14 research outputs found
Coamplification of DAD-R, SOX5, and EKI1 in human testicular seminomas, with specific overexpression of DAD-R, correlates with reduced levels of apoptosis and earlier clinical manifestation
Seminomas and nonseminomas represent the invasive stages of testicular
(TGCTs) of adolescents and adults. Although TGCTs are characterized by
extra copies of the short arm of chromosome 12, the genetic basis for gain
of 12p in the pathogenesis of this cancer is not yet understood. We have
demonstrated that gain of 12p is related to invasive growth and that
amplification of specific 12p sequences, i.e., 12p11.2-p12.1, correlates
with reduced apoptosis in the tumors. Here we show that three known genes
map within the newly determined shortest region of overlap of
amplification (SROA): DAD-R, SOX5, and EKI1. Whereas EKI1 maps close to
the telomeric region of the SROA, DAD-R is the first gene at the
centromeric region within the 12p amplicon. Although all three genes are
amplified to the same level within the SROA, expression of DAD-R is
significantly up-regulated in seminomas with the restricted 12p
amplification compared with seminomas without this amplicon. DAD-R is also
highly expressed in nonseminomas of various histologies and derived cell
lines, both lacking such amplification. This finding is of particular
interest because seminomas with the restricted 12p amplification and
nonseminomas are manifested clinically in the third decade of life and
show a low degree of apoptosis. In contrast, seminomas lacking a
restricted 12p amplification, showing significantly lower levels of DAD-R
with pronounced apoptosis, manifest clinically in the fourth decade of
life. A low level of DAD-R expression is also observed in normal
testicular parenchyma and in parenchyma containing the precursor cells of
this cancer, i.e., carcinoma in situ. Therefore, elevated DAD-R expression
in seminomas and nonseminomas correlates with invasive growth and a
reduced level of apoptosis associated with an earlier clinical
presentation. These data implicate DAD-R as a candidate gene responsible
in part for the pathological effects resulting from gain of 12p sequences
in TGCTs. In addition, our results also imply differences in expression
regulation of DAD-R between seminomas and nonseminomas
Anti-Epithelial Cell Adhesion Molecule Antibodies and the Detection of Circulating Normal-Like Breast Tumor Cells
Identification of specific subtypes of circulating tumor cells in peripheral blood of cancer patients can provide information about the biology of metastasis and improve patient management. However, to be effective, the method used to identify circulating tumor cells must detect all tumor cell types. We investigated whether the five subtypes of human breast cancer cells that have been defined by global gene expression profiling—normal-like, basal, HER2-positive, and luminal A and B—were identified by CellSearch, a US Food and Drug Administration–approved test that uses antibodies against the cell surface–expressed epithelial cell adhesion molecule (EpCAM) to isolate circulating tumor cells. We used global gene expression profiling to determine the subtypes of a well-defined panel of 34 human breast cancer cell lines (15 luminal, nine normal-like, five basal-like, and five Her2-positive). We mixed 50-150 cells from 10 of these cell lines with 7.5 mL of blood from a single healthy human donor, and the mixtures were subjected to the CellSearch test to isolate the breast cancer cells. We found that the CellSearch isolation method, which uses EpCAM on the surface of circulating tumor cells for cell isolation, did not recognize, in particular, normal-like breast cancer cells, which in general have aggressive features. New tests that include antibodies that specifically recognize normal-like breast tumor cells but not cells of hematopoietic origin are needed
Low-risk susceptibility alleles in 40 human breast cancer cell lines
Background: Low-risk breast cancer susceptibility alleles or SNPs confer only modest breast cancer risks ranging from just over 1.0 to 1.3 fold. Yet, they are common among most populations and therefore are involved in the development of essentially all breast cancers. The mechanism by which the low-risk SNPs confer breast cancer risks is currently unclear. The breast cancer association consortium BCAC has hypothesized that the low-risk SNPs modulate expression levels of nearby located genes. Methods: Genotypes of five low-risk SNPs were determined for 40 human breast cancer cell lines, by direct sequencing of PCR-amplified genomic templates. We have analyzed expression of the four genes that are located nearby the low-risk SNPs, by using real-time RT-PCR and Human Exon microarrays. Results: The SNP genotypes and additional phenotypic data on the breast cancer cell lines are presented. We did not detect any effect of the SNP genotypes on expression levels of the nearby-located genes MAP3K1, FGFR2, TNRC9 and LSP1. Conclusion: The SNP genotypes provide a base line for functional studies in a well-characterized cohort of 40 human breast cancer cell lines. Our expression analyses suggest that a putative disease mechanism through gene expression modulation is not operative in breast cancer cell lines
Exon expression arrays as a tool to identify new cancer genes
Background: Identification of genes that are causally implicated in oncogenesis is a major goal in cancer research. An estimated 10-20% of cancer-related gene mutations result in skipping of one or more exons in the encoded transcripts. Here we report on a strategy to screen in a global fashion for such exon-skipping events using PAttern based Correlation (PAC). The PAC algorithm has been used previously to identify differentially expressed splice variants between two predefined subgroups. As genetic changes in cancer are sample specific, we tested the ability of PAC to identify aberrantly expressed exons in single samples. Principal Findings: As a proof-of-principle, we tested the PAC strategy on human cancer samples of which the complete coding sequence of eight cancer genes had been screened for mutations. PAC detected all seven exon-skipping mutants among 12 cancer cell lines. PAC also identified exon-skipping mutants in clinical cancer specimens although detection was compromised due to heterogeneous (wild-type) transcript expression. PAC reduced the number candidate genes/exons for subsequent mutational analysis by two to three orders of magnitude and had a substantial true positive rate. Importantly, of 112 randomly selected outlier exons, sequence analysis identified two novel exon skipping events, two novel base changes and 21 previously reported base changes (SNPs). Conclusions: The ability of PAC to enrich for mutated transcripts and to identify known and novel genetic changes confirms its suitability as a strategy to identify candidate cancer genes
The CHEK2 1100delC mutation identifies families with a hereditary breast and colorectal cancer phenotype
Because of genetic heterogeneity, the identification of breast
cancer-susceptibility genes has proven to be exceedingly difficult. Here,
we define a new subset of families with breast cancer characterized by the
presence of colorectal cancer cases. The 1100delC variant of the cell
cycle checkpoint kinase CHEK2 gene was present in 18% of 55 families with
hereditary breast and colorectal cancer (HBCC) as compared with 4% of 380
families with non-HBCC (P<.001), thus providing genetic evidence for the
HBCC phenotype. The CHEK2 1100delC mutation was, however, not the major
predisposing factor for the HBCC phenotype but appeared to act in synergy
with another, as-yet-unknown susceptibility gene(s). The unequivocal
definition of the HBCC phenotype opens new avenues to search for thi
Distinct gene mutation profiles among luminal-type and basal-type breast cancer cell lines
Affymetrix HG-U133A gene expression profiles of 39 human breast cancer cell lines
Microarrays were used to detail the global programme of gene expression underlying breast cancer cell lines. We identified two main groups of luminal-type and basal-type breast cancer cell lines by unsupervised Pearson correlation of breast cancer cell lines and intrinsic subtyping. Supervised analysis on spindle versus non-spindle breast cancer cell lines identified a spindle cell signature of 1,144 genes identifying all spindle, basal-type, E-cadherin methylated breast cancer cell lines. Breast cancer cell lines were grown to optimal cell densities for RNA extraction and hybridization on Affymetrix microarrays
Affymetrix HG-U133A gene expression profiles of 39 human breast cancer cell lines
Microarrays were used to detail the global programme of gene expression underlying breast cancer cell lines. We identified two main groups of luminal-type and basal-type breast cancer cell lines by unsupervised Pearson correlation of breast cancer cell lines and intrinsic subtyping. Supervised analysis on spindle versus non-spindle breast cancer cell lines identified a spindle cell signature of 1,144 genes identifying all spindle, basal-type, E-cadherin methylated breast cancer cell lines. Breast cancer cell lines were grown to optimal cell densities for RNA extraction and hybridization on Affymetrix microarrays