Identification of Driver Genes in Primary Liver Cancer by Integrating NGS and TCGA Mutation Data

Background: This study is aimed towards an exploration of mutant genes in primary liver cancer (PLC) patients by using bioinformatics and data mining techniques. Methods: Peripheral blood or paraffin-embedded tissues from 8 patients with PLC were analyzed using a 551 cancer-related gene panel on an Illumina NextSeq500 Sequencer (Illumina). Meanwhile, the data of 396 PLC cases were downloaded from The Cancer Genome Atlas (TCGA) database. The common mutated genes were obtained after integrating the mutation information of the above two cohorts, followed by functional enrichment and protein-protein interaction (PPI) analyses. Three well-known databases, including Vogelstein’s list, the Network of Cancer Gene (NCG), and the Catalog of Somatic Mutations in Cancer (COSMIC) database were used to screen driver genes. Furthermore, the Chi-square and logistic analysis were performed to analyze the correlation between the driver genes and clinicopathological characteristics, and Kaplan-Meier (KM) method and multivariate Cox analysis were conducted to evaluate the overall survival outcome. Results: In total, 84 mutation genes were obtained after 8 PLC patients undergoing gene mutation detection with next-generation sequencing (NGS). The top 100 most mutate gene data from PLC patients in TCGA database were downloaded. After integrating the above two cohorts, 17 common mutated genes were identified. Next, 11 driver genes were screened out by analyzing the intersection of the 17 mutation genes and the genes in the three well-known databases. Among them, RB1, TP53, and KRAS gene mutations were connected with clinicopathological characteristics, while all the 11 gene mutations had no relationship with overall survival. Conclusion: This study investigated the mutant genes with significant clinical implications in PLC patients, which may improve the knowledge of gene mutations in PLC molecular pathogenesis.

Mutation analysis of 13 driver genes of colorectalcancer-related pathways in Taiwan Residents patients

AIM To investigate the driver gene mutations associatedwith colorectal cancer （CRC） in the Taiwan Residentspopulation.METHODS： In this study, 103 patients with CRCwere evaluated. The samples consisted of 66 menand 37 women with a median age of 59 years and anage range of 26-86 years. We used high-resolutionmelting analysis （HRM） and direct DNA sequencing tocharacterize the mutations in 13 driver genes of CRCrelatedpathways. The HRM assays were conductedusing the LightCycler？ 480 Instrument provided with the software LightCycler 480 Gene Scanning SoftwareVersion 1.5. We also compared the clinicopathologicaldata of CRC patients with the driver gene mutationstatus.RESULTS： Of the 103 patients evaluated, 73.79%had mutations in one of the 13 driver genes. Wediscovered 18 novel mutations in APC , MLH1 , MSH2 ,PMS2 , SMAD4 and TP53 that have not been previouslyreported. Additionally, we found 16 de novo mutationsin APC , BMPR1A , MLH1 , MSH2 , MSH6 , MUTYH andPMS2 in cancerous tissues previously reported in thedbSNP database; however, these mutations couldnot be detected in peripheral blood cells. The APCmutation correlates with lymph node metastasis（34.69% vs 12.96%, P = 0.009） and cancer stage（34.78% vs 14.04%, P = 0.013）. No association wasobserved between other driver gene mutations andclinicopathological features. Furthermore, having twoor more driver gene mutations correlates with thedegree of lymph node metastasis （42.86% vs 24.07%,P = 0.043）.CONCLUSION： Our findings confirm the importanceof 13 CRC-related pathway driver genes in the developmentof CRC in Taiwan Residents patients.

DGMP: Identifying Cancer Driver Genes by Jointing DGCN and MLP from Multi-omics Genomic Data

Identification of cancer driver genes plays an important role in precision oncology research,which is helpful to understand cancer initiation and progression.However,most existing computational methods mainly used the protein–protein interaction(PPI)networks,or treated the directed gene regulatory networks(GRNs)as the undirected gene–gene association networks to identify the cancer driver genes,which will lose the unique structure regulatory information in the directed GRNs,and then affect the outcome of the cancer driver gene identification.Here,based on the multi-omics pan-cancer data(i.e.,gene expression,mutation,copy number variation,and DNA methylation),we propose a novel method(called DGMP)to identify cancer driver genes by jointing directed graph convolutional network(DGCN)and multilayer perceptron(MLP).DGMP learns the multi-omics features of genes as well as the topological structure features in GRN with the DGCN model and uses MLP to weigh more on gene features for mitigating the bias toward the graph topological features in the DGCN learning process.The results on three GRNs show that DGMP outperforms other existing state-of-the-art methods.The ablation experimental results on the Dawn Net network indicate that introducing MLP into DGCN can offset the performance degradation of DGCN,and jointing MLP and DGCN can effectively improve the performance of identifying cancer driver genes.DGMP can identify not only the highly mutated cancer driver genes but also the driver genes harboring other kinds of alterations(e.g.,differential expression and aberrant DNA methylation)or genes involved in GRNs with other cancer genes.The source code of DGMP can be freely downloaded from https://github.com/NWPU-903PR/DGMP.

C^3:Consensus Cancer Driver Gene Caller

Next-generation sequencing has allowed identification of millions of somatic mutations in human cancer cells.A key challenge in interpreting cancer genomes is to distinguish drivers of cancer development among available genetic mutations.To address this issue,we present the first webbased application,consensus cancer driver gene caller(C^3),to identify the consensus driver genes using six different complementary strategies,i.e.,frequency-based,machine learning-based,functional bias-based,clustering-based,statistics model-based,and network-based strategies.This application allows users to specify customized operations when calling driver genes,and provides solid statistical evaluations and interpretable visualizations on the integration results.C^3 is implemented in Python and is freely available for public use at http://drivergene.rwebox.com/c3.

驱动基因阴性非小细胞肺癌二线治疗中国专家共识

对于驱动基因阴性的晚期非小细胞肺癌(non-small cell lung cancer,NSCLC)患者而言,既往化疗一直都是标准治疗选择,而免疫检查点抑制剂(immune checkpoint inhibitors,ICIs)的加入为这部分患者提供了新的治疗选择。目前一线治疗可以选择化疗、抗血管生成药物或免疫治疗。尽管初始治疗能获得一定的有效率,但仍不可避免地会出现疾病进展或治疗失败,二线及以上治疗疗效差,患者预后不佳,临床上需要更多有效的二线治疗药物。中国临床肿瘤学会非小细胞肺癌专家委员会组织呼吸科、肿瘤科、病理科专家对驱动基因阴性人群临床研究证据进行了深入探讨,根据专家组讨论后广泛认可的临床诊疗经验,对驱动基因阴性NSCLC患者二线治疗制定了统一的专家共识,可作为中国临床医师选择驱动基因阴性NSCLC二线治疗的指导依据。

PD-1抑制剂联合一线化疗方案对晚期驱动基因阴性肺腺癌的效果及安全性分析

目的探讨程序性细胞死亡蛋白-1(PD-1)抑制剂联合一线化疗方案治疗晚期驱动基因阴性肺腺癌的效果及安全性。方法回顾性收集2019年1月至2021年12月收治的60例晚期驱动基因阴性的肺腺癌患者病历资料,依据治疗方式不同分组,将30例接受培美曲塞、顺铂联合PD-1抑制剂(信迪利单抗)治疗的病历资料纳入观察组另30例接受培美曲塞联合顺铂治疗的病历资料纳入对照组。对比2组患者治疗前、治疗30 d时2组临床疗效[客观缓解率(ORR)、疾病控制率(DCR)]、免疫功能[CD_(4)^(+)、CD_(8)^(+)、CD_(4)^(+)/CD_(8)^(+)]、肿瘤标志物[癌胚抗原(CEA)、细胞角蛋白19片段(CYFRA21-1)]、不良反应[恶心、粒细胞减少、肝功能异常、甲状腺功能异常、肺炎、皮疹、血小板降低]。结果观察组ORR显著高于对照组,差异有统计学意义(P<0.05);2组DCR比较差异无统计学意义(P>0.05);治疗后,观察组CD_(4)^(+)、CD_(4)^(+)/CD_(8)^(+)水平高于治疗前,且高于对照组(P<0.05);治疗后,2组CYFRA21-1、CEA水平均下降,且观察组低于对照组(P<0.05)。观察组甲状腺功能异常、肺炎、皮疹等发生例数显著多于对照组,差异有统计学意义(P<0.05)。结论PD-1抑制剂联合化疗一线治疗可有效改善晚期驱动基因阴性肺腺癌患者免疫功能,并降低肿瘤标志物水平,疗效确切。

河南豫东地区661例非小细胞肺癌常见驱动基因突变分析

目的分析河南豫东地区非小细胞肺癌(non-small cell lung cancers,NSCLC)患者常见驱动基因的突变情况。方法回顾性分析2022年3月至2023年7月就诊于商丘市第一人民医院的661例NSCLC患者,入组病例均采用了5种基因突变检测试剂盒(荧光PCR法)进行检测。应用统计学方法分析其临床特征与各驱动基因状态之间的关系。结果661例NSCLC中EGFR、KRAS、ALK、ROS1、PIK3CA、BRAF、HER2、RET、MET14和NRAS的突变率分别为47.35%、9.68%、5.45%、1.82%、2.87%、1.82%、1.21%、0.91%、0.61%和0%。EGFR、ROS1和HER2的突变更易发生在在女性患者中(P<0.05),而KRAS突变常发生于男性患者(P<0.05)。EGFR、KRAS和ALK突变在腺癌中的突变率显著高于鳞癌和非小细胞肺癌非特指型(NSCLC.NOS)(P<0.05),PIK3CA在NSCLC.NOS中的突变率最高。KRAS基因在Ⅰ+Ⅱ期的突变率显著高于Ⅲ+Ⅳ期(P<0.05),其他基因与临床分期无明显相关性。与吸烟者相比,非吸烟者的总驱动基因突变率明显较高(P<0.05),EGFR、ALK、PIK3CA、ROS1、BRAF和HER2常发生于非吸烟患者中(P<0.05),而KRAS基因更易发生于吸烟患者中(P<0.05)。沉渣细胞块标本10种驱动基因突变率78.67%,检出率显著高于其他类型标本(P<0.05)。结论EGFR、KRAS、ALK等常见驱动基因与患者性别、病理类型、临床分期以及吸烟具有一定的相关性。质控合格的沉渣细胞块标本用于基因检测的优势明显,可以在有条件的患者中广泛推广;ARMS-PCR法联合检测10种基因可作为初诊初治NSCLC患者的首选基因检测方法。

不同标本类型在非小细胞肺癌基因检测中的应用及意义

目的研究分析不同标本类型在非小细胞肺癌(NSCLC)患者的驱动基因检出率,并分析表皮生长因子受体(EGFR)、间变性淋巴瘤激酶(ALK)、C-ros原癌基因1-受体酪氨酸激酶(ROS1)、Kristen鼠肉瘤病毒原癌基因同源体(KRAS)、鼠类肉瘤滤过性毒菌致癌基因同源体B(BRAF)等驱动基因异常情况及与临床病理特征关系。方法收集2021年1月—2021年12月我院病理科明确诊断为NSCLC样本180例,包括手术切除标本25例,肺活检标本80例,恶性胸腔积液细胞蜡块标本29例,转移病灶标本46例,采用扩增阻滞突变系统(ARMS)法检测驱动基因突变状态。结果5种驱动基因的总突变率为53.33%(96/180),驱动基因突变可在不同标本类型中检出,不同标本间突变率比较差异无统计学意义(P>0.05)。EGFR基因突变率40.56%(73/180),性别及组织类型突变率比较差异有统计学意义(P<0.05),年龄类型突变率比较差异无统计学意义(P>0.05);KRAS基因突变率6.11%(11/180),其中性别类型突变率比较差异有统计学意义(P<0.05),年龄与组织类型突变率比较差异无统计学意义(P>0.05);ALK融合基因突变率4.44/%(8/180),年龄、性别及组织类型突变率比较差异无统计学意义(P>0.05);BRAF基因突变率1.11%(2/180),ROS1融合基因突变率1.11%(2/180)。结论不同标本类型均可检出驱动基因,增加了临床基因检测的取样途径。NSCLC患者EGFR基因突变率明显高于其他驱动基因,EGFR基因突变与患者性别及组织类型有差异,KRAS基因突变与患者性别有差异;ALK、ROS1、BRAF基因突变率较低,但指导NSCLC治疗有重要意义。多基因联合检测可一次获取更多驱动基因突变信息,能够更快、更全面地指导临床治疗。

靶向肿瘤驱动基因的胃癌治疗研究进展

随着胃癌致病机制深入解析及胃癌驱动基因的鉴定,靶向胃癌驱动基因的药物逐渐应用临床。其中,曲妥珠单抗作为首个胃癌靶向药物,通过靶向过表达的人表皮生长因子受体2(HER2)抑制肿瘤细胞的增殖、生存和转移等过程,已成为HER2阳性胃癌患者的一线治疗药物。雷莫芦单抗则通过靶向血管内皮生长因子受体2(VEGFR2)抑制肿瘤血管生成,用于晚期胃癌患者的二线治疗。此外,贝马利珠单抗和佐妥昔单抗分别靶向过度表达的成纤维细胞生长因子受体2(FGFR2)和紧密连接蛋白18.2(CLDN18.2),在临床试验中显著延长胃癌患者的无进展生存期和总生存期。本文回顾了靶向HER2、VEGF、FGFR2、CLDN18.2和MET等肿瘤驱动基因的胃癌治疗策略,介绍了肿瘤驱动基因在胃癌进程中的作用及其靶向药物的应用,以期为胃癌靶向治疗药物的研发和临床应用提供参考。

原发性血小板增多症患者中JAK2、CALR及三阴性驱动突变的临床特征比较

目的:探讨原发性血小板增多症(ET)患者的突变基因与临床特征的关系。方法:对2018年10月至2022年3月69例ET患者的临床资料进行回顾性分析。将患者按突变的驱动基因类型分为JAK2组、CALR组与三阴性组,对3组患者的性别、年龄、心血管危险因素、血栓、脾肿大、血常规、凝血状态进行分析。结果:69例ET患者中,46例伴随JAK2基因突变,14例伴随CALR基因突变,8例为三阴性,1例伴随MPL基因突变。3组患者的年龄、性别无显著差异(P>0.05)。JAK2组血栓率最高,为26.09%(12/46),三阴性组为12.5%(1/8),CALR组无血栓事件。JAK2组伴随脾肿大发生率最高,为34.78%(16/46),而三阴性组无脾肿大发生。JAK2组的白细胞数为(9.00±4.86)×10^(9)/L,显著高于CALR组的(6.03±2.32)×10^(9)/L(P<0.05)。JAK2组的血红蛋白含量为(148.43±18.79)g/L,显著高于三阴性组的(131.00±15.17)g/L(P<0.05)。JAK2组的红细胞压积为(0.44±0.06)%,亦显著高于三阴性组的(0.39±0.05)%(P<0.05)。JAK2组血小板数为(584.17±175.77)×10^(9)/L,显著低于CALR组的(703.07±225.60)×10^(9)/L(P<0.05)。JAK2组和三阴性组纤维蛋白原含量分别为(2.64±0.69)g/L和(3.05±0.77)g/L,均显著高于CALR组的(2.24±0.47)g/L(P<0.05,P<0.01)。三阴性组活化部分凝血活酶时间为(28.61±1.99)s,较CALR组的(31.45±3.35)s显著降低(P<0.05)。结论:不同驱动基因突变ET患者的血细胞计数与凝血状态存在差异。与CALR组相比,JAK2组血栓率、白细胞数和纤维蛋白原含量均显著升高,而血小板数显著降低;与三阴性组相比,JAK2组脾大发生率和红细胞压积显著升高;与CALR组相比,三阴性组的纤维蛋白原含量显著升高、活化部分凝血活酶时间显著降低。

肺癌驱动基因检测研究进展

肺癌靶向治疗为晚期非小细胞肺癌患者的生存带来了希望,而肺癌驱动基因的检测为肺癌的靶向治疗提供了证据。临床中,只有准确的检测出肺癌相关的驱动基因突变,才能正确的选择靶向治疗的优势人群,进而达到肺癌精准治疗的目标。因此,在肺癌的临床诊治中,驱动基因检测的准确性显得尤为重要。临床医师应该重视肺癌驱动基因检测结果的准确性。本文现就肺癌驱动基因检测的研究进展作一综述,以帮助临床医师更规范的进行肺癌驱动基因的检测。

浸润性肺腺癌的倍增时间与驱动基因状态的相关性

目的比较伴或不伴基因突变的原发性肺腺癌在体积倍增时间(volume doubling time,VDT)和质量倍增时间(mass doubling time,MDT)间的差异。方法选取2019年1月—2020年12月在同济大学附属上海市肺科医院进行手术治疗且术前至少进行2次胸部非增强CT扫描的患者为研究对象。根据放射科医师手工分割的三维掩模计算VDT和MDT。采用Bland-Altman方法进行观察者内变异性评估。采用Mann-Whitney U检验比较驱动基因有无突变肿瘤的VDT和MDT差异。采用Kruskal-Wallis检验比较不同EGFR突变位点VDT和MDT的差异。结果共计279例患者(男性99例,女性280例),平均年龄(62.15±8.90)岁,共287个结节。根据驱动基因状态分为突变组72例,野生组215例,基因突变发生率为74.9%(215/287)。突变组和野生组MDT在驱动基因状态上的差异有统计学意义(537 d vs 824 d,P=0.004),VDT的差异无统计学意义(767 d vs 593 d)。EGFR阳性腺癌的MDT比EGFR阴性腺癌长,但VDT差异并不显著(VDT,758 d vs 593 d,P=0.382;MDT,824 d vs 537 d,P=0.004)。在生长结节中,驱动基因阳性腺癌的VDT和MDT均比野生型腺癌长(VDT,759 d vs 592 d,P=0.048;MDT,749 d vs 499 d,P<0.001;VDT,768 d vs 593 d,P=0.081,MDT,737 d vs 518 d,P=0.001)。结论在原发性浸润性肺腺癌中,驱动基因阳性(尤其是EGFR阳性)的肿瘤倍增时间更长,且在生长中的结节中更为显著。

安罗替尼联合复方斑蝥胶囊治疗不耐受化疗的驱动基因阴性晚期NSCLC合并COPD的效果

目的:探讨安罗替尼联合复方斑蝥胶囊治疗不耐受化疗的驱动基因阴性晚期非小细胞肺癌(NSCLC)合并慢性阻塞性肺疾病(COPD)的效果。方法:选取2021年10月—2022年12月抚州市第一人民医院收治的48例不耐受化疗的驱动基因阴性晚期NSCLC合并COPD患者,按随机数字表法分为试验组和对照组,每组24例。对照组采用复方斑蝥胶囊治疗,试验组在对照组的基础上采用安罗替尼治疗,两组均治疗2个疗程。比较两组近期疗效、细胞生长相关因子[血管内皮细胞生长因子(VEGF)、基质金属蛋白酶-9(MMP-9)]、肿瘤标志物[鳞状细胞癌抗原(SCCA)、癌胚抗原(CEA)、细胞角蛋白19片段(Cyfra21-1)]、生活质量及不良反应发生情况。结果:试验组疾病控制率高于对照组,治疗后VEGF、MMP-9、SCCA、CEA、Cyfra21-1水平均低于对照组,生活质量优于对照组,差异均有统计学意义(P<0.05);两组不良反应发生率比较,差异无统计学意义(P>0.05)。结论:安罗替尼联合复方斑蝥胶囊治疗不耐受化疗驱动基因阴性晚期NSCLC合并COPD患者的安全性较高,且能降低肿瘤标志物水平,改善生活质量,增强治疗效果。

青年型肺腺癌临床特征及驱动基因突变的研究进展

近年来,随着低剂量螺旋CT(low-dose CT,LDCT)在肺癌筛查中的应用,越来越多的年轻患者被确诊为肺癌。虽然青年非小细胞肺癌(non-small cell lung cancer,NSCLC)患者(≤45岁)占比较低,但其有独特的临床病理特征及基因突变位点。肺腺癌作为年轻患者中最常见的NSCLC病理类型,其致癌基因改变(genomic alterations,GAs)和临床特征研究较少。随着肺癌个体化治疗观念的提出,其群体研究也逐渐受到重视。因此对青年肺腺癌进行研究极具临床意义。本文就青年肺腺癌患者的发病趋势、病理特征和驱动基因突变等特点作一综述。

安罗替尼联合信迪利单抗同步放化疗治疗驱动基因阴性非小细胞肺癌临床研究

目的探讨安罗替尼联合信迪利单抗同步放化疗一线治疗驱动基因阴性非小细胞肺癌(NSCLC)的临床疗效和安全性。方法选取苏州大学附属张家港医院2021年3月至2022年3月收治的驱动基因阴性NSCLC患者80例,按随机数字表法分为观察组和对照组,各40例。对照组患者给予NP化疗方案(顺铂30 mg/m^(2)+长春瑞滨25 mg/m^(2))+肺内原发灶和区域淋巴结放射治疗,观察组患者在对照组基础上加用安罗替尼联合信迪利单抗200 mg/m^(2)(第1天)。两组患者均以21 d为1个周期,共治疗4个周期。结果观察组客观缓解率和疾病控制率分别为72.50%和85.00%,均显著高于对照组的37.50%和52.50%(P<0.05)。治疗后,两组患者血清癌胚抗原(CEA)、糖类抗原125(CA125)、细胞角质蛋白19片段抗原21-1(CYFRA21-1)水平均显著降低(P<0.05),生活质量调查核心问卷(QLQ-C30)和肺癌专用问卷(QLQ-LC13)评分均显著升高(P<0.05),且观察组均显著优于对照组(P<0.05)。观察组和对照组患者Ⅲ级及以上不良反应发生率相当(62.50%比52.50%,P>0.05)。所有患者的中位随访时间为15个月(12~24个月),失访3例。观察组中位无进展生存期(PFS)和中位总生存期(OS)分别为6.9个月和12.6个月,均显著长于对照组的4.3个月和8.9个月(Log-rankχ2=13.760,31.830,P<0.05)。结论安罗替尼联合信迪利单抗同步放化疗可提高驱动基因阴性NSCLC患者的临床疗效,改善生活质量,降低血清肿瘤标志物水平,延长生存时间,且安全性高。

Establishment and application of a multiplex genetic mutation-detection method of lung cancer based on MassARRAY platform

Objective: This study aims to establish a method for highly parallel multiplexed detection of genetic mutations in Chinese lung cancer samples through Agena i PLEX chemistry and matrix-assisted laser desorption ionization time-of-flight analysis on Mass ARRAY mass spectrometry platform.Methods: We reviewed the related literature and data on lung cancer treatments. We also identified 99 mutation hot spots in 13 target genes closely related to the pathogenesis, drug resistance, and metastasis of lung cancer. A total of 297 primers, composed of99 paired forward and reverse amplification primers and 99 matched extension primers, were designed using Assay Design software. The detection method was established by analyzing eight cell lines and six lung cancer specimens. The proposed method was then validated through comparisons by using a Lung Carta^(TM) kit. The sensitivity and specificity of the proposed method were evaluated by directly sequencing EGFR and KRAS genes in 100 lung cancer cases.Results: The proposed method was able to detect multiplex genetic mutations in lung cancer cell lines. This finding was consistent with the observations on previously reported mutations. The proposed method can also detect such mutations in clinical lung cancer specimens. This result was consistent with the observations with Lung Carta^(TM) kit. However, an FGFR2 mutation was detected only through the proposed method. The measured sensitivity and specificity were 100% and 96.3%, respectively.Conclusions: The proposed Mass ARRAY technology-based multiplex method can detect genetic mutations in Chinese lung cancer patients. Therefore, the proposed method can be applied to detect mutations in other cancer tissues.

Target genes discovery through copy number alteration analysis in human hepatocellular carcinoma

High-throughput short-read sequencing of exomes and whole cancer genomes in multiple human hepatocellular carcinoma(HCC)cohorts confirmed previously identified frequently mutated somatic genes,such as TP53,CTNNB1 and AXIN1,and identified several novel genes with moderate mutation frequencies,including ARID1A,ARID2,MLL,MLL2,MLL3,MLL4,IRF2,ATM,CDKN2A,FGF19,PIK3CA,RPS6KA3,JAK1,KEAP1,NFE2L2,C16orf62,LEPR,RAC2,and IL6ST.Functional classification of these mutated genes suggested that alterations in pathways participating in chromatin remodeling,Wnt/β-catenin signaling,JAK/STAT signaling,and oxidative stress play critical roles in HCC tumorigenesis.Nevertheless,because there are few druggable genes used in HCC therapy,the identification of new therapeutic targets through integrated genomic approaches remains an important task.Because a large amount of HCC genomic data genotyped by high density single nucleotide polymorphism arrays is deposited in the public domain,copy number alteration(CNA)analyses of these arrays is a cost-effective way to reveal target genes through profiling of recurrent and overlapping amplicons,homozygous deletions and potentially unbalanced chromosomal translocations accumulated during HCC progression.Moreover,integration of CNAs with other high-throughput genomic data,such as aberrantly coding transcriptomes and non-coding gene expression in human HCC tissues and rodent HCC models,provides lines of evidence that can be used to facilitate the identification of novel HCC target genes with the potential of improving the survival of HCC patients.

基于全外显子组测序对头皮皮脂腺癌的基因分析

【目的】在全外显子组水平对比头皮皮脂腺癌(SC)和头皮皮脂腺瘤(SA)的相关致病性基因突变的差异。【方法】对经过病理诊断的头皮SC和SA样本各1例,利用Illumina HiSeq 2500平台进行全外显子组测序(WES)。筛选可疑的单核苷酸变异位点,进行突变的保守性和功能分析。利用SciClone软件来追踪亚克隆进化可以得到每例肿瘤样本的克隆性图谱信息。通过MutSigCV软件筛选得到高频显著基因,将体细胞变异与已知驱动基因进行比较,筛选出该肿瘤样本中的已知驱动基因。【结果】经过对比发现,与头皮SA相比,SC存在两个驱动基因ACVR1B和TFDP1的基因突变。【结论】头皮SC驱动基因ACVR1B和TFDP1的基因突变如果能在更大的病例队列中得到证实,对其发生的可能机制以及治疗靶点有重要的意义。

驱动基因突变非小细胞肺癌免疫治疗的研究进展

随着肺癌靶点的发现和药物研发,靶向治疗改善了驱动基因突变非小细胞肺癌(NSCLC)的临床预后。同时,免疫检查点抑制剂在驱动基因阴性NSCLC中也取得了良好的疗效。虽然部分驱动基因突变患者从对应靶向治疗中明显获益,但对免疫治疗反应欠佳。在大部分免疫治疗临床研究和日常实践中,EGFR/ALK等驱动基因突变阳性的NSCLC患者也被排除在外,或者仅占少数。免疫治疗如何应用于驱动基因突变患者,以及如何在靶向治疗、化疗及免疫治疗中选择最佳治疗方案,制定最优治疗策略,对改善晚期驱动基因突变NSCLC患者预后至关重要。本文对不同基因突变肿瘤免疫微环境的特点及免疫治疗在不同基因突变的NSCLC患者中的应用进行简要综述。

驱动基因阳性非小细胞肺癌的免疫检查点抑制剂治疗的研究进展

非小细胞肺癌(NSCLC)是中国肺癌最常见的病理分型。随着精准医疗的发展,靶向治疗和免疫治疗被广泛应用于恶性肿瘤患者的治疗中,并极大地改善了患者的预后和生存周期。大部分NSCLC患者存在驱动基因突变。以程序性死亡分子-1(PD-1)/程序性死亡因子配体-1(PD-L1)抗体为代表的免疫检查点抑制剂(ICIs)在驱动基因阴性晚期NSCLC患者中取得良好的临床效果,且在部分情况下可作为一线及二线治疗的标准方案。但ICIs治疗在驱动基因阳性NSCLC患者中的应用仍存在争议。本研究对驱动基因阳性NSCLC的免疫特征进行分析,并就ICIs治疗对驱动基因阳性NSCLC患者的应用效果进行综述。