64 research outputs found

    Gene expression profiling in primary breast cancer distinguishes patients developing local recurrence after breast-conservation surgery, with or without postoperative radiotherapy

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    Introduction Some patients with breast cancer develop local recurrence after breast-conservation surgery despite postoperative radiotherapy, whereas others remain free of local recurrence even in the absence of radiotherapy. As clinical parameters are insufficient for identifying these two groups of patients, we investigated whether gene expression profiling would add further information. Methods We performed gene expression analysis (oligonucleotide arrays, 26,824 reporters) on 143 patients with lymph node-negative disease and tumor-free margins. A support vector machine was employed to build classifiers using leave-one-out cross-validation. Results Within the estrogen receptor-positive (ER+) subgroup, the gene expression profile clearly distinguished patients with local recurrence after radiotherapy (n = 20) from those without local recurrence (n = 80 with or without radiotherapy). The receiver operating characteristic (ROC) area was 0.91, and 5,237 of 26,824 reporters had a P value of less than 0.001 (false discovery rate = 0.005). This gene expression profile provides substantially added value to conventional clinical markers (for example, age, histological grade, and tumor size) in predicting local recurrence despite radiotherapy. Within the ER- subgroup, a weaker, but still significant, signal was found (ROC area = 0.74). The ROC area for distinguishing patients who develop local recurrence from those who remain local recurrence-free in the absence of radiotherapy was 0.66 (combined ER+/ER-). Conclusion A highly distinct gene expression profile for patients developing local recurrence after breast-conservation surgery despite radiotherapy has been identified. If verified in further studies, this profile might be a most important tool in the decision making for surgery and adjuvant therapy

    Galectin-8 in IgA Nephritis: Decreased Binding of IgA by Galectin-8 Affinity Chromatography and Associated Increased Binding in Non-IgA Serum Glycoproteins

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    Background Immunoglobulin A nephritis (IgAN) is the most common primary glomerulonephritis worldwide. It is caused by accumulation of IgA1-containing immune complexes in the kidney resulting in renal failure, which is thought to be due to altered glycosylation of IgA with a decrease of 2-3-sialylated galactosides (NeuAc alpha 2-3Gal). less thanbrgreater than less thanbrgreater thanPurpose The purpose of this study was to analyze whether altered glycosylation of IgA would lead to an altered binding to galectin-8, an endogenous lectin with strong affinity for 2-3-sialylated galactosides. Galectins are a family of beta-galactoside-binding proteins; by binding various glycoproteins, they play important roles in the regulation of cellular functions in inflammation and immunity. Hence, an altered binding of IgA to galectin-8 could lead to pathologic immune functions, such as glomerulonephritis. less thanbrgreater than less thanbrgreater thanMethods Affinity chromatography of serum glycoproteins on the human sialogalactoside-binding lectin galectin-8N permitted quantitation of bound and unbound fractions, including IgA. less thanbrgreater than less thanbrgreater thanResults Analysis of similar to 100 IgA nephritis sera showed that the galectin-8N unbound fraction of IgA increased compared to similar to 100 controls, consistent with the known loss of galactosylation. A subgroup of similar to 15% of the IgAN patients had a ratio of galectin-8 bound/unbound IgA andlt;0.09, not found for any of the controls. Unexpectedly, the galectin-8N-binding fraction of serum glycoproteins other than IgA increased in the sera of IgAN patients but not in controls, suggesting a previously unrecognized change in this disease. less thanbrgreater than less thanbrgreater thanConclusion This is the first study that relates a galectin, an endogenous lectin family, to IgA nephritis and thus should stimulate new avenues of research into the pathophysiology of the disease.Funding Agencies|Swedish Research Council (Vetenskapsradet)|2008-3356|Swedish Foundation for Swedish Research|FFL4|Swedish Healthcare System (ALF)||Region Skane||</p

    The Expression of VEGF-A Is Down Regulated in Peripheral Blood Mononuclear Cells of Patients with Secondary Progressive Multiple Sclerosis

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    BACKGROUND: Most patients with relapsing-remitting multiple sclerosis (RRMS) eventually enter a secondary progressive (SPMS) phase, characterized by increasing neurological disability. The mechanisms underlying transition to SPMS are unknown and effective treatments and biomarkers are lacking. Vascular endothelial growth factor-A (VEGF-A) is an angiogenic factor with neuroprotective effects that has been associated with neurodegenerative diseases. SPMS has a prominent neurodegenerative facet and we investigated a possible role for VEGF-A during transition from RRMS to SPMS. METHODOLOGY/PRINCIPAL FINDINGS: VEGF-A mRNA expression in peripheral blood mononuclear (PBMC) and cerebrospinal fluid (CSF) cells from RRMS (n = 128), SPMS (n = 55) and controls (n = 116) were analyzed using real time PCR. We demonstrate reduced expression of VEGF-A mRNA in MS CSF cells compared to controls (p<0.001) irrespective of disease course and expression levels are restored by natalizumab treatment(p<0.001). VEGF-A was primarily expressed in monocytes and our CSF findings in part may be explained by effects on relative monocyte proportions. However, VEGF-A mRNA expression was also down regulated in the peripheral compartment of SPMS (p<0.001), despite unchanged monocyte counts, demonstrating a particular phenotype differentiating SPMS from RRMS and controls. A possible association of allelic variability in the VEGF-A gene to risk of MS was also studied by genotyping for six single nucleotide polymorphisms (SNPs) in MS (n = 1114) and controls (n = 1234), which, however, did not demonstrate any significant association between VEGF-A alleles and risk of MS. CONCLUSIONS/SIGNIFICANCE: Expression of VEGF-A in CSF cells is reduced in MS patients compared to controls irrespective of disease course. In addition, SPMS patients display reduced VEGF-A mRNA expression in PBMC, which distinguish them from RRMS and controls. This indicates a possible role for VEGF-A in the mechanisms regulating transition to SPMS. Decreased levels of PBMC VEGF-A mRNA expression should be further evaluated as a biomarker for SPMS

    High-resolution genomic and expression analyses of copy number alterations in HER2-amplified breast cancer

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    To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldINTRODUCTION: 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

    The human capital transition and the role of policy

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    Along with information and communication technology, infrastructure, and the innovation system, human capital is a key pillar of the knowledge economy with its scope for increasing returns. With this in mind, the purpose of this chapter is to investigate how industrialized economies managed to achieve the transition from low to high levels of human capital. The first phase of the human capital transition was the result of the interaction of supply and demand, triggered by technological change and boosted by the demands for (immaterial) services. The second phase of the human capital transition (i.e., mass education) resulted from enforced legislation and major public investment. The state’s aim to influence children’s beliefs appears to have been a key driver in public investment. Nevertheless, the roles governments played differed according to the developmental status and inherent socioeconomic and political characteristics of their countries. These features of the human capital transition highlight the importance of understanding governments’ incentives and roles in transitions

    Genomic subtypes of breast cancer identified by array comparative genomic hybridization display distinct molecular and clinical characteristics

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    Abstract Introduction Breast cancer is a profoundly heterogeneous disease with respect to biologic and clinical behavior. Gene-expression profiling has been used to dissect this complexity and to stratify tumors into intrinsic gene-expression subtypes, associated with distinct biology, patient outcome, and genomic alterations. Additionally, breast tumors occurring in individuals with germline BRCA1 or BRCA2 mutations typically fall into distinct subtypes. Methods We applied global DNA copy number and gene-expression profiling in 359 breast tumors. All tumors were classified according to intrinsic gene-expression subtypes and included cases from genetically predisposed women. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to identify significant DNA copy-number aberrations and genomic subgroups of breast cancer. Results We identified 31 genomic regions that were highly amplified in > 1% of the 359 breast tumors. Several amplicons were found to co-occur, the 8p12 and 11q13.3 regions being the most frequent combination besides amplicons on the same chromosomal arm. Unsupervised hierarchical clustering with 133 significant GISTIC regions revealed six genomic subtypes, termed 17q12, basal-complex, luminal-simple, luminal-complex, amplifier, and mixed subtypes. Four of them had striking similarity to intrinsic gene-expression subtypes and showed associations to conventional tumor biomarkers and clinical outcome. However, luminal A-classified tumors were distributed in two main genomic subtypes, luminal-simple and luminal-complex, the former group having a better prognosis, whereas the latter group included also luminal B and the majority of BRCA2-mutated tumors. The basal-complex subtype displayed extensive genomic homogeneity and harbored the majority of BRCA1-mutated tumors. The 17q12 subtype comprised mostly HER2-amplified and HER2-enriched subtype tumors and had the worst prognosis. The amplifier and mixed subtypes contained tumors from all gene-expression subtypes, the former being enriched for 8p12-amplified cases, whereas the mixed subtype included many tumors with predominantly DNA copy-number losses and poor prognosis. Conclusions Global DNA copy-number analysis integrated with gene-expression data can be used to dissect the complexity of breast cancer. This revealed six genomic subtypes with different clinical behavior and a striking concordance to the intrinsic subtypes. These genomic subtypes may prove useful for understanding the mechanisms of tumor development and for prognostic and treatment prediction purposes
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