Project description:We have assayed differential miRNA expression between late stage (stage IV) metastatic Her2+ and Her2- breast cancer. 4 late stage metastatic Her2- samples were compared to 3 late stage metastatic Her2+ samples. There are 4 within array replicates for each sample.
Project description:Background MicroRNA expression is frequently dysregulated in cancer and it could be used potentially as a disease classifier and a prognostic tool in cancer. It has been reported that the cancer associated specific microRNAs were stably detected in blood. The objective of this study was to discover a panel of circulating microRNAs as potential ER+/HER2- breast cancer biomarkers. Methods We compared levels of circulating microRNAs in blood samples from 11 ER+/HER2- advanced breast cancer patients with age-matched 5 control subjects by using microarray-based expression profiling. We validated the level of microRNAs by real-time quantitative polymerase cycle reaction (RT-qPCR) in 40 control subjects, 180 early breast cancer patients (EBC), and 52 metastatic breast cancer patients (MBC). Then, we assessed the association between the levels of microRNA and clinical outcomes of ER+/HER2- metastatic breast cancer. Background MicroRNA expression is frequently dysregulated in cancer and it could be used potentially as a disease classifier and a prognostic tool in cancer. It has been reported that the cancer associated specific microRNAs were stably detected in blood. The objective of this study was to discover a panel of circulating microRNAs as potential ER+/HER2- breast cancer biomarkers. Methods We compared levels of circulating microRNAs in blood samples from 11 ER+/HER2- advanced breast cancer patients with age-matched 5 control subjects by using microarray-based expression profiling. We validated the level of microRNAs by real-time quantitative polymerase cycle reaction (RT-qPCR) in 40 control subjects, 180 early breast cancer patients (EBC), and 52 metastatic breast cancer patients (MBC). Then, we assessed the association between the levels of microRNA and clinical outcomes of ER+/HER2- metastatic breast cancer. Controls: 5 cases; ER +/HER2- breast cancer patients : 11 cases
Project description:Disseminated cancer cells reside in the lung alveolar niche where they are exposed to interactions with alveolar macrophages. Here we report singe-cell RNA-sequencing data of lung macrophages from MMTV-HER2 mice at the early stage (16-weeks) harboring single dormant cancer cells and late stage mice (32-weeks harboring metastatic lesions, as well as wildtype control mice. We discovered alveolar macrophage and interstitial macrophage subsets that change in expression profile and frequency between stages. We find majority of the AMs are homeostatic in phenotype, and emergence of inflammatory AM subsets in late-stage MMTV-HER2 mice.
Project description:Background MicroRNA expression is frequently dysregulated in cancer and it could be used potentially as a disease classifier and a prognostic tool in cancer. It has been reported that the cancer associated specific microRNAs were stably detected in blood. The objective of this study was to discover a panel of circulating microRNAs as potential ER+/HER2- breast cancer biomarkers. Methods We compared levels of circulating microRNAs in blood samples from 11 ER+/HER2- advanced breast cancer patients with age-matched 5 control subjects by using microarray-based expression profiling. We validated the level of microRNAs by real-time quantitative polymerase cycle reaction (RT-qPCR) in 40 control subjects, 180 early breast cancer patients (EBC), and 52 metastatic breast cancer patients (MBC). Then, we assessed the association between the levels of microRNA and clinical outcomes of ER+/HER2- metastatic breast cancer. Background MicroRNA expression is frequently dysregulated in cancer and it could be used potentially as a disease classifier and a prognostic tool in cancer. It has been reported that the cancer associated specific microRNAs were stably detected in blood. The objective of this study was to discover a panel of circulating microRNAs as potential ER+/HER2- breast cancer biomarkers. Methods We compared levels of circulating microRNAs in blood samples from 11 ER+/HER2- advanced breast cancer patients with age-matched 5 control subjects by using microarray-based expression profiling. We validated the level of microRNAs by real-time quantitative polymerase cycle reaction (RT-qPCR) in 40 control subjects, 180 early breast cancer patients (EBC), and 52 metastatic breast cancer patients (MBC). Then, we assessed the association between the levels of microRNA and clinical outcomes of ER+/HER2- metastatic breast cancer.
Project description:To investigate transcriptomic changes during development of resistance to lapatinib in a HER2+ breast cancer cell line We performed gene expression profiling analysis using data obtained from RNA-seq of 4 different stage of development of lapatinib resistance in a HER2+ breast cancer cell line
Project description:Breast cancer is a heterogeneous disease encompassing a number of phenotypically diverse tumours. Expression levels of the estrogen, progesterone and HER2/neu receptors which characterise clinically distinct breast tumors have been shown to change during disease progression and in response to systemic therapies. Mi(cro)RNAs play critical roles in diverse biological processes and are aberrantly expressed in several human neoplasms including breast cancer, where they function as regulators of tumour behaviour and progression. The aims of this study were to identify miRNA signatures that accurately predict the oestrogen receptor (ER), progesterone receptor (PR) and HER2/neu receptor status of breast cancer patients to provide insight into the regulation of breast cancer phenotypes and progression. Expression profiling of 353 microRNAs was performed in 29 early stage breast cancer specimens. MiRNA signatures associated with ER, PR and HER2/neu status were generated using artificial neural networks (ANN) and expression of specific microRNAs was validated using RQ-PCR. Results: Stepwise artificial neural network (ANN) analysis identified predictive miRNA signatures corresponding with estrogen (miR-342, miR-299, miR-217, miR -190, miR-135b, miR-218), progesterone (miR-520g, miR-377, miR-527-518a, miR-520f-520c) and HER2/neu (miR-520d, miR-181c, miR-302c, miR-376b, miR-30e) receptor status. MiR-342 and miR-520g expression was further analysed in 95 breast tumours. MiR-342 expression was highest in ER and HER2/neu positive luminal B tumours and lowest in triple-negative tumours. MiR-520g expression was elevated in ER and PR negative tumours.