Single-cell transcriptome analysis reveals functional changes in tumour-infiltrating B lymphocytes after chemotherapy in oesophageal squamous cell carcinoma

Identification of prognostic risk model based on plasma cell markers in hepatocellular carcinoma through single-cell sequencing analysis

Hepatocellular carcinoma (HCC) represents a substantial global health burden. Tumorinfiltrating B lymphocytes (TIL-Bs) contribute to tumor progression and significantly impact the efficacy of tumor therapy. However, the characteristics of TIL-Bs in HCC and their effect on HCC therapy remain elusive. Single-cell RNA sequencing (scRNAseq) was applied to investigate the heterogeneity, cellular differentiation and cell-cell communication of TIL-Bs in HCC. Further, the Cancer Genome Atlas-liver hepatocellular carcinoma (TCGA-LIHC) and liver cancer institutes (LCI) cohorts were applied to construct and validate the plasma cell marker-based prognostic risk model. The relationship between the prognostic risk model and the responsiveness of immunotherapy and chemotherapy in patients with HCC were estimated by OncoPredict and tumor immune dysfunction and exclusion (TIDE) algorithm. Finally, we established nomogram and calibration curves to evaluate the precision of the risk score in predicating survival probability. Our data identified five subtypes of TIL-Bs in HCC, each exhibiting varying levels of infiltration in tumor tissues. The interactions between TIL-Bs and other cell types contributed to shaping distinct tumor microenvironments (TME). Moreover, we found that TIL-Bs subtypes had disparate prognostic values in HCC patients. The prognostic risk model demonstrated exceptional predictive accuracy for overall survival and exhibited varying sensitivities to immunotherapy and chemotherapy among patients with HCC. Our data demonstrated that the risk score stood as an independent prognostic predictor and the nomogram results further affirmed its strong prognostic capability. This study reveals the heterogeneity of TIL-Bs and provides a prognostic risk model based on plasma cell markers in HCC, which could prove valuable in predicting prognosis and guiding the choice of suitable therapies for patients with HCC.

Mechanisms of tumor immunosuppressive microenvironment formation in esophageal cancer

As a highly invasive malignancy, esophageal cancer (EC) is a global health issue, and was the eighth most prevalent cancer and the sixth leading cause of cancer-related death worldwide in 2020. Due to its highly immunogenic nature, emer-ging immunotherapy approaches, such as immune checkpoint blockade, have demonstrated promising efficacy in treating EC; however, certain limitations and challenges still exist. In addition, tumors may exhibit primary or acquired resistance to immunotherapy in the tumor immune microenvironment (TIME); thus, understanding the TIME is urgent and crucial, especially given the im-portance of an immunosuppressive microenvironment in tumor progression. The aim of this review was to better elucidate the mechanisms of the suppressive TIME, including cell infiltration, immune cell subsets, cytokines and signaling pathways in the tumor microenvironment of EC patients, as well as the downregulated expression of major histocompatibility complex molecules in tumor cells, to obtain a better understanding of the differences in EC patient responses to immunotherapeutic strategies and accurately predict the efficacy of immunotherapies. Therefore, personalized treatments could be developed to maximize the advantages of immunotherapy.

Characterization of the Immune Microenvironment and Identification of Biomarkers in Chronic Rhinosinusitis with Nasal Polyps Using Single-Cell RNA Sequencing and Transcriptome Analysis

Purpose

Chronic rhinosinusitis is a prevalent condition in the field of otorhinolaryngology; however, its pathogenesis remains to be elucidated. The immunological defense of the nasal mucosa is significantly influenced by dendritic cells (DCs). We identified specific biological indicators linked to DCs and explored their significance in cases of chronic rhinosinusitis with nasal polyps (CRSwNP).

Patients and Methods

We categorized cells using single-cell RNA (scRNA) sequencing, and combined transcriptome sequencing was used to identify potential candidate genes for CRSwNP. We selected three biomarkers based on two algorithms and performed enrichment and immune correlation analyses. Biomarkers were verified using training and validation sets, receiver operating characteristic curves, immunohistochemistry, and quantitative real-time reverse-transcription PCR (qRT-PCR). Variations in biomarker expression were validated using pseudotime analysis. The networks of competing transcription factor (TF)-mRNA and competing endogenous RNA (ceRNA) were established, and the protein drugs associated with these biomarkers were predicted.

Results

Both scRNA-seq and transcriptome data showed that DCs immune infiltration was higher in the CRSwNP group than in the control group. Three DC-related biomarkers (NR4A1, CLEC4G, and CD163) were identified. In CRSwNP, NR4A1 expression decreased, whereas CLEC4G and CD163 expression increased. All biomarkers were shown to be involved in immunological and metabolic pathways by enrichment analysis. These biomarkers were associated with γδ T cells, effector memory CD4 + T cells, regulatory T cells, and immature DCs. According to pseudotime analysis, NR4A1 and CD163 expression decreased from high to low, whereas CLEC4G expression remained low.

Conclusion

We screened and identified potential DC-associated biomarkers of CRSwNP progression by integrating scRNA-seq with whole transcriptome sequencing. We analyzed the biological pathways in which they were involved, explored their molecular regulatory mechanisms and related drugs, and constructed ceRNA, TF-mRNA, and biomarker-drug networks to identify new CRSwNP treatment targets, laying the groundwork for the clinical management of CRSwNP.