Theoretical and computational studies of the glucose signaling pathways in yeast using global gene expression data

Background: The recent surge of next generation sequencing of breast cancer genomes has enabled development of comprehensive catalogues of somatic mutations and expanded the molecular classification of subtypes of breast cancer. However, somatic mutations and gene expression data have not been leveraged and integrated with epigenomic data to unravel the genomic-epigenomic interaction landscape of triple negative breast cancer (TNBC) and non-triple negative breast cancer (non-TNBC). Methods: We performed integrative data analysis combining somatic mutation, epigenomic and gene expression data from The Cancer Genome Atlas (TCGA) to unravel the possible oncogenic interactions between genomic and epigenomic variation in TNBC and non-TNBC. We hypothesized that within breast cancers, there are differences in somatic mutation, DNA methylation and gene expression signatures between TNBC and non-TNBC. We further hypothesized that genomic and epigenomic alterations affect gene regulatory networks and signaling pathways driving the two types of breast cancer. Results: The investigation revealed somatic mutated, epigenomic and gene expression signatures unique to TNBC and non-TNBC and signatures distinguishing the two types of breast cancer. In addition, the investigation revealed molecular networks and signaling pathways enriched for somatic mutations and epigenomic changes unique to each type of breast cancer. The most significant pathways for TNBC were: retinal biosynthesis, BAG2, LXR/RXR, EIF2 and P2Y purigenic receptor signaling pathways. The most significant pathways for non-TNBC were: UVB-induced MAPK, PCP, Apelin endothelial, Endoplasmatic reticulum stress and mechanisms of viral exit from host signaling Pathways. Conclusion: The investigation revealed integrated genomic, epigenomic and gene expression signatures and signing pathways unique to TNBC and non-TNBC, and a gene signature distinguishing the two types of breast cancer. The study demonstrates that integrative analysis of multi-omics data is a powerful approach for unravelling the genomic-epigenomic interaction landscape in TNBC and non-TNBC.

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Clinical outcome and global gene expression data support the existence of the estrogen receptor-negative/progesterone receptor-positive invasive breast cancer phenotype

Breast Cancer Research and Treatment ◽

10.1007/s10549-015-3651-5 ◽

2015 ◽

Vol 155 (1) ◽

pp. 85-97 ◽

Cited By ~ 8

Author(s):

Werner Schroth ◽

S. Winter ◽

F. Büttner ◽

S. Goletz ◽

S. Faißt ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Estrogen Receptor ◽

Progesterone Receptor ◽

Clinical Outcome ◽

Gene Expression Data ◽

Global Gene Expression ◽

Expression Data ◽

Cancer Phenotype ◽

Estrogen Receptor Negative

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Dimension reduction strategies for analyzing global gene expression data with a response

Mathematical Biosciences ◽

10.1016/s0025-5564(01)00106-7 ◽

2002 ◽

Vol 176 (1) ◽

pp. 123-144 ◽

Cited By ~ 33

Author(s):

Francesca Chiaromonte ◽

Jessica Martinelli

Keyword(s):

Gene Expression ◽

Dimension Reduction ◽

Gene Expression Data ◽

Global Gene Expression ◽

Expression Data ◽

Reduction Strategies

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An analysis of gene expression data involving examination of signaling pathways activation reveals new insights into the mechanism of action of minoxidil topical foam in men with androgenetic alopecia

Cell Cycle ◽

10.1080/15384101.2017.1327492 ◽

2017 ◽

Vol 16 (17) ◽

pp. 1578-1584 ◽

Cited By ~ 4

Author(s):

Georgios N. Stamatas ◽

Jeff Wu ◽

Apostolos Pappas ◽

Paradi Mirmirani ◽

Thomas S. McCormick ◽

...

Keyword(s):

Gene Expression ◽

Signaling Pathways ◽

Gene Expression Data ◽

Mechanism Of Action ◽

Androgenetic Alopecia ◽

Expression Data

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

BMC Cancer ◽

10.1186/s12885-021-08811-7 ◽

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.

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