Single-cell histone chaperones patterns guide intercellular communication of tumor microenvironment that contribute to breast cancer metastases

Single-cell analysis unveils cell subtypes of acral melanoma cells at the early and late differentiation stages

BACKGROUND

Melanoma, a malignant neoplasm originating from melanocytes, is a form of skin cancer with rapidly increasing global incidence, often exacerbated by UV radiation[1]. Particularly, acral melanoma, characterized by its swift metastasis and poor prognosis, underscores the significance of further research into its heterogeneity. Single-cell sequencing has been widely utilized in the study of tumor heterogeneity; however, research related to melanoma remains to be further refined.

MATERIALS AND METHODS

We employed single-cell RNA sequencing (scRNA-seq) transcriptomic analysis to delve into the melanoma cells from six samples of melanoma patients. This approach enabled the identification of critical melanoma cell subpopulations and their roles in melanoma progression. Subsequently, we examined the interactions among these subpopulations and analyzed their interactions with other cell types.

RESULTS

Our analysis identified C3 ID2+ melanoma cells as an early-stage subpopulation and C4 PCLAF+ cells as a late-stage subpopulation in melanoma evolution. Through our analysis, we identified C4 PCLAF+ Melanoma cells as a significant subpopulation in acral melanoma (AM), playing a pivotal role in the differentiation and development of AM. Further analysis of transcription factors, enriched pathways, cell stemness, and cell trajectories highlighted the significant role of C4 PCLAF+ melanoma cells in acral melanoma (AM) proliferation.

CONCLUSION

This study identifies new factors influencing melanoma progression, providing a foundation for subsequent research.

Fibroblast Growth Factor Receptor 4 Promotes Triple-Negative Breast Cancer Progression via Regulating Fatty Acid Metabolism Through the AKT/RYR2 Signaling

BACKGROUND

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Previous studies have found that fibroblast growth factor receptor 4 (FGFR4) plays a crucial role in tumor development and metastasis. However, the potential role and underlying mechanisms of FGFR4 in the progression of TNBC remain unclear.

METHODS

Statistical analysis of FGFR4 expression data in public databases was used to reveal its role in TNBC. qRT-PCR was used to detect FGFR4 expression levels. The impact of FGFR4 level changes on TNBC cell proliferation was assessed using CCK-8 and colony formation assays, while Transwell invasion assays and JC-1 staining were employed to analyze the effects of FGFR4 level changes on the invasiveness and survival capability of TNBC cells. Differentially expressed genes were subjected to Gene Ontology, KEGG, and GSEA enrichment analyses to identify associated signaling pathways. Additionally, Oil Red O staining, fatty acid metabolite detection, and Western blot analysis were used to investigate the impact of FGFR4 and its inhibitor fisogatinib, as well as the AKT activator SC79, on the metabolic reprogramming of fatty acids in TNBC cells.

RESULTS

FGFR4 was found to be upregulated in breast cancer and correlated with poorer patient outcomes. Inhibition of FGFR4 resulted in reduced cell growth and invasion in TNBC cells. It also led to increased lipid accumulation, upregulated lipid biosynthesis-related genes, and downregulated lipolysis-related genes. Mechanistically, FGFR4 inhibition suppressed the activation of the AKT/RYR2 signaling pathway. Reactivating the AKT pathway reversed the suppressive effects of FGFR4 inhibition on TNBC progression.

CONCLUSION

Dysregulated FGFR4 activates the AKT/RYR2 axis, leading to tumor proliferation, invasion, and altered lipid metabolism in TNBC. FGFR4 inhibition could potentially serve as a novel therapeutic strategy for TNBC treatment.

A comprehensive analysis of gene expression and the immune landscape in gastric cancer through single-cell and multi-omics approaches

Gastric cancer (GC) is a common malignant tumor worldwide, characterized by complex biological processes. The distribution of various cell types and gene expression profiles in the GC microenvironment remains unclear. This study uses single-cell RNA sequencing to explore gene expression patterns and identify differentially expressed genes in GC samples, offering new insights into cellular diversity and potential molecular mechanisms. We conducted temporal and clustering analyses with single-cell sequencing, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to clarify their functions. Using machine learning, we identified relevant genes to create highly accurate prediction models. Additionally, ssGSEA analysis provided detailed insights into the immunosuppressive tumor microenvironment, revealing complex gene expression interactions and diverse immune infiltrates in cancer. Correlation analysis highlighted TIMP1 as having significant prognostic value across different immune cell subtypes. Single-cell RNA sequencing revealed the cellular landscape and gene expression profiles of the GC microenvironment, offering crucial data on how cell heterogeneity is regulated in relation to the tumor microenvironment. Moreover, new insights into the expression levels of AGT, INHBA, and TIMP1 showed distinct sex-biased gene functions within the tumor microenvironment. These findings enhance our understanding of the molecular mechanisms associated with gastric cancer development and may lay the groundwork for identifying novel therapeutic targets and diagnostic strategies.

Single-cell RNA sequencing elucidated the landscape of breast cancer brain metastases and identified ILF2 as a potential therapeutic target

Distant metastasis remains the primary cause of morbidity in patients with breast cancer. Hence, the development of more efficacious strategies and the exploration of potential targets for patients with metastatic breast cancer are urgently needed. The data of six patients with breast cancer brain metastases (BCBrM) from two centres were collected, and a comprehensive landscape of the entire tumour ecosystem was generated through the utilisation of single-cell RNA sequencing. We utilised the Monocle2 and CellChat algorithms to investigate the interrelationships among each subcluster. In addition, multiple signatures were collected to evaluate key components of the subclusters through multi-omics methodologies. Finally, we elucidated common expression programs of malignant cells, and experiments were conducted in vitro and in vivo to determine the functions of interleukin enhancer-binding factor 2 (ILF2), which is a key gene in the metastasis module, in BCBrM progression. We found that subclusters in each major cell type exhibited diverse characteristics. Besides, our study indicated that ILF2 was specifically associated with BCBrM, and experimental validations further demonstrated that ILF2 deficiency hindered BCBrM progression. Our study offers novel perspectives on the heterogeneity of BCBrM and suggests that ILF2 could serve as a promising biomarker or therapeutic target for BCBrM.

Exploring the prognostic value of BRMS1 + microglia based on single-cell anoikis regulator patterns in the immunologic microenvironment of GBM

BACKGROUND

Anoikis is a specialized form of programmed cell death induced by the loss of cell adhesion to the extracellular matrix (ECM). Acquisition of anoikis resistance is a significant marker for cancer cell invasion, metastasis, therapy resistance, and recurrence. Although current research has identified multiple factors that regulate anoikis resistance, the pathological mechanisms of anoikis-mediated tumor microenvironment (TME) in glioblastoma (GBM) remain largely unexplored.

METHODS

Utilizing single-cell RNA sequencing (scRNA-seq) data and employing non-negative matrix factorization (NMF), we identified and characterized TME cell clusters with distinct anoikis-associated gene signatures. Prognostic and therapeutic response analyses were conducted using TCGA and CGGA datasets to assess the clinical significance of different TME cell clusters. The spatial relationship between BRMS1 + microglia and tumor cells was inferred from spatial transcriptome RNA sequencing (stRNA-seq) data. To simulate the tumor immune microenvironment, co-culture experiments were performed with microglia (HMC3) and GBM cells (U118/U251), and microglia were transfected with a BRMS1 overexpression lentivirus. Western blot or ELISA were used to detect BRMS1, M2 macrophage-specific markers, PI3K/AKT signaling proteins, and apoptosis-related proteins. The proliferation and apoptosis capabilities of tumor cells were evaluated using CCK-8, colony formation, and apoptosis assays, while the invasive and migratory abilities of tumor cells were assessed using Transwell assays.

RESULTS

NMF-based analysis successfully identified CD8 + T cell and microglia cell clusters with distinct gene signature characteristics. Trajectory analysis, cell communication, and gene regulatory network analyses collectively indicated that anoikis-mediated TME cell clusters can influence tumor cell development through various mechanisms. Notably, BRMS1 + AP-Mic exhibited an M2 macrophage phenotype and had significant cell communication with malignant cells. Moreover, high expression of BRMS1 + AP-Mic in TCGA and CGGA datasets was associated with poorer survival outcomes, indicating its detrimental impact on immunotherapy. Upregulation of BRMS1 in microglia may lead to M2 macrophage polarization, activate the PI3K/AKT signaling pathway through SPP1/CD44-mediated cell interactions, inhibit tumor cell apoptosis, and promote tumor proliferation and invasion.

CONCLUSION

This pioneering study used NMF-based analysis to reveal the important predictive value of anoikis-regulated TME in GBM for prognosis and immunotherapeutic response. BRMS1 + microglial cells provide a new perspective for a deeper understanding of the immunosuppressive microenvironment of GBM and could serve as a potential therapeutic target in the future.

Recent progress and applications of single-cell sequencing technology in breast cancer

Single-cell RNA sequencing (scRNA-seq) technology enables the precise analysis of individual cell transcripts with high sensitivity and throughput. When integrated with multiomics technologies, scRNA-seq significantly enhances the understanding of cellular diversity, particularly within the tumor microenvironment. Similarly, single-cell DNA sequencing has emerged as a powerful tool in cancer research, offering unparalleled insights into the genetic heterogeneity and evolution of tumors. In the context of breast cancer, this technology holds substantial promise for decoding the intricate genomic landscape that drives disease progression, treatment resistance, and metastasis. By unraveling the complexities of tumor biology at a granular level, single-cell DNA sequencing provides a pathway to advancing our comprehension of breast cancer and improving patient outcomes through personalized therapeutic interventions. As single-cell sequencing technology continues to evolve and integrate into clinical practice, its application is poised to revolutionize the diagnosis, prognosis, and treatment strategies for breast cancer. This review explores the potential of single-cell sequencing technology to deepen our understanding of breast cancer, highlighting key approaches, recent advancements, and the role of the tumor microenvironment in disease plasticity. Additionally, the review discusses the impact of single-cell sequencing in paving the way for the development of personalized therapies.

Single‑cell RNA‑seq necroptosis‑related genes predict the prognosis of breast cancer and affect the differentiation of CD4+ T cells in tumor immune microenvironment

Breast cancer (BC) is one of the most prevalent types of malignancy and a major cause of cancer-related death. The purpose of the present study was to identify prognostic models of necroptosis-related genes (NRGs) in BC at the single-cell RNA-sequencing level and reveal the role of NRGs in tumour immune microenvironment (TIME). A risk model was constructed based on Cox regression and LASSO methods. Next, high-scoring cell populations were searched through AUCell scores, and cell subtypes were then analyzed by pseudotime analysis. Finally, the expression level of the model genes was verified by reverse transcription-quantitative (RT-qPCR). A new prognostic model was constructed and validated based on five NRGs (BCL2, BIRC3, AIFM1, IFNG and VDAC1), which could effectively predict the prognosis of patients with BC. NRGs were found to be highly active in CD4+ T cells and differentially expressed in their developmental trajectories. Finally, the RT-qPCR results showed that most of the model genes were significantly overexpressed in MDA-MB-231 and MCF-7 cells (P<0.05). In conclusion, an NRG signature with excellent predictive properties in prognosis and TIME was successfully established. Moreover, NRGs were involved in the differentiation and development of CD4+ T cells in TIME. These findings provide potential therapeutic strategies for BC.

Epigenetic deregulation in breast cancer microenvironment: Implications for tumor progression and therapeutic strategies

Breast cancer comprises a substantial proportion of cancer diagnoses in women and is a primary cause of cancer-related mortality. While hormone-responsive cases generally have a favorable prognosis, the aggressive nature of triple-negative breast cancer presents challenges, with intrinsic resistance to established treatments being a persistent issue. The complexity intensifies with the emergence of acquired resistance, further complicating the management of breast cancer. Epigenetic changes, encompassing DNA methylation, histone and RNA modifications, and non-coding RNAs, are acknowledged as crucial contributors to the heterogeneity of breast cancer. The unique epigenetic landscape harbored by each cellular component within the tumor microenvironment (TME) adds great diversity to the intricate regulations which influence therapeutic responses. The TME, a sophisticated ecosystem of cellular and non-cellular elements interacting with tumor cells, establishes an immunosuppressive microenvironment and fuels processes such as tumor growth, angiogenesis, and extracellular matrix remodeling. These factors contribute to challenging conditions in cancer treatment by fostering a hypoxic environment, inducing metabolic stress, and creating physical barriers to drug delivery. This article delves into the complex connections between breast cancer treatment response, underlying epigenetic changes, and vital interactions within the TME. To restore sensitivity to treatment, it emphasizes the need for combination therapies considering epigenetic changes specific to individual members of the TME. Recognizing the pivotal role of epigenetics in drug resistance and comprehending the specificities of breast TME is essential for devising more effective therapeutic strategies. The development of reliable biomarkers for patient stratification will facilitate tailored and precise treatment approaches.

Single-Cell Informatics for Tumor Microenvironment and Immunotherapy

Cancer comprises malignant cells surrounded by the tumor microenvironment (TME), a dynamic ecosystem composed of heterogeneous cell populations that exert unique influences on tumor development. The immune community within the TME plays a substantial role in tumorigenesis and tumor evolution. The innate and adaptive immune cells "talk" to the tumor through ligand-receptor interactions and signaling molecules, forming a complex communication network to influence the cellular and molecular basis of cancer. Such intricate intratumoral immune composition and interactions foster the application of immunotherapies, which empower the immune system against cancer to elicit durable long-term responses in cancer patients. Single-cell technologies have allowed for the dissection and characterization of the TME to an unprecedented level, while recent advancements in bioinformatics tools have expanded the horizon and depth of high-dimensional single-cell data analysis. This review will unravel the intertwined networks between malignancy and immunity, explore the utilization of computational tools for a deeper understanding of tumor-immune communications, and discuss the application of these approaches to aid in diagnosis or treatment decision making in the clinical setting, as well as the current challenges faced by the researchers with their potential future improvements.

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.

Multi-omics analysis of disulfidptosis regulators and therapeutic potential reveals glycogen synthase 1 as a disulfidptosis triggering target for triple-negative breast cancer

Disruption of disulfide homeostasis during biological processes can have fatal consequences. Excess disulfides induce cell death in a novel manner, termed as "disulfidptosis." However, the specific mechanism of disulfidptosis has not yet been elucidated. To determine the cancer types sensitive to disulfidptosis and outline the corresponding treatment strategies, we firstly investigated the crucial functions of disulfidptosis regulators pan-cancer at multi-omics levels. We found that different tumor types expressed dysregulated levels of disulfidptosis regulators, most of which had an impact on tumor prognosis. Moreover, we calculated the disulfidptosis activity score in tumors and validated it using multiple independent datasets. Additionally, we found that disulfidptosis activity was correlated with classic biological processes and pathways in various cancers. Disulfidptosis activity was also associated with tumor immune characteristics and could predict immunotherapy outcomes. Notably, the disulfidptosis regulator, glycogen synthase 1 (GYS1), was identified as a promising target for triple-negative breast cancer and validated via in vitro and in vivo experiments. In conclusion, our study elucidated the complex molecular phenotypes and clinicopathological correlations of disulfidptosis regulators in tumors, laying a solid foundation for the development of disulfidptosis-targeting strategies for cancer treatment.

Single-cell transcriptomic analysis in clear cell renal cell carcinoma: Deciphering the role of APP within the tumour microenvironment

Clear cell renal cell carcinoma (ccRCC) represents a significant challenge in oncology, primarily due to its resistance to conventional therapies. Understanding the tumour microenvironment (TME) is crucial for developing new treatment strategies. This study focuses on the role of amyloid precursor protein (APP) in tumour-associated macrophages (TAMs) within the ccRCC TME, exploring its potential as a prognostic biomarker. Basing TAM-related genes, the prognostic model was important to constructed. Employing advanced single-cell transcriptomic analysis, this research dissects the TME of ccRCC at an unprecedented cellular resolution. By isolating and examining the gene expression profiles of individual cells, particularly focusing on TAMs, the study investigates the expression levels of APP and their association with the clinical outcomes of ccRCC patients. The analysis reveals a significant correlation between the expression of APP in TAMs and patient prognosis in ccRCC. Patients with higher APP expression in TAMs showed differing clinical outcomes compared to those with lower expression. This finding suggests that APP could serve as a novel prognostic biomarker for ccRCC, providing insights into the disease progression and potential therapeutic targets. This study underscores the importance of single-cell transcriptomics in understanding the complex dynamics of the TME in ccRCC. The correlation between APP expression in TAMs and patient prognosis highlights APP as a potential prognostic biomarker. However, further research is needed to validate these findings and explore the regulatory mechanisms and therapeutic implications of APP in ccRCC.

Engineered Adoptive T-Cell Therapies for Breast Cancer: Current Progress, Challenges, and Potential

Breast cancer remains a significant health challenge, and novel treatment approaches are critically needed. This review presents an in-depth analysis of engineered adoptive T-cell therapies (E-ACTs), an innovative frontier in cancer immunotherapy, focusing on their application in breast cancer. We explore the evolving landscape of chimeric antigen receptor (CAR) and T-cell receptor (TCR) T-cell therapies, highlighting their potential and challenges in targeting breast cancer. The review addresses key obstacles such as target antigen selection, the complex breast cancer tumor microenvironment, and the persistence of engineered T-cells. We discuss the advances in overcoming these barriers, including strategies to enhance T-cell efficacy. Finally, our comprehensive analysis of the current clinical trials in this area provides insights into the future possibilities and directions of E-ACTs in breast cancer treatment.