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- Dyrskjøt, Lars, et al.
(författare)
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Gene expression signatures predict outcome in non-muscle-invasive bladder carcinoma : a multicenter validation study
- 2007
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Ingår i: Clinical Cancer Research. - 1078-0432 .- 1557-3265. ; 13:12, s. 3545-3551
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Tidskriftsartikel (refereegranskat)abstract
- 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 Ta or T1 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.
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| 2. |
- Kamoun, Aurélie, et al.
(författare)
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A Consensus Molecular Classification of Muscle-invasive Bladder Cancer
- 2020
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Ingår i: European Urology. - : Elsevier BV. - 0302-2838. ; 77:4, s. 420-433
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Tidskriftsartikel (refereegranskat)abstract
- Background: Muscle-invasive bladder cancer (MIBC) is a molecularly diverse disease with heterogeneous clinical outcomes. Several molecular classifications have been proposed, but the diversity of their subtype sets impedes their clinical application. Objective: To achieve an international consensus on MIBC molecular subtypes that reconciles the published classification schemes. Design, setting, and participants: We used 1750 MIBC transcriptomic profiles from 16 published datasets and two additional cohorts. Outcome measurements and statistical analysis: We performed a network-based analysis of six independent MIBC classification systems to identify a consensus set of molecular classes. Association with survival was assessed using multivariable Cox models. Results and limitations: We report the results of an international effort to reach a consensus on MIBC molecular subtypes. We identified a consensus set of six molecular classes: luminal papillary (24%), luminal nonspecified (8%), luminal unstable (15%), stroma-rich (15%), basal/squamous (35%), and neuroendocrine-like (3%). These consensus classes differ regarding underlying oncogenic mechanisms, infiltration by immune and stromal cells, and histological and clinical characteristics, including outcomes. We provide a single-sample classifier that assigns a consensus class label to a tumor sample's transcriptome. Limitations of the work are retrospective clinical data collection and a lack of complete information regarding patient treatment. Conclusions: This consensus system offers a robust framework that will enable testing and validation of predictive biomarkers in future prospective clinical trials. Patient summary: Bladder cancers are heterogeneous at the molecular level, and scientists have proposed several classifications into sets of molecular classes. While these classifications may be useful to stratify patients for prognosis or response to treatment, a consensus classification would facilitate the clinical use of molecular classes. Conducted by multidisciplinary expert teams in the field, this study proposes such a consensus and provides a tool for applying the consensus classification in the clinical setting.
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