Biology subjects

Liang, S.

Publications and source records attributed to Liang, S..

At least 91 records · Page 5Linked to original sources

bioRxiv2023

Teacher-student collaborated multiple instance learning for pan-cancer PDL1 expression prediction from histopathology slides

Programmed cell death ligand 1 (PDL1), as an important biomarker, is quantified by immunohistochemistry with few established histopathological patterns. Deep learning aids in histopathological assessment, yet heterogeneity and lacking spatially resolved annotations challenge precise analysis. Here, we present a weakly supervised learning approach using bulk RNA sequencing for PDL1 expression prediction from hematoxylin and eosin (H&E) slides. Our methods, MILTS, extends multiple instance learning paradigm with the teacher-student framework, which assigns dynamic pseudo-labels for intra-slide heterogeneity and retrieves unlabeled instances using temporal ensemble model distillation. The approach, evaluated on 12,299 slides across 20 solid tumor types, achieves a weighted average AUC of 0.83 on fresh-frozen and 0.74 on formalin-fixed specimens for 9 tumors with PDL1 as an established biomarker. MILTS predicts PDL1 expression patterns, validated by immunohistochemistry on 20 slides, offering insights into histologies relevant to PDL1. This demonstrates the potential of deep learning in identifying diverse histological patterns for molecular changes from H&E images.

bioengineering↗

bioRxiv2023

Prominent contributions of selective neuronal subtypes to pediatric drug-resistant focal dysplasia

About 75% cases of epilepsy begin during childhood, and 10 - 30% of pediatric epilepsy patients are resistant to drug treatment. The predominant seizure type in children is focal cortical dysplasia (FCD) which is highly associated with drug-resistant epilepsy, but its underlying cause is poorly understood. We performed single-cell RNA sequencing and patch-clamp recording on fresh brain tissues obtained from pediatric FCD patients shortly after surgery to reveal critical factors contributing to FCD. We report that known epilepsy genes or significant transcriptomic alterations occur in only a few neuronal subgroups, suggesting that epilepsy-associated neurons cluster into only a few neuronal subtypes. These epilepsy-subtypes displayed significant epilepsy-related transcriptomic alterations, especially in the genes associated with excitation/inhibition balance and neuron functional signal pathways. Among eight epilepsy-subtypes, L2_4_CUX2_YWHAH and PVALB_RGS5 subtypes showed the most prominent alterations in FCD patient tissues. Supporting PV-neurons being important, recording from fast-spiking/parvalbumin-containing neurons in acute FCD patient brain slices revealed reduced excitatory synaptic inputs, implicating lower activity in these neurons and fewer synaptic inputs onto them. A higher percentage of mitochondria genes, and likely higher activity in the pathways associated with oxidative phosphorylation and ATP biosynthetic process, was observed in the epilepsy-subtypes, suggesting a high energy expenditure in them. Interestingly, the activity of the above two pathways in most epilepsy-subtypes was lower in the FCD patients, suggesting these subtypes may be more vulnerable to energy deficit in epilepsy. Altogether, transcriptomics is significantly altered in only a few neuronal subtypes in pediatric FCD patient brains. These selective epilepsy-subtypes may play prominent roles in the genesis of pediatric drug-resistant seizure and targeting them may provide new treatment options.

bioinformatics↗

bioRxiv2023

A small molecule inhibitor of PTP1B and PTPN2 enhances T cell anti-tumor immunity

The inhibition of protein tyrosine phosphatases 1B (PTP1B) and N2 (PTPN2) has emerged as an exciting approach for bolstering T cell anti-tumor immunity. ABBV-CLS-484 is a PTP1B/PTPN2 inhibitor in clinical trials for solid tumors. Here we have explored the therapeutic potential of a related small-molecule-inhibitor, Compound-182. We demonstrate that Compound-182 is a highly potent and selective active site competitive inhibitor of PTP1B and PTPN2 that enhances T cell recruitment and activation and represses the growth of tumors in mice, without promoting overt immune-related toxicities. The enhanced anti-tumor immunity in immunogenic tumors could be ascribed to the inhibition of PTP1B/PTPN2 in T cells, whereas in cold tumors, Compound-182 elicited direct effects on both tumor cells and T cells. Importantly, treatment with Compound-182 rendered otherwise resistant tumors sensitive to -PD1 therapy. Our findings establish the potential for small molecule inhibitors of PTP1B and PTPN2 to enhance anti-tumor immunity and combat cancer.

cancer biology↗

bioRxiv2023

CCR9 overexpression promotes T-ALL progression by enhancing cholesterol biosynthesis

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy of the lymphoid progenitor cells contributing to [~] 20% of the total ALL cases with higher prevalence in adults than the children. Despite the important role of human T-ALL cell lines in understanding the biology and treatment options, a detailed comparison of the tumorigenic potential of two commonly used T-ALL cell lines, MOLT4 and JURKAT cells is still lacking. In the present study, we compared the leukemogenic potentials of the two T-ALL cell lines (MOLT4 and JURKAT) in NOD-PrkdcscidIL2rgdull (NTG) mice and found that MOLT4 cells possessed a relatively higher aggressive phenotype characterized by their enhanced tissue infiltration as compared to the JURKAT cells. Gene expression profiling of the two cell lines revealed numerous differentially expressed genes (DEGs) including CC chemokine receptor 9 (CCR9), which augmented the invasion and metastasis of MOLT4 and JURKAT cells in vitro. The upregulation of CCR9 also promoted the tissue infiltration of JURKAT cells in the NTG mice. CCR9 overexpression increased cholesterol production by upregulating the expression of the core regulatory genes of the cholesterol biosynthesis pathway including MSMO1, MVD, and HMGCS1. Moreover, the upregulated expression of EGR1 was also found with CCR9 overexpression that modulated the expression of MSMO1, MVD, and HMGCS1. Notably, the treatment of the cells with simvastatin and siRNA-EGR1 decreased the aggressiveness of the CCR9 overexpressing JURKAT cells in vitro, suggesting the CCR9-EGR1 axis in T-ALL progression. This study highlights the distinct tumorigenic potentials of two T-ALL cell lines and reveals CCR9-regulated enhanced cholesterol biosynthesis in T-ALL. Simple summaryT-ALL is an aggressive cancer of the blood and bone marrow. In order to understand the biological mechanism of T-ALL, in vitro T-ALL cell lines are commonly employed. However, a comprehensive comparison of two common T-ALL cell lines, MOLT4 and JURKAT cells for T-ALL development is not yet available. We compared MOLT4 and JURKAT cells for T-ALL inducing potential and found that MOLT4 cells exhibited a relatively increased aggressiveness in mice as compared to JURKAT cells. We examined the molecular characteristics of two cell lines that could lead to differences in cancer development. Transcriptional profiling of MOLT4 and JURKAT cells revealed significant changes in the expression of several genes including CCR9. This aberrant expression of CCR9 impacted the migration and invasion of the T-ALL cell lines in vitro. In addition, higher expression levels of CCR9 also promoted T-ALL progression in vivo. Transcriptome analysis and gene ontology analysis of the DEGs of CCR9 over-expressing JURKAT cells indicated the enrichment of the genes in the cholesterol biosynthesis pathway, suggesting this metabolic rewiring mechanism as a strategy to cope with the increased energy demand of the malignant T-ALL cells.

cancer biology↗

bioRxiv2023

StructuralDPPIV: A novel deep learning model based on atom-structure for predicting dipeptidyl peptidase-IV inhibitory peptides

MotivationDiabetes is a chronic metabolic disorder that has been a major cause of blindness, kidney failure, heart attacks, stroke, and lower limb amputation across the world. To alleviate the impact of diabetes, researchers have developed the next generation of anti-diabetic drugs, known as dipeptidyl peptidase IV inhibitory peptides (DPP-IV-IPs). However, the discovery of these promising drugs has been restricted due to the lack of effective peptide-mining tools. ResultsHere, we presented StructuralDPPI V, a deep learning model designed for DPP-IV-IP identification, which takes advantage of both molecular graph features in amino acid and sequence information. Experimental results on the independent test dataset and two wet experiment datasets show that our model outperforms the other state-of-art methods. Moreover, to better study what StructuralDPPIV learns, we used CAM technology and perturbation experiment to analyze our model, which yielded interpretable insights into the reasoning behind prediction results. AvailabilityThe project code is available at https://github.com/WeiLab-BioChem/Structural-DPP-IV. Contactweileyi@sdu.edu.cn, ran.su@tju.edu.cn

bioinformatics↗

bioRxiv2023

3D structural human interactome reveals proteome-wide perturbations by disease mutations

Human genome sequencing studies have identified numerous loci associated with complex diseases. However, translating human genetic and genomic findings to disease pathobiology and therapeutic discovery remains a major challenge at multiscale interactome network levels. Here, we present a deep-learning-based ensemble framework, termed PIONEER (Protein-protein InteractiOn iNtErfacE pRediction), that accurately predicts protein binding partner-specific interfaces for all known protein interactions in humans and seven other common model organisms, generating comprehensive structurally-informed protein interactomes. We demonstrate that PIONEER outperforms existing state-of-the-art methods. We further systematically validated PIONEER predictions experimentally through generating 2,395 mutations and testing their impact on 6,754 mutation-interaction pairs, confirming the high quality and validity of PIONEER predictions. We show that disease-associated mutations are enriched in PIONEER-predicted protein-protein interfaces after mapping mutations from [~]60,000 germline exomes and [~]36,000 somatic genomes. We identify 586 significant protein-protein interactions (PPIs) enriched with PIONEER-predicted interface somatic mutations (termed oncoPPIs) from pan-cancer analysis of [~]11,000 tumor whole-exomes across 33 cancer types. We show that PIONEER-predicted oncoPPIs are significantly associated with patient survival and drug responses from both cancer cell lines and patient-derived xenograft mouse models. We identify a landscape of PPI-perturbing tumor alleles upon ubiquitination by E3 ligases, and we experimentally validate the tumorigenic KEAP1-NRF2 interface mutation p.Thr80Lys in non-small cell lung cancer. We show that PIONEER-predicted PPI-perturbing alleles alter protein abundance and correlates with drug responses and patient survival in colon and uterine cancers as demonstrated by proteogenomic data from the National Cancer Institutes Clinical Proteomic Tumor Analysis Consortium. PIONEER, implemented as both a web server platform and a software package, identifies functional consequences of disease-associated alleles and offers a deep learning tool for precision medicine at multiscale interactome network levels.

bioinformatics↗

bioRxiv2023

An interpretable ML model to characterize patient-specific HLA-I antigen presentation

Personalized immunotherapy holds the promise of revolutionizing cancer prevention and treatment. However, selecting HLA-bound peptide targets that are specific to patient tumors has been challenging due to a lack of patient-specific antigen presentation models. Here, we present epiNB, a white-box, positive-example-only, semi-supervised method based on Naive Bayes formulation, with information content-based feature selection, to achieve accurate modeling using Mass Spectrometry data eluted from mono-allelic cell lines and patient-derived cell lines. In addition to achieving state-of-the-art accuracy, epiNB yields novel insights into the structural properties, such as interactions of peptide positions, that appear important for modeling personalized, tumor-specific antigen presentation. epiNB uses substantially less parameters than neural networks, does not require hyperparameter tweaking and can efficiently train and run on our web portal (https://epinbweb.streamlit.app/) or a regular PC/laptop, making it easily applicable in translational settings.

bioinformatics↗

bioRxiv2023

Cdc73 protects Notch-induced T-cell leukemia cells from DNA damage and mitochondrial stress

Activated Notch signaling is highly prevalent in T-cell acute lymphoblastic leukemia (T-ALL) but pan-Notch inhibitors were toxic in clinical trials. To find alternative ways to target Notch signals, we investigated Cell division cycle 73 (Cdc73), which is a Notch cofactor and component of transcriptional machinery, a potential target in T-ALL. While we confirmed previous work that CDC73 interacts with NOTCH1, we also found that the interaction in T-ALL was context-dependent and facilitated by the lymphoid transcription factor ETS1. Using mouse models, we showed that Cdc73 is important for Notch-induced T-cell development and T-ALL maintenance. Mechanistically, Cdc73, Ets1, and Notch intersect chromatin at promoters and enhancers to activate oncogenes and genes that are important for DNA repair and oxidative phosphorylation. Consistently, Cdc73 deletion in T-ALL cells induced DNA damage and impaired mitochondrial function. Our data suggests that Cdc73 might promote a gene expression program that was eventually intersected by Notch to mitigate the genotoxic and metabolic stresses of elevated Notch signaling. We also provide mechanistic support for testing inhibitors of DNA repair, oxidative phosphorylation, and transcriptional machinery. Inhibiting pathways like Cdc73 that intersect with Notch at chromatin might constitute a strategy to weaken Notch signals without directly targeting the Notch complex.

cancer biology↗

bioRxiv2023

Tet-dependent 5-hydroxymethyl-Cytosine modification of mRNA regulates the axon guidance genes robo2 and slit in Drosophila

Modifications of mRNA, especially methylation of adenosine, have recently drawn much attention. The much rarer modification, 5-hydroxymethylation of cytosine (5hmC), is not well understood and is the subject of this study. Vertebrate Tet proteins are 5-methylcytosine (5mC) hydroxylases and catalyze the transition of 5mC to 5hmC in DNA. These enzymes have recently been shown to have the same function in messenger RNAs in both vertebrates and in Drosophila. The Tet gene is essential in Drosophila as Tet knock-out animals do not reach adulthood. We describe the identification of Tet-target genes in the embryo and larval brain by mapping one, Tet DNA-binding sites throughout the genome and two, the Tet-dependent 5hmrC modifications transcriptome-wide. 5hmrC modifications are distributed along the entire transcript, while Tet DNA-binding sites are preferentially located at the promoter where they overlap with histone H3K4me3 peaks. The identified mRNAs are preferentially involved in neuron and axon development and Tet knock-out led to a reduction of 5hmrC marks on specific mRNAs. Among the Tet-target genes were the robo2 receptor and its slit ligand that function in axon guidance in Drosophila and in vertebrates. Tet knock-out embryos show overlapping phenotypes with robo2 and both Robo2 and Slit protein levels were markedly reduced in Tet KO larval brains. Our results establish a role for Tet-dependent 5hmrC in facilitating the translation of modified mRNAs primarily in cells of the nervous system.

neuroscience↗

bioRxiv2022

novoRNABreak: local assembly for novel splice junction and fusion transcript detection from RNA-seq data

We present novoRNABreak, a unified framework for cancer specific novel splice junction and fusion transcript detection in RNA-seq data obtained from human cancer samples. novoRNABreak is based on a local assembly model, which offers a tradeoff between the alignment-based and de novo whole transcriptome assembly (WTA) approaches, namely, being more sensitive in assembling novel junctions that cannot be directly aligned, and more efficient due to the strategy that focuses on junctions rather than full-length transcripts. The performance of novoRNABreak is demonstrated by a comprehensive set of experiments using synthetic data generated based on genome reference, as well as real RNA-seq data from breast cancer and prostate cancer samples. The results show that novoRNABreak can detect novel splice junctions and fusion transcripts efficiently with high sensitivity and reasonable specificity.

bioinformatics↗

bioRxiv2022

Uptake of tumor-derived microparticles induces metabolic reprogramming of macrophages in the early metastatic lung.

The formation of a pre-metastatic niche is a critical step during the metastatic spread of cancer. One way by which primary tumors prime host cells at future metastatic sites is through local shedding of tumor-derived microparticles as a consequence of vascular sheer flow. However, it remains unclear how the uptake of such particles by resident immune cells affects their phenotype and function. Here we show that ingestion of tumor-derived microparticles by macrophages induces a rapid metabolic and phenotypic switch that is characterized by enhanced mitochondrial mass and function, increased oxidative phosphorylation and upregulation of cellular adhesion molecules resulting in reduced motility in the early metastatic lung. We show that this reprogramming event is dependent on signaling through the mTORC1, but not mTORC2 pathway, and is unique to uptake of tumor-derived microparticles. Together, these data support a mechanism by which uptake of tumor-derived microparticles induces reprogramming of macrophages to shape their fate and function in the early metastatic lung.

immunology↗

bioRxiv2022

Conformational dynamics and target-dependent myristoyl switch of calcineurin B homologous protein 3

Calcineurin B homologous protein 3 (CHP3) is an EF-hand Ca2+-binding protein involved in regulation of cancerogenesis, cardiac hypertrophy and neuronal development via interactions with sodium/proton exchangers (NHEs) and signalling proteins. CHP3 binds Ca2+ with micromolar affinity providing the basis to respond to intracellular Ca2+ signals. Ca2+ binding and myristoylation are important for CHP3 function but the underlying molecular mechanism remained elusive. Here, we show that Ca2+ binding and myristoylation independently affect conformational dynamics and functions of human CHP3. Ca2+ binding increased flexibility and hydrophobicity of CHP3 indicative of an open conformation. CHP3 in open Ca2+-bound conformation had higher affinity for NHE1 and associated stronger with lipid membranes compared to the closed Mg2+-bound conformation. Myristoylation enhanced flexibility of CHP3 and decreased its affinity to NHE1 independently of the bound ion, but did not affect its binding to lipid membranes. The data exclude the proposed Ca2+-myristoyl switch for CHP3. Instead, they document a Ca2+-independent exposure of the myristoyl moiety induced by binding of the target peptide to CHP3 enhancing its association to lipid membranes. We name this novel regulatory mechanism "target-dependent myristoyl switch". Taken together, the interplay of Ca2+ binding, myristoylation and target binding allows for a context-specific regulation of CHP3 functions.

biochemistry↗

bioRxiv2022

Toxicity of microplastics and plastic additive co-exposure in liver Disse organoids from healthy donors and patient-derived induced pluripotent stem cells

The ubiquitous microplastics (MPs) and plastic additives in the environment usually form complexes, enter human blood circulation, and increase the risk of steatohepatitis. The liver Disse space plays a vital role in corresponding hepatic pathological processes. However, due to the limited understanding of the regulatory cues in multilineage maturation, the generation of large-scale Disse-like organoids (DOs) mirroring the comprehensive toxicity responses of MPs is challenging. Here, using human-induced pluripotent stem cells (hiPSCs), we biofabricated healthy donors and patient-derived DOs containing hepatocytes, endothelial cells, and hepatic stellate cells, resembling the features of Disse space. These organoids revealed that polystyrene MPs preferentially entered endothelial cells and then dispersed throughout the organoids, similar to reported studies in zebrafish. Co-exposure to MPs and tetrabromobisphenol A (TBBPA), a common plastic additive, showed enhanced accumulation of contamination in the organoids. We also biofabricated alcoholic liver disease (ALD) patient-derived DOs representing the specific disease transcriptional profiles. We found that co-exposure to MPs and TBBPA at environmental-related dosages significantly elevated the pathological transcriptional expression and biochemical profiles in patient-derived DOs but not in healthy organoids, suggesting that both hereditary factors and pollutants contribute to susceptibility to environmental toxicants. This study exemplified the value of biofabricated hiPSC-derived organoids in environmental toxicology and offered a powerful strategy for personalized toxicology evaluation.

bioengineering↗

bioRxiv2022

Positive effects of tree diversity on tropical forest restoration in a field-scale experiment

Experiments under controlled conditions have established that ecosystem functioning is generally positively related to levels of biodiversity, but it is unclear how widespread these effects are in real-world settings and whether they can be harnessed for ecosystem restoration. We used a long-term, field-scale tropical restoration experiment to test how the diversity of planted trees affected recovery measured across a 500 ha area of selectively logged forest using multiple sources of satellite data. Replanting with species rich mixtures of tree seedlings that had higher phylogenetic and functional diversity accelerated restoration rates. Our results are consistent with a positive relationship between biodiversity and ecosystem functioning in the lowland dipterocarp rainforests of SE Asia and demonstrate that using diverse mixtures of species can enhance initial recovery after logging.

ecology↗

bioRxiv2022

A benchmark study of protein folding algorithms on nanobodies

Nanobodies, also known as single domain or VHH antibodies, are the artificial recombinant variable domains of heavy-chain-only antibodies. Nanobodies have many unique properties, including small size, good solubility, superior stability, rapid clearance from blood, and deep tissue penetration. Therefore, nanobodies have emerged as promising tools for diagnosing and treating diseases. In recent years, many deep-learning-based protein structure prediction methods have emerged that require only protein sequences as input to obtain highly-credible 3D protein structures. Among them, AlphaFold2, RoseTTAFold, DeepAb, NanoNet, and tFold performed excellently in protein prediction or antibody/nanobody prediction. In this study, we selected 60 nanobody samples with known experimental 3D structures in the Protein Data Bank (PDB). Next, we predicted their 3D structures using these five prediction algorithms from only their 2D amino acid sequences. Then, we individually compared the predicted and experimental structures. Finally, the results are analyzed and discussed.

bioinformatics↗

bioRxiv2022

FOXP2 confers oncogenic effects in prostate cancer through activating MET signalling

Identification oncogenes is fundamental to revealing the molecular basis of cancer. Here, we found that FOXP2 is overexpressed in human prostate cancer cells and prostate tumors, but its expression is absent in normal prostate epithelial cells and low in benign prostatic hyperplasia. To date, little is known regarding the link of FOXP2 to prostate cancer. We observed that high FOXP2 expression and frequent amplification are significantly associated with high Gleason score. Ectopic expression of FOXP2 induces malignant transformation of mouse NIH3T3 fibroblasts and human prostate epithelial cell RWPE-1. Conversely, FOXP2 knockdown suppresses the proliferation of prostate cancer cells. Transgenic overexpression of FOXP2 in the mouse prostate causes prostatic intraepithelial neoplasia. Overexpression of FOXP2 aberrantly activates oncogenic MET signalling and inhibitors targeting MET signalling effectively reverts the FOXP2-induced oncogenic phenotype. Additionally, the novel recurrent FOXP2-CPED1 fusion identified in prostate tumors results in high expression of truncated FOXP2, which exhibit a similar capacity for malignant transformation. Together, our data demonstrate for the first time that FOXP2 is an oncogene involved in tumorigenicity of prostate.

cancer biology↗

bioRxiv2022

PHAT: interpretable prediction of peptide secondary structures using hypergraph multi-head attention network and transfer learning

Accurately predicting peptide secondary structures remains a challenging task due to the lack of discriminative information in short peptides. In this study, we propose PHAT, a deep graph learning framework for the prediction of peptide secondary structures. The framework includes a novel interpretable deep hypergraph multi-head attention network that uses residue-based reasoning for structure prediction. Our algorithm can incorporate sequential semantic information from large-scale biological corpus and structural semantic information from multi-scale structural segmentation, leading to better accuracy and interpretability even with extremely short peptides. Our interpretable models are able to highlight the reasoning of structural feature representations and the classification of secondary substructures. We further demonstrate the importance of secondary structures in peptide tertiary structure reconstruction and downstream functional analysis, highlighting the versatility of our models. To facilitate the use of our model, we establish an online server which is accessible via http://inner.wei-group.net/PHAT/. We expect our work to assist in the design of functional peptides and contribute to the advancement of structural biology research.

bioinformatics↗

bioRxiv2022

SARS-CoV-2 S protein antagonizes type I interferon downstream signal pathway through interacting and attenuating phosphorylation of STAT1/STAT2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may keep patients in a clinically asymptomatic state by blocking cellular innate antiviral immunity, but the molecular mechanism remains unclear. Here, we screened the viral proteins of SARS-CoV-2 and found that the spike (S) protein inhibits the activation of interferon-stimulated genes (ISGs) and even reduces the expression of these genes to below background values. Mechanistically, the S protein interacted with STAT1, STAT2, and IRF9 and impedes the phosphorylation of STAT1/STAT2, thus preventing the formation of the interferon-stimulating gene factor 3 (ISGF3) complex and inhibiting the downstream production of Interferon-stimulated genes (ISGs). Remarkably, we also have found that the inhibitory mechanism of the S protein was conservative among SARS-CoV-2 variants and other human coronaviruses, including SARS-CoV, MERS-CoV, HCoV-229E, HCoV-NL63, and HCoV-HKU1. Truncation studies indicated that the most conserved S2 domain played a major inhibitory role. Altogether, our findings unveil a new mechanism by which SARS-CoV-2 S protein attenuated the hosts antiviral immune response and provide new insights into the pathogenic mechanism of coronavirus.

microbiology↗