Ferroptosis represents an iron-dependent form of cell death characterized by accumulation of lipid peroxides. However, it is largely elusive how authentic lipid metabolites contribute to ferroptosis, and whether this is dysregulated in malignant cells due to metabolic rewiring. Here, we identify fatty acid amide hydrolase (FAAH) as a crucial ferroptosis regulator in lung adenocarcinoma (LUAD). FAAH is upregulated and correlated with poor prognosis of LUAD patients. FAAH overexpression inhibits ferroptosis, whereas FAAH knockdown robustly enhances ferroptosis of LUAD cells. Mechanistically, FAAH promotes the palmitoylation of STAT3 through converting N-palmitoylethanolamine to palmitic acid. Palmitoylated STAT3 undergoes cytomembrane translocation and phosphorylation by JAK2, and transcriptionally activates GPX4 to suppress ferroptosis. Concomitantly, activated STAT3 licenses FAAH transcription, thus forming a positive feedback loop in LUAD cells. FAAH targeting represses tumor growth and boosts the anti-tumor efficacy of cisplatin in vivo. These findings uncover a novel regulatory circuit of ferroptosis driven by a saturated fatty acid, and demonstrate the applicability of targeting FAAH to overcome ferroptosis resistance in LUAD therapy.

TP53 is a well-documented tumor suppressor gene frequently mutated in malignancies. It has been demonstrated that the gain-of-function (GOF) mutation of p53 promotes the development and progression of cancers; however, its extrinsic oncogenic mechanisms are still poorly understood. Herein, we found that the oncogenic effect of mutant p53 in vivo is dependent on the tumor immune microenvironment. Importantly, our data demonstrated a significant increase in PD-L1 expression in cells expressing mutant p53. Consistently, subsequent investigations indicated that PD-L1 mRNA is subject to N6-methyladenosine modification, and that the reader protein YTHDF3 is required for regulating both the stability and translational output of PD-L1 mRNA in the transformed cells. The mechanistic study showed that mut-p53 inhibits the expression of demethyladenosine transferase ALKBH5, resulting in m6A-YTHDF3 mediated upregulation of PD-L1 in cancer cells and the potentiation of the immune evasion program. Furthermore, exogenous expression of ALKBH5 in mut-p53-expressing cells suppresses PD-L1 levels, enhances the antitumor immune response mediated by cytotoxic T lymphocytes (CTLs), and blocks advanced tumor growth in vivo. Thus, our study gives rise to the reasonable strategy that restoration of ALKBH5 activation or inhibition of the m6A modification-YTHDF3 axis could potentially reactivate immune surveillance and eliminate tumors harboring mut-p53.

Fork-head box protein M1 (FOXM1) plays critical roles in development and progression of multiple cancers, including hepatocellular carcinoma (HCC). However, the exact regulatory hierarchy of FOXM1 remains unclear. Here, a genome-wide screen is performed to identify intranuclear proteins that promote FOXM1 transcription activity via liquid–liquid phase separation (LLPS). Abnormal spindle-like microcephaly associated (ASPM) is identified to interact with FOXM1 protein via LLPS and enhance its stability by preventing proteasome-mediated degradation. ChIP-sequencing data show ASPM and FOXM1 co-occupy the promoters of multiple genes to promote their transcription, enhancing FOXM1-driven oncogenic progression. In functional experiments, inhibition of ASPM suppresses tumor growth of HCC cells in vivo and in vitro, while overexpression of ASPM has opposite effects. Importantly, reconstitution of FOXM1 partially compensates for the weakened proliferative capacity of HCC cells caused by ASPM silencing. Intriguingly, FOXM1 binds to the promoter region of ASPM and transcriptionally activates ASPM expression in HCC cells. Furthermore, we find that a higher co-expression of ASPM and FOXM1 significantly correlates with poor prognosis in HCC patients. It indicates a double positive feedback loop between ASPM and FOXM1 which coordinately promotes the aggressive progression of HCC. Collectively, we demonstrate that LLPS and transcriptional regulation form an oncogenic double positive feedback loop between ASPM and FOXM1. This provides a rationale strategy to treat HCC by targeting this mechanism.

The heterogeneous injuries and resulting cognitive deficits pose significant challenges in the clinical management of mild traumatic brain injury (mTBI). However, the pathophysiological mechanisms related to heterogeneities of mTBI are still unclear. This study aims to explore the mechanisms underlying brain remodeling by examining the morphometric similarity (MS) alterations and corresponding transcriptomic signatures across adult and pediatric mTBI (adult mTBI: 112 acute patients, 47 follow-up chronic patients, 66 healthy controls [HCs]; pediatric mTBI: 30 acute patients, 31 HCs). A healthy adult cohort (N = 840) is included to derive the modularized brain MS networks representing interregional cortical connectivity. Subsequently, cortical MS remodeling patterns are identified involving mostly MS increases in the frontal modules with typical high MS and decreases in the occipital module with typical low MS, with more pronounced changes observed in the developing brain with mTBI. The abnormal MS changes are correlated with variable cognitive impairments. Moreover, cortical MS remodeling is also associated with the genes enriched in CA1 pyramidal cells and neuron-specific biological processes. The transcription-related cortical remodeling in mTBI might reveal the disruption of brain cellular architecture. Therapeutic modalities to intervene in specific cortex and tackle CA1 over-activation might better encircle the neurobiology of TBI.

The diagnosis and treatment of gliomas have traditionally been both a research hotspot and a challenge in clinical medicine. Intracranial multiple gliomas are rare, and their diagnosis and treatment are often more difficult than those of solitary gliomas. In this article, we report our experience with the diagnosis and treatment of a case of intracranial multiple glioblastomas that closely resembled metastatic tumors in terms of neuroimaging and anatomy. This case may provide a useful reference and insight into the clinical management of this type of disease.

Traumatic brain injury (TBI), a risk factor for later-life dementia, leads to salient brain atrophy, particularly in the white matter. It is not clear how white matter atrophy progresses or why some brain regions are damaged while others are spared. We hypothesized that spatial variations of cell-specific gene expression contributed to the selective white matter loss vulnerability following mild TBI (mTBI). Gene expression data were sourced from the publicly available Allen Human Brain Atlas, which comprises microarray data spanning nearly the entire brain, derived from six neurologically normal adult donors. A total of 100 patients with acute stage (within 7 days post-injury) mTBI were enrolled. Of these, 60 patients were followed up at 3 months post-injury and 37 were followed up at 6-12 months post-injury. In addition, 59 healthy controls (HCs), matched for age, gender, and education, were included for comparative analysis. White matter volume changes were analyzed at both the acute stage, 3 months, and 6-12 months follow-up in mTBI patients compared with HCs. Patients with mTBI exhibited significant white matter atrophy in the frontal, parietal, and temporal cortices at 3 months post-injury, which even persisted at 6-12 months follow-up. In addition, mTBI patients with cognitive deficits showed more severe brain atrophy compared with those without cognitive deficits. Crucially, the gene expression marking endothelial cells and S1 pyramidal neurons were associated with increased brain atrophy, whereas the gene expression marking microglia and CA1 pyramidal neurons were associated with decreased brain atrophy in mTBI patients at 3 months post-injury. Microglia and endothelial cells can explain 23.6% of regional variations in the white matter atrophy. These findings suggested that modulating cellular activation, especially by promoting microglial activation at 3 months post-injury, might be a promising approach to prevent white matter atrophy, enhance cognitive outcomes, and reduce the risk of later-life dementia.

Aim This study aims to utilize machine learning (ML) and logistic regression (LR) models to predict surgical outcomes among patients with traumatic brain injury (TBI) based on admission examination, assisting in making optimal surgical treatment decision for these patients. Method We conducted a retrospective review of patients hospitalized in our department for moderate-to-severe TBI. Patients admitted between October 2011 and October 2022 were assigned to the training set, while patients admitted between November 2022 and May 2023 were designated as the external validation set. Five ML algorithms and LR model were employed to predict the postoperative Glasgow Outcome Scale (GOS) status at discharge using clinical and routine blood data collected upon admission. The Shapley (SHAP) plot was utilized for interpreting the models. Results A total of 416 patients were included in this study, and they were divided into the training set ( n = 396) and the external validation set ( n = 47). The ML models, using both clinical and routine blood data, were able to predict postoperative GOS outcomes with area under the curve (AUC) values ranging from 0.860 to 0.900 during the internal cross-validation and from 0.801 to 0.890 during the external validation. In contrast, the LR model had the lowest AUC values during the internal and external validation (0.844 and 0.567, respectively). When blood data was not available, the ML models achieved AUCs of 0.849 to 0.870 during the internal cross-validation and 0.714 to 0.861 during the external validation. Similarly, the LR model had the lowest AUC values (0.821 and 0.638, respectively). Through repeated cross-validation analysis, we found that routine blood data had a significant association with higher mean AUC values in all ML and LR models. The SHAP plot was used to visualize the contributions of all predictors and highlighted the significance of blood data in the lightGBM model. Conclusion The study concluded that ML models could provide rapid and accurate predictions for postoperative GOS outcomes at discharge following moderate-to-severe TBI. The study also highlighted the crucial role of routine blood tests in improving such predictions, and may contribute to the optimization of surgical treatment decision-making for patients with TBI.

Inflammatory bowel disease (IBD) is prevalent, and no satisfactory therapeutic options are available because the mechanisms underlying its development are poorly understood. In this study, we discovered that increased expression of methyltransferase-like 3 (METTL3) in macrophages was correlated with the development of colitis and that depletion of METTL3 in macrophages protected mice against dextran sodium sulfate (DSS)-induced colitis. Mechanistic characterization indicated that METTL3 depletion increased the YTHDF3-mediated expression of phosphoglycolate phosphatase (PGP), which resulted in glucose metabolism reprogramming and the suppression of CD4+ T helper 1 (Th1) cell differentiation. Further analysis revealed that glucose metabolism contributed to the ability of METTL3 depletion to ameliorate colitis symptoms. In addition, we developed two potent small molecule METTL3 inhibitors, namely, F039-0002 and 7460-0250, that strongly ameliorated DSS-induced colitis. Overall, our study suggests that METTL3 plays crucial roles in the progression of colitis and highlights the potential of targeting METTL3 to attenuate intestinal inflammation for the treatment of colitis.

Background Radiotherapy plays a crucial role in pediatric cancer treatment, but challenges exist in achieving precise positioning and irradiation, particularly in young patients. Anesthetics like propofol and chloral hydrate are commonly used, but their associated health risks necessitate exploration of alternative approaches. This study investigates the effectiveness of a novel sleep adjustment method in reducing sedative reliance during radiotherapy for children aged 0–4, aiming to enhance treatment safety and efficacy in this vulnerable population. Methods A randomized controlled Phase II clinical trial will enroll 140 pediatric patients who will be stratified 2:1 into the sleep adjustment group or the sedation group. The WASPE method, which includes watching videos, outdoor activities, stimulation to keep the child awake, playing with toys and eating snacks, will be used to induce deep sleep during radiotherapy in the sleep adjustment group, and the traditional sedation method will be used to deliver radiotherapy in the sedation group. The primary endpoint of the study is radiotherapy completion rate, with secondary endpoints including radiotherapy efficiency and accuracy metrics, quality of life assessments, biological markers of immune function and growth hormone levels, and safety assessments. Discussion This research aims to demonstrate the non-inferiority of the sleep adjustment approach versus standard sedation in radiotherapy completion rates for pediatric cancer patients. Detailed analyses focusing on radiotherapy completion rates, efficiency and accuracy metrics, quality of life assessments using the Pediatric Quality of Life Inventory, immune function indicators, growth hormone levels, and safety outcomes will provide valuable insights into the benefits of reducing sedative use in this context. By investigating innovative strategies to enhance the radiotherapy experience for young patients, this study contributes to advancing pediatric cancer care practices. Trial registration: The trial has been registered on ClinicalTrials.gov with identifier: NCT06443632 (registered May 30, 2024).

Magnetic resonance imaging has been applied in intraoperative neuro-navigation and irradiation guidance in glioma diagnosis. The contrast-enhanced MRI or peritumor edema on T2w image is not precise enough to delineate tumor infiltration. MR spectroscopy (MRS) and chemical exchange saturation transfer (CEST) have been used to evaluate tumor metabolism. Studies showed that amino acid PET surpassed conventional MR imaging for tumor delineation. Here, we explored the correlation between MRS and CEST at 7T and chose PET as gold standard to investigate multimodal MR imaging for glioma metabolic characteristics and tumor extent. An exemplary case with stereotactic biopsy proof was shown.

Glioblastoma multiform (GBM) is recognized as the most malignant brain tumor with a high level of hypoxia, containing a small population of glioblastoma stem like cells (GSCs). These GSCs have the capacity of self-renewal, proliferation, invasion and recapitulating the parent tumor, and are major causes of radio-and chemoresistance of GBM. Upregulated expression of hypoxia inducible factors (HIFs) in hypoxia fundamentally contributes to maintenance and progression of GSCs. Therefore, we thoroughly reviewed the currently acknowledged roles of hypoxia-associated GSCs in development of GBM. In detail, we recapitulated general features of GBM, especially GSC-related features, and delineated essential responses resulted from interactions between GSC and hypoxia, including hypoxia-induced signatures, genes and pathways, and hypoxia-regulated metabolic alterations. Five hypothesized GSC niches are discussed and integrated into one comprehensive concept: hypoxic peri-arteriolar niche of GSCs. Autophagy, another protective mechanism against chemotherapy, is also closely related to hypoxia and is a potential therapeutic target for GBM. In addition, potential causes of therapeutic resistance (chemo-, radio-, surgical-, immuno-), and chemotherapeutic agents which can improve the therapeutic effects of chemo-, radio-, or immunotherapy are introduced and discussed. At last, as a potential approach to reverse the hypoxic microenvironment in GBM, hyperbaric oxygen therapy (HBOT) might be an adjuvant therapy to chemo-and radiotherapy after surgery. In conclusion, we focus on demonstrating the important role of hypoxia on development of GBM, especially by affecting the function of GSCs. Important advantages have been made to understand the complicated responses induced by hypoxia in GBM. Further exploration of targeting hypoxia and GSCs can help to develop novel therapeutic strategies to improve the survival of GBM patients.

Alzheimer’s disease (AD) is a heterogeneous disease with complex clinicopathological characteristics. To date, the role of m6A RNA methylation in monocyte-derived macrophages involved in the progression of AD is unknown. In our study, we found that methyltransferase-like 3 (METTL3) deficiency in monocyte-derived macrophages improved cognitive function in an amyloid beta (Aβ)-induced AD mouse model. The mechanistic study showed that that METTL3 ablation attenuated the m6A modification in DNA methyltransferase 3A (Dnmt3a) mRNAs and consequently impaired YTH N6-methyladenosine RNA binding protein 1 (YTHDF1)-mediated translation of DNMT3A. We identified that DNMT3A bound to the promoter region of alpha-tubulin acetyltransferase 1 (Atat1) and maintained its expression. METTL3 depletion resulted in the down-regulation of ATAT1, reduced acetylation of α-tubulin and subsequently enhanced migration of monocyte-derived macrophages and Aβ clearance, which led to the alleviated symptoms of AD. Collectively, our findings demonstrate that m6A methylation could be a promising target for the treatment of AD in the future.

Hypoxia contributes to the initiation and progression of glioblastoma by regulating a cohort of genes called hypoxia-regulated genes (HRGs) which form a complex molecular interacting network (HRG-MINW). Transcription factors (TFs) often play central roles for MINW. The key TFs for hypoxia induced reactions were explored using proteomic analysis to identify a set of hypoxia-regulated proteins (HRPs) in GBM cells. Next, systematic TF analysis identified CEBPD as a top TF that regulates the greatest number of HRPs and HRGs. Clinical sample and public database analysis revealed that CEBPD is significantly up-regulated in GBM, high levels of CEBPD predict poor prognosis. In addition, CEBPD is highly expressed in hypoxic condition both in GBM tissue and cell lines. For molecular mechanisms, HIF1α and HIF2α can activate the CEBPD promotor. In vitro and in vivo experiments demonstrated that CEBPD knockdown impaired the invasion and growth capacity of GBM cells, especially in hypoxia condition. Next, proteomic analysis identified that CEBPD target proteins are mainly involved in the EGFR/PI3K pathway and extracellular matrix (ECM) functions. WB assays revealed that CEBPD significantly positively regulated EGFR/PI3K pathway. Chromatin immunoprecipitation (ChIP) qPCR/Seq analysis and Luciferase reporter assay demonstrated that CEBPD binds and activates the promotor of a key ECM protein FN1 (fibronectin). In addition, the interactions of FN1 and its integrin receptors are necessary for CEBPD-induced EGFR/PI3K activation by promoting EGFR phosphorylation. Furthermore, GBM sample analysis in the database corroborated that CEBPD is positively correlated with the pathway activities of EGFR/PI3K and HIF1α, especially in highly hypoxic samples. At last, HRPs are also enriched in ECM proteins, indicating that ECM activities are important components of hypoxia induced responses in GBM. In conclusion, CEPBD plays important regulatory roles in the GBM HRG-MINW as a key TF, which activates the EGFR/PI3K pathway through ECM, especially FN1, mediated EGFR phosphorylation.

Background Glioblastoma (GBM) can be divided into subtypes according to their genomic features, including Proneural (PN), Neural (NE), Classical (CL) and Mesenchymal (ME). However, it is a difficult task to unify various genomic expression profiles which were standardized with various procedures from different studies and to manually classify a given GBM sample into a subtype. Methods An algorithm was developed to unify the genomic profiles of GBM samples into a standardized normal distribution (SND), based on their internal expression ranks. Deep neural networks (DNN) and convolutional DNN (CDNN) models were trained on original and SND data. In addition, expanded SND data by combining various The Cancer Genome Atlas (TCGA) datasets were used to improve the robustness and generalization capacity of the CDNN models. Results The SND data kept unimodal distribution similar to their original data, and also kept the internal expression ranks of all genes for each sample. CDNN models trained on the SND data showed significantly higher accuracy compared to DNN and CDNN models trained on primary expression data. Interestingly, the CDNN models classified the NE subtype with the lowest accuracy in the GBM datasets, expanded datasets and in IDH wide type GBMs, consistent with the recent studies that NE subtype should be excluded. Furthermore, the CDNN models also recognized independent GBM datasets, even with small set of genomic expressions. Conclusions The GBM expression profiles can be transformed into unified SND data, which can be used to train CDNN models with high accuracy and generalization capacity. These models suggested NE subtype may be not compatible with the 4 subtypes classification system.

Hepatic glycogen is the main source of blood glucose and controls the intervals between meals in mammals. Hepatic glycogen storage in mammalian pups is insufficient compared to their adult counterparts; however, the detailed molecular mechanism is poorly understood. Here, we show that, similar to glycogen storage pattern, N6-methyladenosine (m6A) modification in mRNAs gradually increases during the growth of mice in liver. Strikingly, in the hepatocyte-specific Mettl3 knockout mice, loss of m6A modification disrupts liver glycogen storage. On the mechanism, mRNA of Gys2, the liver-specific glycogen synthase, is a substrate of METTL3 and plays a critical role in m6A-mediated glycogenesis. Furthermore, IGF2BP2, a "reader" protein of m6A, stabilizes the mRNA of Gys2. More importantly, reconstitution of GYS2 almost rescues liver glycogenesis in Mettl3-cKO mice. Collectively, a METTL3-IGF2BP2-GYS2 axis, in which METTL3 and IGF2BP2 regulate glycogenesis as "writer" and "reader" proteins respectively, is essential on maintenance of liver glycogenesis in mammals.

Objective. Alterations in the methylation state of pseudogenes may serve as clinically useful biomarkers of glioblastomas (GBMs) that do not have glioma-CpG island methylator phenotype (G-CIMP). Methods. Non-G-CIMP GBM datasets were included for evaluation, and a RISK-score signature was determined from the methylation state of pseudogene loci. Both bioinformatic and experimental analyses were performed for biological validation. Results. By integrating clinical information with DNA methylation microarray data, we screened a panel of eight CpGs from discovery cohorts of non-G-CIMP GBMs. Each CpG could accurately and independently predict the prognosis of patients under a treatment regime that combined radiotherapy (RT) and temozolomide (TMZ). The 8-CpG signature appeared to show opposite prognostic correlations between patients treated with RT/TMZ and those treated with RT monotherapy. The analyses further indicated that this signature had predictive value for TMZ efficacy because different survival benefits between RT/TMZ and RT therapies were observed in each risk subgroup. The incorporation of other risk factors, such as age and O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status, with our pseudogene methylation signature could provide precise risk classification. In vitro experimental data revealed that two locus-specific pseudogenes (ZNF767P and CLEC4GP1) may modulate TMZ resistance via distinct mechanisms in GBM cells. Conclusion. The biologically and clinically relevant RISK-score signature, based on pseudogene methylation loci, may offer information for predicting TMZ responses of non-G-CIMP GBMs, that is independent from, but complementary to, MGMT-based approaches.