Intracellular localization of the antitumour drug adriamycin in living cultured cells: A confocal microscopy study

The intracellular distribution of the anthracyclinic antibiotic adriamycin in living cultured cells has been investigated by confocal microscopy. In human melanoma cells (M14), adriamycin was localized inside the nuclei. When adriamycin-treated M14 cells were allowed to recover in drug-free medium, a complete efflux of the drug from the nucleus was revealed. In recovered cells, a weakly fluorescent signal was observed in the perinuclear region. When M14 cells were recovered in a medium containing colcemid, a microtubule depolymerizing agent, the drug transport from the nucleus to the cell periphery appeared to be inhibited, suggesting that the microtubule network is strongly involved in drug transport mechanisms. In multidrug-resistant (MDR) cells the intracellular location of adriamycin was shown to be noticeably different from that of the parental wild-type cells. In particular, in resistant human breast carcinoma cells (MCF-7), adriamycin appeared to be exclusively located within the cytoplasm whereas the nuclei were shown to be completely negative. When adriamycin treatment was performed in association with MDR revertants, such as Lonidamine (inhibitor of the energy metabolism) or verapamil (inhibitor of the P-glycoprotein efflux pump), a marked enhancement of the cytoplasmic signal was observed in resistant cells. Under these conditions, adriamycin appeared concentrated in the perinuclear region, but the nuclei were still negative. Confocal microscopy proved to be a very useful method for the study of the intracellular transport of fluorescent substances, such as anthracyclinic antibiotics, and for the investigation of the multidrug resistance phenomenon in tumour cells.     

Structure-activity studies of human tumour necrosis factors

The mechanism by which tumour necrosis factors (TNF and lymphotoxin,also called TNFß and TNFß respectively) exerttheir cytotoxic activity on many malignant cells, remains largelyunknown. Furthermore, the broad array of differentiation (geneinduction) and mitogenic activities towards many primary cellsis still a subject of intensive investigation. TNF is an importantmediator in inflammation, immune responses and infection-relatedphenomena and these activities contribute to the severe toxidtyseen when TNF is used as an anticancer agent. The first stepin the mechanism of action is the specific binding of the ligandto its receptors and dissection of the molecular mechanism involvedin this interaction is the subject of this review. The reasonsfor the interest in this aspect are obvious: first, the developmentof strong antagonistic TNF analogues can be useful in dampeningthe potentially lethal or debilitating effects of an overproductionof the cytokine (as in septic shock or rheumatoid arthritis).Secondly, since two distinct TNF receptors exist, constructionof TNF muteins that distinguish between both types may leadto derivatives of this plekrtropic agent with a more restrictedbiological activity pattern. Ideally, one would like to developa TNF mutant that has retained its cytotoxic action on tumourcells without inducing the deleterious systemic toxteity. Suchan optimized TNF molecule could become a potent anticancer agent     

Investigating T Cell Immunity in Cancer: Achievements and Prospects

T cells play a key role in tumour surveillance, both identifying and eliminating transformed cells. However, as tumours become established they form their own suppressive microenvironments capable of shutting down T cell function, and allowing tumours to persist and grow. To further understand the tumour microenvironment, including the interplay between different immune cells and their role in anti-tumour immune responses, a number of studies from mouse models to clinical trials have been performed. In this review, we examine mechanisms utilized by tumour cells to reduce their visibility to CD8⁺ Cytotoxic T lymphocytes (CTL), as well as therapeutic strategies trialled to overcome these tumour-evasion mechanisms. Next, we summarize recent advances in approaches to enhance CAR T cell activity and persistence over the past 10 years, including bispecific CAR T cell design and early evidence of efficacy. Lastly, we examine mechanisms of T cell infiltration and tumour regression, and discuss the strengths and weaknesses of different strategies to investigate T cell function in murine tumour models.     

MicroRNAs in Metastasis and the Tumour Microenvironment

Metastasis is the process whereby cancer cells migrate from the primary tumour site to colonise the surrounding or distant tissue or organ. Metastasis is the primary cause of cancer-related mortality and approximately half of all cancer patients present at diagnosis with some form of metastasis. Consequently, there is a clear need to better understand metastasis in order to develop new tools to combat this process. MicroRNAs (miRNAs) regulate gene expression and play an important role in cancer development and progression including in the metastatic process. Particularly important are the roles that miRNAs play in the interaction between tumour cells and non-tumoral cells of the tumour microenvironment (TME), a process mediated largely by circulating miRNAs contained primarily in extracellular vesicles (EVs). In this review, we outline the accumulating evidence for the importance of miRNAs in the communication between tumour cells and the cells of the TME in the context of the pre-metastatic and metastatic niche.     

In Silico Logical Modelling to Uncover Cooperative Interactions in Cancer

The multistep development of cancer involves the cooperation between multiple molecular lesions, as well as complex interactions between cancer cells and the surrounding tumour microenvironment. The search for these synergistic interactions using experimental models made tremendous contributions to our understanding of oncogenesis. Yet, these approaches remain labour-intensive and challenging. To tackle such a hurdle, an integrative, multidisciplinary effort is required. In this article, we highlight the use of logical computational models, combined with experimental validations, as an effective approach to identify cooperative mechanisms and therapeutic strategies in the context of cancer biology. In silico models overcome limitations of reductionist approaches by capturing tumour complexity and by generating powerful testable hypotheses. We review representative examples of logical models reported in the literature and their validation. We then provide further analyses of our logical model of Epithelium to Mesenchymal Transition (EMT), searching for additional cooperative interactions involving inputs from the tumour microenvironment and gain of function mutations in NOTCH.     

多支持向量机的乳腺肿瘤识别

针对乳腺肿块具有大小不固定和个体差异等特性,提出了一种多支持向量机对乳腺肿块的识别方法.选择八个方向上的支持向量生成分类器,选取高斯核函数作为核函数,其中取σ=30时分割正确率达到97.3%.表明多支持向量机应用于乳腺肿块识别可以获得较好的识别效果,为进一步的医学诊断提供可靠的依据.     

基于邻域粗糙集的加权KNN肿瘤基因表达谱分类算法

肿瘤亚型的准确判别对肿瘤的治疗具有重要意义,对肿瘤的不同亚型进行准确判别是当前生物信息学研究的重要课题．本文首先利用Relief算法排序基因并选出初始的肿瘤信息基因子集,然后利用向基于邻域粗糙集模型的向前属性约减算法FARNeM来计算加权基因集合,最后用加权KNN算法对肿瘤对这些数据进行分析,从而发现有差异的基因表达。实验结果表明了上述方法的可行性和有效性。     

Automated classification of brain tumours from short echo time in vivo MRS data using Gaussian Decomposition and Bayesian Neural Networks

Neuro-oncologists must ultimately rely on their acquired knowledge and accumulated experience to undertake the sensitive task of brain tumour diagnosis. This task strongly depends on indirect, non-invasive measurements, which are the source of valuable data in the form of signals and images. Expert radiologists should benefit from their use as part of an at least partially automated computer-based medical decision support system. This paper focuses on Magnetic Resonance Spectroscopy signal analysis and illustrates a method that combines Gaussian Decomposition, dimensionality reduction by Moving Window with Variance Analysis and classification using adaptively regularized Artificial Neural Networks. The method yields encouraging results in the task of binary classification of human brain tumours, even for tumour types that have seldom been analyzed from this viewpoint.     

Three Dimensional Simulation Method in Early Process of Division and Growth for Tumour Cells

The process of division, growth and death for tumour cell mass in the early is simulated. An integrated GUI is provided for users to set the value of each parameters, which are cell growth rates, cell mass division rates, cell mass death rates, simulate type, maximum running time, polarity and cell colour. It can display the growth process of each cell on result GUI. Also, it can display the values of each parameters for observing and analysing in current life cycle on result GUI, which are cell mass division times, cell mass death rate, cell mass division rate and cell mass growth rate. In the process of simulation, The cell growth rate is described by the approach to combine the exponential model with the linear model. In addition, a linked list data structure to store the tumour cells is used by the cellular automata for a reference to determine the position of each cell. It sets up two linked list to store the cells, one of them save the new small division cells and the other one save the big cell. That can make the painting process of cells on result GUI clearer and more organized. At last, the polarity oftumour growth is described for determining the growth direction of cells.     

Patterns in melanocytic lesions: impact of the geometry on growth and transport inside the epidermis

In glabrous skin, nevi and melanomas exhibit pigmented stripes during clinical dermoscopic examination. They find their origin in the basal layer geometry which periodically exhibits ridges, alternatively large (limiting ridges) and thin (intermediate ridges). However, nevus and melanoma lesions differ by the localization of the pigmented stripes along furrows or ridges of the epidermis surface. Here, we propose a biomechanical model of avascular tumour growth which takes into account this specific geometry in the epidermis where both kinds of lesions first appear. Simulations show a periodic distribution of tumour cells inside the lesion, with a global contour stretched out along the ridges. In order to be as close as possible to clinical observations, we also consider the melanin transport by the keratinocytes. Our simulations show that reasonable assumptions on melanocytic cell repartition in the ridges favour the limiting ridges of the basal compared with the intermediate ones in agreement with nevus observations but not really with melanomas. It raises the question of cell aggregation and repartition of melanocytic cells in acral melanomas and requires further biological studies of these cells in situ.