Please use this identifier to cite or link to this item: https://doi.org/10.18632/oncotarget.6255
Title: Sense-antisense gene-pairs in breast cancer and associated pathological pathways
Authors: Grinchuk, O.V 
Motakis, E
Yenamandra, S.P
Ow, G.S
Jenjaroenpun, P
Tang, Z
Yarmishyn, A.A
Ivshina, A.V
Kuznetsov, V.A
Keywords: proteasome
small interfering RNA
complementary RNA
GA binding protein
GABPA protein, human
RNA
Article
breast cancer
cancer prognosis
cancer survival
carcinogenesis
cell cycle
controlled study
copy number variation
disease association
gene expression
high risk population
histopathology
human
major clinical study
molecular genetics
reverse transcription polymerase chain reaction
sense antisense gene pair
spliceosome
tumor growth
breast tumor
DNA microarray
female
gene expression profiling
gene expression regulation
gene regulatory network
genetics
Kaplan Meier method
pathology
procedures
prognosis
proportional hazards model
risk factor
RNA interference
signal transduction
statistics and numerical data
Breast Neoplasms
Cell Cycle
Female
GA-Binding Protein Transcription Factor
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Gene Regulatory Networks
Humans
Kaplan-Meier Estimate
Oligonucleotide Array Sequence Analysis
Prognosis
Proportional Hazards Models
Reverse Transcriptase Polymerase Chain Reaction
Risk Factors
RNA Interference
RNA, Antisense
RNA, Neoplasm
Signal Transduction
Issue Date: 2015
Citation: Grinchuk, O.V, Motakis, E, Yenamandra, S.P, Ow, G.S, Jenjaroenpun, P, Tang, Z, Yarmishyn, A.A, Ivshina, A.V, Kuznetsov, V.A (2015). Sense-antisense gene-pairs in breast cancer and associated pathological pathways. Oncotarget 6 (39) : 42197-42221. ScholarBank@NUS Repository. https://doi.org/10.18632/oncotarget.6255
Rights: Attribution 4.0 International
Abstract: More than 30% of human protein-coding genes form hereditary complex genome architectures composed of sense-antisense (SA) gene pairs (SAGPs) transcribing their RNAs from both strands of a given locus. Such architectures represent important novel components of genome complexity contributing to gene expression deregulation in cancer cells. Therefore, the architectures might be involved in cancer pathways and, in turn, be used for novel drug targets discovery. However, the global roles of SAGPs in cancer pathways has not been studied. Here we investigated SAGPs associated with breast cancer (BC)-related pathways using systems biology, prognostic survival and experimental methods. Gene expression analysis identified 73 BC-relevant SAGPs that are highly correlated in BC. Survival modelling and metadata analysis of the 1161 BC patients allowed us to develop a novel patient prognostic grouping method selecting the 12 survival-significant SAGPs. The qRT-PCR-validated 12-SAGP prognostic signature reproducibly stratified BC patients into low- and high-risk prognostic subgroups. The 1381 SAGP-defined differentially expressed genes common across three studied cohorts were identified. The functional enrichment analysis of these genes revealed the GABPA gene network, including BC-relevant SAGPs, specific gene sets involved in cell cycle, spliceosomal and proteasomal pathways. The co-regulatory function of GABPA in BC cells was supported using siRNA knockdown studies. Thus, we demonstrated SAGPs as the synergistically functional genome architectures interconnected with cancer-related pathways and associated with BC patient clinical outcomes. Taken together, SAGPs represent an important component of genome complexity which can be used to identify novel aspects of coordinated pathological gene networks in cancers.
Source Title: Oncotarget
URI: https://scholarbank.nus.edu.sg/handle/10635/180923
ISSN: 19492553
DOI: 10.18632/oncotarget.6255
Rights: Attribution 4.0 International
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