0.01), and was suppressed by pretreatment with 2-PMPA (2.50 ± 0.45%ID/g, p < 0.01). [99mTc]Tc-(Ham-SCUE)2 has the potential to be a SPECT imaging agent for diagnosing high PSMA-expressing prostate cancer.

1069 What Is the Diagnostic Test Accuracy of Urinary Biomarkers for Prostate Cancer? A Systematic Review

1069 What Is the Diagnostic Test Accuracy of Urinary Biomarkers for Prostate Cancer? A Systematic Review

Single Particle Analysis-Enhanced DNA Walking Machine for Sensitive miRNA Detection.

DNA walking machines have achieved significant breakthroughs in areas such as biosensing, bioimaging, and early cancer diagnosis, facilitated by the self-assembly of DNA or its combination with other materials, such as magnetic beads and metal nanoparticles. However, current DNA walking machine strategies are constantly challenged by inadequate analytical sensitivity, while sophisticated signal amplification procedures are often indispensable. Single-particle inductively coupled plasma mass spectrometry (SP-ICPMS) provides superior sensitivity and can effectively discriminate between background noise and detected signals due to the large number of metal atoms in a nanoparticle and the concentrating effect of single nanoparticle detection. In this study, we present a novel approach utilizing single nanoparticle counting and duplex-specific nuclease (DSN)-assisted signal amplification to construct a 3D DNA walking machine for detecting the aggressive prostate cancer (PCa) biomarker miRNA-200c. The proposed strategy showed an improvement in sensitivity with a detection limit (LOD) of 0.93 pM (28 amol) and was successfully applied in human serum samples. To the best of our knowledge, this is the first report of the DNA walking machine with single nanoparticle counting study.

Optimising Extracellular Vesicle Metabolomic Methodology for Prostate Cancer Biomarker Discovery.

Conventional diagnostic tools for prostate cancer (PCa), such as prostate-specific antigen (PSA), transrectal ultrasound (TRUS), digital rectal examination (DRE), and tissue biopsy face, limitations in individual risk stratification due to invasiveness or reliability issues. Liquid biopsy is a less invasive and more accurate alternative. Metabolomic analysis of extracellular vesicles (EVs) holds a promise for detecting non-genetic alterations and biomarkers in PCa diagnosis and risk assessment. The current research gap in PCa lies in the lack of accurate biomarkers for early diagnosis and real-time monitoring of cancer progression or metastasis. Establishing a suitable approach for observing dynamic EV metabolic alterations that often occur earlier than being detectable by other omics technologies makes metabolomics valuable for early diagnosis and monitoring of PCa. Using four distinct metabolite extraction approaches, the metabolite cargo of PC3-derived large extracellular vesicles (lEVs) was evaluated using a combination of methanol, cell shearing using microbeads, and size exclusion filtration, as well as two fractionation chemistries (pHILIC and C18 chromatography) that are also examined. The unfiltered methanol-microbeads approach (MB-UF), followed by pHILIC LC-MS/MS for EV metabolite extraction and analysis, is effective. Identified metabolites such as L-glutamic acid, pyruvic acid, lactic acid, and methylmalonic acid have important links to PCa and are discussed. Our study, for the first time, has comprehensively evaluated the extraction and separation methods with a view to downstream sample integrity across omics platforms, and it presents an optimised protocol for EV metabolomics in PCa biomarker discovery.

Proteomic profiling of prostate cancer reveals molecular signatures under antiandrogen treatment

BackgroundTumorigenesis and progression of prostate cancer (PCa) are indispensably dependent on androgen receptor (AR). Antiandrogen treatment is the principal preference for patients with advanced PCa. However, the molecular characteristics of PCa with antiandrogen intervention have not yet been fully uncovered.MethodsWe first performed proteome analysis with 32 PCa tumor samples and 10 adjacent tissues using data-independent acquisition (DIA)- parallel accumulation serial fragmentation (PASEF) proteomics. Then label-free quantification (LFQ) mass spectrometry was employed to analyze protein profiles in LNCaP and PC3 cells.ResultsM-type creatine kinase CKM and cartilage oligomeric matrix protein COMP were demonstrated to have the potential to be diagnostic biomarkers for PCa at both mRNA and protein levels. Several E3 ubiquitin ligases and deubiquitinating enzymes (DUBs) were significantly altered in PCa and PCa cells under enzalutamide treatment, and these proteins might reprogram proteostasis at protein levels in PCa. Finally, we discovered 127 significantly varied proteins in PCa samples with antiandrogen therapy and further uncovered 4 proteins in LNCaP cells upon enzalutamide treatment.ConclusionsOur research reveals new potential diagnostic biomarkers for prostate cancer and might help resensitize resistance to antiandrogen therapy.

Development of an effective predictive screening tool for prostate cancer using the ClarityDX machine learning platform

The current prostate cancer (PCa) screen test, prostate-specific antigen (PSA), has a high sensitivity for PCa but low specificity for high-risk, clinically significant PCa (csPCa), resulting in overdiagnosis and overtreatment of non-csPCa. Early identification of csPCa while avoiding unnecessary biopsies in men with non-csPCa is challenging. We built an optimized machine learning platform (ClarityDX) and showed its utility in generating models predicting csPCa. Integrating the ClarityDX platform with blood-based biomarkers for clinically significant PCa and clinical biomarker data from a 3448-patient cohort, we developed a test to stratify patients’ risk of csPCa; called ClarityDX Prostate. When predicting high risk cancer in the validation cohort, ClarityDX Prostate showed 95% sensitivity, 35% specificity, 54% positive predictive value, and 91% negative predictive value, at a ≥ 25% threshold. Using ClarityDX Prostate at this threshold could avoid up to 35% of unnecessary prostate biopsies. ClarityDX Prostate showed higher accuracy for predicting the risk of csPCa than PSA alone and the tested model-based risk calculators. Using this test as a reflex test in men with elevated PSA levels may help patients and their healthcare providers decide if a prostate biopsy is necessary.

Carbon dots functionalized polyaniline as efficient sensing platform for cancer biomarker detection

Implementing simple and rapid detection of cancer biomarker using biosensors has the potential to contribute greatly to basic biological research and early detection of cancer. Tailoring of biosensor matrix based on conducting polymers has gained significant attention in recent years due to its electroactivity, redox property and biocompatibility. Herein, biomass derived carbon dots (CDs) were anchored on polyaniline (PANI) surface to get biocompatible and fluorescent, carbon dots functionalized polyaniline (CDs@PANI) that enable binding of large amount of prostate cancer biomarker, prostate specific antigen (PSA) antibody on its surface via active functional groups. Immobilization efficiency of CDs@PANI was investigated by electrochemical methods which revealed dense immobilization of biomolecules on CDs@PANI as compared to conventional PANI. A sandwich electrochemical biosensor was constructed using CDs@PANI as immobilization matrix for detection of prostate cancer biomarker PSA. The sensor displayed good sensitivity, specificity, stability, reproducibility, wide linear range (0.01–60 ng/ml) and a low detection limit of 20 pg/ml. The importance of CDs in improving the sensor performance was demonstrated by carrying out detailed electrochemical studies using glucose oxidase as a model biomolecule. Biocompatibility of sensing matrix was assessed by performing 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay for cell viability using WI26 cells. The sensing platform demonstrated herein provides great potential for the detection of different cancer biomarkers and metabolites.

LGALS3 cfDNA methylation in seminal fluid as a novel prostate cancer biomarker outperforming PSA.

The unmet challenge in prostate cancer (PCa) management is to discriminate it from benign prostate hyperplasia (BPH) due to the lack of specific diagnostic biomarkers. Contemporary research on potential PCa biomarkers is directed towardmethylated cell-free DNA (cfDNA) from liquid biopsies since epigenetic mechanisms are strongly involved in PCa development. In the present research, cfDNA methylation of the LGALS3 gene in blood and seminal plasma of PCa and BPH patients was assessed using pyrosequencing, as well as LGALS3 DNA methylation in tissue biopsies. Liquid biopsy samples were taken from patients with clinical suspicion of PCa, who were subsequently divided into two groups, that is, 42 with PCa and 55 with BPH, according to the histopathological analysis. Statistically significant higher cfDNA methylation of LGALS3 in seminal plasma of BPH than in PCa patients was detected by pyrosequencing. ROC curve analysis showed that it could distinguish PCa and BPH patients with 56.4% sensitivity and 70.4% specificity, while PSA did not differ between the two patient groups. In contrast, there was no statistically significant difference in LGALS3 cfDNA methylation in blood plasma between the two patient groups. In prostate tumor tissue, there was a statistically significant DNA hypermethylation of LGALS3 compared to surrounding nontumor tissue and BPH tissue. The DNA hypermethylation of the LGALS3 gene represents an event specific to PCa development. In conclusion, LGALS3 cfDNA methylation in seminal fluid discriminates early PCa and BPH presenting itself as a powerful novel PCa biomarker highly outperforming PSA.

BRCA functional domains associated with PARP-inhibitors in patients with prostate cancer: The PROGRESS study.

10543 Background: Homologous recombination repair (HRR) defects are driver mutational imprints and actionable biomarkers in prostate cancer (PrC) patients. However, recent research provides evidence of PrC onset also in the context of mismatch repair deficiency (MMRd). In the current report, we investigated whether the position of pathogenic variants (PVs) in the functional domains (FDs) of HRR genes could be associated with reduced or increased sensitivity to PARP-inhibitors (PARPis). We also questioned whether the HRR FDs had a prognostic significance and affected the development of second primary tumor (SPT) in males with a genetic predisposition. Methods: This was a real-world, observational, study including PrC patients undergoing germline, somatic, and liquid biopsy testing between January 2020 and December 2023. Prognostic factors, SPT history, and PARPi benefit were evaluated according to mutated genes ( BRCA1, BRCA2,No- BRCAHRR), PV location within the FDs, and germline (g) or somatic (s) PV. The BRCA1FDs were RING, DNA-binding domain (DBD), BRCA1 C terminus (BRCT), or other location, and the BRCA2 FDs were RAD51-BD, DBD, or other location. Results: A total of 833 metastatic PrC patients, aging 40 to 91, were included in this study; 169 (20.3%) were carriers of germline (n.48, 5.8%) or somatic (n.121, 14.5%) PVs in HRR genes: 17 in BRCA1 (g BRCA1: n.4, 2.4%; s BRCA1: n.13, 7.7% ), 102 in BRCA2 (g BRCA2: n.33, 19.5%; s BRCA2: n.69, 40.8% ), and 53 in no- BRCA HRR genes (gHRR: n.11, 6.5%; sHRR: n.42, 24.8%). CHEK2was the HRR gene most frequently affected by germline PVs (27.3%), while the most frequent somatic PVs were in the ATM (40.5%). Liquid biopsy identified PVs in 33 patients out of 185 tested, including n.10 (5.4%) not detected through somatic and germline testing, considerably expanding the therapeutic window for the use of PARPi. Notably, differences in PFS rates at 48 months were observed when comparing sub-groups according to PV location in the FDs of BRCA2.Surprisingly, when we investigated the SPT in the cohorts of patients with and without germline PVs, the difference was not significant (14.5% vs 12.4%, respectively) and, in the subgroup without germline PVs, the sites of SPT were predominantly colorectal, gastric, bladder or other tumors classically dominated by MMRd and recognized as Lynch Syndrome-spectrum tumors. This observation may result in unexplored forms of hypermutable tumor phenotypes, potentially impacting cancer risk management and increasing therapeutic opportunities. Conclusions: Our results suggest preliminary evidence that not all BRCA2-mutated PrC are equally sensitive to PARPis, and the response could depend on the PV location within FDs. The study of SPT in patients with no-HRR-associated PrC highlights the need to expand the genes in multigene panel testing, including MMR along with HRR genes, to capture unrecognized constitutional predisposition.

Correlating survival outcomes in patients with advanced prostate cancer with novel hyperpolarized 13C MRI metabolic imaging biomarkers.

e15059 Background: Hyperpolarized 13C (HP 13C) MRI is a novel molecular imaging approach that detects aberrant aerobic metabolism, namely elevated rates of pyruvate-to-lactate conversion (kPL), in patients with advanced malignancies. Higher kPL has been shown to correlate with higher tumor grade among patients with localized prostate cancer (PC). This research sought to evaluate the correlation between kPL and clinical outcome measures in patients with advanced PC. Methods: Patients with metastatic or locally advanced PC (castration sensitive or resistant) were prospectively enrolled at our institution and underwent HP 13C MRI of one or more target lesions identified on prior conventional imaging. Voxelwise kPL values were computed in MATLAB using an inputless two site exchange model. kPL,median was defined as the median kPL value per-patient across all target lesions; kPL,kurtosis measured the tailedness of the kPL distribution per-patient. We retrospectively analyzed progression free survival (PFS) and overall survival (OS) in subgroups divided by metabolic activity below versus above cut-point (kPL,median &lt;0.017 s-1 and ≥ 0.017s-1, respectively). Survival statistics were calculated using the Cox PH model. Results: Sixteen patients (6 with castration-sensitive and 10 with castration-resistant PC) were accrued. With a median follow-up of 22.0 months from the date of MRI, the lower-kPL subgroup had significantly longer median PFS (11.2 vs 0.5 months; p&lt;0.01) and OS (NR vs 18.4 months; p&lt;0.05) compared to the higher-kPL subgroup. By comparison, baseline serum PSA (PFS: p=0.19, OS: p=0.41) and LDH (PFS: p=0.60, OS: p=0.34) did not demonstrate a significant association with clinical outcomes. There was a strong negative correlation between kPL,kurtosis and OS (r = -0.75), and moderate negative correlations between kPL,median and OS (r = -0.45) as well as kPL,max with both PFS (r = -0.48) and OS (r = -0.54). There was no significant kPL,median difference between castration-sensitive and resistant subgroups (0.015±0.011 vs 0.016±0.006 s-1, p&gt;0.8). Conclusions: HP 13C MRI-derived non-invasive metabolic biomarker kPL,median significantly correlated with clinical outcome measures in a retrospective analysis of patients with advanced PC, outperforming established serological prognostic markers PSA and LDH. Limitations include our small sample size, retrospective design, and heterogeneous patient population. Nevertheless, these encouraging preliminary results support further investigation of HP 13C MRI as a prognostic and/or predictive PC biomarker in multi-center prospective imaging trials. [Table: see text]

Identification and validation of the TRHDE-AS1/hsa-miR-449a/ADAMTS5 axis as a novel prognostic biomarker in prostate cancer.

Despite advancements in cancer research, the prognostic implications of competing endogenous RNA (ceRNA) networks in prostate cancer (PCa) remain incompletely understood. This study aimed to elucidate the prognostic relevance of ceRNA networks in PCa, utilizing a comprehensive bioinformatics approach alongside experimental validation. After searching The Cancer Genome Atlas (TCGA) database, RNA sequencing (RNA-Seq) data were extracted to identify differentially expressed RNAs (DERs) between 491 PCa samples and 51 normal prostate tissues, following which a comprehensive bioinformatics strategy was implemented to construct a ceRNA network. An optimal prognostic signature comprising these DERs was then established and validated using TCGA data. In addition, functional validation was performed through RNA pull-down, dual-luciferase reporter assays, quantitative real-time PCR, and western blot analysis conducted in PC-3 and DU145 cell lines, thereby complementing the bioinformatics analysis. A total of 613 DERs, comprising 103 long noncoding RNAs (lncRNAs), 60 microRNAs (miRNAs), and 450 messenger RNAs (mRNAs), were identified and utilized in constructing a ceRNA network, which encompassed 23 lncRNAs, 9 miRNAs, and 52 mRNAs. An optimal prognostic signature was established, including VPS9D1 antisense RNA 1 (VPS9D1-AS1), miR-449a, cyclin-dependent kinase 5 regulatory subunit 1 (CDK5R1), targeting protein for Xklp2 (TPX2), solute carrier family 7 member 11 (SLC7A11), copine7 (CPNE7), and maternal embryonic leucine zipper kinase (MELK), yielding area under the curve (AUC) values exceeding 0.8 across training, validation, and entire datasets. Our experiments results revealed an interaction between lncRNA TRHDE antisense RNA 1 (TRHDE-AS1) and miR-449a and that miR-449a could target the ADAM metallopeptidase with thrombospondin type 1 motif 5 (ADAMTS5) mRNA. Knockdown of miR-449a significantly impeded cell proliferation, G1/S transition, migration and invasion, and promoted apoptosis in PC-3 and DU145 cells. Furthermore, knockdown of miR-449a notably downregulated protein expression of CDK4, cyclin D1, N-cadherin and vimentin, while upregulating protein expression of cleaved caspase-3 and E-cadherin. This study contributes to a deeper understanding of the prognostic-linked ceRNA network in PCa, providing fundamental insights that could improve diagnostic and therapeutic approaches for PCa management.