Prognostic value of metabolic signature on 18F-FDGuptake in breast cancer patients after radiotherapy.
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ABSTRACT:
SUBMITTER: Meng J
PROVIDER: S-EPMC8605077 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Breast cancer (BRCA) is the most common cancer and a major cause of death in women. Long non-coding RNAs (lncRNAs) are emerging as key regulators and have been implicated in carcinogenesis and prognosis. In this study, we aimed to develop a lncRNA signature of BRCA patients to improve risk stratification. In the training cohort (GSE21653, n = 232), 17 lncRNAs were identified by univariate Cox proportional hazards regression, which were significantly associated with patients' survival. The least absolute shrinkage and selection operator-penalized Cox proportional hazards regression analysis was used to identify a six-lncRNA signature. According to the median of the signature risk score, patients were divided into a high-risk group and a low-risk group with significant disease-free survival differences in the training cohort. A similar phenomenon was observed in validation cohorts (GSE42568, n = 101; GSE20711, n = 87). The six-lncRNA signature remained as independent prognostic factors after adjusting for clinical factors in these two cohorts. Furthermore, this signature significantly predicted the survival of grade III patients and estrogen receptor-positive patients. Furthermore, in another cohort (GSE19615, n = 115), the low-risk patients that were treated with tamoxifen therapy had longer disease-free survival than those who underwent no therapy. Overall, the six-lncRNA signature can be a potential prognostic tool used to predict disease-free survival of patients and to predict the benefits of tamoxifen treatment in BRCA, which will be helpful in guiding individualized treatments for BRCA patients.
| S-EPMC7396575 | biostudies-literature
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:BackgroundBreast cancer (BRCA) is a malignant tumor with high morbidity and mortality, which is a threat to women's health worldwide. Ferroptosis is closely related to the occurrence and development of breast cancer. Here, we aimed to establish a ferroptosis-related prognostic gene signature for predicting patients' survival.MethodsGene expression profile and corresponding clinical information of patients from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. The Least absolute shrinkage and selection operator (LASSO)-penalized Cox regression analysis model was utilized to construct a multigene signature. The Kaplan-Meier (K-M) and Receiver Operating Characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes, Genomes (KEGG) pathway and single-sample gene set enrichment analysis (ssGSEA) were performed for patients between the high-risk and low-risk groups divided by the median value of risk score.ResultsWe constructed a prognostic signature consisted of nine ferroptosis-related genes (ALOX15, CISD1, CS, GCLC, GPX4, SLC7A11, EMC2, G6PD and ACSF2). The Kaplan-Meier curves validated the fine predictive accuracy of the prognostic signature (p < 0.001). The area under the curve (AUC) of the ROC curves manifested that the ferroptosis-related signature had moderate predictive power. GO and KEGG functional analysis revealed that immune-related responses were largely enriched, and immune cells, including activated dendritic cells (aDCs), dendritic cells (DCs), T-helper 1 (Th1), were higher in high-risk groups (p < 0.001). Oppositely, type I IFN response and type II IFN response were lower in high-risk groups (p < 0.001).ConclusionOur study indicated that the ferroptosis-related prognostic signature gene could serve as a novel biomarker for predicting breast cancer patients' prognosis. Furthermore, we found that immunotherapy might play a vital role in therapeutic schedule based on the level and difference of immune-related cells and pathways in different risk groups for breast cancer patients.
| S-EPMC8165796 | biostudies-literature
Project description:Clinical applications of gene expression signatures in breast cancer prognosis still remain limited due to poor predictive strength of single training datasets and appropriate invariable platforms. We proposed a gene expression signature by reducing baseline differences and analyzing common probes among three recent Affymetrix U133 plus 2 microarray data sets. Using a newly developed supervised method, a 92-probe signature found in this study was associated with overall survival. It was robustly validated in four independent data sets and then repeated on three subgroups by incorporating 17 breast cancer microarray datasets. The signature was an independent predictor of patients' survival in univariate analysis [(HR) 1.927, 95% CI (1.237-3.002); p < 0.01] as well as multivariate analysis after adjustment of clinical variables [(HR) 7.125, 95% CI (2.462-20.618); p < 0.001]. Consistent predictive performance was found in different multivariate models in increased patient population (p = 0.002). The survival signature predicted a late metastatic feature through 5-year disease free survival (p = 0.006). We identified subtypes within the lymph node positive (p < 0.001) and ER positive (p = 0.01) patients that best reflected the invasive breast cancer biology. In conclusion using the Common Probe Approach, we present a novel prognostic signature as a predictor in breast cancer late recurrences.
| S-EPMC4558178 | biostudies-literature
Project description:High metabolic activity, reflected in increased glucose uptake, is one of the hallmarks of many cancers including breast cancer. However, not all cancers avidly take up glucose, suggesting heterogeneity in their metabolic demand. Thus, we aim to generate a genomic signature of glucose hypermetabolism in breast cancer and examine its clinical relevance. To identify genes significantly associated with glucose uptake, gene expression data were analyzed together with the standardized uptake values (SUVmax) of 18F-fluorodeoxy-glucose on positron emission tomography (PET) for 11 breast cancers. The resulting PET signature was evaluated for prognostic significance in four large independent patient cohorts (n = 5417). Potential upstream regulators accountable for the high glucose uptake were identified by gene network analysis. A PET signature of 242 genes was significantly correlated with SUVmax in breast cancer. In all four cohorts, high PET signature was significantly associated with poorer prognosis. The prognostic value of this PET signature was further supported by Cox regression analyses (hazard ratio 1.7, confidential interval 1.48-2.02; P < 0.001). The PET signature was also strongly correlated with previously established prognostic genomic signatures such as PAM50, Oncotype DX, and NKI. Gene network analyses suggested that MYC and TBX2 were the most significant upstream transcription factors in the breast cancers with high glucose uptake. A PET signature reflecting high glucose uptake is a novel independent prognostic factor in breast cancer. MYC and TBX2 are potential regulators of glucose uptake.
| S-EPMC8356554 | biostudies-literature
Project description:The standardized uptake value (SUV), an indicator of the degree of glucose uptake in 18F-fluorodeoxyglucose positron emission tomography (FDG-PET), has been used for predicting the clinical behavior of malignant tumors. However, its characteristics have been insufficiently explored at the genomics level. Here, we aim to identify genomic signatures reflecting prognostic SUV characteristics in breast cancer (BRC). Through integrative genomic profiling of 3710 BRC patients, including 254 patients who underwent preoperative FDG-PET, we identified an SUV signature, which showed independent clinical utility for predicting BRC prognosis (hazard ratio [HR] 1.27, 95% confidence interval [CI] = 1.12 to 1.45, p = 2.23 × 10-4). The risk subgroups classified by the signature exhibited mutually exclusive mutation patterns of TP53 and PIK3CA and showed significantly different responsiveness to immunotherapy. Experimental assays 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 molecular characterizations support an understanding of glucose metabolism and poor prognosis in BRC with a high SUV, utilizable in clinical practice to assist other diagnostic tools.
| S-EPMC7072341 | biostudies-literature
Project description:BACKGROUND:To identify whether early metabolic responses as determined using 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) during radiotherapy (RT) predict outcomes in patients with esophageal cancer. METHODS:Twenty-one patients with esophageal cancer who received pre-treatment 18F-FDG PET/CT (PET1) and inter-fractional 18F-FDG PET/CT (PET2) after 11 fractions of RT (median 23.1?Gy, 2.1?Gy per fraction) were retrospectively reviewed. The region of interest for each calculation was delineated using "PET Edge". We calculated PET parameters including maximum and mean standardized uptake values (SUVmax and SUVmean, respectively), metabolic tumor volume (MTV), and total lesion glycolysis (TLG). The relative changes (%) were calculated using the logarithmically transformed parameter values for the PET1 and PET2 scans. Multivariate analysis of locoregional recurrence and distant failures were performed using Cox regression analysis. After identifying statistically significant PET parameters for discriminating responders from non-responders, receiver operating characteristics curve analyses were used to assess the potentials of the studied PET parameters. RESULTS:After a median follow-up of 13?months, the 1-year overall and progression-free survival rates were 79.0% and 34.4%, respectively. Four patients developed locoregional recurrences (LRRs) and 8 had distant metastases (DMs). The 1-year overall LRR-free rate was 76.9% while the DM-free rate was 60.6%. The relative changes in MTV (?MTV) were significantly associated with LRR (p =?0.03). Conversely, the relative changes in SUVmean (?SUVmean) were associated with the risk of DM (p =?0.02). An ?MTV threshold of 1.14 yielded a sensitivity of 60%, specificity of 94%, and an accuracy of 86% for predicting an LRR. Additionally, a ?SUVmean threshold of a 35% decrease yielded a sensitivity of 67%, specificity of 83%, and accuracy of 76% for the prediction DM. TRIAL REGISTRATION:Retrospectively registered. CONCLUSIONS:Changes in tumor metabolism during RT could be used to predict treatment responses, recurrences, and prognoses in patients with esophageal cancer.
| S-EPMC6362604 | biostudies-literature
Project description:This study investigated the prognostic value of metabolic parameters determined by 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in patients with stage III gastric cancer. Patients with pre-operative PET/CT and confirmed stage III after curative surgical resection were retrospectively enrolled. Parameters evaluated from pre-operative PET/CTwere maximum standardized uptake value (SUVmax) and peak SUV (SUVpeak) of primary tumor, SUVmax or SUVpeak of tumor to liver ratio (TLRmax and TLRpeak). Volumetric parameters, metabolic tumor volume (MTV) and total lesion glycolysis (TLG), were also evaluated. These PET/CT parameters were compared with the overall survival (OS) and recurrence-free survival (RFS). From total of 133 consecutive patients, tumor recurrence was found in 54 patients (40.6%) and 53 died during the follow-up period (median, 43 mo; range 5-62). In univariate analysis, SUVmax, SUVpeak, TLRmax and TLRpeak were significantly associated with the OS and RFS. In multivariate analysis, high TLRmax and TLRpeak were significantly unfavorable prognostic factors for RFS (both P<0.05) even after adjusting for age, depth of tumor invasion, lymph node metastasis, and chemotherapy. MTV and TLG showed no statistically significant correlation with outcome. In conclusion, glucose metabolism of primary tumor measured by pre-operative PET/CT provides prognostic information, especially for recurrence, in stage III gastric cancer.
| S-EPMC5325418 | biostudies-literature
Project description:Breast cancer (BC) is the most common type of malignancy among females worldwide. Histone modifications, which are the major post-translational modifications, have a significant role in cancer development and prognosis. However, whether histone family genes may serve as potential prognostic biomarkers for BC patients has remained elusive. In the present study, RNA-sequencing data were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed genes were identified and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway functional enrichment analysis was performed. As histone family genes have been reported to be associated with cervical cancer, the present study hypothesized that histone family genes are associated with gynecological tumors. Histone family genes, including histone cluster 1 H1A family member B (HIST1H1B), HIST1H2AJ, HIST1H2AM, HIST1H2BI, HIST1H2BO, HIST1H3B, HIST1H3F, HIST1H3H, HIST1H4C and HIST1H4D, were upregulated and identified as hub genes in the protein-protein interaction network. In addition, Oncomine and the Human Protein Atlas were used to further verify the expression levels of histone gene sets. The PrognoScan database was then used to investigate the association between expression and prognostic value regarding cancer patient survival. The present results indicated that higher expression of histone gene sets was associated with poor overall survival, relapse-free survival and distant metastasis-free survival of BC patients. The differential expression of histone family genes between BC and normal samples was validated by reverse transcription-quantitative PCR. Finally, to determine the clinical role of histone family genes in BC, the correlations between histone family genes expression and clinical characteristics were investigated through data collected from TCGA. Therefore, the present study indicates that histone gene sets may be used as prognostic factors for survival prediction for BC patients.
| S-EPMC6861870 | biostudies-literature
Project description:BACKGROUND:18F-FDG PET/CT metabolic parameters have been applied as prognostic factors in multi-malignancies. However, the role in locally advanced pancreatic cancer (LAPC) was not confirmed. In this study, we investigated the prognostic value of 18F-FDG PET/CT metabolic parameters in LAPC patients treated with stereotactic body radiation therapy (SBRT). METHODS:Seventy three LAPC patients who received SBRT therapy and pre-treatment 18F-FDG PET/CT imaging from January 2012 to January 2016 were included in this retrospective study. The study aim was to evaluate the relationship between metabolic parameters with clinical factors, and the value of metabolic parameters in the prognosis of LAPC. The median of parameters was set as the cut-off value for statistical analysis. Univariate survival analysis was performed by the Kaplan Meier method and log-rank test, and multivariate analysis was carried out by a Cox proportional hazards model. RESULTS:Patients with lymph node metastasis or longer tumor diameters were associated with higher TLG (P?<?0.05). Univariate analysis showed MTV, TLG, radiotherapy dose and chemotherapy were significantly associated with disease progression-free survival (PFS) and overall survival (OS) (P < 0.05). Lymph node metastasis and tumor longest diameter were associated with OS. Multivariate analysis demonstrated TLG, radiotherapy dose, and chemotherapy were independent factors of PFS and OS (HR: 2.307, 0.591, 0.572 and 2.145, 0.480, 0.471, P < 0.05). CONCLUSIONS:TLG was found to be the independent prognostic factor of OS and PFS. Among clinical factors, radiotherapy dose and chemotherapy were independent prognostic factors of OS and PFS.
| S-EPMC7063714 | biostudies-literature