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Cao, Y.

Publications and source records attributed to Cao, Y..

At least 145 records · Page 8Linked to original sources
bioRxiv2025

Evolution of chronic lymphocytic leukemia after allogeneic stem cell transplant

Allogeneic stem cell transplant (alloSCT) for patients with relapsed/refractory chronic lymphocytic leukemia (CLL) can result in cure in some patients. Analogous to chemotherapy and targeted therapy, we hypothesized that allogeneic cellular immunotherapies, including alloSCT and donor lymphocyte infusion (DLI), would impact malignant evolution through the application of selective immunologic pressure with reciprocal changes in the T cell compartment. We tested a cohort of 24 patients treated with HLA-matched alloSCT +/- DLI, two mediators of the graft versus leukemia (GVL) effect. Comparison of pre-alloSCT samples revealed that a key difference between responders (n=13) and non-responders (n=11) is the cellularity of leukemic cells. We further mapped mutational trajectories of tumor cells by whole exome sequencing (WES) of sort-purified CLL in 11 post-transplant relapsed patients and found evidence of subclonal leukemic evolution in 8/11 patients after nonmyeloablative human leukocyte antigen (HLA)-matched alloSCT. Different patterns of CLL evolution were observed, and these changes included putative CLL drivers in every case. To investigate the presence of immune-related variants in patients, we collected 19 T cell co-culture CRISPR datasets and identified the top positive and negative regulators of cancer cells response to T-cell-dependent killing. We found that most mutations linked to T-cell killing emerged after allo-SCT treatment, suggesting that selective pressures from the GVL effect may drive the evolution of these mutations. Together, these data identify cellular homogeneity as a key biomarker for susceptibility to GVL-driven immunity in CLL and illustrate how the leukemic cells further evolve to evade immunosurveillance. SIGNIFICANCEThe impact of allogeneic stem cell transplant (alloSCT) on subclonal leukemia evolution remains poorly understood. By performing whole exome sequencing (WES) on pre- and post-alloSCT patient samples, we reveal different patterns of CLL evolution and potential immune-related driver genes influencing CLL relapse and refractory disease post-alloSCT.

cancer biology↗
bioRxiv2025

Mitoxantrone inhibits and downregulates ERα through binding at the DBD-LBD interface

Targeting the estrogen receptor (ER or ER) through competitive antagonists, receptor downregulators, or estrogen synthesis inhibition remains the primary therapeutic strategy for luminal breast cancer. We have identified a novel mechanism of ER inhibition by targeting the critical interface between its DNA-binding domain (DBD) and ligand-binding domain (LBD). We demonstrate that mitoxantrone (MTO), a topoisomerase II inhibitor, binds at this previously unexplored DBD-LBD interface. Using comprehensive computational, biophysical, biochemical, and cellular analyses, we show that independent of its DNA damage response activity, MTO binding induces distinct conformational changes in ER, leading to its cytoplasmic redistribution and subsequent proteasomal degradation. Notably, MTO effectively inhibits clinically relevant ER mutations (Y537S and D538G) that confer resistance to current endocrine therapies, outperforming fulvestrant in both in vitro and in vivo assays. Our findings establish domain-domain interaction targeting as a viable therapeutic strategy for ER, with translational implications for other nuclear receptors.

cancer biology↗
bioRxiv2024

Virological and antigenic characteristics of SARS-CoV-2 variants LF.7.2.1, NP.1, and LP.8.1

XEC and KP.3.1.1 have surpassed KP.3 to become the globally dominant lineages due to their unique NTD mutations. However, several emerging JN.1 sublineages, such as LF.7.2.1, MC.10.1, NP.1, and, especially, LP.8.1, have demonstrated superior growth advantages compared to XEC. It is critical to access the virological and antigenic characteristics of these emerging SARS-CoV-2 variants. Here, we found that LF.7.2.1 is significantly more immune invasive than XEC, primarily due to the A475V mutation, which enabled the evasion of Class 1 neutralizing antibodies. However, LF.7.2.1s weak ACE2 binding affinity substantially impaired its fitness. Likewise, MC.10.1 and NP.1 exhibited strong antibody immune evasion due to the A435S mutation, but their limited ACE2 engagement efficiency restricted their growth advantage, suggesting that A435S may regulate the Spike conformation, similar to the NTD glycosylation mutations found in KP.3.1.1 and XEC. Most importantly, we found that LP.8.1 showed comparable humoral immune evasion to XEC but demonstrated much increased ACE2 engagement efficiency, supporting its rapid growth. These findings highlight the trade-off between immune evasion and ACE2 engagement efficiency in SARS-CoV-2 evolution, and underscore the importance of monitoring LP.8.1 and its descend lineages.

immunology↗
bioRxiv2024

A Systematic Comparison of Single-Cell Perturbation Response Prediction Models

Predicting single-cell transcriptional responses to perturbations is central to dissecting gene regulation and accelerating therapeutic design, yet the field lacks a rigorous, task-spanning assessment of model behavior. We present a large-scale benchmark of 13 representative methods and baselines across 25 datasets spanning diverse perturbation modalities and species, including two primary immune-cell drug-response resources. We evaluated three core tasks--generalization to unseen single-gene perturbations, prediction of combinatorial interactions, and transfer across cell types--using 24 metrics covering expression-level accuracy, relative changes, differential expression recovery, and distributional similarity. Across tasks, performance depended strongly on perturbation effect size and evaluation perspective: expression-level agreement was highest for small-effect perturbations resembling controls, whereas delta- and DE-based metrics improved with larger effects, providing clearer signals. Models shared a conservative bias, with fine-tuned foundation models compressing variance and underestimating synergistic effects in combinations. PerturbNet showed superior recovery of DE signatures in Tasks 1 and 2, while no method consistently generalized across cell types in Task 3, where biological consistency dominated outcomes. This benchmark establishes current methodological limits, clarifies that different metrics probe distinct biological signals rather than redundant summaries of the same prediction problem, and provides a foundation for developing virtual-cell models that more faithfully capture heterogeneous perturbation responses. Teaser: A large-scale benchmark reveals strengths and limits of models predicting single-cell perturbation responses.

bioinformatics↗
bioRxiv2024

Phosphotyrosine Signal Profiling of Clinical CAR-T Reveals Tonic Signaling Associated with Therapeutic Efficacy

Chimeric Antigen Receptor T (CAR-T) therapies have revolutionized the treatment of cancers such as relapsed and refractory B cell malignancies. However, the precise therapeutic mechanism of CAR-T action remain to be elucidated. In this study, we systematically analyzed CAR signaling via phosphotyrosine (pTyr) proteomics in CAR-T cells from both clinical patients and healthy donors. We found that CAR-T products from clinical patients displayed heightened tyrosine phosphorylation, particularly in the JAK-STAT, MAPK and TCR signaling cascades. We also identified the significantly regulated pTyr sites in primary CAR-T cells under tonic signaling or upon stimulation by antigen-presenting CD19-K562 cells. Although both CD28{zeta} and 4-1BB{zeta} CAR-T cells exhibited comparable pTyr changes, CD28{zeta} CAR-T cells displayed a more pronounced activation in the TCR signaling pathway. Additionally, comparative analysis between clinical and primary CAR-T cells suggested that CAR-T products were subject to heightened tonic signaling, which may be related to therapeutic relapse. Our findings reveal the state of clinical CAR-T products and refine the CAR-T signal transduction network, providing comprehensive insights and informed guidance for CAR-T therapies.

immunology↗
bioRxiv2024

Integrative Omics reveals genetic basis and TaMYB7-A1's function in wheat WUE and drought resilience

Improving water use efficiency (WUE) and drought resistance in wheat is critical for ensuring global food security under changing climate conditions. Here, we integrated multi-omic data, including population-scale phenotyping, transcriptomics, and genomics, to dissect the genetic and molecular mechanisms underlying WUE and drought resilience in wheat. Genome-wide association studies (GWAS) revealed 8,135 SNPs associated with WUE-related traits, identifying 258 conditional and non-conditional QTLs, many of which co-localized with known drought-resistance genes. Pan-transcriptome analysis uncovered tissue-specific expression patterns, core and unique gene functions, and dynamic sub-genomic biases in response to drought. eQTL mapping pinpointed 146,966 regulatory loci, including condition-specific hotspots enriched for genes involved in water regulation, osmoregulation, and photosynthesis. Integration of Weighted gene co-expression network analysis (WGCNA), Summary-data-based Mendelian Randomization (SMR) and GWAS, eQTLs identified 207 candidate causal genes as key regulators for WUE-related traits in wheat, such as TaMYB7-A1. Functional analyses found that TaMYB7-A1 enhances drought tolerance by promoting root growth, reducing oxidative stress, and improving osmotic regulation, enabling better water access and survival under stress. It also increases photosynthesis efficiency and WUE, boosting yield under drought without compromising performance in well-watered conditions, making it ideal target for breeding. Our findings provide a comprehensive omic framework for understanding the genetic architecture of WUE and drought resistance, offering valuable targets for breeding resilient wheat varieties.

plant biology↗
bioRxiv2024

Regulation of Fungal Morphology, Conidiogenesis and Violet Pigment Synthesis by the Betalain Biosynthesis Pathway Genes in Aspergillus sydowii H-1

The biosynthesis of antioxidant pigments, namely, betalains, has predominantly been found in Caryophyllales. The potential betalains biosynthesis was firstly explored in Aspergillus sydowii H-1 under controlled culture conditions. This study identified, knocked out, and overexpressed genes involved in the betanin biosynthesis and assessed the activities of tyrosinase, 45-DOPA dioxygenase and LigB. The results indicated these betanin biosynthesis pathway was crucial for colony morphology, conidiogenesis, stress response, and violet pigment synthesis. Moreover, AsDODA and AsLigB catalyzed the conversion of L-DOPA into 45-seco-DOPA, a key intermediate in the formation of betalamic acid in vitro. Additionally, transcription factors such as AsbHLH, AsMYB1R, and AsWD40 positively regulated the expression of betalain biosynthesis genes. This research provides new insights into the evolutionary origins of betalain-producing species, expanding the scope of betalain biosynthesis to include Aspergillus species. ImportanceTo date, betalains were restricted to plants of the order Caryophyllales, fungi of Basidiomycota and several types of bacteria. This study is the first to demonstrate the potential of Ascomycetes A. sydowii H-1 to synthesize betalains under controlled culture conditions, providing a detailed genetic and biological characterization of the associated genes and metabolic pathways. This finding demonstrates that betalain biosynthesis can be expanded to other Aspergillus.

microbiology↗
bioRxiv2024

Identification of Differentially Expressed Genes and Proteins Related to Diapause in Lymantria Dispar: Insights for the Mechanism of Diapause from Transcriptome and Proteome Analyses

Spongy moth (Lymantria dispar Linnaeus) is a globally recognized quarantine leaf-eating pest. Spongy moths typically enter diapause after completing embryonic development and overwinter in the egg stage. They spend three-quarters of their life cycle (approximately nine months) in the egg stage, which requires a period of low-temperature stimulation to break diapause and continue growth and development. In this study, we explored the molecular mechanism underlying the diapause process in spongy moth. We performed bioinformatics analysis on four Asian populations of spongy moth and one Asian-European hybrid population through a transcriptome analysis combined with proteomics. The results revealed that 1,842 genes were differentially expressed upon diapause initiation, while 264 genes were identified upon diapause termination. Eight diapause-related genes were screened out from the three-level pathways that were significantly enriched by differentially expressed genes at the time of diapause and diapause termination, and the phylogenetic tree and protein three-dimensional structure model were constructed. This study elucidates the diapause mechanism of spongy moth at the gene and protein levels, providing theoretical insights into the early and precise prevention and control of spongy moth. This study can facilitate the development of an efficient, environmentally friendly control system for managing spongy moth populations in the field.

genomics↗
bioRxiv2024

Machine learning reveals novel targets for both glioblastoma and osteosarcoma

Glioblastoma and osteosarcoma originate from the same lineage, yet patients with these two tumour types show significant differences in survival outcomes. Transcriptomic analysis comparing these tumours reveals that over 65% genes show similar expression patterns. Principal component analysis further demonstrates substantial similarities between these two tumour types, albeit with discernible differences. Deep learning analysis employing an autoencoder unveils nuanced distinctions and similarities of these two tumours at a high resolution. A classification model, leveraging gradient boosting with eXtreme Gradient Boosting (XGBoost), achieves high accuracy in distinguishing between these two tumour types. Identification of key contributors to the models performance is facilitated by SHapley Additive exPlanations (SHAP), yielding two lists of top target genes with and without considering gender. Notably, these SHAP targets tend to cluster within one or two networks of signalling pathways. Remarkably, gene expression levels of many of these SHAP targets alone can recapitulate survival differences solely based on clinical data between glioblastoma and osteosarcoma patients. Of particular interest, C2ORF72 emerges as a common target from both lists, representing an uncharacterised protein with promising potential as a novel target for diagnostic, prognostic, and therapeutic target for both glioblastoma and osteosarcoma.

genomics↗
bioRxiv2024

Hope for Others: Research Results from the University of Pittsburgh Rapid Autopsy Program for Breast Cancer

Breast cancer affects 1/8 of women throughout their lifetimes, with over 90% of cancer deaths being caused by metastasis. However, metastasis poses unique challenges to research, as complex changes in the microenvironment in different metastatic sites and difficulty obtaining tissue for study hinder the ability to examine in depth the changes that occur during metastasis. Rapid autopsy programs thus fill a unique need in advancing metastasis research. Here, we describe our protocol and processes for establishing and improving the US-based Hope for OTHERS (Our Tissue Helping Enhance Research and Science) program for organ donation in metastatic breast cancer. As of August 2024, we consented 114 patients and performed 37 autopsies, from which we collected 551 unique metastatic frozen tumor samples, 1244 FFPE blocks, 90 longitudinal liquid biopsy samples and developed 14 patient-derived organoid and 8 patient-derived xenograft models. We report in-depth clinical and histopathological information and discuss extensive new research and novel findings in patient outcomes, metastatic phylogeny, and factors in successful living model development. Our results reveal key logistical and protocol improvements that are uniquely beneficial to certain programs based on identifiable features, such as working closely with patient advocates, methods to rescue RNA quality in cases where tissue quality may degrade due to time delays, as well as guidelines and future expansions of our program. Statement of SignificanceRapid autopsy programs are unique research settings with huge potential for studying metastatic cancer, however, they have complex research challenges. Our work provides a valuable resource in advancing this field of research.

cancer biology↗
bioRxiv2024

Enhanced immune evasion of SARS-CoV-2 KP.3.1.1 and XEC through NTD glycosylation

KP.3.1.1 has surpassed KP.3 to become the new globally dominant strain, while XEC, a recombinant variant of KS.1.1/KP.3.3, is rapidly expanding across Europe and North America. Notably, both variants carry mutations, S31del of KP.3.1.1 and T22N of XEC, that could introduce new N-linked glycans on the Spike N-terminal domain (NTD), emphasizing the urgent need to assess their potential changes in viral characteristics. Here, we found that both KP.3.1.1 and XEC maintained the high ACE2-Spike binding affinity and pseudovirus infectivity of KP.3. Importantly, compared to KP.3, KP.3.1.1, and especially XEC, could further evade the neutralizing antibodies in convalescent plasma, even those elicited by KP.2-like breakthrough infections. Interestingly, both variants demonstrated increased resistance against monoclonal neutralizing antibodies targeting various epitopes on the receptor-binding domain (RBD). These suggest that the additional NTD glycosylation of KP.3.1.1 and XEC could enhance immune evasion via allosteric effects, and supports the future prevalence of XEC.

immunology↗
bioRxiv2024

Inter-Kingdom Interactions and Environmental Influences on the Oral Microbiome in Severe Early Childhood Caries

Dental caries arise from intricate interactions among oral microorganisms, impacting ecological stability and disease progression. This study delves into the bacterial-fungal dynamics in severe early childhood caries (S-ECC) among 61 children aged 3-4 years with complete deciduous dentition. We evaluated environmental factors such as saliva pH, buffering capacity, and trace elements (iron, fluoride). We examined the performance of 16S rRNA V1-V9 regions gene and internal transcribed spacer (ITS) primers for bacteria and fungi from plaque and saliva to characterize community compositions and diversity. Saliva pH and buffering capacity were also measured. Findings revealed significant shifts in bacterial diversity in S-ECC saliva samples, marked by decreased diversity and elevated abundance of cariogenic species, particularly Streptococcus mutans. Candida albicans was notably more prevalent in the S-ECC group, implicating its potential role in pathogenesis. Iron and fluoride concentrations showed no significant correlation with microbial community structure. Network analyses uncovered complex intra- and inter-kingdom interactions, underscoring cooperative and competitive dynamics. S-ECC children exhibited higher abundances of bacteria (Streptococcus mutans, Granulicatella, Actinomyces) and fungi (Candida albicans), with specific microbial taxa associated with reduced saliva pH. ImportanceThis study illuminates the intricate relationship between bacteria and fungi within the oral microbial community of children, specifically highlighting differences between those with severe early childhood caries (S-ECC) and those without caries. Through an extensive analysis of the microbial composition in both saliva and dental plaque, we identified a significant increase in the abundance of specific bacterial taxa (e.g., S. mutans, Granulicatella, Actinomyces) and fungal species (e.g., C. albicans) in the oral cavities of children with S-ECC. This finding underscores the potential role of these microorganisms in the development of caries. Contrary to previous studies that emphasize the importance of iron and fluoride in oral health, our research found no significant correlation between the concentrations of these elements and the composition of oral microbial communities. This result challenges conventional understanding and opens new avenues for future research. Additionally, we discovered an association between certain microbial species and reduced salivary pH, offering fresh insights into the relationship between the oral microenvironment and caries development. The implications of our findings are substantial for the development of prevention and intervention strategies targeting childhood caries. They also underscore the critical need for a deeper exploration of oral microbial interactions and their environmental influences.

microbiology↗
bioRxiv2024

Generative machine learning of ADAR substrates for precise and efficient RNA editing

Adenosine Deaminase Acting on RNA (ADAR) converts adenosine to inosine within certain double-stranded RNA structures. However, ADARs promiscuous editing and poorly understood specificity hinder therapeutic applications. We present an integrated approach combining high-throughput screening (HTS) with generative deep learning to rapidly engineer efficient and specific guide RNAs (gRNAs) to direct ADARs activity to any target. Our HTS quantified ADAR-mediated editing across millions of unique gRNA sequences and structures, identifying key determinants of editing outcomes. We leveraged these data to develop DeepREAD (Deep learning for RNA Editing by ADAR Design), a diffusion-based model that elucidates complex design rules to generate novel gRNAs outperforming existing design heuristics. DeepREADs gRNAs achieve highly efficient and specific editing, including challenging multi-site edits. We demonstrate DeepREADs therapeutic potential by designing gRNAs targeting the MECP2R168X mutation associated with Rett syndrome, achieving both allelic specificity and species cross-reactivity. This approach significantly accelerates the development of ADAR-based RNA therapeutics for diverse genetic diseases.

bioengineering↗
bioRxiv2024

Shape transformation of vesicles induced by orientational arrangement of membrane proteins

Vesicles of lipid bilayer can adopt a variety of shapes due to different coating proteins. The ability of proteins to reshape membrane is typically characterized by inducing spontaneous curvature of the membrane at the coated area. BAR family proteins are known to have a crescent shape and can induce membrane curvature along its concaved body axis but not in the perpendicular direction. We model this type of proteins as a rod-shaped molecule with an orientation and induce normal curvature along its orientation in the tangential plane of the membrane surface. We show how a ring of these proteins reshape an axisymmetric vesicle when the protein curvature or orientation is varied. A discontinuous shape transformation from a protrusion shape without a neck to a one with a neck is found. Increasing the rigidity of the protein ring is able to smooth out the transition. Furthermore, we show that varying the protein orientation is able to induce an hourglass-shaped neck, which is significantly narrower than the reciprocal of the protein curvature. Our results offer a new angle to rationalize the helical structure formed by many proteins that carry out membrane fission functions.

biophysics↗
bioRxiv2024

Mitigating Cellular Dysfunction by Addressing Contaminants in Synthetic circRNA

Synthetic circular RNA (circRNA) shows great potential in biomedical research and therapies, but impurities introduced during its synthesis can undermine circRNA efficacy. This study investigated the immunogenic potential of byproducts generated during its production. We found that trace amounts of double-stranded RNA in high molecular weight impurities, 5 triphosphates of uncircularized RNA or small intron fragments, and hydrolyzed RNA fragments significantly impact the functionality of circRNA by activating innate immune responses through the sensory molecules involved in RNA sensing. To address this, we developed a novel multi-step purification process that employs enzymatic treatments and cellulose-based filtration to selectively remove these detrimental contaminants. This tailored approach minimizes cellular immune reactions and substantially improves circRNA yields with up to more than 10 times increase. Our findings underscore the critical impact of precise contaminant management in enhancing the expression and potential therapeutic utility of circRNA. This suggests a new direction for optimizing their production for both research and clinical applications.

bioengineering↗
bioRxiv2024

Functional Roles of Sensorimotor Alpha and Beta Oscillations in Overt Speech Production

Power decreases, or desynchronization, of sensorimotor alpha and beta oscillations (i.e., alpha and beta ERD) have long been considered as indices of sensorimotor control in overt speech production. However, their specific functional roles are not well understood. Hence, we first conducted a systematic review to investigate how these two oscillations are modulated by speech motor tasks in typically fluent speakers (TFS) and in persons who stutter (PWS). Eleven EEG/MEG papers with source localization were included in our systematic review. The results revealed consistent alpha and beta ERD in the sensorimotor cortex of TFS and PWS. Furthermore, the results suggested that sensorimotor alpha and beta ERD may be functionally dissociable, with alpha related to (somato-)sensory feedback processing during articulation and beta related to motor processes throughout planning and articulation. To (partly) test this hypothesis of a potential functional dissociation between alpha and beta ERD, we then analyzed existing intracranial electroencephalography (iEEG) data from the primary somatosensory cortex (S1) of picture naming. We found moderate evidence for alpha, but not beta, ERDs sensitivity to speech movements in S1, lending supporting evidence for the functional dissociation hypothesis identified by the systematic review.

neuroscience↗
bioRxiv2024

A community-oriented, data-driven resource to improve protocol design for cardiac modelling from human pluripotent stem cells

Protocol design and benchmarking is central to optimising model development using human pluripotent stem cell derived cardiomyocytes (hPSC-CMs). By applying data mining to decades of research and hundreds of peer reviewed studies, we evaluate how protocol variables associate with common properties of cardiac functional and physiological maturation. This resource is publicly accessible through CMPortal, a community-oriented website that provides data-driven tools for researchers to navigate leverage decades of knowledge for benchmarking protocol designs and outcomes for their dedicated applications in developmental biology, disease modelling, and drug screening.

developmental biology↗