Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1246533 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR32974325_1.fastq.gz | Fastqsanger.gz | |||
| SRR32974325_2.fastq.gz | Fastqsanger.gz | |||
| SRR32974326_1.fastq.gz | Fastqsanger.gz | |||
| SRR32974326_2.fastq.gz | Fastqsanger.gz |
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Project description:Breastfeeding protects against breast cancer in some women but not others, however the mechanism remains elusive. Lactation requires intense secretory activity of the endoplasmic reticulum (ER) for the production of milk proteins and ER- mitochondria contacts for lipid synthesis. We show that in female mice that share the same nuclear genome (BL/6) but differ in mitochondrial genomes (C57 or NZB), the biological processes engaged during lactation are entirely different at the sub-cellular organization and transcriptional levels resulting in anti-tumorigenic lactation in BL/6C57 females and pro-tumorigenic lactation in BL/6NZB females. Single cell sequencing identified a sub-population of cells, uniquely amplified during lactation in BL/6NZB females, which shares the genetic signature that characterizes post-partum breast cancer (PPBC) in humans relative to matched breast cancers in never pregnant women. Our data indicate that differences in ER and mitochondrial-stress responses during lactation between genotypes inadvertently leads to loss of p53 tumor suppressor function in BL/6NZB females allowing the expansion of the PPBC-like sub-population of cells. Overall, our data reveals the unexpected idiosyncratic nature of lactation and its impacts on the risk of the development of PPBC.
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Project description:Breast cancer risk is influenced by parity in an age-dependant manner, however human tissue remodelling induced by pregnancy and lactation is not well understood. In most cases, it is difficult to acquire human breast tissue during these key stages of development. Here, we present an approach to overcome this using single-cell RNA sequencing to examine viable primary mammary epithelial cells isolated from human milk (n=4) compared to resting, non-lactating human breast tissue (n=4). Overall, we examined 54,323 viable high-quality cells from mixed age and parous individuals consisting of 29,078 lactation derived mammary cells (LMCs) and 25,245 non-lactation derived mammary cells (NMCs). We identified all documented mammary subpopulations within our breast tissue samples and found that milk contains distinct secretory luminal cells together with myeloid and lymphocytic hematopoietic lineage cells. Comparing the luminal transcriptional profiles of cells isolated from the resting and lactating state identified differences in mammary cell function and metabolism between these maturation states. In future this data may be used to provide an insight into how parity influences human luminal cell metabolism and breast cancer risk.
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Project description:Breastfeeding protects against breast cancer, but not in all women and the mechanism remains elusive. Lactation implicates secretion of proteins through the endoplasmic reticulum (ER) and ER- mitochondria contacts for lipid metabolism. We show that in mice that share the same nuclear genome (BL/6) but differ in mitochondrial genomes (C57 or NZB) the outcome of lactation differs drastically. We analyzed the unfolded protein responses (UPR) of both organelles during lactation. In contrast to the BL/6C57mice, in BL/6NZB females, UPRs signaling is abruptly inhibited, no apoptosis is observed, post-partum hyperplasia develops and RNAseq demonstrates expression of pro-tumorigenic genes, which is consistent with increased post-partum tumor development. However, forced-induction of pro-apoptotic UPRER reverses this phenotype. Remarkably, milk fatty acids (FA) differ between genotypes and correlate with breast cancer risk in humans. These results indicate that mitochondrial genetics modulates organellar responses to lactation and its protective effect. Our results further raise the possibility of using milk FA-signature as a read-out of the underlying biology to predict risk of breast cancer in the future.
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Project description:Mufudza2012 - Estrogen effect on the dynamics
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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.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000642.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2024-09-02 | BIOMD0000000642 | BioModels
Project description:Genome-wide association studies (GWASs) have identified thousands of single nucleotide polymorphisms (SNPs) associated with human traits and diseases. But because the vast majority of these SNPs are located in the noncoding regions of the genome their risk promoting mechanisms are elusive. Employing a new methodology combining cistromics, epigenomics and genotype imputation we annotate the noncoding regions of the genome in breast cancer cells and systematically identify the functional nature of SNPs associated with breast cancer risk. Our results demonstrate that breast cancer risk-associated SNPs are enriched in the cistromes of FOXA1 and ESR1 and the epigenome of H3K4me1 in a cancer and cell-type-specific manner. Furthermore, the majority of these risk-associated SNPs modulate the affinity of chromatin for FOXA1 at distal regulatory elements, which results in allele-specific gene expression, exemplified by the effect of the rs4784227 SNP on the TOX3 gene found within the 16q12.1 risk locus.
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Project description:Breast cancer risk is influenced by parity in an age-dependant manner, however human tissue remodelling induced by pregnancy and lactation is not well understood. In most cases, it is difficult to acquire human breast tissue during these key stages of development. Here, we present an approach to overcome this using single-cell RNA sequencing to examine viable primary mammary epithelial cells isolated from human milk (n=5, LMC) compared to resting, non-lactating human breast tissue (n=3, NMC). We identified all documented mammary subpopulations within our breast tissue samples and found that milk contains distinct secretory luminal cells together with myeloid and lymphocytic lineage cells. Comparing the luminal transcriptional profiles of cells isolated from the resting and lactating state identified differences in mammary cell function and metabolism between these maturation states. This data may be used to provide an insight into how parity influences human luminal cell metabolism and breast cancer risk.
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Project description:Breast cancer risk is influenced by parity in an age-dependant manner, however human tissue remodelling induced by pregnancy and lactation is not well understood. In most cases, it is difficult to acquire human breast tissue during these key stages of development. Here, we present an approach to overcome this using single-cell RNA sequencing to examine viable primary mammary epithelial cells isolated from human milk (n=1, LMC) compared to resting, non-lactating human breast tissue (n=1, NMC, ran over 3 lanes of a 10x Genomics chip). We identified all documented mammary subpopulations within our breast tissue samples and found that milk contains distinct secretory luminal cells together with myeloid and lymphocytic hematopoietic lineage cells. Comparing the luminal transcriptional profiles of cells isolated from the resting and lactating state identified differences in mammary cell function and metabolism between these maturation states. This data may be used to provide an insight into how parity influences human luminal cell metabolism and breast cancer risk.
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