Small noncoding RNA levels in plasma from breast cancer patients and healthy controls
Ontology highlight
ABSTRACT:
ORGANISM(S): synthetic construct Homo sapiens
PROVIDER: GSE118782 | GEO | 2019/08/31
REPOSITORIES: GEO
Similar Datasets
Project description:Small noncoding RNA levels in plasma from breast cancer patients and healthy controls
| PRJNA486792 | ENA
Project description:1. Evaluate the diagnostic value of long noncoding RNA (CCAT1) expression by RT-PCR in peripheral blood in colorectal cancer patients versus normal healthy control personal.
2. Evaluate the clinical utility of detecting long noncoding RNA (CCAT1) expression in diagnosis of colorectal cancer patients & its relation to tumor staging.
3. Evaluate the clinical utility of detecting long noncoding RNA (CCAT1) expression in precancerous colorectal diseases.
4. Compare long noncoding RNA (CCAT1) expression with traditional marker; carcinoembryonic antigen (CEA) and Carbohydrate antigen 19-9 (CA19-9) in diagnosis of colorectal cancer.
| 2330122 | ecrin-mdr-crc
Project description:Breast Cancer is the cancer with most incidence and mortality in women. microRNAs are emerging as novel prognosis/diagnostic tools. Our aim was to identify a serum microRNA signature useful to predict cancer development. We focused on studying the expression levels of 30 microRNAs in the serum of 96 breast cancer patients versus 92 control individuals. Bioinformatic studies provide a microRNA signature, designated as a predictor, based upon the expression levels of 5 microRNAs. Then, we tested the predictor in a group of 60 randomly chosen women. Lastly, a proteomic study unveiled the over-expression and down-regulation of proteins differently expressed in the serum of breast cancer patients versus that of control individuals. Twenty-six microRNAs differentiate cancer tissue from healthy tissue and 16 microRNAs differentiate the serum of cancer patients from that of the control group. The tissue expression of miR-99a-5p, mir-497-5p, miR-362, and miR-1274, and the serum levels of miR-141 correlated with patient survival. Moreover, the predictor consisting of mir-125b-5p, miR-29c-3p, mir-16-5p, miR-1260, and miR-451a was able to differentiate breast cancer patients from controls. The predictor was validated in 20 new cases of breast cancer patients and tested in 60 volunteer women, assigning 11 out of 60 women to the cancer group. An association of low levels of mir-16-5p with a high content of CD44 protein in serum was found. Circulating microRNAs in serum can represent biomarkers for cancer prediction. Their clinical relevance and use of the predictor here described might be of potential importance for breast cancer prediction.
2020-09-18 | PXD020795 | Pride
Project description:We analyzed gene expression in human peripheral blood mononuclear cells (PBMCs) from breast cancer patients, patients with benign breast abnormalities, healthy cancer-free individuals as well as patients with other types of cancer (gastrointestinal and brain cancers). Peripheral blood mononuclear cell (PBMC) samples were collected from women with a suspect initial mammogram prior to undergoing a diagnostic biopsy procedure to determine whether the detected abnormality was benign or malignant. In total, we collected blood from 57 women with a diagnosis of breast cancer and 37 with a benign diagnosis. We also collected blood from 31 women with normal initial mammograms as negative controls and 15 breast cancer patients following surgery. All breast cancer patient samples were collected at the Duke University Medical Center (DUMC) under an institutional review board (IRB)-approved protocol (Duke eIRB#12025) after obtaining informed consent and were provided by Dr. Jeffrey Marks. PBMC samples from patients with various gastrointestinal cancers (n=15) were colelcted and stored at DUMC under IRB-approved protocols (Duke eIRB#12010 and 12025) and were provided by Dr. Jeffrey Marks. Peripheral blood leukocyte samples from patients with brain tumors (n=7) were provided by Dr. John Sampson and were collected by leukapheresis under Duke eIRB#00003877 and #00009403.
2011-03-01 | E-GEOD-27562 | biostudies-arrayexpress
Project description:Mammographic breast cancer screening is effective in reducing breast cancer mortality. Nevertheless, several limitations are known. The objective of this study was to identify circulating microRNAs (miRs) ratios associated with BC in women attending mammography screening. A nested case-control study was conducted within the ANDROMEDA cohort (women of age 46-67 attending BC screening in northern Italy), where pre-diagnostic plasma samples, information on life-styles and common BC risk factors were collected. Small RNA sequencing was carried out on plasma samples from 65 cases and 66 controls. miR-ratios associated with BC were selected by two-sample Wilcoxon test and lasso logistic regression. Subsequent assessment by RT-qPCR of the miRs contained in the selected miR-ratios was carried out as a platform validation. Penalized logistic regression was further applied to candidate miR-ratios alone, or in combination with non-molecular factors, to build a diagnostic model.
2023-07-26 | GSE210329 | GEO
Project description:Long noncoding RNA landscape in breast cancer [Mexico]
| PRJNA554862 | ENA
Project description:The pathophysiology of fulminant myocarditis (FM) is significantly influenced by the interactions between immunological and myocardial cells, involving exosome-mediated intercellular microRNA (miRNA) signaling. To further investigate the pathogenesis of FM and discover diagnostic biomarkers, we have employed miRNA microarray expression profiling as a discovery platform.
2023-05-02 | GSE221090 | GEO
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.
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.
2017-07-26 | BIOMD0000000642 | BioModels
Project description:Five years of tamoxifen reduces breast cancer risk by nearly 50% but is associated with significant side-effects and toxicities. A better understanding of the direct and indirect effects of tamoxifen in benign breast tissue could elucidate new mechanisms of breast carcinogenesis, suggest novel chemoprevention targets, and provide relevant early response biomarkers for Phase II prevention trials. Seventy-three women at increased risk for breast cancer were randomized to tamoxifen (20 mg daily) or placebo for three months. Blood and breast tissue samples were collected at baseline and post-treatment. Sixty-nine women completed all study activities (37 tamoxifen and 32 placebo). The selected biomarkers focused on estradiol and IGFs in the blood, DNA methylation and cytology in random periareolar fine needle aspirates, and tissue morphometry, proliferation, apoptosis, and gene expression (microarray and RT-PCR) in the tissue core samples. Tamoxifen downregulated ets-oncogene family members ETV4 and ETV5 and reduced breast epithelial cell proliferation independent of CYP2D6 genotypes or effects on estradiol, ESR1 or IGFs. Reduction in proliferation was correlated with downregulation of ETV4 and DNAJC12. Tamoxifen also modulated expression of RAB GTPases, and several genes involved in epithelial-stromal interaction, and reduced tumor suppressor gene methylation. Three months of tamoxifen did not affect breast tissue composition, cytological atypia, preneoplasia or apoptosis. Tamoxifen may durably reduce breast cancer risk through downregulation of ETV4 and ETV5 which could deplete mammary progenitor populations. This pathway has the potential to provide novel targets and early response biomarkers for phase II prevention trials. Randomized prospective double blinded placebo-controlled trial of tamoxifen (20 mg daily) versus placeo in women at increased risk for breast cancer. Gene expression was assessed in whole breast tissue cores obtained at baseline and after three months of treatment for 35 women. Core biopsies were obtained in the late luteal phase (day 28 +/- 2) for premenopausal women (N = 19). Breast lobules from the baseline and post-treatment cores were microdissected for 5 tamoxifen subjects.
2011-07-21 | E-GEOD-29338 | biostudies-arrayexpress
Project description:Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer among women worldwide. It is confirmed mainly by fine-needle aspiration biopsy (FNAB), an invasive diagnostic method. The key proteins responsible for thyroid hormone biosynthesis are glycosylated. Changes in site-specific glycosylation are associated with thyroid cancer. Integrated quantitative proteomic and glycoproteomic analyses of body fluids from patients with PTC may identify potential noninvasive biomarkers, improve diagnostic accuracy, and elucidate the basic mechanisms of tumor development. In the present study, we demonstrated a novel integrated method of body fluid proteome and glycoproteome analysis. We showed that it is highly reproducible and fast. It may also quantitatively profile protein glycosylation. Intact N-glycopeptides from the urine and plasma of healthy controls (HC), PTC, and PTC with Hashimoto’s thyroiditis (PHT) were enriched by hydrophilic interaction liquid chromatography. Sialic acid was removed from the N-glycopeptides with trifluoroacetic acid and heat. The desialo-N-glycopeptides were analyzed by HCD-MS/MS using stepped collision energies and several search engines for quantitative profiling. Ninety-two altered proteins and 134 intact N-glycopeptides were isolated from the plasma and urine samples of the three groups (90 samples from 15 subjects). To the best of our knowledge, this study is the first to compare the plasma and urinary proteomes and glycoproteomes of HC, PTC, and PHT. Moreover, we revealed a novel indicator (ratio of fucosylated to non-fucosylated N-glycopeptide or F/NF) through desialo-N-glycopeptide analysis. These differently expressed glycoproteins and F/NF may serve as biomarkers contributing to clinical cancer diagnostics and could be used to improve diagnostic accuracy noninvasively.
2019-12-09 | PXD015360 | Pride