Identification of Key Candidate Genes and Pathways in Colorectal Cancer by Integrated Bioinformatical Analysis

Guo, Yanning; Bao, Yonghua; Ma, Ming; Yang, Wancai

doi:10.3390/ijms18040722

Cited by 134 publications

(117 citation statements)

References 40 publications

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“…Visualizing the most extreme colon tissue samples for this image morphology feature (Figs 5d,e) shows clear differences between the two image extremes. LDHD is downregulated in colorectal cancer, and is also a hot spot for somatic mutations in colorectal cancer 32,33 .…”

Section: Resultsmentioning

confidence: 99%

Joint analysis of gene expression levels and histological images identifies genes associated with tissue morphology

Ash

Darnell

Munro

et al. 2018

Preprint

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Histological images are used to identify and to characterize complex phenotypes such as tumor stage. Our goal is to associate histological image phenotypes with high-dimensional genomic markers; the limitations to incorporating histological image phenotypes in genomic studies are that the relevant image features are difficult to identify and extract in an automated way, and confounders are difficult to control in this high-dimensional setting. In this paper, we use convolutional autoencoders and sparse canonical correlation analysis (CCA) on histological images and gene expression levels from paired samples to find subsets of genes whose expression values in a tissue sample correlate with subsets of morphological features from the corresponding sample image. We apply our approach, ImageCCA, to three data sets, two from TCGA and one from GTEx v6, and we find three types of biological associations. In TCGA, we find gene sets associated with the structure of the extracellular matrix and cell wall infrastructure, implicating uncharacterized genes in extracellular processes. Across studies, we find sets of genes associated with specific cell types, including muscle tissue and neuronal cells, and with cell type proportions in heterogeneous tissues. In the GTEx v6 data, we find image features that capture population variation in thyroid and in colon tissues associated with genetic variants, suggesting that genetic variation regulates population variation in tissue morphological traits. The software is publicly available at:https://github.com/daniel-munro/imageCCA.

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Section: Resultsmentioning

confidence: 99%

Joint analysis of gene expression levels and histological images identifies genes associated with tissue morphology

Ash

Darnell

Munro

et al. 2018

Preprint

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“…Such fold changes were visualized after k-means clustering. In determining the optimal k parameter for clustering, we used "mclust" package to calculate Bayesian Information Criterion of the expectation-maximization model 37 The plates with mCherry-LOV2-BiLINuS2-transfected cells were covered by the aluminum foil for several hours before the assay. We noticed that any exposure to light before the initial background measurement negatively affected the data calculations.…”

Section: Genotyping Dna From Dld-1 and Nucleoporins-targeted Cells Wmentioning

confidence: 99%

Distinct Basket Nucleoporins roles in Nuclear Pore Function and Gene Expression: Tpr is an integral component of the TREX-2 mRNA export pathway

Aksenova

Lee

Smith

et al. 2019

Preprint

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Nuclear pore complexes (NPCs) are important for many processes beyond nucleocytoplasmic trafficking, including protein modification, chromatin remodeling, transcription, mRNA processing and mRNA export. The multi-faceted nature of NPCs and the slow turnover of their components has made it difficult to understand the role of basket nucleoporins (Nup153, Nup50 and Tpr) in these diverse processes. To address this question, we used an Auxin-Induced Degron (AID) system to distinguish roles of basket nucleoporins: Loss of individual nucleoporins caused distinct alteration in patterns of nucleocytoplasmic trafficking and gene expression. Importantly, Tpr elimination caused rapid and pronounced changes in transcriptomic profiles within two hours of auxin addition. These changes were dissimilar to shifts observed after loss of Nup153 or Nup50, but closely related to changes after depletion of mRNA export receptor NXF1 or the GANP subunit of the TRanscription-EXport-2 (TREX-2) mRNA export complex. Moreover, GANP association to NPCs was specifically disrupted upon TPR depletion. Together, our findings demonstrate a unique and pivotal role of Tpr in regulating gene expression through GANP-and/or NXF1-dependent mRNA nuclear export.

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“…Circulating cells and proteins are easily accessible from fresh blood samples, the collection procedure is less invasive. Since central mechanisms underlying progression of the disease is still not clear, much attention has been drawn to systems biology approaches as a new avenue to elucidate the possible roles of biomolecules in complex diseases such as AD [13,14,15,16]. For example, evidence of involvement of miRNA deregulation in the development of neurodegenerative diseases has emerged [17,18].…”

Section: Introductionmentioning

confidence: 99%

Identification of common molecular biomarker signatures in blood and brain of Alzheimer’s disease

Rahman¹,

Islam

Shahjaman

et al. 2018

Preprint

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Background: Alzheimers disease (AD) is a progressive neurodegenerative disease characterized by memory loss and confusion. Neuroimaging and cerebrospinal fluid-based early detection is limited in sensitivity and specificity as well as by cost. Therefore, detecting AD from blood cell analysis could improve early diagnosis and treatment of the disease. The present study aimed to identify blood cell transcripts that reflect brain expression levels of factors linked to AD progression. Methods: We analyzed blood cell and brain microarray gene expression datasets from NCBI-GEO for AD association and expression in blood and brain. We also used eQTL and epigenetics data to identify AD-related genes that were regulated similarly in blood and brain. Results: We identified 9 differentially expressed genes (DEG; AD versus controls) common to blood cells and brain (CNBD1, SUCLG2-AS1, CCDC65, PDE4D, MTMR1, C3, SLC6A15, LINC01806, and FRG1JP) and 18 genes (HSD17B1, GAS5, RPS5, VKORC1, GLE1, WDR1, RPL12, MORN1, RAD52, SDR39U1, NPHP4, MT1E, SORD, LINC00638, MCM3AP-AS1, GSDMD, RPS9, and GNL2) that were commonly dysregulated between AD blood and brain tissues using SNP and cis-eQTL data. This data revealed significant neurodegeneration-associated molecular pathways in the ribosomal and complement systems. Integration of these different analyses revealed dysregulation of hub transcription factors (SREBF2, NR1H2, NR1H3, PRDM1, XBP1) and microRNAs (miR-518e, miR-518a-3p, miR-518b, miR-518c, miR-518d-3p and miR-518f) in AD. Several significant histone modification sites in DEGs were also identified. Conclusion: We have identified new putative links between pathological processes in brain and transcripts in blood cells in AD subjects that may enable the use of blood to diagnose and monitor AD onset and progression.

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Identification of Key Candidate Genes and Pathways in Colorectal Cancer by Integrated Bioinformatical Analysis

Cited by 134 publications

References 40 publications

Joint analysis of gene expression levels and histological images identifies genes associated with tissue morphology

Joint analysis of gene expression levels and histological images identifies genes associated with tissue morphology

Distinct Basket Nucleoporins roles in Nuclear Pore Function and Gene Expression: Tpr is an integral component of the TREX-2 mRNA export pathway

Identification of common molecular biomarker signatures in blood and brain of Alzheimer’s disease

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