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: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.

Dataset Information

Mechanisms of drugs-resistance in small cell lung cancer

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets