FDCSP Is an Immune-Associated Prognostic Biomarker in HPV-Positive Head and Neck Squamous Carcinoma

MGP+ and IDO1+ tumor-associated macrophages facilitate immunoresistance in breast cancer revealed by single-cell RNA sequencing

Immunotherapy is widely applied for the treatment of breast cancer, but to which some patients respond poorly or develop resistance. Therefore, the mechanism needs to be further studied. Transcriptomic data of 31 breast cancer patients treated with anti-programmed death receptor 1 (PD-1) was downloaded from the VIB-KULeuven Center for Cancer Biology to analyze the changes in myeloid cells in tumor tissues before and after immunotherapy. And 24 cell populations that may be immune-related were further identified. Representative cell populations were also screened and validated through cellular and animal experiments to evaluate the relevant molecular expression and pathways of tumor-associated macrophages (TAMs) in the tumor microenvironment. The results demonstrated that MGP+ TAMs and IDO1+ TAMs influenced the efficacy of immunotherapy in breast cancer patients. After anti-PD-1 treatment, Increased numbers of MGP+ TAMs and IDO1+ TAMs in breast cancer patients upregulated pro-tumorigenic factors associated with resistance to immunosuppressive therapy. This study provides new biomarkers for immunotherapy to predict therapeutic responses and overcome potential resistance to immunotherapy. It is an important complement to the immunosuppression caused by TAMs after immunotherapy for breast cancer.

A novel oxidative stress-related gene signature as an indicator of prognosis and immunotherapy responses in HNSCC

PURPOSE

To identify molecular subtypes of oxidative stress-related genes in head and neck squamous cell carcinoma (HNSCC) and to construct a scoring model of oxidative stress-related genes.

METHODS

R language based scRNA-seq and bulk RNA-seq analyses were used to identify molecular isoforms of oxidative stress-related genes in HNSCC. An oxidative stress-related gene scoring (OSRS) model was constructed, which were verified through online data and immunohistochemical staining of clinical samples.

RESULTS

Using TCGA-HNSCC datasets, nine predictive genes for overall patient survival, rarely reported in previous similar studies, were screened. AREG and CES1 were identified as prognostic risk factors. CSTA, FDCSP, JCHAIN, IFFO2, PGLYRP4, SPOCK2 and SPINK6 were identified as prognostic factors. Collectively, all genes formed a prognostic risk signature model for oxidative stress in HNSCC, which were validated in GSE41613, GSE103322 and PRJEB23709 datasets. Immunohistochemical staining of SPINK6 in nasopharyngeal cancer samples validated the gene panel. Subsequent analysis indicated that subgroups of the oxidative stress prognostic signature played important roles during cellular communication, the immune microenvironment, the differential activation of transcription factors, oxidative stress and immunotherapeutic responses.

CONCLUSIONS

The risk model might predict HNSCC prognosis and immunotherapeutic responses.

Novel cell subtypes of SPP1 + S100P+, MS4A1-SPP1 + S100P+ were key subpopulations in intrahepatic cholangiocarcinoma

BACKGROUND

In this study, we integrated single-cell RNA sequencing (scRNA-seq) data to investigate cell heterogeneity and utilized MSigDB and CIBERSORTx to explore the pathways of major cell types and the relationships between different cell subtypes. Subsequently, we explored the correlation of cell subtypes with survival and used Gene Set Enrichment Analysis (GSEA) analyses to assess the pathways associated with the infiltration of specific cell subtypes. Finally, multiplex immunohistochemistry in tissue microarray cohort were performed to validate differences in protein level and their correlation with survival.

RESULTS

iCCA presented a unique immune ecosystem, with increased proportions of Epi (epithelial)-SPP1-2, Epi-S100P-1, Epi-DN (double negative for SPP1 and S100P expression)-1, Epi-DN-2, Epi-DP (double positive for SPP1 and S100P expression)-1, Plasma B-3, Plasma B-2, B-HSPA1A-1, B-HSPA1A-2 cells, and decreased proportions of B-MS4A1. High level of Epi-DN-2, Epi-SPP1-1, Epi-SPP1-2, B-MS4A1, and low level of Epi-DB-1, Epi-S100P-1, and Epi-S100P-2 was significantly associated with longer overall survival (OS), and high level of B-MS4A1_Low_Epi-DN-2_Low was associated with the shortest OS. Moreover, the results of MsigDB and GSEA suggest that bile acid metabolism is a crucial process in iCCA. Finally, we found that S100P+, SPP1+, SPP1 + S100P+, and MS4A1-SPP1 + S100P+ were highly expressed, whereas MS4A1 was lowly expressed in iCCA, and patients with high level of S100P+, SPP1 + S100P+, and MS4A1-SPP1 + S100P+ exhibited shorter survival.

CONCLUSIONS

We identified the cell heterogeneity of iCCA, found that iCCA is a unique immune ecosystem with many cell subtypes, and showed that the novel cell subtypes of SPP1 + S100P+ and MS4A1-SPP1 + S100P+ were key subpopulations in iCCA.

Molecular Evolutionary Landscape of the Immune Microenvironment of Head and Neck Cancer

Head and neck cancer is a highly heterogeneous malignant tumor. Numerous studies have shown that the immune microenvironment of head and neck cancer has a significant impact on its occurrence and development, as well as its prognosis. However, there have been fewer studies related to the accurate immunophenotyping of head and neck cancer. In this study, we used gene expression profile information and clinical information from the TCGA-HNSC cohort (502 samples) and the GSE655858 cohort (270 samples) to identify and independently validate three immune subtypes (Cluster1-Cluster3) with different immune-related molecular profiles and clinical outcomes. Cluster2, which is mainly dominated by B-lymphocyte infiltration, was found to have the best prognosis. In addition, a support vector machine (SVM)-based classifier was constructed, which could accurately classify HNSC based on 19 genes. Furthermore, the results of the prognostic analysis showed activation of antibody-secreting B-lymphocyte function, which showed a good prognostic effect in all three immune subtypes of HNSC. Finally, the immune evolutionary landscape of HNSC was constructed in an attempt to explain the evolutionary pattern of the immune subtypes of HNSC. In summary, we provide a conceptual framework for understanding the tumor immune microenvironment in HNSC and demonstrate the importance of immune infiltration of B lymphocytes in HNSC. Further research is needed to assess the importance of these immunophenotypes in combination drug therapy and to provide a basis for screening appropriate patients for immunotherapy.