Single-cell sequencing and establishment of an 8-gene prognostic model for pancreatic cancer patients

The role of histone H1.2 in pancreatic cancer metastasis and chemoresistance

AIMS

Pancreatic cancer (PC) is a highly metastatic malignant tumor of the digestive system. Drug resistance frequently occurs during cancer treatment process. This study aimed to explore the link between chemoresistance and tumor metastasis in PC and its possible molecular and cellular mechanisms.

METHODS

A Metastasis and Chemoresistance Signature (MCS) scoring system was built and validated based on metastasis- and chemoresistance-related genes using gene expression data of PC, and the model was applied to single-cell RNA sequencing data. The influence of linker histone H1.2 (H1-2) on PC was explored through in vitro and in vivo experiments including proliferation, invasion, migration, drug sensitivity, rescue experiments and immunohistochemistry, emphasizing its regulation with c-MYC signaling pathway.

RESULTS

A novel MCS scoring system accurately predicted PC patient survival and was linked to chemoresistance and epithelial-mesenchymal transition (EMT) in PC single-cell RNA sequencing data. H1-2 emerged as a significant prognostic factor, with its high expression indicating increased chemoresistance and EMT. This upregulation was mediated by c-MYC, which was also found to be highly expressed in PC tissues.

CONCLUSION

The MCS scoring system offers insights into PC chemoresistance and metastasis potential. Targeting H1-2 could enhance therapeutic strategies and improve PC patient outcomes.

Association between spatial distribution of leukocyte subsets and clinical presentation of head and neck squamous cell carcinoma

Background

Interactions between tumor cells and cells in the microenvironment contribute to tumor development and metastasis. The spatial arrangement of individual cells in relation to each other influences the likelihood of whether and how these cells interact with each other.

Methods

This study investigated the effect of spatial distribution on the function of leukocyte subsets in the microenvironment of human head and neck squamous cell carcinoma (HNSCC) using multiplex immunohistochemistry (IHC). Leukocyte subsets were further classified based on analysis of two previously published HNSCC single-cell RNA datasets and flow cytometry (FC).

Results

IHC revealed distinct distribution patterns of leukocytes differentiated by CD68 and CD163. While CD68hiCD163lo and CD68hiCD163hi cells accumulated near tumor sites, CD68loCD163hi cells were more evenly distributed in the tumor stroma. PD-L1hi and PD-1hi cells accumulated predominantly around tumor sites. High cell density of PD-L1hi CD68hiCD163hi cells or PD-1hi T cells near the tumor site correlated with improved survival. FC and single cell RNA revealed high variability within the CD68/CD163 subsets. CD68hiCD163lo and CD68hiCD163hi cells were predominantly macrophages (MΦ), whereas CD68loCD163hi cells appeared to be predominantly dendritic cells (DCs). Differentiation based on CD64, CD80, CD163, and CD206 revealed that TAM in HNSCC occupy a broad spectrum within the classical M1/M2 polarization. Notably, the MΦ subsets expressed predominantly CD206 and little CD80. The opposite was observed in the DC subsets.

Conclusion

The distribution patterns and their distinct interactions via the PD-L1/PD-1 pathway suggest divergent roles of CD68/CD163 subsets in the HNSCC microenvironment. PD-L1/PD-1 interactions appear to occur primarily between specific cell types close to the tumor site. Whether PD-L1/PD-1 interactions have a positive or negative impact on patient survival appears to depend on both the spatial localization and the entity of the interacting cells. Co-expression of other markers, particularly CD80 and CD206, supports the hypothesis that CD68/CD163 IHC subsets have distinct functions. These results highlight the association between spatial leukocyte distribution patterns and the clinical presentation of HNSCC.

Identification and validation of a novel signature based on T cell marker genes to predict prognosis, immunotherapy response and chemotherapy sensitivity in head and neck squamous carcinoma by integrated analysis of single-cell and bulk RNA-sequencing

T cells are among the most potent anti-tumor cells that are found in humans. Our study sought to develop a reliable signature incorporating T cell marker genes (TMGs) for predicting the prognosis and therapy responsiveness of head and neck squamous cell carcinoma (HNSCC) patients. We downloaded scRNA-seq data from the GSE181919 to identify TMGs. Subsequently, we devised a 12 TMG signature in the TCGA HNSCC cohort by using LASSO analysis. Patients with high-risk scores were shown to experience unfavorable progression-free survival, disease-specific survival, and overall survival, which was validated in the GSE65858 cohort. Additionally, the nomogram integrated risk score and clinical features are more suitable for clinical application. The enrichment analyses of both pathways and functions showed that high- and low-risk patients had functionally related distinctions. Furthermore, analysis of the immunological landscape confirmed that the low-risk patients had a larger percentage of infiltrating immune cells as well as a higher incidence rate of immune-related events. In the meantime, a greater IPS score and expression of immune checkpoint genes suggested significantly favorable responsiveness to immunotherapy in low-risk patients. On the other hand, the high-risk patients had a greater degree of sensitivity to the chemotherapy agents, which included paclitaxel, gemcitabine, docetaxel, and cisplatin. Our finding revealed that this TMG signature independently functioned as a prognostic marker and guided individualized immunotherapy and chemotherapy selection for patients with HNSCC.

Nidogen-2 (NID2) is a Key Factor in Collagen Causing Poor Response to Immunotherapy in Melanoma

Background

The incidence of cutaneous melanoma continues to rise rapidly and has an extremely poor prognosis. Immunotherapy strategies are the most effective approach for patients who have developed metastases, but not all cases have been successful due to the complex and variable mechanisms of melanoma response to immune checkpoint inhibition.

Methods

We synthesized collagen-coding gene expression data (second-generation and single-cell sequencing) from public Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Bioinformatics analysis was performed using R software and several database resources such as Metascape database, Gene Set Cancer Analysis (GSCA) database, and Cytoscape software, etc., to investigate the biological mechanisms that may be related with collagens. Immunofluorescence and immunohistochemical staining were used to validate the expression and localization of Nidogen-2 (NID2).

Results

Melanoma patients can be divided into two collagen clusters. Patients with high collagen levels (C1) had a shorter survival than those with low collagen levels (C2) and were less likely to benefit from immunotherapy. We demonstrated that NID2 is a potential key factor in the collagen phenotype, is involved in fibroblast activation in melanoma, and forms a barrier to limit the proximity of CD8+ T cells to tumor cells.

Conclusion

We clarified the adverse effects of collagen on melanoma patients and identified NID2 as a potential therapeutic target.