Dataset Information

Inflammatory-Related Genetic Variants in Non-Muscle-Invasive Bladder Cancer Prognosis: A Multimarker Bayesian Assessment.

ABSTRACT: BACKGROUND:Increasing evidence points to the role of tumor immunologic environment on urothelial bladder cancer prognosis. This effect might be partly dependent on the host genetic context. We evaluated the association of SNPs in inflammation-related genes with non-muscle-invasive bladder cancer (NMIBC) risk-of-recurrence and risk-of-progression. METHODS:We considered 822 NMIBC included in the SBC/EPICURO Study followed-up >10 years. We selected 1,679 SNPs belonging to 251 inflammatory genes. The association of SNPs with risk-of-recurrence and risk-of-progression was assessed using Cox regression single-marker (SMM) and multimarker methods (MMM) Bayes A and Bayesian LASSO. Discriminative abilities of the models were calculated using the c index and validated with bootstrap cross-validation procedures. RESULTS:While no SNP was found to be associated with risk-of-recurrence using SMM, three SNPs in TNIP1, CD5, and JAK3 showed very strong association with posterior probabilities >90% using MMM. Regarding risk-of-progression, one SNP in CD3G was significantly associated using SMM (HR, 2.69; P = 1.55 × 10(-5)) and two SNPs in MASP1 and AIRE, showed a posterior probability ?80% with MMM. Validated discriminative abilities of the models without and with the SNPs were 58.4% versus 60.5% and 72.1% versus 72.8% for risk-of-recurrence and risk-of-progression, respectively. CONCLUSIONS:Using innovative analytic approaches, we demonstrated that SNPs in inflammatory-related genes were associated with NMIBC prognosis and that they improve the discriminative ability of prognostic clinical models for NMIBC. IMPACT:This study provides proof of concept for the joint effect of genetic variants in improving the discriminative ability of clinical prognostic models. The approach may be extended to other diseases. Cancer Epidemiol Biomarkers Prev; 25(7); 1144-50. ©2016 AACR.

SUBMITTER: Masson-Lecomte A

PROVIDER: S-EPMC6984594 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Inflammatory-Related Genetic Variants in Non-Muscle-Invasive Bladder Cancer Prognosis: A Multimarker Bayesian Assessment.

Masson-Lecomte Alexandra A López de Maturana Evangelina E Goddard Michael E ME Picornell Antoni A Rava Marta M González-Neira Anna A Márquez Mirari M Carrato Alfredo A Tardon Adonina A Lloreta Josep J Garcia-Closas Montserrat M Silverman Debra D Rothman Nathaniel N Kogevinas Manolis M Allory Yves Y Chanock Stephen J SJ Real Francisco X FX Malats Núria N

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20160506 7

<h4>Background</h4>Increasing evidence points to the role of tumor immunologic environment on urothelial bladder cancer prognosis. This effect might be partly dependent on the host genetic context. We evaluated the association of SNPs in inflammation-related genes with non-muscle-invasive bladder cancer (NMIBC) risk-of-recurrence and risk-of-progression.<h4>Methods</h4>We considered 822 NMIBC included in the SBC/EPICURO Study followed-up >10 years. We selected 1,679 SNPs belonging to 251 inflamm ...[more]

PMID: 27197286

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Project description:BACKGROUND:The expression alterations of B4GALT1 have been noted in some types of cancer and they are related to cancer cell proliferation, invasiveness, metastasis, and drug resistance. We aimed to establish the expression of B4GALT1 in bladder cancer and its connection to patient outcomes, as well as forecasting the advantages of adjuvant chemotherapy (ACT) in patients with muscle-invasive bladder cancer (MIBC). METHODS:There were 142 and 112 MIBC patients who were consecutively recruited and treated via radical cystectomy from 2008 to 2012 in Shanghai Zhongshan Hospital and Fudan University Shanghai Cancer Center (FUSCC), respectively. Tissue microarrays (TMAs) were constructed in triplicate from specimens that had been fixed in formalin and embedded in paraffin samples. Immunohistochemistry was conducted to evaluate B4GALT1 expression in tumor cores, the connection between B4GALT1 expression and patients' clinical characteristics, and clinical results. RESULTS:B4GALT1 expression was not connected to clinical prognosis markers, but it was linked to overall survival (OS) (P?=?0.013 and P?=?0.010, respectively) in the two groups. Moreover, the high levels of B4GALT1 expression were independent indicators of poor OS (P?=?0.026 and P?=?0.046, respectively). Inclusion of B4GALT1 in the prognostic model revealed a greater predictive accuracy than the primary models. In addition, no differences were observed between B4GALT1 expression (low vs. high) and CD8+ T cell infiltration density (number/cm2) within tumor cores, but there was a positive Pearson correlation between B4GALT1 expression and expression of inhibitory receptor ligands, such as PD-L1 and CTLA4. Most significantly, the advantage of ACT noted in pT3/4 or N+ bladder cancer patients with low B4GALT1 expression was greater than in patients with a high B4GALT1 expression. CONCLUSIONS:Our evaluation indicated that B4GALT1 may be a possible prognosticator of MIBC, and it may be a predictive marker for the choice of ACT in pT3/4 or N+ patients.

Project description:BackgroundRecently, immunotherapies have been approved for advanced muscle invasive bladder cancer (MIBC) treatment, but only a small fraction of MIBC patients could achieve a durable drug response. Our study is aimed at identifying tumor microenvironment (TME) subtypes that have different immunotherapy response rates.MethodsThe mRNA expression profiles of MIBC samples from seven discovery datasets (GSE13507, GSE31684, GSE32548, GSE32894, GSE48075, GSE48276, and GSE69795) were analyzed to identify TME subtypes. The identified TME subtypes were then validated by an independent dataset (TCGA-MIBC). The subtype-related biomarkers were discovered using computational analyses and then utilized to establish a random forest predictive model. The associations of TME subtypes with immunotherapy therapeutic responses were investigated in a group of patients who had been treated with immunotherapy. A prognostic index model was constructed using the subtype-related biomarkers. Two nomograms were built by the subtype-related biomarkers or the clinical parameters.ResultsTwo TME subtypes, including ECM-enriched class (EC) and immune-enriched class (IC), were found. EC was associated with greater extracellular matrix (ECM) pathways, and IC was correlated with immune pathways, respectively. Overall survival was significantly greater for tumors classified as IC, whereas the EC subtype had a worse prognosis. A total of nine genes (AKAP12, APOL3, CXCL13, CXCL9, GBP4, LRIG1, PEG3, PODN, and PTPRD) were selected by computational analyses to construct the random forest model. The area under the curve (AUC) values for this model were 0.827 and 0.767 in the testing and external validation datasets, respectively. Therapeutic response rates were greater in IC patients than in EC patients (28 percent vs. 18 percent). Patients with a high prognostic index had a poorer prognosis than those with a low prognostic index. The nomogram constructed from nine genes and stage achieved a C-index of 0.71.ConclusionThe present investigation defined two distinct TME subtypes and developed models to assess immunotherapeutic treatment outcomes.

Project description:Improved understanding of the molecular mechanisms and immunoregulation of muscle-invasive bladder cancer (MIBC) is essential to predict prognosis and develop new targets for therapies. In this study, we used the cancer genome atlas (TCGA) MIBC and GSE13507 datasets to explore the differential co-expression genes in MIBC comparing with adjacent non-carcinoma tissues. We firstly screened 106 signature genes by Weighted Gene Co-expression Network Analysis (WGCNA) and further identified 15 prognosis-related genes of MIBC using the univariate Cox progression analysis. Then we systematically analyzed the genetic alteration, molecular mechanism, and clinical relevance of these 15 genes. We found a different expression alteration of 15 genes in MIBC comparing with adjacent non-carcinoma tissues and normal tissues. Meanwhile, the biological functions and molecular mechanisms of them were also discrepant. Among these, we observed the ANLN was highly correlated with multiple cancer pathways, molecular function, and cell components, revealing ANLN may play a pivotal role in MIBC development. Next, we performed a consensus clustering of 15 prognosis-related genes; the results showed that the prognosis, immune infiltration status, stage, and grade of MIBC patients were significantly different in cluster1/2. We further identified eight-genes risk signatures using the least absolute shrinkage and selection operator (LASSO) regression analysis based on the expression values of 15 prognosis-related genes, and also found a significant difference in the prognosis, immune infiltration status, stage, grade, and age in high/low-risk cohort. Moreover, the expression of PD-1, PD-L1, and CTLA4 was significantly up-regulated in cluster1/high-risk-cohort than that in cluster2/low-risk-cohort. High normalized enrichment score of the Mitotic spindle, mTORC1, Complement, and Apical junction pathway suggested that they might be involved in the distinct tumor immune microenvironment (TIME) of cluster1/2 and high-/low-risk-cohort. Our study identified 15 prognosis-related genes of MIBC, provided a feasible stratification method to help for the future immunotherapy strategies of MIBC patients.

Project description:BackgroundMolecular subtyping of bladder cancer has revealed luminal tumors generally have a more favourable prognosis. However, some aggressive forms of variant histology, including micropapillary, are often classified luminal. In previous work, we found long non-coding RNA (lncRNA) expression profiles could identify a subgroup of luminal bladder tumors with less aggressive biology and better outcomes.ObjectiveIn the present study, we aimed to investigate whether lncRNA expression profiles could identify high-grade T1 micropapillary bladder cancer with differential outcome.Design, setting, and participantsLncRNAs were quantified from RNA-seq data from a HGT1 bladder cancer cohort that was enriched for primary micropapillary cases (15/84). Unsupervised consensus clustering of variant lncRNAs identified a three-cluster solution, which was further characterised using a panel of micropapillary-associated biomarkers, molecular subtypes, gene signatures, and survival analysis. A single-sample genomic signature was trained using lasso-penalized logistic regression to classify micropapillary-like gene-expression, as characterised by lncRNA clustering. The genomic classifier (GC) was tested on luminal tumors derived from the TCGA cohort (N = 202).Outcome measurements and statistical analysisPatient and tumor characteristics were compared between subgroups by using X2 tests and two-sided Wilcoxon rank-sum tests. Primary endpoints were overall, progression-free and high-grade recurrence-free survival, calculated as the date of high-grade T1 disease at TURBT till date of death from any cause, progression, or recurrence, respectively. Survival rates were estimated using weighted Kaplan-Meier (KM) curves.Results and limitationsPrimary micropapillary HGT1 showed decreased FGFR3, SHH, and p53 pathway activity relative to tumors with conventional urothelial carcinoma. Many bladder cancer-associated lncRNAs were downregulated in micropapillary tumors, including UCA1, LINC00152, and MALAT1. Unsupervised consensus clustering resulted in a lncRNA cluster 1 (LC1) with worse prognosis that was enriched for primary micropapillary histology and the Luminal Unstable (LumU) molecular subtype. Interestingly, LC1 appeared to better identify aggressive HGT1 disease, compared to stratifying outcomes using primary histologic characteristics. A signature trained to identify LC1 cases showed good performance in the testing cohort, identifying seven cases with significantly worse survival (p < 0.001). Limitations include the retrospective nature of the study and the lack of a validation cohort.ConclusionsUsing the lncRNA transcriptome we identified a subgroup of aggressive HGT1 bladder cancer that was enriched with micropapillary histology. These data suggest that lncRNAs can facilitate the identification of aggressive micropapillary-like tumors, potentially improving patient management.

Dataset Information

Inflammatory-Related Genetic Variants in Non-Muscle-Invasive Bladder Cancer Prognosis: A Multimarker Bayesian Assessment.

Publications

Inflammatory-Related Genetic Variants in Non-Muscle-Invasive Bladder Cancer Prognosis: A Multimarker Bayesian Assessment.

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