Establishment of the Ba/F3 method to test the oncogenic potential of cancer gene mutations

Master i biomedisi

Drug-screening and genomic analyses of HER2-positive breast cancer cell lines reveal predictors for treatment response

Background: Approximately 15%-20% of all diagnosed breast cancers are characterized by amplified and overexpressed HER2 (= ErbB2). These breast cancers are aggressive and have a poor prognosis. Although improvements in treatment have been achieved after the introduction of trastuzumab and lapatinib, many patients do not benefit from these drugs. Therefore, in-depth understanding of the mechanisms behind the treatment responses is essential to find alternative therapeutic strategies. Materials and methods: Thirteen HER2 positive breast cancer cell lines were screened with 22 commercially available compounds, mainly targeting proteins in the ErbB2-signaling pathway, and molecular mechanisms related to treatment sensitivity were sought. Cell viability was measured, and treatment responses between the cell lines were compared. To search for response predictors and genomic and transcriptomic profiling, PIK3CA mutations and PTEN status were explored and molecular features associated with drug sensitivity sought. Results: The cell lines were divided into three groups according to the growth-retarding effect induced by trastuzumab and lapatinib. Interestingly, two cell lines insensitive to trastuzumab (KPL4 and SUM190PT) showed sensitivity to an Akt1/2 kinase inhibitor. These cell lines had mutation in PIK3CA and loss of PTEN, suggesting an activated and druggable Akt-signaling pathway. Expression levels of five genes (CDC42, MAPK8, PLCG1, PTK6, and PAK6) were suggested as predictors for the Akt1/2 kinase-inhibitor response. Conclusion: Targeting the Akt-signaling pathway shows promise in cell lines that do not respond to trastuzumab. In addition, our results indicate that several molecular features determine the growth-retarding effects induced by the drugs, suggesting that parameters other than HER2 amplification/expression should be included as markers for therapy decisions.Peer reviewe

An independent poor-prognosis subtype of breast cancer defined by a distinct tumor immune microenvironment

How mixtures of immune cells associate with cancer cell phenotype and affect pathogenesis is still unclear. In 15 breast cancer gene expression datasets, we invariably identify three clusters of patients with gradual levels of immune infiltration. The intermediate immune infiltration cluster (Cluster B) is associated with a worse prognosis independently of known clinicopathological features. Furthermore, immune clusters are associated with response to neoadjuvant chemotherapy. In silico dissection of the immune contexture of the clusters identified Cluster A as immune cold, Cluster C as immune hot while Cluster B has a pro-tumorigenic immune infiltration. Through phenotypical analysis, we find epithelial mesenchymal transition and proliferation associated with the immune clusters and mutually exclusive in breast cancers. Here, we describe immune clusters which improve the prognostic accuracy of immune contexture in breast cancer. Our discovery of a novel independent prognostic factor in breast cancer highlights a correlation between tumor phenotype and immune contexture

High-throughput screens identify microRNAs essential for HER2 positive breast cancer cell growth

MicroRNAs (miRNAs) are non-coding RNAs regulating gene expression post-transcriptionally. We have characterized the role of miRNAs in regulating the human epidermal growth factor receptor 2 (HER2)-pathway in breast cancer. We performed miRNA gain-of-function assays by screening two HER2 amplified cell lines (KPL-4 and JIMT-1) with a miRNA mimic library consisting of 810 human miRNAs. The levels of HER2, phospho-AKT, phospho-ERK1/2, cell proliferation (Ki67) and apoptosis (cPARP) were analyzed with reverse-phase protein arrays. Rank product analyses identified 38 miRNAs (q <0.05) as inhibitors of HER2 signaling and cell growth, the most effective being miR-491-5p, miR-634, miR-637 and miR-342-5p. We also characterized miRNAs directly targeting HER2 and identified seven novel miRNAs (miR-552, miR-541, miR-193a-5p, miR-453, miR-134, miR-498, and miR-331-3p) as direct regulators of the HER2 3'UTR. We demonstrated the clinical relevance of the miRNAs and identified miR-342-5p and miR-744* as significantly down-regulated in HER2-positive breast tumors as compared to HER2-negative tumors from two cohorts of breast cancer patients (101 and 1302 cases). miR-342-5p specifically inhibited HER2-positive cell growth, as it had no effect on the growth of HER2-negative control cells in vitro. Furthermore, higher expression of miR-342-5p was associated with better survival in both breast cancer patient cohorts. In conclusion, we have identified miRNAs which are efficient negative regulators of the HER2 pathway that may play a role in vivo during breast cancer progression. These results give mechanistic insights in HER2 regulation which may open potential new strategies towards prevention and therapeutic inhibition of HER2-positive breast cancer

An independent poor-prognosis subtype of breast cancer defined by a distinct tumor immune microenvironment

How mixtures of immune cells associate with cancer cell phenotype and affect pathogenesis is still unclear. In 15 breast cancer gene expression datasets, we invariably identify three clusters of patients with gradual levels of immune infiltration. The intermediate immune infiltration cluster (Cluster B) is associated with a worse prognosis independently of known clinicopathological features. Furthermore, immune clusters are associated with response to neoadjuvant chemotherapy. In silico dissection of the immune contexture of the clusters identified Cluster A as immune cold, Cluster C as immune hot while Cluster B has a pro-tumorigenic immune infiltration. Through phenotypical analysis, we find epithelial mesenchymal transition and proliferation associated with the immune clusters and mutually exclusive in breast cancers. Here, we describe immune clusters which improve the prognostic accuracy of immune contexture in breast cancer. Our discovery of a novel independent prognostic factor in breast cancer highlights a correlation between tumor phenotype and immune contexture