Bioinformatics of gene expression and copy number data integration

2009 ◽  
pp. 78-101
Author(s):  
Outi Monni ◽  
Sampsa Hautaniemi
Keyword(s):  
Gene Expression ◽  
Data Integration ◽  
Copy Number ◽  
Copy Number Data

scholarly journals 30 Mutli-omic data integration in quantitative genetics

2019 ◽  
Vol 97 (Supplement_2) ◽  
pp. 15-15
Author(s):  
Gota Morota
Keyword(s):  
Gene Expression ◽  
Data Integration ◽  
High Throughput ◽  
Quantitative Genetics ◽  
Copy Number ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Number Variation ◽  
Omic Data Integration ◽  
Omic Data

Abstract The advent of high-throughput technologies has generated diverse omic data including single-nucleotide polymorphisms, copy-number variation, gene expression, methylation, and metabolites. The next major challenge is how to integrate those multi-omic data for downstream analyses to enhance our biological insights. This emerging approach is known as multi-omic data integration, which is in contrast to studying each omic data type independently. I will discuss challenging issues in developing algorithms and methods for multi-omic data integration. The particular focus will be given to the potential for combining diverse types of FAANG data and the utility of multi-omic data integration in association analysis and phenotypic prediction.

scholarly journals Whole genome copy number analyses reveal a highly aberrant genome in TP53 mutant lung adenocarcinoma tumors

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Maria Moksnes Bjaanæs ◽  
Gro Nilsen ◽  
Ann Rita Halvorsen ◽  
Hege G. Russnes ◽  
Steinar Solberg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Gene Expression Data ◽  
Copy Number ◽  
Copy Number Data ◽  
Expression Data ◽  
Mutation Status ◽  
Copy Number Aberrations ◽  
Genomic Architecture ◽  
Lung Adenocarcinomas

Abstract Background Genetic alterations are common in non-small cell lung cancer (NSCLC), and DNA mutations and translocations are targets for therapy. Copy number aberrations occur frequently in NSCLC tumors and may influence gene expression and further alter signaling pathways. In this study we aimed to characterize the genomic architecture of NSCLC tumors and to identify genomic differences between tumors stratified by histology and mutation status. Furthermore, we sought to integrate DNA copy number data with mRNA expression to find genes with expression putatively regulated by copy number aberrations and the oncogenic pathways associated with these affected genes. Methods Copy number data were obtained from 190 resected early-stage NSCLC tumors and gene expression data were available from 113 of the adenocarcinomas. Clinical and histopathological data were known, and EGFR-, KRAS- and TP53 mutation status was determined. Allele-specific copy number profiles were calculated using ASCAT, and regional copy number aberration were subsequently obtained and analyzed jointly with the gene expression data. Results The NSCLC tumors tissue displayed overall complex DNA copy number profiles with numerous recurrent aberrations. Despite histological differences, tissue samples from squamous cell carcinomas and adenocarcinomas had remarkably similar copy number patterns. The TP53-mutated lung adenocarcinomas displayed a highly aberrant genome, with significantly altered copy number profiles including gains, losses and focal complex events. The EGFR-mutant lung adenocarcinomas had specific arm-wise aberrations particularly at chromosome7p and 9q. A large number of genes displayed correlation between copy number and expression level, and the PI(3)K-mTOR pathway was highly enriched for such genes. Conclusions The genomic architecture in NSCLC tumors is complex, and particularly TP53-mutated lung adenocarcinomas displayed highly aberrant copy number profiles. We suggest to always include TP53-mutation status when studying copy number aberrations in NSCLC tumors. Copy number may further impact gene expression and alter cellular signaling pathways.

Integrative analysis of gene expression profiling and high-resolution genomic copy number in gastrointestinal stromal tumor (GIST)

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 10559-10559
Author(s):  
M. Nannini ◽  
A. Astolfi ◽  
M. A. Pantaleo ◽  
M. Di Battista ◽  
S. Formica ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tumor Suppressor ◽  
Tumor Suppressor Genes ◽  
Copy Number ◽  
Snp Array ◽  
Copy Number Data ◽  
Expression Data ◽  
Suppressor Genes ◽  
Genomic Copy Number ◽  
Genomic Copy

10559 Background: Besides mutually exclusive cKIT or PDGFRA mutations, sequential accumulation of other genetic events may be involved in GISTs development and progression, but very few data is still available. Methods: Fresh tissues specimens of GISTs from 10 patients (9 gastric and 1 intestinal) were collected and used for RNA and DNA extraction, labeled and hybridized to HG-U133Plus 2.0 and SNP array 6.0, respectively (Affymetrix). Six patients had exon 9 or exon 11 c-KIT mutation, two PDGFRA mutation, and other two wild-type disease. Gene expression data were quantified by the RMA algorithm, filtered and analysed with supervised techniques (SAM algorithm). Genomic copy number data were analysed with Partek Genomic Suite software against a reference set of 90 Ceu HapMap individuals using a segmentation algorithm with stringent p-value cutoff. Results: Almost all patients exhibited both macroscopic cytogenetic alterations and cryptic microdeletions or amplifications by SNP-array copy number data analysis. The most frequent chromosomal alterations were: 14q complete or partial deletion (7/10), chromosome 19 monosomy (3/10), 22q and 1p deletion (2/10), chromosome 5 trisomy (2/10). The minimal overlapping region ranged from 14q22.3 to 14q32.33, covering a region including 320 genes. The integration of copy number and gene expression data showed that at least 40% of the genes inside the 14q deleted region were significantly downregulated (FDR<10%) in comparison to 14q-diploid patients. In this region several tumor suppressor genes involved in cell cycle checkpoint control (SNW1, CHES1, PPP2R5E), apoptosis induction (PPM1A, MOAP1, PPP1R13B), DNA damage response (MLH3, TDP1), WNT/Notch pathway inhibition (NUMB, DACT1, SEL1L) are located. Conclusions: A wide spectrum of genetic aberrations in GISTs may occur besides c-KIT and PDGFRA mutations. The most frequent is 14q deletion that leads to a significant downregulation of many putative tumor suppressor genes. Combining gene expression and high resolution genomic copy number analysis could identify new haploinsufficient tumor suppressor genes involved in GISTs pathogenesis and tumor progression. No significant financial relationships to disclose.

scholarly journals Whole Genome Copy Number Analyses Reveal a Highly Aberrant Genome in TP53 Mutant Lung Adenocarcinoma Tumors

2021 ◽  
Author(s):  
Maria Moksnes Bjaanaes ◽  
Gro Nilsen ◽  
Ann Rita Halvorsen ◽  
Hege G. Russens ◽  
Steinar Solberg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Gene Expression Data ◽  
Copy Number ◽  
Copy Number Data ◽  
Expression Data ◽  
Mutation Status ◽  
Copy Number Aberrations ◽  
Genomic Architecture ◽  
Lung Adenocarcinomas

Abstract Background: Genetic alterations are common in non-small cell lung cancer (NSCLC), and DNA mutations and translocations are targets for therapy. Copy number aberrations occur frequently in NSCLC tumors and may influence gene expression and further alter signaling pathways. In this study we aimed to characterize the genomic architecture of NSCLC tumors and to identify genomic differences between tumors stratified by histology and mutation status. Furthermore, we sought to integrate DNA copy number data with mRNA expression to find genes with expression putatively regulated by copy number aberrations and the oncogenic pathways associated with these affected genes. Methods: Copy number data were obtained from 190 resected early-stage NSCLC tumors and gene expression data were available from 113 of the adenocarcinomas. Clinical and histopathological data were known, and EGFR-, KRAS- and TP53 mutation status was determined. Allele-specific copy number profiles were calculated using ASCAT, and regional copy number aberration were subsequently obtained and analyzed jointly with the gene expression data.Results:The NSCLC tumors tissue displayed overall complex DNA copy number profiles with numerous recurrent aberrations. Despite histological differences, tissue samples from squamous cell carcinomas and adenocarcinomas had remarkably similar copy number patterns. The TP53-mutated lung adenocarcinomas displayed a highly aberrant genome, with significantly altered copy number profiles including gains, losses and focal complex events. The EGFR-mutant lung adenocarcinomas had specific arm-wise aberrations particularly at chromosome7p and 9q. A large number of genes displayed correlation between copy number and expression level, and the PI(3)K-mTOR pathway was highly enriched for such genes.Conclusions: The genomic architecture in NSCLC tumors is complex, and particularly TP53-mutated lung adenocarcinomas displayed highly aberrant copy number profiles. We suggest to always include TP53-mutation status when studying copy number aberrations in NSCLC tumors. Copy number may further impact gene expression and alter cellular signaling pathways.

scholarly journals Constructing Bayesian networks by integrating gene expression and copy number data identifies NLGN4Y as a novel regulator of prostate cancer progression

Oncotarget ◽  
2016 ◽  
Vol 7 (42) ◽  
pp. 68688-68707 ◽  
Author(s):  
Yixuan Gong ◽  
Li Wang ◽  
Uma Chippada-Venkata ◽  
Xudong Dai ◽  
William K. Oh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Bayesian Networks ◽  
Cancer Progression ◽  
Copy Number ◽  
Copy Number Data ◽  
Prostate Cancer Progression

scholarly journals Exploration of the immune cell landscape in brain cancer utilizing gene expression and copy number data

2018 ◽  
Author(s):  
Yuriy Gusev ◽  
Krithika Bhuvaneshwar ◽  
Subha Madhavan
Keyword(s):  
Gene Expression ◽  
Cancer Patients ◽  
Immune Cells ◽  
Brain Cancer ◽  
Copy Number ◽  
Immune Cell ◽  
Lower Grade ◽  
Copy Number Data ◽  
Large Brain ◽  
The Us

Brain cancer is a common cancer that affects more than 700,000 people in the US every year. We explore the dynamic changes in the abundance of immune cells based on RNA and DNA samples extracted from a large cohort of brain cancer patients. We used gene expression data and copy number data from a large brain cancer collections - the REMBRANDT project (REpository for Molecular BRAin Neoplasia DaTa) that includes 671 patients. We applied virtual flow cytometry tools CIBERSORT and xCell to estimate the abundance of the immune cells in the RNA of these samples. The immune cell landscape in this dataset is compared with that of the TCGA brain cancer collection, that includes 511 patients with Lower Grade Glioma (TCGA-LGG) and 156 patients with Glioblastoma (TCGA-GBM). We also discuss how well the results align with published literature, and how this computational analysis can help better understand how immune cells affect clinical outcome and survival in brain cancer patients.

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