根据在癌突变谱中的共突变基因对识别癌基因

癌是一种涉及多基因变异的遗传异质性疾病,涉及多种生物学功能通路中不同基因的遗传变异。因此,识别癌基因是一项富有挑战性的工作。提出通过寻找在癌样本中突变显著共发生的基因筛选候选癌基因的方法。应用该方法,通过分析蛋白激酶基因在癌组织中的突变谱数据,发现了167个显著共发生突变的基因对,包含85个基因。分析这167个基因对发现:(1)发生共突变的基因富集已知的癌基因;(2)共突变基因对倾向于共扰动与癌症相关的通路对。以上结果提示,在癌样本中显著共发生突变的基因倾向于候选癌基因;在癌发生过程中起重要作用的基因倾向于协同扰动不同的癌相关细胞生物学过程。     

阿霉素诱导下的肝癌细胞HepG2中微小RNA差异表达分析

旨在研究阿霉素诱导引起的DNA损伤压力下,肝癌细胞Hep G2中参与DNA损伤应答的mi RNA,并分析这些mi RNA靶基因参与肝癌DNA损伤应答相关的生物学进程与通路。通过小RNA测序检测阿霉素处理肝癌细胞Hep G2前后mi RNA的差异表达情况,使用GO与KEGG通路富集方法对差异表达mi RNA靶基因进行功能富集分析。结果显示,共检测出显著表达差异mi RNA 68个,其中上调13个,下调55个。mi RNA靶基因的功能分析结果显示,53条mi RNAs靶基因显著富集于调控细胞增殖、细胞凋亡、细胞迁移和细胞周期等与DNA损伤应答以及肿瘤相关的生物进程和信号通路,包括p53信号通路、癌症通路、Wnt信号通路和MAPK信号通路等。研究表明,在阿霉素诱导下,Hep G2中的差异表达mi RNAs与DNA损伤相关的肿瘤生物学进程以及信号通路显著相关,预示这些mi RNAs在阿霉素引发的肝细胞癌DNA损伤应答中起着重要的作用。     

Hsa-miR-125b在人胃癌耐药细胞株中的表达及其靶基因的功能分析

研究表明, Hsa-miR-125b在人胃癌耐氟尿嘧啶细胞株BGC823/Fu中表达下降。为进一步探讨hsa-miR-125b在获得性耐药中所起的作用, 文章应用miRbase、靶基因预测软件、Gene Ontology数据库及KEGG数据库对hsa-miR-125b的序列特征、进化保守性、靶基因及功能以及靶基因所参与的信号通路等进行了深入的生物信息学分析。结果显示：has-miR-125b在多个物种之间具有高度序列保守性; 通过软件预测获得hsa-miR- 125b 靶基因79个, 其分子功能包括转录调节、蛋白质结合和肽酶类活性等(P<0.001), 其所参与的生物学过程主要有细胞周期、细胞增殖、细胞凋亡的正性或负性调控以及细胞因子刺激反应性、药物反应性、DNA损伤反应性等(P<0.001), 调控包括MAPK、Wnt、p53等多条信号转导通路(P<0.01)。上述结果表明hsa-miR-125b可能参与调控多个生物学过程和信号转导通路, 而其中细胞增殖、细胞凋亡、细胞周期等生物学过程以及MAPK、Wnt、p53等信号通路已被证实与肿瘤耐药的发生有关。因此, hsa-miR-125b可能通过调控上述环节中的靶基因来影响肿瘤细胞对药物的敏感性, 从而为hsa-miR-125b在肿瘤耐药中的作用机制提供新的研究线索。     

hsa-miR-381-3p靶基因预测及其相关信号通路的生物信息学分析

应用生物信息学方法分析miR-381-3p序列,预测其靶基因,并对靶基因进行蛋白质互作分析、功能富集分析及信号转导通路富集分析。结果发现,已知的成熟miR-381-3p序列在不同物种间高度保守。蛋白质互作分析显示,mi R-381-3p预测靶基因所编码蛋白质间存在复杂的相互作用,尤其是靶基因BTBD1、NUP160、STX16等编码的蛋白质,在互作中起关键作用。GO分析发现其靶基因集合可能参与细胞过程、生物调节、细胞大分子代谢等生物学过程;KEGG通路分析发现其靶基因集合显著富集于mTOR、Wnt、p53、MAPK等信号通路中。分析结果初步提示miR-381-3p通过调控靶基因广泛参与多种重要的生物学过程,为后续的实验性研究提供了线索。     

多糖调控p53信号网络研究进展

肿瘤抑制基因p53是目前研究最广泛和系统的抑癌基因之一。p53与其上、下游基因形成复杂的信号网络来发挥功能。p53基因的突变或缺失与多种人类恶性肿瘤的发生、发展密切相关,所以p53基因是目前多种抗肿瘤药物开发的靶点。多糖由于其低毒和抗肿瘤效果成为生物大分子抗肿瘤的研究热点。目前认为,多糖在体内外抗肿瘤机制有两方面:一是通过增强机体免疫力以抑制肿瘤增殖,另一则是激活胞内信号通路,调控肿瘤相关基因表达,诱导肿瘤细胞衰老、细胞周期阻滞与凋亡达到对肿瘤细胞的抑制作用。该文综述了近些年多糖通过调控p53信号网络来发挥其抗肿瘤及抗衰老等作用,为多糖的开发与利用提供参考依据。     

褪黑素联合顺铂对A549细胞凋亡相关基因的影响

观察褪黑素以及褪黑素联合顺铂是否可以抑制A549细胞增殖并促进细胞凋亡,探讨ERK1/2MAPK信号通路在这一过程中的作用,为肺腺癌的研究提供实验依据。用不同浓度的褪黑素、不同浓度的顺铂、褪黑素联合顺铂刺激体外培养的肺腺癌细胞系A549细胞,MTT法检测各组细胞的活性,运用Real-time RT-PCR检测凋亡相关基因Bcl-2、Bax、p53的表达水平,Western-blot检测ERK1/2MAPK的活性变化。结果:1)单纯使用褪黑素和顺铂均可抑制A549细胞增殖,褪黑素联合顺铂时,抑制作用更加显著,一定浓度的褪黑素可降低顺铂的使用浓度;2)未经处理的A549细胞Bcl-2/Bax很高,p53基因表达较低,经褪黑素以及褪黑素联合顺铂刺激后A549细胞中Bcl-2/Bax明显下降,p53基因表达明显升高,并有浓度依赖;3)经褪黑素和顺铂刺激后A549细胞中磷酸化ERK1/2MAPK水平明显降低。褪黑素联合顺铂可抑制A549细胞增殖并且诱导凋亡相关基因表达,褪黑素和顺铂对A549细胞的抑制作用可能与ERK1/2MAPK信号通路有关。     

Wnt与MAPK信号通路在肿瘤发生中的串话

Wnt和MAPK信号通路在生物进化过程中高度保守,参与调控胚胎发育和细胞增殖、分化及凋亡等。Wnt和MAPK信号通路调控失常可导致胚胎发育异常和肿瘤形成。近年来发现这两条信号通路在肿瘤发生发展中存在着大量串话（crosstalk）,彼此之间相互调节,共同发挥促癌或抑癌作用,因此,更好地了解两条通路是如何在肿瘤形成中发生交叉对话对于将来肿瘤治疗非常有价值。     

PDZ连接激酶，又一新的原癌基因

PDZ连接激酶(PBK)是一种丝-苏氨酸激酶,属于丝裂原活化蛋白激酶激酶(MAPKK)家族成员.PBK能调控细胞周期进程,促进细胞增殖.近年发现,其在乳腺癌、结肠癌、皮肤癌和前列腺癌等多种恶性肿瘤组织中均呈高表达,与多种癌症预后不良关联密切.PBK主要通过Wnt、PI3K/AKT/mTOR和MAPK等信号通路,调控肿瘤细胞有丝分裂,参与多种癌症的增殖、侵袭转移和耐药等,并受miR-216b-3p、miR-770-5p和miR-372-5p等多种microRNA调控.提示PBK可能作为又一新的原癌基因,有望成为抑癌药物新的分子靶点.     

Wnt/β-catenin信号通路与肝癌

肝细胞癌是常见的恶性肿瘤,其发病机制尚未完全明确。Wnt信号通路与人体内多种病理生理过程相关,其中肝癌的发生、发展可能与经典的Wnt/β-catenin信号通路密切相关。Wnt/β-catein信号通路通过表达癌症相关基因、激活肝星状细胞、调控肝干细胞行为、促进肝癌细胞侵袭转移等方式调控肝癌的发生、发展。Wnt/β-catein信号通路在肝癌发生、发展中的作用有望为肝癌研究提供新的思路。     

肝细胞癌中抑癌基因的发现与研究进展

肝细胞癌（HCC）的发病率高、治疗效果差。HCC的发病机制复杂,主要有2类：肝炎、酒精、黄曲霉素、代谢紊乱引起的肝损伤,进而导致的肝硬化;致癌基因和抑癌基因的突变或对应染色体区域的扩增或缺失。细胞内一些信号通路参与了HCC的发生发展,包括RAF／MEK／ERK、P13K／AKT／mTOR、WNT/β-catenin、胰岛素样生长因子、肝细胞生长因子／c-MET、生长因子调节的血管新生等6类信号通路。抑癌基因通过调节信号通路而调节细胞增殖、细胞周期、细胞凋亡等对肿瘤的发生、发展起重要作用的过程。我们简要概述HCC相关的肿瘤抑制分子及其所在的信号通路及作用的分子机制。     

肺腺癌预后相关miRNA生物信息学筛选及其临床意义

目的：探讨肺腺癌预后相关miRNA组学特征及其临床意义。方法：应用癌症基因组图谱（TCGA）数据库,检索人肺腺癌miRNA表达谱数据,进行差异分析,再利用Cox风险回归模型筛选预后相关miRNA;利用mirwalk分析平台,对筛选出的miRNA进行靶向调控基因预测、KEGG功能富集分析,最后,预测出预后相关miRNA的功能。结果：共筛选肺腺癌差异miRNA46个,其中,上调19个、下调27个;通过Cox生存分析筛选到预后相关miRNA有6个,即hsa-mir-21、hsa-mir-142、hsa-mir-200a高表达,hsa-mir-101、hsa-let-7c、hsa-mir-378e低表达,其中hsa-mir-21、hsa-mir-378e与肺腺癌患者不良预后有关,生存期显著缩短（P<0.05,AUC=0.618）。KEGG分析上述预后相关miRNA靶向调控基因与免疫反应通路、miRNA与癌症通路、代谢通路等有关。结论：hsa-mir-21、hsa-mir-378e与肺腺癌预后不良有关,未来经进一步临床验证有可能作为肺腺癌预后相关的分子标记物。     

BRCA1/2 mutation screening and LOH analysis of lung adenocarcinoma tissue in a multiple-cancer patient with a strong family history of breast cancer

BACKGROUND: Germline mutations in BRCA1/2 greatly elevate risks of breast and ovarian cancers, but the role of these genes in tumourigenesis of other cancer types is still being investigated. OBJECTIVE: We report on an investigation of BRCA1/2 mutations and their loss of heterozygosity (LOH) in a patient with a strong family history of breast cancer who was diagnosed with consecutive primary cervical, ovarian and lung carcinomas. METHODS AND RESULTS: BRCA1/2 mutation screening of the proband revealed a common familial breast- and ovarian cancer-associated germline BRCA2 mutation (3034del4bp). We then performed LOH analysis for BRCA2 in lung adenocarcinoma tissue of the patient. Using the laser-capture microdissection (LCM) technique, we obtained pure populations of neoplastic cells from which DNA could be extracted. Mutation analysis by denaturing high-performance liquid chromatography (DHPLC) and direct sequencing revealed loss of the mutant allele in the adenocarcinoma tumour tissue. CONCLUSION: To our knowledge, this is the first report of investigation for LOH for BRCA2 in primary lung adenocarcinoma tissue of a patient with multiple primary tumours related to a familial germline BRCA2 mutation. Interestingly, it was the mutant, not the wild-type, allele which was lost in the lung adenocarcinoma tissue.     

Finding co-mutated genes and candidate cancer genes in cancer genomes by stratified false discovery rate control

Finding candidate cancer genes playing causal roles in carcinogenesis is an important task in cancer research. The non-randomness of the co-mutation of genes in cancer samples can provide statistical evidence for these genes' involvement in carcinogenesis. It can also provide important information on the functional cooperation of gene mutations in cancer. However, due to the relatively small sample sizes used in current high-throughput somatic mutation screening studies and the extraordinary large-scale hypothesis tests, the statistical power of finding co-mutated gene pairs based on high-throughput somatic mutation data of cancer genomes is very low. Thus, we proposed a stratified FDR (False Discovery Rate) control approach, for identifying significantly co-mutated gene pairs according to the mutation frequency of genes. We then compared the identified co-mutated gene pairs separately by pre-selecting genes with higher mutation frequencies and by the stratified FDR control approach. Finally, we searched for pairs of pathways annotated with significantly more between-pathway co-mutated gene pairs to evaluate the functional roles of the identified co-mutated gene pairs. Based on two datasets of somatic mutations in cancer genomes, we demonstrated that, at a given FDR level, the power of finding co-mutated gene pairs could be increased by pre-selecting genes with higher mutation frequencies. However, many true co-mutation between genes with lower mutation rates will still be missed. By the stratified FDR control approach, many more co-mutated gene pairs could be found. Finally, the identified pathway pairs significantly overrepresented with between-pathway co-mutated gene pairs suggested that their co-dysregulations may play causal roles in carcinogenesis. The stratified FDR control strategy is efficient in identifying co-mutated gene pairs and the genes in the identified co-mutated gene pairs can be considered as candidate cancer genes because their non-random co-mutations in cancer genomes are highly unlikely to be attributable to chance.     

Combination therapy with KRAS siRNA and EGFR inhibitor AZD8931 suppresses lung cancer cell growth in vitro

Lung cancer is a leading cause of cancer-related deaths worldwide, with less than a 5-year survival rate for both men and women. Epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma oncogene (KRAS) signaling pathways play a critical role in the proliferation and progression of various cancers, including lung cancer. Genetic studies have shown that amplification, over-expression, or mutation of EGFR is an early and major molecular event in many human tumors. KRAS mutation is a negative factor in various cancer, including non-small-cell lung cancer, and complicates therapeutic approaches with adjuvant chemotherapy and anti-EGFR directed therapies. This article is dedicated to evaluating the synergistic effect of a novel EGFR inhibitor AZD8931 and KRAS small interfering RNA (siRNA) on the proliferation and apoptosis of lung adenocarcinoma cancer cells. A549 lung cancer cells were treated with KRAS siRNA and the EGFR inhibitor alone or in combination. The cytotoxic effects of KRAS siRNA and te EGFR inhibitor were determined usingMTT assay, and induction of apoptosis was determined by FACS analysis. Suppression of KRAS, Her-2, and EGFR expression by treatments was measured by qRT-PCR and western blotting. KRAS siRNA and the EGFR inhibitor significantly reduced the proliferation of A549 cells as well as KRAS and EGFR mRNA levels 24 hr after treatment. The results also indicated that the silencing of KRAS and EGFR has synergistic effects on the induction of apoptosis on the A549 cells. These results indicated that KRAS and EGFR might play important roles in the progression of lung cancer and could be potential therapeutic targets for treatment of lung cancer.     

胸腔积液中肺腺癌细胞EGFR突变状态与DNA含量的相关性

摘要 目的：探究胸腔积液中肺腺癌细胞表皮生长因子受体（epidermalgrowthfactorreceptor,EGFR）突变状态与DNA含量的相关性,以期探究EGFR突变状态是否同肿瘤的恶性程度存在一定关联。方法：选择2015年1月至2020年1月于我院接受EGFR基因检测以及基因定量分析的591例肺腺癌患者为研究对象,按照其是否出现EGFR基因突变将其分为突变组（335例）与非突变组（256例）,两组患者的胸腔积液均使用激光图像细胞仪开展DNA含量以及非整倍体峰检测,并开展组间差异性比较。结果：（1）将591例患者按照年龄、性别及是否吸烟等临床特征进行分组对比显示,性别（P=0.034）与吸烟（P=0.007）同肺腺癌患者胸腔积液细胞出现EGFR突变具有一定关联,而年龄因素与是否出现突变无明显相关性（P>0.05）;（2）突变组患者的最大DNA指数（DI）、大于5C细胞的平均DI以及大于9C细胞的平均DI均明显高于非突变组,组间差异明显（P<0.05）;（3）开展DNA非整倍体细胞峰比较显示突变组在单峰、双峰占比中明显高于非突变组,而无峰占比明显低于非突变组（P<0.05）,多峰占比方面两组差异不大（P>0.05）。结论：经研究显示,同未出现EGFR突变的肺腺癌患者相比较,发生EGFR突变的肺腺癌患者明显DI值更高,非整倍体细胞以及非整倍体峰值也呈现异常升高态,这提示EGFR发生突变的肺腺癌患者恶变洗吧的侵袭性更强。     

Ion Channel Gene Expression in Lung Adenocarcinoma: Potential Role in Prognosis and Diagnosis

Ion channels are known to regulate cancer processes at all stages. The roles of ion channels in cancer pathology are extremely diverse. We systematically analyzed the expression patterns of ion channel genes in lung adenocarcinoma. First, we compared the expression of ion channel genes between normal and tumor tissues in patients with lung adenocarcinoma. Thirty-seven ion channel genes were identified as being differentially expressed between the two groups. Next, we investigated the prognostic power of ion channel genes in lung adenocarcinoma. We assigned a risk score to each lung adenocarcinoma patient based on the expression of the differentially expressed ion channel genes. We demonstrated that the risk score effectively predicted overall survival and recurrence-free survival in lung adenocarcinoma. We also found that the risk scores for ever-smokers were higher than those for never-smokers. Multivariate analysis indicated that the risk score was a significant prognostic factor for survival, which is independent of patient age, gender, stage, smoking history, Myc level, and EGFR/KRAS/ALK gene mutation status. Finally, we investigated the difference in ion channel gene expression between the two major subtypes of non-small cell lung cancer: adenocarcinoma and squamous-cell carcinoma. Thirty ion channel genes were identified as being differentially expressed between the two groups. We suggest that ion channel gene expression can be used to improve the subtype classification in non-small cell lung cancer at the molecular level. The findings in this study have been validated in several independent lung cancer cohorts.     

VarWalker: Personalized Mutation Network Analysis of Putative Cancer Genes from Next-Generation Sequencing Data

A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data.     

DNA methylation-based diagnostic and prognostic biomarkers of nonsmoking lung adenocarcinoma patients

Currently, there are few studies on patients with nonsmoking lung adenocarcinoma, and the pathogenesis is still unclear. The role of DNA methylation in the pathogenesis of cancer is gradually being recognized. The purpose of this study was to determine the abnormal methylation genes and pathways involved in nonsmoking lung adenocarcinoma patients. Gene expression microarray data (GSE10072, GSE43458) and gene methylation microarray data (GSE62948) were downloaded from the Gene Expression Omnibus (GEO) database and differentially expressed genes were obtained through GEO2R. Next, we analyzed the function and enrichment of the selected genes using Database for Annotation, Visualization, and Integrated Discovery. The protein-protein interaction (PPI) networks were constructed using the Search Tool for the Retrieval of Interacting Genes database and visualized in Cytoscape. Finally, we performed module analysis of the PPI network using Molecular Complex Detection. And we obtained 10 hub genes by Cytoscape Centiscape. We analyzed the independent prognostic value of each hub gene in nonsmoking nonsmall cell lung cancer patients through Kaplan-Meier plotter. Seven hub genes (CXCL12, CDH1, CASP3, CREB1, COL1A1, ERBB2, and ENO2) were closely related to the overall survival time. This study provides an effective bioinformatics basis for further understanding the pathogenesis and prognosis of nonsmoking lung adenocarcinoma patients. Hub genes with prognostic value could be selected as effective biomarkers for timely diagnosis and prognostic of nonsmoking lung adenocarcinoma patients.     

Exhaled Breath Analysis for Lung Cancer Detection Using Ion Mobility Spectrometry

Background

Conventional methods for lung cancer detection including computed tomography (CT) and bronchoscopy are expensive and invasive. Thus, there is still a need for an optimal lung cancer detection technique.

Methods

The exhaled breath of 50 patients with lung cancer histologically proven by bronchoscopic biopsy samples (32 adenocarcinomas, 10 squamous cell carcinomas, 8 small cell carcinomas), were analyzed using ion mobility spectrometry (IMS) and compared with 39 healthy volunteers. As a secondary assessment, we compared adenocarcinoma patients with and without epidermal growth factor receptor (EGFR) mutation.

Results

A decision tree algorithm could separate patients with lung cancer including adenocarcinoma, squamous cell carcinoma and small cell carcinoma. One hundred-fifteen separated volatile organic compound (VOC) peaks were analyzed. Peak-2 noted as n-Dodecane using the IMS database was able to separate values with a sensitivity of 70.0% and a specificity of 89.7%. Incorporating a decision tree algorithm starting with n-Dodecane, a sensitivity of 76% and specificity of 100% was achieved. Comparing VOC peaks between adenocarcinoma and healthy subjects, n-Dodecane was able to separate values with a sensitivity of 81.3% and a specificity of 89.7%. Fourteen patients positive for EGFR mutation displayed a significantly higher n-Dodecane than for the 14 patients negative for EGFR (p<0.01), with a sensitivity of 85.7% and a specificity of 78.6%.

Conclusion

In this prospective study, VOC peak patterns using a decision tree algorithm were useful in the detection of lung cancer. Moreover, n-Dodecane analysis from adenocarcinoma patients might be useful to discriminate the EGFR mutation.