Meiotic transcriptional reprogramming mediated by cell-cell communications in humans and mice revealed by scATAC-seq and scRNA-seq.

Meiosis is a highly complex process significantly influenced by transcriptional regulation. However, studies on the mechanisms that govern transcriptomic changes during meiosis, especially in prophase I, are limited. Here, we performed single-cell ATAC-seq of human testis tissues and observed reprogramming during the transition from zygotene to pachytene spermatocytes. This event, conserved in mice, involved the deactivation of genes associated with meiosis after reprogramming and the activation of those related to spermatogenesis before their functional onset. Furthermore, we identified 282 transcriptional regulators (TRs) that underwent activation or deactivation subsequent to this process. Evidence suggested that physical contact signals from Sertoli cells may regulate these TRs in spermatocytes, while secreted ENHO signals may alter metabolic patterns in these cells. Our results further indicated that defective transcriptional reprogramming may be associated with non-obstructive azoospermia (NOA). This study revealed the importance of both physical contact and secreted signals between Sertoli cells and germ cells in meiotic progression.

Seronegative patients with primary Sjögren's syndrome and non-pSS sicca test positive for anti-SSA/Ro52 and -Ro60 in saliva.

OBJECTIVES: Testing for anti-SSA/Ro antibodies in serum is essential in the diagnostic work-up for primary Sjögren's syndrome (pSS). In this study, we aimed to validate our previous assay for detection of salivary anti-SSA/Ro52, and to develop assays for detection of salivary anti-SSA/Ro60 and for detection of anti-Ro52 and -Ro60 in plasma using the electric field-induced release and measurement (EFIRM) platform. METHODS: Whole saliva samples from two independent Danish cohorts (DN1 and DN2) including 49 patients with pSS, 73 patients with sicca symptoms, but not fulfilling the classification criteria for pSS (non-pSS sicca), and 51 healthy controls (HC), as well as plasma samples from the DN1 cohort were analyzed using EFIRM to detect anti-SSA/Ro52 and -Ro60. RESULTS: In the DN1 cohort, 100 % in the pSS group and 16 % in the non-pSS sicca group were serum anti-SSA/Ro positive by ELISA. EFIRM detected anti-SSA (Ro52 and/or -Ro60) in plasma and saliva in 100 % and 96 % patients with pSS, and 16 % and 29 % with non-pSS sicca. In the DN2 cohort, 80 % patients with pSS and 26 % with non-pSS sicca were serum anti-SSA/Ro positive. Salivary anti-SSA discriminated patients with pSS from HC and non-pSS sicca with an AUC range of 0.74-0.96 in the DN1 and DN2 cohorts. EFIRM discriminated pSS from non-pSS sicca with an AUC of 0.98 in plasma. CONCLUSION: Our findings suggest that salivary anti-SSA/Ro antibodies are potential discriminatory biomarkers for pSS, which may also identify seronegative patients, addressing the unmet clinical need of early detection and stratification of pSS.

scLENS: data-driven signal detection for unbiased scRNA-seq data analysis.

High dimensionality and noise have limited the new biological insights that can be discovered in scRNA-seq data. While dimensionality reduction tools have been developed to extract biological signals from the data, they often require manual determination of signal dimension, introducing user bias. Furthermore, a common data preprocessing method, log normalization, can unintentionally distort signals in the data. Here, we develop scLENS, a dimensionality reduction tool that circumvents the long-standing issues of signal distortion and manual input. Specifically, we identify the primary cause of signal distortion during log normalization and effectively address it by uniformizing cell vector lengths with L2 normalization. Furthermore, we utilize random matrix theory-based noise filtering and a signal robustness test to enable data-driven determination of the threshold for signal dimensions. Our method outperforms 11 widely used dimensionality reduction tools and performs particularly well for challenging scRNA-seq datasets with high sparsity and variability. To facilitate the use of scLENS, we provide a user-friendly package that automates accurate signal detection of scRNA-seq data without manual time-consuming tuning.

Systematic mapping of TF-mediated cell fate changes by a pooled induction coupled with scRNA-seq and multi-omics approaches.

Transcriptional regulation controls cellular functions through interactions between transcription factors (TFs) and their chromosomal targets. However, understanding the fate conversion potential of multiple TFs in an inducible manner remains limited. Here, we introduce iTF-seq as a method for identifying individual TFs that can alter cell fate toward specific lineages at a single-cell level. iTF-seq enables time course monitoring of transcriptome changes, and with biotinylated individual TFs, it provides a multi-omics approach to understanding the mechanisms behind TF-mediated cell fate changes. Our iTF-seq study in mouse embryonic stem cells identified multiple TFs that trigger rapid transcriptome changes indicative of differentiation within a day of induction. Moreover, cells expressing these potent TFs often show a slower cell cycle and increased cell death. Further analysis using bioChIP-seq revealed that GCM1 and OTX2 act as pioneer factors and activators by increasing gene accessibility and activating the expression of lineage specification genes during cell fate conversion. iTF-seq has utility in both mapping cell fate conversion and understanding cell fate conversion mechanisms.

Effective multi-modal clustering method via skip aggregation network for parallel scRNA-seq and scATAC-seq data.

In recent years, there has been a growing trend in the realm of parallel clustering analysis for single-cell RNA-seq (scRNA) and single-cell Assay of Transposase Accessible Chromatin (scATAC) data. However, prevailing methods often treat these two data modalities as equals, neglecting the fact that the scRNA mode holds significantly richer information compared to the scATAC. This disregard hinders the model benefits from the insights derived from multiple modalities, compromising the overall clustering performance. To this end, we propose an effective multi-modal clustering model scEMC for parallel scRNA and Assay of Transposase Accessible Chromatin data. Concretely, we have devised a skip aggregation network to simultaneously learn global structural information among cells and integrate data from diverse modalities. To safeguard the quality of integrated cell representation against the influence stemming from sparse scATAC data, we connect the scRNA data with the aggregated representation via skip connection. Moreover, to effectively fit the real distribution of cells, we introduced a Zero Inflated Negative Binomial-based denoising autoencoder that accommodates corrupted data containing synthetic noise, concurrently integrating a joint optimization module that employs multiple losses. Extensive experiments serve to underscore the effectiveness of our model. This work contributes significantly to the ongoing exploration of cell subpopulations and tumor microenvironments, and the code of our work will be public at https://github.com/DayuHuu/scEMC.

Integration of scRNA and bulk RNA-sequence to construct the 5-gene molecular prognostic model based on the heterogeneity of thyroid carcinoma endothelial cell.

Thyroid cancer (TC) is a kind of cancer with high heterogeneity, which leads to significant difference in prognosis. The prognostic molecular processes are not well understood. Cancer cells and tumor microenvironment (TME) cells jointly determine the heterogeneity. However, quite a little attention was paid to cells in the TME in the past years. In this study, we not only reveal that endothelial cells (ECs) are strongly associated with the progress of papillary thyroid cancer (PTC) using single-cell RNA-seq (scRNA-seq) data downloaded from Gene Expression Omnibus (GEO) and WGCNA, but also screen 5 crucial genes of ECs: CLDN5, ABCG2, NOTCH4, PLAT, and TMEM47. Furthermore, the 5-gene molecular prognostic model is constructed, which can predict how well a patient will do on PD-L1 blockade immunotherapy for TC and evaluate prognosis. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis demonstrates that PLAT is decreased in TC and the increase of PLAT can restrain the migratory capacity of TC cells. Meanwhile, in TC cells, PLAT suppresses VEGFa/VEGFR2-mediated human umbilical vascular endothelial cell (HUVEC) proliferation and tube formation. Totally, we construct the 5-gene molecular prognostic model from the perspective of EC and provide a new idea for immunotherapy of TC.

Circulating mitochondrial long non-coding 7S RNA in primary health care patients with depression/anxiety.

BACKGROUND: The significant role of long non-coding 7S RNA in controlling mitochondrial transcription highlights its importance in mitochondrial function. Considering the suggested connection between mitochondrial dysfunction and the onset of mental disorders, this study aimed to explore the potential involvement of 7S RNA in the context of depression/anxiety. RESULTS: A total of 181 patients in primary health care (age 20-64 years) with depression/anxiety and 59 healthy controls were included in the study. 7S RNA was measured using quantitative real-time PCR in plasma samples collected before (baseline) and after 8 weeks of treatment (mindfulness or cognitive-based behavioral therapy). Upon adjustment for age and sex, the baseline plasma levels of 7S RNA were significantly higher in patients than in healthy controls (p < 0.001). Notably, post-treatment, there was a significant reduction in 7S RNA levels (p = 0.03). These changes in 7S RNA were related to the treatment response, as indicated by HADS-D (Hospital Anxiety and Depression Scale) scores (ß = -0.04, p = 0.04), even after accounting for baseline scores and other cofounders. CONCLUSION: The findings of this study indicate an association between plasma 7S RNA levels and depression/anxiety, as well as treatment response. While further confirmatory analyses are necessary, plasma 7S RNA holds promise as a potential predictive biomarker for both depression/anxiety and the treatment response within these disorders.

Association of Combined Anti-Ro52/TRIM21 and Anti-Ro60/SSA Antibodies With Increased Sjögren Disease Severity Through Interferon Pathway Activation.

OBJECTIVE: The biologic diagnosis of primary Sjögren disease (SjD) mainly relies on anti-Ro60/SSA antibodies, whereas the significance of anti-Ro52/TRIM21 antibodies currently remains unclear. The aim of this study was to characterize the clinical, serological, biologic, transcriptomic, and interferon profiles of patients with SjD according to their anti-Ro52/TRIM21 antibody status. METHODS: Patients with SjD from the European PRECISESADS (n = 376) and the Brittany Diagnostic Suspicion of primitive Sjögren's Syndrome (DIApSS); (n = 146) cohorts were divided into four groups: double negative (Ro52-/Ro60-), isolated anti-Ro52/TRIM21 positive (Ro52+), isolated anti-Ro60/SSA positive (Ro60+), and double-positive (Ro52+/Ro60+) patients. Clinical information; EULAR Sjögren Syndrome Disease Activity Index, a score representing systemic activity; and biologic markers associated with disease severity were evaluated. Transcriptome data obtained from whole blood by RNA sequencing and type I and II interferon signatures were analyzed for PRECISESADS patients. RESULTS: In the DIApSS cohort, Ro52+/Ro60+ patients showed significantly more parotidomegaly (33.3% vs 0%-11%) along with higher ß2-microglobulin (P = 0.0002), total immunoglobulin (P < 0.0001), and erythrocyte sedimentation rate levels (P = 0.002) as well as rheumatoid factor (RF) positivity (66.2% vs 20.8%-25%) compared to other groups. The PRECISESADS cohort corroborated these observations, with increased arthritis (P = 0.046), inflammation (P = 0.005), hypergammaglobulinemia (P < 0.0001), positive RF (P < 0.0001), leukopenia (P = 0.004), and lymphopenia (P = 0.009) in Ro52+/Ro60+ patients. Cumulative EULAR Sjögren Syndrome Disease Activity Index results further confirmed these disparities (P = 0.002). Transcriptome analysis linked anti-Ro52/TRIM21 antibody positivity to interferon pathway activation as an underlying cause for these clinical correlations. CONCLUSION: These results suggest that the combination of anti-Ro52/TRIM21 and anti-Ro60/SSA antibodies is associated with a clinical, biologic, and transcriptional profile linked to greater disease severity in SjD through the potentiation of the interferon pathway activation by anti-Ro52/TRIM21 antibodies.

ATG9A as a potential diagnostic marker of intervertebral disc degeneration: Inferences from experiments and bioinformatics analysis incorporating sc-RNA-seq data.

BACKGROUND: Disfunctional autophagy plays a pivotal role in Intervertebral Disc Degeneration (IDD) progression. however, the connection between Autophagy-related gene 9A (ATG9A) and IDD has not been reported. METHODS: Firstly, transcriptome datasets from the GEO and Autophagy-related genes (ARGs) from GeneCards were carried out using R. Following this, IDD-specific signature genes were identified through methods such as least absolute shrinkage and selection operator (LASSO), random forest (RF), and support vector machine (SVM) analyses. Validation of these findings proceeded through in vitro experiments, evaluation of independent datasets, and analysis of receiver operating characteristic (ROC) curves. Subsequent steps incorporated co-expression analysis, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Gene Set Enrichment Analysis (GSEA), and construction of competing endogenous RNA (ceRNA) network. The final section established the correlation between immune cell infiltration, ATG9A, and IDD utilizing the CIBERSORT algorithm and single-cell RNA (scRNA) sequencing data. RESULTS: Research identified 87 differentially expressed genes, with only ATG9A noted as an IDD signature gene. Analysis of in vitro experiments and independent datasets uncovered a decrease in ATG9A expression within the degeneration group. The area under the curve (AUC) of ATG9A exceeded 0.8 following ROC analysis. Furthermore, immune cell infiltration and scRNA sequencing data analysis elucidated the substantial role of immune cells in IDD progression. A ceRNA network was constructed, centered around ATG9A, included 4 miRNAs and 22 lncRNAs. CONCLUSION: ATG9A was identified as a diagnostic gene for IDD, indicating its viability as a effective target for therapy disease.

Comparative immunological landscape between pre- and early-stage LUAD manifested as ground-glass nodules revealed by scRNA and scTCR integrated analysis.

BACKGROUND: Mechanism underlying the malignant progression of precancer to early-stage lung adenocarcinoma (LUAD) as well as their indolence nature remains elusive. METHODS: Single-cell RNA sequencing (scRNA) with simultaneous T cell receptor (TCR) sequencing on 5 normal lung tissues, 3 precancerous and 4 early-stage LUAD manifested as pulmonary ground-glass nodules (GGNs) were performed. RESULTS: Through this integrated analysis, we have delineated five key modules that drive the malignant progression of early-stage LUAD in a disease stage-dependent manner. These modules are related to cell proliferation and metabolism, immune response, mitochondria, cilia, and cell adhesion. We also find that the tumor micro-environment (TME) of early-stage LUAD manifested as GGN are featured with regulatory T (Tregs) cells accumulation with three possible origins, and loss-functional state (decreased clonal expansion and cytotoxicity) of CD8 + T cells. Instead of exhaustion, the CD8 + T cells are featured with a shift to memory phenotype, which is significantly different from the late stage LUAD. Furthermore, we have identified monocyte-derived macrophages that undergo a lipid-phenotype transition and may contribute to the suppressive TME. Intense interaction between stromal cells, myeloid cells including lipid associated macrophages and LAMP3 + DCs, and lymphocytes were also characterized. CONCLUSIONS: Our work provides new insight into the molecular and cellular mechanism underlying malignant progression of LUAD manifested as GGN, and pave way for novel immunotherapies for GGN. Video Abstract.

Single-cell multi-omics topic embedding reveals cell-type-specific and COVID-19 severity-related immune signatures.

The advent of single-cell multi-omics sequencing technology makes it possible for researchers to leverage multiple modalities for individual cells and explore cell heterogeneity. However, the high-dimensional, discrete, and sparse nature of the data make the downstream analysis particularly challenging. Here, we propose an interpretable deep learning method called moETM to perform integrative analysis of high-dimensional single-cell multimodal data. moETM integrates multiple omics data via a product-of-experts in the encoder and employs multiple linear decoders to learn the multi-omics signatures. moETM demonstrates superior performance compared with six state-of-the-art methods on seven publicly available datasets. By applying moETM to the scRNA + scATAC data, we identified sequence motifs corresponding to the transcription factors regulating immune gene signatures. Applying moETM to CITE-seq data from the COVID-19 patients revealed not only known immune cell-type-specific signatures but also composite multi-omics biomarkers of critical conditions due to COVID-19, thus providing insights from both biological and clinical perspectives.

Detection of a 7SL RNA-derived small non-coding RNA using Molecular Beacons in vitro and in cells.

Small non-coding RNAs (sncRNA) are involved in many steps of the gene expression cascade and regulate processing and expression of mRNAs by the formation of ribonucleoprotein complexes (RNP) such as the RNA-induced silencing complex (RISC). By analyzing small RNA Seq data sets, we identified a sncRNA annotated as piR-hsa-1254, which is likely derived from the 3'-end of 7SL RNA2 (RN7SL2), herein referred to as snc7SL RNA. The 7SL RNA is an abundant long non-coding RNA polymerase III transcript and serves as structural component of the cytoplasmic signal recognition particle (SRP). To evaluate a potential functional role of snc7SL RNA, we aimed to define its cellular localization by live cell imaging. Therefore, a Molecular Beacon (MB)-based method was established to compare the subcellular localization of snc7SL RNA with its precursor 7SL RNA. We designed and characterized several MBs in vitro and tested those by live cell fluorescence microscopy. Using a multiplex approach, we show that 7SL RNA localizes mainly to the endoplasmic reticulum (ER), as expected for the SRP, whereas snc7SL RNA predominately localizes to the nucleus. This finding suggests a fundamentally different function of 7SL RNA and its derivate snc7SL RNA.

Association of Circulating Long Noncoding 7S RNA with Deep Vein Thrombosis.

Mitochondrial dysfunction is a recognized factor in the pathogenesis of deep vein thrombosis (DVT). The role of 7S RNA, a long noncoding RNA that plays an important role in mitochondrial function, in DVT remains unclear. In this study, we aimed to investigate the potential use of 7S RNA as a biomarker in DVT. Plasma samples were obtained from 237 patients (aged 16-95 years) with suspected DVT recruited in a prospective multicenter management study (SCORE) where 53 patients were objectively confirmed with a diagnosis of DVT and the rest were diagnosed as non-DVT. 7S RNA was measured using quantitative real-time polymerase chain reaction in plasma samples. The plasma expression of 7S RNA was significantly lower in DVT compared with non-DVT (0.50 vs. 0.95, p = 0.043). With the linear regression analysis, we showed that the association between the plasma expression of 7S RNA and DVT (ß = -0.72, p = 0.007) was independent of potential confounders. Receiver-operating characteristic curve analysis showed the area under the curve values of 0.60 for 7S RNA. The findings of the present study showed a notable association between 7S RNA and DVT. However, further investigations are needed to fully elucidate the exact role of 7S RNA in the pathophysiology of DVT and its diagnostic value.

Incorporating cell hierarchy to decipher the functional diversity of single cells.

Cells possess functional diversity hierarchically. However, most single-cell analyses neglect the nested structures while detecting and visualizing the functional diversity. Here, we incorporate cell hierarchy to study functional diversity at subpopulation, club (i.e., sub-subpopulation), and cell layers. Accordingly, we implement a package, SEAT, to construct cell hierarchies utilizing structure entropy by minimizing the global uncertainty in cell-cell graphs. With cell hierarchies, SEAT deciphers functional diversity in 36 datasets covering scRNA, scDNA, scATAC, and scRNA-scATAC multiome. First, SEAT finds optimal cell subpopulations with high clustering accuracy. It identifies cell types or fates from omics profiles and boosts accuracy from 0.34 to 1. Second, SEAT detects insightful functional diversity among cell clubs. The hierarchy of breast cancer cells reveals that the specific tumor cell club drives AREG-EGFT signaling. We identify a dense co-accessibility network of cis-regulatory elements specified by one cell club in GM12878. Third, the cell order from the hierarchy infers periodic pseudo-time of cells, improving accuracy from 0.79 to 0.89. Moreover, we incorporate cell hierarchy layers as prior knowledge to refine nonlinear dimension reduction, enabling us to visualize hierarchical cell layouts in low-dimensional space.

The crucial roles of long noncoding RNA SNHGs in lung cancer

Lung cancer is one of the most common malignant tumors with growing morbidity and mortality worldwide. Several treatments are used to manage lung cancer, including surgery, radiotherapy and chemotherapy, as well as molecular-targeted therapy. However, the current measures are still far from satisfactory. Therefore, the current research should focus on exploring the molecular mechanism and then finding an effective treatment. Interestingly, we and others have embarked on a line of investigations focused on the mechanism of lung cancer. Specifically, lncRNA small nucleolar RNA host gene has been shown to be associated with biological characteristics and therapeutic resistance of lung cancer. In addition, small nucleolar RNA host genes may be used as diagnostic biomarker in the future. Herein, we will provide a brief review demonstrating the importance of small nucleolar RNA host genes in lung cancer, especially non-small cell lung cancer. Although lncRNA has shown a crucial role in tumor-related research, a large number of studies are needed to validate its clinical application in the future (AU)

Cancer cell-derived exosomal LINC00313 induces M2 macrophage differentiation in non-small cell lung cancer

Purpose Non-small cell lung cancer (NSCLC) is the major subtype of lung cancer, which is the leading cause of cancer death worldwide. Tumor-associated macrophages (TAMs) are one of the main non-tumor cells in the tumor microenvironment. Here, we investigated the effect of cancer cell-derived exosomal LINC00313 on the M2 macrophage differentiation in NSCLC and clarified its underlying mechanism. Methods Flow cytometry, Western blotting, ELISA and immunohistochemical staining were performed to identify the macrophage phenotype by detecting the expression of M2 markers. The expression levels of LINC00313 and miR-135a-3p were measured by qRT-PCR, and luciferase reporter assay was used to validate the binding of lncRNA to miRNA, and miRNA to the target gene STAT6. The mouse-xenograft models were established by subcutaneous injection of the NCl-H1299 cells with stable overexpression or knockdown of LINC00313. GW4869 was injected intra-tumorally after tumor implantation. Results It was found that the cancer cells promoted M2 macrophage differentiation by secreting exosomes. LINC00313 was overexpressed in H1299-derived exosomes, and its knockdown abolished the effect of H1299-induced M2 macrophage differentiation. LINC00313 sponged miR-135a-3p to increase the STAT6 expression, resulting in the M2 macrophage differentiation. LINC00313 promoted tumor progression and promoted the expression of M2 markers in isolated tumor macrophages. A novel regulatory mechanism of M2 macrophage differentiation in NSCLC was revealed. It was found that cancer cell-derived exosomal LINC00313 promoted M2 macrophage differentiation in NSCLC by up-regulating STAT6 as miR-135a-3p sponge. Conclusions This study provides a new mechanism and direction to prevent the M2 macrophage differentiation in NSCLC (AU)

[scRNA-sequencing uncovers metabolism and CD52 as new targets in ibrutinib-surviving mantle cell lymphoma cells]. / Eine Einzelzell-RNA-Sequenzierung identifiziert Metabolismus und CD52 als neue Angriffspunkte in Ibrutinib-persistenten Mantelzelllymphomzellen.

BACKGROUND: Ibrutinib improves the treatment of relapsed or refractory mantle cell lymphoma, a mature B cell neoplasm. However, relapses following treatment with this Bruton tyrosine kinase inhibitor occur frequently, and the outcome of affected patients is poor. OBJECTIVES: Single-cell RNA sequencing (scRNA-seq) can track trends in gene expression of mantle cell lymphoma cells across ibrutinib treatment and new therapeutic targets can be defined based on the detected resistance mechanisms. MATERIALS AND METHODS: The ibrutinib-sensitive mantle cell lymphoma cell line REC­1 was treated with ibrutinib for 6 h and 48 h. Droplet-based scRNA-seq was performed to examine the transcriptomic alterations of surviving cells using the 10× Genomics platform. Extracellular flux analysis and flow cytometry were applied to further study the observed adaptations to ibrutinib treatment. RESULTS: REC­1 harbored a subpopulation with potential for crosstalk with microenvironment and therefore greater risk for aggressiveness and drug resistance. Following ibrutinib treatment, NF-κB signaling was turned off. In contrast, the cells upregulated B-cell receptor genes and surface antigens such as CD52, and switched their metabolism to increased dependence on oxidative phosphorylation. CONCLUSIONS: Targeting oxidative phosphorylation or CD52 in combination with or as follow-up to ibrutinib might overcome resistance and provide improved prognosis for mantle cell lymphoma patients.

scRNA-sequencing reveals subtype-specific transcriptomic perturbations in DRG neurons of PirtEGFPf mice in neuropathic pain condition.

Functionally distinct subtypes/clusters of dorsal root ganglion (DRG) neurons may play different roles in nerve regeneration and pain. However, details about their transcriptomic changes under neuropathic pain conditions remain unclear. Chronic constriction injury (CCI) of the sciatic nerve represents a well-established model of neuropathic pain, and we conducted single-cell RNA-sequencing (scRNA-seq) to characterize subtype-specific perturbations of transcriptomes in lumbar DRG neurons on day 7 post-CCI. By using PirtEGFPf mice that selectively express an enhanced green fluorescent protein in DRG neurons, we established a highly efficient purification process to enrich neurons for scRNA-seq. We observed the emergence of four prominent CCI-induced clusters and a loss of marker genes in injured neurons. Importantly, a portion of injured neurons from several clusters were spared from injury-induced identity loss, suggesting subtype-specific transcriptomic changes in injured neurons. Moreover, uninjured neurons, which are necessary for mediating the evoked pain, also demonstrated cell-type-specific transcriptomic perturbations in these clusters, but not in others. Notably, male and female mice showed differential transcriptomic changes in multiple neuronal clusters after CCI, suggesting transcriptomic sexual dimorphism in DRG neurons after nerve injury. Using Fgf3 as a proof-of-principle, RNAscope study provided further evidence of increased Fgf3 in injured neurons after CCI, supporting scRNA-seq analysis, and calcium imaging study unraveled a functional role of Fgf3 in neuronal excitability. These findings may contribute to the identification of new target genes and the development of DRG neuron cell-type-specific therapies for optimizing neuropathic pain treatment and nerve regeneration.

Significance of macrophage infiltration in the prognosis of lung adenocarcinoma patients evaluated by scRNA and bulkRNA analysis.

Purpose: To investigate the significance of macrophage infiltration to the prognosis of lung adenocarcinoma. Methods: R language bioinformatics analysis technology, was used to obtain macrophage infiltration-related module genes through WGCNA (Weighted Gene Co-Expression Network Analysis). Marker genes of macrophage subtypes were identified using single-cell sequencing of lung adenocarcinoma tissue. Risk score models were constructed and validated using external data cohorts and clinical samples. Results: Analysis of cohorts TCGA-LUAD, GSE11969, GSE31210, GSE50081, GSE72094 and GSE8894, revealed a negative correlation between macrophage infiltration and survival. Immunohistochemical analyses of clinical samples were consistent with these data. Based on cell-cluster-markers and TAMs-related-genes, TOP8 genes were obtained (C1QTNF6, CCNB1, FSCN1, HMMR, KPNA2, PRC1, RRM2, and TK1) with a significant association to prognosis. Risk score models including 9 factors (C1QTNF6, FSCN1, KPNA2, GLI2, TYMS, BIRC3, RBBP7, KRT8, GPR65) for prognosis were constructed. The efficacy, stability and generalizability of the risk score models were validated using multiple data cohorts (GSE19188, GSE26939, GSE31210, GSE50081, GSE42127, and GSE72094). Conclusions: Macrophage infiltration negatively correlates with prognosis in patients with lung adenocarcinoma. Based on cell-cluster-markers and TAMs-related-genes, both TOP8 genes (C1QTNF6, CCNB1, FSCN1, HMMR, KPNA2, PRC1, RRM2, TK1) and risk score models using C1QTNF6, FSCN1, KPNA2, GLI2, TYMS, BIRC3, RBBP7, KRT8, GPR65 could predict disease prognosis.

Characterization of KIR+CD8+ Regulatory T Cells in Humans by scRNA- and TCR-seq.

Previous studies have demonstrated the regulatory functions of Ly49+CD8+ T cells toward self-reactive CD4+ T cells in mice. Recently, we found KIR+CD8+ T cells are the equivalent of mouse Ly49+CD8+ T cells in humans. They are increased in patients with autoimmune or infectious diseases as a negative feedback mechanism to suppress the arising pathogenic cells and maintain peripheral tolerance. Here, we describe the methods on how we characterize the KIR+CD8+ T cells from different diseases using single-cell RNA and TCR sequencing.