基于TCGA数据库挖掘甲状腺乳头状癌淋巴结转移相关的突变基因及其机制探讨北大核心

目的:挖掘并筛选与甲状腺乳头状癌(papillary thyroid carcinoma,PTC)淋巴结转移相关的突变基因及其潜在的机制。方法:从TCGA数据库获得377例PTC患者的测序数据及完整的临床资料,并分为淋巴结转移组(LM,n=212)与无淋巴结转移组(NLM,n=165)。利用R语言(v3.6.2)对转移组特有的突变基因进行富集分析。采用String在线软件绘制蛋白互作网络,Cytoscape软件筛选网络中的核心基因。在UALCAN网站上验证基因表达量与淋巴结转移之间的关系。利用荧光实时定量PCR测定候选基因在细胞系中mRNA的表达量。结果:一共筛选出1197个仅在LM组发生突变的基因,它们主要富集在黏着连接、细胞黏附分子(cell adhesion molecules,CAMs)通路。CAMs通路的核心基因ITGB1与VCAN的表达量与淋巴结转移相关。与正常甲状腺细胞系相比,VCAN基因在PTC细胞系TPC-1和B-CPAP中mRNA的表达量较高,尤其是B-CPAP细胞系。结论:CAMs通路可能是PTC淋巴结转移相关机制之一,其中VCAN基因可能是潜在的分子标志物。     

Preoperative comprehensive malignancy risk estimation for thyroid nodules: Development and verification of a network-based prediction model

BackgroundIn order to avoid excessive treatment of thyroid nodules in the clinic, it is necessary to find a simple and practical analysis method to comprehensively and accurately reflect benign or malignant thyroid nodules. This study aimed to construct and validate a comprehensive and reliable network-based predictive model using a variety of imaging and laboratory criteria for thyroid nodules to stratify the risk of malignancy prior to surgery.MethodsWe retrospectively analyzed data from patients who underwent surgical treatment for thyroid nodules at the Thyroid and Breast Diagnosis and Treatment Center of Weifang Hospital of Traditional Chinese Medicine between January 2018 and December 2020. Binary logical regression analysis was performed to predict whether nodules were malignant or benign. The developmental dataset included 457 patients (January 2018–December 2020). The validation set included separate data points (n = 225, January 2018–December 2020).ResultsIn this study, criteria that showed significant predictive value for malignant nodules included TI-RADS: 4b (p = 0.065); Bethesda IV, Bethesda V, Bethesda VI (P < 0.0001); BRAF^V600E mutation (P < 0.0001); Calcitonin>5 pg/ml (p = 0.0037); and FNA-Tg>30 ng/ml (p = 0.0003). A 10-grade risk scoring system was developed. The risk of malignancy risk ranged from 2.06% to 100% and was positively associated with increasing risk grade. The areas under the receiver-operating characteristic curve of the development and validation sets were 0.972 and 0.946, respectively.ConclusionA simple, comprehensive and reliable web-based predictive model was designed using a variety of imaging and laboratory criteria to stratify thyroid nodules by probability of malignancy.     

胰腺囊性肿瘤诊疗及进展

胰腺囊性肿瘤(PCNs)是少见肿瘤，发病原因尚不明确，不良生活习惯（吸烟、饮酒、重咖啡、高脂高蛋白饮食等）、慢性胰腺炎、环境污染因素及遗传因素等是潜在致病因素。PCNs分为浆液性囊性肿瘤（SCN）、黏液性囊性肿瘤（MCN）、胰腺导管内乳头状黏液肿瘤(IPMN)和实性假乳头状瘤（SPN）四种类型。发病症状常不典型，早期诊断难。PCNs具有典型影像特点，单个影像检查技术对PCNs的准确性和局限性不同，CT检查在胰腺病变中仍是最基本、最主要的检查方式。MRI对于小的囊性病灶比CT更有优势。超声内镜（EUS）充分结合了内镜和超声检查的优势，与CT、MRI检查相辅相成，同时还可进行细针穿刺取病理及囊液分析。尽管PCNs大部分为良性，但只要达到切除标准，均应推荐患者进行手术治疗，严格遵循PCNs诊治流程，制订个体化PCNs治疗策略，使患者利益最大化。     

Sample size re-estimation for clinical trials with longitudinal negative binomial counts including time trends

In some diseases, such as multiple sclerosis, lesion counts obtained from magnetic resonance imaging (MRI) are used as markers of disease progression. This leads to longitudinal, and typically overdispersed, count data outcomes in clinical trials. Models for such data invariably include a number of nuisance parameters, which can be difficult to specify at the planning stage, leading to considerable uncertainty in sample size specification. Consequently, blinded sample size re-estimation procedures are used, allowing for an adjustment of the sample size within an ongoing trial by estimating relevant nuisance parameters at an interim point, without compromising trial integrity. To date, the methods available for re-estimation have required an assumption that the mean count is time-constant within patients. We propose a new modeling approach that maintains the advantages of established procedures but allows for general underlying and treatment-specific time trends in the mean response. A simulation study is conducted to assess the effectiveness of blinded sample size re-estimation methods over fixed designs. Sample sizes attained through blinded sample size re-estimation procedures are shown to maintain the desired study power without inflating the Type I error rate and the procedure is demonstrated on MRI data from a recent study in multiple sclerosis.