Project description:We found that MCF-7 and T-47D or MDA-MB-157 and MDA-MB-231 are rBC2LCN-positive or -negative breast cancer cell lines, respectively. To examine a global gene expression comparison between the rBC2LCN-positive and -negative breast cancer cell lines, DNA microarray analysis was performed.
Project description:Lymph node status is a crucial predictor for the overall survival of invasive breast cancer. However, lymph node involvement is only detected in about half of HER2 positive patients. Currently, there are no biomarkers available for distinguishing small size HER2-positive breast cancers with different lymph node statuses. Thus, in the present study, we applied label-free quantitative proteomic strategy to construct plasma proteomic profiles of ten patients with small size HER2-positive breast cancers (5 patients with lymph node metastasis versus 5 patients with lymph node metastasis).
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:HER2-targeted therapies including antibody drug conjugates have shown great efficacy in HER2-positive breast cancer. However, resistance to treatment in part due to pre-existing HER2 heterogeneity (HET) is a significant clinical challenge and requires the use of rationally-designed combination therapies. Here we describe transcriptomic profiling of 287 biopsies from 129 patients in a phase II neoadjuvant clinical trial using a combination of T-DM1 and pertuzumab for early-stage HER2-positive breast cancer, we investigated the mechanisms driving T-DM1 resistance. In pre-treatment tumors from patients without a complete response (pCR), distinct molecular features were identified: HER2 HET tumors retained PI3K pathway activation and a basal-like phenotype, while HER2 Non-HET tumors exhibited lower PI3K pathway enrichment. T-DM1 treatment universally reduced HER2 protein expression and copy number heterogeneity while increasing PI3K pathway enrichment and luminal identity in residual tumors. Importantly, HER2 HET tumors showed minimal transcriptomic response compared to HER2 Non-HET tumors, in line with the lesser clinical response. The response to T-DM1 was not associated with hotspot PIK3CA/ERBB2 mutations but rather correlated with immune infiltration. HER2 Non-HET tumors exhibited less effective immune surveillance at baseline but became immune activated with T-DM1 treatment, while HER2 HET tumors exhibited a more immune suppressed microenvironment upon treatment. Our study highlights the multifaceted nature of T-DM1 resistance driven by HER2 heterogeneity and provides essential evidence for optimizing therapeutic strategies for these patients.
Project description:The goal of our study is to build an integrated transcriptome landscape model for HER2 positive breast tumors and identify the crucial signaling pathways associated with HER2 tumors. Genomic features include, 685 genes that were differentially expressed only in HER2-positive tumors, 102 genes that were alternatively spliced in a pattern that is unique to HER2-positive tumors, and 303 genes that expressed single nucleotide sequence variants (eSNVs) that were unique to HER2-positive tumors. Network analysis was performed to integrate the genomic features into a transcriptome landscape model that identified 12 highly interconnected cellular processes that appear to be critical to the establishment and maintenance of HER2-positive tumors. We observed that integrin signaling was linked to lapatinib sensitivity in vitro and strongly associated with risk of relapse in the NCCTG N9831 adjuvant trastuzumab clinical trial dataset. We analyzed RNA-seq data from a survey panel consisting of 8 benign breast lesions, 8 ER+, 8 triple negative, and 8 HER2-positive primary breast tumors to identify genomic features that were uniquely associated with HER2-positive tumors
Project description:The use of trastuzumab and pertuzumab in combination with docetaxel for initial treatment of HER2-positive breast cancer patients has resulted in notable clinical benefits in comparison to docetaxel administered with trastuzumab alone. Nevertheless, although therapeutic success is evident at the outset, the majority of tumours eventually advance, rendering metastatic disease and subsequent recurrence in patients who have developed acquired resistance. There is an urgent requirement to enhance our comprehension of the mechanisms governing resistance, enabling us to develop targeted therapeutic approaches to improve efficacy. We produced four HER2-positive-derived cell lines through prolonged exposure to trastuzumab and pertuzumab, determining their resistance rates. We confirmed long-term resistance through a notable increase in colony formation capacity of the derived cells. We confirmed the molecular identity of the new cell lines using immunohistochemistry of their receptors and profiling of point mutations. We detected HER2 overexpression in all cell lines and resistance to trastuzumab and pertuzumab did not result in variations in ER, PR and HER2 receptor expression. Finally, a study using proteomics analysis confirmed a significant alteration in the abundance patterns of over 600 proteins. This has implications for various vital biological processes such as ribosome creation, mitochondrial functionality, and metabolism. These mechanisms may play a crucial role in developing resistance in HER2-positive breast cancer. We conclude that these BCCLs resistant to trastuzumab plus pertuzumab-based anti-HER2 therapy could be a useful resource to enhance comprehension of resistance acquisition mechanisms.
Project description:The goal of our study is to build an integrated transcriptome landscape model for HER2 positive breast tumors and identify the crucial signaling pathways associated with HER2 tumors. Genomic features include, 685 genes that were differentially expressed only in HER2-positive tumors, 102 genes that were alternatively spliced in a pattern that is unique to HER2-positive tumors, and 303 genes that expressed single nucleotide sequence variants (eSNVs) that were unique to HER2-positive tumors. Network analysis was performed to integrate the genomic features into a transcriptome landscape model that identified 12 highly interconnected cellular processes that appear to be critical to the establishment and maintenance of HER2-positive tumors. We observed that integrin signaling was linked to lapatinib sensitivity in vitro and strongly associated with risk of relapse in the NCCTG N9831 adjuvant trastuzumab clinical trial dataset.
Project description:Conditioned medium experiments carried out in our laboratory with CAFs derived from HER2-positive patients showed a significant capacity to promote resistance to trastuzumab plus pertuzumab therapies in two HER2-positive breast cancer cell lines (BCCLs), even in the presence of docetaxel. In order to elucidate the components of CAF-conditioned medium that would be relevant in the promotion of BCCL resistance, we performed a multi-omics strategy to identify miRNAs, cytokines, transcription factors and/or kinases in the secretome that target specific objectives in cancer cells. The combination of miRNA analysis, label-free LC-MS/MS quantification and cytokine arrays to explore the secretome of CAFs under treatment conditions revealed several up- and down-regulated candidates. We discuss the potential role of some of the most interesting candidates in generating resistance in HER2-positive breast cancer
Project description:Purpose HER2 gene amplification or protein overexpression (HER2+) defines a clinically challenging subgroup of breast cancer with variable prognosis and response to therapy. We aimed to investigate the heterogeneous biological appearance and clinical behavior of HER2+ tumors using molecular profiling. Materials and Methods Hierarchical clustering of gene expression data from 58 HER2-amplified tumors of various stage, histological grade and estrogen receptor (ER) status was used to construct a HER2-derived prognostic predictor that was further evaluated in several large independent breast cancer data sets. Results Unsupervised analysis identified three subtypes of HER2+ tumors with mixed stage, histological grade and ER-status. One subtype had a significantly worse clinical outcome. A prognostic predictor was created based on differentially expressed genes between the subtype with worse outcome and the other subtypes. The predictor was able to define patient groups with better and worse outcome in HER2+ breast cancer across multiple independent breast cancer data sets and identify a sizable HER2+ group with long disease-free survival and low mortality. Significant correlation to prognosis was also observed in basal-like, ER−, lymph node positive or high-grade tumors, irrespective of HER2-status. The predictor included genes associated to immune response, tumor invasion and metastasis. Conclusion The HER2-derived prognostic predictor provides further insight into the heterogeneous biology of HER2+ tumors and may become useful for improved selection of patients that need additional treatment with new drugs targeting the HER2 pathway.