Rare Cell Populations Research Articles

JAK/STAT signaling maintains an intermediate cell population during prostate basal cell fate determination.

Unipotent basal and luminal stem cells maintain prostate homeostasis, with an intermediate cell population emerging during prostate inflammation or cancer. However, the identities of basal stem cell and intermediate cell population remain unclear. Here we identified a rare intermediate cell population expressing luminal markers (termed Basal-B) with enhanced organoid formation capacity, and a larger basal population (termed Basal-A). Genetic lineage tracing revealed Basal-B cells represented a transient basal stem cell state during prostate homeostasis and androgen-mediated regeneration. Activated JAK/STAT signaling was identified in Basal-B cells, and its inhibition significantly reduced Basal-B markers expression. Inflammation increased Basal-B-to-luminal cell transdifferentiation, but JAK/STAT inhibition notably attenuated this effect. Pten gene deletion increased Nkx3.1-expressing Basal-B-like cell population and led to neoplasia. In humans, h-Basal-B cells were more prevalent in benign prostate hyperplasia. This study reveals the identities of intermediate Basal-B cells and underscores the role of JAK/STAT signaling in prostate cell fate determination.

EPCO-60. EXPRESSION OF EARLY PROGENITOR MARKERS WITHIN NF2-ASSOCIATED SPINAL EPENDYMOMA

Abstract Spinal ependymomas (SP-EPNs) are intramedullary spinal tumors commonly found in patients with NF2-related schwannomatosis. Recent work using bulkRNA sequencing has suggested that SP-EPNs express a molecular signature most similar to ependymal cells. However, this type of sequencing may miss rare stem cell populations within tumors. The aim of this study was to assess the spatial heterogeneity within NF2-associated SP-EPNs and explore whether a stem cell population exists within SP-EPNs. Spatial transcriptomics (ST) was performed on a SP-EPN sample previously resected from a patient with NF2-related schwannomatosis using the 10X Genomics Visium Cytassist Platform. Libraries were sequenced on the Illumina NovaSeq 6000. 28-bp reads including spatial barcode and UMI sequences and 50-bp probe reads were generated with Illumina NovaSeq 6000 at the Center for Medical Genomics at Indiana University School of Medicine. Space Ranger 2.1 was used to process the raw files after sequencing. Data analysis was performed with R package Seurat 4.9.9.9041 following preprocessing with spaceranger. Sctransform normalized the spatial transcriptome dataset. Clusters were identified using “FindClusters” and “FindNeighbors” functions. There was diffuse expression of astrocyte and ependymal cell markers throughout the SP-EPN sample with smaller areas expressing radial glia and stem cell markers, as well as overlap between these regions. Expression of vascular and connective tissue markers varied throughout the tumor. There was minimal to no expression of neural genes in the sample. ST on our SP-EPN sample revealed a tumor with marked cellular and molecular heterogeneity. Although the primarily expressed ependymal cell and astrocyte markers, there does appear to be small, stem cell-like populations. This suggests that NF2-associated SP-EPNs may have a developmental hierarchy with radial glia-like cells and more mature progenitors within the ependymal cell lineage. This proof-of-concept study offers important findings that provide justification for further investigation using single-cell sequencing.

Overloading And unpacKing (OAK) - droplet-based combinatorial indexing for ultra-high throughput single-cell multiomic profiling

Multiomic profiling of single cells by sequencing is a powerful technique for investigating cellular diversity. Existing droplet-based microfluidic methods produce many cell-free droplets, underutilizing bead barcodes and reagents. Combinatorial indexing on microplates is more efficient for barcoding but labor-intensive. Here we present Overloading And unpacKing (OAK), which uses a droplet-based barcoding system for initial compartmentalization followed by a second aliquoting round to achieve combinatorial indexing. We demonstrate OAK’s versatility with single-cell RNA sequencing as well as paired single-nucleus RNA sequencing and accessible chromatin profiling. We further showcase OAK’s performance on complex samples, including differentiated bronchial epithelial cells and primary retinal tissue. Finally, we examine transcriptomic responses of over 400,000 melanoma cells to a RAF inhibitor, belvarafenib, discovering a rare resistant cell population (0.12%). OAK’s ultra-high throughput, broad compatibility, high sensitivity, and simplified procedures make it a powerful tool for large-scale molecular analysis, even for rare cells.

Regulatory network analysis of Dclk1 gene expression reveals a tuft cell-ILC2 axis that inhibits pancreatic tumor progression.

Dclk1 expression defines a rare population of cells in the normal pancreas whose frequency is increased at early stages of pancreatic tumorigenesis. The identity and the precise roles of Dclk1 expressing cells in pancreas have been matter of debate, although evidence suggests their involvement in a number of key functions, including regeneration and neoplasia. We employed a recently developed Dclk1 reporter mouse model and single cell RNAseq analysis to define Dclk1 expressing cells in normal pancreas and pancreatic neoplasia. In normal pancreas, Dclk1 epithelial expression identifies subsets of ductal, islet and acinar cells. In pancreatic neoplasia, Dclk1 expression identifies five epithelial cell populations, among which acinar-to-ductal metaplasia (ADM)-like cells and tuft-like cells are predominant. These two cell populations play opposing roles in pancreatic neoplasia, with Dclk1+ ADM-like cells sustaining tumor growth while Dclk1+ tuft-like cells restraining tumor progression. The differentiation of Kras mutant acinar cells into Dclk1+ tuft-like cells requires the activation of the transcription factor SPIB and is further supported by a cellular paracrine loop involving cancer group 2 innate lymphoid cells (ILC2) and cancer activated fibroblasts (CAFs) that provide IL13 and IL33, respectively. In turn, Dclk1+ tuft-like cells release angiotensinogen that plays protective roles against pancreatic neoplasia. Overall, our study provides novel insights on the biology of Dclk1+ cells in normal pancreas and unveils a protective axis against pancreatic neoplasia, involving CAFs, ILC2 and Dclk1+ tuft-like cells, which ultimately results in angiotensinogen release.

Single nucleus DNA sequencing of flow sorted archived frozen and formalin fixed paraffin embedded solid tumors.

Archived samples, including frozen and formalin fixed paraffin embedded (FFPE) tissues, are a vast resource of clinically annotated materials for the application of high-definition genomics to improve patient management and provide a molecular basis for the delivery of personalized cancer therapeutics. Notably, FFPE tissues are stable, provide repeat sampling of tissues of interest, and can be stored indefinitely at ambient temperature. The development of single cell DNA sequencing (scDNA-seq) technologies provides an unparalleled opportunity for the study of tumor heterogeneity and the identification of often rare subclonal cell populations that drive tumor evolution and progression to advanced therapy resistant disease. However, major limitations to the use of archived tissues for scDNA-seq include the low yields of intact cells in the presence of high levels of subcellular debris in biopsies, and the highly variable quantity and quality of the DNA extracted from samples of interest. The latter is of high significance for the use of FFPE tissues due to the presence of DNA-protein crosslinks. In addition, many samples, notably tumors arising in solid tissues, contain admixtures of reactive stroma, inflammatory cells, and necrosis in immediate contact with tumor cells. To expand their use for translational studies, we optimized flow sorting and sequencing of single nuclei from archived fresh frozen (FF) and FFPE tumor tissues. Our methods, which include isolation of intact nuclei suitable for library preparations, quality control (QC) metrics for each step, and a single cell sequencing bioinformatic processing and analysis pipeline, were validated with flow sorted nuclei from matching FF and FFPE ovarian cancer surgical samples and a sequencing panel of 553 amplicons targeting single nucleotide and copy number variants in genes of interest. Our flow sorting based protocol provides intact nuclei suitable for snDNA-seq from archival FF and FFPE tissues. Furthermore, we have developed QC steps that optimize the preparation and selection of samples for deep single cell clonal profiling. Our data processing pipeline captures rare subclones in tumors with highly variable genomes based on variants in genes of interest.

Essential Fluidics for a Flow Cytometer.

Flow cytometry is an inherently fluidic process that flows particles on a one-by-one basis through a sensing region to discretely measure their optical and physical properties. It can be used to analyze particles ranging in size from nanoparticles to whole organisms (e.g., zebrafish). It has particular value for blood analysis, and thus most instruments are fluidically optimized for particles that are comparable in size to a typical blood cell. The principles of fluid dynamics allow for particles of such size to be precisely positioned in flow as they pass through sensing regions that are tens of microns in length at linear velocities of meters per second. Such fluidic systems enable discrete analysis of cell-sized particles at rates approaching 100 kHz. For larger particles, the principles of fluidics greatly reduce the achievable rates, but such high rates of data acquisition for cell-sized particles allow rapid collection of information on many thousands to millions of cells and provides for research and clinical measurements of both rare and common cell populations with a high degree of statistical confidence. Additionally, flow cytometers can accurately count particles via the use of volumetric sample delivery and can be coupled with high-throughput sampling technologies to greatly increase the rate at which independent samples can be delivered to the system. Due to the combination of high analysis rates, sensitive multiparameter measurements, high-throughput sampling, and accurate counting, flow cytometry analysis is the gold standard for many critical applications in clinical, research, pharmaceutical, and environmental areas. Beyond the power of flow cytometry as an analytical technique, the fluidic pathway can be coupled with a sorting mechanism to collect particles based on desired properties. We present an overview of fluidic systems that enable flow cytometry-based analysis and sorting. We introduce historical approaches, explanations of commonly implemented fluidics, and brief discussions of potential future fluidics where appropriate. © 2024 Wiley Periodicals LLC.

DEPICT-seq: Single-Cell Transcriptomic Analysis of Rare Cell Subsets Isolated via Nucleic Acid Cytometry.

The ability to dive deep into specific rare cell populations is critical for understanding tissue physiology and pathology across various biological domains. As single-cell RNA-seq flourishes, many newly discovered cell subtypes are defined by their transcriptomic markers. However, our ability to retrieve and analyze cells based on their nucleic acid markers remains underdeveloped. Here, we present Double Emulsion PCR-Initiated Cell sorting and Transcriptomic Sequencing (DEPICT-seq), a high-throughput droplet nucleic acid cytometry method that integrates batch cell fixation for cellular information preservation, double emulsion digital PCR-based cell sorting to target nucleic acid markers of interest, and in-depth full-length transcriptomic analyses at single-cell resolution. We utilize DEPICT-seq to isolate and characterize T cell receptor (TCR)-engineered T cells within a mixed population and also demonstrate a variation of the workflow by incorporating an RNase H-dependent PCR step to enrich full-length TCR sequences for paired single-cell TCR sequencing and transcriptomic profiling.

Recovering single-cell expression profiles from spatial transcriptomics with scResolve.

Many popular spatial transcriptomics techniques lack single-cell resolution. Instead, these methods measure the collective gene expression for each location from a mixture of cells, potentially containing multiple cell types. Here, we developed scResolve, a method for recovering single-cell expression profiles from spatial transcriptomics measurements at multi-cellular resolution. scResolve accurately restores expression profiles of individual cells at their locations, which is unattainable with cell type deconvolution. Applications of scResolve on human breast cancer data and human lung disease data demonstrate that scResolve enables cell-type-specific differential gene expression analysis between different tissue contexts and accurate identification of rare cell populations. The spatially resolved cellular-level expression profiles obtained throughscResolve facilitate more flexible and precise spatial analysis that complements raw multi-cellular level analysis.

Combinatorial Nutraceutical Supplement Pill (CNSP) stimulates naïve adult telomerase positive stem cells In-Situ to reverse signs and symptoms in multiple human health concerns

Previous IRB-approved studies demonstrated that a rare population of endogenous adult telomerase positive stem cells (aTPSCs), isolated and activated ex vivo, displayed a 100% safety record for reinfusion and an 86% efficacy at reversing signs and symptoms in 97 individuals in 18 disease states. Recent studies demonstrated that these rare aTPSCs could also be activated in vivo by ingestion of a combinatorial nutraceutical supplement pill (CNSP). With IRB permission, CNSP was originally developed for an individual too fragile to undergo the fresh isolate aTPSC technologies. Without any other medical intervention, ingestion of CNSP for 12 months raised his ejection fraction from <10% to about 50%. Based on the results from his study (n=1) [100% safe and 100% efficacious], we received IRB permission to expand the number of clinical trials to determine the effectiveness of using CNSP for other health concerns. Herein, are the preliminary results from 40 people in 28 health concerns utilizing CNSP only and CNSP with other treatment modalities, to affect a better quality of life. Participants were assessed in phase-0, open access, open ended clinical trials, for 1-4+ years. Participants in all 28 clinical trials demonstrated 100% safety and 100% efficacy at reversing signs and symptoms in their respective health concerns, giving them an apparent better quality of life.

Connectivity Network Feature Sharing in Single-Cell RNA Sequencing Data Identifies Rare Cells.

Single-cell RNA sequencing is a valuable technique for identifying diverse cell subtypes. A key challenge in this process is that the detection of rare cells is often missed by conventional methods due to low abundance and subtle features of these cells. To overcome this, we developed SCLCNF (Local Connectivity Network Feature Sharing in Single-Cell RNA sequencing), a novel approach that identifies rare cells by analyzing features uniquely expressed in these cells. SCLCNF creates a cellular connectivity network, considering how each cell relates to its neighbors. This network helps to pinpoint coexpression patterns unique to rare cells, utilizing a rarity score to confirm their presence. Our method performs better in detecting rare cells than existing techniques, offering enhanced robustness. It has proven to be effective in human gastrula data sets for accurately pinpointing rare cells, and in sepsis data sets where it uncovers previously unidentified rare cell populations.

PURE-seq identifies Egr1 as a Potential Master Regulator in Murine Aging by Sequencing Long-Term Hematopoietic Stem Cells.

Single-cell transcriptomics is valuable for uncovering individual cell properties, particularly in highly heterogeneous systems. However, this technique often results in the analysis of many well-characterized cells, increasing costs and diluting rare cell populations. To address this, we developed PURE-seq (PIP-seq for Rare-cell Enrichment and Sequencing) for scalable sequencing of rare cells. PURE-seq allows direct cell loading from FACS into PIP-seq reactions, minimizing handling and reducing cell loss. PURE-seq reliably captures rare cells, with 60 minutes of sorting capturing tens of cells at a rarity of 1 in 1,000,000. Using PURE-seq, we investigated murine long-term hematopoietic stem cells and their transcriptomes in the context of hematopoietic aging, identifying Egr1 as a potential master regulator of hematopoiesis in the aging context. PURE-seq offers an accessible and reliable method for isolating and sequencing cells that are currently too rare to capture successfully with existing methods.

PURE-seq identifies Egr1 as a Potential Master Regulator in Murine Aging by Sequencing Long-Term Hematopoietic Stem Cells.

Single-cell transcriptomics is valuable for uncovering individual cell properties, particularly in highly heterogeneous systems. However, this technique often results in the analysis of many well-characterized cells, increasing costs and diluting rare cell populations. To address this, we developed PURE-seq (PIP-seq for Rare-cell Enrichment and Sequencing) for scalable sequencing of rare cells. PURE-seq allows direct cell loading from FACS into PIP-seq reactions, minimizing handling and reducing cell loss. PURE-seq reliably captures rare cells, with 60 minutes of sorting capturing tens of cells at a rarity of 1 in 1,000,000. Using PURE-seq, we investigated murine long-term hematopoietic stem cells and their transcriptomes in the context of hematopoietic aging, identifying Egr1 as a potential master regulator of hematopoiesis in the aging context. PURE-seq offers an accessible and reliable method for isolating and sequencing cells that are currently too rare to capture successfully with existing methods.

A second wave of Notch signaling diversifies the intestinal secretory lineage.

The small intestine is well known for the function of its nutrient-absorbing enterocytes; yet equally critical for the maintenance of homeostasis is a diverse set of secretory cells, all of which are presumed to differentiate from the same intestinal stem cell. Despite major roles in intestinal function and health, understanding how the full spectrum of secretory cell types arises remains a longstanding challenge, largely due to their comparative rarity. Here, we investigate the fate specification of a rare and distinct population of small intestinal epithelial cells found in rats and humans but not mice: C FTR Hi gh E xpressers (CHEs). We use pseudotime trajectory analysis of single-cell RNA-seq data from rat intestinal jejunum to provide evidence that CHEs are specified along the secretory lineage and appear to employ a second wave of Notch-based signal transduction to distinguish these cells from other secretory cell types. We further validate the general order of transcription factors that direct these cells from unspecified progenitors within the crypt and experimentally demonstrate that Notch signaling is necessary to induce CHE fate both in vivo and in vitro . Our results suggest a model in which Notch is reactivated along the secretory lineage to specify the CHE population: a rare secretory cell type with putative functions in localized coordination of luminal pH and direct relevance to cystic fibrosis pathophysiology.

A 38-colour high dimensional immunophenotyping panel for human peripheral blood mononuclear cells

High dimensional immunophenotyping panels are invaluable resources for performing extensive phenotyping on peripheral blood mononuclear cells (PBMCs). We designed a 38-colour high dimensional phenotyping panel to measure innate (monocytes, dendritic cells, NK cells, basophils, innate like lymphoid cells), T cell (γδ T cells, MAIT cells, CD4 and CD8 memory, Th1, Th2, Th17, Tfh, Treg) and B cell (memory, plasma cells, transitional B cells, plasmablasts, IgG, IgM) subsets in addition to their activation status using the 5-laser Cytek Aurora. We optimised optimal fluorochrome combinations and titres to minimise spread and autofluorescence of rare immune cell populations and tested this panel on PBMCs from 15 healthy adults. This high dimensional panel will be invaluable for direct ex vivo studies to evaluate immune cells in the context of human health and disease, especially when samples are limited.

Fast and efficient isolation of murine circulating tumor cells using screencell technology for pre-clinical analyzes

Circulating tumor cells (CTCs) represent a rare and heterogeneous population of cancer cells that are detached from the tumor site and entered blood or lymphatic circulation. Once disseminated in distant tissues, CTCs could remain dormant or create a tumor mass causing serious danger for patients. Many technologies exist to isolate CTCs from patients’ blood samples, mostly based on microfluidic systems or by sorting them according to their surface antigens, notably EpCAM, and/or cytokeratins for carcinoma. ScreenCell has developed an easy-to-use, antigen-independent, rapid, cost-effective, and efficient technology that isolates CTCs according to their bigger size compared to the blood cells. This study provides the technical information necessary to isolate and characterize CTCs from mouse blood. By using blood samples from transgenic mice with breast cancer or from WT mice in which we spiked cancer cells, we showed that ScreenCell technology is compatible with standard EDTA blood collection tubes. Furthermore, the ScreenCell Cyto kit could treat up to 500 µl and the ScreenCell MB kit up to 200 µl of mouse blood. As the ScreenCell MB kit captures unaltered live CTCs, we have shown that their DNA could be efficiently extracted, and the isolated cells could be grown in culture. In conclusion, ScreenCell provides a rapid, easy, antigen-independent, cost-effective, and efficient technology to isolate and characterize CTCs from the blood samples of cancer patients and murine models. Thanks to this technology CTCs could be captured fixed or alive. Murine cancer models are extensively used in pre-clinical studies. Therefore, this study demonstrates the crucial technical points necessary while manipulating mouse blood samples using ScreenCell technology.

The totipotent 2C-like state safeguards genomic stability of mouse embryonic stem cells.

Mouse embryonic stem cells (mESCs) sporadically transition to a transient totipotent state that resembles blastomeres of the two-cell (2C) embryo stage, which has been proposed to contribute to exceptional genomic stability, one of the key features of mESCs. However, the biological significance of the rare population of 2C-like cells (2CLCs) in ESC cultures remains to be tested. Here we generated an inducible reporter cell system for specific elimination of 2CLCs from the ESC cultures to disrupt the equilibrium between ESCs and 2CLCs. We show that removing 2CLCs from the ESC cultures leads to dramatic accumulation of DNA damage, genomic mutations, and rearrangements, indicating impaired genomic instability. Furthermore, 2CLCs removal results in increased apoptosis and reduced proliferation of mESCs in both serum/LIF and 2i/LIF culture conditions. Unexpectedly, p53 deficiency results in defective response to DNA damage, leading to early accumulation of DNA damage, micronuclei, indicative of genomic instability, cell apoptosis, and reduced self-renewal capacity of ESCs when devoid of 2CLCs in cultures. Together, our data reveal that transition to the privileged 2C-like state is a major component of the intrinsic mechanisms that maintain the exceptional genomic stability of mESCs for long-term self-renewal.

Ru(II)-based complexes containing 2-thiouracil derivatives suppress liver cancer stem cells by targeting NF-κB and Akt/mTOR signaling

Cancer stem cells (CSCs) are defined as a rare population of cancer cells related to tumor initiation and maintenance. These cells are primarily responsible for tumor growth, invasion, metastasis, recurrence, and resistance to chemotherapy. In this paper, we demonstrated the ability of Ru(II)-based complexes containing 2-thiouracil derivatives with the chemical formulas trans-[Ru(2TU)(PPh3)2(bipy)]PF6 (1) and trans-[Ru(6m2TU)(PPh3)2(bipy)]PF6 (2) (where 2TU = 2-thiouracil and 6m2TU = 6-methyl-2-thiouracil) to suppress liver CSCs by targeting NF-κB and Akt/mTOR signaling. Complexes 1 and 2 displayed potent cytotoxic effects on cancer cell lines and suppressed liver CSCs from HepG2 cells. Increased phosphatidylserine exposure, loss of mitochondrial transmembrane potential, increased PARP (Asp214) cleavage, DNA fragmentation, chromatin condensation and cytoplasmic shrinkage were detected in HepG2 cells treated with these complexes. Mechanistically, complexes 1 and 2 target NF-κB and Akt/mTOR signaling in HepG2 cells. Cell motility inhibition was also detected in HepG2 cells treated with these complexes. Complexes 1 and 2 also inhibited tumor progression in mice with HepG2 cell xenografts and exhibited tolerable systemic toxicity. Taken together, these results indicate that these complexes are new anti-HCC drug candidates that can suppress liver CSCs.

Immunotherapeutic Strategies Targeting Breast Cancer Stem Cells.

Breast cancer is the most commonly diagnosed cancer in women and is a leading cause of cancer death in women worldwide. Despite the implementation of multiple treatment options, including immunotherapy, breast cancer treatment remains a challenge. In this review, we aim to summarize present challenges in breast cancer immunotherapy and recent advancements in overcoming treatment resistance. We elaborate on the inhibition of signaling cascades, such as the Notch, Hedgehog, Hippo, and WNT signaling pathways, which regulate the self-renewal and differentiation of breast cancer stem cells and, consequently, disease progression and survival. Cancer stem cells represent a rare population of cancer cells, likely originating from non-malignant stem or progenitor cells, with the ability to evade immune surveillance and develop resistance to immunotherapeutic treatments. We also discuss the interactions between breast cancer stem cells and the immune system, including potential agents targeting breast cancer stem cell-associated signaling pathways, and provide an overview of the emerging approaches to breast cancer stem cell-targeted immunotherapy. Finally, we consider the development of breast cancer vaccines and adoptive cellular therapies, which train the immune system to recognize tumor-associated antigens, for eliciting T cell-mediated responses to target breast cancer stem cells.

Single‐cell RNA sequencing in pediatric research: Focusing on differentiation trajectories and immune microenvironment of neuroblastoma

AbstractRecently, single‐cell RNA sequencing (scRNA‐seq) has emerged as a novel and high‐resolution technique for identifying cell types, states, and subpopulations. This technique enables researchers to uncover cellular heterogeneity and detect rare cell populations that might be indistinguishable in bulk RNA‐seq data. The primary aim of scRNA‐seq analysis is to investigate cellular heterogeneity and distinguish distinct cell types or states. scRNA‐seq provides a detailed understanding of intercellular differences and diversity by obtaining gene expression data for each individual cell. Moreover, clustering methods in scRNA‐seq can be used to group cells bring into subpopulations based on their gene expression patterns, thereby uncovering similarities and differences that assist in identifying and defining cell types. Newly discovered cell types can be validated and named by labeling known cell marker genes. Additionally, scRNA‐seq helps in identifying genes specifically expressed at different developmental stages, in various tissue types, or under various disease states. Recently, there has been a growing trend in using single‐cell transcriptome sequencing technology for neuroblastoma (NB) research. Through conducting a comprehensive review of relevant articles published thus far, our understanding of NB has been significantly enriched from three critical perspectives: differentiation trajectory, tumor heterogeneity, and immune microenvironment. Firstly, in exploring the differentiation trajectory of NB, we have summarized the tumor's origin and subsequent directions of differentiation. By elucidating a complete tumor differentiation pathway, we can enhance our understanding of the mechanisms underlying spontaneous tumor regression. Secondly, we have summarized the heterogeneity of tumors, which encompasses different states, cell morphologies, and characteristic genes of NB identified through single‐cell sequencing technology. This consolidation of knowledge enhances our understanding of the heterogeneity of NB. Lastly, we have employed single‐cell sequencing technology to analyze the immune microenvironment, focusing on the cellular components within the tumor's surrounding environment and the diverse states of immune cells. This valuable information contributes to the advancement of NB diagnosis, treatment, and prognosis. In conclusion, the application of single‐cell sequencing technology in NB research has significantly advanced our understanding of the disease and carries great significance.

Rethinking eco‐evo studies of gene expression for non‐model organisms in the genomic era

AbstractRecent advances in genomic technology, including the rapid development of long‐read sequencing technology and single‐cell RNA‐sequencing methods, are poised to significantly expand the kinds of studies that are feasible in ecological genomics. In this perspective, we review these new technologies and discuss their potential impact on gene expression studies in non‐model organisms. Although traditional RNA‐sequencing methods have been an extraordinarily powerful tool to apply functional genomics in an ecological context, bulk RNA‐seq approaches often rely on de novo transcriptome assembly, and cannot capture expression changes in rare cell populations or distinguish shifts in cell type abundance. Advancements in genome assembly technology, particularly long‐read sequencing, and improvements in the scalability of single‐cell RNA‐sequencing (scRNA‐seq) offer unprecedented resolution in understanding cellular heterogeneity and gene regulation. We discuss the potential of these technologies to enable disentangling differential gene regulation from cell type composition differences and uncovering subtle expression patterns masked by bulk RNA‐seq. The integration of these approaches provides a more nuanced understanding of the ecological and evolutionary dynamics of gene expression, paving the way for refined models and deeper insights into the generation of biodiversity.