Breast Cancer - immune clusters - RNA-seq
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA558331 | ENA |
REPOSITORIES: ENA
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Project description:In this study we use expression data from breast cancer tumors to define immune clusters in breast cancer.
Immune clusters have gradual levels of immune infiltration. In the intermediate immune infiltration cluster, we found a worse prognosis which is independent of known clinicopathological features. We also found the immune clusters associated with treatment response. Further using gene expression data and deconvolution algorithms to dissect the immune contexture of the clusters.
| EGAS00001003631 | EGA
Project description:We use expression data from breast cancer tumors to define immune clusters in breast cancer. Immune clusters have gradual levels of immune infiltration. In the intermediate immune infiltration cluster, we found a worse prognosis which is independent of known clinicopathological features. We also found the immune clusters associated with treatment response. Further we use gene expression data and deconvolution algorithms to dissect the immune contexture of the clusters.
2019-12-10 | GSE135298 | GEO
Project description:Clusters of circulating tumor cells (CTC-clusters) are present in the blood of patients with cancer but their contribution to metastasis is not well defined. Here, we first use mouse models to demonstrate that breast cancer cells injected intravascularly as clusters are more prone to survive and colonize the lungs than single cells. Primary mammary tumors comprised of tagged cells give rise to oligoclonal CTC-clusters, with 50-fold increased metastatic potential, compared with single CTCs. Using intravital imaging and in vivo flow cytometry, CTC-clusters are visualized in the tumor circulation, and they demonstrate rapid clearance in peripheral vessels. In patients with breast cancer, presence of CTC-clusters is correlated with decreased progression-free survival. RNA sequencing identifies the cell junction protein plakoglobin as most differentially expressed between clusters and single human breast CTCs. Expression of plakoglobin is required for efficient CTC-cluster formation and breast cancer metastasis in mice, while its expression is associated with diminished metastasis-free survival in breast cancer patients. Together, these observations suggest that plakoglobin-enriched primary tumor cells break off into the vasculature as CTC-clusters, with greatly enhanced metastasis propensity. RNA-seq from 29 samples (15 pools of single CTCs and 14 CTC-clusters) isolated from 10 breast cancer patients
2014-07-11 | E-GEOD-51827 | biostudies-arrayexpress
Project description:Clusters of circulating tumor cells (CTC-clusters) are present in the blood of patients with cancer but their contribution to metastasis is not well defined. Here, we first use mouse models to demonstrate that breast cancer cells injected intravascularly as clusters are more prone to survive and colonize the lungs than single cells. Primary mammary tumors comprised of tagged cells give rise to oligoclonal CTC-clusters, with 50-fold increased metastatic potential, compared with single CTCs. Using intravital imaging and in vivo flow cytometry, CTC-clusters are visualized in the tumor circulation, and they demonstrate rapid clearance in peripheral vessels. In patients with breast cancer, presence of CTC-clusters is correlated with decreased progression-free survival. RNA sequencing identifies the cell junction protein plakoglobin as most differentially expressed between clusters and single human breast CTCs. Expression of plakoglobin is required for efficient CTC-cluster formation and breast cancer metastasis in mice, while its expression is associated with diminished metastasis-free survival in breast cancer patients. Together, these observations suggest that plakoglobin-enriched primary tumor cells break off into the vasculature as CTC-clusters, with greatly enhanced metastasis propensity.
2014-07-11 | GSE51827 | GEO
Project description:Circulating Cancer-Associated Fibroblasts (cCAFs) have been discovered in circulating tumor cell clusters from all stages of disease progression in breast cancer patients. As the most abundant non-cancerous cell type in the tumor microenvironment (TME), CAFs impart many of the tumor promoting functions defined by the hallmarks of cancer such as: proliferation, invasion, migration, metastasis, stemness, immunosuppression, altered cancer cell metabolism, and drug resistance. Human primary CAF cell lines can form co-clusters in vitro with human breast cancer cells when grown in ultra-low attachment conditions. We have previously used these co-clusters to show that they promote metastasis in the mouse tail vein model. In this study, we seek to understand the cross-talk that occurs between CAFs and TNBC cells when they are present in heterotypic co-clusters compared to TNBC monoclusters or CAF monoclusters. We created samples of mono-clusters and co-clusters grown in 3D conditions for 48 hrs, then disrupted the clusters into a single cell suspension, and subsequently processed them for Single-cell RNA sequencing. Comparisons of breast cancer cells grown as mono-clusters versus co-clusters revealed differentially expressed genes (DEGs) that are up and down regulated in the presence of CAFs. Integration Pathway Analysis and Gene Ontology analysis revealed that CAFs increase expression of several components of the fibrinolysis pathway in breast cancer cells, such as uPA/PLAU and SERPINE1. Upstream regulators identified included TGFbeta. We also looked at DEGs in CAFs when in co-clusters versus mono-clusters and found that when in co-clusters, CAFs become even more CAF-like with the upregulation of genes such as collagens, integrins, and FN1. This study provided us with candidates to study in the process of CAF-mediated breast cancer cell extravasation, such as uPA/PLAU. Pathways identified support our conclusions that circulating CAFs are important players in the metastatic process.
2025-06-25 | GSE300584 | GEO
Project description:Myocardial Infarction accelerates breast cancer via innate immune reprogramming (RNA-seq)
| PRJNA558550 | ENA
Project description:RNA-seq was performed on breast cancer cell lines and primary tumors RNA-seq was performed on 28 breast cancer cell lines, 42 Triple Negative Breast Cancer (TNBC) primary tumors, and 42 Estrogen Receptor Positive (ER+) and HER2 Negative Breast Cancer primary tumors, 30 uninovlved breast tissue samples that were adjacent to ER+ primary tumors, 5 breast tissue samples from reduction mammoplasty procedures performed on patients with no known cancer, and 21 uninvolved breast tissue samples that were adjacent to TNBC primary tumors.
2014-06-11 | E-GEOD-58135 | biostudies-arrayexpress
Project description:Breast cancer development model
2020-10-08 | 627 | FAIRDOMHub
Project description:Immunotherapy is applied to breast cancer to resolve the limitations of survival gain in existing treatment modalities. With immunotherapy, a tumor can be classified into immune-inflamed, excluded and desert based on the distribution of immune cells. We assessed the clinicopathological features, each subtype’s prognostic value and differentially expressed proteins between immune subtypes.
2024-06-16 | PXD043902 | Pride
Project description:Mufudza2012 - Estrogen effect on the dynamics
of breast cancer
This deterministic model shows the
dynamics of breast cancer with immune response. The effects of
estrogen are incorporated to study its effects as a risk factor for
the disease.
This model is described in the article:
Assessing the effects of
estrogen on the dynamics of breast cancer.
Mufudza C, Sorofa W, Chiyaka
ET.
Comput Math Methods Med 2012; 2012:
473572
Abstract:
Worldwide, breast cancer has become the second most common
cancer in women. The disease has currently been named the most
deadly cancer in women but little is known on what causes the
disease. We present the effects of estrogen as a risk factor on
the dynamics of breast cancer. We develop a deterministic
mathematical model showing general dynamics of breast cancer
with immune response. This is a four-population model that
includes tumor cells, host cells, immune cells, and estrogen.
The effects of estrogen are then incorporated in the model. The
results show that the presence of extra estrogen increases the
risk of developing breast cancer.
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BIOMD0000000642.
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2024-09-02 | BIOMD0000000642 | BioModels