Project description:Although the incidence of central nervous system (CNS) cancers is not high, it significantly reduces a patient's quality of life and results in high mortality rates. A low incidence also means a low number of cases, which in turn means a low amount of information. To compensate, researchers have tried to increase the amount of information available from a single test using high-throughput technologies. This approach, referred to as single-omics analysis, has only been partially successful as one type of data may not be able to appropriately describe all the characteristics of a tumor. It is presently unclear what type of data can describe a particular clinical situation. One way to solve this problem is to use multi-omics data. When using many types of data, a selected data type or a combination of them may effectively resolve a clinical question. Hence, we conducted a comprehensive survey of papers in the field of neuro-oncology that used multi-omics data for analysis and found that most of the papers utilized machine learning techniques. This fact shows that it is useful to utilize machine learning techniques in multi-omics analysis. In this review, we discuss the current status of multi-omics analysis in the field of neuro-oncology and the importance of using machine learning techniques.
Project description:Recent reports herald important advances in our understanding and management of gliomas. A role for alkylator chemotherapy in the management of certain high-grade gliomas has been confirmed and linked to specific, clinically ascertainable molecular markers. Magnetic resonance spectroscopy can now image 2-hydroxyglutarate, an oncometabolite restricted to the three-quarters of low-intermediate grade gliomas harboring an isocitrate dehydrogenase gene mutation; this has powerful implications for diagnosis and assessment of response to therapies. Genome-wide association studies point to several SNPs conveying increased risk of glioma; further studies of the involved genes and RNA products will enhance our understanding of glioma development. Finally, high-throughput sequencing has identified novel mutations in a histone-coding gene and in genes related to the histone complex in pediatric glioblastoma.
Project description:A group of impressive immunotherapies for cancer treatment, including immune checkpoint-blocking antibodies, gene therapy and immune cell adoptive cellular immunotherapy, have been established, providing new weapons to fight cancer. Natural killer (NK) cells are a component of the first line of defense against tumors and virus infections. Studies have shown dysfunctional NK cells in patients with cancer. Thus, restoring NK cell antitumor functionality could be a promising therapeutic strategy. NK cells that are activated and expanded ex vivo can supplement malfunctional NK cells in tumor patients. Therapeutic antibodies, chimeric antigen receptor (CAR), or bispecific proteins can all retarget NK cells precisely to tumor cells. Therapeutic antibody blockade of the immune checkpoints of NK cells has been suggested to overcome the immunosuppressive signals delivered to NK cells. Oncolytic virotherapy provokes antitumor activity of NK cells by triggering antiviral immune responses. Herein, we review the current immunotherapeutic approaches employed to restore NK cell antitumor functionality for the treatment of cancer.
Project description:Pancreatic ductal adenocarcinoma (PDAC) is a solid malignant tumor with an extremely poor prognosis. Gemcitabine (GEM)-based chemotherapy remains one of the most important treatment choices for PDAC. However, either as monotherapy or as a part of the combination chemotherapy, GEM achieved only limited success in improving the survival of patients with advanced PDAC, primarily due to GEM resistance. PDAC is characterized by an extensive desmoplasia in the tumor microenvironment (TME). Increasing evidence indicates that this fibrotic TME not only actively participates in the tumor growth and spread of PDAC but also contributes to the induction of GEM resistance. Here we review the current advances of how TME components are involved in the induction of GEM resistance.
Project description:Brain tumors, characterized by the uncontrolled growth of abnormal cells, pose a significant threat to human health. Early detection is crucial for successful treatment and improved patient outcomes. Magnetic Resonance Imaging (MRI) is the primary diagnostic tool for brain tumors, providing detailed visualizations of the brain's intricate structures. However, the complexity and variability of tumor shapes and locations often challenge physicians in achieving accurate tumor segmentation on MRI images. Precise tumor segmentation is essential for effective treatment planning and prognosis. To address this challenge, we propose a novel hybrid deep learning technique, Convolutional Neural Network and ResNeXt101 (ConvNet-ResNeXt101), for automated tumor segmentation and classification. Our approach commences with data acquisition from the BRATS 2020 dataset, a benchmark collection of MRI images with corresponding tumor segmentations. Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. This involves extracting features based on tumor shape, position, shape, and surface characteristics. To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). AWO mimics the hunting behavior of humpback whales to iteratively search for the optimal feature subset. With the selected features, we perform image segmentation using the ConvNet-ResNeXt101 model. This deep learning architecture combines the strengths of ConvNet and ResNeXt101, a type of ConvNet with aggregated residual connections. Finally, we apply the same ConvNet-ResNeXt101 model for tumor classification, categorizing the segmented tumor into distinct types. Our experiments demonstrate the superior performance of our proposed ConvNet-ResNeXt101 model compared to existing approaches, achieving an accuracy of 99.27% for the tumor core class with a minimum learning elapsed time of 0.53 s.
Project description:Transformed plasma cells in multiple myeloma (MM) are susceptible to natural killer (NK) cell-mediated killing via engagement of tumor ligands for NK activating receptors or "missing-self" recognition. Similar to other cancers, MM targets may elude NK cell immunosurveillance by reprogramming tumor microenvironment and editing cell surface antigen repertoire. Along disease continuum, these effects collectively result in a progressive decline of NK cell immunity, a phenomenon increasingly recognized as a critical determinant of MM progression. In recent years, unprecedented efforts in drug development and experimental research have brought about emergence of novel therapeutic interventions with the potential to override MM-induced NK cell immunosuppression. These NK-cell enhancing treatment strategies may be identified in two major groups: (1) immunomodulatory biologics and small molecules, namely, immune checkpoint inhibitors, therapeutic antibodies, lenalidomide, and indoleamine 2,3-dioxygenase inhibitors and (2) NK cell therapy, namely, adoptive transfer of unmanipulated and chimeric antigen receptor-engineered NK cells. Here, we summarize the mechanisms responsible for NK cell functional suppression in the context of cancer and, specifically, myeloma. Subsequently, contemporary strategies potentially able to reverse NK dysfunction in MM are discussed.
Project description:Natural killer (NK) cells are innate immune cells with the ability to identify and eliminate transformed cells. However, within tumors, many studies have described NK cells as non-functional. The developmental stage of tumor-associated NK cells and how this may relate to functionality has not been explored. We examined the developmental state of NK cells from polyoma middle T antigen (pyMT) transgenic mouse (MMTV-pMT) breast tumors. In pyMT tumors, NK cells were immature as evidenced by their decreased expression of DX5 and their CD27(low)CD11b(low) phenotype. These immature NK cells also had increased expression of NKG2A and expressed low levels of NKp46, perforin, and granzyme B. In contrast, splenic NK cells isolated from the same mice maintained their maturity and their expression of activation markers. To delineate whether the tumor microenvironment directly alters NK cells, we adoptively transferred labeled NK cells and followed their activation status in both the spleen and the tumor. NK cells that arrived at the tumor had half the expression of NKp46 within three days of transfer in comparison to those which arrived at the spleen. In an effort to modify the tumor microenvironment and assess the plasticity of intratumoral NK cells, we treated pyMT tumors with IL-12 and anti-TGF-β. After one week of treatment, the maturity of tumor-associated NK cells was increased; thus, indicating that these cells possess the ability to mature and become activated. A better understanding of how NK cells are modified by the tumor microenvironment will help to develop strategies aimed at bolstering immune responses against tumors.
Project description:The emergence of immunotherapy for cancer treatment bears considerable clinical promise. Nevertheless, many patients remain unresponsive, acquire resistance, or suffer dose-limiting toxicities. Immune-editing of tumors assists their escape from the immune system, and the tumor microenvironment (TME) induces immune suppression through multiple mechanisms. Immunotherapy aims to bolster the activity of immune cells against cancer by targeting these suppressive immunomodulatory processes. Natural Killer (NK) cells are a heterogeneous subset of immune cells, which express a diverse array of activating and inhibitory germline-encoded receptors, and are thus capable of directly targeting and killing cancer cells without the need for MHC specificity. Furthermore, they play a critical role in triggering the adaptive immune response. Enhancing the function of NK cells in the context of cancer is therefore a promising avenue for immunotherapy. Different NK-based therapies have been evaluated in clinical trials, and some have demonstrated clinical benefits, especially in the context of hematological malignancies. Solid tumors remain much more difficult to treat, and the time point and means of intervention of current NK-based treatments still require optimization to achieve long term effects. Here, we review recently described mechanisms of cancer evasion from NK cell immune surveillance, and the therapeutic approaches that aim to potentiate NK function. Specific focus is placed on the use of specialized monoclonal antibodies against moieties on the cancer cell, or on both the tumor and the NK cell. In addition, we highlight newly identified mechanisms that inhibit NK cell activity in the TME, and describe how biochemical modifications of the TME can synergize with current treatments and increase susceptibility to NK cell activity.
Project description:Immunotherapy has transformed cancer treatment by promoting durable clinical responses in a proportion of patients; however, treatment still fails in many patients. Innate immune cells play a key role in the response to immunotherapy. Crosstalk between innate and adaptive immune systems drives T-cell activation but also limits immunotherapy response, as myeloid cells are commonly associated with resistance. Hence, innate cells have both negative and positive effects within the tumor microenvironment (TME), and despite investment in early clinical trials targeting innate cells, they have seen limited success. Suppressive myeloid cells facilitate metastasis and immunotherapy resistance through TME remodeling and inhibition of adaptive immune cells. Natural killer (NK) cells, in contrast, secrete inflammatory cytokines and directly kill transformed cells, playing a key immunosurveillance role in early tumor development. Myeloid and NK cells show reciprocal crosstalk, influencing myeloid cell functional status or antigen presentation and NK effector function, respectively. Crosstalk between myeloid cells and the NK immune network in the TME is especially important in the context of therapeutic intervention. Here we discuss how myeloid and NK cell interactions shape anti-tumor responses by influencing an immunosuppressive TME and how this may influence outcomes of treatment strategies involving drugs that target myeloid and NK cells.