Lower-Grade Gliomas: Predicting DNA Methylation Subtyping and its Consequences on Survival with MR Features
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The domestic dog, Canis familiaris, is quickly gaining traction as an advantageous model for use in the study of cancer, one of the leading causes of death worldwide. Naturally occurring canine cancers share clinical, histological, and molecular characteristics with the corresponding human diseases. In this study, we take a deep-learning approach to test how similar the gene expression profile of canine glioma and bladder cancer (BLCA) tumors are to the corresponding human tumors. We likewise develop a tool for identifying misclassified or outlier samples in large canine oncological datasets, analogous to that which was developed for human datasets. We test a number of machine learning algorithms and found that a convolutional neural network outperformed logistic regression and random forest approaches. We use a recently developed RNA-seq-based convolutional neural network, TULIP, to test the robustness of a human-data-trained primary tumor classification tool on cross-species primary tumor prediction. Our study ultimately highlights the molecular similarities between canine and human BLCA and glioma tumors, showing that protein-coding one-to-one homologs shared between humans and canines, are sufficient to distinguish between BLCA and gliomas. The results of this study indicate that using protein-coding one-to-one homologs as the features in the input layer of TULIP performs good primary tumor prediction in both humans and canines. Furthermore, our analysis shows that our selected features also contain the majority of features with known clinical relevance in BLCA and gliomas. Our success in using a human-data-trained model for cross-species primary tumor prediction also sheds light on the conservation of oncological pathways in humans and canines, further underscoring the importance of the canine model system in the study of human disease.
Abstract For over a century, neuroscientists have been working toward parcellating the human cortex into distinct neurobiological regions. Modern technologies offer many parcellation methods for healthy cortices acquired through magnetic resonance imaging. However, these methods are suboptimal for personalized neurosurgical application given that pathology and resection distort the cerebrum. We sought to overcome this problem by developing a novel connectivity‐based parcellation approach that can be applied at the single‐subject level. Utilizing normative diffusion data, we first developed a machine‐learning (ML) classifier to learn the typical structural connectivity patterns of healthy subjects. Specifically, the Glasser HCP atlas was utilized as a prior to calculate the streamline connectivity between each voxel and each parcel of the atlas. Using the resultant feature vector, we determined the parcel identity of each voxel in neurosurgical patients ( n = 40) and thereby iteratively adjusted the prior. This approach enabled us to create patient‐specific maps independent of brain shape and pathological distortion. The supervised ML classifier re‐parcellated an average of 2.65% of cortical voxels across a healthy dataset ( n = 178) and an average of 5.5% in neurosurgical patients. Our patient dataset consisted of subjects with supratentorial infiltrating gliomas operated on by the senior author who then assessed the validity and practical utility of the re‐parcellated diffusion data. We demonstrate a rapid and effective ML parcellation approach to parcellation of the human cortex during anatomical distortion. Our approach overcomes limitations of indiscriminately applying atlas‐based registration from healthy subjects by employing a voxel‐wise connectivity approach based on individual data.
Electric field (EF) directed cell migration (electrotaxis) is known to occur in glioblastoma multiforme (GBM) and neural stem cells, with key signalling pathways frequently dysregulated in GBM. One such pathway is EGFR/PI3K/Akt, which is down-regulated by peroxisome proliferator activated receptor gamma (PPARγ) agonists. We investigated the effect of electric fields on primary differentiated and glioma stem cell (GSCs) migration, finding opposing preferences for anodal and cathodal migration, respectively. We next sought to determine whether chemically disrupting Akt through PTEN upregulation with the PPARγ agonist, pioglitazone, would modulate electrotaxis of these cells. We found that directed cell migration was significantly inhibited with the addition of pioglitazone in both differentiated GBM and GSCs subtypes. Western blot analysis did not demonstrate any change in PPARγ expression with and without exposure to EF. In summary we demonstrate opposing EF responses in primary GBM differentiated cells and GSCs can be inhibited chemically by pioglitazone, implicating GBM EF modulation as a potential target in preventing tumour recurrence.
Highlights: • Human astrocytes increase traction forces of cells applied to the ECM in response to increased substrate stiffness. • Astrocytes apply intercellular stresses with noticeable increase in higher substrate stiffness. • Cell velocity decreases in human astrocytes in brain tumor like environment compared to normal brain environment. • Astrocytes mechanical strength and function could be potentially enhanced by increased stiffness of the microenvironment. Astrocytes are essential to brain homeostasis and their dysfunction can have devastating consequences on human quality of life. Such deleterious effects are generally due in part to changes that occur at the cellular level, which may be biochemical or biomechanical in nature. One biomechanical change that can occur is a change in tissue stiffness. Brain tumors are generally associated with increased brain tissue stiffness, but the impact increased tissue stiffness has on astrocyte biomechanical behavior is poorly understood. Therefore, in this study we cultured human astrocytes on flexible substrates with stiffness that mimicked the healthy human brain (1 kPa), meningioma (4 kPa), and glioma (11 kPa) and investigated astrocyte biomechanical behavior by measuring cell-substrate tractions, strain energies, cell-cell intercellular stresses, and cellular velocities. In general, tractions, intercellular stresses, and strain energy was observed to increase as a function of increased substrate stiffness, while cell velocities were observed to decrease with increased substrate stiffness. We believe this study will be of great importance to the fields of brain pathology and brain physiology.
Abstract Background Tumor hypoxia is a characteristic of paramount importance due to low oxygenation levels in tissue negatively correlating with resistance to traditional therapies. The ability to noninvasively identify such could provide for personalized treatment(s) and enhance survival rates. Accordingly, we recently developed an NIR fluorescent hypoxia‐sensitive smart probe ( NO 2 ‐Rosol ) for identifying hypoxia via selectively imaging nitroreductase (NTR) activity, which could correlate to oxygen deprivation levels in cells, thereby serving as a proxy. We demonstrated proof of concept by subjecting a glioblastoma (GBM) cell line to extreme stress by evaluating such under radiobiological hypoxic ( p O 2 ≤ ~0.5%) conditions, which is a far cry from representative levels for hypoxia for brain glioma ( p O 2 = ~1.7%) which fluctuate little from physiological hypoxic ( p O 2 = 1.0‐3.0%) conditions. Aim We aimed to evaluate the robustness, suitability, and feasibility of NO 2 ‐Rosol for imaging hypoxia in vitro and in vivo via assessing NTR activity in diverse GBM models under relevant oxygenation levels ( p O 2 = 2.0%) within physiological hypoxic conditions that mimic oxygenation levels in GBM tumor tissue in the brain. Methods We evaluated multiple GBM cell lines to determine their relative sensitivity to oxygenation levels via measuring carbonic anhydrase IX (CAIX) levels, which is a surrogate marker for indirectly identifying hypoxia by reporting on oxygen deprivation levels and upregulated NTR activity. We evaluated for hypoxia via measuring NTR activity when employing NO 2 ‐Rosol in in vitro and tumor hypoxia imaging studies in vivo. Results The GBM39 cell line demonstrated the highest CAIX expression under hypoxic conditions representing that of GBM in the brain. NO 2 ‐Rosol displayed an 8‐fold fluorescence enhancement when evaluated in GBM39 cells ( p O 2 = 2.0%), thereby establishing its robustness and suitability for imaging hypoxia under relevant physiological conditions. We demonstrated the feasibility of NO 2 ‐Rosol to afford tumor hypoxia imaging in vivo via it demonstrating a tumor‐to‐background of 5 upon (i) diffusion throughout, (ii) bioreductive activation by NTR activity in, and (iii) retention within, GBM39 tumor tissue. Conclusion We established the robustness, suitability, and feasibility of NO 2 ‐Rosol for imaging hypoxia under relevant oxygenation levels in vitro and in vivo via assessing NTR activity in GBM39 models.
Activin receptor type 1 (ACVR1; ALK2) and activin receptor like type 1 (ACVRL1; ALK1) are transforming growth factor beta family receptors that integrate extracellular signals of bone morphogenic proteins (BMPs) and activins into Mothers Against Decapentaplegic homolog 1/5 (SMAD1/SMAD5) signaling complexes. Several activating mutations in ALK2 are implicated in fibrodysplasia ossificans progressiva (FOP), diffuse intrinsic pontine gliomas, and ependymomas. The ALK2 R206H mutation is also present in a subset of endometrial tumors, melanomas, non-small lung cancers, and colorectal cancers, and ALK2 expression is elevated in pancreatic cancer. Using DNA-encoded chemistry technology, we screened 3.94 billion unique compounds from our diverse DNA-encoded chemical libraries (DECLs) against the kinase domain of ALK2. Off-DNA synthesis of DECL hits and biochemical validation revealed nanomolar potent ALK2 inhibitors. Further structure-activity relationship studies yielded center for drug discovery (CDD)-2789, a potent [NanoBRET (NB) cell IC50: 0.54 μM] and metabolically stable analog with good pharmacological profile. Crystal structures of ALK2 bound with CDD-2281, CDD-2282, or CDD-2789 show that these inhibitors bind the active site through Van der Waals interactions and solvent-mediated hydrogen bonds. CDD-2789 exhibits high selectivity toward ALK2/ALK1 in KINOMEscan analysis and NB K192 assay. In cell-based studies, ALK2 inhibitors effectively attenuated activin A and BMP-induced Phosphorylated SMAD1/5 activation in fibroblasts from individuals with FOP in a dose-dependent manner. Thus, CDD-2789 is a valuable tool compound for further investigation of the biological functions of ALK2 and ALK1 and the therapeutic potential of specific inhibition of ALK2.
Glioblastoma (GBM) is one of the most difficult cancers to effectively treat, in part because of the lack of precision therapies and limited therapeutic access to intracranial tumor sites due to the presence of the blood-brain and blood-tumor barriers. We have developed a precision medicine approach for GBM treatment that involves the use of brain-penetrant RNA interference–based spherical nucleic acids (SNAs), which consist of gold nanoparticle cores covalently conjugated with radially oriented and densely packed small interfering RNA (siRNA) oligonucleotides. On the basis of previous preclinical evaluation, we conducted toxicology and toxicokinetic studies in nonhuman primates and a single-arm, open-label phase 0 first-in-human trial ( NCT03020017 ) to determine safety, pharmacokinetics, intratumoral accumulation and gene-suppressive activity of systemically administered SNAs carrying siRNA specific for the GBM oncogene Bcl2Like12 (Bcl2L12). Patients with recurrent GBM were treated with intravenous administration of siBcl2L12-SNAs (drug moniker: NU-0129), at a dose corresponding to 1/50th of the no-observed-adverse-event level, followed by tumor resection. Safety assessment revealed no grade 4 or 5 treatment–related toxicities. Inductively coupled plasma mass spectrometry, x-ray fluorescence microscopy, and silver staining of resected GBM tissue demonstrated that intravenously administered SNAs reached patient tumors, with gold enrichment observed in the tumor-associated endothelium, macrophages, and tumor cells. NU-0129 uptake into glioma cells correlated with a reduction in tumor-associated Bcl2L12 protein expression, as indicated by comparison of matched primary tumor and NU-0129–treated recurrent tumor. Our results establish SNA nanoconjugates as a potential brain-penetrant precision medicine approach for the systemic treatment of GBM.
Significant opportunities remain for pharmacologically enhancing the clinical effectiveness of proton and carbon ion-based radiotherapies to achieve both tumor cell radiosensitization and normal tissue radioprotection. We investigated whether pretreatment with the hydroxamate-based histone deacetylase inhibitors (HDACi) SAHA (vorinostat), M344, and PTACH impacts radiation-induced DNA double-strand break (DSB) induction and repair, cell killing, and transformation (acquisition of anchorage-independent growth in soft agar) in human normal and tumor cell lines following gamma ray and light ion irradiation. Treatment of normal NFF28 primary fibroblasts and U2OS osteosarcoma, A549 lung carcinoma, and U87MG glioma cells with 5–10 µM HDACi concentrations 18 h prior to cesium-137 gamma irradiation resulted in radiosensitization measured by clonogenic survival assays and increased levels of colocalized gamma-H2AX/53BP1 foci induction. We similarly tested these HDACi following irradiation with 200 MeV protons, 290 MeV/n carbon ions, and 350 MeV/n oxygen ions delivered in the Bragg plateau region. Unlike uniform gamma ray radiosensitization, effects of HDACi pretreatment were unexpectedly cell type and ion species-dependent with C-12 and O-16 ion irradiations showing enhanced G0/G1-phase fibroblast survival (radioprotection) and in some cases reduced or absent tumor cell radiosensitization. DSB-associated foci levels were similar for proton-irradiated DMSO control and SAHA-treated fibroblast cultures, while lower levels of induced foci were observed in SAHA-pretreated C-12 ion-irradiated fibroblasts. Fibroblast transformation frequencies measured for all radiation types were generally LET-dependent and lowest following proton irradiation; however, both gamma and proton exposures showed hyperlinear transformation induction at low doses (≤25 cGy). HDACi pretreatments led to overall lower transformation frequencies at low doses for all radiation types except O-16 ions but generally led to higher transformation frequencies at higher doses (>50 cGy). The results of these in vitro studies cast doubt on the clinical efficacy of using HDACi as radiosensitizers for light ion-based hadron radiotherapy given the mixed results on their radiosensitization effectiveness and related possibility of increased second cancer induction.
Increased mitotic activity is associated with the genesis and aggressiveness of many cancers. To assess the clinical value of mitotic activity as prognostic biomarker, we performed a pan-cancer study on the mitotic network activity index (MNAI) constructed based on 54-gene mitotic apparatus network. Our pan-cancer assessment on TCGA (33 tumor types, 10,061 patients) and validation on other publicly available cohorts (23 tumor types, 9,209 patients) confirmed the significant association of MNAI with overall survival, progression-free survival, and other prognostic endpoints in multiple cancer types, including lower-grade gliomas (LGG), breast invasive carcinoma (BRCA), as well as many others. We also showed significant association between MNAI and genetic instability, which provides a biological explanation of its prognostic impact at pan-cancer landscape. Our association analysis revealed that patients with high MNAI benefitted more from anti-PD-1 and Anti-CTLA-4 treatment. In addition, we demonstrated that multimodal integration of MNAI and the AI-empowered Cellular Morphometric Subtypes (CMS) significantly improved the predictive power of prognosis compared to using MNAI and CMS alone. Our results suggest that MNAI can be used as a potential prognostic biomarker for different tumor types toward different clinical endpoints, and multimodal integration of MNAI and CMS exceeds individual biomarker for precision prognosis.
In many university and healthcare projects, models are built for very different data types such as tables, institutional time series, and medical images, but they are deployed as separate applications. In this work, that separation made testing and maintenance difficult because each module had its own pipeline and runtime requirements. This paper presents an integrated AI lakehouse-style implementation that runs three model pipelines inside one containerized backend. For medical imaging, we used MRI datasets from IEEE DataPort: a four-class classification set with 7012 images (5708 train/1304 test) and a segmentation set with 3063 image–mask pairs. The classification model (ResNet50 transfer learning) is evaluated using a proper train–validation–test protocol across multiple splits (80/10/10, 70/10/20, 60/10/30, and 10/30/60), achieving a test accuracy of 99.00% under the standard 80/10/10 split. Additionally, a patient-level evaluation is conducted using an external glioma dataset to provide a more realistic assessment without data leakage. The segmentation model (DeepLabV3-ResNet50) achieved 83.09% validation mIoU and 88.79% Dice score. For university KPI forecasting, we used annual IPEDS and NSF HERD data from 2010 to 2023 for three universities (BSU, EOU, and UAB). To examine the effect of preprocessing on forecasting performance, two case studies are conducted. In the first case, linear interpolation is applied to generate semester-level data. In the second case, the original annual data is used directly without interpolation. Random Forest regression and ARIMA models are evaluated using MAE, RMSE, MAPE, and R 2 . The results showed that interpolation improved apparent forecasting performance due to smoothing, while evaluation on the original annual data provided a more realistic assessment of model behavior. To further validate the framework on a larger dataset, an additional case study is conducted using a student dropout dataset. For water potability, we trained and compared multiple tabular classifiers on a large dataset (1,048,575 samples). A Random Forest model (100 trees, max depth 10) achieved 85.86% test accuracy and high recall for unsafe samples (0.8447). All modules are served via FastAPI and deployed together using Docker, with workflow automation routing requests to the correct endpoint. System-level benchmarking indicates that the backend maintains stable throughput and latency under concurrent requests.
Several new techniques are reported for studying cardiovascular circulation in small laboratory animals kept in metabolic chambers. Chronical cannulation, miniaturized membrane type heart-lung machines, a prototype walking chamber, and a fluorocarbon immersion method to simulate weightlessness are outlined. Differential hypothermia work on rat cancers provides localized embedding of radionuclides and other chemotherapeutical agents in tumors and increases at the same time blood circulation through the warmed tumor as compared to the rest of the cold body. Some successful clinical applications of combined chemotherapy and differential hypothermia in skin cancer, mammary tumors, and brain gliomas are described.
Alterations in the neuromuscular junction were observed in rats preceding loss of muscle mass. In view of the possibility that these alterations involve changes in the secretion of myotrophic agents by presynaptic motor neurons, an investigation was undertaken to characterize a neuronall factor which is thought to be involved in the initiation and maintenance of cholinergic synapses. This factor, which is secreted into the incubation medium by NG108-15 neuroblastoma x glioma hybrid cells, induces the aggregation of nicotinic acetylcholine receptors on primary cultures of rat hindlimb myotubes. Previous attempts to purify this factor failed. Extensive washing of the NG108-15 cells with hepes-buffered salt solution followed by short (4 hour) collection times resulted in the collection of incubation medium containing maximal aggregation activity with as little as 5 ug secreted protein per ml of fresh medium. A three-fold increase in specific activity was obtained after anion exchange chromatography.
Cancer cells must secrete proteolytic enzymes to invade adjacent tissues and migrate to a new metastatic site. Urokinase (uPA) is a key enzyme related to metastasis in cancers of the lung, colon, gastric, uterine, breast, brain, and malignant melanoma. A NASA technology utilization project has combined fluorescence microscopy, image analysis, and flow cytometry, using fluorescent dyes, and urokinase-specific antibodies to measure uPA and abnormal DNA levels (related to cancer cell proliferation) inside the cancer cells. The project is focused on developing quantitative measurements to determine if a patient's tumor cells are actively metastasizing. If a significant number of tumor cells contain large amounts of uPA (esp. membrane-bound) then the post-surgical chemotherapy or radiotherapy can be targeted for metastatic cells that have already left the primary tumor. These analytical methods have been applied to a retrospective study of biopsy tissues from 150 node negative, stage 1 breast cancer patients. Cytopathology and image analysis has shown that uPA is present in high levels in many breast cancer cells, but not found in normal breast. Significant amounts of uPA also have been measured in glioma cell lines cultured from brain tumors. Commercial applications include new diagnostic tests for metastatic cells, in different cancers, which are being developed with a company that provides a medical testing service using flow cytometry for DNA analysis and hormone receptors on tumor cells from patient biopsies. This research also may provide the basis for developing a new 'magic bullet' treatment against metastasis using chemotherapeutic drugs or radioisotopes attached to urokinase-specific monoclonal antibodies that will only bind to metastatic cells.
Neuregulins are growth factor domain proteins with diverse bioactivities, such as cell proliferation, receptor binding, and differentiation. Neureguh- 1 binds to two members of the ErbB class I tyrosine kinase receptors, ErbB3 and ErbB4. A number of human cancers overexpress the ErbB receptors, and neuregulin can modulate the growth of certain cancer types. Neuregulin-1 has been shown to promote the migration of invasive gliomas of the central nervous system. Neuregulin has also been implicated in schizophrenia, multiple sclerosis and abortive cardiac abnormalities. The full function of neuregulin-1 is not known. In this study we are inserting a cDNA clone obtained from American Type Culture Collection into E.coli expression vectors to express neuregulin- 1 protein. Metal chelate affinity chromatography is used for recombinant protein purification. Crystallization screening will proceed for X-ray diffraction studies following expression, optimization, and protein purification. In spite of medical and scholarly interest in the neuregulins, there are currently no high-resolution structures available for these proteins. Here we present the first steps toward attaining a high-resolution structure of neuregulin- 1, which will help enable us to better understand its function