Factors associated with longer survival among older medicare patients after diagnosis of supratentorial primary brain malignancies: a retrospective cohort study.

OBJECTIVES: Despite recent advances, the prognosis for primary malignant brain tumors (PMBTs) remains poor. Some commonly prescribed medications may exhibit anti-tumor properties in various cancers, and neurodegenerative diseases may activate pathways that counteract gliomagenesis. Our study is focused on determining if there is a correlation between the use of metformin, beta-blockers, angiotensin converting enzyme inhibitors (ACEIs), and angiotensin receptor blockers (ARBs), or the presence of Parkinson's disease (PD), and the survival rates following a diagnosis of a PMBT. METHODS: This analysis of the 100% Texas Medicare Database identified patients aged 66+ years diagnosed with a supratentorial PMBT from 2014-2017. Cox proportional hazards regression was employed to analyze survival following diagnosis and associations of survival with surgical intervention, radiation, PD diagnosis, and prescription of metformin, beta-blockers, ACEIs, or ARBs. RESULTS: There were 1,943 patients who met study criteria, and the median age was 74 years. When medication utilization was stratified by none, pre-diagnosis only, post-diagnosis only, or both pre- and post-diagnosis (continuous), continuous utilization of metformin, beta-blockers, ACEIs, or ARBs was associated with prolonged survival compared to no utilization (hazard ratio [HR]:0.45, 95% CI:0.33-0.62; HR:0.71. 95% CI:0.59-0.86; HR:0.59, 95% CI:0.48-0.72; and HR:0.45, 95% CI:0.35-0.58 respectively). PD was also associated with longer survival (HR:0.59-0.63 across the four models). DISCUSSION: Our study suggests that metformin, beta-blockers, ACEIs, ARBs, and comorbid PD are associated with a survival benefit among geriatric Medicare patients with supratentorial PMBTs.

Neurosurgery at Baylor Scott & White Health: Recent History and a Decade of Neurosurgery Residency Training.

Neurosurgery at Baylor Scott & White Memorial Hospital in Temple, Texas began as a division in the Department of Surgery many decades ago. The hospital has long served as the flagship tertiary referral center for the Baylor Scott & White healthcare system, which merged in 2013 with Baylor University Medical Center, a hospital system based in Dallas. It is now the largest non-profit hospital system as well as the most awarded hospital system by the US News and World Report within the state of Texas. The Department of Neurosurgery was established at Baylor Scott & White Memorial Hospital in the 2006-2007 academic year. Between then and 2014, four neurosurgeons served as department chair or interim chair: Dr. Robert Buchanan, Dr. Gerhard Friehs, Dr. Ibrahim El Nihum, and Dr. David Garrett Jr. In 2014, Dr. Jason Huang was appointed chairman after a national search and established the neurosurgery residency program in 2015. The department has undergone tremendous growth under the leadership of Dr. Huang, and the residency program is a priority of the department. Surgical excellence is honed at primarily three campuses: Baylor Scott & White Memorial Hospital, Baylor Scott & White McLane Children's Medical Center, and Baylor Scott & White Medical Center - Hillcrest. In this editorial, we provide a brief history of the institution, a recent history of the neurosurgical presence at Baylor Scott & White Memorial Hospital in Temple, Texas, and briefly describe the program's future directions under the continued leadership of Dr. Jason Huang.

Astrocytic calcium waves: unveiling their roles in sleep and arousal modulation.

Neuron-astrocyte interactions are vital for the brain's connectome. Understanding astrocyte activities is crucial for comprehending the complex neural network, particularly the population-level functions of neurons in different cortical states and associated behaviors in mammals. Studies on animal sleep and wakefulness have revealed distinct cortical synchrony patterns between neurons. Astrocytes, outnumbering neurons by nearly fivefold, support and regulate neuronal and synaptic function. Recent research on astrocyte activation during cortical state transitions has emphasized the influence of norepinephrine as a neurotransmitter and calcium waves as key components of ion channel signaling. This summary focuses on a few recent studies investigating astrocyte-neuron interactions in mouse models during sleep, wakefulness, and arousal levels, exploring the involvement of noradrenaline signaling, ion channels, and glutamatergic signaling in different cortical states. These findings highlight the significant impact of astrocytes on large-scale neuronal networks, influencing brain activity and responsiveness. Targeting astrocytic signaling pathways shows promise for treating sleep disorders and arousal dysregulation. More research is needed to understand astrocytic calcium signaling in different brain regions and its implications for dysregulated brain states, requiring future human studies to comprehensively investigate neuron-astrocyte interactions and pave the way for therapeutic interventions in sleep- and arousal-related disorders.

Polyphyllin VII induces CTC anoikis to inhibit lung cancer metastasis through EGFR pathway regulation.

Circulating tumor cells (CTCs) are cells that detach from the primary tumor and enter the bloodstream, playing a crucial role in the metastasis of lung cancer. Unfortunately, there is currently a lack of drugs specifically designed to target CTCs and prevent tumor metastasis. In this study, we present evidence that polyphyllin VII, a potent anticancer compound, effectively inhibits the metastasis of lung cancer by inducing a process called anoikis in CTCs. We observed that polyphyllin VII had significant cytotoxicity and inhibited colony formation, migration, and invasion in both our newly established cell line CTC-TJH-01 and a commercial lung cancer cell line H1975. Furthermore, we found that polyphyllin VII induced anoikis and downregulated the TrkB and EGFR-MEK/ERK signaling pathways. Moreover, activation of TrkB protein did not reverse the inhibitory effect of polyphyllin VII on CTCs, while upregulation of EGFR protein effectively reversed it. Furthermore, our immunodeficient mouse models recapitulated that polyphyllin VII inhibited lung metastasis, which was associated with downregulation of the EGFR protein, and reduced the number of CTCs disseminated into the lungs by inducing anoikis. Together, these results suggest that polyphyllin VII may be a promising compound for the treatment of lung cancer metastasis by targeting CTCs.

Identification of exosome protein panels as predictive biomarkers for non-small cell lung cancer.

BACKGROUND: Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related deaths worldwide, primarily due to its propensity for metastasis. Patients diagnosed with localized primary cancer have higher survival rates than those with metastasis. Thus, it is imperative to discover biomarkers for the early detection of NSCLC and the timely prediction of tumor metastasis to improve patient outcomes. METHODS: Here, we utilized an integrated approach to isolate and characterize plasma exosomes from NSCLC patients as well as healthy individuals. We then conducted proteomics analysis and parallel reaction monitoring to identify and validate the top-ranked proteins of plasma exosomes. RESULTS: Our study revealed that the proteome in exosomes from NSCLC patients with metastasis was distinctly different from that from healthy individuals. The former had larger diameters and lower concentrations of exosomes than the latter. Furthermore, among the 1220 identified exosomal proteins, we identified two distinct panels of biomarkers. The first panel of biomarkers (FGB, FGG, and VWF) showed potential for early NSCLC diagnosis and demonstrated a direct correlation with the survival duration of NSCLC patients. The second panel of biomarkers (CFHR5, C9, and MBL2) emerged as potential biomarkers for assessing NSCLC metastasis, of which CFHR5 alone was significantly associated with the overall survival of NSCLC patients. CONCLUSIONS: These findings underscore the potential of plasma exosomal biomarkers for early NSCLC diagnosis and metastasis prediction. Notably, CFHR5 stands out as a promising prognostic indicator for NSCLC patients. The clinical utility of exosomal biomarkers offers the potential to enhance the management of NSCLC.

Identification of new aptamer BC-3 targeting RPS7 from rapid screening for bladder carcinoma.

Aptamers, short single DNA or RNA oligonucleotides, have shown immense application potential as molecular probes for the early diagnosis and therapy of cancer. However, conventional cell-SELEX technologies for aptamer discovery are time-consuming and laborious. Here we discovered a new aptamer BC-3 by using an improved rapid X-Aptamer selection process for human bladder carcinoma, for which there is no specific molecular probe yet. We show that BC-3 exhibited excellent affinity in bladder cancer cells but not normal cells. We demonstrate that BC-3 displayed high selectivity for tumor cells over their normal counterparts in vitro, in mice, and in patient tumor tissue specimens. Further endocytosis pathway analysis revealed that BC-3 internalized into bladder cancer cells via clathrin-mediated endocytosis. Importantly, we identified ribosomal protein S7 (RPS7) as the binding target of BC-3 via an integrated methodology (mass spectrometry, colocalization assay, and immunoblotting). Together, we report that a novel aptamer BC-3 is discovered for bladder cancer and its properties in the disease are unearthed. Our findings will facilitate the discovery of novel diagnostic and therapeutic strategies for bladder cancer.

A Non-G-Quadruplex DNA Aptamer Targeting NCL for Diagnosis and Therapy in Bladder Cancer.

Bladder cancer (BC) is a highly aggressive malignant tumor affecting the urinary system, characterized by metastasis and a poor prognosis that often leads to limited therapeutic success. This study aims to develop a novel DNA aptamer for the diagnosis and treatment of BC using a tissue-based systematic evolution of ligands by an exponential enrichment (SELEX) process. By using SELEX, this work successfully generates a new aptamer named TB-5, which demonstrates a remarkable and specific affinity for nucleolin (NCL) in BC tissues and displays marked biocompatibility both in vitro and in vivo. Additionally, this work shows that NCL is a reliable tissue-specific biomarker in BC. Moreover, according to circular dichroism spectroscopy, TB-5 forms a non-G-quadruplex structure, distinguishing it from the current NCL-targeting aptamer AS1411, and exhibits a distinct binding region on NCL compared to AS1411. Notably, this study further reveals that TB-5 activates NCL function by promoting autophagy and suppressing the migration and invasion of BC cells, which occurs by disrupting mRNA transcription processes. These findings highlight the critical role of NCL in the pathological examination of BC and warrant more comprehensive investigations on anti-NCL aptamers in BC imaging and treatment.

Targeting tumor endothelial cells with methyltransferase inhibitors: Mechanisms of action and the potential of combination therapy.

Tumor endothelial cells (TECs) reside in the inner lining of blood vessels and represent a promising target for targeted cancer therapy. DNA methylation is a chemical process that involves the transfer of a methyl group to a specific base in the DNA strand, catalyzed by a DNA methyltransferase (DNMT). DNMT inhibitors (DNMTis) can inhibit the activity of DNMTs, thereby preventing the transfer of methyl groups from s-adenosyl methionine (SAM) to cytosine. Currently, the most viable therapy for TECs is the development of DNMTis to release cancer suppressor genes from their repressed state. In this review, we first outline the characteristics of TECs and describe the development of tumor blood vessels and TECs. Abnormal DNA methylation is closely linked to tumor initiation, progression, and cell carcinogenesis, as evidenced by numerous studies. Therefore, we summarize the role of DNA methylation and DNA methyltransferase and the therapeutic potential of four types of DNMTi in targeting TECs. Finally, we discuss the accomplishments, challenges, and opportunities associated with combination therapy with DNMTis for TECs.

Distinct astrocytic modulatory roles in sensory transmission during sleep, wakefulness, and arousal states in freely moving mice.

Despite extensive research on astrocytic Ca2+ in synaptic transmission, its contribution to the modulation of sensory transmission during different brain states remains largely unknown. Here, by using two-photon microscopy and whole-cell recordings, we show two distinct astrocytic Ca2+ signals in the murine barrel cortex: a small, long-lasting Ca2+ increase during sleep and a large, widespread but short-lasting Ca2+ spike when aroused. The large Ca2+ wave in aroused mice was inositol trisphosphate (IP3)-dependent, evoked by the locus coeruleus-norepinephrine system, and enhanced sensory input, contributing to reliable sensory transmission. However, the small Ca2+ transient was IP3-independent and contributed to decreased extracellular K+, hyperpolarization of the neurons, and suppression of sensory transmission. These events respond to different pharmacological inputs and contribute to distinct sleep and arousal functions by modulating the efficacy of sensory transmission. Together, our data demonstrate an important function for astrocytes in sleep and arousal states via astrocytic Ca2+ waves.

AI-DrugNet: A network-based deep learning model for drug repurposing and combination therapy in neurological disorders.

Discovering effective therapies is difficult for neurological and developmental disorders in that disease progression is often associated with a complex and interactive mechanism. Over the past few decades, few drugs have been identified for treating Alzheimer's disease (AD), especially for impacting the causes of cell death in AD. Although drug repurposing is gaining more success in developing therapeutic efficacy for complex diseases such as common cancer, the complications behind AD require further study. Here, we developed a novel prediction framework based on deep learning to identify potential repurposed drug therapies for AD, and more importantly, our framework is broadly applicable and may generalize to identifying potential drug combinations in other diseases. Our prediction framework is as follows: we first built a drug-target pair (DTP) network based on multiple drug features and target features, as well as the associations between DTP nodes where drug-target pairs are the DTP nodes and the associations between DTP nodes are represented as the edges in the AD disease network; furthermore, we incorporated the drug-target feature from the DTP network and the relationship information between drug-drug, target-target, drug-target within and outside of drug-target pairs, representing each drug-combination as a quartet to generate corresponding integrated features; finally, we developed an AI-based Drug discovery Network (AI-DrugNet), which exhibits robust predictive performance. The implementation of our network model help identify potential repurposed and combination drug options that may serve to treat AD and other diseases.

AD-Syn-Net: systematic identification of Alzheimer's disease-associated mutation and co-mutation vulnerabilities via deep learning.

Alzheimer's disease (AD) is one of the most challenging neurodegenerative diseases because of its complicated and progressive mechanisms, and multiple risk factors. Increasing research evidence demonstrates that genetics may be a key factor responsible for the occurrence of the disease. Although previous reports identified quite a few AD-associated genes, they were mostly limited owing to patient sample size and selection bias. There is a lack of comprehensive research aimed to identify AD-associated risk mutations systematically. To address this challenge, we hereby construct a large-scale AD mutation and co-mutation framework ('AD-Syn-Net'), and propose deep learning models named Deep-SMCI and Deep-CMCI configured with fully connected layers that are capable of predicting cognitive impairment of subjects effectively based on genetic mutation and co-mutation profiles. Next, we apply the customized frameworks to data sets to evaluate the importance scores of the mutations and identified mutation effectors and co-mutation combination vulnerabilities contributing to cognitive impairment. Furthermore, we evaluate the influence of mutation pairs on the network architecture to dissect the genetic organization of AD and identify novel co-mutations that could be responsible for dementia, laying a solid foundation for proposing future targeted therapy for AD precision medicine. Our deep learning model codes are available open access here: https://github.com/Pan-Bio/AD-mutation-effectors.

Transcriptomic analyses of patient peripheral blood with hemoglobin depletion reveal glioblastoma biomarkers.

Peripheral blood is gaining prominence as a noninvasive alternative to tissue biopsy to develop biomarkers for glioblastoma (GBM); however, widely utilized blood-based biomarkers in clinical settings have not yet been identified due to the lack of a robust detection approach. Here, we describe the application of globin reduction in RNA sequencing of whole blood (i.e., WBGR) and perform transcriptomic analysis to identify GBM-associated transcriptomic changes. By using WBGR, we improved the detection sensitivity of informatic reads and identified differential gene expression in GBM blood. By analyzing tumor tissues, we identified transcriptomic traits of GBM blood. Further functional enrichment analyses retained the most changed genes in GBM. Subsequent validation elicited a 10-gene panel covering mRNA, long noncoding RNA, and microRNA (i.e., GBM-Dx panel) that has translational potential to aid in the early detection or clinical management of GBM. Here, we report an integrated approach, WBGR, with comprehensive analytic capacity for blood-based marker identification.

Assessment and prediction of glioblastoma therapy response: challenges and opportunities.

Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.

Landscape of MicroRNA Regulatory Network Architecture and Functional Rerouting in Cancer.

Somatic mutations are a major source of cancer development, and many driver mutations have been identified in protein coding regions. However, the function of mutations located in miRNA and their target binding sites throughout the human genome remains largely unknown. Here, we built detailed cancer-specific miRNA regulatory networks across 30 cancer types to systematically analyze the effect of mutations in miRNAs and their target sites in 3' untranslated region (3' UTR), coding sequence (CDS), and 5' UTR regions. A total of 3,518,261 mutations from 9,819 samples were mapped to miRNA-gene interactions (mGI). Mutations in miRNAs showed a mutually exclusive pattern with mutations in their target genes in almost all cancer types. A linear regression method identified 148 candidate driver mutations that can significantly perturb miRNA regulatory networks. Driver mutations in 3'UTRs played their roles by altering RNA binding energy and the expression of target genes. Finally, mutated driver gene targets in 3' UTRs were significantly downregulated in cancer and functioned as tumor suppressors during cancer progression, suggesting potential miRNA candidates with significant clinical implications. A user-friendly, open-access web portal (mGI-map) was developed to facilitate further use of this data resource. Together, these results will facilitate novel noncoding biomarker identification and therapeutic drug design targeting the miRNA regulatory networks. SIGNIFICANCE: A detailed miRNA-gene interaction map reveals extensive miRNA-mediated gene regulatory networks with mutation-induced perturbations across multiple cancers, serving as a resource for noncoding biomarker discovery and drug development.

Identification of BAG5 as a Potential Biomarker for Parkinson's Disease Patients With R492X PINK1 Mutation.

Parkinson's disease (PD) is a degenerative, progressive nervous system disorder with an unknown cause. PINK1 [phosphatase and tensin homolog deleted on chromosome 10 (PTEN)-induced putative kinase 1] causative mutations R492X may cause autosomal recessive early-onset parkinsonism. In this study, we utilized patient samples and cell line system to investigate roles of Bcl2-associated athanogene 5 (BAG5) in PD patients with R492X PINK1 mutation. We show that the expression levels of BAG5 in the skin tissues from PD patients with R492X PINK1 mutation are markedly lower than those from the healthy control subjects in a small cohort of patients, which has not been recognized before. In addition, we demonstrate that BAG5 physically binds to R492X mutated PINK1 protein. Furthermore, we reveal that BAG5 promotes the degradation of R492X mutated PINK1 protein via ubiquitin/proteasome-dependent pathway, suggesting that decreased level of BAG5 may lead to R492X mutated PINK1 protein accumulation. These findings suggest that BAG5 may serve as an early detection biomarker for PD patients with R492X PINK1 mutation and provide important new insights on how BAG5 affects R492X mutated PINK1 protein, highlighting therapeutic targets for this disease.

Clinical Investigations of CAR-T Cell Therapy for Solid Tumors.

Cell therapy is a distinguished targeted immunotherapy with great potential to treat solid tumors in the new era of cancer treatment. Cell therapy products include genetically engineered cell products and non-genetically engineered cell products. Several recent cell therapies, especially chimeric antigen receptor (CAR)-T cell therapies, have been approved as novel treatment strategies for cancer. Many clinical trials on cell therapies, in the form of cell therapy alone or in combination with other treatments, in solid tumors, have been conducted or ongoing. However, there are still challenges since adverse events and the limited efficacy of cell therapies have also been observed. Here, we concisely summarize the clinical milestones of the conducted and ongoing clinical trials of cell therapy, introduce the evolution of CARs, discuss the challenges and limitations of these therapeutic modalities taking CAR-T as the main focus, and analyze the disparities in the regulatory policies in different countries.

Transcranial near-infrared light in treatment of neurodegenerative diseases.

Light is a natural agent consisting of a range of visible and invisible electromagnetic spectrum travels in waves. Near-infrared (NIR) light refers to wavelengths from 800 to 2,500 nm. It is an invisible spectrum to naked eyes and can penetrate through soft and hard tissues into deep structures of the human body at specific wavelengths. NIR light may carry different energy levels depending on the intensity of emitted light and therapeutic spectrum (wavelength). Stimulation with NIR light can activate intracellular cascades of biochemical reactions with local short- and long-term positive effects. These properties of NIR light are employed in photobiomodulation (PBM) therapy, have been linked to treating several brain pathologies, and are attracting more scientific attention in biomedicine. Transcranial brain stimulations with NIR light PBM in recent animal and human studies revealed a positive impact of treatment on the progression and improvement of neurodegenerative processes, management of brain energy metabolism, and regulation of chronic brain inflammation associated with various conditions, including traumatic brain injury. This scientific overview incorporates the most recent cellular and functional findings in PBM with NIR light in treating neurodegenerative diseases, presents the discussion of the proposed mechanisms of action, and describes the benefits of this treatment in neuroprotection, cell preservation/detoxification, anti-inflammatory properties, and regulation of brain energy metabolism. This review will also discuss the novel aspects and pathophysiological role of the glymphatic and brain lymphatics system in treating neurodegenerative diseases with NIR light stimulations. Scientific evidence presented in this overview will support a combined effort in the scientific community to increase attention to the understudied NIR light area of research as a natural agent in the treatment of neurodegenerative diseases to promote more research and raise awareness of PBM in the treatment of brain disorders.