A novel genomic signature predicting FDG uptake in diverse metastatic tumors
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ABSTRACT:
PROVIDER: PRJNA421282 | ENA |
REPOSITORIES: ENA
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Project description:Purpose: Building a universal genomic signature predicting the intensity of FDG uptake in diverse metastatic tumors may allow us to understand better the biological processes underlying this phenomenon and their requirements of glucose uptake. Methods: A balanced training set (n=71) of metastatic tumors including some of the most frequent histologies, with matched PET/CT quantification measurements and whole human genome gene expression microarrays, was used to build the signature. Selection of microarray features was carried out exclusively on the basis of their strong association with FDG uptake (as measured by SUVmean35) by means of univariate linear regression. A thorough bioinformatics study of these genes was performed and multivariable models were built by fitting several state of the art regression techniques to the training set for comparison. Results: The 909 probes with the strongest association with the SUVmean35 (comprising 742 identifiable genes and 62 probes not matched to a symbol) were used to build the signature. Partial Least Squares using 3 components (PLS-3) was the best performing model in the training dataset cross-validation (Root Mean Square Error, RMSE=0.443) and was validated further in an independent validation dataset (n=13) obtaining a performance within the 95% CI of that obtained in the training dataset (RMSE=0.645). Significantly overrepresented biological processes correlating with the SUVmean35 were identified beyond glycolysis, such as ribosome biogenesis and DNA replication (correlating with a higher SUVmean35), and cytoskeleton reorganization and autophagy (correlating with a lower SUVmean35), among others. Conclusions: PLS-3 is a signature predicting accurately the intensity of FDG uptake in diverse metastatic tumors. FDG-PET might help in the design of specific targeted therapies directed to counteract the identified malignant biological processes more likely activated in a tumor as inferred from the SUVmean35 and also from its variations in response to antineoplastic treatments.
2018-01-22 | GSE107754 | GEO
Project description: Not available
| S-EPMC5773462 | biostudies-literature
Project description:Although remission rates for metastatic melanoma are generally very poor, some patients can survive for prolonged periods following metastasis. We used gene expression profiling, mitotic index (MI), and quantification of tumor infiltrating leukocytes (TILs) and CD3+ cells in metastatic lesions to search for a molecular basis for this observation and to develop improved methods for predicting patient survival. We identified a group of 266 genes associated with postrecurrence survival. Genes positively associated with survival were predominantly immune response related (e.g., ICOS, CD3d, ZAP70, TRAT1, TARP, GZMK, LCK, CD2, CXCL13, CCL19, CCR7, VCAM1) while genes negatively associated with survival were cell proliferation related (e.g., PDE4D, CDK2, GREF1, NUSAP1, SPC24). Identification of genes associated with survival of metastatic melanoma Survival Analysis was performed using Statistical Analysis of Microarrays B D denotes same patient with multiple reccurences
2009-11-30 | E-GEOD-19234 | biostudies-arrayexpress
Project description:The standardized uptake value (SUV), an indicator of the glucose uptake degree in 18F-fluorodeoxyglucose positron emission tomography (FDG-PET), has been used as a prognostic factor in malignant tumors. We aimed to identify a signature reflecting prognostic SUV characteristics in breast cancer (BRC). Transcriptome profiling was performed to identify a signature associated with the SUV in BRC patients who underwent preoperative FDG-PET. We defined a signature consisting of 723 genes significantly correlated with the SUV (|r| > .35; P < .001). The patient subgroups classified by the signature were significantly similar to those classified by the SUV (odds ratio, 8.02; 95% CI, 2.45 to 29.3; P < 0.001). The SUV signature showed independent clinical utility for predicting BRC prognosis (hazard ratio, 1.25; 95% CI, 1.11 to 1.42; P < 0.001). Integrative analysis demonstrated a significance of the signature in predicting the response to immunotherapy and revealed that a signaling axis defined by TP53-FOXM1 and its downstream effectors in glycolysis-gluconeogenesis, including LDHA, might be important mediators in the FDG-PET process. Our results reveal characteristics of glucose uptake captured by FDG-PET, supporting an understanding of glucose metabolism as well as poor prognosis in BRC patients with a high SUV.
2020-03-18 | GSE131769 | GEO
Project description:Although remission rates for metastatic melanoma are generally very poor, some patients can survive for prolonged periods following metastasis. We used gene expression profiling, mitotic index (MI), and quantification of tumor infiltrating leukocytes (TILs) and CD3+ cells in metastatic lesions to search for a molecular basis for this observation and to develop improved methods for predicting patient survival. We identified a group of 266 genes associated with postrecurrence survival. Genes positively associated with survival were predominantly immune response related (e.g., ICOS, CD3d, ZAP70, TRAT1, TARP, GZMK, LCK, CD2, CXCL13, CCL19, CCR7, VCAM1) while genes negatively associated with survival were cell proliferation related (e.g., PDE4D, CDK2, GREF1, NUSAP1, SPC24). Identification of genes associated with survival of metastatic melanoma
2009-12-01 | GSE19234 | GEO
Project description:The risk of locoregional or distant failure in advanced HPV-negative head and neck squamous cell carcinoma (HNSCC) patients is high. However, no suitable markers for stratification are clinically available. Thus, we aimed to identify a microRNA(miRNA)-signature predicting disease recurrence. For this purpose the miRNA profiles from 162 HNSCC samples were analysed with regard to identification of a low-complex porgnostic signature. The data set consists of a discovery dataset (n=85) and a validation dataset (n=77). The study resulted in a prognostic 5-miRNA signature significantly predicting the relevant clinical endpoint freedom from recurrence.
2018-09-06 | E-MTAB-5793 | biostudies-arrayexpress
Project description:BACKGROUND: Due to their varied outcomes, men with biochemical recurrence (BCR) following radical prostatectomy (RP) present a management dilemma. Here, we evaluate Decipher, a genomic classifier (GC), for its ability to predict metastasis following BCR. METHODS: The study population included 85 clinically high-risk patients who developed BCR after RP. Time-dependent receiver operating characteristic (ROC) curves, weighted Cox proportional hazard models, and decision curves were used to compare GC scores to Gleason score (GS), PSA doubling time (PSAdT), time to BCR (ttBCR), the Stephenson nomogram, and CAPRA-S for predicting metastatic disease progression. All tests were two-sided with a type I error probability of 5%. RESULTS: GC scores stratified men with BCR into those who would or would not develop metastasis (8% of patients with low versus 40% with high scores developed metastasis, p<0.001). The area under the curve for predicting metastasis after BCR was 0.82 (95% CI, 0.76-0.86) for GC, compared to GS 0.64 (0.58-0.70), PSAdT 0.69 (0.61-0.77) and ttBCR 0.52 (0.46-0.59). Decision curve analysis showed that GC scores had a higher overall net benefit compared to models based solely on clinicopathologic features. In multivariable modeling with clinicopathologic variables, GC score was the only significant predictor of metastasis (p=0.003). CONCLUSIONS: When compared to clinicopathologic variables, GC better predicted metastatic progression among this cohort of men with BCR following RP. While confirmatory studies are needed, these results suggest that use of GC may allow for better selection of men requiring earlier initiation of treatment at the time of BCR.
2016-09-19 | GSE51066 | GEO
Project description:The purpose of the study is to examine the efficacy of educational materials to promote hepatitis C virus (HCV) screening and colorectal cancer (CRC) screening uptake among adults born between 1945-1965.
| 2384707 | ecrin-mdr-crc
Project description:Analysis of different proteomics profile in primary tumors of metastatic and non-metastatic breast cancers.
2023-03-09 | PXD037288 | Pride
Project description:The standardized uptake value (SUV), an indicator of the glucose uptake degree in 18F-fluorodeoxyglucose positron emission tomography (FDG-PET), has been used as a prognostic factor in malignant tumors. We aimed to identify a signature reflecting prognostic SUV characteristics in triple negative breast cancer (TNBC). Transcriptome profiling was performed to identify a signature associated with the SUV in TNBC patients who underwent preoperative FDG-PET. We defined a signature significantly associated with the SUV (|r| > .35; P < .01). The SUV signature showed independent clinical utility for predicting BRC prognosis. Integrative analysis demonstrated a significance of the signature in predicting the response to immunotherapy and revealed that a signaling axis defined by TP53-FOXM1 and its downstream effectors in glycolysis-gluconeogenesis, including LDHA, might be important mediators in the FDG-PET process. Our results reveal characteristics of glucose uptake captured by FDG-PET, supporting an understanding of glucose metabolism as well as poor prognosis in TNBC patients with a high SUV.
2020-03-18 | GSE135565 | GEO