Showing papers by "Hugo M. Horlings published in 2011"
TL;DR: In this article, an ultra-high-density array that tiles the promoters of 56 cell-cycle genes was used to interrogate 108 samples representing diverse perturbations, identifying 216 transcribed regions that encode putative lncRNAs, many with RT-PCR-validated periodic expression during the cell cycle.
Abstract: Transcription of long noncoding RNAs (lncRNAs) within gene regulatory elements can modulate gene activity in response to external stimuli, but the scope and functions of such activity are not known. Here we use an ultrahigh-density array that tiles the promoters of 56 cell-cycle genes to interrogate 108 samples representing diverse perturbations. We identify 216 transcribed regions that encode putative lncRNAs, many with RT-PCR-validated periodic expression during the cell cycle, show altered expression in human cancers and are regulated in expression by specific oncogenic stimuli, stem cell differentiation or DNA damage. DNA damage induces five lncRNAs from the CDKN1A promoter, and one such lncRNA, named PANDA, is induced in a p53-dependent manner. PANDA interacts with the transcription factor NF-YA to limit expression of pro-apoptotic genes; PANDA depletion markedly sensitized human fibroblasts to apoptosis by doxorubicin. These findings suggest potentially widespread roles for promoter lncRNAs in cell-growth control.
969 citations
01 Jun 2011
TL;DR: This work uses an ultrahigh-density array that tiles the promoters of 56 cell-cycle genes to interrogate 108 samples representing diverse perturbations and identifies 216 transcribed regions that encode putative lncRNAs, many with RT-PCR–validated periodic expression during the cell cycle.
Abstract: Transcription of long noncoding RNAs (lncRNAs) within gene regulatory elements can modulate gene activity in response to external stimuli, but the scope and functions of such activity are not known. Here we use an ultrahigh-density array that tiles the promoters of 56 cell-cycle genes to interrogate 108 samples representing diverse perturbations. We identify 216 transcribed regions that encode putative lncRNAs, many with RT-PCR-validated periodic expression during the cell cycle, show altered expression in human cancers and are regulated in expression by specific oncogenic stimuli, stem cell differentiation or DNA damage. DNA damage induces five lncRNAs from the CDKN1A promoter, and one such lncRNA, named PANDA, is induced in a p53-dependent manner. PANDA interacts with the transcription factor NF-YA to limit expression of pro-apoptotic genes; PANDA depletion markedly sensitized human fibroblasts to apoptosis by doxorubicin. These findings suggest potentially widespread roles for promoter lncRNAs in cell-growth control.
933 citations
TL;DR: In this paper, miRNAs were organized in genomic clusters representing promoter-controlled miRNA expression and sequence families representing seed-sequence-dependent miRNA-target regulation, showing that normal breast samples were separated from most non-invasive ductal carcinoma in situ and invasive carcinomas by increased miR-21 (the most abundant miRNA in carcinomas) and multiple decreased miRNA families, with most miRNA changes apparent already in the noninvasive carcinomas.
Abstract: MicroRNAs (miRNAs) regulate many genes critical for tumorigenesis. We profiled miRNAs from 11 normal breast tissues, 17 non-invasive, 151 invasive breast carcinomas, and 6 cell lines by in-house-developed barcoded Solexa-sequencing. miRNAs were organized in genomic clusters representing promoter-controlled miRNA expression and sequence families representing seed-sequence-dependent miRNA-target regulation. Unsupervised clustering of samples by miRNA sequence families best reflected the clustering based on mRNA expression available for this sample set. Clustering and comparative analysis of miRNA read frequencies showed that normal breast samples were separated from most non-invasive ductal carcinoma in situ and invasive carcinomas by increased miR-21 (the most abundant miRNA in carcinomas) and multiple decreased miRNA families (including miR-98/let-7), with most miRNA changes apparent already in the non-invasive carcinomas. In addition, patients that went on to develop metastasis demonstrated increased expression of mir-423, and triple negative breast carcinomas were most distinct from other tumor subtypes due to up-regulation of the mir-17~92 cluster. However, absolute miRNA levels between normal breast and carcinomas did not reveal any significant differences. We also discovered two polymorphic nucleotide variations among the more abundant miRNAs miR-181a (T19G) and miR-185 (T16G), but we did not identify nucleotide variations expected for classical tumor suppressor function associated with miRNAs. The differentiation of tumor subtypes and prediction of metastasis based on miRNA levels is statistically possible, but is not driven by deregulation of abundant miRNAs, implicating far fewer miRNAs in tumorigenic processes than previously suggested.
315 citations
TL;DR: The identification of RBM38 in a genetic screen for RBPs whose expression controls miRNA access to target mRNAs indicates a novel layer of p53 gene regulation, which is required for its tumour suppressive function.
Abstract: MicroRNAs (miRNAs) interact with 3'-untranslated regions of messenger RNAs to restrict expression of most protein-coding genes during normal development and cancer. RNA-binding proteins (RBPs) can control the biogenesis, stability and activity of miRNAs. Here we identify RBM38 in a genetic screen for RBPs whose expression controls miRNA access to target mRNAs. RBM38 is induced by p53 and its ability to modulate miRNA-mediated repression is required for proper p53 function. In contrast, RBM38 shows lower propensity to block the action of the p53-controlled miR-34a on SIRT1. Target selectivity is determined by the interaction of RBM38 with uridine-rich regions near miRNA target sequences. Furthermore, in large cohorts of human breast cancer, reduced RBM38 expression by promoter hypermethylation correlates with wild-type p53 status. Thus, our results indicate a novel layer of p53 gene regulation, which is required for its tumour suppressive function.
94 citations
TL;DR: IGF1R expression in ER-positive IDC is strongly related to a favorable DFS and BCSS, but to a shorter DFS in TN-IDC tumors, which may affect selection of patients for IGF1R targeted therapy.
Abstract: The insulin-like growth factor type 1 receptor (IGF1R) is involved in progression of breast cancer and resistance to systemic treatment. Targeting IGF1R signaling may, therefore, be beneficial in systemic treatment. We report the effect of IGF1R expression on prognosis in invasive ductal breast carcinoma (IDC), the most common type of breast cancer. Immunohistochemistry was performed on tumor tissue of a consecutive cohort of 429 female patients treated for operable primary IDC. Associations between IGF1R expression with clinicopathological parameters, disease free survival (DFS) and breast cancer specific survival (BCSS) were evaluated by multivariate analyses focusing on ER-positive and triple negative IDC (TN-IDC). To enlarge the TN-IDCs cohort, we analyzed a combined dataset of 51 TN-IDC tumors from our series with 64 TN-IDCs with similar clinicopathological parameters. Patients with tumors expressing cytoplasmic IGF1R have a longer DFS and BCSS (DFS: HR 0.46, 95% CI 0.27-0.49, P = 0.005, BCSS: HR 0.38, 95% CI 0.19-0.74, P = 0.005). This effect was most prominent in ER-positive tumors. However, in a combined series of 105 TN-IDCs cytoplasmic IGF1R expression was associated with a shorter DFS (HR = 2.29, 95% CI 1.08-4.84, P = 0.03), also when combined in a multivariate model, including well-known prognostic factors (HR 2.06; 95% CI 0.95-4.47; P = 0.07). IGF1R expression in ER-positive IDC is strongly related to a favorable DFS and BCSS, but to a shorter DFS in TN-IDC tumors. This divergent effect of IGF1R expression in subgroups of IDC may affect selection of patients for IGF1R targeted therapy.
53 citations
TL;DR: Adjuvant!
Abstract: Background
Adjuvant! Online is a web-based application designed to provide 10 years survival probability of patients with breast cancer. Several predictors have not been assessed in the original Adjuvant! Online study. We provide the validation of Adjuvant! Online algorithm on two breast cancer datasets, and we determined whether the accuracy of Adjuvant! Online is improved with other well-known prognostic factors.
Patients and Methods
The French data set is composed of 456 women with early breast cancer. The Dutch data set is composed of 295 women less than 52 years of age. Agreement between observation and Adjuvant! Online prediction was checked, and logistic models were performed to estimate the prognostic information added by risk factors to Adjuvant! Online prediction.
Results
Adjuvant! Online prediction was overall well-calibrated in the French data set but failed in some subgroups of such high grade and HER2 positive patients. HER2 status, Mitotic Index and Ki67 added significant information to Adjuvant! Online prediction. In the Dutch data set, the overall 10-year survival was overestimated by Adjuvant! Online, particularly in patients less than 40 years old.
Conclusion
Adjuvant! Online needs to be updated to adjust overoptimistic results in young and high grade patients, and should consider new predictors such as Ki67, HER2 and Mitotic Index.
43 citations
TL;DR: The results indicate that common polymorphisms in specific pathways may add to the worse prognosis of patients with tumors in which these pathways are affected by somatic alterations.
Abstract: The tumor suppressor gene TP53 and its regulator MDM2 are both important players in the DNA-damage repair "TP53 response pathway". Common germline polymorphisms in these genes may affect outcome in patients with tumors characterized by additional somatic changes in the same or a related pathway. To evaluate this hypothesis, we determined the effect of the common germline TP53 R72P and MDM2 SNP309 polymorphisms on breast cancer survival in a consecutive cohort of breast cancer patients (age at diagnosis <53 years, n = 295) with gene expression data available. Patients were classified in subgroups according to their tumor TP53 mutation status and three gene expression profiles; a TP53 mutation status expression signature, a PTEN/PI3K pathway signature and the 70-gene prognosis profile. Survival analyses were performed using Cox regression models adjusting for clinico-pathological characteristics and treatment. An increase in breast cancer-specific mortality was observed for carriers of the germline MDM2 SNP309 rare GG-genotype (range hazard ratios: 2-3) or TP53 R72P heterozygous GC-genotype (range hazard ratios: 1-2) compared to those having the common genotypes within subgroups of tumors displaying a "more aggressive phenotype" gene expression profile. There was no evidence of such an effect on survival within the TP53-mutated tumor group for TP53 R72P carriers but a suggestion of an effect for MDM2 SNP309 carriers (GG vs. TT-genotype HR 2.99, P = 0.06). These results indicate that common polymorphisms in specific pathways may add to the worse prognosis of patients with tumors in which these pathways are affected by somatic alterations.
11 citations