A platform-independent AI tumor lineage and site (ATLAS) classifier.

Histopathologic diagnosis and classification of cancer plays a critical role in guiding treatment. Advances in next-generation sequencing have ushered in new complementary molecular frameworks. However, existing approaches do not independently assess both site-of-origin (e.g. prostate) and lineage (e.g. adenocarcinoma) and have minimal validation in metastatic disease, where classification is more difficult. Utilizing gradient-boosted machine learning, we developed ATLAS, a pair of separate AI Tumor Lineage and Site-of-origin models from RNA expression data on 8249 tumor samples. We assessed performance independently in 10,376 total tumor samples, including 1490 metastatic samples, achieving an accuracy of 91.4% for cancer site-of-origin and 97.1% for cancer lineage. High confidence predictions (encompassing the majority of cases) were accurate 98-99% of the time in both localized and remarkably even in metastatic samples. We also identified emergent properties of our lineage scores for tumor types on which the model was never trained (zero-shot learning). Adenocarcinoma/sarcoma lineage scores differentiated epithelioid from biphasic/sarcomatoid mesothelioma. Also, predicted lineage de-differentiation identified neuroendocrine/small cell tumors and was associated with poor outcomes across tumor types. Our platform-independent single-sample approach can be easily translated to existing RNA-seq platforms. ATLAS can complement and guide traditional histopathologic assessment in challenging situations and tumors of unknown primary.

Clonal hematopoiesis is associated with protection from Alzheimer's disease.

Clonal hematopoiesis of indeterminate potential (CHIP) is a premalignant expansion of mutated hematopoietic stem cells. As CHIP-associated mutations are known to alter the development and function of myeloid cells, we hypothesized that CHIP may also be associated with the risk of Alzheimer's disease (AD), a disease in which brain-resident myeloid cells are thought to have a major role. To perform association tests between CHIP and AD dementia, we analyzed blood DNA sequencing data from 1,362 individuals with AD and 4,368 individuals without AD. Individuals with CHIP had a lower risk of AD dementia (meta-analysis odds ratio (OR) = 0.64, P = 3.8 × 10-5), and Mendelian randomization analyses supported a potential causal association. We observed that the same mutations found in blood were also detected in microglia-enriched fraction of the brain in seven of eight CHIP carriers. Single-nucleus chromatin accessibility profiling of brain-derived nuclei in six CHIP carriers revealed that the mutated cells comprised a large proportion of the microglial pool in the samples examined. While additional studies are required to validate the mechanistic findings, these results suggest that CHIP may have a role in attenuating the risk of AD.

ssDNA nanotubes for selective targeting of glioblastoma and delivery of doxorubicin for enhanced survival.

Effective treatment of glioblastoma remains a daunting challenge. One of the major hurdles in the development of therapeutics is their inability to cross the blood-brain tumor barrier (BBTB). Local delivery is an alternative approach that can still suffer from toxicity in the absence of target selectivity. Here, we show that nanotubes formed from self-assembly of ssDNA-amphiphiles are stable in serum and nucleases. After bilateral brain injections, nanotubes show preferential retention by tumors compared to normal brain and are taken up by glioblastoma cells through scavenger receptor binding and macropinocytosis. After intravenous injection, they cross the BBTB and internalize in glioblastoma cells. In a minimal residual disease model, local delivery of doxorubicin showed signs of toxicity in the spleen and liver. In contrast, delivery of doxorubicin by the nanotubes resulted in no systemic toxicity and enhanced mouse survival. Our results demonstrate that ssDNA nanotubes are a promising drug delivery vehicle to glioblastoma.

Machine Learning-Enabled High-Resolution Dynamic Deuterium MR Spectroscopic Imaging.

Deuterium magnetic resonance spectroscopic imaging (DMRSI) has recently been recognized as a potentially powerful tool for noninvasive imaging of brain energy metabolism and tumor. However, the low sensitivity of DMRSI has significantly limited its utility for both research and clinical applications. This work presents a novel machine learning-based method to address this limitation. The proposed method synergistically integrates physics-based subspace modeling and data-driven deep learning for effective denoising, making high-resolution dynamic DMRSI possible. Specifically, a novel subspace model was used to represent the dynamic DMRSI signals; deep neural networks were trained to capture the low-dimensional manifolds of the spectral and temporal distributions of practical dynamic DMRSI data. The learned subspace and manifold structures were integrated via a regularization formulation to remove measurement noise. Theoretical analysis, computer simulations, and in vivo experiments have been conducted to demonstrate the denoising efficacy of the proposed method which enabled high-resolution imaging capability. The translational potential was demonstrated in tumor-bearing rats, where the Warburg effect associated with cancer metabolism and tumor heterogeneity were successfully captured. The new method may not only provide an effective tool to enhance the sensitivity of DMRSI for basic research and clinical applications but also provide a framework for denoising other spatiospectral data.

Zika virus-based immunotherapy enhances long-term survival of rodents with brain tumors through upregulation of memory T-cells.

Zika virus (ZIKV) exhibits a tropism for brain tumor cells and has been used as an oncolytic virus to target brain tumors in mice with modest effects on extending median survival. Recent studies have highlighted the potential for combining virotherapy and immunotherapy to target cancer. We postulated that ZIKV could be used as an adjuvant to enhance the long-term survival of mice with malignant glioblastoma and generate memory T-cells capable of providing long-term immunity against cancer remission. To test this hypothesis mice bearing malignant intracranial GL261 tumors were subcutaneously vaccinated with irradiated GL261 cells previously infected with the ZIKV. Mice also received intracranial injections of live ZIKV, irradiation attenuated ZIKV, or irradiated GL261 cells previously infected with ZIKV. Long-term survivors were rechallenged with a second intracranial tumor to examine their immune response and look for the establishment of protective memory T-cells. Mice with subcutaneous vaccination plus intracranial irradiation attenuated ZIKV or intracranial irradiated GL261 cells previously infected with ZIKV exhibited the greatest extensions to overall survival. Flow cytometry analysis of immune cells within the brains of long-term surviving mice after tumor rechallenge revealed an increase in the number of T-cells, including CD4+ and tissue-resident effector/ effector memory CD4+ T-cells, in comparison to long-term survivors that were mock-rechallenged, and in comparison to naïve untreated mice challenged with intracranial gliomas. These results suggest that ZIKV can serve as an adjuvant to subcutaneous tumor vaccines that enhance long-term survival and generate protective tissue-resident memory CD4+ T-cells.

Efficacy of Cell-Based Therapies for Traumatic Brain Injuries.

Traumatic brain injuries (TBIs) are a leading cause of death and disability. Additionally, growing evidence suggests a link between TBI-induced neuroinflammation and neurodegenerative disorders. Treatments for TBI patients are limited, largely focused on rehabilitation therapy, and ultimately, fail to provide long-term neuroprotective or neurorestorative benefits. Because of the prevalence of TBI and lack of viable treatments, new therapies are needed which can promote neurological recovery. Cell-based treatments are a promising avenue because of their potential to provide multiple therapeutic benefits. Cell-based therapies can promote neuroprotection via modulation of inflammation and promote neurorestoration via induction of angiogenesis and neurogenesis. Neural stem/progenitor cell transplantations have been investigated in preclinical TBI models for their ability to directly contribute to neuroregeneration, form neural-like cells, and improve recovery. Mesenchymal stem cells (MSCs) have been investigated in clinical trials through multiple different routes of administration. Intravenous administration of MSCs appears most promising, demonstrating a robust safety profile, correlation with neurological improvements, and reductions in systemic inflammation following TBI. While still preliminary, evidence suggests cell-based therapies may become a viable treatment for TBI based on their ability to promote neuroregeneration and reduce inflammation.

Efficacy of stem cell-based therapies for stroke.

Stroke remains a prevalent disease with limited treatment options. Available treatments offer little in the way of enhancing neurogenesis and recovery. Because of the limitations of available treatments, new therapies for stroke are needed. Stem cell-based therapies for stroke offer promise because of their potential to provide neurorestorative benefits. Stem cell-based therapies aim to promote neurogenesis and replacement of lost neurons or protect surviving neurons in order to improve neurological recovery. The mechanism through which stem cell treatments mediate their therapeutic effect is largely dependent on the type of stem cell and route of administration. Neural stem cells have been shown in pre-clinical and clinical trials to promote functional recovery when used in intracerebral transplantations. The therapeutic effects of neural stem cells have been attributed to their formation of new neurons and promotion of neuroregeneration. Bone marrow stem cells (BMSC) and mesenchymal stem cells (MSC) have been shown to enhance neurogenesis in pre-clinical models in intracerebral transplantations, but lack clinical evidence to support this therapeutic approach in patients and appear to be less effective than neural stem cells. Intravenous and intra-arterial administration of BMSC and MSC have shown more promise, where their effects are largely mediated through neuroprotective mechanisms. The immune system has been implicated in exacerbating initial damage caused by stroke, and BMSC and MSC have demonstrated immunomodulatory properties capable of dampening post-stroke inflammation and potentially improving recovery. While still in development, stem cell therapies may yield new treatments for stroke which can improve neurological recovery.