Different gene expression profiles between de novo and progressive muscle invasive bladder cancer: prognostic implications
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PROVIDER: PRJNA629311 | ENA |
REPOSITORIES: ENA
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Project description:INTRODUCTION: Progressive muscle-invasive bladder cancer (MIBC) has more aggressive behavior than de novo MIBC. This study aimed to ascertain the differences in gene expression profiles between both MIBC groups and to identify prognostic biomarkers to improve the treatment in these patients. MATERIAL AND METHODS: Retrospective multicentre study in which 212 MIBC patients (104 progressive and 108 de novo) who underwent radical cystectomy in the Hospital Clinic (Barcelona) and Radboud UMC (Nijmegen) were included. Total RNA from formalin-fixed paraffin-embedded tissue samples was obtained. Gene expression profiles of 27,965 coding transcripts were determined in 26 patients using Illumina microarrays. Expression levels of 94 genes selected from microarray data and literature were studied by quantitative PCR in an independent series of 186 de novo and progressive MIBC patients. Survival analysis was performed with the Kaplan-Meier method. R-software and SPSSv23 were used for all calculations. RESULTS: A total of 480 genes were found differently expressed (FDR<0.01) between progressive and de novo MIBC samples. Differential expression of 23 out of the 94 genes selected was validated in an independent set of samples. Survival analysis showed that expression of eight genes were prognostic factors of BCR. CONCLUSION: De novo and progressive MIBC patients show different gene expression profiles. In addition, we have identified eight genes with prognostic value which may contribute to improve BC risk stratification and, consequently, to tailor treatment and surveillance strategies in these patients.
2021-03-23 | GSE149582 | GEO
Project description:Prognosis of metastatic BRAF V600E mutant colorectal cancer (CRC) is poor, and the prognostic implications of immune contextures in the tumor microenvironment (TME) for CRC remain elusive. Complement activation in the TME was significantly associated with poor OS and was correlated with TAM M2 in patients with de novo metastatic BRAF V600E mutant CRC.
2022-11-08 | GSE211576 | GEO
Project description:Chronic lymphocytic leukemia (CLL) is a heterogeneous malignancy, characterized by a variable clinical course. While clinical and laboratory parameters are increasingly being used to refine prognosis, they do not accurately predict response to commonly used therapy. We used gene expression profiling to generate and further refine prognostic and predictive markers. Genomic signatures that reflect progressive disease and responses to chemotherapy or chemo-immunotherapy were created using cancer cell lines and patient leukemia samples. We validated these signatures using independent clinical data from four separate cohorts representing a total of 301 CLL patients. A prognostic genomic signature created from patient leukemic cell gene expression data coupled with clinical parameters could statistically differentiate patients with stable or progressive disease in the training dataset. The progression signature was then validated in two independent datasets, demonstrating a capacity to accurately identify patients at risk for progressive disease. In addition, two distinct genomic signatures that predict response to chlorambucil or pentostatin, cyclophosphamide, and rituximab were also generated and were shown to accurately distinguish responding and non-responding CLL patients. Microarray analysis of CLL patientsâ lymphocytes can be used to refine prognosis and predict response to different therapies. These results have direct implications for standard and investigational therapeutics in CLL patients. Experiment Overall Design: For the prognostic genomic signature, 68 CLL leukemia samples were used (36 from patients with stable disease and 32 from patients with progressive disease).
2009-11-11 | E-GEOD-10138 | biostudies-arrayexpress
Project description:Although recent advances in high-throughput technology and data-driven approach have provided many insights into non-muscle invasive bladder cancer (NMIBC), previous studies are still limited in their ability to predict the clinical behavior of NMIBC including response to intravesical therapy. We aim to develop a prognostic index (PI) consisting of a small gene group that predicts the NMIBC progression and response to intravesical bacillus calmette-guérin (BCG) therapy. We analyzed progression-associated genes using Cox regression analysis and validated their predictive values using a fully connected neural network (FNN) algorithm. By applying a pathway enrichment analysis to these genes, a PI system consisting of small core genes for NMIBC progression was developed. Gene expression profiling in NMIBC patients identified a prognostic gene set for predicting NMIBC progression in multiple patient cohorts. Pathway enrichment analysis revealed a 23-gene signature. We incorporated these genes into the PI system, which was a significant prognostic indicator of NMIBC progression. The PI system was shown to be an independent risk factor by a multivariate analysis and subset stratification according to stage and grade. The subset analysis also revealed that the PI system could identify patients who would benefit from BCG immunotherapy. The 23-gene-based PI represents a promising diagnostic tool for identifying high-risk NMIBC patients who would display different clinical behaviors and response to BCG immunotherapy.
2024-02-01 | GSE224248 | GEO
Project description:Chemoradiation therapy (CRT) is a treatment for muscle invasive bladder cancer (MIBC). Using a novel transcriptomic profiling panel, we validated prognostic immune biomarkers for response to CRT on 70 pre-treatment tumor samples from NRG/RTOG 0524 and 0712, two prospective trials of MIBC. Disease-free survival (DFS) and overall survival (OS) was estimated by Kaplan-Meier method and stratified by genes correlated with immune cell proportions and activation. Cox proportional hazards models were used to assess group differences. Sample clustering based on gene expression profiles driven by immune cell proportions demonstrated cluster 2 with a high percentage of immune cell content with significantly longer DFS (Hazard Ratio (HR): 0.53 (95% CI: 0.26 – 1.10), p=0.071) and OS (HR: 0.48 (95% CI: 0.24 – 0.97), p=0.040) than cluster 1 with a low percentage of immune cell content. Higher expression of T cell infiltration genes (CD8A and ICOS ) showed longer DFS (HR: 0.40 (95% CI: 0.21 – 0.75), p=0.005) and OS (HR: 0.49 (95% CI: 0.25 – 0.94), p=0.033). Higher expression of interferon gamma signaling (IDO1) also showed longer DFS (HR: 0.44 (95% CI: 0.24 – 0.88), p=0.021) and OS (HR: 0.49 (95% CI: 0.24 – 0.99), p=0.048). These findings have treatment implications that should be validated in CRT MIBC trials particularly those that integrate immunotherapy.
2023-12-31 | GSE245748 | GEO
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Project description:Breast carcinoma (BC) have been extensively profiled by high-throughput technologies for over a decade, and broadly speaking, these studies can be grouped into those that seek to identify patient subtypes (studies of heterogeneity) or those that seek to identify gene signatures with prognostic or predictive capacity. The shear number of reported signatures has led to speculation that everything is prognostic in BC. Here we show that this ubiquity is an apparition caused by a poor understanding of the inter- relatedness between subtype and the molecular determinants of prognosis. Our approach constructively shows how to avoid confounding due to a patient's subtype, clinicopathological or treatment profile. The approach identifies patients who are predicted to have good outcome at time of diagnosis by all available clinical and molecular markers, but who experience a distant metastasis within five years. These inherently difficult patients (~7% of BC) are prioritized for investigations of intra-tumoral heterogeneity. 321 samples from breast cancer patients.
2014-10-08 | E-GEOD-58644 | biostudies-arrayexpress
Project description:Prognostic implications of 5-hydroxymethylcytosines from circulating cell-free DNA in diffuse large B-cell lymphoma
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Project description:Breast carcinoma (BC) have been extensively profiled by high-throughput technologies for over a decade, and broadly speaking, these studies can be grouped into those that seek to identify patient subtypes (studies of heterogeneity) or those that seek to identify gene signatures with prognostic or predictive capacity. The shear number of reported signatures has led to speculation that everything is prognostic in BC. Here we show that this ubiquity is an apparition caused by a poor understanding of the inter- relatedness between subtype and the molecular determinants of prognosis. Our approach constructively shows how to avoid confounding due to a patient's subtype, clinicopathological or treatment profile. The approach identifies patients who are predicted to have good outcome at time of diagnosis by all available clinical and molecular markers, but who experience a distant metastasis within five years. These inherently difficult patients (~7% of BC) are prioritized for investigations of intra-tumoral heterogeneity.
2014-10-08 | GSE58644 | GEO