Recurrent Genomic Gains in Preinvasive Lesions as a Biomarker of Risk for Lung Cancer

Lung carcinoma development is accompanied by field changes that may have diagnostic significance. We have previously shown the importance of chromosomal aneusomy in lung cancer progression. Here, we tested whether genomic gains in six specific loci, TP63 on 3q28, EGFR on 7p12, MYC on 8q24, 5p15.2, and centromeric regions for chromosomes 3 (CEP3) and 6 (CEP6), may provide further value in the prediction of lung cancer. Bronchial biopsy specimens were obtained by LIFE bronchoscopy from 70 subjects (27 with prevalent lung cancers and 43 individuals without lung cancer). Twenty six biopsies were read as moderate dysplasia, 21 as severe dysplasia and 23 as carcinoma in situ (CIS). Four-micron paraffin sections were submitted to a 4-target FISH assay (LAVysion, Abbott Molecular) and reprobed for TP63 and CEP 3 sequences. Spot counts were obtained in 30–50 nuclei per specimen for each probe. Increased gene copy number in 4 of the 6 probes was associated with increased risk of being diagnosed with lung cancer both in unadjusted analyses (odds ratio = 11, p<0.05) and adjusted for histology grade (odds ratio = 17, p<0.05). The most informative 4 probes were TP63, MYC, CEP3 and CEP6. The combination of these 4 probes offered a sensitivity of 82% for lung cancer and a specificity of 58%. These results indicate that specific cytogenetic alterations present in preinvasive lung lesions are closely associated with the diagnosis of lung cancer and may therefore have value in assessing lung cancer risk.     

Understanding the Role of Dicer in Astrocyte Development

The Dicer1 allele is used to show that microRNAs (miRNAs) play important roles in astrocyte development and functions. While it is known that astrocytes that lack miRNAs are dysregulated, the in vivo phenotypes of these astrocytes are not well understood. In this study, we use Aldh1l1-EGFP transgene, a marker of astrocytes, to characterize mouse models with conditional Dicer1 ablation (via either human or mouse GFAP-Cre). This transgene revealed novel features of the defective astrocytes from the absence of miRNA. Although astrocyte miRNAs were depleted in both lines, we found histological and molecular differences in the Aldh1l1-EGFP cells between the two Cre lines. Aldh1l1-EGFP cells from hGFAP-Cre mutant lines displayed up-regulation of Aldh1l1-EGFP with increased proliferation and a genomic profile that acquired many features of wildtype primary astrocyte cultures. In the young mGFAP-Cre mutant lines we found that Aldh1l1-EGFP cells were disorganized and hyperproliferative in the developing cerebellum. Using the Aldh1l1-EGFP transgene, our work provides new insights into the roles of miRNAs in astrocyte development and the features of astrocytes in these two mouse models.     

基于指标自动筛选的新疆开孔河流域生态健康评价

生态健康评价对了解区域生态健康状况和促进区域可持续发展具有重要意义,如何自动筛选出能反映生态系统特性的重要指标,是生态健康定量评估的关键问题。基于压力-状态-响应(PSR,Press-State-Response)框架和生态等级网络框架(EHN,Ecological Hierarchy Network),通过文献调研和因果分析建立要素层与指标层之间的交叉联系,构建了生态健康评价"网状"指标体系;在保证指标体系完备性基础上,通过结合主成分分析和熵权法的候选指标权重的客观计算,基于目标优化理论构建了评价指标的自动筛选模型,并基于中选指标计算了新疆开孔河流域2001—2017年生态健康指数(EHCI,Ecological Health Comprehensive Indexes),分析其空间分异和时间变化特征。结果表明:利用所建立的评价指标自动筛选模型,开孔河流域生态健康评价指标由31个候选指标自动筛选出了17个中选指标,用54.8%的指标表达了85.98%的信息,中选的17个指标在干旱/半干旱区域有关文献中应用较多,使用频次比例都在20%以上,其中归一化植被指数(NDVI,Normalized Difference Vegetation Index)、年降水量和植被覆盖度(FVC,Fractional Vegetation Coverage)3个指标的使用频次百分比均超过了50%,说明指标自动筛选模型的合理性;开孔河流域空间分布差异显著,总体上西北高、东南低,东南部和中部绿洲区外围生态健康状况较差,西北部河谷地带和中部两大绿洲区生态健康状况较好;17年来,流域生态质量整体趋于改善,显著改善区域占10.26%,远高于显著退化的1.61%,显著改善区域以孔雀河绿洲最为明显。开孔河流域生态健康的总体好转趋势说明区域生态综合治理取得一定成效。