刺果甘草全基因组Survey及叶绿体基因组特征分析＊

目的 基于基因组Survey分析对刺果甘草Glycyrrhiza pallidiflora Maxim.基因组大小和杂合率进行估计，并通过叶绿体基因组序列特征对其在甘草属Glycyrrhiza L.中的系统发育位置进行研究。方法 使用二代测序技术对刺果甘草进行测序，采用K-mer方法对测序reads进行分析，估算刺果甘草基因组大小和杂合率，使用生物信息学方法进行叶绿体基因组组装、注释和系统发育分析。结果 Survey分析结果显示其基因组大小约为577.82 Mb，杂合度约为0.31%，重复序列比例约为53.72%。叶绿体基因组长度为127，267 bp，不具有典型的四分体结构，总GC含量为34.32%，包含110个基因，其中76个蛋白质编码基因，30个tRNA基因和4个rRNA基因。系统发育分析表明，刺果甘草与圆果甘草G. squamulosa Franch.亲缘较接近。结论 刺果甘草存在低杂合和重复序列较多的特点，为了更好地对全基因组进行序列拼接和组装，可尝试采用三代测序结合二代测序的分析策略进行基因组组装；刺果甘草叶绿体全基因组比对和系统发育分析，为后续开展甘草属遗传多样性研究和分子鉴定标记筛选提供了重要依据。     

Iterative treatment with surgery and radiofrequency ablation of uveal melanoma liver metastasis: Retrospective analysis of a series of very long-term survivors

BackgroundAfter treatment of primary ocular uveal melanoma (UM), up to 50% of patients will develop metastases, mostly in the liver. Systemic treatments do not provide any overall survival benefit for these patients and surgery remains the most effective therapy for selected patients. Radiofrequency ablation (RFA) alone or in combination with surgery is frequently used to spare hepatic parenchyma. When patients relapse after treatment of their first metastases, and when the liver recurrence is limited, new local liver treatment is questionable.MethodsA total of 14 patients with liver metastases from uveal melanoma (LMUM) were retrospectively evaluated. All patients had a complete first liver resection and a second treatment with RFA. Overall survival, recurrence-free interval after the first and the second treatment was evaluated.ResultsTreatment of hepatic recurrence was percutaneous RFA for ten patients and per-operative RFA for four patients associated with new metastasectomy. The median time to onset of LMUMs after ocular UM treatment was 50 months, and the median time to recurrence of hepatic metastasis after the first liver treatment was 20 months. The overall survival was 70% at five years and 35% at ten years. The recurrence-free interval was 50% and 56% at two years after the first and the second treatment, respectively.ConclusionProlonged survival can be achieved by exclusive and iterative local treatment combining surgery and RFA in a small proportion of patients with a first recurrence of isolated LMUM.     

Evidence-based data and rare cancers: The need for a new methodological approach in research and investigation

Rare cancers are not so rare, their incidence is increasing and, as a group, they have worse survival than the common cancers. These factors emphasise the societal need to ensure sufficient focus on research into their biological basis, aetiological factors, new more effective therapies and organisation of healthcare to improve access to best practice and innovation. Accuracy of diagnosis is one of the first hurdles to be overcome, with around one third of tumours being reclassified – by type or risk group – when subject to a centralised pathology review process. Timely access to appropriate expert knowledge is a second challenge for patients – in Europe this is being addressed by the establishment of European Reference Networks (ERNs) as part of the EU cross border healthcare initiative. There are ERNs for adult solid and haematological cancers and childhood cancers, all of which are individually rare. These ERNs will facilitate creation of large databases of rare tumours that will incorporate knowledge of their molecular features and build an evidence base for the effectiveness of innovative, biology-directed therapies. With an increasing focus on ‘real world’ outcome data, research methodologies are evolving, to include randomised registry trials and data linkage approaches that exploit the ever-richer information held on patients in routine health care data. The inclusion of genomic analysis into cancer diagnosis, treatment and risk prediction raises many issues for the conduct of clinical research and cohort studies and personal data sharing. Sophisticated means of pseudonymisation, together with full involvement of affected and ‘at risk’ patients, are supporting novel research designs and access to data that will continue to build the evidence base to improve outcomes for patients with rare cancers.     

微阵列比较基因组杂交技术对不明原因智力低下/生长发育迟缓患儿的分子诊断

目的　分析不明原因智力低下(ID)和(或)生长发育迟缓(DD)患儿潜在的致病性基因组不平衡, 及其与表型的相关性, 探讨高密度微阵列比较基因组杂交技术(array-CGH)在临床分子遗传学诊断中的应用价值。方法　采用array-CGH技术对16例ID/DD患儿进行全基因组扫描分析, 并用多重连接探针扩增技术(MLPA)对检出的基因组不平衡异位进行验证。结果　16例患儿高分辨G显带核型分析均无异常。6例(38%)患儿存在基因拷贝数异常(CNVs), 其中3例CNVs为正常多态性改变; 1例CNVs涉及4p16.3区域微缺失, 考虑为Wolf-Hirschhorn综合征; 1例CNVs涉及7q11.23区域微缺失, 考虑为Williams-Beuren 综合征; 另1例CNVs临床意义不明确, 包含2个重复突变, 该突变与智力低下、脑发育迟缓、特殊面容、隐睾、牙列不齐等有关, 证实该CNVs具有临床意义。结论 通过array-CGH技术对不明原因ID/DD患儿进行全基因组扫描, 可为部分患儿明确病因诊断。该技术作为一种高通量、快速的疾病研究手段, 在ID/DD的病因诊断中具有重要的临床意义。     

13q13.3 microdeletion associated with apparently balanced translocation of 46,XX,t(7;13) suggests NBEA involvement

BackgroundDeletion of 13q13.3 is an extremely rare event.CaseWe report on a 25-month-old girl with neurodevelopmental disorder and intellectual disability. She had dysmorphic facies characterized by synophrys, long and narrow palpebral fissures; and a large, round face with small organs such as the eyes and mouth positioned near the center. She was hypotonic and had autism-like behaviors. Blood tests and brain MRI revealed no specific findings. However, G-banding chromosome analysis showed an apparently balanced translocation: 46,XX,t(7,13)(q11.23;q12.3). Both parents had normal karyotypes. Furthermore, her abnormal phenotype and chromosomal breakpoint lesion were suspected to be associated. Hence, we conducted array comparative genomic hybridization, which revealed a 3.2 Mb novel pathological microdeletion at 13q13.3 involving 17 genes including neurobeachin (NBEA), a neurodevelopment disorder gene. Furthermore, fluorescence in situ hybridization using probes adjacent to the microdeletion suggested a concomitant occurrence of the deletion and translocation as the structural basis of this rare genomic variant.ConclusionNBEA may have roles in her neurodevelopmental phenotypes, whereas other genes within the 13q13.3 microdeletion may contribute to her dysmorphic features.