Single-cell sequencing analysis related to sphingolipid metabolism guides immunotherapy and prognosis of skin cutaneous melanoma

Integrative Single-Cell Analysis of Cardiomyopathy Identifies Differences in Cell Stemness and Transcriptional Regulatory Networks among Fibroblast Subpopulations

Background

Cardiomyopathy encompasses a broad spectrum of diseases affecting myocardial tissue, characterized clinically by abnormalities in cardiac structure, heart failure, and/or arrhythmias. Clinically heterogeneous, major types include dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), restrictive cardiomyopathy (RM), ischemic cardiomyopathy (ICM), among which DCM is more prevalent, while ICM exhibits higher incidence and mortality rates. Myocardial injury during cardiomyopathy progression may lead to myocardial fibrosis. Failure to intervene early and inhibit the process of myocardial fibrosis may culminate in heart failure. Cardiac fibroblasts constitute crucial cellular components determining the extent and quality of myocardial fibrosis, with various subpopulations exerting diverse roles in cardiomyopathy progression. Despite this, understanding of the cellular plasticity and transcriptional regulatory networks of cardiac fibroblasts in cardiomyopathy remains limited. Therefore, in this study, we conducted comprehensive single-cell analysis of cardiac fibroblasts in cardiomyopathy to explore differences in cellular plasticity and transcriptional regulatory networks among fibroblast subpopulations, with the aim of providing as many useful references as possible for the diagnosis, prognosis, and treatment of cardiomyopathy.

Materials and Methods

Cells with mitochondrial gene expression comprising >20% of total expressed genes were excluded. Differential expression genes (DEGs) and stemness genes within cardiac fibroblast subpopulations were subjected to Gene Ontology (GO) analysis of biological processes (BP) and AUCell analysis. Monocle software was employed to analyze the pseudo-temporal trajectory of cardiac fibroblasts in cardiomyopathy. Additionally, the Python package SCENIC was utilized to assess enrichment of transcription factors and activity of regulators within cardiac fibroblast subpopulations in cardiomyopathy.

Results

Following batch effect correction, 179,927 cells were clustered into 32 clusters, designated as T_NK cells, endothelial cells, myeloid cells, fibroblasts, pericytes, SMCs, CMs, proliferating cells, EndoCs, and EPCs. Among them, 8148 fibroblasts were further subdivided into 4 subpopulations, namely C0 THBS4+ Fibroblasts, C1 LINC01133+ Fibroblasts, C2 FGF7+ Fibroblasts, and C3 AGT + Fibroblasts. Results from GO_BP and AUCell analyses suggest that C3 AGT + Fibroblasts may be associated with immune response activation, protein transport, and myocardial contractile function, correlating with disease progression in cardiomyopathy. Transcription factor enrichment analysis indicates that FOS is the most significant TF in C3 AGT + Fibroblasts, also associated with the M1 module, possibly implicated in protein hydrolysis, intracellular DNA replication, and cell proliferation. Moreover, correlation analysis of transcriptional regulatory activity between fibroblast subpopulations reveals a more pronounced heterogeneity within C3 AGT + Fibroblasts in cardiomyopathy.

Conclusion

C3 AGT + Fibroblasts exhibit increased sensitivity towards adverse outcomes in cardiomyopathy, such as myocardial fibrosis and impaired cardiac contractile function, compared to other cardiac fibroblast subpopulations. The differential cellular plasticity and transcriptional regulatory activity between C3 AGT + Fibroblasts and other subgroups offer new perspectives for targeting fibroblast subpopulation activity to treat cardiomyopathy. Additionally, stemness genes EPAS1 and MYC, along with the regulator FOS, may play roles in modulating the biological processes of cardiac fibroblasts in cardiomyopathy.

Identification of necroptosis-related gene signatures for predicting the prognosis of ovarian cancer

Ovarian cancer (OC) is one of the most prevalent and fatal malignant tumors of the female reproductive system. Our research aimed to develop a prognostic model to assist inclinical treatment decision-making.Utilizing data from The Cancer Genome Atlas (TCGA) and copy number variation (CNV) data from the University of California Santa Cruz (UCSC) database, we conducted analyses of differentially expressed genes (DEGs), gene function, and tumor microenvironment (TME) scores in various clusters of OC samples.Next, we classified participants into low-risk and high-risk groups based on the median risk score, thereby dividing both the training group and the entire group accordingly. Overall survival (OS) was significantly reduced in the high-risk group, and two independent prognostic factors were identified: age and risk score. Additionally, three genes-C-X-C Motif Chemokine Ligand 10 (CXCL10), RELB, and Caspase-3 (CASP3)-emerged as potential candidates for an independent prognostic signature with acceptable prognostic value. In Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, pathways related to immune responses and inflammatory cell chemotaxis were identified. Cellular experiments further validated the reliability and precision of our findings. In conclusion, necroptosis-related genes play critical roles in tumor immunity, and our model introduces a novel strategy for predicting the prognosis of OC patients.

Prediction of immunotherapy responsiveness in melanoma through single-cell sequencing-based characterization of the tumor immune microenvironment

Immune checkpoint inhibitors (ICB) therapy have emerged as effective treatments for melanomas. However, the response of melanoma patients to ICB has been highly heterogenous. Here, by analyzing integrated scRNA-seq datasets from melanoma patients, we revealed significant differences in the TiME composition between ICB-resistant and responsive tissues, with resistant or responsive tissues characterized by an abundance of myeloid cells and CD8+ T cells or CD4+ T cell predominance, respectively. Among CD4+ T cells, CD4+ CXCL13+ Tfh-like cells were associated with an immunosuppressive phenotype linked to immune escape-related genes and negative regulation of T cell activation. We also develop an immunotherapy response prediction model based on the composition of the immune compartment. Our predictive model was validated using CIBERSORTx on bulk RNA-seq datasets from melanoma patients pre- and post-ICB treatment and showed a better performance than other existing models. Our study presents an effective immunotherapy response prediction model with potential for further translation, as well as underscores the critical role of the TiME in influencing the response of melanomas to immunotherapy.

Combining bulk and scRNA-seq to explore the molecular mechanisms governing the distinct efferocytosis activities of a macrophage subpopulation in PDAC

Pancreatic ductal adenocarcinoma (PDAC), a very aggressive tumour, is currently the third leading cause of cancer-related deaths. Unfortunately, many patients face the issue of inoperability at the diagnostic phase leading to a quite dismal prognosis. The onset of metastatic processes has a crucial role in the elevated mortality rates linked to PDAC. Individuals with metastatic advances receive only palliative therapy and have a grim prognosis. It is essential to carefully analyse the intricacies of the metastatic process to enhance the prognosis for individuals with PDAC. Malignancy development is greatly impacted by the process of macrophage efferocytosis. Our current knowledge about the complete range of macrophage efferocytosis activities in PDAC and their intricate interactions with tumour cells is still restricted. This work aims to resolve communication gaps and pinpoint the essential transcription factor that is vital in the immunological response of macrophage populations. We analysed eight PDAC tissue samples sourced from the gene expression omnibus. We utilized several software packages such as Seurat, DoubletFinder, Harmony, Pi, GSVA, CellChat and Monocle from R software together with pySCENIC from Python, to analyse the single-cell RNA sequencing (scRNA-seq) data collected from the PDAC samples. This study involved the analysis of a comprehensive sample of 22,124 cells, which were classified into distinct cell types. These cell types encompassed endothelial and epithelial cells, PDAC cells, as well as various immune cells, including CD4+ T cells, CD8+ T cells, NK cells, B cells, plasma cells, mast cells, monocytes, DC cells and different subtypes of macrophages, namely C0 macrophage TGM2+, C1 macrophage PFN1+, C2 macrophage GAS6+ and C3 macrophage APOC3+. The differentiation between tumour cells and epithelial cells was achieved by the implementation of CopyKat analysis, resulting in the detection and categorization of 1941 PDAC cells. The amplification/deletion patterns observed in PDAC cells on many chromosomes differ significantly from those observed in epithelial cells. The study of Pseudotime Trajectories demonstrated that the C0 macrophage subtype expressing TGM2+ had the lowest level of differentiation. Additionally, the examination of gene set scores related to efferocytosis suggested that this subtype displayed higher activity during the efferocytosis process compared to other subtypes. The most active transcription factors for each macrophage subtype were identified as BACH1, NFE2, TEAD4 and ARID3A. In conclusion, the examination of human PDAC tissue samples using immunofluorescence analysis demonstrated the co-localization of CD68 and CD11b within regions exhibiting the presence of keratin (KRT) and alpha-smooth muscle actin (α-SMA). This observation implies a spatial association between macrophages, fibroblasts, and epithelial cells. There is variation in the expression of efferocytosis-associated genes between C0 macrophage TGM2+ and other macrophage cell types. This observation implies that the diversity of macrophage cells might potentially influence the metastatic advancement of PDAC. Moreover, the central transcription factor of different macrophage subtypes offers a promising opportunity for targeted immunotherapy in the treatment of PDAC.

Regulatory T cells subgroups in the tumor microenvironment cannot be overlooked: Their involvement in prognosis and treatment strategy in melanoma

BACKGROUND

Melanoma, the most lethal form of skin cancer, presents substantial challenges despite effective surgical interventions for in situ lesions. Regulatory T cells (Tregs) wield a pivotal immunomodulatory influence within the tumor microenvironment, yet their impact on melanoma prognosis and direct molecular interactions with melanoma cells remain elusive. This investigation employs single-cell analysis to unveil the intricate nature of Tregs in human melanoma.

METHODS

Single-cell RNA and bulk sequencing data, alongside clinical information, were obtained from public repositories. Initially, GO and GSEA analyses were employed to delineate functional disparities among distinct cell subsets. Pseudotime and cell-cell interconnection analyses were conducted, followed by an endeavor to construct a prognostic model grounded in Treg-associated risk scores. This model's efficacy was demonstrated via PCA and K-M analyses, with multivariate Cox regression affirming its independent prognostic value in melanoma patients. Furthermore, immune infiltration analysis, immune checkpoint gene expression scrutiny, and drug sensitivity assessments were performed to ascertain the clinical relevance of this prognostic model.

RESULTS

Following batch effect correction, 80 025 cells partitioned into 31 clusters, encompassing B cells, plasma cells, endothelial cells, fibroblasts, melanoma cells, monocytes, macrophages, and T_NK cells. Within these, 4240 CD4+ T cells were subclassified into seven distinct types. Functional analysis underscored the immunomodulatory function of Tregs within the melanoma tumor microenvironment, elucidating disparities among Treg subpopulations. Notably, the ITGB2 signaling pathway emerged as a plausible molecular nexus linking Tregs to melanoma cells. Our prognostic signature exhibited robust predictive capacities for melanoma prognosis and potential implications in evaluating immunotherapy response.

CONCLUSION

Tregs exert a critical role in immune suppression within the melanoma tumor microenvironment, revealing a potential molecular-level association with melanoma cells. Our innovative Treg-centered signature introduces a promising prognostic marker for melanoma, holding potential for future clinical prognostic assessments.

Deciphering the molecular landscape: integrating single-cell transcriptomics to unravel myofibroblast dynamics and therapeutic targets in clear cell renal cell carcinomas

Background

Clear cell renal cell carcinomas (ccRCCs) epitomize the most formidable clinical subtype among renal neoplasms. While the impact of tumor-associated fibroblasts on ccRCC progression is duly acknowledged, a paucity of literature exists elucidating the intricate mechanisms and signaling pathways operative at the individual cellular level.

Methods

Employing single-cell transcriptomic analysis, we meticulously curated UMAP profiles spanning substantial ccRCC populations, delving into the composition and intrinsic signaling pathways of these cohorts. Additionally, Myofibroblasts were fastidiously categorized into discrete subpopulations, with a thorough elucidation of the temporal trajectory relationships between these subpopulations. We further probed the cellular interaction pathways connecting pivotal subpopulations with tumors. Our endeavor also encompassed the identification of prognostic genes associated with these subpopulations through Bulk RNA-seq, subsequently validated through empirical experimentation.

Results

A notable escalation in the nFeature and nCount of Myofibroblasts and EPCs within ccRCCs was observed, notably enriched in oxidation-related pathways. This phenomenon is postulated to be closely associated with the heightened metabolic activities of Myofibroblasts and EPCs. The Myofibroblasts subpopulation, denoted as C3 HMGA1+ Myofibroblasts, emerges as a pivotal subset, displaying low differentiation and positioning itself at the terminal point of the temporal trajectory. Intriguingly, these cells exhibit a high degree of interaction with tumor cells through the MPZ signaling pathway network, suggesting that Myofibroblasts may facilitate tumor progression via this pathway. Prognostic genes associated with C3 were identified, among which TUBB3 is implicated in potential resistance to tumor recurrence. Finally, experimental validation revealed that the knockout of the key gene within the MPZ pathway, MPZL1, can inhibit tumor activity, proliferation, invasion, and migration capabilities.

Conclusion

This investigation delves into the intricate mechanisms and interaction pathways between Myofibroblasts and ccRCCs at the single-cell level. We propose that targeting MPZL1 and the oxidative phosphorylation pathway could serve as potential key targets for treating the progression and recurrence of ccRCC. This discovery paves the way for new directions in the treatment and prognosis diagnosis of ccRCC in the future.

Investigating the mechanisms of drug resistance and prognosis in ovarian cancer using single-cell RNA sequencing and bulk RNA sequencing

Ovarian cancer stands as a prevalent malignancy within the realm of gynecology, and the emergence of resistance to chemotherapeutic agents remains a pivotal impediment to both prognosis and treatment. Through a single-cell level investigation, we scrutinize the drug resistance and mitotic activity of the core tumor cells in ovarian cancer. Our study revisits the interrelationships and temporal trajectories of distinct epithelial cells (EPCs) subpopulations, while identifying genes associated with ovarian cancer prognosis. Notably, our findings establish a strong association between the drug resistance of EPCs and oxidative phosphorylation pathways. Subsequently, through subpopulation and temporal trajectory analysis, we confirm the intermediate position of EPCs subpopulation C0. Furthermore, we delve into the immunological functions and differentially expressed genes associated with the prognosis of C0, shedding light on the potential for constructing novel ovarian cancer prognosis models and identifying new therapeutic targets.

Unraveling the intricacies of glioblastoma progression and recurrence: insights into the role of NFYB and oxidative phosphorylation at the single-cell level

Background

Glioblastoma (GBM), with its high recurrence and mortality rates, makes it the deadliest neurological malignancy. Oxidative phosphorylation is a highly active cellular pathway in GBM, and NFYB is a tumor-associated transcription factor. Both are related to mitochondrial function, but studies on their relationship with GBM at the single-cell level are still scarce.

Methods

We re-analyzed the single-cell profiles of GBM from patients with different subtypes by single-cell transcriptomic analysis and further subdivided the large population of Glioma cells into different subpopulations, explored the interrelationships and active pathways among cell stages and clinical subtypes of the populations, and investigated the relationship between the transcription factor NFYB of the key subpopulations and GBM, searching for the prognostic genes of GBM related to NFYB, and verified by experiments.

Results

Glioma cells and their C5 subpopulation had the highest percentage of G2M staging and rGBM, which we hypothesized might be related to the higher dividing and proliferating ability of both Glioma and C5 subpopulations. Oxidative phosphorylation pathway activity is elevated in both the Glioma and C5 subgroup, and NFYB is a key transcription factor for the C5 subgroup, suggesting its possible involvement in GBM proliferation and recurrence, and its close association with mitochondrial function. We also identified 13 prognostic genes associated with NFYB, of which MEM60 may cause GBM patients to have a poor prognosis by promoting GBM proliferation and drug resistance. Knockdown of the NFYB was found to contribute to the inhibition of proliferation, invasion, and migration of GBM cells.

Conclusion

These findings help to elucidate the key mechanisms of mitochondrial function in GBM progression and recurrence, and to establish a new prognostic model and therapeutic target based on NFYB.

Decoding the tumor microenvironment and molecular mechanism: unraveling cervical cancer subpopulations and prognostic signatures through scRNA-Seq and bulk RNA-seq analyses

Background

Cervical carcinoma (CC) represents a prevalent gynecological neoplasm, with a discernible rise in prevalence among younger cohorts observed in recent years. Nonetheless, the intrinsic cellular heterogeneity of CC remains inadequately investigated.

Methods

We utilized single-cell RNA sequencing (scRNA-seq) transcriptomic analysis to scrutinize the tumor epithelial cells derived from four specimens of cervical carcinoma (CC) patients. This method enabled the identification of pivotal subpopulations of tumor epithelial cells and elucidation of their contributions to CC progression. Subsequently, we assessed the influence of associated molecules in bulk RNA sequencing (Bulk RNA-seq) cohorts and performed cellular experiments for validation purposes.

Results

Through our analysis, we have discerned C3 PLP2+ Tumor Epithelial Progenitor Cells as a noteworthy subpopulation in cervical carcinoma (CC), exerting a pivotal influence on the differentiation and progression of CC. We have established an independent prognostic indicator-the PLP2+ Tumor EPCs score. By stratifying patients into high and low score groups based on the median score, we have observed that the high-score group exhibits diminished survival rates compared to the low-score group. The correlations observed between these groups and immune infiltration, enriched pathways, single-nucleotide polymorphisms (SNPs), drug sensitivity, among other factors, further underscore their impact on CC prognosis. Cellular experiments have validated the significant impact of ATF6 on the proliferation and migration of CC cell lines.

Conclusion

This study enriches our comprehension of the determinants shaping the progression of CC, elevates cognizance of the tumor microenvironment in CC, and offers valuable insights for prospective CC therapies. These discoveries contribute to the refinement of CC diagnostics and the formulation of optimal therapeutic approaches.

Global, Regional, and National Incidence Trend Analysis of Malignant Skin Melanoma Between 1990 and 2019, and Projections Until 2034

BACKGROUND

The goal of this study was to evaluate the global burden of malignant skin melanoma (MSM) from 1990 to 2019 using MSM-related data from the Global Burden of Disease study.

METHODS

The incidences' relationships with the social-demographic index (SDI) and human developmental index (HDI) were investigated. To determine significant changes in incidence trends, the joinpoint regression model was used. To demonstrate trends in MSM mortality rates, an Age-Period-Cohort framework was conducted. For the projection of new cases and the age-standardized incidence rate (ASR) of MSM incidence to 2034, the Nordpred method was used.

RESULTS

In 2019, the ASR incidence per 100, 000 people for MSM was 3.6 (95% UI, 2.6-4.2). MSM prevalence increased in most countries between 1990 and 2019 (average annual percentage change >0). HDI and annual percentage change (APC) (ρ = .63, P < .001), as well as SDI and ASR, had a positive correlation. The total MSM mortality rate declined globally, with an APC of -.61%. Likewise, the mortality rate for the age group of people with ages <77.5 years declined. Predictive analysis demonstrated a declining trend in ASR incidence and a growing number of MSM.

CONCLUSION

There are significant differences in ASR incidence among regions and countries. Despite decreases in ASR incidence and fatality, MSM remains one of the leading sources of cancer mortality and morbidity globally. MSM necessitates more primary prevention measures and screening in high-risk areas.