Ultrasound Molecular Imaging of Epithelial Mesenchymal Transition for Evaluating Tumor Metastatic Potential via Targeted Biosynthetic Gas Vesicles

Epithelial mesenchymal transition (EMT) of tumor cells is recognized as the main driver to promote metastasis. Extensive researches suggest that gradually decreased E-cadherin (E-cad) and increased N-cadherin (N-cad) exist in the tumor cells during the EMT process. However, there still lacks suitable imaging methods to monitor the status of EMT for evaluating tumor metastatic potentials. Herein, the E-cad-targeted and N-cad-targeted gas vesicles (GVs) are developed as the acoustic probes to monitor the EMT status in tumor. The resulting probes have ≈200 nm particle size and good tumor cell targeting performance. Upon systemic administration, E-cad-GVs and N-cad-GVs can traverse through blood vessels and bind to the tumor cells, producing strong contrast imaging signals in comparison with the nontargeted GVs. The contrast imaging signals correlate well with the expression levels of E-cad and N-cad and tumor metastatic ability. This study provides a new strategy to noninvasively monitor the EMT status and help to evaluate tumor metastatic potential in vivo.     

Performance analysis of computer aided brain tumor detection system using ANFIS classifier

The abrupt changes in brain cells due to the environmental effects or genetic disorders leads to form the abnormal lesions in brain. These abnormal lesions are combined as mass and known as tumor. The detection of these tumor cells in brain image is a complex task due to the similarities between normal cells and tumor cells. In this paper, an automated brain tumor detection and segmentation methodology is proposed. The proposed method consists of feature extraction, classification and segmentation. In this paper, Grey Level Co‐Occurrence Matrix (GLCM), Discrete Wavelet Transform (DWT) and Law's texture features are used as features. These features are fed to Adaptive Neuro Fuzzy Inference System (ANFIS) classifier as input pattern, which classifies the brain image. Morphological operations are now applied on the classified abnormal brain image to segment the tumor regions. The proposed system achieves 95.07% of sensitivity, 99.84% of specificity and 99.80% of accuracy for tumor segmentation.     

Performance analysis of brain tissues and tumor detection and grading system using ANFIS classifier

Abnormal growth of cells in brain leads to the formation of tumors, which are categorized into benign and malignant. In this article, Co‐Active Adaptive Neuro Fuzzy Inference System (CANFIS) classification based brain tumor detection and its grading system is proposed. It has two phases as brain tumor segmentation and brain tissue segmentation. In brain tumor segmentation, CANFIS classifier is used to classify the test brain image into benign or malignant. Then, morphological operations are applied over the malignant image in order to segment the tumor regions in brain image. The K‐means classifier is used to classify the brain tissues into Grey Matter (GM), White Matter (WM) and Cerebro Spinal Fluid (CSF) regions as three different classes. Next, the segmented tumor is graded as mild, moderate or severe based on the presence of segmented tumor region in brain tissues.     

Granzyme B Functionalized Nanoparticles Targeting Membrane Hsp70‐Positive Tumors for Multimodal Cancer Theranostics

Functionalized superparamagnetic iron oxide nanoparticles (SPIONs) have emerged as potential clinical tools for cancer theranostics. Membrane‐bound 70 kDa heat shock protein (mHsp70) is ubiquitously expressed on the cell membrane of various tumor types but not normal cells and therefore provides a tumor‐specific target. The serine protease granzyme B (GrB) that is produced as an effector molecule by activated T and NK cells has been shown to specifically target mHsp70 on tumor cells. Following binding to Hsp70, GrB is rapidly internalized into tumor cells. Herein, it is demonstrated that GrB functionalized SPIONs act as a contrast enhancement agent for magnetic resonance imaging and induce specific tumor cell apoptosis. Combinatorial regimens employing stereotactic radiotherapy and/or magnetic targeting are found to further enhance the therapeutic efficacy of GrB‐SPIONs in different tumor mouse models.     

A Learning Based Brain Tumor Detection System

Brain tumor is one of the most dangerous disease that causes due to uncontrollable and abnormal cell partition. In this paper, we have used MRI brain scan in comparison with CT brain scan as it is less harmful to detect brain tumor. We considered watershed segmentation technique for brain tumor detection. The proposed methodology is divided as follows: pre-processing, computing foreground applying watershed, extract and supply features to machine learning algorithms. Consequently, this study is tested on big data set of images and we achieved acceptable accuracy from K-NN classification algorithm in detection of brain tumor.     

Implantable Synthetic Immune Niche for Spatiotemporal Modulation of Tumor‐Derived Immunosuppression and Systemic Antitumor Immunity: Postoperative Immunotherapy

The development of biomaterial‐based immune niches that can modulate immunosuppressive factors in tumor microenvironment (TME) will be a key technology for improving current cancer immunotherapy. Here, implantable, engineered 3D porous scaffolds are designed to generate synergistic action between myeloid‐derived suppressor cell (MDSC)‐depleting agents, which can accommodate the establishment of a permissive immunogenic microenvironment to counteract tumor‐induced immunosuppression, and cancer vaccines consisting of whole tumor lysates and nanogel‐based adjuvants, which can generate tumor antigen‐specific T cell responses. The local peritumoral implantation of the synthetic immune niche (termed immuneCare‐DISC, iCD) as a postsurgical treatment in an advanced‐stage primary 4T1 breast tumor model generates systemic antitumor immunity and prevents tumor recurrence at the surgical site as well as the migration of residual tumor cells into the lungs, resulting in 100% survival. These therapeutic outcomes are achieved through the inhibition of immunosuppressive MDSCs in tumors and spleens by releasing gemcitabine and recruitment/activation of dendritic cells, enhanced population of CD4⁺ and CD8⁺ T cells, and increased IFN‐γ production by cancer vaccines from the iCD. This combined spatiotemporal modulation of tumor‐derived immunosuppression and vaccine‐induced immune stimulation through the iCD is expected to provide an immune niche for prevention of postoperative tumor recurrence and metastasis.     

Engineering Macrophages for Cancer Immunotherapy and Drug Delivery

Macrophages play an important role in cancer development and metastasis. Proinflammatory M1 macrophages can phagocytose tumor cells, while anti-inflammatory M2 macrophages such as tumor-associated macrophages (TAMs) promote tumor growth and invasion. Modulating the tumor immune microenvironment through engineering macrophages is efficacious in tumor therapy. M1 macrophages target cancerous cells and, therefore, can be used as drug carriers for tumor therapy. Herein, the strategies to engineer macrophages for cancer immunotherapy, such as inhibition of macrophage recruitment, depletion of TAMs, reprograming of TAMs, and blocking of the CD47-SIRPα pathway, are discussed. Further, the recent advances in drug delivery using M1 macrophages, macrophage-derived exosomes, and macrophage-membrane-coated nanoparticles are elaborated. Overall, there is still significant room for development in macrophage-mediated immune modulation and macrophage-mediated drug delivery, which will further enhance current tumor therapies against various malignant solid tumors, including drug-resistant tumors and metastatic tumors.     

Fully automatic brain tumor extraction and tissue segmentation from multimodal MRI brain images

Segmentation of Brain tumor from the magnetic resonance imaging (MRI) of head scans is an essential requirement for clinical diagnosis since manual segmentation is a fatigue and time‐consuming process. Recent computer‐aided diagnosis systems depend on the development of fully automatic methods to overcome these problems. In the present work, a fully automated algorithm is proposed to extract and segment tumor regions from multimodal magnetic resonance imaging (MMMRI) sequences. The algorithm has three phases: (a) tumor portion extraction, (b) tumor substructure segmentation, and (c) 3D postprocessing. First, the algorithm extracts tumor portion using a set of image processing operations from T2, fluid‐attenuated inversion recovery (FLAIR), and T1C images. Here, the proposed modified fuzzy c means clustering algorithm is used for enhancing the tumor portion extraction process. Then, the substructures of tumor such as edema, enhancing tumor, and necrotic regions are segmented from MMMRI sequences, T2, FLAIR, and T1C using region‐wise set operations in Phase II. Finally, 3D visualization of the segmented tumor and volume estimation is performed as postprocessing in Phase III. The proposed work was experimented on BraTS 2013 dataset. The quantitative analysis is performed using William's Index, Dice, sensitivity, specificity, and accuracy and is compared with 19 state‐of‐the‐art methods. The proposed method yields comparable results as 77%, 53%, and 59% of Dice for complete, core, and enhancing tumor regions, respectively.     

Through Scalp and Skull NIR‐II Photothermal Therapy of Deep Orthotopic Brain Tumors with Precise Photoacoustic Imaging Guidance

Brain tumor is one of the most lethal cancers owing to the existence of blood–brain barrier and blood–brain tumor barrier as well as the lack of highly effective brain tumor treatment paradigms. Herein, cyclo(Arg‐Gly‐Asp‐D‐Phe‐Lys(mpa)) decorated biocompatible and photostable conjugated polymer nanoparticles with strong absorption in the second near‐infrared (NIR‐II) window are developed for precise photoacoustic imaging and spatiotemporal photothermal therapy of brain tumor through scalp and skull. Evidenced by the higher efficiency to penetrate scalp and skull for 1064 nm laser as compared to common 808 nm laser, NIR‐II brain‐tumor photothermal therapy is highly effective. In addition, via a real‐time photoacoustic imaging system, the nanoparticles assist clear pinpointing of glioma at a depth of almost 3 mm through scalp and skull with an ultrahigh signal‐to‐background ratio of 90. After spatiotemporal photothermal treatment, the tumor progression is effectively inhibited and the survival spans of mice are significantly extended. This study demonstrates that NIR‐II conjugated polymer nanoparticles are promising for precise imaging and treatment of brain tumors.     

Vesicular Antibodies: A Bioactive Multifunctional Combination Platform for Targeted Therapeutic Delivery and Cancer Immunotherapy

The ability to selectively kill cancerous cell populations while leaving healthy cells unaffected is a key goal in oncology. The use of nanovesicles (NVs) as chemotherapeutic delivery vehicles has been recently proven successful, yet monotherapy with monomodalities remains a significant limitation for solid tumor treatment. Here, as a proof of principle, a novel cell‐membrane‐derived NVs that can display full‐length monoclonal antibodies (mAbs) is engineered. The high affinity and specificity of mAb for tumor‐specific antigens allow these vesicular antibodies (VAs) to selectively deliver a cytotoxic agent to tumor cells and exert potent inhibition effects. These VAs can also regulate the tumor immune microenvironment. They can mediate antibody‐dependent cellular cytotoxicity to eradicate tumor cells via recruitment and activation of natural killer cells in the tumor. Upon further encapsulation with chemotherapeutic agents, the VAs show unequaled cooperative effects in chemotherapy and immunotherapy in tumor‐bearing mice. As far as it is known, this is the first report of a VA‐based multifunctional combination therapy platform. This might lead to additional applications of vesicular antibodies in cancer theranostics.     

CANFIS based glioma brain tumor classification and retrieval system for tumor diagnosis

Brain tumor classification and retrieval system plays an important role in medical field. In this paper, an efficient Glioma Brain Tumor detection and its retrieval system is proposed. The proposed methodology consists of two modules as classification and retrieval. The classification modules are designed using preprocessing, feature extraction and tumor detection techniques using Co‐Active Adaptive Neuro Fuzzy Inference System (CANFIS) classifier. The image enhancement can be achieved using Heuristic histogram equalization technique as preprocessing and further texture features as Local Ternary Pattern (LTP) features and Grey Level Co‐occurrence Matrix (GLCM) features are extracted from the enhanced image. These features are used to classify the brain image into normal and abnormal using CANFIS classifier. The tumor region in abnormal brain image is segmented using normalized graph cut segmentation algorithm. The retrieval module is used to retrieve the similar segmented tumor regions from the dataset for diagnosing the tumor region using Euclidean algorithm. The proposed Glioma Brain tumor classification methodology achieves 97.28% sensitivity, 98.16% specificity and 99.14% accuracy. The proposed retrieval system achieves 97.29% precision and 98.16% recall rate with respect to ground truth images.     

A Highly Efficient Tumor‐Targeting Nanoprobe with a Novel Cell Membrane Permeability Mechanism

Efficient tumor targeting has been a great challenge in the clinic for a very long time. The traditional targeting methods based on enhanced permeability and retention (EPR) effects show only an ≈5% targeting rate. To solve this problem, a new graphene‐based tumor cell nuclear targeting fluorescent nanoprobe (GTTN), with a new tumor‐targeting mechanism, is developed. GTTN is a graphene‐like single‐crystalline structure amphiphilic fluorescent probe with a periphery that is functionalized by sulfonic and hydroxyl groups. This probe has the characteristic of specific tumor cell targeting, as it can directly cross the cell membrane and specifically target to the tumor cell nucleus by the changed permeability of the tumor cell membranes in the tumor tissue. This new targeting mechanism is named the cell membrane permeability targeting (CMPT) mechanism, which is very different from the EPR effect. These probes can recognize tumor tissue at a very early stage and track the invasion and metastasis of tumor cells at the single cell level. The tumor‐targeting rate is improved from less than 5% to more than 50%. This achievement in efficient and accurate tumor cell targeting will speed up the arrival of a new era of tumor diagnosis and treatment.     

Active Targeting of Dendritic Polyglycerols for Diagnostic Cancer Imaging

Active tumor targeting involves the decoration of nanomaterials (NMs) with oncotropic vector biomolecules that selectively recognize certain antigens on malignant cells or in the tumor microenvironment. This strategy can facilitate intracellular uptake of NM through specific interactions such as receptor‐mediated endocytosis and can lead to prolonged retention in the malignant tissues by preventing rapid efflux from the tumor. Here, the design of actively targeting, renally excretible bimodal dendritic polyglycerols (dPGs) for diagnostic cancer imaging is described. Single‐domain antibodies (sdAbs) specifically binding to the epidermal growth factor receptor (EGFR) are employed herein as targeting warheads owing to their small size and high affinity for their corresponding antigen. The dPGs equipped with EGFR‐targeting feature are compared head‐to‐head with their nontargeting counterparts in terms of interaction with EGFR‐overexpressing cells in vitro as well as accumulation at receptor‐positive tumors in vivo. Experimental results reveal a higher specificity and preferential tumor accumulation for the α‐EGFR dPGs, resulting from the introduction of active targeting capabilities on their backbone. These results highlight the potential for improving the tumor uptake properties of dPGs by strategic use of sdAb functionalization, which can ultimately prove useful to the development of ultrasmall NM with highly specific tumor accumulation.     

Multi‐modal brain tumor image segmentation based on SDAE

Accurate tumor segmentation has the ability to provide doctors with a basis for surgical planning. Moreover, brain tumor segmentation needs to extract different tumor tissues (Edema, tumor, tumor enhancement, and necrosis) from normal tissues which is a big challenge because tumor structures vary considerably across patients in terms of size, extension, and localization. In this article, we evaluate a fully automated method for segmenting brain tumor images from multi‐modal magnetic resonance imaging volumes based on stacked de‐noising auto‐encoders (SDAEs). Specially, we adopted multi‐modality information from T1, T1c, T2, and Flair images, respectively. We extracted gray level patches from different modalities as the input of the SDAE. After trained by the SDAE, the raw network parameters will be obtained, which are adopted as a parameter of the feed forward neural network for classification. A simple post‐processing is implemented by threshold segmentation method to generate a mask to get the final segmentation result. By evaluating the proposed method on the BRATS 2015, it can be proven that our method obtains the better performance than other state‐of‐the‐art counterpart methods. And a preliminary dice score of 0.86 for whole tumor segmentation has been achieved.     

Multi-functional nanoparticles for cancer therapy

Many immunotherapeutic strategies developed in recent years involve the targeting of immune cells to tumors. In this study, we synthesized and characterized modified fluorescent nanoparticles as a targeting and delivery system, by conjugating both tumor targeting agent and chemokines to the nanoparticles, to attract immune cells to tumor cells. Biodegradable chitosan nanoparticles encapsulating quantum dots were prepared, with suitable surface modification to immobilize both tumor targeting agent and chemokine on their surfaces. The interactions between immune cells and tumor cells were visualized using optical microscope.     

Traveling wave behavior in a two-phase flow model of tumor growth

Tumor growth which undergoes complex bio-mechanical processes has been a significant focus for mathematical modeling, with particular interest in its dynamic behavior. In this paper, we consider a two-phase flow model for describing the dynamics of tumor growth. The model accounts for aggregate cell movement and mechanical interactions between tumor cells as well as cell proliferation. In suitable limits, by using the dynamical systems theory approach, tumor growth in this mechanical model is shown to occur in the form of traveling waves that can propagate either forward or backward, depending on the values of the parameters. Our results, in particular, the wave profiles of tumor cell density are more realistic and explain those obtained in a recently developed simple, experiment-based, model for studying non-spatial dynamics of tumor cells.     

Tumor-Targeted Quantum Dots Can Help Surgeons Find Tumor Boundaries

Despite surgical advances and recent progress in adjuvant therapies, the prognosis for patients with malignant brain tumors such as glioblastoma multiforme has remained poor, and the neurological deterioration suffered by most patients as a consequence of tumor progression is dramatic and severe. In addition, malignant brain tumors have ≫95% recurrence close to the primary site of initial resection. Unfortunately, standard imaging techniques do not permit the intraoperative identification of individual or small clusters of residual tumor cells, precluding their selective removal while sparing the surrounding normal brain tissue. In this report, we show that quantum dots (QDs) coupled to epidermal growth factor (EGF) or anti-EGF receptor receptor (EGFR, Her1) specifically and sensitively label glial tumor cells in cell culture, glioma mouse models, and human brain–tumor biopsies. A clear demarcation between brain and tumor tissue at the macroscopic as well as the cellular level is provided by the fluorescence emission of the QDs.      

Transforming Weakness into Strength: Photothermal‐Therapy‐Induced Inflammation Enhanced Cytopharmaceutical Chemotherapy as a Combination Anticancer Treatment

A new synergistic treatment that combines photothermal therapy (PTT) and inflammation‐mediated active targeting (IMAT) chemotherapy based on cytopharmaceuticals is developed. During PTT, the photothermal tumor ablation is accompanied by an inflammatory effect and upregulation of inflammatory factors at the tumor site, which may accelerate tumor regeneration. Moreover, PTT‐induced inflammation can also recruit neutrophils (NEs) to the tumor site. To convert the disadvantages of PTT‐induced inflammation into strengths, NEs are investigated as cytopharmaceuticals for IMAT chemotherapy to further inhibit the tumor recurrence after PTT due to the chemotaxis of NEs to the inflammatory sites. In this study, PEGylated gold nanorods (PEG‐GNRs) are explored as the photothermal agent and paclitaxel‐loaded cytopharmaceuticals of NEs as the IMAT chemotherapeutic agent. PTT is conducted at 72 h postinjection of PEG‐GNRs, followed by cytopharmaceuticals for IMAT chemotherapy. It is demonstrated that the cytopharmaceuticals effectively accumulate in the tumor sites after PTT, which leads to a significant enhancement of antitumor efficacy and a reduction in systemic toxicity. These studies suggest that PTT‐induced inflammation further enhances the chemotherapy of cytopharmaceuticals, and the combination of PTT and IMAT chemotherapy may be a promising synergistic strategy for targeted cancer therapy.     

A “Missile‐Detonation” Strategy to Precisely Supply and Efficiently Amplify Cerenkov Radiation Energy for Cancer Theranostics

Cerenkov radiation (CR) from radionuclides can act as a built‐in light source for cancer theranostics, opening a new horizon in biomedical applications. However, considerably low tumor‐targeting efficiency of existing radionuclides and radionuclide‐based nanomedicines limits the efficacy of CR‐induced theranostics (CRIT). It remains a challenge to precisely and efficiently supply CR energy to the tumor site. Here, a “missile‐detonation” strategy is reported, in which a high dose of p‐SCN‐Bn‐deferoxamine‐porphyrin‐PEG nanocomplex (Df‐PPN) is first adminstered as a CR energy receiver/missile to passively target to tumor, and then a low dose of the ⁸⁹Zr‐labeled Df‐PPN is administrated as a CR energy donor/detonator, which can be visualized and quantified by Cerenkov energy transfer imaging, positron‐emission tomography, and fluorescence imaging. Based on homologous properties, the colocalization of Df‐PPN and ⁸⁹Zr‐Df‐PPN in the tumor site is maximized and efficient CR energy transfer is enabled, which maximizes the tumor‐targeted CRIT efficacy in an optimal spatiotemporal setting while also reducing adverse off‐target effects from CRIT. This precise and efficient CRIT strategy causes significant tumor vascular damage and inhibited tumor growth.     

Systemic Delivery of a STING Agonist-Loaded Positively Charged Liposome Selectively Targets Tumor Immune Microenvironment and Suppresses Tumor Angiogenesis

Although stimulator of interferon genes (STING) agonists has shown great promise in preclinical studies, the clinical development of STING agonist therapy is challenged by its limited systemic delivery. Here, positively charged fusogenic liposomes loaded with a STING agonist (PoSTING) are designed for systemic delivery and to preferentially target the tumor microenvironment. When PoSTING is administered intravenously, it selectively targets not only tumor cells but also immune and tumor endothelial cells (ECs). In particular, delivery of STING agonists to tumor ECs normalizes abnormal tumor vasculatures, induces intratumoral STING activation, and elicits robust anti-tumor T cell immunity within the tumor microenvironment. Therefore, PoSTING can be used as a systemic delivery platform to overcome the limitations of using STING agonists in clinical trials.