Diffusion-weighted MRI for early detection and characterization of prostate cancer in the transgenic adenocarcinoma of the mouse prostate model

Classification and biomarker identification of prostate tissue from TRAMP mice with hyperpolarized 13C-SIRA

Hyperpolarized ¹³C isotope resolved spectroscopy boosts NMR signal intensity, which improves signal detection and allows metabolic fluxes to be analyzed. Such hyperpolarized flux data may offer new approaches to tissue classification and biomarker identification that could be translated in vivo. Here we used hyperpolarized stable isotope resolved analysis (SIRA) to measure metabolite specific ¹³C isotopic enrichments in the central carbon metabolism of mouse prostate. Prostate and tumor tissue samples were acquired from transgenic adenocarcinomas of the mouse prostate (TRAMP) mice. Before euthanasia, mice were injected with [U-¹³C]glucose intraperitoneally (i.p.). Polar metabolite extracts were prepared, and hyperpolarized 1D-¹³C NMR spectra were obtained from normal prostate (n = 19) and cancer tissue (n = 19) samples. Binary classification and feature analysis was performed to make a separation model and to investigate differences between samples originating from normal and cancerous prostate tissue, respectively. Hyperpolarized experiments were carried out according to a standardized protocol, which showed a high repeatability (CV = 15%) and an average linewidth in the 1D-¹³C NMR spectra of 2 ± 0.5 Hz. The resolution of the hyperpolarized 1D-¹³C spectra was high with little signal overlap in the carbonyl region and metabolite identification was easily accomplished. A discrimination with 95% success rate could be made between samples originating from TRAMP mice prostate and tumor tissue based on isotopomers from uniquely identified metabolites. Hyperpolarized ¹³C-SIRA allowed detailed metabolic information to be obtained from tissue specimens. The positional information of ¹³C isotopic enrichments lead to easily interpreted features responsible for high predictive classification of tissue types. This analytical approach has matured, and the robust experimental protocols currently available allow systematic tracking of metabolite flux ex vivo.

Ultrasound-Mediated Delivery of Chemotherapy into the Transgenic Adenocarcinoma of the Mouse Prostate Model

Ultrasound (US) in combination with microbubbles (MB) has had promising results in improving delivery of chemotherapeutic agents. However, most studies are done in immunodeficient mice with xenografted tumors. We used two phenotypes of the spontaneous transgenic adenocarcinoma of the mouse prostate (TRAMP) model to evaluate if US + MB could enhance the therapeutic efficacy of cabazitaxel (Cab). Cab was either injected intravenously as free drug or encapsulated into nanoparticles. In both cases, Cab transiently reduced tumor and prostate volume in the TRAMP model. No additional therapeutic efficacy was observed combining Cab with US + MB, except for one tumor. Additionally, histology grading and immunostaining of Ki67 did not reveal differences between treatment groups. Mass spectrometry revealed that nanoparticle encapsulation of Cab increased the circulation time and enhanced the accumulation in liver and spleen compared with free Cab. The therapeutic results in this spontaneous, clinically relevant tumor model differ from the improved therapeutic response observed in xenografts combining US + MB and chemotherapy.

Ultrasound and magnetic resonance imaging for group stratification and treatment monitoring in the transgenic adenocarcinoma of the mouse prostate model

BACKGROUND

The transgenic adenocarcinoma of the mouse prostate (TRAMP) is a widely used genetically engineered spontaneous prostate cancer model. However, both the degree of malignancy and time of cancer onset vary. While most mice display slowly progressing cancer, a subgroup develops fast-growing poorly differentiated (PD) tumors, making the model challenging to use. We investigated the feasibility of using ultrasound (US) imaging to screen for PD tumors and compared the performances of US and magnetic resonance imaging (MRI) in providing reliable measurements of disease burden.

METHODS

TRAMP mice (n = 74) were screened for PD tumors with US imaging and findings verified with MRI, or in two cases with gross pathology. PD tumor volume was estimated with US and MR imaging and the methods compared (n = 11). For non-PD mice, prostate volume was used as a marker for disease burden and estimated with US imaging, MRI, and histology (n = 11). The agreement between the measurements obtained by the various methods and the intraobserver variability (IOV) was assessed using Bland-Altman analysis.

RESULTS

US screening showed 81% sensitivity, 91% specificity, 72% positive predictive value, and 91% negative predictive value. The smallest tumor detected by US screening was 14 mm³ and had a maximum diameter of 2.6 mm. MRI had the lowest IOV for both PD tumor and prostate volume estimation. US IOV was almost as low as MRI for PD tumor volumes but was considerably higher for prostate volumes.

CONCLUSIONS

US imaging was found to be a good screening method for detecting PD tumors and estimating tumor volume in the TRAMP model. MRI had better repeatability than US, especially when estimating prostate volumes.

R2* Relaxation Affects Pharmacokinetic Analysis of Dynamic Contrast-Enhanced MRI in Cancer and Underestimates Treatment Response at 7 T

Effective transverse relaxivity of gadolinium-based contrast agents is often neglected in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Here, we assess time and tissue dependence of R2* enhancement and its impact on pharmacokinetic parameter quantification and treatment monitoring. Multiecho DCE-MRI was performed at 7 T on mice bearing subcutaneous TOV-21G human ovarian cancer xenografts (n = 8) and on the transgenic adenocarcinoma of the mouse prostate (TRAMP) model (n = 7). Subsequently, the TOV-21G tumor-bearing mice were treated with bevacizumab and rescanned 2 days later. Pharmacokinetic analysis (extended Tofts model) was performed using either the first echo signal only (standard single-echo DCE-MRI) or the estimated signal at TE = 0 derived from exponential fitting of R2* relaxation (R2*-corrected). Neglecting R2* enhancement causes underestimation of Gd-DOTA concentration (peak enhancement underestimated by 9.4%-16% in TOV-21G tumors and 13%-20% in TRAMP prostates). Median K^trans and v_e were underestimated in every mouse (TOV-21G K^trans: 11%-19%, TOV-21G v_e: 5.3%-8.9%; TRAMP K^trans: 8.6%-19%, TRAMP v_e: 12%-21%). Bevacizumab treatment reduced K^trans in all TOV-21G tumors after 48 hours. Treatment effect was significantly greater in all tumors after R2* correction (median change of -0.050 min^-1 in R2*-corrected K^trans vs. -0.037 min^-1 in uncorrected K^trans). R2* enhancement in DCE-MRI is both time- and tissue-dependent and may not be negligible at 7 T in tissue with high K^trans. This has consequences for the use of K^trans and other DCE-MRI parameters as biomarkers, because treatment effect size can be underestimated when R2* enhancement is neglected.

Identification of Potential MR-Derived Biomarkers for Tumor Tissue Response to 177Lu-Octreotate Therapy in an Animal Model of Small Intestine Neuroendocrine Tumor

Magnetic resonance (MR) methods enable noninvasive, regional tumor therapy response assessment, but associations between MR parameters, underlying biology, and therapeutic effects must be investigated. The aim of this study was to investigate response assessment efficacy and biological associations of MR parameters in a neuroendocrine tumor (NET) model subjected to radionuclide treatment. Twenty-one mice with NETs received 177Lu-octreotate at day 0. MR experiments (day -1, 1, 3, 8, and 13) included T2-weighted, dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI) and relaxation measurements (T1/T2*). Tumor tissue was analyzed using proteomics. MR-derived parameters were evaluated for each examination day and for different radial distances from the tumor center. Response assessment efficacy and biological associations were evaluated using feature selection and protein expression correlations, respectively. Reduced tumor growth rate or shrinkage was observed until day 8, followed by reestablished growth in most tumors. The most important MR parameter for response prediction was DCE-MRI-derived pretreatment signal enhancement ratio (SER) at 40% to 60% radial distance, where it correlated significantly also with centrally sampled protein CCD89 (association: DNA damage and repair, proliferation, cell cycle arrest). The second most important was changed diffusion (D) between day -1 and day 3, at 60% to 80% radial distance, where it correlated significantly also with peripherally sampled protein CATA (association: oxidative stress, proliferation, cell cycle arrest, apoptotic cell death). Important information regarding tumor biology in response to radionuclide therapy is reflected in several MR parameters, SER and D in particular. The spatial and temporal information provided by MR methods increases the sensitivity for tumor therapy response.

APIM-peptide targeting PCNA improves the efficacy of docetaxel treatment in the TRAMP mouse model of prostate cancer

Docetaxel is the chemotherapeutic choice for metastatic hormone-refractory prostate cancer, however, it only marginally improves the survival rate. The purpose of the present study was to examine if a peptide targeting the cellular scaffold protein PCNA could improve docetaxel's efficacy. We found that docetaxel given in combination with a cell penetrating peptide containing the AlkB homolog 2 PCNA interacting motif (APIM-peptide), reduced the prostate volume and limited prostate cancer regrowth in vivo in the immunocompetent transgenic adenocarcinoma model of prostate cancer (TRAMP). In accordance with this, we found that the APIM-peptide enhanced the efficacy of docetaxel in vitro. Gene expression analysis on prostate cancer cell lines indicated that the combination of docetaxel and APIM-peptide alters expression of genes involved in cellular signaling, apoptosis, and prostate cancer development. These changes were not detected in single agent treated cells. Our results suggest that targeting PCNA and thereby affecting multiple cellular pathways simultaneously has the potential to improve docetaxel therapy of advanced prostate cancer.

Non-Invasive Prostate Cancer Characterization with Diffusion-Weighted MRI: Insight from In silico Studies of a Transgenic Mouse Model

Diffusion-weighted magnetic resonance imaging (DWI) enables non-invasive, quantitative staging of prostate cancer via measurement of the apparent diffusion coefficient (ADC) of water within tissues. In cancer, more advanced disease is often characterized by higher cellular density (cellularity), which is generally accepted to correspond to a lower measured ADC. A quantitative relationship between tissue structure and in vivo measurements of ADC has yet to be determined for prostate cancer. In this study, we establish a theoretical framework for relating ADC measurements with tissue cellularity and the proportion of space occupied by prostate lumina, both of which are estimated through automatic image processing of whole-slide digital histology samples taken from a cohort of six healthy mice and nine transgenic adenocarcinoma of the mouse prostate (TRAMP) mice. We demonstrate that a significant inverse relationship exists between ADC and tissue cellularity that is well characterized by our model, and that a decrease of the luminal space within the prostate is associated with a decrease in ADC and more aggressive tumor subtype. The parameters estimated from our model in this mouse cohort predict the diffusion coefficient of water within the prostate-tissue to be 2.18 × 10-3 mm2/s (95% CI: 1.90, 2.55). This value is significantly lower than the diffusion coefficient of free water at body temperature suggesting that the presence of organelles and macromolecules within tissues can drastically hinder the random motion of water molecules within prostate tissue. We validate the assumptions made by our model using novel in silico analysis of whole-slide histology to provide the simulated ADC (sADC); this is demonstrated to have a significant positive correlation with in vivo measured ADC (r2 = 0.55) in our mouse population. The estimation of the structural properties of prostate tissue is vital for predicting and staging cancer aggressiveness, but prostate tissue biopsies are painful, invasive, and are prone to complications such as sepsis. The developments made in this study provide the possibility of estimating the structural properties of prostate tissue via non-invasive virtual biopsies from MRI, minimizing the need for multiple tissue biopsies and allowing sequential measurements to be made for prostate cancer monitoring.

Magnetic nanoparticles in cancer diagnosis, drug delivery and treatment

In recent years, magnetic nanoparticles (MNPs) have demonstrated marked progress in the field of oncology. General nanoparticles are widely used in tumor targeting, and the intrinsic magnetic property of MNPs makes them the most promising nanomaterial to be used as contrast agents for magnetic resonance imaging (MRI) and induced magnetic hyperthermia. The properties of MNPs are fully exploited when they are used as drug delivery agents, wherein drugs may be targeted to the desired specific location in vivo by application of an external magnetic field. Early diagnosis of cancer may be achieved by MRI, therefore, individualized treatment may be combined with MRI, so as to achieve the precise definition and appropriate treatment. In the present review, research on MNPs in cancer diagnosis, drug delivery and treatment has been summarized. Furthermore, the future perspectives and challenges of MNPs in the field of oncology are also discussed.

Role of mpMRI of the prostate in screening for prostate cancer

Prostate cancer screening offers the opportunity to significantly reduce morbidity and mortality from this disease. Currently, serum prostate-specific antigen (PSA) testing is the most widely used screening modality. However, PSA testing continues to have low positive and negative predictive value leading to unnecessary invasive prostate biopsy while missing patients with aggressive forms of the disease. Magnetic resonance imaging (MRI) has been gaining an increasingly large role in the management of patients with early stage prostate cancer including diagnosis in patients with abnormal PSA levels, monitoring of patients on active surveillance, and staging prior to definitive interventions. MRI-based prostate cancer risk assessment has been shown to better distinguish between clinically-significant and insignificant tumors than PSA testing alone or from nomograms. Preliminary data indicate that, among unselected patients, MRI outperforms PSA in the identification of patients with clinically significant prostate cancer. Further work is needed to examine the role of mpMRI in prostate cancer screening.

Diffusion radiomics analysis of intratumoral heterogeneity in a murine prostate cancer model following radiotherapy: Pixelwise correlation with histology

PURPOSE

To investigate the biological meaning of apparent diffusion coefficient (ADC) values in tumors following radiotherapy.

MATERIALS AND METHODS

Five mice bearing TRAMP-C1 tumor were half-irradiated with a dose of 15 Gy. Diffusion-weighted images, using multiple b-values from 0 to 3000 s/mm² , were acquired at 7T on day 6. ADC values calculated by a two-point estimate and monoexponential fitting of signal decay were compared between the irradiated and nonirradiated regions of the tumor. Pixelwise ADC maps were correlated with histological metrics including nuclear counts, nuclear sizes, nuclear spaces, cytoplasmic spaces, and extracellular spaces.

RESULTS

As compared with the nonirradiated region, the irradiated region exhibited significant increases in ADC, extracellular space, and nuclear size, and a significant decrease in nuclear counts (P < 0.001 for all). Optimal ADC to differentiate the irradiated from nonirradiated regions was achieved at a b-value of 800 s/mm² by the two-point method and monoexponential curve fitting. ADC positively correlated with extracellular spaces (r = 0.74) and nuclear sizes (r = 0.72), and negatively correlated with nuclear counts (r = -0.82, P < 0.001 for all).

CONCLUSION

As a radiomic biomarker, ADC maps correlating with histological metrics pixelwise could be a means of evaluating tumor heterogeneity and responses to radiotherapy.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:483-489.

Zinc-sensitive MRI contrast agent detects differential release of Zn(II) ions from the healthy vs. malignant mouse prostate

Many secretory tissues release Zn(II) ions along with other molecules in response to external stimuli. Here we demonstrate that secretion of Zn(II) ions from normal, healthy prostate tissue is stimulated by glucose in fasted mice and that release of Zn(II) can be monitored by MRI. An ∼50% increase in water proton signal enhancement is observed in T1-weighted images of the healthy mouse prostate after infusion of a Gd-based Zn(II) sensor and an i.p. bolus of glucose. Release of Zn(II) from intracellular stores was validated in human epithelial prostate cells in vitro and in surgically exposed prostate tissue in vivo using a Zn(II)-sensitive fluorescent probe known to bind to the extracellular surface of cells. Given the known differences in intracellular Zn(II) stores in healthy versus malignant prostate tissues, the Zn(II) sensor was then evaluated in a transgenic adenocarcinoma of the mouse prostate (TRAMP) model in vivo. The agent proved successful in detecting small malignant lesions as early as 11 wk of age, making this noninvasive MR imaging method potentially useful for identifying prostate cancer in situations where it may be difficult to detect using current multiparametric MRI protocols.