Project description:Circulating microRNAs (c-miRNAs) have emerged as measurable biomarkers (liquid biopsies) for cancer detection. The goal of our study was to identify novel biomarkers to predict long-term breast cancer risk in cancer-free women. We evaluated the ability of c-miRNAs to identify women most likely to develop breast cancer by profiling miRNA from serum obtained long before diagnosis. 24 breast cancer cases and controls (matched for risk and age) were identified from women enrolled in the High-Risk Breast Program at the UVM Cancer Center. We used Affymetrix miRNA v4 microarrays to interrogate miRNAs (miRBase v20) in the serum of cancer-free women at high-risk for breast cancer. The 24 cases developed breast cancer at least 6 months (average of 3.2 years) and the 24 controls remain cancer-free.
Project description:This dataset consists of miRNA expression in plasma of 78 women with germline BRCA1/2 mutations and expression in serum of 11 of them. Serum samples of remaining 67 women have been already submitted to GEO in GSE226445 dataset and to SRA as Bioproject PRJNA898621, while counts generated in re-mapping for this project are deposited as GSE299846 data set. MicroRNA abundance was quantified with sequencing in both biological materials. Data was analyzed with the aim of assessing the impact of blood processing steps on quantified miRNA abundance. Generation of this dataset was supported by The Gray Foundation grant “Circulating microRNAs for assessment of risk beyond the BRCA genes and early detection of breast cancer in high-risk families” awarded to Dipanjan Chowdhury and Polish National Research Center grant OPUS “Predictive Potential of Circulating MicroRNA Biomarkers in Patients with High Familial or Genetic Risk of Cancer” (2023/49/B/NZ5/03835) awarded to Wojciech Fendler.
Project description:This dataset contains serum miRNA expression of 94 healthy women, among which 56 harbored germline BRCA1 or BRCA2 mutations. MicroRNA abundance was quantified with sequencing and qPCR, the latter being the subject of separate GEO submission. Data was analyzed with the aim of assessing concordance between two miRNA assays and the possibility of translating miRNA biomarkers from sequencing to qPCR panel. Generation of this dataset was supported by The Gray Foundation grant “Circulating microRNAs for assessment of risk beyond the BRCA genes and early detection of breast cancer in high-risk families” awarded to Dipanjan Chowdhury and Polish National Research Center grant OPUS “Predictive Potential of Circulating MicroRNA Biomarkers in Patients with High Familial or Genetic Risk of Cancer” (2023/49/B/NZ5/03835) awarded to Wojciech Fendler.
Project description:This dataset consists of miRNA expression in serum of 69 women. This data is the result of remapping raw sequencing FASTQ files being a part of the GSE226445 dataset and the SRA Bioproject PRJNA898621. MicroRNA abundance was quantified by sequencing. Data was analyzed together with plasma samples of those same patients with the aim of assessing the impact of blood processing steps on quantified miRNA abundance. Plasma data belongs to a separate submission (accession will be added when issued). Generation of this dataset was supported by The Gray Foundation grant “Circulating microRNAs for assessment of risk beyond the BRCA genes and early detection of breast cancer in high-risk families” awarded to Dipanjan Chowdhury and Polish National Research Center grant OPUS “Predictive Potential of Circulating MicroRNA Biomarkers in Patients with High Familial or Genetic Risk of Cancer” (2023/49/B/NZ5/03835) awarded to Wojciech Fendler.
Project description:This dataset was created in order to evaluate the concordance of miRNA expression between serum and plasma in humans. miRNA expression was quantified in both biological materials using sequencing. Differential expression and correlations analysis were used to evaluate similarities and differences between miRNAs abundance in plasma and serum. Concurrently, miRNA quantification in the subset of these samples was performed by qPCR, the results of which belong to the separate submission to GEO. Generation of this dataset was supported by The Gray Foundation grant “Circulating microRNAs for assessment of risk beyond the BRCA genes and early detection of breast cancer in high-risk families” awarded to Dipanjan Chowdhury and Polish National Research Center grant OPUS “Predictive Potential of Circulating MicroRNA Biomarkers in Patients with High Familial or Genetic Risk of Cancer” (2023/49/B/NZ5/03835) awarded to Wojciech Fendler.
Project description:microRNAs are small, non-coding, single-stranded RNAs between 18-22 nucleotides long that regulate gene expression. Expression of microRNAs is altered in tumor compared to normal tissue; there is some evidence that these changes may be reflected in the serum of cancer cases compared to healthy individuals. This has yet to be examined in a prospective study where samples are collected before diagnosis. We used Affymetrix arrays to examine serum miRNA expression profiles in 410 participants in the Sister Study, a prospective cohort study of 50,884 women. All women in the cohort had never been diagnosed with breast cancer at the time of enrollment. We compared global miRNA expression patterns in 205 women who subsequently developed breast cancer and 205 women who remained breast cancer-free.
Project description:Introduction: Circulating microRNAs (miRNAs) exhibit remarkable stability and may serve as biomarkers in several clinical cancer settings. The aim of this study was to investigate changes in the levels of specific circulating miRNA following breast cancer surgery and evaluate whether these alterations were also observed in an independent data set. Methods: Global miRNA analysis was performed on prospectively collected serum samples from 24 post-menopausal women with estrogen receptor-positive early-stage breast cancer before surgery and 3 weeks after tumor resection using global LNA-based quantitative real-time PCR (qPCR). Results: Numbers of specific miRNAs detected in the samples ranged from 142 to 161, with 107 miRNAs detectable in all samples. After correction for multiple comparisons, 3 circulating miRNAs (miR-338-3p, miR-223 and miR-148a) exhibited significantly lower, and 1 miRNA (miR-107) higher levels in post-operative vs. pre-operative samples (p<0.05). No miRNAs were consistently undetectable in the post-operative samples compared to the pre-operative samples. Subsequently, our findings were compared to a dataset from a comparable patient population analyzed using similar study design and the same qPCR profiling platform, resulting in limited agreement. Conclusions: A panel of 4 circulating miRNAs exhibited significantly altered levels following radical resection of primary ER+ breast cancers in post-menopausal women. These specific miRNAs may be involved in tumorigenesis and could potentially be used to monitor whether all cancer cells have been removed at surgery and/or, subsequently, whether the patients develop recurrence. 48 serum samples were prospectively collected from 24 patients with early stage breast cancer before and after surgery at Odense University Hospital. Serum was prepared within one hour of sample collection after centrifugation (2000 x g; 10 min at 20 M-BM-:C) and immediately stored at -80 M-BM-:C.
Project description:Serum samples from 94 healthy women were analyzed using a custom qPCR panel comprising 182 miRNAs. Since this experiment is part of a broader study on miRnome alterations associated with BRCA mutations or BRCA-related cancers (particularly ovarian and breast cancer), 37 of the analyzed samples came from patients with BRCA1 mutations and 19 from BRCA2 mutation carriers. This analysis was preceded by sequencing-based quantification on the same set of the samples, the results of which are submitted separately to GEO under accession number GSE299787. The generation of this dataset was supported by The Gray Foundation grant “Circulating microRNAs for assessment of risk beyond the BRCA genes and early detection of breast cancer in high-risk families” awarded to Dipanjan Chowdhury, and by the National Science Centre (Poland) OPUS grant “Predictive Potential of Circulating MicroRNA Biomarkers in Patients with High Familial or Genetic Risk of Cancer” (2023/49/B/NZ5/03835) awarded to Wojciech Fendler.
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.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000642.
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BioModels Database:
An enhanced, curated and annotated resource for published
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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.