Transcriptional Signature Derived from Murine Tumor-Associated Macrophages Correlates with Poor Outcome in Breast Cancer Patients

Tuit, Sander; Salvagno, Camilla; Kapellos, Theodore S.; Hau, Cheei-Sing; Seep, Lea; Oestreich, Marie; Klee, Kathrin; Visser, Karin E. de; Ulas, Thomas; Schultze, Joachim L.

doi:10.1016/j.celrep.2019.09.067

Cited by 32 publications

(29 citation statements)

References 69 publications

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“…The IL2Ra level in serum may be meaningful for prognosis after cancer treatment, which increased by 63.8% in HNSCC patients (p = 0.032) after cisplatin chemoradiation in Panagiota's report (33). The heterogeneity of TFs in different TMEs is enormous and of great significance (34). Our correlation analysis revealed some key TFs that regulate MGMs.…”

Section: Discussionmentioning

confidence: 62%

Prognostic Value of a Ten-Gene Signature in HNSCC Patients Based on Tumor-Associated Macrophages Expression Profiling

Duan

2020

Front. Oncol.

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Section: Discussionmentioning

confidence: 62%

Prognostic Value of a Ten-Gene Signature in HNSCC Patients Based on Tumor-Associated Macrophages Expression Profiling

Duan

2020

Front. Oncol.

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“…These cells are enriched for phagocytic genes such as Axl and Hexb , as well as genes that define pro-inflammatory macrophages ( Cd86, Tnf ) and immunosuppressive function ( Il1b and Tgfb1 ). Interestingly, cluster 3 also highly expresses Cxcl16 , which was shown to define a subset of tumor-associated macrophages in Neu-driven mouse tumors characterized by Cxc3r1 and Mmp14 ( 40 ). Cluster 6 highly expresses tissue reparative/wound healing genes shared by MC0, such as Mrc1 and Gas6 , as well as pro-inflammatory genes common to MC3, including Tnf, Ccl7 , and Ccl2 .…”

Section: Resultsmentioning

confidence: 99%

Diverse Macrophage Populations Contribute to the Inflammatory Microenvironment in Premalignant Lesions During Localized Invasion

et al. 2020

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Myeloid cell heterogeneity remains poorly studied in breast cancer, and particularly in premalignancy. Here, we used single cell RNA sequencing to characterize macrophage diversity in mouse pre-invasive lesions as compared to lesions undergoing localized invasion. Several subpopulations of macrophages with transcriptionally distinct profiles were identified, two of which resembled macrophages in the steady state. While all subpopulations expressed tumor-promoting genes, many of the populations expressed pro-inflammatory genes, differing from reports in tumor-associated macrophages. Gene profiles of the myeloid cells were similar between early and late stages of premalignancy, although expansion of some subpopulations occurred. These results unravel macrophage heterogeneity in early progression and may provide insight into early intervention strategies that target macrophages.

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“…The mean GFC expression for each cluster and condition was visualized in the Cluster/Condition heatmap. Clusters smaller than 10 genes were not shown 47 .…”

Section: Methodsmentioning

confidence: 99%

Transcriptomic analysis of immune cells in a multi-ethnic cohort of systemic lupus erythematosus patients identifies ethnicity- and disease-specific expression signatures

et al. 2021

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Systemic lupus erythematosus (SLE) is an autoimmune disease in which outcomes vary among different racial groups. We leverage cell-sorted RNA-seq data (CD14+ monocytes, B cells, CD4+ T cells, and NK cells) from 120 SLE patients (63 Asian and 57 White individuals) and apply a four-tier approach including unsupervised clustering, differential expression analyses, gene co-expression analyses, and machine learning to identify SLE subgroups within this multiethnic cohort. K-means clustering on each cell-type resulted in three clusters for CD4 and CD14, and two for B and NK cells. To understand the identified clusters, correlation analysis revealed significant positive associations between the clusters and clinical parameters including disease activity as well as ethnicity. We then explored differentially expressed genes between Asian and White groups for each cell-type. The shared differentially expressed genes across cells were involved in SLE or other autoimmune-related pathways. Co-expression analysis identified similarly regulated genes across samples and grouped these genes into modules. Finally, random forest classification of disease activity in the White and Asian cohorts showed the best classification in CD4+ T cells in White individuals. The results from these analyses will help stratify patients based on their gene expression signatures to enable SLE precision medicine.

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Transcriptional Signature Derived from Murine Tumor-Associated Macrophages Correlates with Poor Outcome in Breast Cancer Patients

Cited by 32 publications

References 69 publications

Prognostic Value of a Ten-Gene Signature in HNSCC Patients Based on Tumor-Associated Macrophages Expression Profiling

Prognostic Value of a Ten-Gene Signature in HNSCC Patients Based on Tumor-Associated Macrophages Expression Profiling

Diverse Macrophage Populations Contribute to the Inflammatory Microenvironment in Premalignant Lesions During Localized Invasion

Transcriptomic analysis of immune cells in a multi-ethnic cohort of systemic lupus erythematosus patients identifies ethnicity- and disease-specific expression signatures

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