Classifying bladder cancer subtypes

Mapping Intimacies ◽

10.1101/250258 ◽

2018 ◽

Author(s):

Cihan Kaya ◽

Nicolas Arcenio Pabon

Keyword(s):

Bladder Cancer ◽

Mrna Expression ◽

Tumor Cells ◽

Bladder Tumor ◽

Expression Profiles ◽

The United States ◽

Micro Rna ◽

The Cancer Genome Atlas ◽

Test Accuracy ◽

Genetic Features

AbstractUrothelial carcinoma of the bladder is is estimated to have killed over 16,000 people in the United States in 2016. Like breast cancer, bladder cancer is a heterogeneous disease, and characterization of it’s various subtypes can be useful for forecasting prognosis and treatment efficacy. According to The Cancer Genome Atlas (TCGA) project, the mRNA expression profiles of bladder tumours can be used to cluster the tumors into four different categories: I - Papillary-like, II ‐Luminal A, III - basal/squamous-like, and IV - other (similar to III). However it is not clear whether these mRNA expression based clusters correlate with other molecular and genetic features of the tumor cells. In other words, do differences in mRNA expression profile contain the same information as differences in protein expression, micro RNA (miRNA) expression, copy number variation and somatic mutation data. We tried to recreate mRNA based bladder tumor clusters from other multi-omic data for 328 bladder cancer tumor samples using a special deep and wide belief network composed of restricted Boltzmann machines and a multilayer perceptron. For 10-fold cross validation, we got 79% average test accuracy which implies that that differences in mRNA expression between bladder tumor cells can be reliably, though not perfectly, inferred from different molecular and genetic features of the tumors.

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Iron-Bound Lipocalin-2 from Tumor-Associated Macrophages Drives Breast Cancer Progression Independent of Ferroportin

Metabolites ◽

10.3390/metabo11030180 ◽

2021 ◽

Vol 11 (3) ◽

pp. 180

Author(s):

Christina Mertens ◽

Matthias Schnetz ◽

Claudia Rehwald ◽

Stephan Grein ◽

Eiman Elwakeel ◽

...

Keyword(s):

Breast Cancer ◽

Tumor Progression ◽

Tumor Cells ◽

Cancer Progression ◽

Lung Metastases ◽

Expression Profiles ◽

The Cancer Genome Atlas ◽

Lipocalin 2 ◽

Tumor Associated Macrophages

Macrophages supply iron to the breast tumor microenvironment by enforced secretion of lipocalin-2 (Lcn-2)-bound iron as well as the increased expression of the iron exporter ferroportin (FPN). We aimed at identifying the contribution of each pathway in supplying iron for the growing tumor, thereby fostering tumor progression. Analyzing the expression profiles of Lcn-2 and FPN using the spontaneous polyoma-middle-T oncogene (PyMT) breast cancer model as well as mining publicly available TCGA (The Cancer Genome Atlas) and GEO Series(GSE) datasets from the Gene Expression Omnibus database (GEO), we found no association between tumor parameters and Lcn-2 or FPN. However, stromal/macrophage-expression of Lcn-2 correlated with tumor onset, lung metastases, and recurrence, whereas FPN did not. While the total iron amount in wildtype and Lcn-2−/− PyMT tumors showed no difference, we observed that tumor-associated macrophages from Lcn-2−/− compared to wildtype tumors stored more iron. In contrast, Lcn-2−/− tumor cells accumulated less iron than their wildtype counterparts, translating into a low migratory and proliferative capacity of Lcn-2−/− tumor cells in a 3D tumor spheroid model in vitro. Our data suggest a pivotal role of Lcn-2 in tumor iron-management, affecting tumor growth. This study underscores the role of iron for tumor progression and the need for a better understanding of iron-targeted therapy approaches.

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Development and Validation of a Prognostic Nomogram Based on DNA Methylation-Driven Genes for Patients With Ovarian Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.675197 ◽

2021 ◽

Vol 12 ◽

Author(s):

Min Zhou ◽

Shasha Hong ◽

Bingshu Li ◽

Cheng Liu ◽

Ming Hu ◽

...

Keyword(s):

Ovarian Cancer ◽

Dna Methylation ◽

Mrna Expression ◽

Risk Score ◽

Cox Regression ◽

Expression Profiles ◽

Figo Stage ◽

Prognostic Indicator ◽

Tissue Expression ◽

The Cancer Genome Atlas

Background: DNA methylation affects the development, progression, and prognosis of various cancers. This study aimed to identify DNA methylated-differentially expressed genes (DEGs) and develop a methylation-driven gene model to evaluate the prognosis of ovarian cancer (OC).Methods: DNA methylation and mRNA expression profiles of OC patients were downloaded from The Cancer Genome Atlas, Genotype-Tissue Expression, and Gene Expression Omnibus databases. We used the R package MethylMix to identify DNA methylation-regulated DEGs and built a prognostic signature using LASSO Cox regression. A quantitative nomogram was then drawn based on the risk score and clinicopathological features.Results: We identified 56 methylation-related DEGs and constructed a prognostic risk signature with four genes according to the LASSO Cox regression algorithm. A higher risk score not only predicted poor prognosis, but also was an independent poor prognostic indicator, which was validated by receiver operating characteristic (ROC) curves and the validation cohort. A nomogram consisting of the risk score, age, FIGO stage, and tumor status was generated to predict 3- and 5-year overall survival (OS) in the training cohort. The joint survival analysis of DNA methylation and mRNA expression demonstrated that the two genes may serve as independent prognostic biomarkers for OS in OC.Conclusion: The established qualitative risk score model was found to be robust for evaluating individualized prognosis of OC and in guiding therapy.

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Prognostic value of CLIC3 mRNA overexpression in bladder cancer

PeerJ ◽

10.7717/peerj.8348 ◽

2020 ◽

Vol 8 ◽

pp. e8348

Author(s):

Mei Chen ◽

Shufang Zhang ◽

Xiaohong Wen ◽

Hui Cao ◽

Yuanhui Gao

Keyword(s):

Gene Expression ◽

Bladder Cancer ◽

Mrna Expression ◽

Prognostic Value ◽

Multivariate Analyses ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Receptor Interaction ◽

Normal Tissues

Background Human intracellular chloride channel 3 (CLIC3) is involved in the development of various cancers, but the expression and prognostic value of CLIC3 mRNA in bladder cancer (BC) remain unclear. Methods The gene expression data and clinical information of CLIC3 were obtained from the Gene Expression Omnibus (GEO) database and verified in the Oncomine and The Cancer Genome Atlas (TCGA) database. The expression of CLIC3 mRNA in BC tissues and adjacent normal tissues was detected by quantitative real-time polymerase chain reaction (qRT-PCR). The Kaplan-Meier method was used to analyze the relationship between the expression of CLIC3 mRNA and the prognosis of BC. Cox univariate and multivariate analyses were performed on the overall survival and tumor-specific survival of BC patients. The genes coexpressed with CLIC3 were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). CLIC3-related signal transduction pathways in BC were explored with gene set enrichment analysis (GSEA). Results The expression of CLIC3 mRNA in BC tissues was higher than that in normal tissues (P < 0.01). High CLIC3 mRNA expression was associated with age (P = 0.021) and grade (P = 0.045) in BC patients. High CLIC3 mRNA expression predicted a poor prognosis in BC patients (P < 0.05). Cox univariate and multivariate analyses showed that high CLIC3 mRNA expression was associated with tumor-specific survival in BC patients (P < 0.05). Functional enrichment analyses indicated that CLIC3 may be significantly associated with the cell cycle, focal adhesion, the extracellular matrix (ECM) receptor interaction and the P53 signaling pathway. Conclusions CLIC3 mRNA is highly expressed in BC, and its high expression is related to the adverse clinicopathological factors and prognosis of BC patients. CLIC3 can be used as a biomarker for the prognosis of BC patients.

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A Prognostic Nomogram Model Based on mRNA Expression of DNA Methylation-Driven Genes for Gastric Cancer

Frontiers in Oncology ◽

10.3389/fonc.2020.584733 ◽

2020 ◽

Vol 10 ◽

Author(s):

Zuhua Chen ◽

Bo Liu ◽

Minxiao Yi ◽

Hong Qiu ◽

Xianglin Yuan

Keyword(s):

Gastric Cancer ◽

Dna Methylation ◽

Mrna Expression ◽

Risk Model ◽

Cox Regression ◽

Risk Group ◽

Expression Profiles ◽

The Cancer Genome Atlas ◽

Clinicopathological Parameters ◽

Dna Hypomethylation

PurposeThe exploration and interpretation of DNA methylation-driven genes might contribute to molecular classification, prognostic prediction and therapeutic choice. In this study, we built a prognostic risk model via integrating analysis of the transcriptome and methylation profile for patients with gastric cancer (GC).MethodsThe mRNA expression profiles, DNA methylation profiles and corresponding clinicopathological information of 415 GC patients were downloaded from The Cancer Genome Atlas (TCGA). Differential expression and correlation analysis were performed to identify DNA methylation-driven genes. The candidate genes were selected by univariate Cox regression analyses followed by the least absolute shrinkage and selection operator (LASSO) regression. A prognostic risk nomogram model was then built together with clinicopathological parameters.Results5 DNA methylation-driven genes (CXCL3, F5, GNAI1, GAMT and GHR) were identified by integrated analyses and selected to construct the prognostic risk model with clinicopathological parameters. High expression and low DNA hypermethylation of F5, GNAI1, GAMT and GHR, as well as low expression and high DNA hypomethylation of CXCL3 were significantly associated with poor prognosis rates, respectively. The high-risk group showed a significantly shorter prognosis than the low-risk group in the TCGA dataset (HR = 0.212, 95% CI = 0.139–0.322, P = 2e-15). The final nomogram model showed high predictive efficiency and consistency in the training and validation group.ConclusionWe construct and validate a prognostic nomogram model for GC based on five DNA methylation-driven genes with high performance and stability. This nomogram model might be a powerful tool for prognosis evaluation in the clinic and also provided novel insights into the epigenetics in GC.

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Bladder Tumor Heterogeneity: The Impact on Clinical Treatment

Urologia Internationalis ◽

10.1159/000370165 ◽

2015 ◽

Vol 95 (1) ◽

pp. 1-8 ◽

Cited By ~ 13

Author(s):

Chao Chen ◽

Xiang Jie Qi ◽

Yan Wei Cao ◽

Yong Hua Wang ◽

Xue Cheng Yang ◽

...

Keyword(s):

Bladder Cancer ◽

Treatment Failure ◽

Tumor Cells ◽

Cancer Progression ◽

Tumor Heterogeneity ◽

Bladder Tumor ◽

Gene Sequencing ◽

Generation Model ◽

And Control ◽

The Impact

Bladder cancer relapse and treatment failure in most patients have often been attributed to chemoresistance in tumor cells and metastasis. Emerging evidence indicates that tumor heterogeneity may play an equally important role and extends to virtually all measurable properties of cancer cells. Although the idea of tumor heterogeneity is not new, little attention has been paid to applying it to understand and control bladder cancer progression. With the development of biotechnology, such as Gene sequencing, recent advances in understanding its generation model, original basis, consequent problems, and derived therapies provide great potential for tumor heterogeneity to be considered a new insight in the treatment of bladder cancers.

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Spatial heterogeneity and organization of tumor mutation burden and immune infiltrates within tumors based on whole slide images correlated with patient survival in bladder cancer

10.1101/554527 ◽

2019 ◽

Cited By ~ 5

Author(s):

Hongming Xu ◽

Sunho Park ◽

Jean René Clemenceau ◽

Jinhwan Choi ◽

Nathan Radakovich ◽

...

Keyword(s):

Bladder Cancer ◽

Spatial Heterogeneity ◽

Tumor Cells ◽

Tumor Infiltrating Lymphocytes ◽

The Cancer Genome Atlas ◽

Mutation Burden ◽

Prognostic Utility ◽

Cancer Genome Atlas ◽

Infiltrating Lymphocytes ◽

Whole Slide Images

AbstractHigh-TMB (TMB-H) could result in an increased number of neoepitopes from somatic mutations expressed by a patient’s own tumor cell which can be recognized and targeted by neighboring tumor-infiltrating lymphocytes (TILs). Deeper understanding of spatial heterogeneity and organization of tumor cells and their neighboring immune infiltrates within tumors could provide new insights into tumor progression and treatment response. Here we developed and applied computational approaches using digital whole slide images (WSIs) to investigate spatial heterogeneity and organization of regions harboring TMB-H tumor cells and TILs within tumors, and its prognostic utility. In experiments using WSIs from The Cancer Genome Atlas bladder cancer (BLCA), our findings show that WSI-based approaches can reliably predict patient-level TMB status and delineate spatial TMB heterogeneity and co-organization with TILs. TMB-H patients with low spatial heterogeneity enriched with high TILs show improved overall survival indicating a prognostic role of spatial TMB and TILs information in BLCA.

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Programmed death-ligand 1 (PD-L1) expression in pheochromocytoma.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.7_suppl.537 ◽

2019 ◽

Vol 37 (7_suppl) ◽

pp. 537-537

Author(s):

Yasuhiro Hashimoto ◽

Hayato Yamamoto ◽

Shingo Hatakeyama ◽

Takahiro Yoneyama ◽

Chikara Ohyama

Keyword(s):

Prostate Cancer ◽

Bladder Cancer ◽

Mrna Expression ◽

Malignant Pheochromocytoma ◽

The Cancer Genome Atlas ◽

Tumor Diameter ◽

Tumor Aggressiveness ◽

Positive Expression ◽

Programmed Death ◽

Cancer Genome Atlas

537 Background: Programmed cell death ligand-1 (PD-L1) is a key target molecule of immunotherapy that is frequently overexpressed in several neoplasms. But there were few reports about PD-L1 expression of pheochromocytoma. In the present study, we examined PD-L1 expression in pheochromocytoma. Methods: PD-L1 mRNA expression was compared across 184 pheochromocytoma, 492 prostate cancer cases and 404 bladder cancer cases based on The Cancer Genome Atlas (TCGA). Furthermore, we enrolled 32 pheochromocytoma patients treated with surgery at our hospital between June 2005 and February 2016. We conducted an immunohistochemistry (IHC) of PD-L1 using the SP142 assay. PD-L1 expression was scored at three diagnostic levels (0/1/2). Results: Comparison of PD-L1 mRNA expression based on the TCGA revealed that PD-L1 expression was significantly higher in pheochromocytoma than in bladder cancer and in prostate cancer (p < 0.001). In the SP 142 assay of our 32 pheochromocytoma, the prevalence of positive PD-L1 expression (IHC score 1 or 2 (1/2)) in tumor-infiltrating immune cells (TICs) was 8 patients (25%). The prevalence of positive PD-L1 expression in tumor cells (TCs) was 9 patients (28.1%). Tumor diameter of PD-L1 (+) in TICs patients was 3.36±0.35 cm and that of PD-L1 (-) in TCs patients was 5.37±0.50cm, there was statistically significance between two groups. (unpaired t test: p=0.044) In our cohort, there were two malignant pheochromocytoma. But there were not PD-L1 positive cases in malignant pheochromocytoma. Conclusions: PD-L1 expression is relatively high in pheochromocytoma compared to bladder cancer and prostate cancer based on TCGA. In the SP142 assay of our 32 pheochromocytoma cases, tumor diameter of PD-L1 (-) in TICs cases was larger than that of PD-L1 (+) cases. In our cohort, there were not PD-L1 (+) cases in malignant pheochromocytoma. These findings suggest that PD-L1 expression of pheochromocytoma was comparatively common and PD-L1 positive expression of pheochromocytoma may not be associated with tumor aggressiveness.

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Muscle invasive bladder cancer (MIBC) demonstrates neoadjuvant cisplatin-based chemotherapy (NAC) related changes in molecular subtype and immune infiltration.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.7_suppl.443 ◽

2019 ◽

Vol 37 (7_suppl) ◽

pp. 443-443

Author(s):

Samuel Aaron Funt ◽

Alexander Solovyov ◽

Bishoy Morris Faltas ◽

Gopa Iyer ◽

Mariel Elena Boyd ◽

...

Keyword(s):

Bladder Cancer ◽

Bladder Tumor ◽

Molecular Subtypes ◽

Molecular Subtype ◽

Expression Patterns ◽

The Cancer Genome Atlas ◽

Rna Expression ◽

Cancer Therapies ◽

Primary Bladder ◽

Muscle Invasive

443 Background: Defining the role of MIBC molecular subtypes and immune expression in determining clinical outcomes is an area of active investigation. However, changes in these transcriptomic profiles pre- and post-NAC have not been well characterized. Methods: This retrospective study reviewed 53 pts with MIBC treated with NAC, of whom 12 pts without complete pathological response had both pre- and post-NAC samples of sufficient quality. Post-NAC staging was > = pT2 in 11 pts and pT1 in 1 pt. We performed RNA expression analysis of matched pre-NAC transurethral resection of bladder tumor specimens and post-treatment radical cystectomy primary bladder tumor specimens. We used a customized NanoString panel incorporating previously reported immune signatures (Ayers, JCI 2017; O’Donnell, ASCO 2017) and additional genes to assign basal ( CD14, CD44, PDGFC, KRT14, KRT5) and luminal ( GATA3, PPARG, SHH, CD24, FOXA1, WNT7B, ERBB2) molecular subtypes. Results: We first classified the bladder cancer cohort of The Cancer Genome Atlas into basal and luminal subtypes using the BASE47 signature (Damrauer, PNAS 2014) and the NanoString panel and there was good agreement (Rand Index = 0.72). We then assigned subtypes using the NanoString panel on matched pre- and post-NAC samples and found marked subtype shift (Table). We identified two robust clusters of samples according to immune expression with a 3-fold change of immune expression between them (FDR = 0.0008). We found that 4 pts switched from the low to the high cluster, while 2 switched from the high to the low cluster after NAC (Table). Conclusions: MIBC molecular subtype membership is dynamic and is influenced by NAC. NAC can induce both enhanced and suppressed immune activity. These findings have implications on future studies exploring the predictive value of RNA expression patterns for bladder cancer therapies as well as post-NAC immunotherapy. [Table: see text]

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