Combining single-cell and bulk RNA sequencing, NK cell marker genes reveal a prognostic and immune status in pancreatic ductal adenocarcinoma.

The NK cell is an important component of the tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC), also plays a significant role in PDAC development. This study aimed to explore the relationship between NK cell marker genes and prognosis, immune response of PDAC patients. By scRNA-seq data, we found the proportion of NK cells were significantly downregulated in PDAC and 373 NK cell marker genes were screened out. By TCGA database, we enrolled 7 NK cell marker genes to construct the signature for predicting prognosis in PDAC patients. Cox analysis identified the signature as an independent factor for pancreatic cancer. Subsequently, the predictive power of signature was validated by 6 GEO datasets and had an excellent evaluation. Our analysis of relationship between the signature and patients' immune status revealed that the signature has a strong correlation with immunocyte infiltration, inflammatory reaction, immune checkpoint inhibitors (ICIs) response. The NK cell marker genes are closely related to the prognosis and immune capacity of PDAC patients, and they have potential value as a therapeutic target.

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.

Bone marrow cells contribute to seven different endothelial cell populations in the heart.

Understanding the mechanisms underlying vascular regeneration in the heart is crucial for developing novel therapeutic strategies for myocardial ischemia. This study investigates the contribution of bone marrow-derived cells to endothelial cell populations in the heart, and their role in cardiac function and coronary circulation following repetitive ischemia (RI). Chimeric rats were created by transplanting BM cells from GFP female rats into irradiated male recipients. After engraftment chimeras were subjected to RI for 17 days. Vascular growth was assessed from recovery of cardiac function and increases in myocardial blood flow during LAD occlusion. After sorting GFP+ BM cells from heart and bone of Control and RI rats, single-cell RNA sequencing was implemented to determine the fate of BM cells. Our in vivo RI model demonstrated an improvement in cardiac function and myocardial blood flow after 17 days of RI with increased capillary density in the rats subjected to RI compared to Controls. Single-cell RNA sequencing of bone marrow cells isolated from rats' hearts identified distinct endothelial cell (EC) subpopulations. These ECs exhibited heterogeneous gene expression profiles and were enriched for markers of capillary, artery, lymphatic, venous, and immune ECs. Furthermore, BM-derived ECs in the RI group showed an angiogenic profile, characterized by upregulated genes associated with blood vessel development and angiogenesis. This study elucidates the heterogeneity of bone marrow-derived endothelial cells in the heart and their response to repetitive ischemia, laying the groundwork for targeting specific subpopulations for therapeutic angiogenesis in myocardial ischemia.

The Novel-B-Cell-Related Gene Signature Predicts the Prognosis and Immune Status of Patients with Esophageal Carcinoma.

BACKGROUND: The current understanding of the prognostic significance of B cells and their role in the tumor microenvironment (TME) in esophageal carcinoma (ESCA) is limited. METHODS: We conducted a screening for B-cell-related genes through the analysis of single-cell transcriptome data. Subsequently, we developed a B-cell-related gene signature (BRGrisk) using LASSO regression analysis. Patients from The Cancer Genome Atlas cohort were divided into a training cohort and a test cohort. Patients were categorized into high- and low-risk groups based on their median BRGrisk scores. The overall survival was assessed using the Kaplan-Meier method, and a nomogram based on BRGrisk was constructed. Immune infiltration profiles between the risk groups were also compared. RESULTS: The BRGrisk prognostic model indicated significantly worse outcomes for patients with high BRGrisk scores (p < 0.001). The BRGrisk-based nomogram exhibited good prognostic performance. Analysis of immune infiltration revealed that patients in the high-BRGrisk group had notably higher levels of immune cell infiltration and were more likely to be in an immunoresponsive state. Enrichment analysis showed a strong correlation between the prognostic gene signature and cancer-related pathways. IC50 results indicated that patients in the low-BRGrisk group were more responsive to common drugs compared to those in the high-BRGrisk group. CONCLUSIONS: This study presents a novel BRGrisk that can be used to stratify the prognosis of ESCA patients and may offer guidance for personalized treatment strategies aimed at improving prognosis.

Integrated analysis of single-cell RNA-seq, bulk RNA-seq, Mendelian randomization, and eQTL reveals T cell-related nomogram model and subtype classification in rheumatoid arthritis.

Objective: Rheumatoid arthritis (RA) is a systemic disease that attacks the joints and causes a heavy economic burden on humans worldwide. T cells regulate RA progression and are considered crucial targets for therapy. Therefore, we aimed to integrate multiple datasets to explore the mechanisms of RA. Moreover, we established a T cell-related diagnostic model to provide a new method for RA immunotherapy. Methods: scRNA-seq and bulk-seq datasets for RA were obtained from the Gene Expression Omnibus (GEO) database. Various methods were used to analyze and characterize the T cell heterogeneity of RA. Using Mendelian randomization (MR) and expression quantitative trait loci (eQTL), we screened for potential pathogenic T cell marker genes in RA. Subsequently, we selected an optimal machine learning approach by comparing the nine types of machine learning in predicting RA to identify T cell-related diagnostic features to construct a nomogram model. Patients with RA were divided into different T cell-related clusters using the consensus clustering method. Finally, we performed immune cell infiltration and clinical correlation analyses of T cell-related diagnostic features. Results: By analyzing the scRNA-seq dataset, we obtained 10,211 cells that were annotated into 7 different subtypes based on specific marker genes. By integrating the eQTL from blood and RA GWAS, combined with XGB machine learning, we identified a total of 8 T cell-related diagnostic features (MIER1, PPP1CB, ICOS, GADD45A, CD3D, SLFN5, PIP4K2A, and IL6ST). Consensus clustering analysis showed that RA could be classified into two different T-cell patterns (Cluster 1 and Cluster 2), with Cluster 2 having a higher T-cell score than Cluster 1. The two clusters involved different pathways and had different immune cell infiltration states. There was no difference in age or sex between the two different T cell patterns. In addition, ICOS and IL6ST were negatively correlated with age in RA patients. Conclusion: Our findings elucidate the heterogeneity of T cells in RA and the communication role of these cells in an RA immune microenvironment. The construction of T cell-related diagnostic models provides a resource for guiding RA immunotherapeutic strategies.

Lipid-associated macrophages reshape BAT cell identity in obesity.

Obesity and type 2 diabetes cause a loss in brown adipose tissue (BAT) activity, but the molecular mechanisms that drive BAT cell remodeling remain largely unexplored. Using a multilayered approach, we comprehensively mapped a reorganization in BAT cells. We uncovered a subset of macrophages as lipid-associated macrophages (LAMs), which were massively increased in genetic and dietary model of BAT expansion. LAMs participate in this scenario by capturing extracellular vesicles carrying damaged lipids and mitochondria released from metabolically stressed brown adipocytes. CD36 scavenger receptor drove LAM phenotype, and CD36-deficient LAMs were able to increase brown fat genes in adipocytes. LAMs released transforming growth factor ß1 (TGF-ß1), which promoted the loss of brown adipocyte identity through aldehyde dehydrogenase 1 family member A1 (Aldh1a1) induction. These findings unfold cell dynamic changes in BAT during obesity and identify LAMs as key responders to tissue metabolic stress and drivers of loss of brown adipocyte identity.

A distinct subset of urothelial cells with enhanced EMT features promotes chemotherapy resistance and cancer recurrence by increasing COL4A1-ITGB1 mediated angiogenesis.

Drug resistance and tumor recurrence remain clinical challenges in the treatment of urothelial carcinoma (UC). However, the underlying mechanism is not fully understood. Here, we performed single-cell RNA sequencing and identified a subset of urothelial cells with epithelial-mesenchymal transition (EMT) features (EMT-UC), which is significantly correlated with chemotherapy resistance and cancer recurrence. To validate the clinical significance of EMT-UC, we constructed EMT-UC like cells by introducing overexpression of two markers, Zinc Finger E-Box Binding Homeobox 1 (ZEB1) and Desmin (DES), and examined their histological distribution characteristics and malignant phenotypes. EMT-UC like cells were mainly enriched in UC tissues from patients with adverse prognosis and exhibited significantly elevated EMT, migration and gemcitabine tolerance in vitro. However, EMT-UC was not specifically identified from tumorous tissues, certain proportion of them were also identified in adjacent normal tissues. Tumorous EMT-UC highly expressed genes involved in malignant behaviors and exhibited adverse prognosis. Additionally, tumorous EMT-UC was associated with remodeled tumor microenvironment (TME), which exhibited high angiogenic and immunosuppressive potentials compared with the normal counterparts. Furthermore, a specific interaction of COL4A1 and ITGB1 was identified to be highly enriched in tumorous EMT-UC, and in the endothelial component. Targeting the interaction of COL4A1 and ITGB1 with specific antibodies significantly suppressed tumorous angiogenesis and alleviated gemcitabine resistance of UC. Overall, our findings demonstrated that the driven force of chemotherapy resistance and recurrence of UC was EMT-UC mediated COL4A1-ITGB1 interaction, providing a potential target for future UC treatment.

CD300LF+ microglia impede the neuroinflammation following traumatic brain injury by inhibiting STING pathway.

INTRODUCTION: The diversity in microglial phenotypes and functions following traumatic brain injury (TBI) is poorly characterized. The aim of this study was to explore precise targets for improving the prognosis of TBI patients from a microglial perspective. OBJECTIVES: To assess whether the prognosis of TBI can be improved by modulating microglia function. RESULTS: In CD300LF-deficient mice, we observed an increase in glial cell proliferation, more extensive neuronal loss, and worsened neurological function post-TBI. Transcriptomic comparisons between CD300LF-positive and CD300LF-negative microglia illuminated that the neuroprotective role of CD300LF is principally mediated by the inhibition of the STING signaling pathway. In addition, this protective effect can be augmented using the STING pathway inhibitor C-176. CONCLUSIONS: Our research indicates that CD300LF reduces neuroinflammation and promotes neurological recovery after TBI, and that microglia are integral to the protective effects of CD300LF in this context. In summary, our findings highlight CD300LF as a critical molecular regulator modulating the adverse actions of microglia following acute brain injury and propose a novel therapeutic approach to enhance outcomes for patients with TBI.

Prostate cancer cancer-associated fibroblasts with stable markers post-androgen deprivation therapy associated with tumor progression and castration resistant prostate cancer.

The specificity and clinical relevance of cancer-associated fibroblasts (CAFs) in prostate cancer (PCa), as well as the effect of androgen deprivation therapy (ADT) on CAFs, remain to be fully elucidated. Using cell lineage diversity and weighted gene co-expression network analysis (WGCNA), we pinpointed a unique CAF signature exclusive to PCa. The specificity of this CAF signature was validated through single-cell RNA sequencing (scRNA-seq), cell line RNA sequencing, and immunohistochemistry. This signature associates CAFs with tumor progression, elevated Gleason scores, and the emergence of castration resistant prostate cancer (CRPC). Using scRNA-seq on collected samples, we demonstrated that the CAF-specific signature is not altered by ADT, maintaining its peak signal output. Identifying a PCa-specific CAF signature and observing signaling changes in CAFs after ADT lay essential groundwork for further PCa studies.

RNA-binding protein AZGP1 inhibits epithelial cell proliferation by regulating the genes of alternative splicing in COPD.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is characterized by high morbidity, disability, and mortality rates worldwide. RNA-binding proteins (RBPs) might regulate genes involved in oxidative stress and inflammation in COPD patients. Single-cell transcriptome sequencing (scRNA-seq) offers an accurate tool for identifying intercellular heterogeneity and the diversity of immune cells. However, the role of RBPs in the regulation of various cells, especially AT2 cells, remains elusive. MATERIALS AND METHODS: A scRNA-seq dataset (GSE173896) and a bulk RNA-seq dataset acquired from airway tissues (GSE124180) were employed for data mining. Next, RNA-seq analysis was performed in both COPD and control patients. Differentially expressed genes (DEGs) were identified using criteria of fold change (FC ≥ 1.5 or ≤ 1.5) and P value ≤ 0.05. Lastly, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and alternative splicing identification analyses were carried out. RESULTS: RBP genes exhibited specific expression patterns across different cell groups and participated in cell proliferation and mitochondrial dysfunction in AT2 cells. As an RBP, AZGP1 expression was upregulated in both the scRNA-seq and RNA-seq datasets. It might potentially be a candidate immune biomarker that regulates COPD progression by modulating AT2 cell proliferation and adhesion by regulating the expression of SAMD5, DNER, DPYSL3, GBP5, GBP3, and KCNJ2. Moreover, AZGP1 regulated alternative splicing events in COPD, particularly DDAH1 and SFRP1, holding significant implications in COPD. CONCLUSION: RBP gene AZGP1 inhibits epithelial cell proliferation by regulating genes participating in alternative splicing in COPD.

Characterizing efficient feature selection for single-cell expression analysis.

Unsupervised feature selection is a critical step for efficient and accurate analysis of single-cell RNA-seq data. Previous benchmarks used two different criteria to compare feature selection methods: (i) proportion of ground-truth marker genes included in the selected features and (ii) accuracy of cell clustering using ground-truth cell types. Here, we systematically compare the performance of 11 feature selection methods for both criteria. We first demonstrate the discordance between these criteria and suggest using the latter. We then compare the distribution of selected genes in their means between feature selection methods. We show that lowly expressed genes exhibit seriously high coefficients of variation and are mostly excluded by high-performance methods. In particular, high-deviation- and high-expression-based methods outperform the widely used in Seurat package in clustering cells and data visualization. We further show they also enable a clear separation of the same cell type from different tissues as well as accurate estimation of cell trajectories.

Human post-implantation blastocyst-like characteristics of Muse cells isolated from human umbilical cord.

Muse cells, identified as cells positive for the pluripotent surface marker SSEA-3, are pluripotent-like endogenous stem cells located in the bone marrow (BM), peripheral blood, and organ connective tissues. The detailed characteristics of SSEA-3(+) cells in extraembryonic tissue, however, are unknown. Here, we demonstrated that similar to human-adult tissue-Muse cells collected from the BM, adipose tissue, and dermis as SSEA-3(+), human-umbilical cord (UC)-SSEA-3(+) cells express pluripotency markers, differentiate into triploblastic-lineage cells at a single cell level, migrate to damaged tissue, and exhibit low telomerase activity and non-tumorigenicity. Notably, ~ 20% of human-UC-SSEA-3(+) cells were negative for X-inactive specific transcript (XIST), a naïve pluripotent stem cell characteristic, whereas all human adult tissue-Muse cells are XIST-positive. Single-cell RNA sequencing revealed that the gene expression profile of human-UC-SSEA-3(+) cells was more similar to that of human post-implantation blastocysts than human-adult tissue-Muse cells. The DNA methylation level showed the same trend, and notably, the methylation levels in genes particularly related to differentiation were lower in human-UC-SSEA-3(+) cells than in human-adult tissue-Muse cells. Furthermore, human-UC-SSEA-3(+) cells newly express markers specific to extraembryonic-, germline-, and hematopoietic-lineages after differentiation induction in vitro whereas human-adult tissue-Muse cells respond only partially to the induction. Among various stem/progenitor cells in living bodies, those that exhibit properties similar to post-implantation blastocysts in a naïve state have not yet been found in humans. Easily accessible human-UC-SSEA-3(+) cells may be a valuable tool for studying early-stage human development and human reproductive medicine.

Exploring the Pathogenesis of Autoimmune Liver Diseases from the Heterogeneity of Target Cells.

The incidence of autoimmune liver diseases (ALDs) and research on their pathogenesis are increasing annually. However, except for autoimmune hepatitis, which responds well to immunosuppression, primary biliary cholangitis and primary sclerosing cholangitis are insensitive to immunosuppressive therapy. Besides the known effects of the environment, genetics, and immunity on ALDs, the heterogeneity of target cells provides new insights into their pathogenesis. This review started by exploring the heterogeneity in the development, structures, and functions of hepatocytes and epithelial cells of the small and large bile ducts. For example, cytokeratin (CK) 8 and CK18 are primarily expressed in hepatocytes, while CK7 and CK19 are primarily expressed in intrahepatic cholangiocytes. Additionally, emerging technologies of single-cell RNA sequencing and spatial transcriptomic are being applied to study ALDs. This review offered a new perspective on understanding the pathogenic mechanisms and potential treatment strategies for ALDs.

Requirement of Pdgfrα+ cells for calvarial bone repair.

Platelet-derived growth factor receptor α (PDGFRα) is often considered as a general marker of mesenchymal cells and fibroblasts, but also shows expression in a portion of osteoprogenitor cells. Within the skeleton, Pdgfrα+ mesenchymal cells have been identified in bone marrow and periosteum of long bones, where they play a crucial role in participating in fracture repair. A similar examination of Pdgfrα+ cells in calvarial bone healing has not been examined. Here, we utilize Pdgfrα-CreERTM;mT/mG reporter animals to examine the contribution of Pdgfrα+ mesenchymal cells to calvarial bone repair through histology and single-cell RNA sequencing (scRNA-Seq). Results showed that Pdgfrα+ mesenchymal cells are present in several cell clusters by scRNA-Seq, and by histology a dramatic increase in Pdgfrα+ cells populated the defect site at early timepoints to give rise to healed bone tissue overtime. Notably, diphtheria toxin-mediated ablation of Pdgfrα reporter+ cells resulted in significantly impaired calvarial bone healing. Our findings suggest that Pdgfrα-expressing cells within the calvarial niche play a critical role in the process of calvarial bone repair.

Single-Cell RNA Sequencing Reveals Transcriptional Signatures and Cell-Cell Communication in Diabetic Retinopathy.

BACKGROUND: Diabetic retinopathy (DR) is a major cause of vision loss in workingage individuals worldwide. Cell-to-cell communication between retinal cells and retinal pigment epithelial cells (RPEs) in DR is still unclear, so this study aimed to generate a single-cell atlas and identify receptor‒ligand communication between retinal cells and RPEs. METHODS: A mouse single-cell RNA sequencing (scRNA-seq) dataset was retrieved from the GEO database (GSE178121) and was further analyzed with the R package Seurat. Cell cluster annotation was performed to further analyze cell‒cell communication. The differentially expressed genes (DEGs) in RPEs were explored through pathway enrichment analysis and the protein‒ protein interaction (PPI) network. Core genes in the PPI were verified by quantitative PCR in ARPE-19 cells. RESULTS: We observed an increased proportion of RPEs in STZ mice. Although some overall intercellular communication pathways did not differ significantly in the STZ and control groups, RPEs relayed significantly more signals in the STZ group. In addition, THBS1, ITGB1, COL9A3, ITGB8, VTN, TIMP2, and FBN1 were found to be the core DEGs of the PPI network in RPEs. qPCR results showed that the expression of ITGB1, COL9A3, ITGB8, VTN, TIMP2, and FBN1 was higher and consistent with scRNA-seq results in ARPE-19 cells under hyperglycemic conditions. CONCLUSION: Our study, for the first time, investigated how signals that RPEs relay to and from other cells underly the progression of DR based on scRNA-seq. These signaling pathways and hub genes may provide new insights into DR mechanisms and therapeutic targets.

Integrative Analysis of Long Isoform Sequencing and Functional Data Identifies Distinct Cortical Layer Neuronal Subtypes Derived from Human iPSCs.

Generation of human induced pluripotent stem cells (iPSCs) through reprogramming was a transformational change in the field of regenerative medicine that led to new possibilities for drug discovery and cell replacement therapy. Several protocols have been established to differentiate hiPSCs into neuronal lineages. However, low differentiation efficiency is one of the major drawbacks of these approaches. Here, we compared the efficiency of two methods of neuronal differentiation from iPSCs cultured in two different culture media, StemFlex Medium (SFM) and Essential 8 Medium (E8M). The results indicated that iPSCs cultured in E8M efficiently generated different types of neurons in a shorter time and without the growth of undifferentiated non-neuronal cells in the culture as compared to those generated from iPSCs in SFM. Furthermore, these neurons were validated as functional units immunocytochemically by confirming the expression of mature neuronal markers (i.e., NeuN, Beta tubulin, and Synapsin I), and whole-cell patch-clamp recordings. Long-read single-cell RNA sequencing confirms the presence of upper and deep layer cortical layer excitatory and inhibitory neuronal subtypes in addition to small populations of GABAergic neurons in day 30 neuronal cultures. Pathway analysis indicated that our protocol triggers the signaling transcriptional networks important for the process of neuronal differentiation in vivo.

Thyroid hormone T4 mitigates traumatic brain injury in mice by dynamically remodeling cell type specific genes, pathways, and networks in hippocampus and frontal cortex.

The complex pathology of mild traumatic brain injury (mTBI) is a main contributor to the difficulties in achieving a successful therapeutic regimen. Thyroxine (T4) administration has been shown to prevent the cognitive impairments induced by mTBI in mice but the mechanism is poorly understood. To understand the underlying mechanism, we carried out a single cell transcriptomic study to investigate the spatiotemporal effects of T4 on individual cell types in the hippocampus and frontal cortex at three post-injury stages in a mouse model of mTBI. We found that T4 treatment altered the proportions and transcriptomes of numerous cell types across tissues and timepoints, particularly oligodendrocytes, astrocytes, and microglia, which are crucial for injury repair. T4 also reversed the expression of mTBI-affected genes such as Ttr, mt-Rnr2, Ggn12, Malat1, Gnaq, and Myo3a, as well as numerous pathways such as cell/energy/iron metabolism, immune response, nervous system, and cytoskeleton-related pathways. Cell-type specific network modeling revealed that T4 mitigated select mTBI-perturbed dynamic shifts in subnetworks related to cell cycle, stress response, and RNA processing in oligodendrocytes. Cross cell-type ligand-receptor networks revealed the roles of App, Hmgb1, Fn1, and Tnf in mTBI, with the latter two ligands having been previously identified as TBI network hubs. mTBI and/or T4 signature genes were enriched for human genome-wide association study (GWAS) candidate genes for cognitive, psychiatric and neurodegenerative disorders related to mTBI. Our systems-level single cell analysis elucidated the temporal and spatial dynamic reprogramming of cell-type specific genes, pathways, and networks, as well as cell-cell communications as the mechanisms through which T4 mitigates cognitive dysfunction induced by mTBI.

Single-cell RNA-seq reveals the transcriptional program underlying tumor progression and metastasis in neuroblastoma.

Neuroblastoma (NB) is one of the most common childhood malignancies. Sixty percent of patients present with widely disseminated clinical signs at diagnosis and exhibit poor outcomes. However, the molecular mechanisms triggering NB metastasis remain largely uncharacterized. In this study, we generated a transcriptomic atlas of 15 447 NB cells from eight NB samples, including paired samples of primary tumors and bone marrow metastases. We used time-resolved analysis to chart the evolutionary trajectory of NB cells from the primary tumor to the metastases in the same patient and identified a common 'starter' subpopulation that initiates tumor development and metastasis. The 'starter' population exhibited high expression levels of multiple cell cycle-related genes, indicating the important role of cell cycle upregulation in NB tumor progression. In addition, our evolutionary trajectory analysis demonstrated the involvement of partial epithelial-to-mesenchymal transition (p-EMT) along the metastatic route from the primary site to the bone marrow. Our study provides insights into the program driving NB metastasis and presents a signature of metastasis-initiating cells as an independent prognostic indicator and potential therapeutic target to inhibit the initiation of NB metastasis.

Characterization of cuproptosis signature in clear cell renal cell carcinoma by single cell and spatial transcriptome analysis.

Cuproptosis is a novel type to regulate cell death with copper-dependent manner, and has been reported to involve in the occurrence and development of various malignant tumors. However, the association between cuproptosis and the tumor microenvironment (TME) of clear cell renal cell carcinoma (ccRCC) remained unclear. To address this question, we integrated the single cell RNA sequencing (scRNA-seq) datasets of ccRCC across different stages, systematically examined the distinctive expression patterns of cuproptosis-related genes (CRGs) within the TME of ccRCC, and explored the crucial signatures using the spatial transcriptome sequencing (ST-seq) dataset. The cuproptosis activities reduced in cancer tissues along with the ccRCC development, and recovered after therapy. We identified HILPDA+ ccRCC1 subtype, characterized with hypoxia, as cuproptosis susceptible cells associated with a better prognosis. The main co-expression modules of HILPDA+ ccRCC1 subtype highlighted the role in anion transport, response to oxygen species and PD-L1-PD-1 pathway. Furthermore, the immunosuppressive cells might interact with HILPDA+ ccRCC1 subtype via HAVCR2-LGALS9, C3-C3AR1, HLA-A-CD8B and HLA-C-CD8A axises to shape the cuproptosis-related TME landscape. In summary, we anticipate that this study will offer valuable insights and potential strategies of cuproptosis for therapy of ccRCC.

Developing an advanced diagnostic model for hepatocellular carcinoma through multi-omics integration leveraging diverse cell-death patterns.

Introduction: Hepatocellular carcinoma (HCC), representing more than 80% of primary liver cancer cases, lacks satisfactory etiology and diagnostic methods. This study aimed to elucidate the role of programmed cell death-associated genes (CDRGs) in HCC by constructing a diagnostic model using single-cell RNA sequencing (scRNA-seq) and RNA sequencing (RNA-seq) data. Methods: Six categories of CDRGs, including apoptosis, necroptosis, autophagy, pyroptosis, ferroptosis, and cuproptosis, were collected. RNA-seq data from blood-derived exosomes were sourced from the exoRBase database, RNA-seq data from cancer tissues from the TCGA database, and scRNA-seq data from the GEO database. Subsequently, we intersected the differentially expressed genes (DEGs) of the HCC cohort from exoRBase and TCGA databases with CDRGs, as well as DEGs obtained from single-cell datasets. Candidate biomarker genes were then screened using clinical indicators and a machine learning approach, resulting in the construction of a seven-gene diagnostic model for HCC. Additionally, scRNA-seq and spatial transcriptome sequencing (stRNA-seq) data of HCC from the Mendeley data portal were used to investigate the underlying mechanisms of these seven key genes and their association with immune checkpoint blockade (ICB) therapy. Finally, we validated the expression of key molecules in tissues and blood-derived exosomes through quantitative Polymerase Chain Reaction (qPCR) and immunohistochemistry experiments. Results: Collectively, we obtained a total of 50 samples and 104,288 single cells. Following the meticulous screening, we established a seven-gene diagnostic model for HCC, demonstrating high diagnostic efficacy in both the exoRBase HCC cohort (training set: AUC = 1; testing set: AUC = 0.847) and TCGA HCC cohort (training set: AUC = 1; testing set: AUC = 0.976). Subsequent analysis revealed that HCC cluster 3 exhibited a higher stemness index and could serve as the starting point for the differentiation trajectory of HCC cells, also displaying more abundant interactions with other cell types in the microenvironment. Notably, key genes TRIB3 and NQO1 displayed elevated expression levels in HCC cells. Experimental validation further confirmed their elevated expression in both tumor tissues and blood-derived exosomes of cancer patients. Additionally, stRNA analysis not only substantiated these findings but also suggested that patients with high TRIB3 and NQO1 expression might respond more favorably to ICB therapy. Conclusions: The seven-gene diagnostic model demonstrated remarkable accuracy in HCC screening, with TRIB3 emerging as a promising diagnostic tool and therapeutic target for HCC.