Deciphering Macrophage and Monocyte Code to Stratify Human Breast Cancer Patients

G-CSF/GM-CSF-induced hematopoietic dysregulation in the progression of solid tumors

There are two types of abnormal hematopoiesis in solid tumor occurrence and treatment: pathological hematopoiesis, and myelosuppression induced by radiotherapy and chemotherapy. In this review, we primarily focus on the abnormal pathological hematopoietic differentiation in cancer induced by tumor-released granulocyte colony stimulating factor (G-CSF) and granulocyte-macrophage colony stimulating factor (GM-CSF). As key factors in hematopoietic development, G-CSF/GM-CSF are well-known facilitators of myelopoiesis and mobilization of hematopoietic stem cells (HSCs). In addition, these two cytokines can also promote or inhibit tumors, dependent on tumor type. In multiple cancer types, hematopoiesis is greatly enhanced and abnormal lineage differentiation is induced by these two cytokines. Here, dysregulated hematopoiesis induced by G-CSF/GM-CSF in solid tumors and its mechanism are summarized, and the prognostic value of G-CSF/GM-CSF-associated dysregulated hematopoiesis for tumor metastasis is also briefly highlighted.

Identification and Verification of Tumor Immune Microenvironment-Related Prognostic Genes in Kidney Renal Clear Cell Carcinoma

Background

The tumor immune microenvironment is vital to kidney renal clear cell carcinoma (KIRC) progression, and immunotherapies have been shown to be effective in the management of KIRC. However, the prognostic genes associated with the tumor immune microenvironment in KIRC have not been fully identified. We obtained the KIRC RNA sequencing data and the clinical characteristics from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. We screened the gene modules associated with the tumor immune microenvironment based on the ESTIMATE algorithm and weighted gene coexpression network analysis (WGCNA). Univariate Cox analysis and the LASSO method were used to construct a prognostic model. Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the accuracy of our risk model. TIMER and Single-Sample Gene Set Enrichment Analysis (ssGSEA) were used to explore the correlation between prognostic genes and immune cell infiltration.

Results

Fifty-four genes in modules were significantly associated with the overall survival (OS) time of patients with KIRC. Furthermore, 12 hub genes were selected to construct the prognostic model. The prognostic model showed superior accuracy in both TCGA and ICGC cohorts using ROC curve analysis. Systematic analysis of immune cell infiltration revealed that nine genes were significantly correlated with levels of tumor-infiltrating immune cells.

Conclusions

Our findings indicated that the tumor immune microenvironment was an important determinant of KIRC outcomes and revealed potential biomarkers for predicting patient OS and for targeted immunotherapies.

Six Immune Associated Genes Construct Prognostic Model Evaluate Low-Grade Glioma

Background

The immunotherapy of Glioma has always been a research hotspot. Although tumor associated microglia/macrophages (TAMs) proves to be important in glioma progression and drug resistance, our knowledge about how TAMs influence glioma remains unclear. The relationship between glioma and TAMs still needs further study.

Methods

We collected the data of TAMs in glioma from NCBI Gene Expression Omnibus (GEO) that included 20 glioma samples and 15 control samples from four datasets. Six genes were screened from the Differential Expression Gene through Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, protein-protein interaction (PPI) network and single-cell sequencing analysis. A risk score was then constructed based on the six genes and patients' overall survival rates of 669 patients from The Cancer Genome Atlas (TCGA). The efficacy of the risk score in prognosis and prediction was verified in Chinese Glioma Genome Atlas (CGGA).

Results

Six genes, including CD163, FPR3, LPAR5, P2ry12, PLAUR, SIGLEC1, that participate in signal transduction and plasma membrane were selected. Half of them, like CD163, FPR3, SIGLEC1, were mainly expression in M2 macrophages. FPR3 and SIGLEC1 were high expression genes in glioma associated with grades and IDH status. The overall survival rates of the high risk score group was significantly lower than that of the low risk score group, especially in LGG.

Conclusion

Joint usage of the 6 candidate genes may be an effective method to diagnose and evaluate the prognosis of glioma, especially in Low-grade glioma (LGG).

Distinct Populations of Immune-Suppressive Macrophages Differentiate from Monocytic Myeloid-Derived Suppressor Cells in Cancer

Here, we report that functional heterogeneity of macrophages in cancer could be determined by the nature of their precursors: monocytes (Mons) and monocytic myeloid-derived suppressor cells (M-MDSCs). Macrophages that are differentiated from M-MDSCs, but not from Mons, are immune suppressive, with a genomic profile matching that of M-MDSCs. Immune-suppressive activity of M-MDSC-derived macrophages is dependent on the persistent expression of S100A9 protein in these cells. S100A9 also promotes M2 polarization of macrophages. Tissue-resident- and Mon-derived macrophages lack expression of this protein. S100A9-dependent immune-suppressive activity of macrophages involves transcription factor C/EBPβ. The presence of S100A9-positive macrophages in tumor tissues is associated with shorter survival in patients with head and neck cancer and poor response to PD-1 antibody treatment in patients with metastatic melanoma. Thus, this study reveals the pathway of the development of immune-suppressive macrophages and suggests an approach to their selective targeting.

Prognostic value of immune-related genes and immune cell infiltration analysis in the tumor microenvironment of head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is one of the few malignant tumors that respond well to immunotherapy. We aimed to investigate the immune-related genes and immune cell infiltration of HNSCC and construct a predictive model for its prognosis.

METHODS

We calculated the stromal/immune scores of patients with HNSCC from The Cancer Genome Atlas using the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm and investigated the relationship between the scores and patients' prognosis. Three machine learning algorithms (LASSO, Random Forest, and Rbsurv) were performed to screen key immune-related genes and constructed a predictive model. The immune cell infiltrating was calculated by the Tumor Immune Estimation Resource algorithm.

RESULTS

The stromal and immune scores significantly correlated with prognosis. A 6-gene signature was selected and displayed a robust predictive effect. The expressions of key genes were associated with immune infiltrating. GSE65858 validated the results.

CONCLUSION

Our study comprehensively analyzed the tumor microenvironment of HNSCC and constructed a robust predictive model, providing a basis for further investigation of therapy.

Identification of prognostic immune-related genes in the tumor microenvironment of endometrial cancer

Endometrial cancer (EC) is one of the most common gynecologic malignancies. To identify potential prognostic biomarkers for EC, we analyzed the relationship between the EC tumor microenvironment and gene expression profiles. Using the ESTIMATE R tool, we found that immune and stromal scores correlated with clinical data and the prognosis of EC patients. Based on the immune and stromal scores, 387 intersection differentially expressed genes were identified. Eight immune-related genes were then identified using two machine learning algorithms. Functional enrichment analysis revealed that these genes were mainly associated with T cell activation and response. Kaplan-Meier survival analysis showed that expression of TMEM150B, CACNA2D2, TRPM5, NOL4, CTSW, and SIGLEC1 significantly correlated with overall survival times of EC patients. In addition, using the TIMER algorithm, we found that expression of TMEM150B, SIGLEC1, and CTSW correlated positively with the tumor infiltration levels of B cells, CD8+ T cells, CD4+ T cells, macrophages, and dendritic cells. These findings indicate that the composition of the tumor microenvironment affects the clinical outcomes of EC patients, and suggests that it may provide a basis for development of novel prognostic biomarkers and immunotherapies for EC patients.

Breast cancer cells promote CD169+ macrophage-associated immunosuppression through JAK2-mediated PD-L1 upregulation on macrophages

Macrophages are recognized as one of the major cell types in tumor microenvironment, and macrophage infiltration has been predominantly associated with poor prognosis among patients with breast cancer. Using the murine models of triple-negative breast cancer in CD169-DTR mice, we found that CD169⁺ macrophages support tumor growth and metastasis. CD169⁺ macrophage depletion resulted in increased accumulation of CD8⁺ T cells within tumor, and produced significant expansion of CD8⁺ T cells in circulation and spleen. In addition, we observed that CD169⁺ macrophage depletion alleviated tumor-induced splenomegaly in mice, but had no improvement in bone loss and repression of bone marrow erythropoiesis in tumor-bearing mice. Cancer cells and tumor associated macrophages exploit the upregulation of the immunosuppressive protein PD-L1 to subvert T cell-mediated immune surveillance. Within the tumor microenvironment, our understanding of the regulation of PD-L1 protein expression is limited. We showed that there was a 5-fold higher relative expression of PD-L1 on macrophages as compared with 4T1 tumor cells; coculture of macrophages with 4T1 cells augmented PD-L1 levels on macrophages, but did not upregulate the expression of PD-L1 on 4T1 cells. JAK2/STAT3 signaling pathway was activated in macrophages after coculture, and we further identified the JAK2 as a critical regulator of PD-L1 expression in macrophages during coculture with 4T1 cells. Collectively, our data reveal that breast cancer cells and CD169⁺ macrophages exhibit bidirectional interactions that play a critical role in tumor progression, and inhibition of JAK2 signaling pathway in CD169⁺ macrophages may be potential strategy to block tumor microenvironment-derived immune escape.

Prognostic Significance of Tumor-Associated Macrophage Content in Head and Neck Squamous Cell Carcinoma: A Meta-Analysis

Background: Head and neck squamous cell carcinoma (HNSCC) exists within a microenvironment rich in immune cells. Macrophages are particularly abundant in and around tumor tissue, and have been implicated in the growth, malignancy, and persistence of HNSCC (1). However, current literature reports variable degrees of association between the density of tumor-associated macrophages (TAMs) and clinicopathologic markers of disease (2, 3). These inconsistent findings may be a result of differences in approach to TAM detection. Authors have measured total TAMs in tumor tissue, while others have stained tumor samples for individual subtypes of TAMs, which include pro-inflammatory (M1-like) and immunosuppressive (M2-like). Our aim is to more clearly define the prognostic significance of the phenotypes of tumor-associated macrophages in HNSCC. Methods: We conducted a meta-analysis of the existing publications investigating the relationship between TAMs (total and M2-like subtype) and T stage, nodal involvement, vascular invasion, lymphatic invasion, and tumor differentiation (Figure 1). A total of 12 studies were included. Forest plots and risk ratios were generated to report overall effect. Results: Higher density of both total and M2-like subtype of TAMs in the tumor microenvironment is associated with advanced T stage, increased rates of nodal positivity, presence of vascular invasion, and presence of lymphatic invasion (p < 0.0001; Figures 2-9). There is no significant association between TAM density, either total or M2-like subtype, and tumor differentiation (Figures 10, 11). Conclusions: Increased density of TAMs, including those of the M2-like phenotype, correlate with poor clinicopathologic markers in HNSCC. Our findings warrant additional investigation into the subpopulations of TAMs, the mechanisms behind their recruitment and differentiation, and the associated influence of each phenotype on tumor growth and invasion. A greater understanding of TAM dynamics in HNSCC is critical for directing further research and employing TAM-targeted adjunct therapies.