English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Volume 4 • Issue 1 • 1000127 J Data Mining Genomics Proteomics ISSN:2153-0602 JDMGP an open access journal Of all human carcinomas, breast cancer (BrCa) is worldwide the most frequently occurring tumor in women [1]. Most breast cancer patients succumb to their disease as a result of tumor metastasis [2,3]. It is therefore important to elucidate the factors which effect BrCa progression, therapy resistance and metastasis. Accumulated evidence could demonstrate that breast cancer is a very complex and intrinsically heterogeneous disease, which progresses through accumulation of genomic aberrations that enable development of cancer-specific pathophysiological changes such as unlimited growth in even nutrient limited environments and metastasis to distant organs [4,5]. Recent advances in technology, such as DNA and RNA microarrays, have allowed to deconvolute some of the heterogeneity and complexity of somatic BrCa genetics. Using RNA microarrayderived expression data, breast cancer has been classified into five molecular subtypes: normal breast like, luminal A, luminal B, HER2+/ ERBB2+, and basal-like. Among these molecular subtypes, basal-type breast cancer is associated with a most aggressive growth and poor prognosis [6]. Based on these molecular findings, some improvements have been made in diagnosis and treatment of breast cancer. However, for most patients, the prognosis and disease-free survival times have not changed dramatically. This is likely due to mechanisms by which gene amplifications affect survival or other aspects of cancer pathophysiology most of which are not well understood. Thus, mechanistic and functional studies of molecular changes in breast cancer-are urgently required.

journal of data mining in genomics and proteomics

Meta-analysis of Aurora Kinase A (AURKA) Expression Data Reveals a Significant Correlation between Increased AURKA Expression and Distant Metastases in Human ER-positive Breast Cancers