Investigating Mechanisms of Response or Resistance to Immune Checkpoint Inhibitors by Analyzing Cell-Cell Communications in Tumors Before and After Programmed Cell Death-1 (PD-1) Targeted Therapy: An Integrative Analysis Using Single-cell RNA and Bulk-RNA Sequencing Data

Single-cell atlas of the human brain vasculature across development, adulthood and disease

A broad range of brain pathologies critically relies on the vasculature, and cerebrovascular disease is a leading cause of death worldwide. However, the cellular and molecular architecture of the human brain vasculature remains incompletely understood1. Here we performed single-cell RNA sequencing analysis of 606,380 freshly isolated endothelial cells, perivascular cells and other tissue-derived cells from 117 samples, from 68 human fetuses and adult patients to construct a molecular atlas of the developing fetal, adult control and diseased human brain vasculature. We identify extensive molecular heterogeneity of the vasculature of healthy fetal and adult human brains and across five vascular-dependent central nervous system (CNS) pathologies, including brain tumours and brain vascular malformations. We identify alteration of arteriovenous differentiation and reactivated fetal as well as conserved dysregulated genes and pathways in the diseased vasculature. Pathological endothelial cells display a loss of CNS-specific properties and reveal an upregulation of MHC class II molecules, indicating atypical features of CNS endothelial cells. Cell-cell interaction analyses predict substantial endothelial-to-perivascular cell ligand-receptor cross-talk, including immune-related and angiogenic pathways, thereby revealing a central role for the endothelium within brain neurovascular unit signalling networks. Our single-cell brain atlas provides insights into the molecular architecture and heterogeneity of the developing, adult/control and diseased human brain vasculature and serves as a powerful reference for future studies.

Identification of tumor-specific T cell signature predicting cancer immunotherapy response in bladder cancer by multi-omics analysis and experimental verification

BACKGROUND

Numerous gene signatures predicting the prognosis of bladder cancer have been identified. However, a tumor-specific T cell signature related to immunotherapy response in bladder cancer remains under investigation.

METHODS

Single-cell RNA and TCR sequencing from the Gene expression omnibus (GEO) database were used to identify tumor-specific T cell-related genes in bladder cancer. Subsequently, we constructed a tumor-specific T cell signature (TstcSig) and validated its clinical relevance for predicting immunotherapy response in multiple immunotherapy cohorts. Further analyses explored the immune characteristics of TstcSig in bladder cancer patients from other cohorts in the TCGA and GEO databases. Western blot (WB), multicolor immunofluorescence (MIF), qRT-PCR and flow cytometry assays were performed to validate the results of bioinformatics analysis.

RESULTS

The established TstcSig, based on five tumor-specific T cell-related genes, could predict outcomes in a bladder cancer immunotherapy cohort. This was verified using two additional immunotherapy cohorts and showed better predictive performance compared to 109 published T cell signatures. TstcSig was strongly correlated with immune characteristics such as immune checkpoint gene expression, tumor mutation burden, and T cell infiltration, as validated by single-cell and spatial transcriptomics datasets. Notably, the positive correlation between TstcSig and T cell infiltration was confirmed in the TCGA cohort. Furthermore, pan-cancer analysis demonstrated the heterogeneity of the prognostic value of TstcSig. Tumor-specific T cells highly expressed CD27, IFNG, GZMB and CXCL13 and secreted more effector cytokines for tumor cell killing, as validated experimentally.

CONCLUSION

We developed a five-gene signature (including VAMP5, TIGIT, LCK, CD27 and CACYBP) based on tumor-specific T cell-related genes to predict the immunotherapy response in bladder cancer patients.

The tumor immune microenvironment remodeling and response to HER2-targeted therapy in HER2-positive advanced gastric cancer

Combination therapy with anti-HER2 agents and immunotherapy has demonstrated significant clinical benefits in gastric cancer (GC), but the underlying mechanism remains unclear. In this study, we used multiplex immunohistochemistry to assess the changes of the tumor microenvironment in 47 advanced GC patients receiving anti-HER2 therapy. Additionally, we performed single-cell transcriptional sequencing to investigate potential cell-to-cell communication and molecular mechanisms in four HER2-positive GC baseline samples. We observed that post-treated the infiltration of NK cells, CD8+ T cells, and B lymphocytes were significantly higher in patients who benefited from anti-HER2 treatment than baseline. Further spatial distribution analysis demonstrated that the interaction scores between NK cells and CD8+ T cells, B lymphocytes and M2 macrophages, B lymphocytes and Tregs were also significantly higher in benefited patients. Cell-cell communication analysis from scRNA sequencing showed that NK cells utilized CCL3/CCL4-CCR5 to recruit CD8+ T cell infiltration. B lymphocytes employed CD74-APP/COPA/MIF to interact with M2 macrophages, and utilized TNF-FAS/ICOS/TNFRSR1B to interact with Tregs. These cell-cell interactions contribute to inhibit the immune resistance of M2 macrophages and Tregs. Our research provides potential guidance for the use of anti-HER2 therapy in combination with immune therapy.

Single-cell integrated transcriptomics reveals the role of keratinocytes in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a prevalent malignant tumor with significant morbidity and mortality. Understanding the molecular mechanisms of HNSCC and identifying prognostic markers and therapeutic targets are crucial for improving patient outcomes. In this study, we utilized single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data to comprehensively analyze HNSCC at the cellular level. We identified keratinocytes as the predominant cell type in tumor samples, suggesting their potential role in HNSCC development. Through hdWGCNA co-expression network analysis, we identified gene modules associated with HNSCC progression. Furthermore, we constructed a prognostic model based on specific genes and demonstrated its robust predictive performance in multiple datasets. The model exhibited strong correlations with immune cell infiltration patterns and signaling pathways related to tumor progression. Additionally, drug sensitivity analysis revealed potential chemotherapeutic targets for HNSCC treatment. Our findings provide valuable insights into the molecular characteristics and immune microenvironment of HNSCC, offering new perspectives for prognosis prediction and therapeutic interventions in clinical practice. Further research is warranted to validate and expand upon these findings, ultimately improving patient outcomes in HNSCC.

Single-cell RNA sequencing reveals cellular dynamics and therapeutic effects of astragaloside IV in slow transit constipation

The cellular characteristics of intestinal cells involved in the therapeutic effects of astragaloside IV (AS-IV) for treating slow transit constipation (STC) remain unclear. This study aimed to determine the dynamics of colon tissue cells in the STC model and investigate the effects of AS-IV treatment by single-cell RNA sequencing (scRNA-seq). STC mouse models were developed using loperamide, with subsequent treatment using AS-IV. Colon tissues and feces were collected for scRNA-seq and targeted short-chain fatty acid quantification. We integrated scRNA-seq data with network pharmacology to analyze the effect of AS-IV on constipation. AS-IV showed improvement in defecation for STC mice induced by loperamide. Notably, in STC mice, epithelial cells, T cells, B cells, and fibroblasts demonstrated alterations in cell proportions and aberrant functions, which AS-IV partially rectified. AS-IV has the potential to modulate the metabolic pathway of epithelial cells through its interaction with peroxisome proliferator-activated receptor gamma (PPARγ). AS-IV reinstated fecal butyrate levels and improved energy metabolism in epithelial cells. The proportion of naïve CD4+T cells is elevated in STC, and the differentiation of these cells into regulatory T cells (Treg) is regulated by B cells and fibroblasts through the interaction of ligand-receptor pairs. AS-IV treatment can partially alleviate this trend. The status of fibroblasts in STC undergoes alterations, and the FB_C4_Adamdec1 subset, associated with angiogenesis and the Wingless-related integration (Wnt) pathway, emerges. Our comprehensive analysis identifies perturbations of epithelial cells and tissue microenvironment cells in STC and elucidates mechanisms underlying the therapeutic efficacy of AS-IV.

ADGRE5-centered Tsurv model in T cells recognizes responders to neoadjuvant cancer immunotherapy

Background

Neoadjuvant immunotherapy with anti-programmed death-1 (neo-antiPD1) has revolutionized perioperative methods for improvement of overall survival (OS), while approaches for major pathologic response patients' (MPR) recognition along with methods for overcoming non-MPR resistance are still in urgent need.

Methods

We utilized and integrated publicly-available immune checkpoint inhibitors regimens (ICIs) single-cell (sc) data as the discovery datasets, and innovatively developed a cell-communication analysis pipeline, along with a VIPER-based-SCENIC process, to thoroughly dissect MPR-responding subsets. Besides, we further employed our own non-small cell lung cancer (NSCLC) ICIs cohort's sc data for validation in-silico. Afterward, we resorted to ICIs-resistant murine models developed by us with multimodal investigation, including bulk-RNA-sequencing, Chip-sequencing and high-dimensional cytometry by time of flight (CYTOF) to consolidate our findings in-vivo. To comprehensively explore mechanisms, we adopted 3D ex-vivo hydrogel models for analysis. Furthermore, we constructed an ADGRE5-centered Tsurv model from our discovery dataset by machine learning (ML) algorithms for a wide range of tumor types (NSCLC, melanoma, urothelial cancer, etc.) and verified it in peripheral blood mononuclear cells (PBMCs) sc datasets.

Results

Through a meta-analysis of multimodal sequential sc sequencing data from pre-ICIs and post-ICIs, we identified an MPR-expanding T cells meta-cluster (MPR-E) in the tumor microenvironment (TME), characterized by a stem-like CD8+ T cluster (survT) with STAT5-ADGRE5 axis enhancement compared to non-MPR or pre-ICIs TME. Through multi-omics analysis of murine TME, we further confirmed the existence of survT with silenced function and immune checkpoints (ICs) in MPR-E. After verification of the STAT5-ADGRE5 axis of survT in independent ICIs cohorts, an ADGRE5-centered Tsurv model was then developed through ML for identification of MPR patients pre-ICIs and post-ICIs, both in TME and PBMCs, which was further verified in pan-cancer immunotherapy cohorts. Mechanistically, we unveiled ICIs stimulated ADGRE5 upregulation in a STAT5-IL32 dependent manner in a 3D ex-vivo system (3D-HYGTIC) developed by us previously, which marked Tsurv with better survival flexibility, enhanced stemness and potential cytotoxicity within TME.

Conclusion

Our research provides insights into mechanisms underlying MPR in neo-antiPD1 and a well-performed model for the identification of non-MPR.

Single-cell disulfidptosis regulator patterns guide intercellular communication of tumor microenvironment that contribute to kidney renal clear cell carcinoma progression and immunotherapy

Background

Disulfidptosis, an emerging type of programmed cell death, plays a pivotal role in various cancer types, notably impacting the progression of kidney renal clear cell carcinoma (KIRC) through the tumor microenvironment (TME). However, the specific involvement of disulfidptosis within the TME remains elusive.

Methods

Analyzing 41,784 single cells obtained from seven samples of KIRC through single-cell RNA sequencing (scRNA-seq), this study employed nonnegative matrix factorization (NMF) to assess 24 disulfidptosis regulators. Pseudotime analysis, intercellular communication mapping, determination of transcription factor activities (TFs), and metabolic profiling of the TME subgroup in KIRC were conducted using Monocle, CellChat, SCENIC, and scMetabolism. Additionally, public cohorts were utilized to predict prognosis and immune responses within the TME subgroup of KIRC.

Results

Through NMF clustering and differential expression marker genes, fibroblasts, macrophages, monocytes, T cells, and B cells were categorized into four to six distinct subgroups. Furthermore, this investigation revealed the correlation between disulfidptosis regulatory factors and the biological traits, as well as the pseudotime trajectories of TME subgroups. Notably, disulfidptosis-mediated TME subgroups (DSTN+CD4T-C1 and FLNA+CD4T-C2) demonstrated significant prognostic value and immune responses in patients with KIRC. Multiple immunohistochemistry (mIHC) assays identified marker expression within both cell clusters. Moreover, CellChat analysis unveiled diverse and extensive interactions between disulfidptosis-mediated TME subgroups and tumor epithelial cells, highlighting the TNFSF12-TNFRSF12A ligand-receptor pair as mediators between DSTN+CD4T-C1, FLNA+CD4T-C2, and epithelial cells.

Conclusion

Our study sheds light on the role of disulfidptosis-mediated intercellular communication in regulating the biological characteristics of the TME. These findings offer valuable insights for patients with KIRC, potentially guiding personalized immunotherapy approaches.

Mitochondrial-related genes markers that predict survival in patients with head and neck squamous cell carcinoma affect immunomodulation through hypoxia, glycolysis, and angiogenesis pathways

Mitochondria play a crucial role in the occurrence and development of tumors. We used mitochondria-related genes for consistent clustering to identify three stable molecular subtypes of head and neck squamous cell carcinoma (HNSCC) with different prognoses, mutations, and immune characteristics. Significant differences were observed in clinical characteristics, immune microenvironment, immune cell infiltration, and immune cell scores. TP53 was the most significantly mutated; cell cycle-related pathways and tumorigenesis-related pathways were activated in different subtypes. Risk modeling was conducted using a multifactor stepwise regression method, and nine genes were identified as mitochondria-related genes affecting prognosis (DKK1, EFNB2, ITGA5, AREG, EPHX3, CHGB, P4HA1, CCND1, and JCHAIN). Risk score calculations revealed significant differences in prognosis, immune cell scores, immune cell infiltration, and responses to conventional chemotherapy drugs. Glycolysis, angiogenesis, hypoxia, and tumor-related pathways were positively correlated with the RiskScore. Clinical samples were subjected to qPCR to validate the results. In this work, we constructed a prognostic model based on the mitochondrial correlation score, which well reflects the risk and positive factors for the prognosis of patients with HNSCC. This model can be used to guide individualized adjuvant and immunotherapy in patients with HNSCC.

Research progress on the role of cationic amino acid transporter (CAT) family members in malignant tumors and immune microenvironment

Amino acids are essential for the survival of all living organisms and living cells. Amino acid transporters mediate the transport and absorption of amino acids, and the dysfunction of these proteins can induce human diseases. Cationic amino acid transporters (CAT family, SLC7A1-4, and SLC7A14) are considered to be a group of transmembrane transporters, of which SLC7A1-3 are essential for arginine transport in mammals. Numerous studies have shown that CAT family-mediated arginine transport is involved in signal crosstalk between malignant tumor cells and immune cells, especially T cells. The modulation of extracellular arginine concentration has entered a number of clinical trials and achieved certain therapeutic effects. Here, we review the role of CAT family on tumor cells and immune infiltrating cells in malignant tumors and explore the therapeutic strategies to interfere with extracellular arginine concentration, to elaborate its application prospects. CAT family members may be used as biomarkers for certain cancer entities and might be included in new ideas for immunotherapy of malignant tumors.

Metabolic-suppressed cancer-associated fibroblasts limit the immune environment and survival in colorectal cancer with liver metastasis

Background: Colorectal cancer liver metastasis is a major risk factor of poor outcomes, necessitating proactive interventions and treatments. Cancer-associated fibroblasts (CAFs) play essential roles in metastasis, with a focus on metabolic reprogramming. However, knowledge about associations between Cancer-associated fibroblasts metabolic phenotypes and immune cell is limited. This study uses single-cell and bulk transcriptomics data to decode roles of metabolism-related subtype of Cancer-associated fibroblasts and immune cells in liver metastasis, developing a CAF-related prognostic model for colorectal cancer liver metastases. Methods: In this study, Cancer-associated fibroblasts metabolism-related phenotypes were screened using comprehensive datasets from The Cancer Genome Atlas and gene expression omnibus (GEO). Cox regression and Lasso regression were applied to identify prognostic genes related to Cancer-associated fibroblasts, and a model was constructed based on the Cancer-associated fibroblasts subtype gene score. Subsequently, functional, immunological, and clinical analyses were performed. Results: The study demonstrated the metabotropic heterogeneity of Cancer-associated fibroblasts cells. Cancer-associated fibroblasts cells with varying metabolic states were found to exhibit significant differences in communications with different immune cells. Prognostic features based on Cancer-associated fibroblasts signature scores were found to be useful in determining the prognostic status of colorectal cancer patients with liver metastases. High immune activity and an enrichment of tumor-related pathways were observed in samples with high Cancer-associated fibroblasts signature scores. Furthermore, Cancer-associated fibroblasts signature score could be practical in guiding the selection of chemotherapeutic agents with higher sensitivity. Conclusion: Our study identified a prognostic signature linked to metabotropic subtype of Cancer-associated fibroblasts. This signature has promising clinical implications in precision therapy for colorectal cancer liver metastases.

Establishment and validation of exhausted CD8+ T cell feature as a prognostic model of HCC

Objectives

The exhausted CD8+T (Tex) cells are a unique cell population of activated T cells that emerges in response to persistent viral infection or tumor antigens. Tex cells showed the characteristics of aging cells, including weakened self-renewal ability, effector function inhibition, sustained high expression of inhibitory receptors including PD-1, TIGIT, TIM-3, and LAG-3, and always accompanied by metabolic and epigenetic reprogramming. Tex cells are getting more and more attention in researching immune-related diseases and tumor immunotherapy. However, studies on Tex-related models for tumor prognosis are still lacking. We hope to establish a risk model based on Tex-related genes for HCC prognosis.

Methods

Tex-related GEO datasets from different pathologic factors (chronic HBV, chronic HCV, and telomere shortening) were analyzed respectively to acquire differentially expressed genes (DEGs) by the ‘limma’ package of R. Genes with at least one intersection were incorporated into Tex-related gene set. GO, KEGG, and GSEA enrichment analyses were produced. Hub genes and the PPI network were established and visualized by the STRING website and Cytoscape software. Transcription factors and targeting small molecules were predicted by the TRUST and CLUE websites. The Tex-related HCC prognostic model was built by Cox regression and verified based on different datasets. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms tested immunotherapy sensitivity. Finally, qRT-PCR and Flow Cytometry was used to confirm the bioinformatic results.

Results

Hub genes such as AKT1, CDC6, TNF and their upstream transcription factor ILF3, Regulatory factor X-associated protein, STAT3, JUN, and RELA/NFKB1 were identified as potential motivators for Tex. Tex-related genes SLC16A11, CACYBP, HSF2, and ATG10 built the HCC prognostic model and helped with Immunotherapy sensitivity prediction.

Conclusion

Our study demonstrated that Tex-related genes might provide accurate prediction for HCC patients in clinical decision-making, prognostic assessment, and immunotherapy. In addition, targeting the hub genes or transcription factors may help to reverse T cell function and enhance the effect of tumor immunotherapy.

Divergent outcomes of anti-PD-L1 treatment coupled with host-intrinsic differences in TCR repertoire and distinct T cell activation states in responding versus non-responding tumors

Differential responses to immune checkpoint inhibitors (ICI) may be attributed to tumor-intrinsic factors or environmental cues; however, these mechanisms cannot fully explain the variable ICI responses in different individuals. Here, we investigate the potential contribution of immunological heterogeneity with a focus on differences in T-cell receptor (TCR) repertoire to ICI responses, which has not been defined previously. To reveal additional factors underlying heterogeneous responses to ICI, we employed a squamous cell carcinoma (SCC) mouse model in which tumor-bearing recipients unambiguously diverged into responders (R) or non-responders (NR) upon anti-PD-L1 treatment. Treatment efficacy absolutely required CD8 T-cells and correlated positively with effector functions of CD8 tumor-infiltrating lymphocytes (TILs). We showed that TCR repertoires exhibited a similar magnitude of clonal expansion in R vs. NR CD8 TILs. However, the top expanded TCR clonotypes appeared to be mutually exclusive between R and NR CD8 TILs, which also occurred in a recipient-specific manner, demonstrating preferential expansion of distinct TCR clonotypes against the same SCC tumor. Unexpectedly, R vs. NR CD8 TILs reached all activation clusters and did not exhibit substantial global differences in transcriptomes. By linking single-cell transcriptomic data with unique TCR clonotypes, CD8 TILs harboring top TCR clonotypes were found to occupy distinct activation clusters and upregulate genes favoring anti-tumor immunity to different extents in R vs. NR. We conclude that stochastic differences in CD8 TIL TCR repertoire and distinct activation states of top TCR clonotypes may contribute to differential anti-PD-L1 responses. Our study suggests that host-intrinsic immunological heterogeneity may offer a new explanation for differential ICI responses in different individuals, which could impact on strategies for personalized cancer immunotherapy.

Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy

The advent of single-cell RNA sequencing (scRNA-seq) has provided insight into the tumour immune microenvironment (TIME). This review focuses on the application of scRNA-seq in investigation of the TIME. Over time, scRNA-seq methods have evolved, and components of the TIME have been deciphered with high resolution. In this review, we first introduced the principle of scRNA-seq and compared different sequencing approaches. Novel cell types in the TIME, a continuous transitional state, and mutual intercommunication among TIME components present potential targets for prognosis prediction and treatment in cancer. Thus, we concluded novel cell clusters of cancer-associated fibroblasts (CAFs), T cells, tumour-associated macrophages (TAMs) and dendritic cells (DCs) discovered after the application of scRNA-seq in TIME. We also proposed the development of TAMs and exhausted T cells, as well as the possible targets to interrupt the process. In addition, the therapeutic interventions based on cellular interactions in TIME were also summarized. For decades, quantification of the TIME components has been adopted in clinical practice to predict patient survival and response to therapy and is expected to play an important role in the precise treatment of cancer. Summarizing the current findings, we believe that advances in technology and wide application of single-cell analysis can lead to the discovery of novel perspectives on cancer therapy, which can subsequently be implemented in the clinic. Finally, we propose some future directions in the field of TIME studies that can be aided by scRNA-seq technology.

SLC7A1 Overexpression Is Involved in Energy Metabolism Reprogramming to Induce Tumor Progression in Epithelial Ovarian Cancer and Is Associated with Immune-Infiltrating Cells

Cationic amino acid transporters (SLC7A1/CAT1) are highly expressed in human ovarian cancer (OC) tissues. However, the specific biological functions and mechanisms involved remain unclear. We used bioinformatics analysis to explore SLC7A1 expression level, prognostic value, and tumor mutation burden (TMB) in ovarian cancer (OC) tissues. We performed in vitro experiments to identify the expression and biological function of SLC7A1 in epithelial ovarian cancer (EOC) tissues and cells. An amino acid autoanalyzer was used to detect the effect of SLC7A1 on amino acid metabolism in EOC cells. Finally, SLC7A1 in OC was evaluated for cell-to-cell signalling and immune infiltration using online databases. We found that increased SLC7A1 expression in EOC cells and tissues was associated with poorer survival outcomes (P < 0.05) but not with tumor stage or grade of OC (P > 0.05). SLC7A1 is involved in the transport of phenylalanine and arginine in EOC cells, and its knockdown reduced the proliferation and migration of EOC cells and the resistance of cells to cisplatin. Furthermore, the TIMER database indicated that SLC7A1 overexpression was significantly positively correlated with levels of CD4⁺ memory resting cells, CD8⁺ effector memory cells, M0 macrophages, and cancer-associated fibroblasts (CAFs) in OC (P < 0.05) and significantly negatively correlated with CD4⁺ memory-activated cells (P < 0.05). Cell immunofluorescence indicated that SLC7A1 overexpression may affect the distribution of immune-infiltrating lymphocytes in tumors by inhibiting the expression of CCL4. Therefore, we concluded that SLC7A1 is involved in the metabolic remodelling of amino acids in EOC to promote tumor development and cisplatin resistance and is related to the tumor-infiltrating immune microenvironment of OC. SLC7A1 is a biomarker for predicting EOC progression and cisplatin resistance and represents a promising target for EOC treatment.

Trial watch: Dendritic cell (DC)-based immunotherapy for cancer

Dendritic cell (DC)-based vaccination for cancer treatment has seen considerable development over recent decades. However, this field is currently in a state of flux toward niche-applications, owing to recent paradigm-shifts in immuno-oncology mobilized by T cell-targeting immunotherapies. DC vaccines are typically generated using autologous (patient-derived) DCs exposed to tumor-associated or -specific antigens (TAAs or TSAs), in the presence of immunostimulatory molecules to induce DC maturation, followed by reinfusion into patients. Accordingly, DC vaccines can induce TAA/TSA-specific CD8+/CD4+ T cell responses. Yet, DC vaccination still shows suboptimal anti-tumor efficacy in the clinic. Extensive efforts are ongoing to improve the immunogenicity and efficacy of DC vaccines, often by employing combinatorial chemo-immunotherapy regimens. In this Trial Watch, we summarize the recent preclinical and clinical developments in this field and discuss the ongoing trends and future perspectives of DC-based immunotherapy for oncological indications.

Single-Cell Transcriptome Analysis Reveals Changes of Tumor Immune Microenvironment in Oral Squamous Cell Carcinoma After Chemotherapy

Induction chemotherapy in oral squamous cell carcinoma is a controversial issue in clinical practice. To investigate the evolution of cancer cells and tumor microenvironment (TME) response to chemotherapy in oral squamous cell carcinoma, single-cell transcriptome analysis was performed in a post-chemotherapy squamous cell carcinoma located in oral cavity. The main cell types were identified based on gene expression patterns determined using dimensionality reduction and unsupervised cell clustering. Non-negative matrix factorization clustering of the gene expression of Cancer-associated fibroblasts (CAFs) and macrophages was performed. Kyoto Encyclopedia of Genes and Genomes pathway analyses and gene set enrichment analysis were performed to explore significant functional pathways. CellPhoneDB and NicheNet were used to detect the intercellular communication between cell types. CAFs were divided into "inflammatory CAFs," "antigen-presenting CAFs" and "myofibroblastic CAFs." Three classic subgroups of tumor-associated macrophages (TAMs) were detected, namely C1Q (+), FCN1 (+) and SPP1(+) TAMs. The inflammatory cytokine expression is elevated, and several molecular pathways, such as PI3K/Akt/mTORC1, TNF-α via NFκB, TGF-β, IL-6/JAK2/STAT3 and CXCL12/CXCR4 axis associated with epithelial-mesenchymal transition were enriched in TME. Also, CD74-MIF/COPA/APP interactions were expressed in TME of oral squamous cell carcinoma after chemotherapy. The results revealed the characteristics of TME in post-chemotherapy oral squamous cell carcinoma at single-cell transcriptome level, providing new insights and clues for further investigation.

Mapping and Validation of scRNA-Seq-Derived Cell-Cell Communication Networks in the Tumor Microenvironment

Recent advances in single-cell technologies, particularly single-cell RNA-sequencing (scRNA-seq), have permitted high throughput transcriptional profiling of a wide variety of biological systems. As scRNA-seq supports inference of cell-cell communication, this technology has and continues to anchor groundbreaking studies into the efficacy and mechanism of novel immunotherapies for cancer treatment. In this review, we will highlight methods developed to infer inter- and intracellular signaling from scRNA-seq and discuss how they have contributed to studies of immunotherapeutic intervention in the tumor microenvironment (TME). However, a central challenge remains in validating the hypothesized cell-cell interactions. Therefore, this review will also cover strategies for integration of these scRNA-seq-derived interaction networks with existing experimental and computational approaches. Integration of these networks with imaging, protein secretion measurements, and network analysis and mathematical modeling tools addresses challenges that remain with scRNA-seq to enhance studies of immunosuppressive and immunotherapy-altered signaling in the TME.

Targeting NKG2A to boost anti-tumor CD8 T-cell responses in human colorectal cancer

Recently, the inhibitory CD94/NKG2A receptor has joined the group of immune checkpoints (ICs) and its expression has been documented in NK cells and CD8⁺ T lymphocytes in several cancers and some infectious diseases. In colorectal cancer (CRC), we previously reported that NKG2A⁺ tumor-infiltrating lymphocytes (TILs) are predominantly CD8⁺ αβ T cells and that CD94 overexpression and/or its ligand HLA-E were associated with a poor prognosis. This study aimed to thoroughly characterize the NKG2A⁺ CD8⁺ TIL subpopulation and document the impact of NKG2A on anti-tumor responses in CRC. Our findings highlight new features of this subpopulation: (i) enrichment in colorectal tumors compared to paired normal colonic mucosa, (ii) their character as tissue-resident T cells and their majority terminal exhaustion status, (iii) co-expression of other ICs delineating two subgroups differing mainly in the level of NKG2A expression and the presence of PD-1, (iv) high functional avidity despite reduced proliferative capacity and finally (v) inhibition of anti-tumor reactivity that is overcome by blocking NKG2A. From a clinical point of view, these results open a promising alternative for immunotherapies based on NKG2A blockade in CRC, which could be performed alone or in combination with other IC inhibitors, adoptive cell transfer or therapeutic vaccination.

Machine Learning of Single Cell Transcriptomic Data From anti-PD-1 Responders and Non-responders Reveals Distinct Resistance Mechanisms in Skin Cancers and PDAC

Immune checkpoint therapies such as PD-1 blockade have vastly improved the treatment of numerous cancers, including basal cell carcinoma (BCC). However, patients afflicted with pancreatic ductal carcinoma (PDAC), one of the deadliest malignancies, overwhelmingly exhibit negative responses to checkpoint therapy. We sought to combine data analysis and machine learning to differentiate the putative mechanisms of BCC and PDAC non-response. We discover that increased MHC-I expression in malignant cells and suppression of MHC and PD-1/PD-L expression in CD8⁺ T cells is associated with nonresponse to treatment. Furthermore, we leverage machine learning to predict response to PD-1 blockade on a cellular level. We confirm divergent resistance mechanisms between BCC, PDAC, and melanoma and highlight the potential for rapid and affordable testing of gene expression in BCC patients to accurately predict response to checkpoint therapies. Our findings present an optimistic outlook for the use of quantitative cross-cancer analyses in characterizing immune responses and predicting immunotherapy outcomes.

Immunotherapy of cancer in single-cell RNA sequencing era: A precision medicine perspective

Immunotherapy has revolutionized cancer treatment and brought new aspects into tumor immunology. Effective immunotherapy will require using the suitable target antigens, optimizing the interaction between the antigenic peptide, the APC, and the T cell, and the simultaneous inhibitor of the negative regulatory process that inhibits immunotherapeutic effects and develop resistance. Tumor heterogeneity and its microenvironment is the leading cause of resistance in patients. Recently by emerging the single-cell RNA sequencing technology and its combination with immunotherapy, now we can specifically evaluate the mechanism of tumors in the face of immunotherapy agents at the single-cell resolution by detecting the transcriptional activity of immune checkpoints, screening neoantigens with high transcription levels, identifying rare cells, and other important processes. This review focuses on scRNA-seq, particularly on its application in cancer immunotherapy.

Anhydroicaritin Inhibits EMT in Breast Cancer by Enhancing GPX1 Expression: A Research Based on Sequencing Technologies and Bioinformatics Analysis

Background: Breast cancer (BC) is the leading cause of cancer-related deaths among women worldwide. The application of advanced technology has promoted accurate diagnosis and treatment of cancer. Anhydroicaritin (AHI) is a flavonoid with therapeutic potential in BC treatment. The current study aimed to determine AHI's mechanism in BC treatment via RNA sequencing, comprehensive bioinformatics analysis, and experimental verification. Methods: Network pharmacology and MTT (3-(4,5)-dimethylthiazolyl-3,5- diphenyltetrazolium bromide) experiments were conducted to first confirm AHI's anti-BC effect. RNA sequencing was performed to identify the genes affected by AHI. Differential expression analysis, survival analysis, gene set enrichment analysis, and immune infiltration analysis were performed via bioinformatics analysis. Western blot analysis, reverse transcription-polymerase chain reaction (RT-PCR) experiment, molecular docking, and drug affinity responsive target stability (DARTS) experiments were also performed to confirm AHI's direct effect on glutathione peroxidase 1 (GPX1) expression. Confocal immunofluorescence analysis was conducted to verify AHI's effect on the occurrence and development of epithelial-mesenchymal transition (EMT). Finally, BC nude mouse xenografts were established, and AHI's molecular mechanism on BC was explored. Results: Network pharmacology results demonstrated that AHI's therapeutic targets on BC were related to the proliferation, invasion, and metastasis of BC cells. AHI significantly inhibited the proliferation of 4T1 and MDA-MB-231 BC cells in the MTT experiments. RNA sequencing results showed that AHI upregulated the GPX1 expression in the 4T1 and MDA-MB-231 BC cells. Next, bioinformatics analysis revealed that GPX1 is less expressed in BC than in normal breast tissues. Patients with high GPX1 expression levels tended to have prolonged overall survival and disease-free survival than patients with low GPX1 expression levels in BC. Western blot and RT-PCR experiments revealed that AHI increased the protein and mRNA levels of GPX1. Molecular docking and DARTS experiments confirmed the direct binding combination between AHI and GPX1. After the evaluation of the EMT scores of 1,078 patients with BC, we found a potential anti-BC role of GPX1 possibly via suppression of the malignant EMT. The confocal immunofluorescence analysis showed that AHI increased E-cadherin expression levels and reduced vimentin expression levels in BC cells. Animal experiments showed that AHI significantly inhibited tumor growth. AHI also inhibited EMT by enhancing GPX1 and caspase3 cleavage, hence inhibiting EMT markers (i.e., N-cadherin and vimentin) and Ki-67. Conclusion: GPX1 plays a critical role in BC, which may be a biomarker for the prognosis. In addition, AHI suppressed EMT by increasing GPX1 expression, which may serve as a potential therapy for BC treatment.