Identification and Characterization of Cells with Cancer Stem Cell Properties in Human Primary Lung Cancer Cell Lines

Lung cancer (LC) with its different subtypes is generally known as a therapy resistant cancer with the highest morbidity rate worldwide. Therapy resistance of a tumor is thought to be related to cancer stem cells (CSCs) within the tumors. There have been indications that the lung cancer is propagated and maintained by a small population of CSCs. To study this question we established a panel of 15 primary lung cancer cell lines (PLCCLs) from 20 fresh primary tumors using a robust serum-free culture system. We subsequently focused on identification of lung CSCs by studying these cell lines derived from 4 representative lung cancer subtypes such as small cell lung cancer (SCLC), large cell carcinoma (LCC), squamous cell carcinoma (SCC) and adenocarcinoma (AC). We identified a small population of cells strongly positive for CD44 (CD44^high) and a main population which was either weakly positive or negative for CD44 (CD44^low/−). Co-expression of CD90 further narrowed down the putative stem cell population in PLCCLs from SCLC and LCC as spheroid-forming cells were mainly found within the CD44^highCD90⁺ sub-population. Moreover, these CD44^highCD90⁺ cells revealed mesenchymal morphology, increased expression of mesenchymal markers N-Cadherin and Vimentin, increased mRNA levels of the embryonic stem cell related genes Nanog and Oct4 and increased resistance to irradiation compared to other sub-populations studied, suggesting the CD44^highCD90⁺ population a good candidate for the lung CSCs. Both CD44^highCD90⁺ and CD44^highCD90⁻ cells in the PLCCL derived from SCC formed spheroids, whereas the CD44^low/− cells were lacking this potential. These results indicate that CD44^highCD90⁺ sub-population may represent CSCs in SCLC and LCC, whereas in SCC lung cancer subtype, CSC potentials were found within the CD44^high sub-population.     

结合基因表达数据和ChIP-chip数据的酵母转录调控模块的识别

活细胞依赖其众多的转录调控模块来实现复杂的生物功能,识别转录调控模块对深入理解细胞的功能及其转录机制有着重要的意义。本文结合酵母基因表达数据和ChIP-chip数据,提出了一种转录调控模块识别算法。该算法通过采用不同的P值阈值分别得到了核心集和粗糙集,然后对核心集和粗糙集进行判别,最后对基因进行扩展之后得到基因转录调控模块。将该算法运用到两个酵母基因表达数据中,得到了一些具有显著生物学意义的基因转录调控模块。与其它算法相比,该算法不仅可以识别含有较多基因的转录调控模块,而且可以识别一些其它算法不能识别的基因转录调控模块。识别得到的基因转录调控模块有着不同的生物学功能,并且有助于进一步理解酵母的转录调控机制。     

Modulation of Aminoacylation and Editing Properties of Leucyl-tRNA Synthetase by a Conserved Structural Module

A conserved structural module following the KMSKS catalytic loop exhibits α-α-β-α topology in class Ia and Ib aminoacyl-tRNA synthetases. However, the function of this domain has received little attention. Here, we describe the effect this module has on the aminoacylation and editing capacities of leucyl-tRNA synthetases (LeuRSs) by characterizing the key residues from various species. Mutation of highly conserved basic residues on the third α-helix of this domain impairs the affinity of LeuRS for the anticodon stem of tRNA^Leu, which decreases both aminoacylation and editing activities. Two glycine residues on this α-helix contribute to flexibility, leucine activation, and editing of LeuRS from Escherichia coli (EcLeuRS). Acidic residues on the β-strand enhance the editing activity of EcLeuRS and sense the size of the tRNA^Leu D-loop. Incorporation of these residues stimulates the tRNA-dependent editing activity of the chimeric minimalist enzyme Mycoplasma mobile LeuRS fused to the connective polypeptide 1 editing domain and leucine-specific domain from EcLeuRS. Together, these results reveal the stem contact-fold to be a functional as well as a structural linker between the catalytic site and the tRNA binding domain. Sequence comparison of the EcLeuRS stem contact-fold domain with editing-deficient enzymes suggests that key residues of this module have evolved an adaptive strategy to follow the editing functions of LeuRS.     

Induction of Cancer Stem Cell Properties in Colon Cancer Cells by Defined Factors

Cancer stem cells (CSCs) are considered to be responsible for the dismal prognosis of cancer patients. However, little is known about the molecular mechanisms underlying the acquisition and maintenance of CSC properties in cancer cells because of their rarity in clinical samples. We herein induced CSC properties in cancer cells using defined factors. We retrovirally introduced a set of defined factors (OCT3/4, SOX2 and KLF4) into human colon cancer cells, followed by culture with conventional serum-containing medium, not human embryonic stem cell medium. We then evaluated the CSC properties in the cells. The colon cancer cells transduced with the three factors showed significantly enhanced CSC properties in terms of the marker gene expression, sphere formation, chemoresistance and tumorigenicity. We designated the cells with CSC properties induced by the factors, a subset of the transduced cells, as induced CSCs (iCSCs). Moreover, we established a novel technology to isolate and collect the iCSCs based on the differences in the degree of the dye-effluxing activity enhancement. The xenografts derived from our iCSCs were not teratomas. Notably, in contrast to the tumors from the parental cancer cells, the iCSC-based tumors mimicked actual human colon cancer tissues in terms of their immunohistological findings, which showed colonic lineage differentiation. In addition, we confirmed that the phenotypes of our iCSCs were reproducible in serial transplantation experiments. By introducing defined factors, we generated iCSCs with lineage specificity directly from cancer cells, not via an induced pluripotent stem cell state. The novel method enables us to obtain abundant materials of CSCs that not only have enhanced tumorigenicity, but also the ability to differentiate to recapitulate a specific type of cancer tissues. Our method can be of great value to fully understand CSCs and develop new therapies targeting CSCs.     

Identification of Phytopathogenic Virus Strains by their Luminescent Properties

A quick test has been developed to identify phytopathogenic virus strains by variations in their photoluminescence parameters. When heated, the virus suspension shows a jumpwise drop or rise in fluorescence intensity caused by conformational changes in the macromolecules of the virion protein capsules. The relative value of the jump in fluorescence intensity and the temperature value at which the jump occurs are essentially strain-specific. The minimum time needed for one test is from 15 to 20 minutes.     

A Pilot Study Combining a GC-Sensor Device with a Statistical Model for the Identification of Bladder Cancer from Urine Headspace

There is a need to reduce the number of cystoscopies on patients with haematuria. Presently there are no reliable biomarkers to screen for bladder cancer. In this paper, we evaluate a new simple in–house fabricated, GC-sensor device in the diagnosis of bladder cancer based on volatiles. Sensor outputs from 98 urine samples were used to build and test diagnostic models. Samples were taken from 24 patients with transitional (urothelial) cell carcinoma (age 27-91 years, median 71 years) and 74 controls presenting with urological symptoms, but without a urological malignancy (age 29-86 years, median 64 years); results were analysed using two statistical approaches to assess the robustness of the methodology. A two-group linear discriminant analysis method using a total of 9 time points (which equates to 9 biomarkers) correctly assigned 24/24 (100%) of cancer cases and 70/74 (94.6%) controls. Under leave-one-out cross-validation 23/24 (95.8%) of cancer cases were correctly predicted with 69/74 (93.2%) of controls. For partial least squares discriminant analysis, the correct leave-one-out cross-validation prediction values were 95.8% (cancer cases) and 94.6% (controls). These data are an improvement on those reported by other groups studying headspace gases and also superior to current clinical techniques. This new device shows potential for the diagnosis of bladder cancer, but the data must be reproduced in a larger study.     

Combining Information from Cancer Registry and Medical Records Data to Improve Analyses of Adjuvant Cancer Therapies

Summary .  Cancer registry records contain valuable data on provision of adjuvant therapies for cancer patients. Previous studies, however, have shown that these therapies are underreported in registry systems. Hence direct use of the registry data may lead to invalid analysis results. We propose first to impute correct treatment status, borrowing information from an additional source such as medical records data collected in a validation sample, and then to analyze the multiply imputed data, as in Yucel and Zaslavsky (2005,  Journal of the American Statistical Association   100, 1123–1132). We extend their models to multiple therapies using multivariate probit models with random effects. Our model takes into account the associations among different therapies in both administration and probability of reporting, as well as the multilevel structure (patients clustered within hospitals) of registry data. We use Gibbs sampling to estimate model parameters and impute treatment status. The proposed methodology is applied to the data from the Quality of Cancer Care project, in which stage II or III colorectal cancer patients were eligible to receive adjuvant chemotherapy and radiation therapy.     

Identification of Plasma Lipid Biomarkers for Prostate Cancer by Lipidomics and Bioinformatics

Background

Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer.

Methodology/Principal Findings

Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient''s age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer.

Conclusions/Significance

Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy.     

细胞SELEX技术用于胰腺癌细胞特异性适配体的筛选及鉴定

细胞SELEX是目前常用的筛选细胞特异性适配体的技术。胰腺癌细胞特异性适配体在胰腺癌的诊断和治疗中有巨大的应用潜力。本研究拟通过该技术获得特异性识别胰腺癌PANC-1细胞的适配体,并对所筛选的适配体进行功能鉴定。本研究以胰腺癌PANC-1细胞为正筛细胞,正常胰腺导管上皮细胞HPDE6-C7为负筛细胞,通过磁珠法细胞SELEX技术进行筛选。经过12轮筛选,对筛选文库进行PCR扩增、质粒转染、单克隆挑选及测序,获得2条适配体Apt-5和Apt-12。流式细胞术检测发现,适配体Apt-5和Apt-12可特异性识别PANC-1细胞,其Kd值分别为8.27±2.10 nmol/L和8.88±2.51 nmol/L,Kd值均处于纳摩尔级别。通过RNA结构预测,2条适配体的二级结构均为茎-环结构。细胞免疫荧光验证了适配体的结合部位为细胞膜表面。本研究表明,通过磁珠法细胞SELEX技术,成功获得可特异性识别胰腺癌PANC-1细胞的适配体。该适配体有望成为胰腺癌诊断和治疗中的特异性分子靶向剂。     

Evolutionary and Topological Properties of Genes and Community Structures in Human Gene Regulatory Networks

The diverse, specialized genes present in today’s lifeforms evolved from a common core of ancient, elementary genes. However, these genes did not evolve individually: gene expression is controlled by a complex network of interactions, and alterations in one gene may drive reciprocal changes in its proteins’ binding partners. Like many complex networks, these gene regulatory networks (GRNs) are composed of communities, or clusters of genes with relatively high connectivity. A deep understanding of the relationship between the evolutionary history of single genes and the topological properties of the underlying GRN is integral to evolutionary genetics. Here, we show that the topological properties of an acute myeloid leukemia GRN and a general human GRN are strongly coupled with its genes’ evolutionary properties. Slowly evolving (“cold”), old genes tend to interact with each other, as do rapidly evolving (“hot”), young genes. This naturally causes genes to segregate into community structures with relatively homogeneous evolutionary histories. We argue that gene duplication placed old, cold genes and communities at the center of the networks, and young, hot genes and communities at the periphery. We demonstrate this with single-node centrality measures and two new measures of efficiency, the set efficiency and the interset efficiency. We conclude that these methods for studying the relationships between a GRN’s community structures and its genes’ evolutionary properties provide new perspectives for understanding evolutionary genetics.     

二甲双胍联合阿霉素应用对人乳腺癌细胞增殖和凋亡的影响

目的：观察二甲双胍联合阿霉素应用对人乳腺癌细胞MDA-MB-231增殖和凋亡的影响。方法：MTT法分别检测二甲双胍、阿霉素和二甲双胍联合阿霉素对MDA-MB-231细胞生长的抑制作用;平板克隆实验检测二甲双胍联合阿霉素对MDA-MB-231细胞克隆形成能力的影响;流式细胞仪检测二甲双胍联合阿霉素对MDA-MB-231细胞凋亡的影响。结果：二甲双胍和阿霉素分别对MDA-MB-231细胞生长有抑制作用,二甲双胍联合阿霉素应用对MDA-MB-231细胞生长的抑制作用更加显著,并且随着药物浓度的增加而增加;二甲双胍联合阿霉素应用与单药相比能够明显降低MDA-MB-231细胞克隆形成率,并且促进细胞凋亡。结论：二甲双胍联合阿霉素应用与单药相比能够显著抑制人乳腺癌细胞MDA-MB-231细胞的增值,促进其凋亡,可见两药联用对肿瘤细胞的杀伤具有协同性。     

肺癌转移相关蛋白的比较蛋白质组分析与鉴定

采用比较蛋白质组技术对肺巨细胞癌高、低转移株的蛋白质表达谱进行双向电泳分离和MALDI-TOF分析,并在蛋白质和mRNA水平进行进一步验证,成功鉴定了11个肺癌转移相关蛋白.其中,候选蛋白膜联蛋白1(ANX1)、细胞骨架蛋白(CK18)、Rho-GDP解离抑制剂1(GDIR)、原肌球蛋白3(TPMF)、蛋白谷氨酰胺γ-谷氨酰转移酶(TGLC)和白介素18(IL-18)在肺巨细胞癌高转移株显著高表达,而候选蛋白核氯离子通道蛋白1(CLI1)、蛋白质二硫键异构酶(ER60)、肌酸激酶、硫氧还蛋白过氧化物酶1(PDX1)和热休克蛋白60(CH60)在肺巨细胞癌高转移株显著低表达.大多数的候选蛋白可通过调控肿瘤细胞的生长、迁移、粘附、凋亡和肿瘤免疫等环节来影响肿瘤细胞的侵袭和转移能力.迄今为止,还未见候选蛋白CLI1和IL-18与肺癌转移相关的报道,提示这两种蛋白质可能为新的肺癌转移相关蛋白.     

乳腺癌转移相关基因的筛选与生物信息学分析

乳腺癌是女性最常见的恶性肿瘤,转移与复发是乳腺癌患者死亡的主要原因. 研究与乳腺癌细胞转移相关的分子靶点对预防乳腺癌术后复发、提高疗效有重要意义. 本研究以3组乳腺癌转移相关的基因表达谱数据(GSE2034, GSE2603, GSE12276)为分析材料,采用GeneSpring软件筛选乳腺癌原发瘤与转移瘤芯片数据的差异表达基因,结合生物信息学工具PATHER、STRING、pSTIING和文献挖掘工具iHOP对差异基因及其相互作用关系进行分析. 结果显示,共筛选出乳腺癌转移共同差异基因147个,其中表达上调93个,表达下调54个. 这些差异基因主要涉及细胞周期与增殖、细胞粘附、细胞迁移、血管形成及信号转导等生物通路和生物过程. 差异基因编码蛋白间的相互作用主要集中在14个蛋白,且在更为复杂的网络图谱中仍可见其中9个基因（CXCR4、MMP1、MMP2、MMP3、CTGF、COL1A1、MEF2C、PTGS2及SPARC）在重要的节点位置. 文献挖掘发现,COL1A1基因可能为新发现的乳腺癌转移候选基因,为乳腺癌转移的发病机制提供新的思路,也为转移性乳腺癌的分子诊断和个体化治疗奠定基础.     

Topological classification and enumeration of RNA structures by genus

To an RNA pseudoknot structure is naturally associated a topological surface, which has its associated genus, and structures can thus be classified by the genus. Based on earlier work of Harer–Zagier, we compute the generating function $\mathbf{D}_{g,\sigma }(z)=\sum _{n}\mathbf{d}_{g,\sigma }(n)z^n$ for the number $\mathbf{d}_{g,\sigma }(n)$ of those structures of fixed genus $g$ and minimum stack size $\sigma $ with $n$ nucleotides so that no two consecutive nucleotides are basepaired and show that $\mathbf{D}_{g,\sigma }(z)$ is algebraic. In particular, we prove that $\mathbf{d}_{g,2}(n)\sim k_g\,n^{3(g-\frac{1}{2})} \gamma _2^n$ , where $\gamma _2\approx 1.9685$ . Thus, for stack size at least two, the genus only enters through the sub-exponential factor, and the slow growth rate compared to the number of RNA molecules implies the existence of neutral networks of distinct molecules with the same structure of any genus. Certain RNA structures called shapes are shown to be in natural one-to-one correspondence with the cells in the Penner–Strebel decomposition of Riemann’s moduli space of a surface of genus $g$ with one boundary component, thus providing a link between RNA enumerative problems and the geometry of Riemann’s moduli space.     

Identification of miRNA-Mediated Core Gene Module for Glioma Patient Prediction by Integrating High-Throughput miRNA,mRNA Expression and Pathway Structure

The prognosis of glioma patients is usually poor, especially in patients with glioblastoma (World Health Organization (WHO) grade IV). The regulatory functions of microRNA (miRNA) on genes have important implications in glioma cell survival. However, there are not many studies that have investigated glioma survival by integrating miRNAs and genes while also considering pathway structure. In this study, we performed sample-matched miRNA and mRNA expression profilings to systematically analyze glioma patient survival. During this analytical process, we developed pathway-based random walk to identify a glioma core miRNA-gene module, simultaneously considering pathway structure information and multi-level involvement of miRNAs and genes. The core miRNA-gene module we identified was comprised of four apparent sub-modules; all four sub-modules displayed a significant correlation with patient survival in the testing set (P-values≤0.001). Notably, one sub-module that consisted of 6 miRNAs and 26 genes also correlated with survival time in the high-grade subgroup (WHO grade III and IV), P-value = 0.0062. Furthermore, the 26-gene expression signature from this sub-module had robust predictive power in four independent, publicly available glioma datasets. Our findings suggested that the expression signatures, which were identified by integration of miRNA and gene level, were closely associated with overall survival among the glioma patients with various grades.