Integrated microRNA and mRNA Signatures Associated with Survival in Triple Negative Breast Cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Cascione L
PROVIDER: S-ECPF-GEOD-41970 | biostudies-other | 2013
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways.Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P?=?0.05) and distant-disease free survival (P?=?0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs. Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis.
| S-EPMC3566108 | biostudies-literature
Project description:Triple negative breast cancer (TNBC) includes basal and non-basal subclasses. To further stratify TNBC we determined microRNA (miRNA) and mRNA expression profiles, linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify TNBC subclasses associated with expression of canonical signal pathways RNA was isolated from formalin-fixed paraffin-embedded tissue cores of 165 primary tumors, 59 adjacent normal and 54 lymph node metastatic samples and expression of 664 miRNAs and 230 cancer-associated mRNAs was assessed for each sample using the nanoString nCounter platform. Kaplan-Meier distant-disease free and overall survival curves were compared using the log-rank test. Cox proportional hazard regression and risk score analysis were used to identify miRNAs for classification of patients with significantly different prognoses.
2013-04-19 | E-GEOD-41970 | biostudies-arrayexpress
Project description:Triple negative breast cancer (TNBC) includes basal and non-basal subclasses. To further stratify TNBC we determined microRNA (miRNA) and mRNA expression profiles, linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify TNBC subclasses associated with expression of canonical signal pathways
2013-04-19 | GSE41970 | GEO
Project description:Triple negative breast cancer (TNBC) includes basal and non-basal subclasses. To further stratify TNBC we determined microRNA (miRNA) and mRNA expression profiles, linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify TNBC subclasses associated with expression of canonical signal pathways
2021-02-01 | GSE45498 | GEO
Project description:Ovarian cancer (OC), the eighth-leading cause of cancer-related death among females worldwide, is mainly represented by epithelial OC (EOC) that can be further subdivided into four subtypes: serous (75%), endometrioid (10%), clear cell (10%), and mucinous (3%). Major reasons for high mortality are the poor biological understanding of the OC mechanisms and a lack of reliable markers defining each EOC subtype. MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression primarily by targeting messenger RNA (mRNA) transcripts. Their aberrant expression patterns have been associated with cancer development, including OC. However, the role of miRNAs in tumorigenesis is still to be determined, mainly due to the lack of consensus regarding optimal methodologies for identification and validation of miRNAs and their targets. Several tools for computational target prediction exist, but false interpretations remain a problem. The experimental validation of every potential miRNA-mRNA pair is not feasible, as it is laborious and expensive. In this study, we analyzed the correlation between global miRNA and mRNA expression patterns derived from microarray profiling of 197 EOC patients to identify the signatures of miRNA-mRNA interactions associated with overall survival (OS). The aim was to investigate whether these miRNA-mRNA signatures might have a prognostic value for OS in different subtypes of EOC. The content of our cohort (162 serous carcinomas, 15 endometrioid carcinomas, 11 mucinous carcinomas, and 9 clear cell carcinomas) reflects a real-world scenario of EOC. Several interaction pairs between 6 miRNAs (hsa-miR-126-3p, hsa-miR-223-3p, hsa-miR-23a-5p, hsa-miR-27a-5p, hsa-miR-486-5p, and hsa-miR-506-3p) and 8 mRNAs (ATF3, CH25H, EMP1, HBB, HBEGF, NAMPT, POSTN, and PROCR) were identified and the findings appear to be well supported by the literature. This indicates that our study has a potential to reveal miRNA-mRNA signatures relevant for EOC. Thus, the evaluation on independent cohorts will further evaluate the performance of such findings.
| S-EPMC8318284 | biostudies-literature
Project description:Infectious agents are the third highest human cancer risk factor and may have a greater role in the origin and/or progression of cancers, and related pathogenesis. Thus, knowing the specific viruses and microbial agents associated with a cancer type may provide insights into cause, diagnosis and treatment. We utilized a pan-pathogen array technology to identify the microbial signatures associated with triple negative breast cancer (TNBC). This technology detects low copy number and fragmented genomes extracted from formalin-fixed paraffin embedded archival tissues. The results, validated by PCR and sequencing, define a microbial signature present in TNBC tissue which was underrepresented in normal tissue. Hierarchical clustering analysis displayed two broad microbial signatures, one prevalent in bacteria and parasites and one prevalent in viruses. These signatures demonstrate a new paradigm in our understanding of the link between microorganisms and cancer, as causative or commensal in the tumor microenvironment and provide new diagnostic potential.
| S-EPMC4606812 | biostudies-literature
Project description:Triple-negative breast cancer (TNBC) is a specific type of breast cancer with poor overall survival (OS) time. Previous studies revealed that microRNAs (miRNAs/miRs) serve important roles in the pathogenesis, progression and prognosis of TNBC. The present study analyzed the miRNA expression and clinical data of patients with TNBC downloaded from The Cancer Genome Atlas. A total of 194 differentially expressed miRNAs were identified between TNBC and matched normal tissues using the cut-off criteria of P<0.05 and |log2 fold change|>2. Of these miRNAs, 65 were downregulated and 129 were upregulated. Using Kaplan-Meier survival analysis, a total of 77 miRNAs that were closely associated with OS time were identified (P<0.05). The intersection of the 77 miRNAs and 194 differentially expressed miRNAs revealed six miRNAs. Log-rank tests based on survival curves were performed and two miRNAs were eliminated. The prognostic value of the remaining four miRNAs was evaluated with a Cox proportional hazards model using multiple logistic regression with forward stepwise selection of variables. Three miRNAs (miR-21-3p, miR-659-5p and miR-200b-5p) were subsequently identified as independent risk factors associated with OS time in the model. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed that the target genes of these three miRNAs were mainly involved in 'cell protein metabolism', 'RNA transcriptional regulation', 'cell migration', 'MAPK signaling pathway', 'ErbB signaling pathway', 'prolactin signaling pathway' and 'adherens junctions'. Taken together, the results obtained in the present study suggested that the three-miRNA signature may serve as a prognostic biomarker for patients with TNBC.
| S-EPMC6923981 | biostudies-literature
Project description:Triple negative breast cancer (TNBC) is a type of breast cancer where the tumor cells are negative for the estrogen, progesterone and human epidermal growth factor 2 receptors. To date, expression profiling of microRNA (miRNA/miR) and mRNA sequences have been widely applied for the diagnosis of TNBC. In the present study, an integrated analysis of miRNA‑mRNA profiling arrays was performed. A total of five dysregulated miRNAs in patients with TNBC were identified, including upregulated miR‑558 expression and downregulated miR‑320d‑1, miR‑548v, miR‑99a and miR‑21 expression. In addition, 49 potential target mRNA sequences were identified. Bioinformatics analyses were performed on the identified miRNAs and mRNAs, including gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes pathway and miRNA‑mRNA network analyses. A total of 31 GO terms and three signaling pathways were identified. The results indicated that the differentially expressed miRNAs and their potential target mRNAs may affect the pathogenesis of TNBC, and may therefore be considered as promising biomarkers for the early diagnosis and targeted therapy of patients with TNBC.
| S-EPMC5561991 | biostudies-literature
Project description:Antimicrobial exposure during curative-intent treatment of triple-negative breast cancer (TNBC) may lead to gut microbiome dysbiosis, decreased circulating and tumor-infiltrating lymphocytes, and inferior outcomes. Here, we investigate the association of antimicrobial exposure and peripheral lymphocyte count during TNBC treatment with survival, using integrated electronic medical record and California Cancer Registry data in the Oncoshare database. Of 772 women with stage I-III TNBC treated with and without standard cytotoxic chemotherapy - prior to the immune checkpoint inhibitor era - most (654, 85%) used antimicrobials. Applying multivariate analyses, we show that each additional total or unique monthly antimicrobial prescription is associated with inferior overall and breast cancer-specific survival. This antimicrobial-mortality association is independent of changes in neutrophil count, is unrelated to disease severity, and is sustained through year three following diagnosis, suggesting antimicrobial exposure negatively impacts TNBC survival. These results may inform mechanistic studies and antimicrobial prescribing decisions in TNBC and other hormone receptor-independent cancers.
| S-EPMC10097670 | biostudies-literature
Project description:Background and objectiveBiomarkers for subtyping triple negative breast cancer (TNBC) are needed given the absence of responsive therapy and relatively poor prediction of survival. Morphology of cancer tissues is widely used in clinical practice for stratifying cancer patients, while genomic data are highly effective to classify cancer patients into subgroups. Thus integration of both morphological and genomic data is a promising approach in discovering new biomarkers for cancer outcome prediction. Here we propose a workflow for analyzing histopathological images and integrate them with genomic data for discovering biomarkers for TNBC.Materials and methodsWe developed an image analysis workflow for extracting a large collection of morphological features and deployed the same on histological images from The Cancer Genome Atlas (TCGA) TNBC samples during the discovery phase (n=44). Strong correlations between salient morphological features and gene expression profiles from the same patients were identified. We then evaluated the same morphological features in predicting survival using a local TNBC cohort (n=143). We further tested the predictive power on patient prognosis of correlated gene clusters using two other public gene expression datasets.Results and conclusionUsing TCGA data, we identified 48 pairs of significantly correlated morphological features and gene clusters; four morphological features were able to separate the local cohort with significantly different survival outcomes. Gene clusters correlated with these four morphological features further proved to be effective in predicting patient survival using multiple public gene expression datasets. These results suggest the efficacy of our workflow and demonstrate that integrative analysis holds promise for discovering biomarkers of complex diseases.
| S-EPMC3721170 | biostudies-literature