Single-cell transcriptomics reveals the role of Macrophage-Naïve CD4 + T cell interaction in the immunosuppressive microenvironment of primary liver carcinoma

Potential crosstalk between Naïve CD4+ T cells and SPP1+ Macrophages is associated with clinical outcome and therapeutic response in hepatocellular carcinoma

BACKGROUND

The highly heterogeneity of the tumor microenvironment (TME) in hepatocellular carcinoma (HCC) results in diverse clinical outcomes and therapeutic responses. This study aimed to investigate potential intercellular crosstalk and its impact on clinical outcomes and therapeutic responses.

METHODS

Single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (ST) and bulk RNA sequencing (RNA-seq) datasets were integrated to comprehensively analyze the intercellular interactions within the TME. Multiplex immunohistochemistry was conducted to validate the intercellular interactions. A machine learning-based integrative procedure was used in bulk RNA-seq datasets to generate a risk model to predict prognosis and therapeutic responses.

RESULTS

Survival analyses based on the bulk RNA-seq datasets revealed the negative impact of the naïve Cluster of Differentiation 4+ (CD4) T cells and Secreted Phosphoprotein 1+ (SPP1) macrophages on prognosis. Furthermore, their intricate intercellular crosstalk and spatial colocalization were also observed by scRNA-seq and ST analyses. Based on this crosstalk, a machine learning model, termed the naïve CD4+ T cell and SPP1+ macrophage prognostic score (TMPS), was established in the bulk-RNA seq datasets for prognostic prediction. The TMPS achieved C-index values of 0.785, 0.715, 0.692 and 0.857, respectively, across 4 independent cohorts. A low TMPS was associated with a significantly increased survival rates, improved response to immunotherapy and reduced infiltration of immunosuppressive cells, such as. regulatory T cells. Finally, 8 potential sensitive drugs and 6 potential targets were predicted for patients based on their TMPS.

CONCLUSION

The crosstalk between naïve CD4+ T cells and SPP1+ macrophages play a crucial role in the TME. TMPS can reflect this crosstalk and serve as a valuable tool for prognostic stratification and guiding clinical decision-making.

Single-cell transcriptomics reveals tumor microenvironment changes and prognostic gene signatures in hepatocellular carcinoma

BACKGROUND

Hepatocellular Carcinoma (HCC) is the most common type of primary liver cancer, accounting for the majority of liver cancer cases. Hepatocellular Carcinoma not only exhibits high heterogeneity but also possesses an immune-suppressive tumor microenvironment that promotes tumor evasion, posing substantial difficulties for efficient therapy. Our aim is to utilize single-cell RNA transcriptome data to investigate the dynamic changes in the tumor microenvironment during the malignant progression of HCC, the communication among immune cells, and the marker genes associated with patient prognosis.

METHODS

We constructed expression matrices from open single-cell RNA transcriptome data (GSE149614) of HCC patients (representing stages I-IV), establishing single-cell RNA transcriptional atlases for different stages of HCC progression. For each stage, we conducted cell subgroup analysis to identify cell types at each stage. Horizontally, we explored the dynamic changes of the same cell type across different stages, performing trajectory analysis and prognosis analysis. Vertically, we investigated pairwise comparisons of different stages of HCC progression, probing the dynamic alterations in tumor microenvironment immune cell signaling pathways. Finally, potential drugs for the treatment of HCC were predicted based on relevant genes.

FINDINGS

As the HCC advances towards increased malignancy, there is a shift in the predominant composition of the tumor microenvironment, with a decline in the dominance of hepatic cells. Tumor-infiltrating immune cells migrate and accumulate within the tumor microenvironment, where T cells and myeloid cells display distinct patterns of change. Genes associated with cancer-associated fibroblasts (CAFs) and T cells are correlated with adverse patient outcomes. In the late stages of HCC, the tumor microenvironment is infiltrated by more myeloid-derived suppressor cells (MDSCs), and a prognostic model constructed based on genes related to myeloid cells can predict patient outcomes. Additionally, in the analysis of transcription factors, YY1 and MYC are found to be highly expressed. Cell communication analysis among tumor-infiltrating immune cells reveals significant differences in the main signaling pathways at different stages of HCC progression. Finally, drug sensitivity analysis based on key genes identifies Acetalax, Allopurinol, and Amonafide as potential candidates for HCC treatment.

Regulation of Fuzheng Huayu capsule on inhibiting the fibrosis-associated hepatocellular carcinogenesis

In the current study, bioinformatics analysis of the hepatocellular carcinoma (HCC) dataset was conducted with the hepatoprotective effect of the Fuzheng Huayu (FZHY) capsule against the diethylnitrosamine-induced HCC progression analyzed. Eight cell clusters were defined and tanshinone IIA, arachidonic acid, and quercetin, compounds of the FZHY capsule, inhibit HCC progression-related fibrosis by regulating the expression of PLAU and IGFBP3. Combined with the ameliorative effect of the FZHY capsule against liver dysfunctions and expression of PLAU and IGFBP3, our study confirmed the effect of the FZHY capsule on inhibiting the fibrosis-associated HCC progression via regulating the expression of PLAU and IGFBP3.

OmicVerse: a framework for bridging and deepening insights across bulk and single-cell sequencing

Single-cell sequencing is frequently affected by "omission" due to limitations in sequencing throughput, yet bulk RNA-seq may contain these ostensibly "omitted" cells. Here, we introduce the single cell trajectory blending from Bulk RNA-seq (BulkTrajBlend) algorithm, a component of the OmicVerse suite that leverages a Beta-Variational AutoEncoder for data deconvolution and graph neural networks for the discovery of overlapping communities. This approach effectively interpolates and restores the continuity of "omitted" cells within single-cell RNA sequencing datasets. Furthermore, OmicVerse provides an extensive toolkit for both bulk and single cell RNA-seq analysis, offering seamless access to diverse methodologies, streamlining computational processes, fostering exquisite data visualization, and facilitating the extraction of significant biological insights to advance scientific research.

Liver macrophages revisited: The expanding universe of versatile responses in a spatiotemporal context

The liver is a vital organ that continuously adapts to a wide and dynamic diversity of self-antigens and xenobiotics. This involves the active contribution of immune cells, particularly by the liver-resident macrophages, the Kupffer cells (KCs), which exert a variety of central functions in liver homeostasis and disease. As such, KCs interact with their microenvironment to shape the hepatic cellular landscape, control gut-derived signal integration, and modulate metabolism. On injury, the rapid recruitment of bone marrow monocyte-derived macrophages alters this status quo and, when unrestrained, drastically compromises liver homeostasis, immune surveillance, and tissue organization. Several factors determine the functional roles of liver macrophages in these processes, such as their ontogeny, activation/polarization profile and, importantly, spatial distribution within the liver. Loss of tolerance and adaptability of the hepatic immune environment may result in persistent inflammation, hepatic fibrosis, cirrhosis, and a tumorigenic niche promoting liver cancer. In this review, we aim at providing the most recent breakthroughs in our understanding of liver macrophage biology, particularly their diversity and adaptability in the hepatic spatiotemporal context, as well as on potential therapeutic interventions that may hold the key to tackling remaining clinical challenges of varying etiologies in hepatology.

A single-cell characterised signature integrating heterogeneity and microenvironment of lung adenocarcinoma for prognostic stratification

BACKGROUND

The high heterogeneity of tumour and the complexity of tumour microenvironment (TME) greatly impacted the tumour development and the prognosis of cancer in the era of immunotherapy. In this study, we aimed to portray the single cell-characterised landscape of lung adenocarcinoma (LUAD), and develop an integrated signature incorporating both tumour heterogeneity and TME for prognosis stratification.

METHODS

Single-cell tagged reverse transcription sequencing (STRT-seq) was performed on tumour tissues and matched normal tissues from 14 patients with LUAD for immune landscape depiction and candidate key genes selection for signature construction. Kaplan-Meier survival analyses and in-vitro cell experiments were conducted to confirm the gene functions. The transcriptomic profile of 1949 patients from 11 independent cohorts including nine public datasets and two in-house cohorts were obtained for validation.

FINDINGS

We selected 11 key genes closely related to cell-to-cell interaction, tumour development, T cell phenotype transformation, and Ma/Mo cell distribution, including HLA-DPB1, FAM83A, ITGB4, OAS1, FHL2, S100P, FSCN1, SFTPD, SPP1, DBH-AS1, CST3, and established an integrated 11-gene signature, stratifying patients to High-Score or Low-Score group for better or worse prognosis. Moreover, the prognostically-predictive potency of the signature was validated by 11 independent cohorts, and the immunotherapeutic predictive potency was also validated by our in-house cohort treated by immunotherapy. Additionally, the in-vitro cell experiments and drug sensitivity prediction further confirmed the gene function and generalizability of this signature across the entire RNA profile spectrum.

INTERPRETATION

This single cell-characterised 11-gene signature might offer insights for prognosis stratification and potential guidance for treatment selection.

FUNDING

Support for the study was provided by National key research and development project (2022YFC2505004, 2022YFC2505000 to Z.W. and J.W.), Beijing Natural Science Foundation (7242114 to J.X.), National Natural Science Foundation of China of China (82102886 to J.X., 81871889 and 82072586 to Z.W.), Beijing Nova Program (20220484119 to J.X.), NSFC general program (82272796 to J.W.), NSFC special program (82241229 to J.W.), CAMS Innovation Fund for Medical Sciences (2021-1-I2M-012, 2022-I2M-1-009 to Z.W. and J.W.), Beijing Natural Science Foundation (7212084 to Z.W.), CAMS Key lab of translational research on lung cancer (2018PT31035 to J.W.), Aiyou Foundation (KY201701 to J.W.). Medical Oncology Key Foundation of Cancer Hospital Chinese Academy of Medical Sciences (CICAMS-MOCP2022003 to J.X.).

Novel prognostic biomarker TBC1D1 is associated with immunotherapy resistance in gliomas

Background

Glioma, an aggressive brain tumor, poses a challenge in understanding the mechanisms of treatment resistance, despite promising results from immunotherapy.

Methods

We identified genes associated with immunotherapy resistance through an analysis of The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) databases. Subsequently, qRT-PCR and western blot analyses were conducted to measure the mRNA and protein levels of TBC1 Domain Family Member 1 (TBC1D1), respectively. Additionally, Gene Set Enrichment Analysis (GSEA) was employed to reveal relevant signaling pathways, and the expression of TBC1D1 in immune cells was analyzed using single-cell RNA sequencing (scRNA-seq) data from GEO database. Tumor Immune Dysfunction and Exclusion (TIDE) database was utilized to assess T-cell function, while Tumor Immunotherapy Gene Expression Resource (TIGER) database was employed to evaluate immunotherapy resistance in relation to TBC1D1. Furthermore, the predictive performance of molecules on prognosis was assessed using Kaplan-Meier plots, nomograms, and ROC curves.

Results

The levels of TBC1D1 were significantly elevated in tumor tissue from glioma patients. Furthermore, high TBC1D1 expression was observed in macrophages compared to other cells, which negatively impacted T cell function, impaired immunotherapy response, promoted treatment tolerance, and led to poor prognosis. Inhibition of TBC1D1 was found to potentially synergistically enhance the efficacy of immunotherapy and prolong the survival of cancer patients with gliomas.

Conclusion

Heightened expression of TBC1D1 may facilitate an immunosuppressive microenvironment and predict a poor prognosis. Blocking TBC1D1 could minimize immunotherapy resistance in cancer patients with gliomas.

Macrophage barrier in the tumor microenvironment and potential clinical applications

The tumor microenvironment (TME) constitutes a complex microenvironment comprising a diverse array of immune cells and stromal components. Within this intricate context, tumor-associated macrophages (TAMs) exhibit notable spatial heterogeneity. This heterogeneity contributes to various facets of tumor behavior, including immune response modulation, angiogenesis, tissue remodeling, and metastatic potential. This review summarizes the spatial distribution of macrophages in both the physiological environment and the TME. Moreover, this paper explores the intricate interactions between TAMs and diverse immune cell populations (T cells, dendritic cells, neutrophils, natural killer cells, and other immune cells) within the TME. These bidirectional exchanges form a complex network of immune interactions that influence tumor immune surveillance and evasion strategies. Investigating TAM heterogeneity and its intricate interactions with different immune cell populations offers potential avenues for therapeutic interventions. Additionally, this paper discusses therapeutic strategies targeting macrophages, aiming to uncover novel approaches for immunotherapy. Video Abstract.

Targeting tumor-associated macrophages: Novel insights into immunotherapy of skin cancer

BACKGROUND

The incidence of skin cancer is currently increasing, and conventional treatment options inadequately address the demands of disease management. Fortunately, the recent rapid advancement of immunotherapy, particularly immune checkpoint inhibitors (ICIs), has ushered in a new era for numerous cancer patients. However, the efficacy of immunotherapy remains suboptimal due to the impact of the tumor microenvironment (TME). Tumor-associated macrophages (TAMs), a major component of the TME, play crucial roles in tumor invasion, metastasis, angiogenesis, and immune evasion, significantly impacting tumor development. Consequently, TAMs have gained considerable attention in recent years, and their roles have been extensively studied in various tumors. However, the specific roles of TAMs and their regulatory mechanisms in skin cancer remain unclear.

AIM OF REVIEW

This paper aims to elucidate the origin and classification of TAMs, investigate the interactions between TAMs and various immune cells, comprehensively understand the precise mechanisms by which TAMs contribute to the pathogenesis of different types of skin cancer, and finally discuss current strategies for targeting TAMs in the treatment of skin cancer.

KEY SCIENTIFIC CONCEPTS OF OVERVIEW

With a specific emphasis on the interrelationship between TAMs and skin cancer, this paper posits that therapeutic modalities centered on TAMs hold promise in augmenting and harmonizing with prevailing clinical interventions for skin cancer, thereby charting a novel trajectory for advancing the landscape of immunotherapeutic approaches for skin cancer.

Immunoglobulin superfamily 6 is a molecule involved in the anti-tumor activity of macrophages in lung adenocarcinoma

BACKGROUND

Immunoglobulin superfamily 6 (IGSF6) is a novel member of the immunoglobulin superfamily and has been implicated in various diseases. However, the specific role of IGSF6 in the anti-tumor immunity within lung adenocarcinoma (LUAD) remains unclear.

METHODS

We analyzed the IGSF6 expression in LUAD using data from TCGA, and we performed qRT-PCR and western blotting to validate these findings using tissue samples obtained from LUAD patients. Images of IHC staining were obtained from HPA. To assess the clinical relevance of IGSF6 expression, we utilized UALCAN and SPSS to analyze its association with major clinical features of LUAD. Additionally, we employed ROC curves and survival analysis to evaluate the potential diagnostic and prognostic value of IGSF6 in LUAD. To gain insights into the functional implications of IGSF6, we performed enrichment analysis using the R software clusterProfiler package. Moreover, we utilized TIMER2.0 and TISIDB to investigate the relationship between IGSF6 and immune infiltrates in LUAD. The proportion of tumor-infiltrating immune cells in LUAD was assessed using FCM, and their correlation with IGSF6 expression in tumor tissues was analyzed. The localization of IGSF6 protein on macrophages was confirmed using the HPA and FCM. To determine the regulatory role of IGSF6 on macrophage activity in LUAD, we employed ELISA, FCM, and tumor-bearing models.

RESULTS

We discovered that both IGSF6 mRNA and protein levels were significantly decreased in LUAD. Additionally, we observed a negative correlation between IGSF6 expression and TNM stages as well as pathologic stages in LUAD. Notably, IGSF6 exhibited high sensitivity and specificity in diagnosing LUAD, and was positively associated with the survival rate of LUAD patients. Furthermore, IGSF6 expression was closely linked to gene sets involved in immune response. IGSF6 expression showed a positive correlation with immune infiltrates exhibiting anti-tumor activity, particularly M1 macrophages. We confirmed the predominant localization of the IGSF6 protein on the membrane of M1 macrophages. Importantly, the knockdown of IGSF6 resulted in a reduction in the anti-tumor activity of M1 macrophages, thereby promoting tumor progression.

CONCLUSION

IGSF6 is a molecule that is essential for the anti-tumor activity of macrophages in LUAD.

Integrated immunological analysis of single-cell and bulky tissue transcriptomes reveals the role of interactions between M0 macrophages and naïve CD4+ T cells in the immunosuppressive microenvironment of cervical cancer

In recent decades, the incidence and mortality of cervical cancer have declined in developed countries due to the implementation of screening and vaccination programs. However, cervical cancer remains one of the major culprits of cancer-related deaths in young women. Current studies have found that immune cell-related intercellular communication in the tumor microenvironment has a large impact on the construction of the immunosuppressive microenvironment. In this study, we performed a comprehensive immune analysis on bulk RNA-seq and scRNA-seq data obtained from cervical cancer and revealed that two highly plastic cell populations, M0 macrophages and naïve CD4+ T cells, were significantly correlated with prognosis and clinical phenotypes. Notably, signaling between M0 macrophages and naïve CD4+ T cells as well as intracellular transcription factor activity were significantly altered in the tumor state. Furthermore, we identified overlapping genes between the transcription factor target genes of M0 macrophages or naïve CD4+ T cells and the differentially expressed genes in each type of cell, and these overlapping genes were subsequently subjected to an analysis using the LASSO regression model. Finally, we generated a score index that was significantly associated with the clinical prognosis of cervical cancer. In conclusion, interventions to improve the communication between M0 macrophages and naïve CD4+ T cells may help to improve the immunosuppressive microenvironment of cervical cancer and prevent immune evasion. The relevant molecular mechanisms need to be further validated by experimental and cohort studies.

Lactobacillus brevis alleviates the progress of hepatocellular carcinoma and type 2 diabetes in mice model via interplay of gut microflora, bile acid and NOTCH 1 signaling

Type 2 diabetes (T2DM) clinically exhibits a higher incidence of hepatocellular carcinoma (HCC), contributing to a lousy prognosis in patients harboring both diseases. Microflora-based therapy draws attention with low side effects. Accumulating evidence shows that Lactobacillus brevis can improve blood glucose and body weight of the T2DM mice model and reduce several cancer incidences. However, the therapeutic effect of Lactobacillus brevis in affecting the prognosis of T2DM+HCC remains unknown. In this study, we aim to explore this question via an established T2DM+HCC mice model. We observed a significant alleviation after the probiotic intervention. Lactobacillus brevis improves blood glucose and insulin resistance and ameliorates Mechanically. Combined with a multi-omics approach including 16SrDNA, GC-MS, and RNA-seq, we identified distinct intestinal microflora composition and metabolites after Lactobacillus brevis intervention. Furthermore, we found that Lactobacillus brevis delayed disease progression by regulating MMP9 and NOTCH 1 signaling pathways, potentially through gut microflora and BA interaction. This study indicates that Lactobacillus brevis may improve the prognosis of T2DM + HCC, providing novel therapeutic opportunities via targeting intestinal flora for patients with T2DM+HCC.

Identification of potential resistance mechanisms and therapeutic targets for the relapse of BCMA CAR-T therapy in relapsed/refractory multiple myeloma through single-cell sequencing

BACKGROUND

BCMA CAR-T is highly effective for relapsed/refractory multiple myeloma(R/R-MM) and significantly improves the survival of patients. However, the short remission time and high relapse rate of MM patients treated with BCMA CAR-T remain bottlenecks that limit long-term survival. The immune microenvironment of the bone marrow (BM) in R/R-MM may be responsible for this. The present study aims to present an in-depth analysis of resistant mechanisms and to explore potential novel therapeutic targets for relapse of BCMA CAR-T treatment via single-cell RNA sequencing (scRNA-seq) of BM plasma cells and immune cells.

METHODS

This study used 10X Genomic scRNA-seq to identify cell populations in R/R-MM CD45+ BM cells before BCMA CAR-T treatment and relapse after BCMA CAR-T treatment. Cell Ranger pipeline and CellChat were used to perform detailed analysis.

RESULTS

We compared the heterogeneity of CD45+ BM cells before BCMA CAR-T treatment and relapse after BCMA CAR-T treatment. We found that the proportion of monocytes/macrophages increased, while the percentage of T cells decreased at relapse after BCMA CAR-T treatment. We then reclustered and analyzed the alterations in plasma cells, T cells, NK cells, DCs, neutrophils, and monocytes/macrophages in the BM microenvironment before BCMA CAR-T treatment and relapse after BCMA CAR-T treatment. We show here that the percentage of BCMA positive plasma cells increased at relapse after BCMA CAR-T cell therapy. Other targets such as CD38, CD24, SLAMF7, CD138, and GPRC5D were also found to be expressed in plasma cells of the R/R-MM patient at relapse after BCMA CAR-T cell therapy. Furthermore, exhausted T cells, TIGIT+NK cells, interferon-responsive DCs, and interferon-responsive neutrophils, increased in the R/R-MM patient at relapse after BCMA CAR-T cell treatment. Significantly, the proportion of IL1βhi Mφ, S100A9hi Mφ, interferon-responsive Mφ, CD16hi Mφ, MARCO hi Mφ, and S100A11hi Mφ significantly increased in the R/R-MM patient at relapse after BCMA CAR-T cell therapy. Cell-cell communication analysis indicated that monocytes/macrophages, especially the MIF and APRIL signaling pathway are key players in R/R-MM patient at relapse after BCMA CAR-T cell therapy.

CONCLUSION

Taken together, our data extend the understanding of intrinsic and extrinsic relapse of BCMA CAR-T treatment in R/R-MM patient and the potential mechanisms involved in the alterations of antigens and the induced immunosuppressive microenvironment, which may provide a basis for the optimization of BCMA CAR-T strategies. Further studies should be performed to confirm these findings.

Multi-omics characterization of a scoring system to quantify hypoxia patterns in patients with head and neck squamous cell carcinoma

BACKGROUND

The 5-year survival rate of patients with head and neck squamous cell carcinoma (HNSCC) remains  < 50%. Hypoxia patterns are a hallmark of HNSCC that are associated with its occurrence and progression. However, the precise role of hypoxia during HNSCC, such as the relationship between hypoxia, tumor immune landscape and cell communication orchestration remains largely unknown. The current study integrated data from bulk and single-cell RNA sequencing analyses to define the relationship between hypoxia and HNSCC.

METHODS

A scoring system named the hypoxia score (HS) was constructed based on hypoxia-related genes (HRGs) expression. The predictive value of HS response for patient outcomes and different treatments was evaluated. Single-cell datasets and cell communication were utilized to rule out cell populations which hypoxia targeted on.

RESULTS

The survival outcomes, immune/Estimate scores, responses to targeted inhibitors, and chemotherapeutic, and immunotherapy responses were distinct between a high HS group and a low HS group (all P < 0.05). Single-cell datasets showed different distributions of HS in immune cell populations (P < 0.05). Furthermore, HLA-DPA1/CD4 axis was identified as a unique interaction between CD4 + T Conv and pDC cells.

CONCLUSIONS

Altogether, the quantification for hypoxia patterns is a potential biomarker for prognosis, individualized chemotherapeutic and immunotherapy strategies. The portrait of cell communication characteristics over the HNSCC ecosystem enhances the understanding of hypoxia patterns in HNSCC.