Biology subjects

Lu, H.

Publications and source records attributed to Lu, H..

At least 199 records · Page 11Linked to original sources

bioRxiv2022

Abnormal intrinsic neural timescale in Parkinson's disease

BACKGROUND: Numerous studies indicate altered peak latency of event-related potential and altered time variability of brain function network in Parkinsons disease (PD), and the intrinsic neural timescale estimated how long neural information stored in a local brain area has been specialized. However, it was unclear whether PD patients exhibited abnormal intrinsic timescales and accompanied with abnormal grey matter and whether PD patients exhibited different temporal feature at different stages. STUDY TYPE: Prospective. POPULATION: 74 PD patients, including 44 patients in the early stage (PD-ES) and 30 patients in the late stage (PD-LS), and 73 healthy controls (HC). SEQUENCE: 3.0T MRI scanner; prototypic T1 magnetization prepared rapid acquisition gradient echo (MPRAGE); resting-state fMRI. ASSESSMENT: the intrinsic timescales were estimated by using the magnitude of the autocorrelation of intrinsic neural signals. Voxel-based morphometry (VBM) was performed to calculate the grey matter volume (GMV) in the whole brain. STATISTICAL TEST: Analysis of variance (ANOVA); two-sample t-tests; Spearman rank correlation analysis; Mann-Whitney U test; Kruskal-Wallis H test. RESULTS: We identified that the PD group had abnormal intrinsic timescales in bilateral lingual and calcarine gyri, bilateral postcentral and precentral gyri, and the right middle cingulum gyrus, which correlated with the symptom severity and the GMV. Moreover, longer timescale in the right middle frontal gyrus were also found in the PD group. Increasingly, the PD-ES group had longer timescales in the anterior cortical regions, whereas the PD-LS group had shorter timescales in the posterior cortical regions. DATA CONCLUSION: Our findings suggest that PD patients exhibit abnormal intrinsic timescales in visual, sensorimotor, and cognitive systems and distinct patterns of intrinsic timescales and GMV in cerebral cortex at different stages, which might provide new insights for the neural substrate of PD.

neuroscience↗

bioRxiv2022

Tumor microenvironments impair T cell receptor affinity and function

CD8+ T cells underpin effective anti-tumor immune responses in melanoma; however, their functions are attenuated due to various immunosuppressive factors in the tumor microenvironment (TME), resulting in disease progression. T cell function is elicited by the T cell receptor (TCR), which recognizes antigen peptide-major histocompatibility complex (pMHC) expressed on tumor cells via direct physical contact, i.e., two-dimensional (2D) interaction. TCR-pMHC 2D affinity plays a central role in antigen recognition and discrimination, and is sensitive to both the conditions of the T cell and the microenvironment in which it resides. Herein, we demonstrate that CD8+ T cells residing in TME have lower 2D TCR-pMHC bimolecular affinity and TCR-pMHC-CD8 trimolecular avidity, pull fewer TCR-pMHC bonds by endogenous forces, flux lower level of intracellular calcium in response to antigen stimulation, exhibit impaired in vivo activation, and show diminished anti-tumor effector function. These detrimental effects are localized in the tumor and tumor draining lymph node (TdLN), and affect both antigen-inexperienced and antigen-experienced CD8+ T cells irrespective of their TCR specificities. These findings implicate impaired antigen recognition as a mechanism of T cell dysfunction in the TME.

immunology↗

bioRxiv2022

Modeling and Simulation of Rat Non-Barrel Somatosensory Cortex. Part I: Modeling Anatomy

The function of the neocortex is fundamentally determined by its repeating microcircuit motif, but also by its rich, interregional connectivity. We present a data-driven computational model of the anatomy of non-barrel primary somatosensory cortex of juvenile rat, integrating whole-brain scale data while providing cellular and subcellular specificity. The model consists of 4.2 million morphologically detailed neurons, placed in a digital brain atlas. They are connected by 14.2 billion synapses, comprising local, mid-range and extrinsic connectivity. We delineated the limits of determining connectivity from neuron morphology and placement, finding that it reproduces targeting by Sst+ neurons, but requires additional specificity to reproduce targeting by PV+ and VIP+ interneurons. Globally, connectivity was characterized by local clusters tied together through hub neurons in layer 5, demonstrating how local and interegional connectivity are complicit, inseparable networks. The model is suitable for simulation-based studies, and a 211,712 neuron subvolume is made openly available to the community.

neuroscience↗

bioRxiv2022

Identify non-mutational p53 loss of function in human cancers

An accurate assessment of TP53s functional status is critical for cancer genomic medicine. However, there is a significant challenge in identifying tumors with non-mutational p53 inactivations that are not detectable through DNA sequencing. These undetected cases are often misclassified as p53-normal, leading to inaccurate prognosis and downstream association analyses. To address this issue, we build the support vector machine (SVM) models to systematically reassess p53s functional status in TP53 wild-type (TP53WT) tumors from multiple TCGA cohorts. Cross-validation demonstrates the excellent performance of the SVM models with a mean AUC of 0.9822, precision of 0.9747, and recall of 0.9784. Our study reveals that a significant proportion (87-99%) of TP53WT tumors actually have compromised p53 function. Additional analyses uncovered that these genetically intact but functionally impaired (termed as predictively reduced function of p53 or TP53WT-pRF) tumors exhibit genomic and pathophysiologic features akin to p53 mutant tumors: heightened genomic instability and elevated levels of hypoxia. Clinically, patients with TP53WT-pRF tumors experience significantly shortened overall survival or progression-free survival compared to those with TP53WT-pN (predictive normal function of p53) tumors, and these patients also display increased sensitivity to platinum-based chemotherapy and radiation therapy.

bioinformatics↗

bioRxiv2022

Characterization and Preclinical Treatment of Rotational Force-Induced Brain Injury

Millions of traumatic brain injuries (TBIs) occur annually. TBIs commonly result from falls, traffic accidents, and sports-related injuries, all of which involve rotational acceleration/deceleration of the brain. During these injuries, the brain endures a multitude of primary insults including compression of brain tissue, damaged vasculature, and diffuse axonal injury. All of these deleterious effects can contribute to secondary brain ischemia, cellular death, and neuroinflammation that progress for weeks to months after injury and impede neurological recovery. While the linear effects of head trauma have been extensively modeled, less is known about how rotational injuries mediate neuronal damage following injury. Here, we developed a new model of rotational head trauma in rodents and extensively characterized the pathological, behavioral, and electrophysiological effects of rotational TBI (rTBI). We identify aberrant cyclin dependent kinase 5 (Cdk5) activity as a principal mediator of rTBI and show pharmacological inhibition of Cdk5 reduces the cognitive and pathological consequences of injury. Finally, we utilize Cdk5-enriched phosphoproteomics to uncover potential downstream mediators of rTBI. These studies contribute meaningfully to our understanding of the mechanisms of rTBI and how they may be effectively treated.

neuroscience↗

bioRxiv2022

A Mechanistic Study on the Cellular Uptake, Intracellular Trafficking, and Antisense Gene Regulation of Bottlebrush Polymer-Conjugated Oligonucleotides

We have developed a non-cationic transfection vector in the form of a bottlebrush polymer-antisense oligonucleotide (ASO) conjugate. Termed pacDNA (polymer-assisted compaction of DNA), these agents show improved biopharmaceutical characteristics and antisense potency in vivo while suppressing non-antisense side effects. Nonetheless, there still lacks a mechanistic understanding regarding the cellular uptake, subcellular trafficking, and gene knockdown with pacDNA. Here, we show that the pacDNA enters human non-small cell lung cancer cells (NCI-H358) predominantly by scavenger receptor-mediated endocytosis and macropinocytosis, and trafficks via the endolysosomal pathway within the cell. The pacDNA significantly reduces a target gene expression (KRAS) in the protein level but not in the mRNA level, despite that the transfection of free ASOs causes ribonuclease H1 (RNase H)-dependent degradation of KRAS mRNA. In addition, the antisense activity of pacDNA is independent of ASO chemical modification, suggesting that the pacDNA functions as a steric blocker. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=148 SRC="FIGDIR/small/496353v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@56e08eorg.highwire.dtl.DTLVardef@1b09510org.highwire.dtl.DTLVardef@a785corg.highwire.dtl.DTLVardef@1641874_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2022

Redefining and subtyping of major depression based on brain functional connectivity signatures with high generalization: an ensemble hybrid framework

Current clinical diagnosis of major depression is solely based on subjective symptoms and signs rather than the underlying biological mechanisms, which has hindered the improvement in treatment effectiveness and outcomes. Redefining and subtyping major depressive disorder (MDD) based on neural circuits has been an emerging consensus. Here, we proposed a novel ensemble hybrid deep-learning framework based on graph neural network for redefining and subtyping of MDD with the brains "fingerprinting", i.e. nuanced functional connectivity profiles. A graph neural network (GNN) based supervised model was first employed to discriminate MDD patients from healthy controls. The graph embedding features obtained from the supervised classifier was then employed for subtyping of MDD with an unsupervised clustering by fast search and find of density peaks (CFDP) approach. The generalization accuracy and reproducibility of the proposed framework were further validated with one of the largest resting-state fMRI data set for MDD which included 2428 participants recruited from 25 independent sites. Our classifier showed a high generalization of 75% for leave-one-site-out cross validation. In addition, we obtained three biologically homogenous MDD subtypes characterized by impairments in subcortical-limbic, DMN-FPN, VN-SMN circuits, respectively. Notably, we demonstrated that subtyping of MDD according to graph embedding features showed high robustness and reproducibility across different sites. The proposed framework is not only essential for redefining and subtyping of MDD, but also paves the way towards precision medicine of mental disorders.

neuroscience↗

bioRxiv2022

Sex differences in the nasal microbiome of healthy young adults

Respiratory diseases impose an immense health burden worldwide. Epidemiological studies have revealed extensive disparities in the incidence and severity of respiratory tract infections (RTIs) between males and females. It is recently hypothesized that there might also be a nasal microbiome axis contributing to the observed sex disparities, but without evidence. In this work, we study the nasal microbiome of healthy young adults in, as of today, the largest cohort based on deep shot-gun metagenomic sequencing. We mainly focus on the bacteriome, but also integrate the mycobiome to get a more holistic perspective. De novo assembly is performed to catalog the nasal bacterial colonizers/residents, which also identify and therefore account for uncharacterized components of the community. The bacteriome is then profiled based on the non-redundant metagenome-assembled genomes (MAGs) catalog constructed therefrom. Unsupervised clustering reveals clearly separable structural patterns in the nasal microbiome between the two sexes. Following this link, we systematically evaluate sex differences for the first time and reveal extensive sex-specific features in the nasal microbiome composition. More importantly, through network analyses, we capture markedly higher ecological stability and antagonistic potentials in the nasal microbiome of females than that of males. The analysis of the keystone bacteria of the communities reveal that the sex-dependent evolutionary characteristics might have contributed to this difference. HighlightsThe non-redundant nasal bacterial MAGs catalog constructed from ultra-deeply sequenced metagenomic data provides a valuable resource. Integrating nasal bacteriome and mycobiome data provides a more holistic perspective for the understudied human nasal microbiome. Unsupervised clustering helps uncover extensive sex differences in the nasal microbiome compositions. Network analyses capture markedly higher ecological stability and antagonistic potentials in the nasal microbiome of females than that of males. Sex-dependent genetic evolutionary forces play a role in the shaping of keystones in the nasal microbial community.

microbiology↗

bioRxiv2022

Fast, Efficient, and Accurate Neuro-Imaging Denoising via Deep Learning

Volumetric functional imaging is widely used for recording neuron activities in vivo, but there exist tradeoffs between the quality of the extracted calcium traces, imaging speed, and laser power. While deep-learning methods have recently been applied to denoise images, their applications to downstream analyses, such as recovering high-SNR calcium traces, have been limited. Further, these methods require temporally-linked pre-registered data with ultrafast rates. Here, we demonstrate supervised deep-denoising methods to circumvent these tradeoffs for several applications, including whole-brain imaging, large field-of-view imaging in freely moving animals, and recovering complex neurite structures in C. elegans. Our framework has 30x smaller memory footprint, and is fast in training and inference (50-70ms); it is highly accurate and generalizable, and further, only small, non-temporally-sequential, independently-acquired training datasets ([~]500 images) are needed. We envision that the framework will enable faster and long-term imaging experiments necessary to study neuronal mechanisms of many behaviors.

neuroscience↗

bioRxiv2022

MRSCloud: a Cloud-based MR Spectroscopy Tool for Basis Set Simulation

BackgroundAccurate quantification of in vivo proton magnetic resonance spectra involves modeling with a linear combination of known metabolite basis functions. Basis sets can be generated by numerical simulation using the quantum mechanical density-matrix formalism. Accurate simulations for a basis set require correct sequence timings, and pulse shapes and durations. PurposeTo present a cloud-based spectral simulation tool MRSCloud. It allows community users of MRS to simulate a vendor- and sequence-specific basis set online in a convenient and timeefficient manner. This tool can simulate basis sets for 3 major MR scanner vendors (GE, Philips, Siemens), including conventional acquisitions and spectral editing schemes (MEGA, HERMES, HERCULES) with PRESS and semi-LASER localization. Study TypeProspective. SpecimenN/A Field Strength/SequenceSimulations of 3T basis sets for conventional and spectral-editing sequences (MEGA, HERMES, HERCULES) with PRESS and sLASER localizations. AssessmentSimulated metabolite basis functions generated by MRSCloud are compared to those generated by FID-A and MARSS, and a phantom-acquired basis-set from LCModel. Statistical TestsIntraclass correlation coefficients (ICC) were calculated to measure the agreement between individual metabolite basis functions generated using different packages. Statistical analysis was performed using R in RStudio. ResultsSimulation time for a full basis set is approximately 1 hour. ICCs between MRSCloud and FID-A were at least 0.98 and ICCs between MRSCloud and MARSS were at least 0.96. ICCs between simulated MRSCloud basis spectra and acquired LCModel basis spectra were lowest for Gln at 0.68 and highest for NAA at 0.96. Data ConclusionSubstantial reductions in runtime have been achieved by implementing the 1D projection method, coherence-order filtering, and pre-calculation of propagators. High ICC values indicated that the accelerating features are running correctly and produce comparable and accurate basis sets. The generated basis set has been successfully used with LCModel.

bioengineering↗

bioRxiv2022

Cellular Mechanisms Underlying Central Sensitization in a Mouse Model of Chronic Muscle Pain

Chronic pain disorders are often associated with psychiatric symptoms. The central nucleus of the amygdala (CeA) has emerged as an integrative hub for nociceptive and affective components during the development of central pain. Although the exact cause for this process remains unknown, prior adverse injuries are precipitating factors and thought to transform nociceptors into a primed state for chronic pain. However, the cellular basis underlying the primed state and the subsequent pain chronification remains unknown. Here, we investigated cellular and synaptic alterations of the CeA in a mouse model of chronic muscle pain. In these mice, local infusion of pregabalin, a clinically approved drug for fibromyalgia and other chronic pain disorders, into the CeA or selective inactivation of somatostatin-expressing CeA (CeA-SST) neurons during the priming phase prevented pain chronification. Further, electrophysiological recording revealed that CeA-SST neurons received increased excitatory transmission and showed enhanced excitability in chronic pain states. In line with the possible role of CeA-SST neurons in central sensitization, chemogenetic inactivation of CeA-SST neurons or pharmacological suppression of nociceptive afferents from the brainstem to CeA-SST neurons by pregabalin after the development of chronic muscle pain alleviated pain and negative emotions.

neuroscience↗

bioRxiv2022

A novel anti-PD-L1/IL-15 immunocytokine overcomes resistance to PD-L1 blockade and elicits potent antitumor immunity

Despite the demonstrated immense potential of immune checkpoint inhibitors in various types of cancers, only a minority of patients respond to these therapies. Immunocytokines designed to deliver an immune-activating cytokine directly to the immunosuppressive tumor microenvironment (TME) and block the immune checkpoint simultaneously may provide a strategic advantage over the combination of two single agents. To increase response rate to checkpoint blockade, in this study we developed a novel immunocytokine (LH01) composed of the antibody against programmed death-ligand 1 (PD-L1) fused to IL-15 receptor alpha-sushi domain/IL-15 complex. We demonstrate that LH01 efficiently binds mouse or human PD-L1 and maintains IL-15 stimulatory activity. In syngeneic mouse models, LH01 showed improved antitumor efficacy and safety versus anti-PD-L1 plus LH02 (Fc-Sushi-IL15) combination and overcame resistance to anti-PD-L1 treatment. Mechanistically, the dual anti-immunosuppressive function of LH01 led to activation of both the innate and adaptive immune response and decreased levels of transforming growth factor-{beta}1 (TGF-{beta}1) within the TME. Furthermore, combination therapy with LH01 and bevacizumab exerts synergistic antitumor effects in HT29 colorectal xenograft model. Collectively, our results provide supporting evidence that fusion of anti-PD-L1 and IL-15 might be a potent strategy to treat patients with cold tumors or resistance to checkpoint blockade.

immunology↗

bioRxiv2022

Transient regulation of focal adhesion via Tensin3 is required for nascent oligodendrocyte differentiation

The differentiation of oligodendroglia from oligodendrocyte precursor cells (OPCs) to complex and extensive myelinating oligodendrocytes (OLs) is a multistep process that involves largescale morphological changes with significant strain on the cytoskeleton. While key chromatin and transcriptional regulators of differentiation have been identified, their target genes responsible for the morphological changes occurring during OL myelination are still largely unknown. Here, we show that the regulator of focal adhesion, Tensin3 (Tns3), is a direct target gene of Olig2, Chd7, and Chd8, transcriptional regulators of OL differentiation. Tns3 is transiently upregulated and localized to cell processes of immature OLs, together with integrin-{beta}1, a key mediator of survival at this transient stage. Constitutive Tns3 loss-of-function leads to reduced viability in mouse and humans, with surviving knockout mice still expressing Tns3 in oligodendroglia. Acute deletion of Tns3 in vivo, either in postnatal neural stem cells (NSCs) or in OPCs, leads to a two-fold reduction in OL numbers. We find that the transient upregulation of Tns3 is required to protect differentiating OPCs and immature OLs from cell death by preventing the upregulation of p53, a key regulator of apoptosis. Altogether, our findings reveal a specific time window during which transcriptional upregulation of Tns3 in immature OLs is required for OL differentiation likely by mediating integrin-{beta}1 survival signaling to the actin cytoskeleton as OL undergo the large morphological changes required for their terminal differentiation.

neuroscience↗

bioRxiv2022

ASGR1 is a candidate receptor for SARS-CoV-2 that promotes infection of liver cells

Backgroud & AimsCurrently, the COVID-19 pandemic, caused by SARS-CoV-2 infection, represents a serious public health problem worldwide. Although it has been shown that ACE2 serves as the main receptor for SARS-CoV-2 entry into host cells, studies have shown that ACE2 is expressed at extremely low levels in various tissues, especially in some organs where virus particles have been found, such as the heart and liver. Therefore, these organs potentially express additional SARS-CoV-2 receptors that have not yet been discovered. Methods & ResultsHere, by a genome-wide CRISPR-Cas9 activation library screening, we found that ASGR1 promoted SARS-CoV-2 infection of 293T cells. In Huh-7 and HepG2 cell lines, simultaneous knock out of ACE2 and ASGR1 prevented SARS-CoV-2 pseudovirus infection. In the immortalized THLE-2 hepatocyte cell line and primary liver parenchymal cells, both of which hardly express ACE2, SARS-CoV-2 could successfully establish an infection. After treatment with ASGR1 antibody, the infection rate significantly reduced. This suggests that SARS-CoV-2 infects liver cells mainly through an ASGR1-dependent mechanism. Finally, we also found that the soluble ASGR1 could not only prevent the SARS-CoV-2 pseudovirus, which binds to the ASGR1 receptors, from infecting host liver cells, but also had a protective effect on those expressing ACE2, indicating that administration of soluble ASGR1 protein may represent a new treatment approach. ConclusionsColletively, these findings indicate that ASGR1 is a candidate receptor for SARS-CoV-2 that promotes infection of liver cells. Lay SummaryWe show that ASGR1 is a candidate receptor for SARS-CoV-2 to infect liver cells.

microbiology↗

bioRxiv2022

Patterns of Saliency and Semantic Features Distinguish Gaze of Expert and Novice Viewers of Surveillance Footage

When viewing the actions of others, we not only see patterns of body movements, but we also "see" the intentions and social relations of people, enabling us to understand the surrounding social environment. Previous research has shown that experienced forensic examiners--Closed Circuit Television (CCTV) operators--convey superior performance in identifying and predicting hostile intentions from surveillance footages than novices. However, it remains largely unknown what visual content CCTV operators actively attend to when viewing surveillance footage, and whether CCTV operators develop different strategies for active information seeking from what novices do. In this study, we conducted computational analysis for the gaze-centered stimuli captured by experienced CCTV operators and novices eye movements when they viewed the same surveillance footage. These analyses examined how low-level visual features and object-level semantic features contribute to attentive gaze patterns associated with the two groups of participants. Low-level image features were extracted by a visual saliency model, whereas object-level semantic features were extracted by a deep convolutional neural network (DCNN), AlexNet, from gaze-centered regions. We found that visual regions attended by CCTV operators versus by novices can be reliably classified by patterns of saliency features and DCNN features. Additionally, CCTV operators showed greater inter-subject correlation in attending to saliency features and DCNN features than did novices. These results suggest that the looking behavior of CCTV operators differs from novices by actively attending to different patterns of saliency and semantic features in both low-level and high-level visual processing. Expertise in selectively attending to informative features at different levels of visual hierarchy may play an important role in facilitating the efficient detection of social relationships between agents and the prediction of harmful intentions. Author SummaryImagine seeing a person walking toward another person menacingly on the street, we may instantly feel that some physical confrontation will happen in the next second. However, it remains unclear how we efficiently infer social intentions and outcomes from the observed dynamic visual input. To answer this question, CCTV experts, who have years of experience on observing social scenes and making online predictions of the action outcomes, provide a unique perspective. Here, we collected experts and novices eye movements when observing different action sequences and compared the attended visual information between groups. A saliency model was used to compare low-level visual features such as luminance and color, and a deep convolutional neural network was used to extract object-level semantic visual features. Our findings showed that experts obtained different patterns of low-level and semantic-level features in visual processing compared to novices. Thus, the expertise in selectively attending to informative features at different levels of visual hierarchy may play an important role in facilitating the efficient detection of social relationships between agents and the prediction of harmful intentions.

neuroscience↗

bioRxiv2022

HMGN5 escorts oncogenic STAT3 signaling by regulating chromatin landscape in tumorigenesis of breast cancer

Epigenetic alterations are widely linked with carcinogenesis, therefore becoming emerging therapeutic targets in the treatment of cancers, including breast cancer. HMGNs are nucleosome binding proteins, which regulate chromatin structures in a cell type- and disease-specific manner. However, the roles of HMGNs in the tumorigenesis of breast cancer are less known. In this study, we report that HMGNs are highly expressed in 3D-cultured breast cancer cells. HMGN5, a member of HMGNs, controls the proliferation, invasion and metastasis of breast cancer cells in vitro and in vivo. Clinically, HMGN5 is an unfavorable prognostic marker in patients. Mechanistically, HMGN5 is governed by active STAT3 transcriptionally and further escorts STAT3 to shape oncogenic chromatin landscape and transcriptional program. Lastly, we provide evidence that interference of HMGN5 by nanoparticle-packaged siRNA is potentially an effective approach in breast cancer treatment. Taken together, our findings reveal a novel feed-forward circuit between HMGN5 and STAT3 in promoting breast cancer tumorigenesis and suggest HMGN5 as a novel epigenetic therapeutic-target in STAT3- hyperactive breast cancer.

cancer biology↗

bioRxiv2021

Transcriptomic Profiling Reveals Cancer-Associated Fibroblasts as Potential Targets for the Prognosis and Treatment of Cervical Squamous Cell Carcinoma

Effective treatment of advanced invasive cervical cancer remains challenging nowadays. Herein, single-nucleus RNA sequencing (snRNA-seq) and SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq) technology are used to investigate the immunological microenvironment of cervical squamous cell carcinoma (CSCC), a major type of cervical cancers. The expression levels of most immune checkpoint genes in tumor and inflammation areas of CSCC were not significantly higher than those in the non-cancer samples except for LGALS9 and IDO1. Stronger signals of CD56+ NK cells and immature dendritic cells are found in the hypermetabolic tumor areas, while more eosinophils, immature B cells, and Treg cells are found in the hypometabolic tumor areas. Moreover, a cluster of cancer-associated fibroblasts (CAFs) are identified around some tumors, which highly expressed ACTA2, POSTN, ITGB4, and FAP. The CAFs might support the growth and metastasis of tumors by inhibiting lymphocyte infiltration and remodeling the tumor extracellular matrix. Furthermore, CAFs are associated with poorer survival probability in CSCC patients and might be present in a small fraction ([~]20%) of advanced cancer patients. Collectively, these findings might enhance understanding of the CSCC immunological microenvironment and shed some light on the treatment of advanced CSCC.

cancer biology↗

bioRxiv2021

Histone demethylase UTX regulates glioblastoma progression through affecting periostin expression

The histone H3K27 demethylase UTX participates in regulating multiple cancer types. However, less is known about the UTX function in glioblastoma (GBM). This study aims to define the effect of UTX on GBM. GEPIA2 database analysis showed that UTX expression was significantly increased in GBM and inversely correlated with survival. Knockdown UTX inhibited GBM cell proliferation, migration, and invasion while promoting apoptosis. Moreover, knockdown UTX also hampered tumor growth in the heterotopic xenograft model. RNA-seq combined with qRT-PCR and ChIP-qPCR were used to identify the target genes. The results showed that the UTX-mediated genes were strongly associated with tumor progression and the extracellular environment. Protein-protein interaction analysis suggested that periostin (POSTN) interacted with most of the other UTX-mediated genes. POSTN supplement abolished the effect of UTX knockdown in GBM cells. Furthermore, silencing UTX exhibited similar antitumor effect in patient-derived glioblastoma stem-like cells, while UTX functions were partially restored after exposing POSTN. Our findings may reveal a new insight into the onset of gliomagenesis and progression, providing a promising therapeutic strategy for GBM treatment. Bullet PointsUTX correlates with survival in glioblastoma. Silencing UTX decreased the levels of H3K27 methylation in the POSTN gene, thereby suppressing POSTN expression. UTX-mediated POSTN expression is crucial for glioblastoma cell growth and tumorigenesis. O_LIUTX expression is increased in GBM and negatively correlated with survival. C_LIO_LIUTX knockdown influences proliferation and apoptosis in both GBM cells and GSCs. C_LIO_LIThe antitumor effect of UTX knockdown is achieved by suppressing POSTN expression. C_LI

cancer biology↗