Cellular and Molecular Targeting of Recurrence in Acute Myeloid Leukemia
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE75086 | GEO | 2018/09/10
REPOSITORIES: GEO
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Project description:The derivation of molecular signatures indicative of disease status and predictive of subsequent behavior could facilitate the optimal choice of treatment for prostate cancer patients. In this study, we conducted a computational analysis of gene expression profile data obtained from 79 cases, 39 of which were classified as having disease recurrence, to investigate whether advanced computational algorithms can derive more accurate prognostic signatures for prostate cancer. At the 90% sensitivity level, a newly derived prognostic genetic signature achieved 85% specificity. This is the first reported genetic signature to outperform a clinically used postoperative nomogram. Furthermore, a hybrid prognostic signature derived by combination of the nomogram and gene expression data significantly outperformed both genetic and clinical signatures, and achieved a specificity of 95%. Our study demonstrates the feasibility of utilizing gene expression information for highly accurate prostate cancer prognosis beyond the current clinical systems, and shows that more advanced computational modeling of tissue-derived microarray data is warranted before clinical application of molecular signatures is considered. mRNA profiling was performed using 79 cases of prostate cancer of known disease recurrence status
2010-11-05 | E-GEOD-25136 | biostudies-arrayexpress
Project description:Lung cancer remains the leading cause of cancer death worldwide. Overall 5-year survival is about 10-15% and despite curative intent surgery, treatment failure is primarily due to recurrent disease. Conventional prognostic markers are unable to determine which patients with completely resected disease within each stage group are likely to relapse. To identify a gene signature associated with recurrent squamous cell carcinoma (SCC) of lung, we analyzed primary tumour gene expression for a total of fifty-one SCCs (stage I-III) on 22,323 element microarrays, comparing expression profiles for individuals who remained disease-free for a minimum of 36 months with those from individuals whose disease recurred within 18 months of complete resection. Cox proportional hazards modeling with leave-one-out cross-validation identified a 70-gene capable of predicting the likelihood of tumor recurrence and a 79-gene signature predictive for overall survival. These two signatures were pooled to generate a 111-gene classifier which achieved an overall predictive accuracy for disease recurrence of 72% (77% sensitivity, 67% specificity) in an independent set of fifty-eight stage I-III SCCs. This classifier also predicted differences in survival (log-rank P=0.0008, hazard ratio (HR), 3.8 [95% confidence interval, 1.6-8.7]), and was superior to conventional prognostic markers such as TNM stage or N stage in predicting patient outcome. Genome-wide profiling has revealed a distinct gene expression profile for recurrent lung SCC which may be clinically useful as a prognostic tool. Expression profiling using 22K element microarrays of 51 primary lung squamous cell carcinomas.
2010-07-01 | E-GEOD-5123 | biostudies-arrayexpress
Project description:Glioblastoma (GBM) remains among the most lethal brain tumors despite improvements in treatment. Surgical resection is a universal component of glioma therapy. However, the mechanism underlying postoperative recurrence remains a challenge due to limited information regarding the changes that occur in the postoperative microenvironment. Here, we show that a subtype of proinflammatory reactive astrocytes designated is induced by inflammatory cytokines or injury. We show that reactive astrocytes can secrete the long noncoding RNA (lncRNA) LOC646762 to promotes recurrence glioblastoma proliferation in an exosome-dependent manner.We firstly named this reactive astrocyte associated lnRNA as “lnc-RVT1”.
2018-06-08 | GSE115459 | GEO
Project description:Lung cancer remains the leading cause of cancer death worldwide. Overall 5-year survival is about 10-15% and despite curative intent surgery, treatment failure is primarily due to recurrent disease. Conventional prognostic markers are unable to determine which patients with completely resected disease within each stage group are likely to relapse. To identify a gene signature associated with recurrent squamous cell carcinoma (SCC) of lung, we analyzed primary tumour gene expression for a total of fifty-one SCCs (stage I-III) on 22,323 element microarrays, comparing expression profiles for individuals who remained disease-free for a minimum of 36 months with those from individuals whose disease recurred within 18 months of complete resection. Cox proportional hazards modeling with leave-one-out cross-validation identified a 70-gene capable of predicting the likelihood of tumor recurrence and a 79-gene signature predictive for overall survival. These two signatures were pooled to generate a 111-gene classifier which achieved an overall predictive accuracy for disease recurrence of 72% (77% sensitivity, 67% specificity) in an independent set of fifty-eight stage I-III SCCs. This classifier also predicted differences in survival (log-rank P=0.0008, hazard ratio (HR), 3.8 [95% confidence interval, 1.6-8.7]), and was superior to conventional prognostic markers such as TNM stage or N stage in predicting patient outcome. Genome-wide profiling has revealed a distinct gene expression profile for recurrent lung SCC which may be clinically useful as a prognostic tool. Keywords: non-small cell lung carcinoma, squamous cell, tumor recurrence, expression profiling
2006-11-21 | GSE5123 | GEO
Project description:Treatment of late-stage melanoma patients with immune checkpoint blockade (ICB) is currently one of the most effective standard therapies. The response rates upon neoadjuvant ICB in stage III melanoma are higher as compared to stage IV disease. Given that successful ICB depends on systemic immune response, we hypothesized that systemic immune suppression might be a mechanism responsible for lower response rates in late-stage disease, and also potentially with disease recurrence in early-stage disease.
2024-01-09 | PXD040399 | Pride
Project description:Our results provide compelling evidence for the potential usefulness of specific serum miRNAs as an effective predictive tool of recurrence and prognostic in BTC patients with radical surgery.
2019-04-17 | GSE119892 | GEO
Project description:Background: Local recurrence is the major manifestation of treatment failure in patients with operable laryngeal carcinoma. Established clinicopathological factors cannot sufficiently predict patients that are likely to recur after treatment. Additional tools are therefore required to accurately identify patients at high risk for recurrence. Methods: Using Affymetrix U133A Genechips, we profiled fresh-frozen tumor tissues from 59 patients with operable laryngeal cancer. All patients were treated locally with surgery, with or without radiation therapy. We performed Cox regression proportional hazards modeling to identify multigene predictors of recurrence. The end-point of our analysis was disease-free survival (DFS). Gene models were directly validated in a separate, similarly treated cohort of 50 patients using Affymetrix chips. In an attempt to further validate our results, we profiled 12 selected genes of our model in formalin-fixed tumor tissues from an independent cohort of 75 patients, using quantitative real time-polymerase chain reaction (qRT-PCR). Results: We focused on genes univariately associated with DFS (p<0.05) in the training set. Among several gene models comprising different numbers of genes, a 30-gene model demonstrated optimal performance (log-rank, p<0.001). We directly applied these gene models to the validation set, after adjusting for non-biological experimental variability, and observed similar results. Specifically, median DFS, as predicted by the 30-gene model, was 34 and 80 months for high- and low-risk patients, respectively (p=0.01). Hazard Ratio (HR) for recurrence for the high-risk group was 3.87 (95% CI 1.28-11.73, p=0.017). Furthermore, unsupervised hierarchical clustering of the 75 patients, based on the qRT-PCR 12-gene profile, yielded two groups, which differed significantly in DFS (log-rank, p=0.027). HR= for recurrence was 2.26, (95% CI 1.08-4.76, p=0.031). Conclusion: We have established and validated gene models that can successfully stratify patients with laryngeal cancer, based on their risk for recurrence. Thus, patients with unfavorable prognosis, when accurately identified, could be ideal candidates for the application of more aggressive treatment modalities. Training set comprises 59 samples and validation set 50 samples
2013-10-30 | E-GEOD-27020 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE18916: Expression data from 42 prostate cancer samples - 16 recurrent and 26 recurrence-free GSE18917: Expression data from 22 prostate cancer samples - 6 recurrent and 16 recurrence-free from the validation dataset Refer to individual Series
2011-06-15 | E-GEOD-18918 | biostudies-arrayexpress
Project description:Tumor recurrence is a slow biological process involving therapy resistance, immune escape and metastasis and is the leading cause of death in medulloblastoma, the most frequent malignant pediatric brain tumor. By studying paired primary-recurrent patient samples and patient-derived xenografts we identified significant accumulation of SOX9-positive cells in relapses and metastases. They exist as rare, quiescent cells in Group 3 and Group 4 patients that constitute two thirds of medulloblastoma. To follow relapse at the single cell level we developed an inducible dual Tet Off animal model of MYC-driven MB, where MYC can be directed from treatment-sensitive bulk cells to resistant, dormant SOX9-positive cells. SOX9 promoted immune escape, DNA repair suppression and was essential for recurrence. Tumor cell dormancy was non-hierarchical, migratory and depended on MYC suppression by SOX9 to promote relapse. By using computational modeling and treatment we further showed how doxorubicin and MGMT inhibitors are specifically targeting relapsing cells.
2022-10-28 | GSE162080 | GEO
Project description:Bladder carcinoma (BLCA) is characterized by a high rate of post-surgery relapse and multifocality, with multifocal tumors carrying a 40% higher risk of recurrence compared to single tumors. Recurrence is a major contributor to bladder cancer-specific mortality. However, understanding interregional or intraregional malignant heterogeneity and cellular communication within the primary and recurrence tumor microenvironment (TME) remains a significant challenge. Here, we employed single-cell RNA sequencing (scRNA-seq) to analyze separate tumor lesions from five multifocal bladder cancer patients (comprising three primary tumors and two recurrence tumors).
2024-11-15 | GSE277524 | GEO