Standard chemotherapy impacts on in vitro cellular heterogeneity in spheroids enriched with cancer stem cells (CSCs) derived from triple-negative breast cancer cell line.

Triple-negative breast cancer is a heterogeneous disease with high recurrence and mortality, linked to cancer stem cells (CSCs). Our study characterized distinct cell subpopulations and signaling pathways to explore chemoresistance. We observed cellular heterogeneity among and within the cells regarding phenotyping and drug response. In untreated BT-549 cells, we noted plasticity properties in both CD44+/CD24+/CD146+ hybrid cells and CD44-/CD24+/CD146+ epithelial cells, enabling phenotypic conversion into CD44+/CD24-/CD146- epithelial-mesenchymal transition (EMT)-like like breast CSCs (BCSCs). Additionally, non-BCSCs may give rise to ALDH+ epithelial-like BCSCs. Enriched BCSCs demonstrated the potential to differentiation into CD44-/CD24-/CD146- cells and exhibited self-renewal capabilities. Similar phenotypic plasticity was not observed in untreated Hs 578T and HMT-3522 S1 cells. BT-549 cells were more resistant to paclitaxel/PTX than to doxorubicin/DOX, a phenomenon potentially linked to the presence of CD24+ cells prior to treatment. Under the CSCs-enriched spheroids model, BT-549 demonstrated extreme resistance to DOX, likely due to the enrichment of BCSCs CD44+/CD24-/CD146- and the tumor cells CD44-/CD24-/CD146-. Additionally, DOX treatment induced the enrichment of plastic and chemoresistant cells, further exacerbating resistance mechanisms. BT-549 exhibited high heterogeneity, leading to significant alterations in cell subpopulations under BCSCs enrichment, demonstrating increased phenotypic plasticity during EMT. This phenomenon appears to play a major role in DOX resistance, as indicated by the presence of the refractory cells CD44+/CD24-/CD146- BCSCs EMT-like, CD44-/CD24-/CD146- tumor cells, and elevated STAT3 expression. Gene expression data from BT-549 CSCs-enriched spheroids suggests that ferroptosis may be occurring via autophagic regulation triggered by RAB7A, highlighting this gene as a potential therapeutic target.

Single-cell RNA sequencing in endometrial cancer: exploring the epithelial cells and the microenvironment landscape.

Single-cell RNA sequencing (scRNA-seq) technology has emerged as a powerful tool for dissecting cellular heterogeneity and understanding the intricate biology of diseases, including cancer. Endometrial cancer (EC) stands out as the most prevalent gynecological malignancy in Europe and the second most diagnosed worldwide, yet its cellular complexity remains poorly understood. In this review, we explore the contributions of scRNA-seq studies to shed light on the tumor cells and cellular landscape of EC. We discuss the diverse tumoral and microenvironmental populations identified through scRNA-seq, highlighting the implications for understanding disease progression. Furthermore, we address potential limitations inherent in scRNA-seq studies, such as technical biases and sample size constraints, emphasizing the need for larger-scale research encompassing a broader spectrum of EC histological subtypes. Notably, a significant proportion of scRNA-seq analyses have focused on primary endometrioid carcinoma tumors, underscoring the need to incorporate additional histological and aggressive types to comprehensively capture the heterogeneity of EC. By critically evaluating the current state of scRNA-seq research in EC, this review underscores the importance of advancing towards more comprehensive studies to accelerate our understanding of this complex disease.

Insights into the Pathobiology of GM1 Gangliosidosis from Single-Nucleus Transcriptomic Analysis of CNS Cells in a Mouse Model.

GM1 gangliosidosis is a lysosomal storage disorder characterized by the accumulation of GM1 ganglioside, leading to severe neurodegeneration and early mortality. The disease primarily affects the central nervous system, causing progressive neurodegeneration, including widespread neuronal loss and gliosis. To gain a deeper understanding of the neuropathology associated with GM1 gangliosidosis, we employed single-nucleus RNA sequencing to analyze brain tissues from both GM1 gangliosidosis model mice and control mice. No significant changes in cell proportions were detected between the two groups of animals. Differential expression analysis revealed cell type-specific changes in gene expression in neuronal and glial cells. Functional analysis highlighted the neurodegenerative processes, oxidative phosphorylation, and neuroactive ligand-receptor interactions as the significantly affected pathways. The contribution of the impairment of neurotransmitter system disruption and neuronal circuitry disruption was more important than neuroinflammatory responses to GM1 pathology. In 16-week-old GM1 gangliosidosis mice, no microglial or astrocyte activation or increased expression of innate immunity genes was detected. This suggested that nerve degeneration did not induce the inflammatory response but rather promoted glial cell clearance. Our findings provide a crucial foundation for understanding the cellular and molecular mechanisms of GM1 gangliosidosis, potentially guiding future therapeutic strategies.

Dissecting SOX9 dynamics reveals its differential regulation in osteoarthritis.

The transcription factor SOX9 is integral to tissue homeostasis and is implicated in skeletal malformation, campomelic dysplasia, and osteoarthritis (OA). Despite extensive research, the complete regulatory landscape of SOX9 transcriptional activity, interconnected with signaling pathways (TGFß, WNT, BMP, IHH, NFκB, and HIF), remains challenging to decipher. This study focuses on elucidating SOX9 signaling in OA pathology using Fluorescence Recovery After Photobleaching (FRAP) to assess SOX9 activity directly in live human primary chondrocytes (hPCs). Single cell FRAP data revealed two distinct subpopulations with differential SOX9 dynamics, showing varied distribution between healthy and OA hPCs. Moreover, inherently elevated SOX9-DNA binding was observed in healthy hPCs compared to preserved and OA counterparts. Anabolic factors (BMP7 and GREM1) and catabolic inhibitors (DKK1 and FRZb) were found to modulate SOX9 transcriptional activity in OA-hPCs. These findings provide valuable insights into the intricate regulation of SOX9 signaling in OA, suggesting potential therapeutic avenues for modulating SOX9 activity in diseased states.

Deciphering the cellular landscape and potential targets of nasopharyngeal and oral cancers using single-cell RNA sequencing.

Cellular heterogeneity in nasopharyngeal cancer (NPC) and oral cancer remains unclear. In the current study, using single-cell RNA sequencing techniques, we investigated the cellular landscape in NPC and oral cancers. We identified a diverse range of cell types within the tumor microenvironment (TME) and variations in cell infiltration between NPC and oral cancer. In oral cancer, we observed a predominant infiltration of epithelial cells, fibroblasts, and endothelial cells (ECs), while T cells were the main infiltrating cell population in NPCs. We further classified these infiltrating cells into subclusters. Additionally, we observed complex interactions among cells that led to distinct trajectories. In particular, a unique epithelial subcluster with high expression of major histocompatibility complex class II (MHC-II) molecules was correlated with a favorable outcome and infiltration of CD4+ T cells. In addition, MHC-II+ epithelial cells inhibited mouse tumor growth and promoted T-cell infiltration. Consequently, our findings provide a deep understanding of the TME showing a significant prognostic value and therapeutic potential.

Comprehensive review on single-cell RNA sequencing: A new frontier in Alzheimer's disease research.

Alzheimer's disease (AD) is a multifaceted neurodegenerative condition marked by gradual cognitive deterioration and the loss of neurons. While conventional bulk RNA sequencing techniques have shed light on AD pathology, they frequently obscure the cellular diversity within brain tissues. The advent of single-cell RNA sequencing (scRNA-seq) has transformed our capability to analyze the cellular composition of AD, allowing for the detection of unique cell populations, rare cell types, and gene expression alterations at an individual cell level. This review examines the use of scRNA-seq in AD research, focusing on its contributions to understanding cellular diversity, disease progression, and potential therapeutic targets. We discuss key technological innovations, data analysis techniques, and challenges associated with scRNA-seq in studying AD. Furthermore, we highlight recent studies that have utilized scRNA-seq to identify novel biomarkers, uncover disease-associated pathways, and elucidate the role of non-neuronal cells, such as microglia and astrocytes, in AD pathogenesis. By providing a comprehensive overview of advancements in scRNA-seq for unraveling cellular heterogeneity in AD, this review highlights the transformative impact of scRNA-seq on our comprehension of disease mechanisms and the creation of targeted treatments.

Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes.

Single-cell analysis has become an essential tool in modern biological research, providing unprecedented insights into cellular behavior and heterogeneity. By examining individual cells, this approach surpasses conventional population-based methods, revealing critical variations in cellular states, responses to environmental cues, and molecular signatures. In the context of cancer, with its diverse cell populations, single-cell analysis is critical for investigating tumor evolution, metastasis, and therapy resistance. Understanding the phenotype-genotype relationship at the single-cell level is crucial for deciphering the molecular mechanisms driving tumor development and progression. This review highlights innovative strategies for selective cell isolation based on desired phenotypes, including robotic aspiration, laser detachment, microraft arrays, optical traps, and droplet-based microfluidic systems. These advanced tools facilitate high-throughput single-cell phenotypic analysis and sorting, enabling the identification and characterization of specific cell subsets, thereby advancing therapeutic innovations in cancer and other diseases.

Similarities and differences of bone marrow and peripheral blood samples from acute myeloid leukemia patients in terms of cellular heterogeneity and ex-vivo drug sensitivity.

Background: Bone marrow (BM) evaluation is the de facto standard for diagnosis, molecular analysis, risk stratification, and therapy response assessment in acute myeloid leukemia (AML), but in patients with a high number of circulating blast cells, the peripheral blood (PB) sample could provide similar information as BM. However, there is no large-scale molecular study comparing the two specimens in terms of their gene expression profiles, cellular heterogeneities, and ex-vivo drug sensitivity. Methodology: We used (i) the BEAT-AML cohort each with detailed molecular data; (ii) cell-type deconvolution to estimate leukemic and immune cell proportions between specimen types; (iii) differential expression (DE) and drug-cell type association analysis; and (iv) logistic regression models to assess the association between induction therapy response, cell-type composition and first-line drug treatment. Results: Results: We identified 207 patients having BM and 116 patients having PB samples. There was a total of 1271 DE genes (false discovery rate < 0.05) between BM and PB; the top enriched pathways in terms of DE genes belong to the immune system pathways. Aggregated ex-vivo drug response profiles from the two specimens were largely similar, as were the cellular components, except for the GMP-like cell type (17% in BM vs. 5% in PB, p-value = 2 × 10-7). Among the specimen-specific results, the GMP-like subtype was associated with multiple drug resistance in BM and the ProMono-like subtype in PB. Several cell types were associated with the response to induction therapy, but the impact of specimen type on the interaction of cell type and cytarabine-associated induction therapy was not statistically significant for most cell types. Results: Conclusions: Even though there are molecular and cellular differences between BM and PB samples, they show many similarities in ex-vivo drug response profiles, indicating the clinical utility of the substantially less-invasive PB samples.

Unveiling heterogeneity and prognostic markers in ductal breast cancer through single-cell RNA-seq.

BACKGROUND: Breast cancer (BC) is a heterogeneous disease, with the ductal subtype exhibiting significant cellular diversity that influences prognosis and response to treatment. Single-cell RNA sequencing data from the GEO database were utilized in this study to investigate the underlying mechanisms of cellular heterogeneity and to identify potential prognostic markers and therapeutic targets. METHODS: Bioinformatics analysis was conducted using R packages to analyze the single-cell sequencing data. The presence of highly variable genes and differences in malignant potency within the same BC samples were examined. Differential gene expression and biological function between Type 1 and Type 2 ductal epithelial cells were identified. Lasso regression and Cox proportional hazards regression analyses were employed to identify genes associated with patient prognosis. Experimental validation was performed in vitro and in vivo to confirm the functional relevance of the identified genes. RESULTS: The analysis revealed notable heterogeneity among BC cells, with the presence of highly variable genes and differences in malignant behavior within the same samples. Significant disparities in gene expression and biological function were identified between Type 1 and Type 2 ductal epithelial cells. Through regression analyses, CYP24A1 and TFPI2 were identified as pivotal genes associated with patient prognosis. Kaplan-Meier curves demonstrated their prognostic significance, and experimental validation confirmed their inhibitory effects on malignant behaviors of ductal BC cells. CONCLUSION: This study highlights the cellular heterogeneity in ductal subtype breast cancer and delineates the differential gene expressions and biological functions between Type 1 and Type 2 ductal epithelial cells. The genes CYP24A1 and TFPI2 emerged as promising prognostic markers and therapeutic targets, exhibiting inhibitory effects on BC cell malignancy in vitro and in vivo. These findings offer the potential for improved BC management and the development of targeted treatment strategies.

Single-cell analysis of Crohn's disease: Unveiling heterogeneity and evaluating ustekinumab outcomes.

BACKGROUND: The present study aimed to dissect the cellular complexity of Crohn's disease (CD) using single-cell RNA sequencing, focusing on identifying key cell populations and their transcriptional profiles in inflamed tissue. METHODS: We applied scRNA-sequencing to compare the cellular composition of CD patients with healthy controls, utilizing Seurat for clustering and annotation. Differential gene expression analysis and protein-protein interaction networks were constructed to identify crucial genes and pathways. RESULTS: Our study identified eight distinct cell types in CD, highlighting crucial fibroblast and T cell interactions. The analysis revealed key cellular communications and identified significant genes and pathways involved in the disease's pathology. The role of fibroblasts was underscored by elevated expression in diseased samples, offering insights into disease mechanisms and potential therapeutic targets, including responses to ustekinumab treatment, thus enriching our understanding of CD at a molecular level. CONCLUSIONS: Our findings highlight the complex cellular and molecular interplay in CD, suggesting new biomarkers and therapeutic targets, offering insights into disease mechanisms and treatment implications.

High-confidence calling of normal epithelial cells allows identification of a novel stem-like cell state in the colorectal cancer microenvironment.

Single-cell analyses can be confounded by assigning unrelated groups of cells to common developmental trajectories. For instance, cancer cells and admixed normal epithelial cells could adopt similar cell states thus complicating analyses of their developmental potential. Here, we develop and benchmark CCISM (for Cancer Cell Identification using Somatic Mutations) to exploit genomic single nucleotide variants for the disambiguation of cancer cells from genomically normal non-cancer cells in single-cell data. We find that our method and others based on gene expression or allelic imbalances identify overlapping sets of colorectal cancer versus normal colon epithelial cells, depending on molecular characteristics of individual cancers. Further, we define consensus cell identities of normal and cancer epithelial cells with higher transcriptome cluster homogeneity than those derived using existing tools. Using the consensus identities, we identify significant shifts of cell state distributions in genomically normal epithelial cells developing in the cancer microenvironment, with immature states increased at the expense of terminal differentiation throughout the colon, and a novel stem-like cell state arising in the left colon. Trajectory analyses show that the new cell state extends the pseudo-time range of normal colon stem-like cells in a cancer context. We identify cancer-associated fibroblasts as sources of WNT and BMP ligands potentially contributing to increased plasticity of stem cells in the cancer microenvironment. Our analyses advocate careful interpretation of cell heterogeneity and plasticity in the cancer context and the consideration of genomic information in addition to gene expression data when possible.

Decoding ecosystem heterogeneity and transcriptional regulation characteristics of multi-subtype renal cell carcinoma.

Background: Renal cell carcinoma (RCC) is characterized by its heterogeneity and the complexity of its tumor microenvironment. This study addresses the need to understand RCC at a cellular level, with a focus on its three main subtypes: clear cell (ccRCC), chromophobe (chRCC), and papillary renal cell carcinoma (pRCC). Objective: This study aims to comprehensively characterize the cellular diversity and intercellular communication networks of RCC subtypes using scRNA-seq technology. By focusing on macrophages and cancer-associated fibroblasts (CAFs), we seek to reveal their functional states, developmental trajectories, and signaling pathways. Methodology: We utilized single-cell RNA sequencing (scRNA-seq) data from various kidney cancer subtypes. Advanced analytical techniques, including Uniform Manifold Approximation and Projection (UMAP) and Reactome Gene Set Variation Analysis (ReactomeGSA), were employed to assess cellular heterogeneity and pathway activities. The developmental dynamics of macrophages were studied using CytoTRACE, and cell-to-cell communication was analyzed to identify subtype-specific interaction networks. Results: Our comprehensive analysis revealed significant cellular diversity within RCC. Distinct macrophage and CAF subpopulations were identified, each exhibiting unique gene expression profiles and pathway activities. Notably, ccRCC showed prominent bidirectional communication between macrophages and CAFs, while chRCC and pRCC displayed disrupted signaling pathways. Metabolic pathway analysis reflected the adaptability of macrophages and CAFs to the tumor microenvironment, and the MIF signaling pathway was identified as a key mediator of cellular interactions. Conclusion: The study highlights the cellular heterogeneity and the intricate communication networks within RCC subtypes, underscoring the complexity of the tumor microenvironment. Our findings suggest that targeting specific cellular interactions and pathways may offer new avenues for therapeutic intervention in RCC. The unique macrophage and CAF profiles across RCC subtypes provide valuable insights for the development of personalized and targeted treatment strategies.

From whole bodies to single cells: A guide to transcriptomic approaches for ecology and evolutionary biology.

RNA sequencing (RNAseq) methodology has experienced a burst of technological developments in the last decade, which has opened up opportunities for studying the mechanisms of adaptation to environmental factors at both the organismal and cellular level. Selecting the most suitable experimental approach for specific research questions and model systems can, however, be a challenge and researchers in ecology and evolution are commonly faced with the choice of whether to study gene expression variation in whole bodies, specific tissues, and/or single cells. A wide range of sometimes polarised opinions exists over which approach is best. Here, we highlight the advantages and disadvantages of each of these approaches to provide a guide to help researchers make informed decisions and maximise the power of their study. Using illustrative examples of various ecological and evolutionary research questions, we guide the readers through the different RNAseq approaches and help them identify the most suitable design for their own projects.

Unraveling the Drug Response Heterogeneity with Single-Cell Vibrational Phenomics.

Drug responses heterogeneity is often highlighted to justify the need for precision medicine. However, due to the highly complex nature of cell phenotypes in many diseases, one of key challenges is how to obtain the high content features in a cellular population. Here we present a single-cell vibrational phenomics approach, integrating synchrotron infrared microspectroscopy and multivariate calculation, for quantitatively evaluating the cellular responses to drug perturbation with single cell resolution. In a human hepatocellular carcinoma HepG2 cell model, the phenotypic changes induced by two types of drugs, taxol (TAX) and protopanaxadiol (PPD), were analyzed and revealed the response heterogeneity in drug concentration and chemical components. These findings not only provide a label-free strategy for determining the drug response at the single cell level, but also demonstrate the great potential of vibrational phenomics as a drug discovery platform.

Investigating cellular similarities and differences between upper tract urothelial carcinoma and bladder urothelial carcinoma using single-cell sequencing.

Background: Upper tract urothelial carcinoma (UTUC) and bladder urothelial carcinoma (BLCA) both originate from uroepithelial tissue, sharing remarkably similar clinical manifestations and therapeutic modalities. However, emerging evidence suggests that identical treatment regimens may lead to less favorable outcomes in UTUC compared to BLCA. Therefore, it is imperative to explore molecular processes of UTUC and identify biological differences between UTUC and BLCA. Methods: In this study, we performed a comprehensive analysis using single-cell RNA sequencing (scRNA-seq) on three UTUC cases and four normal ureteral tissues. These data were combined with publicly available datasets from previous BLCA studies and RNA sequencing (RNA-seq) data for both cancer types. This pooled analysis allowed us to delineate the transcriptional differences among distinct cell subsets within the microenvironment, thus identifying critical factors contributing to UTUC progression and phenotypic differences between UTUC and BLCA. Results: scRNA-seq analysis revealed seemingly similar but transcriptionally distinct cellular identities within the UTUC and BLCA ecosystems. Notably, we observed striking differences in acquired immunological landscapes and varied cellular functional phenotypes between these two cancers. In addition, we uncovered the immunomodulatory functions of vein endothelial cells (ECs) in UTUC, and intercellular network analysis demonstrated that fibroblasts play important roles in the microenvironment. Further intersection analysis showed that MARCKS promote UTUC progression, and immunohistochemistry (IHC) staining revealed that the diverse expression patterns of MARCKS in UTUC, BLCA and normal ureter tissues. Conclusion: This study expands our multidimensional understanding of the similarities and distinctions between UTUC and BLCA. Our findings lay the foundation for further investigations to develop diagnostic and therapeutic targets for UTUC.

Extracellular matrices of stromal cell subtypes regulate phenotype and contribute to the stromal microenvironment in vivo.

BACKGROUND: Bone marrow stromal cells (BMSCs) are highly heterogeneous, which may reflect their diverse biological functions, including tissue maintenance, haematopoietic support and immune control. The current understanding of the mechanisms that drive the onset and resolution of heterogeneity, and how BMSCs influence other cells in their environment is limited. Here, we determined how the secretome and importantly the extracellular matrix of BMSCs can influence cellular phenotype. METHODS: We used two immortalised clonal BMSC lines isolated from the same heterogeneous culture as model stromal subtypes with distinct phenotypic traits; a multipotent stem-cell-like stromal line (Y201) and a nullipotent non-stem cell stromal line (Y202), isolated from the same donor BMSC pool. Label-free quantitative phase imaging was used to track cell morphology and migration of the BMSC lines over 96 h in colony-forming assays. We quantified the secreted factors of each cell line by mass spectrometry and confirmed presence of proteins in human bone marrow by immunofluorescence. RESULTS: Transfer of secreted signals from a stem cell to a non-stem cell resulted in a change in morphology and enhanced migration to more closely match stem cell-like features. Mass spectrometry analysis revealed a significant enrichment of extracellular matrix (ECM) proteins in the Y201 stem cell secretome compared to Y202 stromal cells. We confirmed that Y201 produced a more robust ECM in culture compared to Y202. Growth of Y202 on ECM produced by Y201 or Y202 restored migration and fibroblastic morphology, suggesting that it is the deficiency of ECM production that contributes to its phenotype. The proteins periostin and aggrecan, were detected at 71- and 104-fold higher levels in the Y201 versus Y202 secretome and were subsequently identified by immunofluorescence at rare sites on the endosteal surfaces of mouse and human bone, underlying CD271-positive stromal cells. These proteins may represent key non-cellular components of the microenvironment for bona-fide stem cells important for cell maintenance and phenotype in vivo. CONCLUSIONS: We identified plasticity in BMSC morphology and migratory characteristics that can be modified through secreted proteins, particularly from multipotent stem cells. Overall, we demonstrate the importance of specific ECM proteins in co-ordination of cellular phenotype and highlight how non-cellular components of the BMSC microenvironment may provide insights into cell population heterogeneity and the role of BMSCs in health and disease.

Studying the Dynamics of Tunneling Tubes and Cellular Spheres.

Cancer cytogenetic analyses often involve cell culture. However, many cytogeneticists overlook interesting phenotypes associated with cultured cells. Given that cytogeneticists need to focus more on phenotypes to comprehend the genotypes, the biological significance of seemingly trivial cellular variations deserves attention. One example is the formation of cellular tunneling tubes (TTs) in cultured cancer cells, which likely play a role in cell-to-cell communication and material transport. In this chapter, we describe protocols for studying these TTs as well as cellular spheres. In addition to diverse chromosomal variants, these different types of variations should be considered for understanding cancer heterogeneity and dynamics, as they illustrate the importance of various forms of fuzzy inheritance.

Advancing skeletal health and disease research with single-cell RNA sequencing.

Orthopedic conditions have emerged as global health concerns, impacting approximately 1.7 billion individuals worldwide. However, the limited understanding of the underlying pathological processes at the cellular and molecular level has hindered the development of comprehensive treatment options for these disorders. The advent of single-cell RNA sequencing (scRNA-seq) technology has revolutionized biomedical research by enabling detailed examination of cellular and molecular diversity. Nevertheless, investigating mechanisms at the single-cell level in highly mineralized skeletal tissue poses technical challenges. In this comprehensive review, we present a streamlined approach to obtaining high-quality single cells from skeletal tissue and provide an overview of existing scRNA-seq technologies employed in skeletal studies along with practical bioinformatic analysis pipelines. By utilizing these methodologies, crucial insights into the developmental dynamics, maintenance of homeostasis, and pathological processes involved in spine, joint, bone, muscle, and tendon disorders have been uncovered. Specifically focusing on the joint diseases of degenerative disc disease, osteoarthritis, and rheumatoid arthritis using scRNA-seq has provided novel insights and a more nuanced comprehension. These findings have paved the way for discovering novel therapeutic targets that offer potential benefits to patients suffering from diverse skeletal disorders.

A facile single-cell patterning strategy based on harbor-like microwell microfluidics.

Single-cell analysis is an effective method for conducting comprehensive heterogeneity studies ranging from cell phenotype to gene expression. The ability to arrange different cells in a predetermined pattern at single-cell resolution has a wide range of applications in cell-based analysis and plays an important role in facilitating interdisciplinary research by researchers in various fields. Most existing microfluidic microwell chips is a simple and straightforward method, which typically use small-sized microwells to accommodate single cells. However, this method imposes certain limitations on cells of various sizes, and the single-cell capture efficiency is relatively low without the assistance of external forces. Moreover, the microwells limit the spatiotemporal resolution of reagent replacement, as well as cell-to-cell communication. In this study, we propose a new strategy to prepare a single-cell array on a planar microchannel based on microfluidic flip microwells chip platform with large apertures (50 µm), shallow channels (50 µm), and deep microwells (50 µm). The combination of three configuration characteristics contributes to multi-cell trapping and a single-cell array within microwells, while the subsequent chip flipping accomplishes the transfer of the single-cell array to the opposite planar microchannel for cells adherence and growth. Further assisted by protein coating of bovine serum albumin and fibronectin on different layers, the single-cell capture efficiency in microwells is achieved at 92.1% ± 1%, while ultimately 85% ± 3.4% on planar microchannel. To verify the microfluidic flip microwells chip platform, the real-time and heterogeneous study of calcium release and apoptosis behaviours of single cells is carried out. To our knowledge, this is the first time that high-efficiency single-cell acquisition has been accomplished using a circular-well chip design that combines shallow channel, large aperture and deep microwell together. The chip is effective in avoiding the shearing force of high flow rates on cells, and the large apertures better allows cells to sedimentation. Therefore, this strategy owns the advantages of easy preparation and user-friendliness, which is especially valuable for researchers from different fields.