During the evolution of cancer, the incipient tumour experiences 'oncogenic stress', which evokes a counter-response to eliminate such hazardous cells. However, the nature of this stress remains elusive, as does the inducible anti-cancer barrier that elicits growth arrest or cell death. Here we show that in clinical specimens from different stages of human tumours of the urinary bladder, breast, lung and colon, the early precursor lesions (but not normal tissues) commonly express markers of an activated DNA damage response. These include phosphorylated kinases ATM and Chk2, and phosphorylated histone H2AX and p53. Similar checkpoint responses were induced in cultured cells upon expression of different oncogenes that deregulate DNA replication. Together with genetic analyses, including a genome-wide assessment of allelic imbalances, our data indicate that early in tumorigenesis (before genomic instability and malignant conversion), human cells activate an ATR/ATM-regulated DNA damage response network that delays or prevents cancer. Mutations compromising this checkpoint, including defects in the ATM-Chk2-p53 pathway, might allow cell proliferation, survival, increased genomic instability and tumour progression.
microRNAs (miRNA) are involved in cancer development and progression, acting as tumor suppressors or oncogenes. Here, we profiled the expression of 290 unique human miRNAs in 11 normal and 106 bladder tumor samples using spotted locked nucleic acid-based oligonucleotide microarrays. We identified several differentially expressed miRNAs between normal urothelium and cancer and between the different disease stages. miR-145 was found to be the most down-regulated in cancer compared with normal, and miR-21 was the most upregulated in cancer. Furthermore, we identified miRNAs that significantly correlated to the presence of concomitant carcinoma in situ. We identified several miRNAs with prognostic potential for predicting disease progression (e.g., miR-129, miR-133b, and miR-518c*). We localized the expression of miR-145, miR-21, and miR-129 to urothelium by in situ hybridization. We then focused on miR-129 that exerted significant growth inhibition and induced cell death upon transfection with a miR-129 precursor in bladder carcinoma cell lines T24 and SW780 cells. Microarray analysis of T24 cells after transfection showed significant miR-129 target downregulation (P = 0.0002) and pathway analysis indicated that targets were involved in cell death processes. By analyzing gene expression data from clinical tumor samples, we identified significant expression changes of target mRNA molecules related to the miRNA expression. Using luciferase assays, we documented a direct link between miR-129 and the two putative targets GALNT1 and SOX4. The findings reported here indicate that several miRNAs are differentially regulated in bladder cancer and may form a basis for clinical development of new biomarkers for bladder cancer. [Cancer Res 2009;69(11):4851-60]
Purpose: Clinically useful molecular markers predicting the clinical course of patients diagnosed with non^muscle-invasive bladder cancer are needed to improve treatment outcome. Here, we validated four previously reported gene expression signatures for molecular diagnosis of disease stage and carcinoma in situ (CIS) and for predicting disease recurrence and progression. Experimental Design:We analyzed tumors from 404 patients diagnosed with bladder cancer in hospitals in Denmark, Sweden, England, Spain, and France using custom microarrays. Molecular classifications were compared with pathologic diagnosis and clinical outcome. Results: Classification of disease stage using a 52-gene classifier was found to be highly significantly correlated with pathologic stage (P < 0.001). Furthermore, the classifier added information regarding disease progression of T a or T 1 tumors (P < 0.001). The molecular 88-gene progression classifier was highly significantly correlated with progression-free survival (P < 0.001) and cancer-specific survival (P = 0.001). Multivariate Cox regression analysis showed the progression classifier to be an independently significant variable associated with disease progression after adjustment for age, sex, stage, grade, and treatment (hazard ratio, 2.3; P = 0.007). The diagnosis of CIS using a 68-gene classifier showed a highly significant correlation with histopathologic CIS diagnosis (odds ratio, 5.8; P < 0.001) in multivariate logistic regression analysis. Conclusion:This multicenter validation study confirms in an independent series the clinical utility of molecular classifiers to predict the outcome of patients initially diagnosed with non^muscle-invasive bladder cancer. This information may be useful to better guide patient treatment.Bladder cancer is a common malignant disease with 357,000 new cases and 145,000 deaths worldwide annually (1). Its prevalence is 3-to 8-fold higher than its incidence, making bladder cancer one of the most prevalent neoplasms, and hence a major burden for health care systems. The overall causespecific 5-year survival rate is about 65%. The disease presents in two different forms: non -muscle-invasive tumors (stages T a and T 1 ), usually treated with a local, organ-sparing approach, and muscle-invasive cancers (stages T 2 -T 4 ), usually requiring cystectomy if cure is intended.The non -muscle-invasive tumors account for f75% of newly diagnosed cases. A low proportion of patients are cured after tumor resection, but the tumors of more than 60% of these patients recur, and the frequency of recurrences has a significant effect on the patients' quality of life. Some of these patients also develop muscle-invasive tumors over time, the proportion ranging from very low for noninvasive papillary low-grade tumors to up to 60% progression for high-grade submucosa-invasive tumors (2, 3). Clinical risk factors for progression include invasion of the lamina propria, high grade, tumor size, occurrence of carcinoma in situ (CIS), and multiplicity or recurrence of ...
Purpose: Bladder tumors develop through different molecular pathways. Recent reports suggest activating mutations of the fibroblast growth factor receptor 3 (FGFR3) gene as marker for the ''papillary'' pathway with good prognosis, in contrast to the more malignant ''carcinoma in situ'' (CIS) pathway. The aim of this clinical follow-up study was to investigate the role of FGFR3 mutations in bladder cancer development in a longitudinal study. Experimental Design: We selected 85 patients with superficial bladder tumors, stratified into early (stage T a /grade 1-2, n = 35) and more advanced (either stage T 1 or grade 3, n = 50) developmental stages.The patients were followed prospectively, and metachronous tumors were included.We did screening for FGFR3 and TP53 mutations by direct bidirectional sequencing and for genome-wide molecular changes with microarray technology. Results: A total of 43 of 85 cases (51%) showed activating mutations of FGFR3. The mutations were associated with papillary tumors of early developmental stage. However, after stratifying for developmental stage, FGFR3-mutated tumors showed the same malignant potential as wild-type tumors. Tumors with concomitant CIS were generally FGFR3 wild type. They were characterized by different patterns of chromosomal changes and gene expression signatures compared with FGFR3-mutated tumors, indicating different molecular pathways. Conclusions: FGFR3 mutations seem to have a central role in the early development of papillary bladder tumors.These tumors follow a common molecular pathway, which is different from tumors with concomitant CIS. FGFR3 mutations do not seem to play a role in bladder cancer progression.
Purpose: Cancer of the urinary bladder is a common malignant disease in the western countries. The majority of patients presents with superficial tumors with a high recurrence frequency, a minor fraction of these patients experience disease progression to a muscle invasive stage. No clinical useful molecular markers exist to identify patients showing later disease progression. The purpose of this study was to identify markers of disease progression using fullgenome expression analysis. Experimental Design: We did a full-genome expression analysis (59,619 genes and expressed sequence tags) of superficial bladder tumors from 29 bladder cancer patients (13 without later disease progression and 16 with later disease progression) using high-density oligonucleotide microarrays.We used supervised learning for identification of the optimal genes for predicting disease progression. The identified genes were validated on an independent test set (74 superficial tumor samples) using in house-fabricated 60-mer oligonucleotide microarrays. Results: We identified a 45-gene signature of disease progression. By monitoring this progression signature in an independent test set, we found a significant correlation between our classifications and the clinical outcome (P < 0.03). The genes identified as differentially expressed were involved in regulating apoptosis, cell differentiation, and cell cycle and hence may represent potential therapeutic targets. Conclusions: Our results indicate that it may be possible to identify patients with a high risk of disease progression at an early stage using a molecular signature present already in the superficial tumors. In this way, better treatment and follow-up regimens could be assigned to patients suffering from superficial bladder cancer.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.