Genomic copy number alterations as predictive markers in breast cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE10181 | GEO | 2008/01/17
SECONDARY ACCESSION(S): PRJNA108393
REPOSITORIES: GEO
Similar Datasets
Project description:This SuperSeries is composed of the following subset Series: GSE10128: Genomic copy number alterations as predictive markers of systemic recurrence in breast cancer GSE10129: Genomic copy number alterations as predictive markers of neoadjuvant chemotherapy response in breast cancer Refer to individual Series
2010-05-27 | E-GEOD-10181 | biostudies-arrayexpress
Project description:Genomic copy number alterations as predictive markers in breast cancer
| PRJNA108393 | ENA
Project description:Array CGH containing 4,044 human bacterial artificial chromosome clones was used to assess copy number changes in 31 pairs of clinicopathologically well matched recurred / nonrecurred breast cancer tissues. Keywords: array CGH
2008-01-17 | GSE10128 | GEO
Project description:Array CGH containing 4,044 human bacterial artificial chromosome clones was used to assess copy number changes in 31 pairs of clinicopathologically well matched recurred / nonrecurred breast cancer tissues. Array CGH containing 4,044 human bacterial artificial chromosome clones was used to assess copy number changes in 31 pairs of clinicopathologically well matched recurred / nonrecurred breast cancer tissues.
2010-05-26 | E-GEOD-10128 | biostudies-arrayexpress
Project description:Array CGH containing 4,044 human bacterial artificial chromosome clones was used to assess different copy number changes between chemotherapy responsive and non-resposive breast cancer tissues. Keywords: Array CGH
2008-01-17 | GSE10129 | GEO
Project description:Array CGH containing 4,044 human bacterial artificial chromosome clones was used to assess different copy number changes between chemotherapy responsive and non-resposive breast cancer tissues. Array CGH containing 4,044 human bacterial artificial chromosome clones was used to assess different copy number changes between chemotherapy responsive and non-resposive breast cancer tissues.
2010-05-26 | E-GEOD-10129 | biostudies-arrayexpress
Project description:BackgroundPABC, commonly defined as breast cancer diagnosed during or ≤ 1 year after pregnancy, accounts for 7% of all breast cancers in women ≤ 45 years. Compared to age-matched non-PABC patients, PABC is characterized by a particularly aggressive histopathologic profile with poorly differentiated and estrogen- and progesterone receptor negative tumors and associated high mortality rates. This study assessed the genomic background of triple-negative PABC tumors by detection of copy number alterations (CNAs).MethodsMLPA was used to compare CNAs in breast cancer-associated chromosomal loci between triple-negative PABC- and subtype-matched non-PABC patients. Both CNA patterns were evaluated by cluster analysis; associations between individual gene CNAs, pathological characteristics and survival were explored.ResultsTriple-negative PABC tumors exhibited unique CNAs compared to non-PABC tumors, including enrichment for TOP2A copy number loss, an independent predictor of worse overall survival (HR 8.96, p = 0.020). Cluster analysis based on CNA profiles identified a triple-negative PABC-subgroup with a particularly poor prognosis, characterized by chromosome 8p copy number loss. Individual gene CNAs analysis revealed that FGFR1 copy number loss on chromosome 8p11.23 was an independent predictor of poor outcome in multivariate analysis (HR 3.59, p = 0.053) and predicted the development of distant metastases (p = 0.048).ConclusionThis study provides novel insights into the biology of triple-negative PABC tumors suggesting that CNAs, particularly 8p loss and TOP2A loss, are involved in the development of breast cancer during pregnancy. FGFR1 loss and TOP2A loss seem to be promising new biomarkers that independently identify subgroups of PABC patients with poor prognosis. These genomic biomarkers may provide clues for personalized therapy.
| S-EPMC9424154 | biostudies-literature
Project description:INTRODUCTION: HER2 gene amplification and protein overexpression (HER2+) define a clinically challenging subgroup of breast cancer with variable prognosis and response to therapy. Although gene expression profiling has identified an ERBB2 molecular subtype of breast cancer, it is clear that HER2+ tumors reside in all molecular subtypes and represent a genomically and biologically heterogeneous group, needed to be further characterized in large sample sets. METHODS: Genome-wide DNA copy number profiling, using bacterial artificial chromosome (BAC) array comparative genomic hybridization (aCGH), and global gene expression profiling were performed on 200 and 87 HER2+ tumors, respectively. Genomic Identification of Significant Targets in Cancer (GISTIC) was used to identify significant copy number alterations (CNAs) in HER2+ tumors, which were related to a set of 554 non-HER2 amplified (HER2-) breast tumors. High-resolution oligonucleotide aCGH was used to delineate the 17q12-q21 region in high detail. RESULTS: The HER2-amplicon was narrowed to an 85.92 kbp region including the TCAP, PNMT, PERLD1, HER2, C17orf37 and GRB7 genes, and higher HER2 copy numbers indicated worse prognosis. In 31% of HER2+ tumors the amplicon extended to TOP2A, defining a subgroup of HER2+ breast cancer associated with estrogen receptor-positive status and with a trend of better survival than HER2+ breast cancers with deleted (18%) or neutral TOP2A (51%). HER2+ tumors were clearly distinguished from HER2- tumors by the presence of recurrent high-level amplifications and firestorm patterns on chromosome 17q. While there was no significant difference between HER2+ and HER2- tumors regarding the incidence of other recurrent high-level amplifications, differences in the co-amplification pattern were observed, as shown by the almost mutually exclusive occurrence of 8p12, 11q13 and 20q13 amplification in HER2+ tumors. GISTIC analysis identified 117 significant CNAs across all autosomes. Supervised analyses revealed: (1) significant CNAs separating HER2+ tumors stratified by clinical variables, and (2) CNAs separating HER2+ from HER2- tumors. CONCLUSIONS: We have performed a comprehensive survey of CNAs in HER2+ breast tumors, pinpointing significant genomic alterations including both known and potentially novel therapeutic targets. Our analysis sheds further light on the genomically complex and heterogeneous nature of HER2+ tumors in relation to other subgroups of breast cancer.
| S-EPMC2917012 | biostudies-literature
Project description:Breast cancer diagnosis in young women has emerged as an independent prognostic factor with higher recurrence risk and death than their older counterparts. We aim to find recurrent somatic copy number alteration (CNA) regions identified from breast cancer microarray data and associate the CNA status of the genes harbored in the regions to the survival of young women with breast cancer. By using the interval graph-based algorithm we developed, and the CNA data consisting of a Discovery set with 130 young women and a Validation set with 125 young women, we identified 38 validated recurrent CNAs containing 39 protein encoding genes. CNA gain regions encompassing genes CAPN2, CDC73 and ASB13 are the top 3 with the highest occurring frequencies in both the Discovery and Validation dataset, while gene SGCZ ranked top for the recurrent CNA loss regions. The mutation status of 9 of the 39 genes shows significant associations with breast cancer specific survival. Interestingly, the expression level of 2 of the 9 genes, ASB13 and SGCZ, shows significant association with survival outcome. Patients with CNA mutations in both of these genes had a worse survival outcome when compared to patients without the gene mutations. The mutated CNA status in gene ASB13 was associated with a higher gene expression, which predicted patient survival outcome. Together, identification of the CNA events with prognostic significance in young women with breast cancer may be used in genomic-guided treatment.
| S-EPMC5837756 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2018-08-31 | GSE87049 | GEO