Towards the Personalized Treatment of Glioblastoma: Integrating Patient-Specific Clinical Data in a Continuous Mechanical Model

Glioblastoma multiforme (GBM) is the most aggressive and malignant among brain tumors. In addition to uncontrolled proliferation and genetic instability, GBM is characterized by a diffuse infiltration, developing long protrusions that penetrate deeply along the fibers of the white matter. These features, combined with the underestimation of the invading GBM area by available imaging techniques, make a definitive treatment of GBM particularly difficult. A multidisciplinary approach combining mathematical, clinical and radiological data has the potential to foster our understanding of GBM evolution in every single patient throughout his/her oncological history, in order to target therapeutic weapons in a patient-specific manner. In this work, we propose a continuous mechanical model and we perform numerical simulations of GBM invasion combining the main mechano-biological characteristics of GBM with the micro-structural information extracted from radiological images, i.e. by elaborating patient-specific Diffusion Tensor Imaging (DTI) data. The numerical simulations highlight the influence of the different biological parameters on tumor progression and they demonstrate the fundamental importance of including anisotropic and heterogeneous patient-specific DTI data in order to obtain a more accurate prediction of GBM evolution. The results of the proposed mathematical model have the potential to provide a relevant benefit for clinicians involved in the treatment of this particularly aggressive disease and, more importantly, they might drive progress towards improving tumor control and patient’s prognosis.     

Immunophenotypic and Ultrastructural Validation of a New Human Glioblastoma Cell Line

1. A human glioma cell line, NG97, was established by Grippo et al. in 2001 from tissue obtained from a grade III astrocytoma (WHO, 2000). In this first study, the cell line grew as two morphologically distinct subpopulations: dendritic/spindle cells and small round cells. The injection of NG97 cells into nude mice induced an aggressive tumor characterized by: severe cytological atypia, vascular proliferation and pseudopalisading necrosis (glioblastoma multiforme features). 2. The purpose of the present study was to characterize the immunophenotype and ultrastructural aspects of this cell line, using the parental tumor, cultured cells and the xenotransplant, in order to assess its glial nature and possible divergent differentiation. 3. NG97 cells and xenotransplant expressed the main neuroglial markers (GFAP, S-100 protein, NSE and Leu-7) and showed no aberrant expression of other histogenetic markers. GFAP was similarly expressed in the parental tumor and in the cells in culture, but decreased in the xenotransplant. NSE expression was reduced in NG97 cells, but substantially recovered in the xenotransplant. This variability in expression of GFAP and NSE was interpreted as either a phenomenon of dedifferentiation or to microenvironmental selection of specific subclones. S-100 was equally expressed in the three contexts. The xenotransplant's ultrastructural features were those of a highly undifferentiated tumor. No significant immunophenotypic or ultrastructural differences between the two morphologically distinct populations were found. 4. Thus, our data demonstrate that NG97 cells constitute a pure glial-committed cell line, which may prove useful as a malignant glioma model in studies addressing pathophysiological, diagnostic and therapeutic issues.     

冰草属(Agropyron Gaertn.)植物遗传多样性取样策略基于醇溶蛋白的研究

对冰草属(Agropyron Gaertn.)植物的5个种22个居群分8个取样梯度,分别随机取3、6、9、12、15、18、21、24粒种子的混合样进行醇溶蛋白的A-PAGE分析,结果发现:平均Simpson指数依取样量的增加表现增大,以3粒种子0.922表现最低,以21粒0.933表现最高,变异系数(CV%)为0.41.醇溶蛋白谱带数依所提取的混合样的籽粒数目发生显著变化,冰草属内5个种表现趋势相同,22个居群不同取样整体平均以3粒种子提取的醇溶蛋白谱带数18.38为最少,以18粒种子提取的醇溶蛋白谱带28.24为最多,CV%为13.21.取样量达到12粒以上醇溶蛋白谱带差异不明显(P=0.01),图谱表现基本一致.建议在利用生化指纹进行冰草属居群间及种间的遗传多样性研究中,混合取样量最低应保持在12个个体及以上方能代表居群整体,反映居群的整体遗传特性.     

Personalized Treatment of Patients With Primary Aldosteronism

Primary aldosteronism (PA) is a highly prevalent yet underdiagnosed secondary cause of hypertension. PA is associated with increased cardiovascular and renal morbidity compared with patients with primary hypertension. Thus, prompt identification and targeted therapy of PA are essential to reduce cardiovascular and renal morbidity and mortality in a large population with hypertension. Unilateral adrenalectomy is preferred for lateralized PA as the only potentially curative therapy. Surgery also mitigates the risk of cardiovascular and renal complications associated with PA. Targeted medical therapy, commonly including a mineralocorticoid receptor antagonist, is offered to patients with bilateral PA and those who are not surgical candidates. Novel therapies, including nonsteroidal mineralocorticoid receptor antagonists and aldosterone synthase inhibitors, are being developed as alternative options for PA treatment. In this review article, we discuss how to best individualize therapy for patients with PA.     

高脂血症性急性重症胰腺炎特征分析及治疗策略

目的:探讨高脂血症性急性重症胰腺炎(HSAP)患者的临床特点及诊疗分析,为急性重症胰腺炎(SAP)的诊治提供偱证依据。方法:回顾性分析了我科自2008年9月到2013年9月收治的101例急性胰腺炎患者血清脂肪酶、淀粉酶浓度、酶恢复时间、白细胞、甘油三酯差异以分析高脂血症性急性重症胰腺炎患者的病情转归情况。结果:HSAP患者甘油三酯(TG)水平男性明显高于女性,差异有统计学意义(P0.05);HSAP患者入院后经过降脂药物治疗HSAP与其他SAP相比较甘油三酯(TG)在短期内基本恢复正常,HSAP中白细胞、酶恢复时间低于其他SAP组,差异有统计学意义(P0.05);HSAP与高脂血症性急性轻型胰腺炎(HMAP)相比较两组间淀粉酶、脂肪酶、甘油三酯比较差异无统计学意义(P0.05),白细胞、酶恢复时间比较差异有统计学意义(P0.05)。结论:HSAP患者TG水平可能与患者的性别有一定的相关性;HSAP患者的病情转归可能与甘油三酯水平相关;甘油三酯水平不能直接决定高脂血症性急性胰腺炎患者病情的轻重。     

Automated Glioblastoma Segmentation Based on a Multiparametric Structured Unsupervised Classification

Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation.     

Rectal Organoids Enable Personalized Treatment of Cystic Fibrosis

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High-Resolution Mutational Profiling Suggests the Genetic Validity of Glioblastoma Patient-Derived Pre-Clinical Models

Recent advances in the ability to efficiently characterize tumor genomes is enabling targeted drug development, which requires rigorous biomarker-based patient selection to increase effectiveness. Consequently, representative DNA biomarkers become equally important in pre-clinical studies. However, it is still unclear how well these markers are maintained between the primary tumor and the patient-derived tumor models. Here, we report the comprehensive identification of somatic coding mutations and copy number aberrations in four glioblastoma (GBM) primary tumors and their matched pre-clinical models: serum-free neurospheres, adherent cell cultures, and mouse xenografts. We developed innovative methods to improve the data quality and allow a strict comparison of matched tumor samples. Our analysis identifies known GBM mutations altering PTEN and TP53 genes, and new actionable mutations such as the loss of PIK3R1, and reveals clear patient-to-patient differences. In contrast, for each patient, we do not observe any significant remodeling of the mutational profile between primary to model tumors and the few discrepancies can be attributed to stochastic errors or differences in sample purity. Similarly, we observe ∼96% primary-to-model concordance in copy number calls in the high-cellularity samples. In contrast to previous reports based on gene expression profiles, we do not observe significant differences at the DNA level between in vitro compared to in vivo models. This study suggests, at a remarkable resolution, the genome-wide conservation of a patient’s tumor genetics in various pre-clinical models, and therefore supports their use for the development and testing of personalized targeted therapies.     

Focus: Personalized Medicine: Tailoring the Treatment of Melanoma: Implications for Personalized Medicine

Oncology has been revolutionized by the ability to selectively inhibit the growth of cancerous cells while ostensibly avoiding the disruption of proteins and pathways necessary for normal cellular function. This paradigm has triggered an explosion of targeted therapies for cancer, creating a burgeoning billion-dollar industry of small molecules and monoclonal antibodies [1]. Largely due to these new treatments, spending on cancer pharmaceuticals has surpassed $100 billion worldwide [2]. In particular, the treatment of melanoma, a deadly and fast-spreading form of skin cancer, has been transformed by these new targeted therapies. In this mini-review, we summarize the progress made in the field of personalized treatment of melanoma, with an emphasis on targeted therapies. We then outline future directions for treatment, including novel cell-mediated therapies and new potential targets.     

Current Progress for the Use of miRNAs in Glioblastoma Treatment

Glioblastoma (GBM) is a highly aggressive brain cancer with the worst prognosis of any central nervous system disease despite intensive multimodal therapy. Inevitably, glioblastoma is fatal, with recurrence of treatment-resistant tumour growth at distal sites leading to an extremely low median survival rate of 12–15 months from the time of initial diagnosis. With the advent of microarray and gene profiling technology, researchers have investigated trends in genetic alterations and, in this regard, the role of dysregulated microRNAs (highly conserved endogenous small RNA molecules) in glioblastoma has been studied with a view to identifying novel mechanisms of acquired drug resistance and allow for development of microRNA (miRNA)-based therapeutics for GBM patients. Considering the development of miRNA research from initial association to GBM to commercial development of miR-based therapeutics in less than a decade, it is not beyond reasonable doubt to anticipate significant advancements in this field of study, hopefully with the ultimate conclusion of improved patient outcome. This review discusses the recent advancements in miRNA-based therapeutic development for use in glioblastoma treatment and the challenges faced with respect to in vivo and clinical application.     

紫薇品种表型多样性分析

对111个紫薇品种的17个表型分类性状多样性进行了研究。结果表明,紫薇品种具有丰富的表型多样性,平均遗传多样性指数为0.707。总体上是数量性状形态多样性指数大于质量性状,其中花色、瓣爪色2个质量性状和花径、着花数、花序长、花序宽、种子千粒重5个数量性状变异明显,其多样性指数分别大于1.2和1.4。不同紫薇品种群表型性状多样性差异明显,多样性指数由高到低依次为:红薇品种群(H'=0.838)、堇薇品种群(H'=0.823)、银薇品种群(H'=0.696)、矮生品种群(H'=0.604)、复色品种群(H'=0.573)。通过主成分分析,上述2个质量性状和5个数量性状主成分的贡献率为67.70%,包括花序长、花序宽、着花数、花色数、花色、种子千粒重、瓣爪色、叶色、小枝四棱、花香、花径等11个形态性状指标,代表了紫薇品种表型分类性状的综合特征。基于表型形态性状,111个紫薇品种可聚类为5大类群,其遗传聚类与花色及株型关系密切,4个以花色为主要分类性状的品种群总体演化趋势是:堇薇品种群→红薇品种群→银薇品种群→复色品种群。     

一种新的基于STR的染色体三体性疾病诊断策略中遗传标记的评估

背景:在此前发表的文章中,我们提出了一种新的基于短串联重复序列(Short Tandem Repeats,STR)的染色体三体性疾病的诊断策略.当应用这种策略来检测特定染色体拷贝数时,需要从人类基因组众多的STR中选择适宜的染色体特异性STR基因座构建一个诊断系统,根据系统中的STR基因座是否检测到三种不同的等位基因产物来判断个体是否为三体患者.目的:本研究拟进一步提出并验证对单个STR基因座及由多个STR基因座构成的诊断系统的评估方法,旨在帮助选择适宜的STR基因座构建一个高效能的诊断系统.方法:我们提出一个新的参数--三等位基因栓出率,并推导出该参数的计算公式,用于定量评估一个STR基因座在这种诊断策略中的效能.在此基础上,推导出另一个数学公式,计算一个非整倍体诊断系统能够在一个三体性患者?哌 检测到三个不同等位基因的概率,根据这个概率的大小来衡量系统诊断效能的高低.最后,我们将所提出的两个公式用于评估我们在先前研究中构建的一个21三体的诊断系统.结果:这个21三体诊断系统由9个21号染色体特异性STR基因座构成.根据我们所提出的两个公式,这些STR基因座的三等位基因检出率在0.203-0.638之间,该系统在21三体患者能够检测到三个不同等位基因的概率大于0.95.结论:我们所提出并验证的公式可以对单个STR基因座和系统的诊断效能进行定量评估,帮助选择适宜的STR遗传标记,并确定一个高效能诊断系统所需的STR基因座的数量,从而为这种诊断策略的广泛应用提供基础.     

基于分级诊疗视角的就医行为分析及相关策略研究

通过国内外相关文献资料的患者门诊就医行为分析和研究,发现并总结出患者就医行为的影响因素、不同病种和不同人群的就医流向趋势。其研究结果可为我国分级诊疗的基层首诊、双向转诊等相关政策的制订和完善提供较为准确的理论依据,以促进分级诊疗的健康发展。     

利用ISSR标记研究野大豆居群内遗传变异及其取样策略

为了有效地保护野大豆(Glycine soja Sieb.et Zucc.)并制定合理的居群取样策略,对上海江湾机场的一个人然野大豆居群进行了 100个单株(个体)的随机取样,并用ISSR分子标记对其进行了遗传多样性分析.利用筛选出的15条ISSR引物在这个居群中检测到较高的遗传变异,样本内个体间的相似系数变化在0.17～0.89之间.居群内平均每个位点的平均预期杂合度(He)为0.171 4,香农指数(I)为0.271 4.PCA分析显示,江湾野大豆居群内的遗传变异不是呈均匀分布,而是呈从状分布.该野大豆居群遗传多样性和样本内个体数量间的相关性分析显示:在个体数少于40的情况下,遗传多样性随个体数的增加而迅速增加;当样本中的个体数大于40时,遗传多样性的增加减慢并很快趋于饱和.研究表明:对野大豆居群进行异地保护时,对各居群的采样植株数不应当低于35～45;在居群内采样时,所采集的个体之间最好相隔一定的空间距离.     

利用ISSR标记研究野大豆居群内遗传变异及其取样策略

为了有效地保护野大豆(Glycine soja Sieb.et Zucc.)并制定合理的居群取样策略,对上海江湾机场的一个天然野大豆居群进行了100个单株(个体)的随机取样,并用ISSR分子标记对其进行了遗传多样性分析。利用筛选出的15条ISSR引物在这个居群中检测到较高的遗传变异,样本内个体间的相似系数变化在0．17～0．89之间。居群内平均每个位点的平均预期杂合度(He)为0．1714,香农指数(I)为0．2714。PCA分析显示,江湾野大豆居群内的遗传变异不是呈均匀分布,而是呈丛状分布。该野大豆居群遗传多样性和样本内个体数量间的相关性分析显示：在个体数少于40的情况下,遗传多样性随个体数的增加而迅速增加：当样本中的个体数大于40时,遗传多样性的增加减慢并很快趋于饱和。研究表明：对野大豆居群进行异地保护时,对各居群的采样植株数不应当低于35～45;在居群内采样时,所采集的个体之间最好相隔一定的空间距离。     

Noscapine,a Non-addictive Opioid and Microtubule-Inhibitor in Potential Treatment of Glioblastoma

Neurochemical Research - Noscapine is a phthalide isoquinoline alkaloid that easily traverses the blood brain barrier and has been used for years as an antitussive agent with high safety. Despite...     

Genetic Markers for Personalized Therapy of Polygenic Diseases: Pharmacogenetics of Multiple Sclerosis

Molecular Biology - Pharmacogenetics (PG) investigates the inherited variants of the human genome that underlie individual differences in drug metabolic transformation, delivery, and mechanism of...