Sight and switch off: Nerve density visualization for interventions targeting nerves in prostate cancer

Cutting-edge technologies illuminate the neural landscape of cancer: Insights into tumor development

Neurogenesis constitutes a pivotal facet of malignant tumors, wherein cancer and its therapeutic interventions possess the ability to reconfigure the nervous system, establishing a pathologic feedback loop that exacerbates tumor progression. Recent strides in high-resolution imaging, single-cell analysis, multi-omics technologies, and experimental models have opened unprecedented avenues in cancer neuroscience. This comprehensive review summarizes the latest advancements of these emerging technologies in elucidating the biological mechanisms underlying tumor initiation, invasion, metastasis, and the dynamic heterogeneity of the tumor microenvironment(TME), with a specific focus on neuron-glial-tumor interactions in glioblastoma(GBM) and other neurophilic cancers. Moreover, we innovatively propose target screening processes based on sequencing technologies and database frameworks. It rigorously evaluates ongoing clinical trial drugs and efficacy while spotlighting characteristic cells in the central and peripheral TME, consolidating cancer biomarkers pivotal for future targeted therapies and management strategies. By integrating these cutting-edge findings, this review aims to offer fresh insights into tumor-nervous system interactions, establishing a robust foundation for forthcoming clinical advancements.

CXCR4-targeted sensitive magnetic particle imaging for abdominal aortic aneurysm early detection and prognosis evaluation by recognizing total inflammatory cells

AIMS

The maximum aortic diameter remains the diagnostic criteria and the indicator for prognosis prediction of abdominal aortic aneurysms (AAAs). An additional imaging modality is currently needed to help evaluate the prognosis of AAA as well as early detection of AAA formation. This study evaluated the most effective inflammatory markers for AAA using single-cell sequencing and, from these, developed probes to facilitate in vivo multimodal imaging of AAA inflammation.

METHODS AND RESULTS

Single-cell RNA sequencing (scRNAseq) of the human aortic aneurysms, GSE155468 and GSE166676 data sets, identified CXCR4 as the most representative marker. Anti-CXCR4-PE antibody was conjugated to superparamagnetic iron oxide nanoparticles to synthesize Fe3O4-anti-CXCR4-PE probes. The biocompatibility and specificity of the probes were validated in vivo and in vitro. Magnetic particle imaging (MPI) and fluorescence imaging (FLI) were performed to assess inflammation in early and advanced AAA mouse models. CXCR4-specific receptor inhibitor, AMD3100, was used for confirming CXCR4 as an excellent target for AAA imaging and therapy. scRNAseq indicated that chemokine-related pathways were upregulated in aortic aneurysms, and CXCR4 was the chemokine receptor that marks all AAA-related immune cells and inflammatory vascular cells. Fe3O4-anti-CXCR4-PE effectively recognized immune cells and inflammatory vascular cells, as strong MPI and FLI signals corresponded to increased CXCR4, CD45, and CD68 levels that represented AAA severity and rupture risk. Importantly, Fe3O4-anti-CXCR4-PE can help identify early AAA formation when ultrasound is undiagnosable. Finally, AMD3100 treatment in AAA mouse model inhibited AAA expansion and rupture and reduced aortic wall inflammation by inhibiting accumulation of immune cells and haematopoietic stem cells.

CONCLUSION

CXCR4 marks immune cells and inflammatory vascular cells in AAA and is associated with AAA prognosis in a mouse model of AAA. CXCR4-targeting multimodal MPI/FLI provides a novel approach for AAA prognosis prediction and early detection.

Peripheral nerves-cancer cross-talk: the next frontier in cancer treatment

The nervous system, which regulates organogenesis, homeostasis, and plasticity of the organism during human growth and development, integrates physiological functions of all organ systems, including the immune system. Its extensive network of branches throughout the body reaches the tumor microenvironment (TME), where it secretes neurotransmitters that directly regulate or influence immune cells. This, in turn, indirectly affects the occurrence, development, and metastasis of cancer. Conversely, cancer cells are now understood to secrete neurotrophic factors that remodel the nervous system. Targeting the cross-talk between the nervous system and cancer represents a promising strategy for cancer treatment, some aspects of which have been confirmed in clinical trials. This review addresses gaps in our understanding of the interaction between peripheral nerves and various human cancers. At the intersection of neuroscience and cancer biology, new targets for neuroscience-based cancer therapies are emerging, establishing a significant new pillar in cancer treatment.

Bimagnetic Core/Shell Nanoprobes with Tunable Exchange Coupling for High Resolution and Sensitive Magnetic Particle Imaging

Magnetic particle imaging (MPI) has demonstrated versatile applications in biomedicine, including tumor imaging, cell tracking, and image-guided hyperthermia. Despite these advancements, the prevalent use of clinically approved tracers has posed limitations on MPI's resolution and sensitivity. In this study, we engineered a bimagnetic core/shell nanocrystals (BMCS) tailored for MPI by optimizing the heterostructure and modulating the exchange coupling effect between the two magnetic components. The resulting BMCS exhibited remarkably heightened susceptibility and magnetization while maintaining low coercivity, thereby substantially improved both MPI resolution and sensitivity compared to conventional tracers such as VivoTrax. At an equivalent mass concentration, BMCS demonstrated a notable 5.08-fold increase in signal intensity and achieved an unprecedentedly high resolution down to 1 mm. The excellent MPI performance contributes to high resolution MPI and the sensitive detection of orthotopic colorectal cancer in mice. The design strategy employed in BMCS, centered on the exchange coupling effect, introduces an efficacious approach for the development of high performance MPI tracers.

Targeted intervention in nerve-cancer crosstalk enhances pancreatic cancer chemotherapy

Nerve-cancer crosstalk has gained substantial attention owing to its impact on tumour growth, metastasis and therapy resistance. Effective therapeutic strategies targeting tumour-associated nerves within the intricate tumour microenvironment remain a major challenge in pancreatic cancer. Here we develop Escherichia coli Nissle 1917-derived outer membrane vesicles conjugated with nerve-binding peptide NP41, loaded with the tropomyosin receptor kinase (Trk) inhibitor larotrectinib (Lar@NP-OMVs) for tumour-associated nerve targeting. Lar@NP-OMVs achieve efficient nerve intervention to diminish neurite growth by disrupting the neurotrophin/Trk signalling pathway. Moreover, OMV-mediated repolarization of M2-like tumour-associated macrophages to an M1-like phenotype results in nerve injury, further accentuating Lar@NP-OMV-induced nerve intervention to inhibit nerve-triggered proliferation and migration of pancreatic cancer cells and angiogenesis. Leveraging this strategy, Lar@NP-OMVs significantly reduce nerve infiltration and neurite growth promoted by gemcitabine within the tumour microenvironment, leading to augmented chemotherapy efficacy in pancreatic cancer. This study sheds light on a potential avenue for nerve-targeted therapeutic intervention for enhancing pancreatic cancer therapy.

Advancements in molecular imaging probes for precision diagnosis and treatment of prostate cancer

Prostate cancer is the second most common cancer in men, accounting for 14.1% of new cancer cases in 2020. The aggressiveness of prostate cancer is highly variable, depending on its grade and stage at the time of diagnosis. Despite recent advances in prostate cancer treatment, some patients still experience recurrence or even progression after undergoing radical treatment. Accurate initial staging and monitoring for recurrence determine patient management, which in turn affect patient prognosis and survival. Classical imaging has limitations in the diagnosis and treatment of prostate cancer, but the use of novel molecular probes has improved the detection rate, specificity, and accuracy of prostate cancer detection. Molecular probe-based imaging modalities allow the visualization and quantitative measurement of biological processes at the molecular and cellular levels in living systems. An increased understanding of tumor biology of prostate cancer and the discovery of new tumor biomarkers have allowed the exploration of additional molecular probe targets. The development of novel ligands and advances in nano-based delivery technologies have accelerated the research and development of molecular probes. Here, we summarize the use of molecular probes in positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), optical imaging, and ultrasound imaging, and provide a brief overview of important target molecules in prostate cancer.

Neuronal Tracing and Visualization of Nerve Injury by a Membrane-Anchoring Aggregation-Induced Emission Probe

Deciphering neuronal circuits is pivotal for deepening our understanding of neuronal functions and advancing treatments for neurological disorders. Conventional neuronal tracers suffer from restrictions such as limited penetration depth, high immunogenicity, and inadequacy for long-term and in vivo imaging. In this context, we introduce an aggregation-induced emission luminogen (AIEgen), MeOTFVP, engineered for enhanced neuronal tracing and imaging. MeOTFVP is strategically designed to target cell membranes by integrating into the phospholipid bilayer through its amphipathy. The donor-acceptor molecular skeleton facilitates a red shift of its photoluminescence into the near-infrared (NIR) spectrum, significantly improving tissue penetration. The affinity of MeOTFVP for cell membranes, coupled with its deep tissue penetration, allows precise tracing in the paw-dorsal root ganglia (DRG) circuit and detailed imaging of the sciatic nerve. This study showcases the application of MeOTFVP as a dual-function neuronal tracer, propelling forward the possibilities for advanced neuronal tracing and imaging using AIEgens.

Development and Validation of a Biparametric MRI Deep Learning Radiomics Model with Clinical Characteristics for Predicting Perineural Invasion in Patients with Prostate Cancer

RATIONALE AND OBJECTIVES

Perineural invasion (PNI) is an important prognostic biomarker for prostate cancer (PCa). This study aimed to develop and validate a predictive model integrating biparametric MRI-based deep learning radiomics and clinical characteristics for the non-invasive prediction of PNI in patients with PCa.

MATERIALS AND METHODS

In this prospective study, 557 PCa patients who underwent preoperative MRI and radical prostatectomy were recruited and randomly divided into the training and the validation cohorts at a ratio of 7:3. Clinical model for predicting PNI was constructed by univariate and multivariate regression analyses on various clinical indicators, followed by logistic regression. Radiomics and deep learning methods were used to develop different MRI-based radiomics and deep learning models. Subsequently, the clinical, radiomics, and deep learning signatures were combined to develop the integrated deep learning-radiomics-clinical model (DLRC). The performance of the models was assessed by plotting the receiver operating characteristic (ROC) curves and precision-recall (PR) curves, as well as calculating the area under the ROC and PR curves (ROC-AUC and PR-AUC). The calibration curve and decision curve were used to evaluate the model's goodness of fit and clinical benefit.

RESULTS

The DLRC model demonstrated the highest performance in both the training and the validation cohorts, with ROC-AUCs of 0.914 and 0.848, respectively, and PR-AUCs of 0.948 and 0.926, respectively. The DLRC model showed good calibration and clinical benefit in both cohorts.

CONCLUSION

The DLRC model, which integrated clinical, radiomics, and deep learning signatures, can serve as a robust tool for predicting PNI in patients with PCa, thus aiding in developing effective treatment strategies.

Responsive Magnetic Particle Imaging Tracer: Overcoming "Always-On" Limitation, Eliminating Interference, and Ensuring Safety in Adaptive Therapy

Magnetic particle imaging (MPI) has emerged as a novel technology utilizing superparamagnetic nanoparticles as tracers, essential for disease diagnosis and treatment guidance in preclinical animal models. Unlike other modalities, MPI provides high sensitivity, deep tissue penetration, and no signal attenuation. However, existing MPI tracers suffer from "always-on" signals, which complicate organ-specific imaging and hinder accuracy. To overcome these challenges, we have developed a responsive MPI tracer using pH-responsive PdFe alloy particles coated with a gatekeeper polymer. This tracer exhibits pH-sensitive Fe release and modulation of the MPI signal, enabling selective imaging with a higher signal-to-noise ratio and intratumoral pH quantification. Notably, this responsive tracer facilitates subtraction-enhanced MPI imaging, effectively eliminating interference from liver uptake and expanding the scope of abdominal imaging. Additionally, the tracer employs a dual-function mechanism for adaptive cancer therapy, combining pH-switchable enzyme-like catalysis with dual-key co-activation of ROS generation, and Pd skeleton that scavenges free radicals to minimize Fe-related toxicity. This advancement promises to significantly expand MPI's applicability in diagnostics and therapeutic monitoring, marking a leap forward in imaging technology.

MPIGAN: An end-to-end deep based generative framework for high-resolution magnetic particle imaging reconstruction

BACKGROUND

Magnetic particle imaging (MPI) is a recently developed, non-invasive in vivo imaging technique to map the spatial distribution of superparamagnetic iron oxide nanoparticles (SPIONs) in animal tissues with high sensitivity and speed. It is a challenge to reconstruct images directly from the received signals of MPI device due to the complex physical behavior of the nanoparticles. System matrix and X-space are two commonly used MPI reconstruction methods, where the former is extremely time-consuming and the latter usually produces blurry images.

PURPOSE

Currently, we proposed an end-to-end machine learning framework to reconstruct high-resolution MPI images from 1-D voltage signals directly and efficiently.

METHODS

The proposed framework, which we termed "MPIGAN", was trained on a large MPI simulation dataset containing 291 597 pairs of high-resolution 2-D phantom images and each image's corresponding voltage signals, so that it was able to accurately capture the nonlinear relationship between the spatial distribution of SPIONs and the received voltage signal, and realized high-resolution MPI image reconstruction.

RESULTS

Experiment results showed that, MPIGAN exhibited remarkable abilities in high-resolution MPI image reconstruction. MPIGAN outperformed the traditional methods of system matrix and X-space in recovering the fine-scale structure of magnetic nanoparticles' spatial distribution and achieving enhanced reconstruction performance in both visual effects and quantitative assessments. Moreover, even when the received signals were severely contaminated with noise, MPIGAN could still generate high-quality MPI images.

CONCLUSION

Our study provides a promising AI solution for end-to-end, efficient, and high-resolution magnetic particle imaging reconstruction.

Integration of photomagnetic bimodal imaging to monitor an autogenous exosome loaded platform: unveiling strong targeted retention effects for guiding the photothermal and magnetothermal therapy in a mouse prostate cancer model

BACKGROUND

Prostate cancer (PCa) is the most prevalent cancer among males, emphasizing the critical need for precise diagnosis and treatment to enhance patient prognosis. Recent studies have extensively utilized urine exosomes from patients with cancer for targeted delivery. This study aimed to employ highly sensitive magnetic particle imaging (MPI) and fluorescence molecular imaging (FMI) to monitor the targeted delivery of an exosome-loaded platform at the tumour site, offering insights into a potential combined photothermal and magnetic thermal therapy regime for PCa.

RESULTS

MPI and FMI were utilized to monitor the in vivo retention performance of exosomes in a prostate tumour mouse model. The exosome-loaded platform exhibited robust homologous targeting ability during imaging (SPIONs@EXO-Dye:66·48%±3·85%; Dye-SPIONs: 34·57%±7·55%, **P<0·01), as verified by in vitro imaging and in vitro tissue Prussian blue staining.

CONCLUSIONS

The experimental data underscore the feasibility of using MPI for in vivo PCa imaging. Furthermore, the exosome-loaded platform may contribute to the precise diagnosis and treatment of PCa.

Adhesion molecule-targeted magnetic particle imaging nanoprobe for visualization of inflammation in acute lung injury

PURPOSE

Uncontrolled intra-alveolar inflammation is a central pathogenic feature, and its severity translates into a valid prognostic indicator of acute lung injury (ALI). Unfortunately, current clinical imaging approaches are unsuitable for visualizing and quantifying intra-alveolar inflammation. This study aimed to construct a small-sized vascular cell adhesion molecule-1 (VCAM-1)-targeted magnetic particle imaging (MPI) nanoprobe (ESPVPN) to visualize and accurately quantify intra-alveolar inflammation at the molecular level.

METHODS

ESPVPN was engineered by conjugating a peptide (VHPKQHRGGSK(Cy7)GC) onto a polydopamine-functionalized superparamagnetic iron oxide core. The MPI performance, targeting, and biosafety of the ESPVPN were characterized. VCAM-1 expression in HUVECs and mouse models was evaluated by western blot. The degree of inflammation and distribution of VCAM-1 in the lungs were assessed using histopathology. The expression of pro-inflammatory markers and VCAM-1 in lung tissue lysates was measured using ELISA. After intravenous administration of ESPVPN, MPI and CT imaging were used to analyze the distribution of ESPVPN in the lungs of the LPS-induced ALI models.

RESULTS

The small-sized (~10 nm) ESPVPN exhibited superior MPI performance compared to commercial MagImaging® and Vivotrax, and ESPVPN had effective targeting and biosafety. VCAM-1 was highly expressed in LPS-induced ALI mice. VCAM-1 expression was positively correlated with the LPS-induced dose (R = 0.9381). The in vivo MPI signal showed positive correlations with both VCAM-1 expression (R = 0.9186) and representative pro-inflammatory markers (MPO, TNF-α, IL-6, IL-8, and IL-1β, R > 0.7).

CONCLUSION

ESPVPN effectively targeted inflammatory lungs and combined the advantages of MPI quantitative imaging to visualize and evaluate the degree of ALI inflammation.

[Near-infrared targeted probe designed for intraoperative imaging of prostatic neurovascular bundles]

OBJECTIVE

To investigate the imaging effect of a near-infrared fluorescent targeted probe ICG-NP41 on the neurovascular bundles (NVB) around the prostate in rats.

METHODS

A near-infrared fluorescent targeted probe ICG-NP41 was synthesized. An animal model for NVB imaging was established using Sprague-Dawley rats (250-400 g). Experiments were conducted using a custom-built near-infrared windowⅡ(NIR-Ⅱ) small animal in vivo imaging system, and images collected were processed using ImageJ and Origin. The fluorescence signal data were statistically analyzed using GraphPad Prism. The signal-to-background ratio (SBR) for NVB was quantitatively calculated to explore the effective dosage and imaging time points. Finally, paraffin pathology sections and HE staining were performed on the imaging structures.

RESULTS

Except for rats in the control group (n=2), right-sided NVB of the rats injected with ICG-NP41 (n=2 per group) were all observed in NIR-Ⅱ fluorescence mode 2 h and 4 h after administration. At 2 h and 4 h, average SBR of cavernous nerve in 2 mg/kg group in fluorescence mode was 1.651±0.142 and 1.619±0.110, respectively, both higher than that in white light mode (1.111±0.036), with no significant difference (P>0.05); average SBR of 4 mg/kg group in fluorescence mode were 1.168±0.066 and 1.219±0.118, respectively, both higher than that in white light mode (1.081±0.040), with no significant difference (P>0.05). At 2 h and 4 h, the average SBR of 2 mg/kg and 4 mg/kg groups in fluorescence mode were higher than that of the control group (SBR=1), the average SBR of the 2 mg/kg group was higher than that of the 4 mg/kg group, and all the above with no significant difference (P>0.05). The average diameter of the nerve measured by full width at half maxima method was about (178±15) μm. HE staining of paraffin sections showed the right major pelvic ganglion.

CONCLUSION

The near-infrared fluorescent targeted probe ICG-NP41 can be used for real-time imaging of the NVB around the prostate in rats, providing a potential feasible solution for localizing NVB in real time during nerve-sparing radical prostatectomy.

Advances in landscape and related therapeutic targets of the prostate tumor microenvironment

The distinct tumor microenvironment (TME) of prostate cancer (PCa), which promotes tumor proliferation and progression, consists of various stromal cells, immune cells, and a dense extracellular matrix (ECM). The understanding of the prostate TME extends to tertiary lymphoid structures (TLSs) and metastasis niches to provide a more concise comprehension of tumor metastasis. These constituents collectively structure the hallmarks of the pro-tumor TME, including immunosuppressive, acidic, and hypoxic niches, neuronal innervation, and metabolic rewiring. In combination with the knowledge of the tumor microenvironment and the advancement of emerging therapeutic technologies, several therapeutic strategies have been developed, and some of them have been tested in clinical trials. This review elaborates on PCa TME components, summarizes various TME-targeted therapies, and provides insights into PCa carcinogenesis, progression, and therapeutic strategies.

Sensitive magnetic particle imaging of haemoglobin degradation for the detection and monitoring of intraplaque haemorrhage in atherosclerosis

BACKGROUND

Intraplaque haemorrhage (IPH) drives atherosclerosis progression and is a key imaging biomarker of unstable plaques. Non-invasive and sensitive monitoring of IPH is challenging due to the compositional complexity and dynamic nature of atherosclerotic plaques. Magnetic particle imaging (MPI) is a highly sensitive, radiation-free, and no-tissue-background tomographic technique that detects superparamagnetic nanoparticles. Thus, we aimed to investigate whether MPI can in vivo detect and monitor IPH.

METHODS

Thirty human carotid endarterectomy samples were collected and scanned with MPI. The tandem stenosis (TS) model was employed to establish unstable plaques with IPH in ApoE^-/- mice. MPI and 7 T T1-weighted magnetic resonance imaging (MRI) were performed on TS ApoE^-/- mice. Plaque specimens were analyzed histologically.

FINDINGS

Human carotid endarterectomy samples exhibited endogenous MPI signals, which histologically colocalized with IPH. In vitro experiments identified haemosiderin, a haemoglobin degradation product, as a potential source of MPI signals. Longitudinal MPI of TS ApoE^-/- mice detected IPH at unstable plaques, of which MPI signal-to-noise ratio values increased from 6.43 ± 1.74 (four weeks) to 10.55 ± 2.30 (seven weeks) and reduced to 7.23 ± 1.44 (eleven weeks). In contrast, 7 T T1-weighted MRI did not detect the small-size IPH (329.91 ± 226.82 μm²) at four weeks post-TS. The time-course changes in IPH were shown to correlate with neovessel permeability providing a possible mechanism for signal changes over time.

INTERPRETATION

MPI is a highly sensitive imaging technology that allows the identification of atherosclerotic plaques with IPH and may help detect and monitor unstable plaques in patients.

FUNDING

This work was supported in part by the Beijing Natural Science Foundation under Grant JQ22023; the National Key Research and Development Program of China under Grant 2017YFA0700401; the National Natural Science Foundation of China under Grant 62027901, 81827808, 81730050, 81870178, 81800221, 81527805, and 81671851; the CAS Youth Innovation Promotion Association under Grant Y2022055 and CAS Key Technology Talent Program; and the Project of High-Level Talents Team Introduction in Zhuhai City (Zhuhai HLHPTP201703).

Cross-domain knowledge transfer based parallel-cascaded multi-scale attention network for limited view reconstruction in projection magnetic particle imaging

Projection magnetic particle imaging (MPI) can significantly improve the temporal resolution of three-dimensional (3D) imaging compared to that using traditional point by point scanning. However, the dense view of projections required for tomographic reconstruction limits the scope of temporal resolution optimization. The solution to this problem in computed tomography (CT) is using limited view projections (sparse view or limited angle) for reconstruction, which can be divided into: completing the limited view sinogram and image post-processing for streaking artifacts caused by insufficient projections. Benefiting from large-scale CT datasets, both categories of deep learning-based methods have achieved tremendous progress; yet, there is a data scarcity limitation in MPI. We propose a cross-domain knowledge transfer learning strategy that can transfer the prior knowledge of the limited view learned by the model in CT to MPI, which can help reduce the network requirements for real MPI data. In addition, the size of the imaging target affects the scale of the streaking artifacts caused by insufficient projections. Therefore, we propose a parallel-cascaded multi-scale attention module that allows the network to adaptively identify streaking artifacts at different scales. The proposed method was evaluated on real phantom and in vivo mouse data, and it significantly outperformed several advanced limited view methods. The streaking artifacts caused by an insufficient number of projections can be overcome using the proposed method.

Enhanced glypican-3-targeted identification of hepatocellular carcinoma with liver fibrosis by pre-degrading excess fibrotic collagen

Most hepatocellular carcinomas (HCCs) occur in cirrhotic livers, but unequivocal diagnosis of early HCC from the fibrotic microenvironment remains a formidable challenge with conventional imaging strategies, mainly because of the massive fibrotic collagen deposition leading to hepatic nodules formation and dysfunction of contrast agent metabolism. Here, we developed a "sweep-and-illuminate" imaging strategy, pre-degrade hepatic fibrotic collagen with collagenase I conjugated human serum albumin (HSA-C) and then targeting visualize HCC lesion with GPC3 targeting nanoparticles (TSI NPs, TJ2 peptide-superparamagnetic iron oxide-indocyanine green) via fluorescence imaging (FLI) and magnetic particle imaging (MPI). TSI NPs delineated a clear boundary of HCC and normal liver, and the tumor-to-background ratios (TBRs) detected by FLI and MPI were 5.43- and 1.34-fold higher than the non-targeted group, respectively. HSA-C could degrade 24.7% fibrotic collagen, followed by 27.2% reduction of nonspecific NPs retention in mice with liver fibrosis. In a pathological state in which HCC occurs in the fibrotic microenvironment, HSA-C-mediated pre-degradation of fibrotic collagen reduced background signal interference in fibrotic tissues and enhanced the intratumoral uptake of TSI NPs, resulting in the clear demarcation between HCC and liver fibrosis, and the TBR was increased 2.61-fold compared to the group without HSA-C pretreatment. We demonstrated the feasibility of combined pre-degradation of fibrotic collagen and application of a GPC3-targeted FLI/MPI contrast agent for early HCC identification, as well as its clinical value in the management of patients with advanced liver fibrosis. STATEMENT OF SIGNIFICANCE: Given that liver fibrosis hinders early detection and treatment options of hepatocellular carcinomas (HCCs), we report a "sweep-and-illuminate" imaging strategy to enhance the efficiency of HCC identification by modulating the irreversible liver fibrosis. We first "sweep" nonspecific interference of contrast agent by pre-degrading fibrotic collagen with human serum albumin-carried collagenase I (HSA-C); and then specifically "illuminate" HCC lesions with GPC3-targeted-SPIO-ICG nanoparticles (TSI NPs). HSA-C can degrade 24.7% fibrotic collagen, followed by 27.2% reduction of nonspecific NPs retention in mice with liver fibrosis. Furthermore, in HCC models coexisting with liver fibrosis, the combined application of HSA-C and TSI NPs can clarify the demarcation between HCC and liver fibrosis with a 2.61-fold increase in the tumor-to-background ratio. This study may expand the potential of combinatorial biomaterials for early HCC diagnosis.

Vagus innervation in the gastrointestinal tumor: Current understanding and challenges

The vagus nerve (VN) is the main parasympathetic nerve of the autonomic nervous system. It is widely distributed in the gastrointestinal tract and maintains gastrointestinal homeostasis with the sympathetic nerve under physiological conditions. The VN communicates with various components of the tumor microenvironment to positively and dynamically affect the progression of gastrointestinal tumors (GITs). The intervention in vagus innervation delays GIT progression. Developments in adeno-associated virus vectors, nanotechnology, and in vivo neurobiological techniques have enabled the creation of precisely regulated "tumor neurotherapies". Furthermore, the combination of neurobiological techniques and single cell sequencing may reveal more insights into VN and GIT. The present review aimed to summarize the mechanisms of communication between the VN and the gastrointestinal TME and to explore the potential and challenges of VN-based tumor neurotherapy in GITs.

Clinical advancement of precision theranostics in prostate cancer

Theranostic approaches with positron emission tomography/computed tomography (PET/CT) or PET/magnetic resonance imaging (PET/MRI) molecular imaging probes are being implemented clinically in prostate cancer (PCa) diagnosis and imaging-guided precision surgery. This review article provides a comprehensive summary of the rapidly expanding list of molecular imaging probes in this field, including their applications in early diagnosis of primary prostate lesions; detection of lymph node, skeletal and visceral metastases in biochemical relapsed patients; and intraoperative guidance for tumor margin detection and nerve preservation. Although each imaging probe shows preferred efficacy in some applications and limitations in others, the exploration and research efforts in this field will eventually lead to improved precision theranostics of PCa.

Understanding and modeling nerve-cancer interactions

The peripheral nervous system plays an important role in cancer progression. Studies in multiple cancer types have shown that higher intratumoral nerve density is associated with poor outcomes. Peripheral nerves have been shown to directly regulate tumor cell properties, such as growth and metastasis, as well as affect the local environment by modulating angiogenesis and the immune system. In this Review, we discuss the identity of nerves in organs in the periphery where solid tumors grow, the known mechanisms by which nerve density increases in tumors, and the effects these nerves have on cancer progression. We also discuss the strengths and weaknesses of current in vitro and in vivo models used to study nerve-cancer interactions. Increased understanding of the mechanisms by which nerves impact tumor progression and the development of new approaches to study nerve-cancer interactions will facilitate the discovery of novel treatment strategies to treat cancer by targeting nerves.

Predicting Tumor Perineural Invasion Status in High-Grade Prostate Cancer Based on a Clinical-Radiomics Model Incorporating T2-Weighted and Diffusion-Weighted Magnetic Resonance Images

PURPOSE

To explore the role of bi-parametric MRI radiomics features in identifying PNI in high-grade PCa and to further develop a combined nomogram with clinical information.

METHODS

183 high-grade PCa patients were included in this retrospective study. Tumor regions of interest (ROIs) were manually delineated on T2WI and DWI images. Radiomics features were extracted from lesion area segmented images obtained. Univariate logistic regression analysis and the least absolute shrinkage and selection operator (LASSO) method were used for feature selection. A clinical model, a radiomics model, and a combined model were developed to predict PNI positive. Predictive performance was estimated using receiver operating characteristic (ROC) curves, calibration curves, and decision curves.

RESULTS

The differential diagnostic efficiency of the clinical model had no statistical difference compared with the radiomics model (area under the curve (AUC) values were 0.766 and 0.823 in the train and test group, respectively). The radiomics model showed better discrimination in both the train cohort and test cohort (train AUC: 0.879 and test AUC: 0.908) than each subcategory image (T2WI train AUC: 0.813 and test AUC: 0.827; DWI train AUC: 0.749 and test AUC: 0.734). The discrimination efficiency improved when combining the radiomics and clinical models (train AUC: 0.906 and test AUC: 0.947).

CONCLUSION

The model including radiomics signatures and clinical factors can accurately predict PNI positive in high-grade PCa patients.

Recent developments of the reconstruction in magnetic particle imaging

Magnetic particle imaging (MPI) is an emerging molecular imaging technique with high sensitivity and temporal-spatial resolution. Image reconstruction is an important research topic in MPI, which converts an induced voltage signal into the image of superparamagnetic iron oxide particles concentration distribution. MPI reconstruction primarily involves system matrix- and x-space-based methods. In this review, we provide a detailed overview of the research status and future research trends of these two methods. In addition, we review the application of deep learning methods in MPI reconstruction and the current open sources of MPI. Finally, research opinions on MPI reconstruction are presented. We hope this review promotes the use of MPI in clinical applications.

Applications of Magnetic Particle Imaging in Biomedicine: Advancements and Prospects

Magnetic particle imaging (MPI) is a novel emerging noninvasive and radiation-free imaging modality that can quantify superparamagnetic iron oxide nanoparticles tracers. The zero endogenous tissue background signal and short image scanning times ensure high spatial and temporal resolution of MPI. In the context of precision medicine, the advantages of MPI provide a new strategy for the integration of the diagnosis and treatment of diseases. In this review, after a brief explanation of the simplified theory and imaging system, we focus on recent advances in the biomedical application of MPI, including vascular structure and perfusion imaging, cancer imaging, the MPI guidance of magnetic fluid hyperthermia, the visual monitoring of cell and drug treatments, and intraoperative navigation. We finally optimize MPI in terms of the system and tracers, and present future potential biomedical applications of MPI.

Exploring the Role of Metabolites in Cancer and the Associated Nerve Crosstalk

Since Otto Warburg's first report on the increased uptake of glucose and lactate release by cancer cells, dysregulated metabolism has been acknowledged as a hallmark of cancer that promotes proliferation and metastasis. Over the last century, studies have shown that cancer metabolism is complex, and by-products of glucose and glutamine catabolism induce a cascade of both pro- and antitumorigenic processes. Some vitamins, which have traditionally been praised for preventing and inhibiting the proliferation of cancer cells, have also been proven to cause cancer progression in a dose-dependent manner. Importantly, recent findings have shown that the nervous system is a key player in tumor growth and metastasis via perineural invasion and tumor innervation. However, the link between cancer-nerve crosstalk and tumor metabolism remains unclear. Here, we discuss the roles of relatively underappreciated metabolites in cancer-nerve crosstalk, including lactate, vitamins, and amino acids, and propose the investigation of nutrients in cancer-nerve crosstalk based on their tumorigenicity and neuroregulatory capabilities. Continued research into the metabolic regulation of cancer-nerve crosstalk will provide a more comprehensive understanding of tumor mechanisms and may lead to the identification of potential targets for future cancer therapies.

Emerging experimental models for assessing perineural invasion in human cancers

Cancer neuroscience has emerged as a burgeoning field for the investigation of cancer-nervous system interactions. Perineural invasion (PNI) is defined as the presence of cancer cells that surround and/or invade the nerves infiltrating the tumor microenvironment. PNI is closely associated with increased tumor recurrence and diminished survival in many cancer types. Based on diverse in vitro, ex vivo, and in vivo models, mounting evidence suggests that the reciprocal crosstalk between nerves and cancer cells drives PNI, which is mediated by several factors including secreted neurotrophins, chemokines, exosomes, and inflammatory cells. Typical in vitro models using dorsal root ganglia (DRG) cells cocultured with cancer cells or other cell types allow the study of isolated factors. Ex vivo PNI models created by cocultivating cancer cells with explanted vagus and sciatic nerves enable the study of neuroaffinity in a time-saving and cost-efficient manner. In vivo models such as genetically engineered mouse models (GEMMs) and the chicken embryo chorioallantoic membrane (CAM)-DRG model, provide the nerve microenvironment needed to recapitulate the complex pathophysiological processes of PNI. Here, we summarize the current methods commonly used for modeling PNI and discuss the inherent pros and cons of these approaches for understanding PNI biology.

Intraoperative near-infrared fluorescence imaging can identify pelvic nerves in patients with cervical cancer in real time during radical hysterectomy

Purpose

Radical hysterectomy combined with pelvic lymphadenectomy is the standard treatment for early-stage cervical cancer, but unrecognized pelvic nerves are vulnerable to irreversible damage during surgery. This early clinical trial investigated the feasibility and safety of intraoperative near-infrared (NIR) fluorescence imaging (NIR-FI) with indocyanine green (ICG) for identifying pelvic nerves during radical hysterectomy for cervical cancer.

Methods

Sixty-six adults with cervical cancer were enrolled in this prospective, open-label, single-arm, single-center clinical trial. NIR-FI was performed in vivo to identify genitofemoral (GN), obturator (ON), and hypogastric (HN) nerves intraoperatively. The primary endpoint was the presence of fluorescence in pelvic nerves. Secondary endpoints were the ICG distribution in a nerve specimen and potential underlying causes of fluorescence emission in pelvic nerves.

Results

In total, 63 patients were analyzed. The ON was visualized bilaterally in 100% (63/63) of patients, with a mean fluorescence signal-to-background ratio (SBR) of 5.3±2.1. The GN was identified bilaterally in 93.7% (59/63) of patients and unilaterally in the remaining 4 patients, with a mean SBR of 4.1±1.9. The HN was identified bilaterally in 81.0% (51/63) of patients and unilaterally in 7.9% (5/63) of patients, with a mean SBR of 3.5±1.3. ICG fluorescence was detected in frozen sections of a nerve specimen, and was mainly distributed in axons. No ICG-related complications were observed.

Conclusion

This early clinical trial demonstrated the feasibility and safety of NIR-FI to visualize pelvic nerves intraoperatively. Thus, NIR-FI may help surgeons adjust surgical decision-making, avoid nerve damage, and improve surgical outcomes.

Trial registration

ClinicalTrials.gov NCT04224467

The Adrenergic Nerve Network in Cancer

The central and autonomic nervous systems interact and converge to build up an adrenergic nerve network capable of promoting cancer. While a local adrenergic sympathetic innervation in peripheral solid tumors influences cancer and stromal cell behavior, the brain can participate to the development of cancer through an intermixed dysregulation of the sympathoadrenal system, adrenergic neurons, and the hypothalamo-pituitary-adrenal axis. A deeper understanding of the adrenergic nerve circuitry within the brain and tumors and its interactions with the microenvironment should enable elucidation of original mechanisms of cancer and novel therapeutic strategies.

Nerve density in cancer: Less is better

The density of nerves in cancer is emerging as a relevant clinical parameter for patient survival. Nerves in the tumor microenvironment have been associated with poor survival and recurrence, particularly if involved in perineural invasion. However, usually only a few nerves inside a tumor are affected by perineural invasion, while most nerves are not. Mechanistic studies have shown nerve-secreted factors promote tumor growth and invasion thereby making tumors more aggressive. Therefore, the overall number of nerves in the tumor microenvironment should be more representative of the nerve-tumor biological interaction than perineural invasion. This review summarizes the available clinical information about nerve density as a measure of clinical outcome in cancer and explores the mechanisms underlying nerve density in cancer, specifically, neurogenesis, axonogenesis, and neurotropism.

Engineering of magnetic nanoparticles as magnetic particle imaging tracers

Magnetic particle imaging (MPI) has recently emerged as a promising non-invasive imaging technique because of its signal linearly propotional to the tracer mass, ability to generate positive contrast, low tissue background, unlimited tissue penetration depth, and lack of ionizing radiation. The sensitivity and resolution of MPI are highly dependent on the properties of magnetic nanoparticles (MNPs), and extensive research efforts have been focused on the design and synthesis of tracers. This review examines parameters that dictate the performance of MNPs, including size, shape, composition, surface property, crystallinity, the surrounding environment, and aggregation state to provide guidance for engineering MPI tracers with better performance. Finally, we discuss applications of MPI imaging and its challenges and perspectives in clinical translation.

Investigation of Neural Microenvironment in Prostate Cancer in Context of Neural Density, Perineural Invasion, and Neuroendocrine Profile of Tumors

Background

Cancer stroma contains the neural compartment with specific components and action. Neural microenvironment processing includes among others axonogenesis, perineural invasion (PNI), neurosignaling, and tumor cell neural/neuroendocrine differentiation. Growing data suggest that tumor-neural crosstalk plays an important function in prostate cancer (PCa) biology. However, the mechanisms involved in PNI and axonogenesis, as well as their patho-clinical correlations in this tumor are unclear.

Methods

The present study was carried out on FFPE samples of 73 PCa and 15 benign prostate (BP) cases. Immunohistochemistry with neural markers PGP9.5, TH, and NFP was performed on constructed TMAs and selected tissue sections. The analyzed parameters of tumor innervation included small nerve density (ND) measured on pan-neural marker (PGP9.5) and TH s4tained slides, as well assessment of PNI presence and morphology. The qualitative and topographic aspects were studied. In addition, the expression of neuroendocrine marker chromogranin and NPY was assessed with dedicated indexes. The correlations of the above parameters with basic patho-clinical data such as patients’ age, tumor stage, grade, angioinvasion, and ERG status were examined.

Results

The study showed that innervation parameters differed between cancer and BP. The neural network in PCa revealed heterogeneity, and ND PGP9.5 in tumor was significantly lower than in its periphery. The density of sympathetic TH-positive fibers and its proportion to all fibers was lower in cancer than in the periphery and BP samples. Perineural invasion was confirmed in 76% of cases, usually multifocally, occurring more commonly in tumors with a higher grade. NPY expression in PCa cells was common with its intensity often rising towards PNI. ERG+ tumors showed higher ND, more frequent PNI, and a higher stage. Moreover, chromogranin-positive cells were more pronounced in PCa with higher NPY expression.

Conclusions

The analysis showed an irregular axonal network in prostate cancer with higher neural density (panneural and adrenergic) in the surroundings and the invasive front. ND and PNI interrelated with NPY expression, neuroendocrine differentiation, and ERG status. The above findings support new evidence for the presence of autocrine and paracrine interactions in prostate cancer neural microenvironment.

Clinical Potential of Nerve Input to Tumors: A Bioelectricity Perspective

We support the notion that the neural connections of the tumor microenvironment (TME) and the associated 'bioelectricity' play significant role in the pathophysiology of cancer. In several cancers, the nerve input promotes the cancer process. While straightforward surgical denervation of tumors, therefore, could improve prognosis, resulting side effects of such a procedure would be unpredictable and irreversible. On the other hand, tumor innervation can be manipulated effectively for therapeutic purposes by alternative novel approaches broadly termed "electroceuticals." In this perspective, we evaluate the clinical potential of targeting the TME first through manipulation of the nerve input itself and second by application of electric fields directly to the tumor. The former encompasses several different biophysical and biochemical approaches. These include implantable devices, nanoparticles, and electroactive polymers, as well as optogenetics and chemogenetics. As regard bioelectrical manipulation of the tumor itself, the "tumor-treating field" technique, applied to gliomas commonly in combination with chemotherapy, is evaluated. Also, as electroceuticals, drugs acting on ion channels and neurotransmitter receptors are highlighted for completeness. It is concluded, first, that electroceuticals comprise a broad range of biomedical tools. Second, such electroceuticals present significant clinical potential for exploiting the neural component of the TME as a strategy against cancer. Finally, the inherent bioelectric characteristics of tumors themselves are also amenable to complementary approaches. Collectively, these represent an evolving, dynamic field and further progress and applications can be expected to follow both conceptually and technically.

Highly sensitive magnetic particle imaging of vulnerable atherosclerotic plaque with active myeloperoxidase-targeted nanoparticles

Inflammation is a pivotal driver of atherosclerotic plaque progression and rupture and is a target for identifying vulnerable plaques. However, challenges arise with the current in vivo imaging modalities for differentiating vulnerable atherosclerotic plaques from stable plaques due to their low specificity and sensitivity. Herein, we aimed to develop a novel multimodal imaging platform that specifically targets and identifies high-risk plaques in vivo by detecting active myeloperoxidase (MPO), a potential inflammatory marker of vulnerable atherosclerotic plaque.

Methods: A novel multimodal imaging agent, 5-HT-Fe₃O₄-Cy7 nanoparticles (5HFeC NPs), used for active MPO targeting, was designed by conjugating superparamagnetic iron oxide nanoparticles (SPIONs) with 5-hydroxytryptamine and cyanine 7 N-hydroxysuccinimide ester. The specificity and sensitivity of 5HFeC NPs were evaluated using magnetic particle imaging (MPI), fluorescence imaging (FLI), and computed tomographic angiography (CTA) in an ApoE^-/- atherosclerosis mouse model. Treatment with 4-ABAH, an MPO inhibitor, was used to assess the monitoring ability of 5HFeC NPs.

Results: 5HFeC NPs can sensitively differentiate and accurately localize vulnerable atherosclerotic plaques in ApoE^-/- mice via MPI/FLI/CTA. High MPI and FLI signals were observed in atherosclerotic plaques within the abdominal aorta, which were histologically confirmed by multiple high-risk features of macrophage infiltration, neovascularization, and microcalcification. Inhibition of active MPO reduced accumulation of 5HFeC NPs in the abdominal aorta. Accumulation of 5HFeC NPs in plaques enabled quantitative evaluation of the severity of inflammation and monitoring of MPO activity.

Conclusions: This multimodal MPI approach revealed that active MPO-targeted nanoparticles might serve as a method for detecting vulnerable atherosclerotic plaques and monitoring MPO activity.

Relation between structural patterns and magnetism in small iron oxide clusters: reentrance of the magnetic moment at high oxidation ratios

Due to quantum confinement effects, the understanding of iron oxide nanoparticles is a challenge that opens the possibility of designing nanomaterials with new capacities. In this work, we report a theoretical density functional theory study of the structural, electronic, and magnetic properties of neutral and charged iron oxide clusters FenOm0/± (n = 1-6), with m values until oxygen saturation is achieved. We determine the putative ground state configuration and low-energy structural and spin isomers. Based on the total energy differences between the obtained global minimum structure of the parent clusters and their possible fragments, we explore the fragmentation channels for cationic oxides, comparing with experiments. Our results provide fundamental insight on how the structural pattern develops upon oxidation and its connection with the magnetic couplings and net total moment. Upon addition of oxygen, electronic charge transfer from iron to oxygen is found which weakens the iron-iron bond and consequently the direct exchange coupling in Fe. The binding energy increases as the oxygen ratio increases, rising faster at low oxidation rates. When molecular oxygen adsorption starts to take place, the binding energy increases more slowly. The oxygen environment is a crucial factor related to the stabilities and to the magnetic character of iron oxides. We identified certain iron oxide clusters of special relevance in the context of magnetism due to their high stability, expected abundance and parallel magnetic couplings that cause large total magnetic moments even at high oxidation ratios.

The Applications of Magnetic Particle Imaging: From Cell to Body

Magnetic particle imaging (MPI) is a cutting-edge imaging technique that is attracting increasing attention. This novel technique collects signals from superparamagnetic nanoparticles as its imaging tracer. It has characteristics such as linear quantitativity, positive contrast, unlimited penetration, no radiation, and no background signal from surrounding tissue. These characteristics enable various medical applications. In this paper, we first introduce the development and imaging principles of MPI. Then, we discuss the current major applications of MPI by dividing them into four categories: cell tracking, blood pool imaging, tumor imaging, and visualized magnetic hyperthermia. Even though research on MPI is still in its infancy, we hope this discussion will promote interest in the applications of MPI and encourage the design of tracers tailored for MPI.

The updated landscape of tumor microenvironment and drug repurposing

Accumulating evidence shows that cellular and acellular components in tumor microenvironment (TME) can reprogram tumor initiation, growth, invasion, metastasis, and response to therapies. Cancer research and treatment have switched from a cancer-centric model to a TME-centric one, considering the increasing significance of TME in cancer biology. Nonetheless, the clinical efficacy of therapeutic strategies targeting TME, especially the specific cells or pathways of TME, remains unsatisfactory. Classifying the chemopathological characteristics of TME and crosstalk among one another can greatly benefit further studies exploring effective treating methods. Herein, we present an updated image of TME with emphasis on hypoxic niche, immune microenvironment, metabolism microenvironment, acidic niche, innervated niche, and mechanical microenvironment. We then summarize conventional drugs including aspirin, celecoxib, β-adrenergic antagonist, metformin, and statin in new antitumor application. These drugs are considered as viable candidates for combination therapy due to their antitumor activity and extensive use in clinical practice. We also provide our outlook on directions and potential applications of TME theory. This review depicts a comprehensive and vivid landscape of TME from biology to treatment.