Dataset Information

Computational analysis of mRNA expression profiles identifies the ITG family and PIK3R3 as crucial genes for regulating triple negative breast cancer cell migration.

ABSTRACT: Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer that does not express estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (Her2/neu). TNBC has worse clinical outcomes than other breast cancer subtypes. However, the key molecules and mechanisms of TNBC migration remain unclear. In this study, we compared two normalized microarray datasets from GEO database between Asian (GSE33926) and non-Asian populations (GSE46581) to determine the molecules and common pathways in TNBC migration. We demonstrated that 16 genes in non-Asian samples and 9 genes in Asian samples are related to TNBC migration. In addition, our analytic results showed that 4 genes, PIK3R3, ITGB1, ITGAL, and ITGA6, were involved in the regulation of actin cytoskeleton. Our results indicated potential genes that link to TNBC migration. This study may help identify novel therapeutic targets for drug development in cancer therapy.

SUBMITTER: Klahan S

PROVIDER: S-EPMC4032728 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Computational analysis of mRNA expression profiles identifies the ITG family and PIK3R3 as crucial genes for regulating triple negative breast cancer cell migration.

Klahan Sukhontip S Wu Mei-Shin MS Hsi Edward E Huang Chi-Cheng CC Hou Ming-Feng MF Chang Wei-Chiao WC

BioMed research international 20140506

Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer that does not express estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (Her2/neu). TNBC has worse clinical outcomes than other breast cancer subtypes. However, the key molecules and mechanisms of TNBC migration remain unclear. In this study, we compared two normalized microarray datasets from GEO database between Asian (GSE33926) and non-Asian populations (GSE46581) to determ ...[more]

PMID: 24982892

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Project description:Triple negative breast cancer (TNBC) is high-risk due to its rapid drug resistance and recurrence, metastasis, and lack of targeted therapy. So far, no molecularly targeted therapeutic agents have been clinically approved for TNBC. It is imperative that we discover new targets for TNBC therapy.A large volume of cancer genomics data are emerging and advancing breast cancer research. We may integrate different types of TNBC genomic data to discover molecular targets for TNBC therapy.We used publicly available TNBC tumor tissue genomic data in the Cancer Genome Atlas database in this study.We integratively explored genomic profiles (gene expression, copy number, methylation, microRNA [miRNA], and gene mutation) in TNBC and identified hyperactivated genes that have higher expression, more copy numbers, lower methylation level, or are targets of miRNAs with lower expression in TNBC than in normal samples. We ranked the hyperactivated genes into different levels based on all the genomic evidence and performed functional analyses of the sets of genes identified. More importantly, we proposed potential molecular targets for TNBC therapy based on the hyperactivated genes.Some of the genes we identified such as FGFR2, MAPK13, TP53, SRC family, MUC family, and BCL2 family have been suggested to be potential targets for TNBC treatment. Others such as CSF1R, EPHB3, TRIB1, and LAD1 could be promising new targets for TNBC treatment. By utilizing this integrative analysis of genomic profiles for TNBC, we hypothesized that some of the targeted treatment strategies for TNBC currently in development are more likely to be promising, such as poly (ADP-ribose) polymerase inhibitors, while the others are more likely to be discouraging, such as angiogenesis inhibitors.The findings in this study need to be experimentally validated in the future.This is a systematic study that combined 5 different types of genomic data to molecularly characterize TNBC and identify potential targets for TNBC therapy. The integrative analysis of genomic profiles for TNBC could assist in identifying potential new therapeutic targets and predicting the effectiveness of a targeted treatment strategy for TNBC therapy.

Dataset Information

Computational analysis of mRNA expression profiles identifies the ITG family and PIK3R3 as crucial genes for regulating triple negative breast cancer cell migration.

Publications

Computational analysis of mRNA expression profiles identifies the ITG family and PIK3R3 as crucial genes for regulating triple negative breast cancer cell migration.

Similar Datasets

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