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A Spatially-Defined Metastasis-Associated Microglia Subset Promotes Brain Metastasis Outgrowth through Cx3cr1-Mediated Interferon Response

ABSTRACT: A Spatially-Defined Metastasis-Associated Microglia Subset Promotes Brain Metastasis Outgrowth through Cx3cr1-Mediated Interferon Response

PROVIDER: PRJNA488552 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR7768620_1.fastq.gz	Fastqsanger.gz
	SRR7768620_2.fastq.gz	Fastqsanger.gz
	SRR7768621_1.fastq.gz	Fastqsanger.gz
	SRR7768621_2.fastq.gz	Fastqsanger.gz
	SRR7768622_1.fastq.gz	Fastqsanger.gz

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A Spatially-Defined Metastasis-Associated Microglia Subset Promotes Brain Metastasis Outgrowth through Cx3cr1-Mediated Interferon Response

Project description:We use single cell RNA-seqencing (Drop-seq based) to profile and compare (1) the transcriptomes of naïve brain myeloid cells from wild type C57Bl/6 mice to brain metastasis-associated myeloid cells (Br.MAM) from C57Bl/6 mice bearing E0771 brain metastases and (2) the transcriptomes of Br.MAM in Cx3cr1+/- (het) mouse hosts bearing E0771 brain metastases to Br.MAM in Cx3cr1-/- (KO) mouse hosts bearing E0771 brain metastases.

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Project description:When tumor cells colonize distant organs during metastasis, they interact extensively with surrounding cells. These interactions often change the behavior of surrounding cell populations which collectively induce a pro-tumor microenvironment that permits tumor cell outgrowth into overt, clinically detectable metastatic disease. The lung is one of the most common sites of breast cancer (BC) metastasis. A chronic wound repair-related phenotype developed within the lung microenvironment during metastatic outgrowth in immunocompetent preclinical mouse models of BC. This phenotype was characterized by an increased number and activation of lung type II alveolar epithelial (AT2) cells surrounding growing metastases. Metastatic outgrowth significantly changed AT2 gene expression, resulting in a modified secretome. AT2-derived secreted factors also promote triple-negative breast cancer (TNBC) growth. AT2 secreted factors are regulated by the cyclic adenosine monophosphate (cAMP) response element-binding protein (CREB). Targeting CREB signaling with the phosphodiesterase 4 (PDE4) inhibitor roflumilast reduced AT2-BC reciprocal interactions in vitro and metastatic outgrowth in vivo. Finally, AT2 cells adjacent to metastases in lungs from patients with metastatic BC express higher PDE4B compared to AT2 cells in normal lungs. Alveolar epithelial cells are the most common cell type in the lung. Our studies demonstrate the potential for targeting metastasis-associated wound repair and lung epithelial cell activation during metastatic outgrowth with FDA-approved PDE4 inhibitors. This strategy may be an effective way to treat and manage progression of established metastatic BC within the lung.

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Gut Dysbiosis Impacts Brain Metastasis Outgrowth and Immune Response Dynamics [CITE-seq]

Project description:We used CITE-seq (10x Gemoics-based) to profile and compare the transcriptomes and cell surface expression of a set of immune markers of brain immune cells from young-adult C57BL/6 mice with and without antibiotics induced gut microbiota depletion (ABX) during brain metastasis. Brain immune cells were collected from naive brains (D00) and at different time points throughout brain metastasis outgrowth (4 (D04), 8 (D08) and 14 (D14) days post injection). We sequenced a total of 24 different mouse brains (3 biological replicates per group: (1) D00 control, (2) D00 ABX, (3) D04 control, (4) D04 ABX, (5) D08 control, (6) D08 ABX, (7) D14 control, (8) D14 ABX). We created an antibody pool consisting of 31 different antibodies (CCR2/CD192, C117/c-kit, CD11b, CD11c, CD172a/SIRPα, CD25, CD3, CD38, CD4, CD44, CD45, CD45R/B220, CD86, CD8a, CD90.1, Cx3cr1, F4/80, I-A/I-E, Ly6C, Ly6G, NK1.1, PD-1, PD-L1, CD169/Siglec-1, Siglec-H, TMEM119, XCR1, CD24, CD103, CD64, CD83) and stained each brain individually with this antibody pool. Then, we stained each brain with it's own unique hashing antibody so that we could subsequently pool samples. Two groups were collapsed into one to generate four samples, each loaded into one well on the 10x Chromium (D00 control + D00 ABX, D04 control + D04 ABX, D08 control + D08 ABX, D14 control + D14 ABX). Sequencing libraries were prepared for each of the four collapsed groups (6 samples per group). Following sequencing, each sample is separated in silico by it's unique hashing antibody.

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Project description:Gut Dysbiosis Impacts Brain Metastasis Outgrowth and Immune Response Dynamics [CITE-seq]

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