Project description:Purpose: Due to the rarity of Merkel Cell Carcinoma (MCC), prospective clinical trials have not been practical. This study seeks to identify biomarkers to differentiate between patients with a good and poor prognosis. Methods: Patients were stratified into good, moderate or poor prognosis. Merkel cell carcinoma (MCC) patients were stratified into one of three groups based upon status 24 months following treatment. Poor prognosis patients either presented with or progressed to distant metastasis. Patients with favorable prognosis had local disease presentation with no subsequent recurrence or nodal disease at presentation with no progression during follow-up of longer than 24 months. Moderate prognosis had recurrent local disease, development of nodal metastasis, or nodal disease at presentation with no progression during follow-up of fewer than 24 months. Using ArcturusXT Laser Capture Microdissection (Molecular Devices), tumor cells were isolated from the specific areas of interest. The captured tumor tissue was subjected to RNA extraction using the Invitrogen PureLinkM-bM-^DM-" FFPE RNA Isolation Kit. The extracted RNA was analyzed for integrity with the Agilent Bioanalyzer then amplified and hybridized to Affymetrix GeneChip Human Exon 1.0 ST arrays using the NuGEN WT- OvationM-bM-^DM-" FFPE System. Results: A total of 191 genes showed significant differential expression (pM-bM-^IM-$0.05 and 1.5-fold cutoff) between the different between the good and poor prognosis groups. Keratin 20 (KRT20) and Neurofilament protein (NEFM) have been identified in previous studies as proteins of interest in MCC. Our study showed these genes to be significantly upregulated in patients with a poor prognosis. Of interest, phospholipase A2, group X was upregulated in poor responders. Phospholipases liberate arachidonic acid from cellular membranes which can be metabolized to eicosanoids through three major pathways: the cyclooxygenase (COX), the lipoxygenase (LOX) and the cytochrome P450 monooxygenase pathways. This pathway has been implicated in several cancers. Conclusions: The study identified genes with a previous association with MCC as well as some novel genes. These genes provide the basis for further research into possible biomarkers that will enable the differentiation between patients with a good and poor prognosis. Using laser capture microdissection, tumor cells of patients with a good (n=5), moderate (n=3), and poor prognosis (n=7) were isolated from paraffin embedded archival tissue of 15 patients with Merkel cell carcinoma. Affymetrix Human Exon 1.0ST microarrays were utilized to compare gene expression signatures from good and poor prognosis patients.

Project description:Purpose: Due to the rarity of Merkel Cell Carcinoma (MCC), prospective clinical trials have not been practical. This study seeks to identify biomarkers to differentiate between patients with a good and poor prognosis. Methods: Patients were stratified into good, moderate or poor prognosis. Merkel cell carcinoma (MCC) patients were stratified into one of three groups based upon status 24 months following treatment. Poor prognosis patients either presented with or progressed to distant metastasis. Patients with favorable prognosis had local disease presentation with no subsequent recurrence or nodal disease at presentation with no progression during follow-up of longer than 24 months. Moderate prognosis had recurrent local disease, development of nodal metastasis, or nodal disease at presentation with no progression during follow-up of fewer than 24 months. Using ArcturusXT Laser Capture Microdissection (Molecular Devices), tumor cells were isolated from the specific areas of interest. The captured tumor tissue was subjected to RNA extraction using the Invitrogen PureLink™ FFPE RNA Isolation Kit. The extracted RNA was analyzed for integrity with the Agilent Bioanalyzer then amplified and hybridized to Affymetrix GeneChip Human Exon 1.0 ST arrays using the NuGEN WT- Ovation™ FFPE System. Results: A total of 191 genes showed significant differential expression (p≤0.05 and 1.5-fold cutoff) between the different between the good and poor prognosis groups. Keratin 20 (KRT20) and Neurofilament protein (NEFM) have been identified in previous studies as proteins of interest in MCC. Our study showed these genes to be significantly upregulated in patients with a poor prognosis. Of interest, phospholipase A2, group X was upregulated in poor responders. Phospholipases liberate arachidonic acid from cellular membranes which can be metabolized to eicosanoids through three major pathways: the cyclooxygenase (COX), the lipoxygenase (LOX) and the cytochrome P450 monooxygenase pathways. This pathway has been implicated in several cancers. Conclusions: The study identified genes with a previous association with MCC as well as some novel genes. These genes provide the basis for further research into possible biomarkers that will enable the differentiation between patients with a good and poor prognosis.

Project description:Background Neuroendcrine carcinoma (NEC) of lung consists of small-cell lung carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC). Although long-term outcomes of SCLC patients are usually poor, a few patients achieve long-term survivals. Prognostic factors in SCLC have not been fully elucidated. microRNAs (miRNAs) are known to negatively regulate gene expression and to be relevant to tumorigenesis, tumor classification and prognosis. Methods 63 samples (46 neuroendocrine carcinoma including 35 SCLC and 11 LCNEC, 4 adenocarcinoma, 5 squamous cell carcinoma and 8 normal lung) were obtained through surgical resection. miRNA expression in each sample was comprehensively investigated using miRNA microarray. Results Unsupervised hierarchial clustering classified the all NEC into two subgroups, group 1 and 2. Group 1 was felt into an independent branch that consisted of only NEC, whereas group 2 was included in a branch that contained both NEC and non-NEC. Compared with SCLC of group 1 (SCLC 1), SCLC of group 2 (SCLC 2) was a distinct subgroup with surprisingly good prognosis (0% v 79% survived for 5 years; p=0.007). Serum proGRP level was significantly lower in SCLC 2 than in SCLC 1 despite of similar tumor stages between the two groups. Among 12 cases treated by presurgical chemotherapy, PR:NC ratio was 6:3 in SCLC 1 and 2:1 in SCLC 2, suggesting no apparent difference of chemosensitivity. Histologically, distinction between both groups was difficult. Cox regression analysis demonstrated that three miRNA signature was correlated with survival of SCLC patients. These prognostic miRNAs were differentially expressed between SCLC 1 and 2, which were validated by quantitative real time RT-PCR. Bioinformatics analysis predicted that these miRNAs targeted not only genes involving with tumorigenesis but also genes associated with neuroendocrine function. Conclusion miRNA expression profiling identified a distinct subgroup of SCLC with favorable prognosis. This subgroup might have less neuroendocrine character than usual SCLC.

Project description:Background Neuroendcrine carcinoma (NEC) of lung consists of small-cell lung carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC). Although long-term outcomes of SCLC patients are usually poor, a few patients achieve long-term survivals. Prognostic factors in SCLC have not been fully elucidated. microRNAs (miRNAs) are known to negatively regulate gene expression and to be relevant to tumorigenesis, tumor classification and prognosis. Methods 63 samples (46 neuroendocrine carcinoma including 35 SCLC and 11 LCNEC, 4 adenocarcinoma, 5 squamous cell carcinoma and 8 normal lung) were obtained through surgical resection. miRNA expression in each sample was comprehensively investigated using miRNA microarray. Results Unsupervised hierarchial clustering classified the all NEC into two subgroups, group 1 and 2. Group 1 was felt into an independent branch that consisted of only NEC, whereas group 2 was included in a branch that contained both NEC and non-NEC. Compared with SCLC of group 1 (SCLC 1), SCLC of group 2 (SCLC 2) was a distinct subgroup with surprisingly good prognosis (0% v 79% survived for 5 years; p=0.007). Serum proGRP level was significantly lower in SCLC 2 than in SCLC 1 despite of similar tumor stages between the two groups. Among 12 cases treated by presurgical chemotherapy, PR:NC ratio was 6:3 in SCLC 1 and 2:1 in SCLC 2, suggesting no apparent difference of chemosensitivity. Histologically, distinction between both groups was difficult. Cox regression analysis demonstrated that three miRNA signature was correlated with survival of SCLC patients. These prognostic miRNAs were differentially expressed between SCLC 1 and 2, which were validated by quantitative real time RT-PCR. Bioinformatics analysis predicted that these miRNAs targeted not only genes involving with tumorigenesis but also genes associated with neuroendocrine function. Conclusion miRNA expression profiling identified a distinct subgroup of SCLC with favorable prognosis. This subgroup might have less neuroendocrine character than usual SCLC. All samples were tissue samples obtained by surgical resection. 35 samples of small-cell lung cancer were investigated. 11 samples of larege cell neuroendocrine cancer, 4 samples of adenocarcinoma, 5 samples of squamous cell carcinoma and 8 samples of normal lung were also included as reference.

Project description:Breast carcinoma (BC) is the leading cause of death in women worldwide, making up 23% of all cancers in women, with 1.38 million new cases worldwide annually and responsible for 460,000 deaths. Despite the significant advances in the identification of molecular markers and different modalities of treatment in primary BC, the ability to predict the metastatic behavior in breast cancer is still limited. The purpose of this study was to help identify novel molecular markers associated with clinical outcome in a cohort of Brazilian BC patients. We generated global gene expression profiles from 24 patients with invasive ductal BC followed for â¥ 5-years, including 15 samples from patients classified as presenting good prognosis based on traditional markers and clinical criteria and 9 patients that developed metastasis. We identified a set of 58 differentially expressed genes (p â¤0.01) between groups of patients with good and poor prognosis. Up-regulation of B3GNT7, PPM1D, TNKS2, PHB and GTSE1 in patients with poor prognosis was confirmed by quantitative RT-PCR in an independent sample set from patients with BC (47 with good prognosis and 8 that presented metastasis). Expression of BAD protein was investigated by immunohistochemistry in 1276 BC samples and confirmed the reduced expression levels in metastatic cases observed in the oligoarray data. These findings point to novel prognostic markers that can distinguish breast carcinoma samples according to clinical course and progression of the disease. Global expression profiles from 38 ductal breast tumor patient samples were used to search for molecular signatures correlated with current prognostic markers. A subset of 24 cases comprising 15 patients that remained free of disease after surgery and 9 patients that developed metastasis was used to identify candidate biomarkers associated with metastatic progression. Candidates were subsequently validated in additional independent samples by RT-qPCR or immunohistochemistry.

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Distinct gene expression profile between ARID1Ahigh and good prognosis and ARID1Alow and poor prognosis groups

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