Biology subjects

Li, S.

Publications and source records attributed to Li, S..

At least 559 records · Page 31Linked to original sources

bioRxiv2024

Digital Immunoassay for Rapid Detection of SARS-CoV-2 Infection in a Broad Spectrum of Animals

The ability of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) to infect a wide-range of species raises significant concerns regarding both human-to-animal and animal-to-human transmission. There is an increasing demand for highly sensitive, rapid, and simple diagnostic assays that can detect viral infection across various species. In this study, we developed a biosensor assay that adapted a monoclonal-antibody (mAb)-based blocking ELISA format into an Activate Capture + Digital Counting (AC + DC)-based immunoassay. The assay employs a photonic crystal (PC) biosensor, gold-nanoparticle (AuNP) tags, SARS-CoV-2 nucleocapsid (N) protein, and specific anti-N mAb to detect antibody responses in animals exposed with SARS-CoV-2. We demonstrated a simple 2-step 15-min test that was capable of detecting as low as 12.5 ng of antibody in controlled standard serum samples. Based on an evaluation of 176 cat serum samples with known antibody status, an optimal percentage of inhibition (PI) cut-off value of 0.588 resulted in a diagnostic sensitivity of 98.3% and a diagnostic specificity of 96.5%. The test is highly repeatable with low variation coefficients of 2.04%, 2.73%, and 4.87% across different runs, within a single run, and on a single chip, respectively. The test was further employed to detect antibody responses in multiple animal species as well as investigate dynamics of antibody response in experimentally infected cats. This test platform provides an important tool for rapid field surveillance of SARS-CoV-2 infection across multiple species.

microbiology↗

bioRxiv2024

Molecular basis of Ad5-nCoV Vaccine-Induced Immunogenicity

In response to coronavirus disease 2019 (COVID-19), numerous vaccines have been developed to protect against SARS-CoV-2 infection. Ad5-nCoV (Convidecia) is a vaccine listed for emergency use by the WHO and has been administrated to millions of people globally. It comprises a series of human adenovirus 5 (Ad5) replication-incompetent vectored vaccines that transduce the spike protein (S) gene of various SARS-CoV-2 strains. Despite promising clinical data demonstrating its safety and effectiveness, the underlying molecular mechanism of its high immunogenicity and incidence of adverse reactions remains less understood. Here we combined cryo-ET, fluorescence microscopy and mass spectrometry to characterize the in situ structures, density and site-specific glycan compositions of the Ad5-nCoV_Wu and Ad5-nCoV_O vaccine-induced S antigens, which encode the unmodified SARS-CoV-2 Wuhan-Hu-1 S gene and optimized Omicron S gene, respectively. We found that the vaccine-induced S are structurally intact, antigenic and densely distributed on the cell membrane. Compared to Ad5-nCoV_Wu induced S, the Ad5-nCoV_O induced S demonstrate significantly better stability and is less likely to induce syncytia among inoculated cells. Our work demonstrated that Ad5-nCoV is a prominent platform for antigen induction and cryo-ET can be a useful technique for vaccine characterization and development.

biophysics↗

bioRxiv2024

Multi-dimensionality of tree communities structure host-parasitoid networks and their phylogenetic composition

Environmental factors can influence ecological networks, but these effects are poorly understood in the realm of the phylogeny of host-parasitoid interactions. Especially, we lack a comprehensive understanding of the ways that biotic factors, including plant species richness, overall community phylogenetic and functional composition of consumers, and abiotic factors such as microclimate, determining host-parasitoid network structure and host-parasitoid community dynamics. To address this, we leveraged a five-year dataset of trap-nesting bees and wasps and their parasitoids collected in a highly-controlled, large-scale subtropical tree biodiversity experiment. We tested for effects of tree species richness, tree phylogenetic and functional diversity, and species and phylogenetic composition on species and phylogenetic diversity of both host and parasitoid communities and the composition of their interaction networks. We show that multiple components of tree diversity and canopy cover impacted both, species and phylogenetic composition of hosts and parasitoids. Generally, phylogenetic associations between hosts and parasitoids reflected non-randomly structured interactions between phylogenetic trees of hosts and parasitoids. Further, host-parasitoid network structure was influenced by tree species richness, tree phylogenetic diversity, and canopy cover. Our study indicates that the composition of higher trophic levels and corresponding interaction networks are determined by plant diversity and canopy cover especially via trophic links in species-rich ecosystems.

ecology↗

bioRxiv2024

The continuous differentiation of multiscale structural gradients from childhood to adolescence correlates with the maturation of cortical morphology and functional specialization

From childhood to adolescence, the structural organization of the human brain undergoes dynamic and regionally heterogeneous changes across multiple scales, from synaptic pruning to the reorganization of large-scale anatomical wiring. However, during this period, the developmental process of multiscale structural architecture, its association with cortical morphological changes, and its role in the maturation of functional organization remain largely unknown. Here, we utilized a longitudinal multimodal imaging dataset including 276 children aged 6 to 14 years to investigate the developmental process of multiscale cortical wiring. We used an in vivo model of cortical wiring that combines features of white matter tractography, cortico-cortical proximity, and microstructural similarity to construct a multiscale brain structural connectome. By employing the gradient mapping method, the gradient space derived from the multiscale structural connectome effectively recapitulated the sensory-association axis and anterior-posterior axis. Our findings revealed a continuous expansion of the multiscale structural gradient space during development, with the principal gradient increasingly distinguishing between primary and transmodal regions. This age-related differentiation coincided with regionally heterogeneous changes in cortical morphology. Furthermore, our study revealed that developmental changes in coupling between multiscale structural and functional connectivity were correlated with functional specialization refinement, as evidenced by changes in the participation coefficient. We also found that the differentiation of the principal multiscale structural gradient was associated with improved cognitive abilities, such as enhanced working memory and attention performance, and potentially supported by molecular processes related to synaptic functions. These findings advance our understanding of the intricate maturation process of brain structural organization and its implications for cognitive performance.

neuroscience↗

bioRxiv2024

Inferring single-cell spatial gene expression with tissue morphology via explainable deep learning

Deep learning models trained with spatial omics data uncover complex patterns and relationships among cells, genes, and proteins in a high-dimensional space. State-of-the-art in silico spatial multi-cell gene expression methods using histological images of tissue stained with hematoxylin and eosin (H&E) allow us to characterize cellular heterogeneity. We developed a vision transformer (ViT) framework to map histological signatures to spatial single-cell transcriptomic signatures, named SPiRiT. SPiRiT predicts single-cell spatial gene expression using the matched H&E image tiles of human breast cancer and whole mouse pup, evaluated by Xenium (10x Genomics) datasets. Importantly, SPiRiT incorporates rigorous strategies to ensure reproducibility and robustness of predictions and provides trustworthy interpretation through attention-based model explainability. SPiRiT model interpretation revealed the areas, and attention details it uses to predict gene expressions like marker genes in invasive cancer cells. In an apple-to-apple comparison with ST-Net, SPiRiT improved the predictive accuracy by 40%. These gene predictions and expression levels were highly consistent with the tumor region annotation. In summary, SPiRiT highlights the feasibility to infer spatial single-cell gene expression using tissue morphology in multiple-species.

bioinformatics↗

bioRxiv2024

Single-Cell Transcriptomic Analysis Highlights Specific Cell Types of Wheat Manipulated by Fusarium graminearum Leading to Susceptibility

Phytopathogenic fungi can be recognized by the plant immune system and trigger host defenses, but adapted pathogens cause susceptibility. How different cell types cooperate and orchestrate biological processes in response to heterogeneous colonization of organs by adapted and non-adapted pathogens remains largely unknown. Here we employed single-cell RNA sequencing to dissect the responses of wheat coleoptiles to infection by the adapted fungal pathogen Fusarium graminearum (Fgr) and the non-adapted fungal pathogen Fusarium oxysporum f. sp. cubense (Foc) at 1-, 2-, and 3-days post-inoculation. We profiled the transcriptomes of over 90,000 cells and identified eight major cell types in coleoptiles: stomata, epidermis, chlorenchyma, parenchyma, outer sheath, inner sheath, phloem, and procambium. Differential expression analyses showed that the capacity of different cell types to respond to fungal infection varied. The upregulation of immune pathways was compartmentalized in nonhost resistance to Foc, but widespread in susceptible interaction with Fgr. Pseudotime analyses revealed continuous cell state transitions in the disease progression of infected cell types. Our work indicates that the phloem and outer sheath are specific cell types that collaborate for the rapid onset of nonhost resistance. Fgr induces a state of low transcriptional activity in the chlorenchyma. Cell trajectory analysis suggests that the competition between immune and susceptible processes in parenchyma results in specific cell states that are favored by the adapted pathogen Fgr. Overall, this work explains how cell types collaborate and are manipulated during fungal infections, providing insight into the intercellular mechanisms of plant immunity.

plant biology↗

bioRxiv2024

Critical assessment of missense variant effect predictors on disease-relevant variant data

Regular, systematic, and independent assessment of computational tools used to predict the pathogenicity of missense variants is necessary to evaluate their clinical and research utility and suggest directions for future improvement. Here, as part of the sixth edition of the Critical Assessment of Genome Interpretation (CAGI) challenge, we assess missense variant effect predictors (or variant impact predictors) on an evaluation dataset of rare missense variants from disease-relevant databases. Our assessment evaluates predictors submitted to the CAGI6 Annotate-All-Missense challenge, predictors commonly used by the clinical genetics community, and recently developed deep learning methods for variant effect prediction. To explore a variety of settings that are relevant for different clinical and research applications, we assess performance within different subsets of the evaluation data and within high-specificity and high-sensitivity regimes. We find strong performance of many predictors across multiple settings. Meta-predictors tend to outperform their constituent individual predictors; however, several individual predictors have performance similar to that of commonly used meta-predictors. The relative performance of predictors differs in high-specificity and high-sensitivity regimes, suggesting that different methods may be best suited to different use cases. We also characterize two potential sources of bias. Predictors that incorporate allele frequency as a predictive feature tend to have reduced performance when distinguishing pathogenic variants from very rare benign variants, and predictors supervised on pathogenicity labels from curated variant databases often learn label imbalances within genes. Overall, we find notable advances over the oldest and most cited missense variant effect predictors and continued improvements among the most recently developed tools, and the CAGI Annotate-All-Missense challenge (also termed the Missense Marathon) will continue to assess state-of-the-art methods as the field progresses. Together, our results help illuminate the current clinical and research utility of missense variant effect predictors and identify potential areas for future development.

genetics↗

bioRxiv2024

Expression of a single inhibitory Ly49 receptor is sufficient to license NK cells for effector functions

Natural killer (NK) cells recognize target cells through germline-encoded activation and inhibitory receptors enabling effective immunity against viruses and cancer. The Ly49 receptor family in the mouse and killer immunoglobin-like receptor family in humans play a central role in NK cell immunity through recognition of MHC class I and related molecules. Functionally, these receptor families are involved in licensing and rejection of MHC-I-deficient cells through missing-self. The Ly49 family is highly polymorphic, making it challenging to detail the contributions of individual Ly49 receptors to NK cell function. Herein, we showed mice lacking expression of all Ly49s were unable to reject missing-self target cells in vivo, were defective in NK cell licensing, and displayed lower KLRG1 on the surface of NK cells. Expression of Ly49A alone on a H-2Dd background restored missing-self target cell rejection, NK cell licensing, and NK cell KLRG1 expression. Thus, a single inhibitory Ly49 receptor is sufficient to license NK cells and mediate missing-self in vivo.

immunology↗

bioRxiv2024

Cold seeps are hotspots of deep-sea nitrogen-loss driven by microorganisms across 21 phyla

Nitrogen bioavailability, governed by the balance of fixation and loss processes, is a key factor regulating oceanic productivity, ecosystem functions, and global biogeochemical cycles. The key nitrogen-loss organisms--denitrifiers and anaerobic ammonium-oxidizing (anammox) bacteria--are not well understood in marine seafloor environments, especially in deep-sea cold seeps. In this study, we combined geochemical measurements, 15N stable isotope tracer analysis, metagenomics, metatranscriptomics, and three-dimensional protein structural simulations to investigate the diversity of denitrifying and anammox microbial communities and their biogeochemical roles in these habitats. Geochemical evidence from 301 sediment samples shows significantly higher nitrogen-loss rates in cold seeps compared to typical deep-sea sediments, with an estimated annual nitrogen loss of 6.16 Tg from seafloor surface sediments. Examination of a total of 147 million non-redundant genes reveals a high prevalence and active expression of nitrogen-loss genes, including nitrous-oxide reductase (NosZ; 6.88 genes per million or GPM on average), nitric oxide dismutase (Nod; 1.29 GPM), and hydrazine synthase (HzsA; 3.35 GPM) in surface sediments. Analysis of 3,164 metagenome-assembled genomes from this habitat has expanded the known diversity of nitrous-oxide reducers to six phyla and nitric oxide-dismutating organisms to one phylum and two new orders, while ten phyla host anammox bacteria going beyond Planctomycetota. These microbes show diverse structural adaptations and complex gene cluster arrangements that potentially enable survival in the harsh conditions of cold seeps. These findings suggest that cold seeps, despite their low temperatures, are significant, previously underestimated hotspots of nitrogen loss, potentially contribute substantially to the global nitrogen cycle.

microbiology↗

bioRxiv2024

Spatial Transcriptomics-Aided Localization for Single-Cell Transcriptomics with STALocator

Single-cell RNA-sequencing (scRNA-seq) techniques can measure gene expression at the single-cell resolution but lack spatial information. The spatial transcriptomics (ST) techniques simultaneously provide gene expression data and spatial information. However, the data quality on the spatial resolution or gene coverage is still much lower than the single-cell transcriptomics data. To this end, we develop a Spatial Transcriptomics-Aided Locator for single-cell transcriptomics (STALocator) to localize single cells to corresponding ST data. Applications on simulated data showed that STALocator performed better than other localization methods from different angles. When applied to human brain scRNA-seq data and dorsolateral prefrontal cortex 10x Visium data, STALocator could robustly reconstruct the laminar organization of layer-associated cell types. Applications on scRNA-seq data and Spatial Transcriptomics data of human squamous cell carcinoma illustrated that STALocator could robustly reconstruct the relative spatial relationship between tumor-specific keratinocytes, microenvironment-associated cell populations, and immune cells. Moreover, STALocator could enhance gene expression patterns for Slide-seqV2 data and predict genome-wide gene expression data for FISH data, leading to the identification of more spatially variable genes and more biologically relevant GO terms compared to raw data.

bioinformatics↗

bioRxiv2024

Enrichment of glycoRNAs using galactose oxidase, hydrazide chemistry, and glycosidase digestion

Ribonucleic acid (RNA), essential for protein production and immune function, undergoes glycosylation, a process that attaches carbohydrates to RNA, creating unique glycoRNAs. These sugar-coated RNA molecules regulate immune responses and may be related to immune disorders. However, studying them is challenging due to RNAs fragility. Therefore, a robust method for identifying glycosylated RNA is important. To address this, we optimized methods for enriching and identifying glycoRNAs, opening doors to explore their potential interactions with immune receptors and tumor suppression. Our approach involved investigating factors such as preservation solutions, enzyme buffers, digestion temperature, and incubation time. We successfully achieved efficient digestion of both N-linked and O-linked glycoRNAs at room temperature using 25 mM ammonium bicarbonate, demonstrating the effectiveness of this method. Additionally, RNA preservation in RNAlater at -80{degrees}C allows controlled release of glycoRNAs within hours. While sequential digestion of different glycoRNA types is possible, significant degradation occurs after the first enzyme step. Thus, we recommend separate harvesting for each type of glycoRNA. These optimized protocols, utilizing SPCgRNA and TnORNA methods, pave the way for further research on N- and O-glycoRNAs in health and disease.

biochemistry↗

bioRxiv2024

A longitudinal atlas of post-viral lung regeneration reveals persistent injury-associated cell states

Functional regeneration of the lungs gas exchange surface following injury requires the coordination of a complex series of cell behaviors within the alveolar niche. Using a multi-modal approach, we have mapped the temporal sequencing of mouse lung regeneration after acute viral injury, demonstrating that this response is asynchronously phased across different cellular compartments. This longitudinal atlas of regeneration has produced a catalogue of new cell states that reflect transient and persistent transcriptional alterations in daughter cells as they transit across axes of differentiation. These new cell states include an injury-induced capillary endothelial cell (iCAP) that arises after injury, persists indefinitely, and shares transcriptional hallmarks with both developing lung endothelium and the endothelial aberrations found in degenerative human lung diseases. This comprehensive atlas of lung regeneration provides a foundational resource to understand the complexity of the cellular and molecular responses to injury, reveals the critical importance of capillary endothelium in maintaining and rebuilding the alveolar niche after injury, and correlates these responses to those found in development and human lung diseases.

cell biology↗

bioRxiv2024

Causal network perturbation analysis identifies known and novel type-2 diabetes driver genes

The molecular pathogenesis of type 2 diabetes mellitus (T2DM) involves environmental and genetic factors that remain poorly understood. Increased insulin resistance leads to pancreatic {beta}-islet cell exhaustion and failure, leading to more severe T2DM. As such, targeting {beta}-cell dysfunction is an attractive pathway for T2DM treatment. Single-cell RNA sequencing can help identify differentially expressed genes (DEGs) that may contribute to disease-associated pathophysiology, but cannot capture the full spectrum of disease pathophysiology, as some genes that are not differentially expressed may still play important roles in disease progression or mechanisms. As such, we investigated single-cell gene expression changes in {beta}-cells from healthy (C57BL/6J) and diabetic (NZO/HlLtJ) mice fed with normal or high-fat, high-sugar diet (HFHS) across the spectrum of T2DM development (prediabetic, mild or severely diabetic) using an innovative integration of the causal network perturbation assessment (ssNPA) framework with meta-cell transcriptome analysis to identify driver genes for T2DM. By generating a reference causal network and conducting in silico perturbations, we identified three classes of genes implicated in T2DM pathophysiology: (1) DEGs that were not perturbed (e.g, Igf2bp2 strongly linked to {beta} cell dysfunction and glucose regulation), (2) perturbed non-DEGs (e.g., Glp1r a therapeutic target of modern diabetes drugs) that were perturbed, and (3) DEGs that were perturbed (e.g., Pdx1 a master {beta} cell transcription factor), and validated some of the targets using the KOMP database. Together, these results show that each analytic layer captures complementary mechanisms underlying T2DM severity, and their synthesis provides a more complete view of the disease pathophysiology.

bioinformatics↗

bioRxiv2024

A Peptide Derived from Sorting Nexin 1 Inhibits HPV16 Entry, Retrograde Trafficking, and L2 Membrane Spanning

High risk human papillomavirus (HPV) infection is responsible for 99% of cervical cancers and 5% of all human cancers worldwide. HPV infection requires the viral genome (vDNA) to gain access to nuclei of basal keratinocytes of epithelium. After virion endocytosis, the minor capsid protein L2 dictates the subcellular retrograde trafficking and nuclear localization of the vDNA during mitosis. Prior work identified a cell-permeable peptide termed SNX1.3, derived from the BAR domain of sorting nexin 1 (SNX1), that potently blocks the retrograde and nuclear trafficking of EGFR in triple negative breast cancer cells. Given the importance of EGFR and retrograde trafficking pathways in HPV16 infection, we set forth to study the effects of SNX1.3 within this context. SNX1.3 inhibited HPV16 infection by both delaying virion endocytosis, as well as potently blocking virion retrograde trafficking and Golgi localization. SNX1.3 had no effect on cell proliferation, nor did it affect post-Golgi trafficking of HPV16. Looking more directly at L2 function, SNX1.3 was found to impair membrane spanning of the minor capsid protein. Future work will focus on mechanistic studies of SNX1.3 inhibition, and the role of EGFR signaling and SNX1-mediated endosomal tubulation, cargo sorting, and retrograde trafficking in HPV infection.

microbiology↗

bioRxiv2024

IP3R1 is required for meiotic progression and embryonic development by regulating mitochondrial calcium and oxidative damage

Calcium ions (Ca2+) regulate cell proliferation and differentiation and participate in various physiological activities of cells. The calcium transfer protein inositol 1,4,5-triphosphate receptor (IP3R), located between the endoplasmic reticulum (ER) and mitochondria, plays an important role in regulating Ca2+ levels. However, the mechanism by which IP3R1 affects porcine meiotic progression and embryonic development remains unclear. We established a model in porcine oocytes using siRNA-mediated knockdown of IP3R1 to investigate the effects of IP3R1 on porcine oocyte meiotic progression and embryonic development. The results indicated that a decrease in IP3R1 expression significantly enhanced the interaction between the ER and mitochondria. Additionally, the interaction between the ER and the mitochondrial Ca2+ ([Ca2+]m) transport network protein IP3R1-GRP75-VDAC1 was disrupted. PLA decreased IP3R1, weakened the pairwise interaction between IP3R1-GRP75 and VDAC1 and significantly enhanced the interaction between GRP75 and VDAC1, resulting in the accumulation of large amounts of [Ca2+]m. These changes led to mitochondrial oxidative stress and reduced ATP production, which hindered the maturation and late development of porcine oocytes and caused apoptosis.

cell biology↗

bioRxiv2024

Fate-mapping and functional dissection reveal perilous influence of type I interferon signaling in mouse brain aging

Although aging significantly elevates the risk of developing neurodegenerative diseases, how age-related neuroinflammation preconditions the brain toward pathological progression is ill-understood. To comprehend the scope of type I interferon (IFN-I) activity in the aging brain, we surveyed IFN-I-responsive reporter mice and detected age-dependent signal escalation in multiple brain cell types from various regions. Selective ablation of Ifnar1 from microglia in aged mice significantly reduced overall brain IFN-I signature, dampened microglial reactivity, lessened neuronal loss, and diminished the accumulation of lipofuscin, a core hallmark of cellular aging in the brain. Overall, our study demonstrates pervasive IFN-I activity during normal mouse brain aging and reveals a pathogenic role played by microglial IFN-I signaling in perpetuating neuroinflammation, neuronal dysfunction, and molecular aggregation. These findings extend the understanding of a principal axis of age-related inflammation in the brain, and provide a rationale to modulate aberrant immune activation to mitigate neurodegenerative process at all stages.

neuroscience↗

bioRxiv2024

CRISPR Double Knockout Library Reveals Synthetic Lethal Gene Pairs in Triple-Negative Breast Cancer

Synthetic lethality, a genetic interaction involving two or more genes whose combined loss results in cell death, has emerged as a promising strategy for targeted cancer therapy. By exploiting synthetic lethal interactions, cancer cells can be selectively targeted and eradicated while preserving healthy cells, minimizing off-target effects, and reducing toxicity. The development of PARP inhibitors for ovarian and breast cancer patients with BRCA mutations exemplifies the potential of synthetic lethality-based therapy. Various experimental approaches, including CRISPR/Cas9 screens, have been employed to identify synthetic lethal gene pairs. Our lab has developed a CRISPR double knockout library, leveraging the XDeathDB database for candidate gene selection. This comprehensive platform offers insights into 12 cell death modes and 149 cell death hallmark genes. We aim to construct a cell-death double knock-out library using these genes and perform double knock-out screening on MDA-MB-231, a representative cell line for TNBC chemo poor responders. The identified synergistic lethal gene pairs may serve as potential drug targets for treating TNBC.

cancer biology↗

bioRxiv2024

Identifying Novel Therapeutic Targets for Overcoming TNBC Chemo Resistance Through Comprehensive CRISPR-Cas9 Genome Screening

Triple-negative breast cancer (TNBC) represents 15-20% of cases but disproportionately contributes to 35% of breast cancer deaths. Chemotherapy resistance remains a significant challenge in TNBC treatment. In this study, we identified the MDA-MB-231 cell line as the most representative model for TNBC chemotherapy-poor responders by comparing genomic profiles from TNBC cell lines and patient samples. We performed a genome-wide CRISPR-Cas9 screen and RNAseq analysis in MDA-MB-231 cells to uncover potential synthetic lethal targets for cisplatin/doxorubicin treatment. Our analysis confirmed the involvement of known essential genes in DNA damage repair and regulation of DNA replication pathways, such as BCL2L1, ATM, CDC25B, and NBN, in sensitizing cells to cisplatin/doxorubicin. Additionally, We identified hundreds of previously unrecognized genes and pathways related to DNA repair, G2/M DNA damage checkpoint, AMPK signaling, and mTOR signaling. The observed differences between transcriptomic responses and essential pathways from the CRISPR screen suggest a complex regulatory system in cellular response to DNA damage drugs. By combining various data analysis methods and biological experimental approaches, we have pinpointed several promising genes, such as MCM9 and NEPPS, which could serve as potential drug targets to overcome chemoresistance. Overall, our approach efficiently identified essential genes with potential synthetic lethal interactions with cisplatin/doxorubicin, offering new possibilities for combination therapies in chemo resistant TNBC patients.

cancer biology↗