Diffusion MRI signal cumulants and hepatocyte microstructure at fixed diffusion time: Insights from simulations, 9.4T imaging, and histology.

PURPOSE: Relationships between diffusion-weighted MRI signals and hepatocyte microstructure were investigated to inform liver diffusion MRI modeling, focusing on the following question: Can cell size and diffusivity be estimated at fixed diffusion time, realistic SNR, and negligible contribution from extracellular/extravascular water and exchange? METHODS: Monte Carlo simulations were performed within synthetic hepatocytes for varying cell size/diffusivity L / D0 , and clinical protocols (single diffusion encoding; maximum b-value: {1000, 1500, 2000} s/mm2 ; 5 unique gradient duration/separation pairs; SNR = { ∞ , 100, 80, 40, 20}), accounting for heterogeneity in (D0,L) and perfusion contamination. Diffusion ( D ) and kurtosis ( K ) coefficients were calculated, and relationships between (D0,L) and (D,K) were visualized. Functions mapping (D,K) to (D0,L) were computed to predict unseen (D0,L) values, tested for their ability to classify discrete cell-size contrasts, and deployed on 9.4T ex vivo MRI-histology data of fixed mouse livers RESULTS: Relationships between (D,K) and (D0,L) are complex and depend on the diffusion encoding. Functions mapping D,K to (D0,L) captures salient characteristics of D0(D,K) and L(D,K) dependencies. Mappings are not always accurate, but they enable just under 70% accuracy in a three-class cell-size classification task (for SNR = 20, bmax = 1500 s/mm2 , δ = 20 ms, and Δ = 75 ms). MRI detects cell-size contrasts in the mouse livers that are confirmed by histology, but overestimates the largest cell sizes. CONCLUSION: Salient information about liver cell size and diffusivity may be retrieved from minimal diffusion encodings at fixed diffusion time, in experimental conditions and pathological scenarios for which extracellular, extravascular water and exchange are negligible.

Insulin-like growth factor 1 receptor affects the survival of primary prostate cancer patients depending on TMPRSS2-ERG status.

BACKGROUND: Prostate cancer (PCa) is characterized by clinical and biological heterogeneity and has differential outcomes and mortality rates. Therefore, it is necessary to identify molecular alterations to define new therapeutic strategies based on the risk of progression. In this study, the prognostic relevance of the insulin-like growth factor (IGF) system was examined in molecular subtypes defined by TMPRSS2-ERG (T2E) gene fusion within a series of patients with primary localized PCa. METHODS: A cohort of 270 formalin-fixed and paraffin-embedded (FFPE) primary PCa samples from patients with more than 5 years' follow-up was collected. IGF-1R, IGF-1, IGFBP-3 and INSR expression was analyzed using quantitative RT-PCR. The T2E status and immunohistochemical ERG findings were considered in the analyses. The association with both biochemical and clinical progression-free survival (BPFS and PFS, respectively) was evaluated for the different molecular subtypes using the Kaplan-Meier proportional risk log-rank test and the Cox proportional hazards model. RESULTS: An association between IGF-1R overexpression and better BPFS was found in T2E-negative patients (35.3% BPFS, p-value = 0.016). Multivariate analysis demonstrated that IGF-1R expression constitutes an independent variable in T2E-negative patients [HR: 0.41. CI 95% (0.2-0.82), p = 0.013]. These data were confirmed using immunohistochemistry of ERG as subrogate of T2E. High IGF-1 expression correlated with prolonged BPFS and PFS independent of the T2E status. CONCLUSIONS: IGF-1R, a reported target of T2E, constitutes an independent factor for good prognosis in T2E-negative PCa. Quantitative evaluation of IGF-1/IGF-1R expression combined with molecular assessment of T2E status or ERG protein expression represents a useful marker for tumor progression in localized PCa.

Optimizing the clinical utility of PCA3 to diagnose prostate cancer in initial prostate biopsy.

BACKGROUND: PCA3 has been included in a nomogram outperforming previous clinical models for the prediction of any prostate cancer (PCa) and high grade PCa (HGPCa) at the initial prostate biopsy (IBx). Our objective is to validate such IBx-specific PCA3-based nomogram. We also aim to optimize the use of this nomogram in clinical practice through the definition of risk groups. METHODS: Independent external validation. Clinical and biopsy data from a contemporary cohort of 401 men with the same inclusion criteria to those used to build up the reference's nomogram in IBx. The predictive value of the nomogram was assessed by means of calibration curves and discrimination ability through the area under the curve (AUC). Clinical utility of the nomogram was analyzed by choosing thresholds points that minimize the overlapping between probability density functions (PDF) in PCa and no PCa and HGPCa and no HGPCa groups, and net benefit was assessed by decision curves. RESULTS: We detect 28% of PCa and 11 % of HGPCa in IBx, contrasting to the 46 and 20% at the reference series. Due to this, there is an overestimation of the nomogram probabilities shown in the calibration curve for PCa. The AUC values are 0.736 for PCa (C.I.95%:0.68-0.79) and 0.786 for HGPCa (C.I.95%:0.71-0.87) showing an adequate discrimination ability. PDF show differences in the distributions of nomogram probabilities in PCa and not PCa patient groups. A minimization of the overlapping between these curves confirms the threshold probability of harboring PCa >30 % proposed by Hansen is useful to indicate a IBx, but a cut-off > 40% could be better in series of opportunistic screening like ours. Similar results appear in HGPCa analysis. The decision curve also shows a net benefit of 6.31% for the threshold probability of 40%. CONCLUSIONS: PCA3 is an useful tool to select patients for IBx. Patients with a calculated probability of having PCa over 40% should be counseled to undergo an IBx if opportunistic screening is required.

Identification of miR-187 and miR-182 as biomarkers of early diagnosis and prognosis in patients with prostate cancer treated with radical prostatectomy.

PURPOSE: miRNAs are noncoding RNAs that negatively regulate target mRNA gene expression. Aberrant miRNA expression is associated with prostate cancer pathogenesis. We identified miRNAs as potential biomarkers for prostate cancer diagnosis and prognosis. MATERIALS AND METHODS: Total RNA was obtained from 10 normal prostate and 50 prostate cancer samples, and analyzed using the GeneChip® miRNA 2.0 Array. At a median followup of 92 months (range 2 to 189) an independent cohort of 273 paraffin embedded prostate cancer samples was used for validation by quantitative reverse transcriptase-polymerase chain reaction. Another 92 urine samples from patients undergoing prostate biopsy were evaluated for these miRNAs. RESULTS: miR-182 and 187, the miRNAs most differentially expressed between normal and tumor tissue, were selected for further validation. miR-187 inversely correlated with cT (p = 0.125) and pT (p = 0.0002) stages, Gleason score (p = 0.003) and TMPRSS2-ERG status (p = 0.003). The log rank test showed associations of miR-182 with biochemical (p = 0.026) and clinical (p = 0.043) progression-free survival, as also noted on multivariate analysis. A significant independent improvement in the definition of risk of progression was achieved by combining miR-182 expression with Gleason score (p <0.0001). miR-187 detection in urine provided an independent predictive value for positive biopsy. A prediction model including serum prostate specific antigen, urine PCA3 and miR-187 provided 88.6% sensitivity and 50% specificity (AUC 0.711, p = 0.001). CONCLUSIONS: Results show that miR-182 and 187 are promising biomarkers for prostate cancer prognosis to identify patients at risk for progression and for diagnosis to improve the predictive capability of existing biomarkers.

[New biomarkers to optimize the selection and follow up of patients with prostate cancer on active surveillance]. / Nuevos biomarcadroes para optimizar selección y seguimiento de pacientes con cáncer de prostata en vigilancia activa.

Identification of biomarkers that, at the time of diagnosis of prostate cancer (PCa), are associated with presence of disease or a more aggressive behavior will transform the clinical management of this disease. If both patients and clinicians would have reproducible and valid tools to estimate the specific risk of morbidity associated with PCa, then many patients would opt to and join active surveillance (AS) protocols, and consequently costs and comorbidities associated with the current overtreatment of prostate cancer would be reduced. Thus, a biomarker, or a panel of biomarkers, with high specificity to identify patients at risk for progression in AS protocols, would identify those men who could benefit from less intensive AS protocols with less repeated biopsies, so reducing the risk and cost of these invasive procedures. In this review we try to offer an overview of the new markers identified by genomic techniques and to discuss their potential role in an AS context. Moreover, the AS protocol offers an adequate setting for validation of biomarkers associated to disease progression.

Genomic Biomarkers and Genome-Wide Loss-of-Heterozygosity Scores in Metastatic Prostate Cancer Following Progression on Androgen-Targeting Therapies.

PURPOSE: To study the impact of standard-of-care hormonal therapies on metastatic prostate cancer (mPC) clinical genomic profiles in real-world practice, with a focus on homologous recombination-repair (HRR) genes. PATIENTS AND METHODS: Targeted next-generation sequencing of 1,302 patients with mPC was pursued using the FoundationOne or FoundationOne CDx assays. Longitudinal clinical data for correlative analysis were curated via technology-enabled abstraction of electronic health records. Genomic biomarkers, including individual gene aberrations and genome-wide loss-of-heterozygosity (gLOH) scores, were compared according to biopsy location and time of sample acquisition (androgen deprivation therapy [ADT]-naïve, ADT-progression and post-ADT, and novel hormonal therapies [NHT]-progression), using chi-square and Wilcoxon rank-sum tests. Multivariable analysis used linear regression. False-discovery rate of 0.05 was applied to account for multiple comparisons. RESULTS: Eight hundred forty (65%), 132 (10%), and 330 (25%) biopsies were ADT-naïve, ADT-progression, and NHT-progression, respectively. Later-stage samples were enriched for AR, MYC, TP53, PTEN, and RB1 aberrations (all adjusted P values < .05), but prevalence of HRR-related BRCA2, ATM, and CDK12 aberrations remained stable. Primary and metastatic ADT-naïve biopsies presented similar prevalence of TP53 (36% v 31%) and BRCA2 (8% v 7%) aberrations; 81% of ADT-naïve BRCA2-mutated samples presented BRCA2 biallelic loss. Higher gLOH scores were independently associated with HRR genes (BRCA2, PALB2, and FANCA), TP53, and RB1 aberrations, and with prior exposure to hormonal therapies in multivariable analysis. CONCLUSION: Prevalence of HRR-gene aberrations remains stable along mPC progression, supporting the use of diagnostic biopsies to guide poly (ADP-ribose) polymerase inhibitor treatment in metastatic castration-resistant prostate cancer. gLOH scores increase with emerging resistance to hormonal therapies, independently of individual HRR gene mutations.

Quantitative and Qualitative Analysis of Blood-based Liquid Biopsies to Inform Clinical Decision-making in Prostate Cancer.

CONTEXT: Genomic stratification can impact prostate cancer (PC) care through diagnostic, prognostic, and predictive biomarkers that aid in clinical decision-making. The temporal and spatial genomic heterogeneity of PC together with the challenges of acquiring metastatic tissue biopsies hinder implementation of tissue-based molecular profiling in routine clinical practice. Blood-based liquid biopsies are an attractive, minimally invasive alternative. OBJECTIVE: To review the clinical value of blood-based liquid biopsy assays in PC and identify potential applications to accelerate the development of precision medicine. EVIDENCE ACQUISITION: A systematic review of PubMed/MEDLINE was performed to identify relevant literature on blood-based circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and extracellular vesicles (EVs) in PC. EVIDENCE SYNTHESIS: Liquid biopsy has emerged as a practical tool to profile tumor dynamics over time, elucidating features that evolve (genome, epigenome, transcriptome, and proteome) with tumor progression. Liquid biopsy tests encompass analysis of DNA, RNA, and proteins that can be detected in CTCs, ctDNA, or EVs. Blood-based liquid biopsies have demonstrated promise in the context of localized tumors (diagnostic signatures, risk stratification, and disease monitoring) and advanced disease (response/resistance biomarkers and prognostic markers). CONCLUSIONS: Liquid biopsies have value as a source of prognostic, predictive, and response biomarkers in PC. Most clinical applications have been developed in the advanced metastatic setting, where CTC and ctDNA yields are significantly higher. However, standardization of assays and analytical/clinical validation is necessary prior to clinical implementation. PATIENT SUMMARY: Traces of tumors can be isolated from blood samples from patients with prostate cancer either as whole cells or as DNA fragments. These traces provide information on tumor features. These minimally invasive tests can guide diagnosis and treatment selection.

Advanced Prostate Cancer with ATM Loss: PARP and ATR Inhibitors.

BACKGROUND: Deleterious ATM alterations are found in metastatic prostate cancer (PC); PARP inhibition has antitumour activity against this subset, but only some ATM loss PCs respond. OBJECTIVE: To characterise ATM-deficient lethal PC and to study synthetic lethal therapeutic strategies for this subset. DESIGN, SETTING, AND PARTICIPANTS: We studied advanced PC biopsies using validated immunohistochemical (IHC) and next-generation sequencing (NGS) assays. In vitro cell line models modified using CRISPR-Cas9 to impair ATM function were generated and used in drug-sensitivity and functional assays, with validation in a patient-derived model. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: ATM expression by IHC was correlated with clinical outcome using Kaplan-Meier curves and log-rank test; sensitivity to different drug combinations was assessed in the preclinical models. RESULTS AND LIMITATIONS: Overall, we detected ATM IHC loss in 68/631 (11%) PC patients in at least one biopsy, with synchronous and metachronous intrapatient heterogeneity; 46/71 (65%) biopsies with ATM loss had ATM mutations or deletions by NGS. ATM IHC loss was not associated with worse outcome from advanced disease, but ATM loss was associated with increased genomic instability (NtAI:number of subchromosomal regions with allelic imbalance extending to the telomere, p = 0.005; large-scale transitions, p = 0.05). In vitro, ATM loss PC models were sensitive to ATR inhibition, but had variable sensitivity to PARP inhibition; superior antitumour activity was seen with combined PARP and ATR inhibition in these models. CONCLUSIONS: ATM loss in PC is not always detected by targeted NGS, associates with genomic instability, and is most sensitive to combined ATR and PARP inhibition. PATIENT SUMMARY: Of aggressive prostate cancers, 10% lose the DNA repair gene ATM; this loss may identify a distinct prostate cancer subtype that is most sensitive to the combination of oral drugs targeting PARP and ATR.

The PHLPP2 phosphatase is a druggable driver of prostate cancer progression.

Metastatic prostate cancer commonly presents with targeted, bi-allelic mutations of the PTEN and TP53 tumor suppressor genes. In contrast, however, most candidate tumor suppressors are part of large recurrent hemizygous deletions, such as the common chromosome 16q deletion, which involves the AKT-suppressing phosphatase PHLPP2. Using RapidCaP, a genetically engineered mouse model of Pten/Trp53 mutant metastatic prostate cancer, we found that complete loss of Phlpp2 paradoxically blocks prostate tumor growth and disease progression. Surprisingly, we find that Phlpp2 is essential for supporting Myc, a key driver of lethal prostate cancer. Phlpp2 dephosphorylates threonine-58 of Myc, which renders it a limiting positive regulator of Myc stability. Furthermore, we show that small-molecule inhibitors of PHLPP2 can suppress MYC and kill PTEN mutant cells. Our findings reveal that the frequent hemizygous deletions on chromosome 16q present a druggable vulnerability for targeting MYC protein through PHLPP2 phosphatase inhibitors.

Tumour exosomal CEMIP protein promotes cancer cell colonization in brain metastasis.

The development of effective therapies against brain metastasis is currently hindered by limitations in our understanding of the molecular mechanisms driving it. Here we define the contributions of tumour-secreted exosomes to brain metastatic colonization and demonstrate that pre-conditioning the brain microenvironment with exosomes from brain metastatic cells enhances cancer cell outgrowth. Proteomic analysis identified cell migration-inducing and hyaluronan-binding protein (CEMIP) as elevated in exosomes from brain metastatic but not lung or bone metastatic cells. CEMIP depletion in tumour cells impaired brain metastasis, disrupting invasion and tumour cell association with the brain vasculature, phenotypes rescued by pre-conditioning the brain microenvironment with CEMIP+ exosomes. Moreover, uptake of CEMIP+ exosomes by brain endothelial and microglial cells induced endothelial cell branching and inflammation in the perivascular niche by upregulating the pro-inflammatory cytokines encoded by Ptgs2, Tnf and Ccl/Cxcl, known to promote brain vascular remodelling and metastasis. CEMIP was elevated in tumour tissues and exosomes from patients with brain metastasis and predicted brain metastasis progression and patient survival. Collectively, our findings suggest that targeting exosomal CEMIP could constitute a future avenue for the prevention and treatment of brain metastasis.

ERG deregulation induces IGF-1R expression in prostate cancer cells and affects sensitivity to anti-IGF-1R agents.

Identifying patients who may benefit from targeted therapy is an urgent clinical issue in prostate cancer (PCa). We investigated the molecular relationship between TMPRSS2-ERG (T2E) fusion gene and insulin-like growth factor receptor (IGF-1R) to optimize the use of IGF-1R inhibitors.IGF-1R was analyzed in cell lines and in radical prostatectomy specimens in relation to T2E status. ERG binding to IGF-1R promoter was evaluated by chromatin immunoprecipitation (ChIP). Sensitivity to anti-IGF-1R agents was evaluated alone or in combination with anti-androgen abiraterone acetate in vitro at basal levels or upon ERG modulation.IGF-1R analysis performed in PCa cells or clinical samples showed that T2E expression correlated with higher IGF-1R expression at mRNA and protein levels. Genetic modulation of ERG directly affected IGF-1R protein levels in vitro. ChIP analysis showed that ERG binds IGF-1R promoter and that promoter occupancy is higher in T2E-positive cells. IGF-1R inhibition was more effective in cell lines expressing the fusion gene and combination of IGF-1R inhibitors with abiraterone acetate produced synergistic effects in T2E-expressing cells.Here, we provide the rationale for use of T2E fusion gene to select PCa patients for anti-IGF-1R treatments. The combination of anti-IGF-1R-HAbs with an anti-androgen therapy is strongly advocated for patients expressing T2E.

MiR-187 Targets the Androgen-Regulated Gene ALDH1A3 in Prostate Cancer.

miRNAs are predicted to control the activity of approximately 60% of all protein-coding genes participating in the regulation of several cellular processes and diseases, including cancer. Recently, we have demonstrated that miR-187 is significantly downregulated in prostate cancer (PCa) and here we propose a proteomic approach to identify its potential targets. For this purpose, PC-3 cells were transiently transfected with miR-187 precursor and miRNA mimic negative control. Proteins were analyzed by a two-dimensional difference gel electrophoresis (2D-DIGE) and defined as differentially regulated if the observed fold change was ±1.06. Then, MALDI-TOF MS analysis was performed after protein digestion and low abundance proteins were identified by LC-MS/MS. Peptides were identified by searching against the Expasy SWISS PROT database, and target validation was performed both in vitro by western blot and qRT-PCR and in clinical samples by qRT-PCR, immunohistochemistry and ELISA. DIGE analysis showed 9 differentially expressed spots (p<0.05) and 7 showed a down-regulated expression upon miR-187 re-introduction. Among these targets we identified aldehyde dehydrogenase 1A3 (ALDH1A3). ALDH1A3 expression was significantly downregulated in PC3, LNCaP and DU-145 cells after miR-187 re-introduction. Supporting these data, the expression of ALDH1A3 was found significantly (p<0.0001) up-regulated in PCa samples and inversely correlated (p<0.0001) with miR-187 expression, its expression being directly associated with Gleason score (p = 0.05). The expression of ALDH1A3 was measured in urine samples to evaluate the predictive capability of this biomarker for the presence of PCa and, at a signification level of 10%, PSA and also ALDH1A3 were significantly associated with a positive biopsy of PCa. In conclusion, our data illustrate for the first time the role of ALDH1A3 as a miR-187 target in PCa and provide insights in the utility of using this protein as a new biomarker for PCa.

Clinico-pathological significance of the molecular alterations of the SPOP gene in prostate cancer.

AIMS: Speckle-type POZ protein (SPOP) is an E3 ubiquitin ligase adaptor recently described to be mutated in prostate cancer (PCa). Hence, studying the gene expression profile and the presence of SPOP mutations in PCa and understanding its clinico-pathological significance as prognostic and therapeutic biomarker are important to further understand its role in PCa development. PATIENTS AND METHODS: A cohort of 265 paraffin-embedded PCa samples from patients with more than 5 years of follow-up and treated with radical prostatectomy were collected at our institution for SPOP evaluation. RT-qPCR analysis was performed for expression studies while mutations were assessed by next generation sequencing. Relationship with prognosis was analysed using log-rank analysis and multivariable Cox regression. RESULTS: SPOP was found to be strongly down-regulated in PCa (median=0.24; range=0.04-9.98) and its expression was associated with both, biochemical (p=0.003) and clinical progression free survival (p=0.023), the very low SPOP expression levels being associated to the worst prognosis. Multivariate analysis demonstrated that low levels of SPOP independently predicted a worse prognosis for both, biochemical (Hazard ratio (HR)=0.5; confidence interval (CI) 95% [0.4-0.9], p=0.011) and clinical progression (HR=0.6; IC 95% [0.4-1], p=0.046). SPOP mutations were found in 10% of TMPRSS2-ERG (T2E)-negative cases. Log-rank tests showed that mutations were significantly associated with biochemical progression free survival (BPFS) (p=0.009) and also were significant in the multivariable analysis (HR=3.4; IC 95% [1.5-7.6], p=0.004). CONCLUSIONS: The present study demonstrates that prognosis varies depending on SPOP expression and mutational status, hence, defining a new biotype of PCa associated with a worse prognosis.

miRNAs as biomarkers in prostate cancer.

Current prostate cancer (PCa) diagnosis is based in the serum prostate-specific antigen biomarker and digital rectal examination. However, these methods are limited by a low predictive value (24-37 %) and a high risk of mistaken results. During last years, new promising biomarkers such as Prostate Cancer Antigen 3 (PCA-3) and TMPRSS2-ETS fusion genes have been evaluated for their clinical use. However, the search of new biomarkers that could be used for PCa diagnosis and prognosis is still needed. Recent studies have demonstrated that the aberrant expression of microRNAs (miRNAs), small non-coding RNAs that negatively regulate gene expression, is related with the development of several cancers, including PCa. Since miRNAs serve as phenotypic signatures of different cancers, they appear as potential diagnostic, prognostic and therapeutic tools. Here, we review the current knowledge of miRNA expression patterns in PCa and their role in PCa prognosis and therapeutics.

Nuevos biomarcadores para optimizar selección y seguimiento de pacientes con cáncer de próstata en vigilancia activa / New biomarkers to optimize the selection and follow up of patients with prostate cancer on active surveillance

La identificación de biomarcadores que, en el momento del diagnóstico del CaP, se asocian con la presencia de enfermedad o de un comportamiento más agresivo del CaP transformará el manejo clínico de esta enfermedad. Si tanto los pacientes como los clínicos contaran con herramientas reproducibles y válidas para estimar el riesgo específico de la morbilidad asociada al CaP, entonces muchos pacientes optarían y se adherirían a los protocolos de vigilancia activa (VA), y consecuentemente se reducirían los costes y comorbilidades asociados al sobretratamiento actual del CaP. Así un biomarcador, o un panel de biomarcadores, con elevada especificidad para identificar pacientes con riesgo de progresión en protocolos de VA, identificaría a aquellos hombres que pudieran beneficiarse de protocolos de VA menos intensos con menos biopsias de repetición, reduciendo así el riesgo y los costes de estos procedimientos invasivos. En esta revisión se pretende ofrecer una visión de los nuevos biomarcadores identificados por técnicas genómicas y discutir su posible papel en un contexto de VA. Por otra parte, el protocolo de VA, ofrece un marco adecuado para la validación de biomarcadores asociados a la progresión de la enfermedad

Identification of biomarkers that, at the time of diagnosis of prostate cancer (PCa) , are associated with presence of disease or a more aggressive behavior will transform the clinical management of this disease. If both patients and clinicians would have reproducible and valid tools to estimate the specific risk of morbidity associated with PCa, then many patients would opt to and join active surveillance (AS) protocols, and consequently costs and comorbidities associated with the current overtreatment of prostate cancer would be reduced. Thus, a biomarker, or a panel of biomarkers, with high specificity to identify patients at risk for progression in AS protocols, would identify those men who could benefit from less intensive AS protocols with less repeated biopsies, so reducing the risk and cost of these invasive procedures. In this review we try to offer an overview of the new markers identified by genomic techniques and to discuss their potential role in an AS context. Moreover, the AS protocol offers an adequate setting for validation of biomarkers associated to disease progression