Project description:Triple-negative breast cancer (TNBC) patients with residual disease after neoadjuvant chemotherapy generally have worse outcome; however, some patients with residual tumor after neoadjuvant chemotherapy do not relapse. We hypothesize that there are subgroups of chemoresistant TNBC patients with different prognosis. In this study, 25 chemoresistant samples from 47 neoadjuvant chemotherapy-treated TNBC (The Methodist Hospital) are chosen for study We used gene expression data of TNBC patients with residual disease and different prognosis to molecularly define the clinically relevant subgroups, and developed a 7-gene prognostic signature for chemoresistant TNBCs
Project description:Triple-negative breast cancer (TNBC) patients with residual disease after neoadjuvant chemotherapy generally have worse outcome; however, some patients with residual tumor after neoadjuvant chemotherapy do not relapse. We hypothesize that there are subgroups of chemoresistant TNBC patients with different prognosis. In this study, 25 chemoresistant samples from 47 neoadjuvant chemotherapy-treated TNBC (The Methodist Hospital) are chosen for study
Project description:Discrepancies in the prognosis of triple negative breast cancer exist between Caucasian and Asian populations. Yet, the gene signature of triple negative breast cancer specifically for Asians has not become available. Therefore, the purpose of this study is to construct a prediction model for recurrence of triple negative breast cancer in Taiwanese patients.
Project description:Discrepancies in the prognosis of triple negative breast cancer exist between Caucasian and Asian populations. Yet, the gene signature of triple negative breast cancer specifically for Asians has not become available. Therefore, the purpose of this study is to construct a prediction model for recurrence of triple negative breast cancer in Taiwanese patients. Whole genome expression profiling of breast cancers from 185 patients in Taiwan from 1995 to 2008 was performed, and the results were compared to the previously published literature to detect differences between Asian and Western patients. Pathway analysis and Cox proportional hazard models were applied to construct a prediction model for the recurrence of triple negative breast cancer. Most expression data of samples (181/185) were reanalyzed from previous studies already uploaded to GEO (see "reanalysis of" links below). Four additional gene expression profiling data of triple negative breast cancer sample were added to this study.
Project description:Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype with the worst prognosis. It is characterised by the absence of hormone receptors for estrogen, progesterone, and human epidermal growth factor 2, and as a consequence there are no targeted endocrine treatments available. TNBC patients are more likely to develop metastases and disease relapse than patients with other breast cancer subtypes. The identification of biomarkers that can be used to predict which patient is likely to develop metastatic disease remains a priority since this is the major cause of cancer-related death in these women.
Project description:Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype with the worst prognosis. It is characterised by the absence of hormone receptors for estrogen, progesterone, and human epidermal growth factor 2, and as a consequence there are no targeted endocrine treatments available. TNBC patients are more likely to develop metastases and disease relapse than patients with other breast cancer subtypes. The identification of biomarkers that can be used to predict which patient is likely to develop metastatic disease remains a priority since this is the major cause of cancer-related death in these women.
Project description:Triple negative breast cancer (TNBC) accounts for 15-20% of all breast carcinomas and it is clinically characterized by an aggressive phenotype and bad prognosis. TNBC does not benefit from any targeted therapy, so further characterization is needed to define subgroups with potential therapeutic value. In this work, the proteomes of one hundred twenty-five formalin-fixed paraffin-embedded samples from patients diagnosed with triple negative breast cancer were analyzed by mass spectrometry using data-independent acquisition. Hierarchical clustering, probabilistic graphical models and Significance Analysis of Microarrays were used to characterize molecular groups. Additionally, a predictive signature related with relapse was defined. Two molecular groups with differences in several biological processes as glycolysis, translation and immune response, were defined in this cohort, and a prognostic signature based on the abundance of proteins RBM3 and NIPSNAP1 was defined. This predictor split the population into low-risk and high-risk groups. The differential processes identified between the two molecular groups may serve to design new therapeutic strategies in the future and the prognostic signature could be useful to identify a population at high-risk of relapse that could be directed to clinical trials.
Project description:RNA-sequencing was performed in SUM 159 parental and PTX resistant breast cancer cells in an effort to identify novel regulators of chemoresistance that could potentially be targeted in Triple Negative Breast Cancer (TNBC). The bioinformatic analysis identified numerous differentially expressed genes including several known chemoresistance markers, as well as novel genes that may play an important role in breast cancer chemoresistant cells.
Project description:Profiling of loss of heterozygosity (LOH) in HGSC, subcrouping HGSC by LOH-based clustering and comparing to the LOH profiles of triple-negative breast cancer [previously submitted; GSE19594]. Study for the correlation of LOH burdern and LOH-based subgroups to clinical response to platinum-based chemotherapy in patients suffered from HGSC.
