Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases

Parkinson’s Disease: Insights from Drosophila Model

Parkinson’s disease (PD) is a medical condition that has been known since ancient times. It is the second most common neurodegenerative disorder affecting approximately 1% of the population over 50 years. It is characterized by both motor and non-motor symptoms. Most of PD cases are sporadic while 5–10% cases are familial. Environment factors such as exposure to pesticides, herbicides and other heavy metals are expected to be the main cause of sporadic form of the disease. Mutation of the susceptible genes such as SNCA, PINK1, PARKIN, DJ1, and others are considered to be the main cause of the familial form of disease. Drosophila offers many advantages for studying human neurodegenerative diseases and their underlying molecular and cellular pathology. Shorter life span; large number of progeny; conserved molecular mechanism(s) among fly, mice and human; availability of many techniques, and tools to manipulate gene expression makes drosophila a potential model system to understand the pathology associated with PD and to unravel underlying molecular mechanism(s) responsible for dopaminergic neurodegeneration in PD—understanding of which will be of potential assistance to develop therapeutic strategies to PD. In the present review, we made an effort to discuss the contribution of fly model to understand pathophysiology of PD, in understanding the biological functions of genes implicated in PD; to understand the gene-environment interaction in PD; and validation of clues that are generated through genome-wide association studies (GWAS) in human through fly; further to screen and develop potential therapeutic molecules for PD. In nutshell, fly has been a great model system which has immensely contributed to the biomedical research relating to understand and addressing the pathology of human neurological diseases in general and PD in particular

Proteomics and network analysis identify common and specific pathways of neurodegeneration

Neurodegenerative disorders, such as Parkinson's disease (PD), Alzheimer's disease (AD) and amyotrophic lateral sclerosis (ALS) are multi-factorial in nature, involving several genetic mutations (in coding or regulatory regions) and epigenetic and environmental factors. The main clinical manifestation (movement disorders, cognitive impairment and/or psychiatric disturbances) depends on the neuron population being primarily affected. Complex and multifactorial neurodegenerative diseases can be investigated using a holistic approach that can give a global view about the pathogenetic process and shed light on specific and generic pathways of neurodegeneration. Proteomics offers a global molecular snapshot of proteins and consequently of processes that may influence neuronal death. The proteome in fact provides a dynamic view of what is happening in the system under investigation, because the expression of proteins, their abundance, their localization in tissues or cells, the type and amount of their post-translational changes depend from the environment and from the cellular physiological state. Therefore, all the projects presented in this thesis, by combining bioinformatics tools with proteomics, aimed at highlighting biochemical processes shared by different neurodegenerative diseases and diseasespecific pathways, which may justify the degeneration of dopaminergic neurons in PD. Finally, a focus on the mitochondrial interactome and proteome intended to elucidate important specific steps of the degenerative process in PD

Identification of idh1 mutation-related gene signature of glioblastoma multiforme

Background: Glioblastoma multiforme (GBM) is a type of commonly occurred malignant astrocytoma with an extremely poor prognosis. GBMs display a remarkable genetic variability, and it is essential to study the genomic alterations and pathway dysregulations based on the different tumor entities. The gene IDH1 encodes cytosolic isocitrate dehydrogenase 1, which catalyzes the reactions of oxidative decarboxylation of isocitrate to Alpha-ketoglutarate. Different types of mutation of IDH1 has been found in gliomas and GBMs, especially in secondary GBMs. Among the IDH1 mutations, R132H mutation is the most prominent one. IDH1 mutation in GBMs is correlated with a longer survival time, and no IDH1 mutations are reported in many other tumor types. Thus IDH1 is hypothesized as crucial in the pathogenesis of GBMs, and it is regarded as a potential drug target. The fundamental goal of this study is to identify a gene signature correlated with IDH1 mutation in GBMs. And related genes and biological pathways are also studied. Methods: Most of the work of data collection and analysis are achieved with R packages. The step-down maxT method is adopted to perform the multiple testing procedure in order to find differently expressed genes. The p-values of statistical tests are corrected by controlling FWER. The clustering result is explicated as heatmap, and clinical data is elucidated with boxplot and Kaplan Meier-plot. Analysis of GO and KEGG pathways are used to extract more information from the genes. And the results are visualized as graphs in Cytoscape. Results: A framework is created for identifying gene signatures as well as studying biological pathways. The expression data from 548 samples are collected, and 58 genes out of 12042 genes are identified as differently expressed. Finally a gene signature with 50 genes are proposed. Conclusion: Microarray technology and statistics methods are effective for the studying of alterations in gene expression and biological pathways. The gene signature proposed by this study can distinguish samples harboring IDH1 mutation from GBMs. And future researches are necessary to corroborate and extend the results

Exploring New Strategies to Overcome Resistance in Glioblastoma Multiforme: A Dissertation

Glioblastoma multiforme (GBM) tumors are highly malignant in nature and despite an aggressive therapy regimen, long–term survival for glioma patients is uncommon as cells with intrinsic or acquired resistance to treatment repopulate the tumor. This creates the need to investigate new therapies for enhancing GBM treatment outside of the standard of care, which includes Temozolomide (TMZ). Our lab focused on two novel strategies to overcome resistance in GBMs. In our first approach, the cellular responses of GBM cell lines to two new TMZ analogues, DP68 and DP86, are reported. The efficacy of these compounds was independent of DNA repair mediated by Methyl Guanine Methyl Transferase (MGMT) and the mismatch repair (MMR) pathway. DP68 or DP86 treated cells do not give rise to secondary spheres, demonstrating that they are no longer capable of self-renewal. DP68-induced damage includes interstrand DNA crosslinks and exhibits a distinct S-phase accumulation before G2/M arrest; a profile that is not observed for TMZ-treated cells. DP68 induces a strong DNA damage response and suppression of FANCD2 expression or ATR expression/kinase activity enhanced the anti-GBM effects of DP68. Collectively, these data demonstrate that DP68, and to a lesser extent DP86, are potent anti-GBM compounds that circumvent TMZ resistance and inhibit recovery of cultures. Our second approach stems from a previous discovery in our lab which demonstrated that the combination of TMZ with Notch inhibition, using a gamma secretase inhibitor (GSI), enhances GBM therapy. Efficacy of TMZ + GSI treatment is partially due to GBM cells shifting into a permanent senescent state. We sought to identify a miR signature that mimics the effects of TMZ + GSI as an alternative vi approach to enhance GBM therapy. MiR-34a expression was highly upregulated in response to TMZ or TMZ + GSI treatment. Exogenous expression of miR-34a revealed that it functions as a tumor suppressor and mimicked the in vitro effects of TMZ + GSI treatment. Additionaly, miR-34a overexpression leads to the downregulation of Notch family members. Together these two studies contribute to our understanding of the complex mechanisms driving resistance in GBM tumors and suggest strategies to develop more effective therapies

Protein Structure

Since the dawn of recorded history, and probably even before, men and women have been grasping at the mechanisms by which they themselves exist. Only relatively recently, did this grasp yield anything of substance, and only within the last several decades did the proteins play a pivotal role in this existence. In this expose on the topic of protein structure some of the current issues in this scientific field are discussed. The aim is that a non-expert can gain some appreciation for the intricacies involved, and in the current state of affairs. The expert meanwhile, we hope, can gain a deeper understanding of the topic

2002 Fourteenth Annual IMSA Presentation Day

As you begin to turn the pages and learn about the extraordinary research work of IMSA\u27s young investigators, I hope you will begin to see what is possible.https://digitalcommons.imsa.edu/archives_sir/1023/thumbnail.jp