Dataset Information

Genetic features associated with ¹⁸F-FDG uptake in intrahepatic cholangiocarcinoma.

ABSTRACT:

Purpose

In intrahepatic cholangiocarcinoma (iCCA), genetic characteristics on ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG)-PET scans are not yet clarified. If specific genetic characteristics were found to be related to FDG uptake in iCCA, we can predict molecular features based on the FDG uptake patterns and to distinguish different types of treatments. In this purpose, we analyzed RNA sequencing in iCCA patients to evaluate gene expression signatures associated with FDG uptake patterns.

Methods

We performed RNA sequencing of 22 cases iCCA who underwent preoperative ¹⁸F-FDG-PET, and analyzed the clinical and molecular features according to the maximum standard uptake value (SUVmax). Genes and biological pathway which are associated with SUVmax were analyzed.

Results

Patients with SUVmax higher than 9.0 (n = 9) had poorer disease-free survival than those with lower SUVmax (n = 13, P = 0.035). Genes related to glycolysis and gluconeogenesis, phosphorylation and cell cycle were significantly correlated with SUVmax (r ≥ 0.5). RRM2, which is related to the toxicity of Gemcitabine was positively correlated with SUVmax, and SLC27A2 which is associated with Cisplastin response was negatively correlated with SUVmax. According to the pathway analysis, cell cycle, cell division, hypoxia, inflammatory, and metabolism-related pathways were enriched in high SUVmax patients.

Conclusion

The genomic features of gene expression and pathways can be predicted by FDG uptake features in iCCA. Patients with high FDG uptake have enriched cell cycle, metabolism and hypoxic pathways, which may lead to a more rational targeted treatment approach.

SUBMITTER: Ahn KS

PROVIDER: S-EPMC6444048 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

Genetic features associated with <sup>18</sup>F-FDG uptake in intrahepatic cholangiocarcinoma.

Ahn Keun Soo KS Kang Koo Jeong KJ Kim Yong Hoon YH Kim Tae-Seok TS Song Bong-Il BI Kim Hae Won HW O'Brien Daniel D Roberts Lewis R LR Lee Jeong Woo JW Won Kyoung Sook KS

Annals of surgical treatment and research 20190328 4

<h4>Purpose</h4>In intrahepatic cholangiocarcinoma (iCCA), genetic characteristics on <sup>18</sup>F-fluorodeoxyglucose (<sup>18</sup>F-FDG)-PET scans are not yet clarified. If specific genetic characteristics were found to be related to FDG uptake in iCCA, we can predict molecular features based on the FDG uptake patterns and to distinguish different types of treatments. In this purpose, we analyzed RNA sequencing in iCCA patients to evaluate gene expression signatures associated with FDG uptak ...[more]

PMID: 30941318

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Project description:BackgroundSurgical resection remains the mainstay of curative treatment for intrahepatic cholangiocarcinoma (ICC). Prognosis after surgery is unsatisfactory despite improvements in treatment and post-operative clinical management. Despite developments in the molecular profiling of ICC, the preoperative prediction of prognosis remains a challenge. This study aimed to identify clinical prognostic indicators by investigating the molecular profiles of ICC and evaluating the preoperative imaging data of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET).MethodsA retrospective analysis was performed on 50 consecutive patients with ICC who underwent curative hepatectomy after 18F-FDG-PET examination. To evaluate the molecular profiles of ICC, KRAS mutation status was assessed in resected specimens. For the assessment of glucose uptake, we observed the expression of glucose transporter-1 (GLUT-1) by immunohistochemistry. The data of 18F-FDG-PET were re-evaluated as follows: maximum standardized uptake value, metabolic tumor volume (MTV), and total lesion glycolysis (TLG). Cut-off values were determined using receiver operating characteristic (ROC) curve analysis. Cumulative overall survival (OS) was analyzed using the Kaplan-Meier analysis.ResultsOverall, 16 (32.0%) patients had mutations in KRAS. Patients with mutated KRAS exhibited shorter OS than those with wild-type KRAS (5-year OS, 0% vs. 35.1%, P?<?0.001). GLUT-1 expression was significantly higher in tumors with mutated KRAS than in tumors with wild-type KRAS (median, 4.0 vs. 1.0, P?<?0.001). Survival was significantly different when stratified by expression of GLUT-1 (5-year OS, 0% vs. 46.5%, P?<0.001). Among the 18F-FDG-PET parameters, the MTV and TLG were significantly higher in the mutated KRAS group than in the wild-type KRAS group (P?=?0.013 and P?=?0.026, respectively). ROC curve analysis revealed a cut-off value of 38 for the MTV, with the highest accuracy (area under the curve?=?0.789; 95% confidence interval, 0.581-0.902) for predicting KRAS mutation. This cut-off value permitted stratification of OS (high vs. low: 5-year OS, 13.1% vs. 36.7%, P?=?0.008).ConclusionsHigh MTV is associated with KRAS mutation and poor postoperative outcomes in patients with ICC, suggesting that the MTV of ICC measured by 18F-FDG-PET may provide useful information for tumor molecular profiles and prognosis.

Project description:BackgroundThere is evidence that metabolic disease burden in lymphoma influences patient outcome. However, the impact of disease severity on the cardiovascular system is unknown.ObjectivesThe aim of this study was to examine whether lymphoma is associated with arterial inflammation by investigating the relationship between disease metabolic burden and arterial fluorodeoxyglucose (FDG) uptake.MethodsSixty-two chemotherapy-naïve patients with active Hodgkin's or non-Hodgkin's lymphoma were matched (2:1) to individual control groups of lymphoma patients previously treated and free of active disease. All groups underwent 18F-FDG position emission tomography-computed tomography imaging. Disease severity was quantified by metabolic tumor volume (MTV) and total lesion glycolysis corresponding to standardized uptake values (SUVs) ≥41% or ≥2.5 of the maximum SUV within lymphoma regions, and aortic FDG uptake was quantified through the target-to-background ratio (TBR). Inflammatory and disease severity biomarkers were also measured.ResultsMTV and total lesion glycolysis measurements were significantly correlated with inflammatory and disease biomarkers. Aortic TBR was higher in patients with active non-Hodgkin's lymphoma compared with control subjects (median difference 0.51; 95% confidence interval [CI]: 0.28 to 0.78; p < 0.001). Similarly, patients with active Hodgkin's lymphoma had higher values of aortic TBR compared with control subjects (median difference 0.31; 95% CI: 0.15 to 0.49; p < 0.001). In addition, aortic TBR was modestly increased in patients with stage III to IV disease compared with those with stage I to II disease (median aortic TBR: 2.23 [interquartile range: 2.01 to 2.54] vs. 2.06 [interquartile range: 1.83 to 2.27; p = 0.050). In multivariable analysis, aortic FDG uptake and MTV≥2.5 values were independently associated (β = 0.425; 95% CI: 0.189 to 0.662; p = 0.001; R2 = 0.208), as were aortic FDG uptake and MTV≥41% (β = 0.407; 95% CI: 0.167 to 0.649, p = 0.001; R2 = 0.191).ConclusionsAortic wall FDG uptake is related with disease severity indicative of a possible vascular effect of lymphoma. This work highlights a new potential role of molecular imaging in cardio-oncology for evaluating disease severity and its consequences on the vasculature.

Project description:Knowledge of the intrinsic variability of radiomic features is essential to the proper interpretation of changes in these features over time. The primary aim of this study was to assess the test-retest repeatability of radiomic features extracted from 18F-FDG PET images of cervical tumors. The impact of different image preprocessing methods was also explored. Methods: Patients with cervical cancer underwent baseline and repeat 18F-FDG PET/CT imaging within 7 d. PET images were reconstructed using 2 methods: ordered-subset expectation maximization (PETOSEM) or ordered-subset expectation maximization with point-spread function (PETPSF). Tumors were segmented to produce whole-tumor volumes of interest (VOIWT) and 40% isocontours (VOI40). Voxels were either left at the default size or resampled to 3-mm isotropic voxels. SUV was discretized to a fixed number of bins (32, 64, or 128). Radiomic features were extracted from both VOIs, and repeatability was then assessed using the Lin concordance correlation coefficient (CCC). Results: Eleven patients were enrolled and completed the test-retest PET/CT imaging protocol. Shape, neighborhood gray-level difference matrix, and gray-level cooccurrence matrix features were repeatable, with a mean CCC value of 0.81. Radiomic features extracted from PETOSEM images showed significantly better repeatability than features extracted from PETPSF images (P < 0.001). Radiomic features extracted from VOI40 were more repeatable than features extracted from VOIWT (P < 0.001). For most features (78.4%), a change in bin number or voxel size resulted in less than a 10% change in feature value. All gray-level emphasis and gray-level run emphasis features showed poor repeatability (CCC values < 0.52) when extracted from VOIWT but were highly repeatable (mean CCC values > 0.96) when extracted from VOI40 Conclusion: Shape, gray-level cooccurrence matrix, and neighborhood gray-level difference matrix radiomic features were consistently repeatable, whereas gray-level run length matrix and gray-level zone length matrix features were highly variable. Radiomic features extracted from VOI40 were more repeatable than features extracted from VOIWT Changes in voxel size or SUV discretization parameters typically resulted in relatively small differences in feature value, though several features were highly sensitive to these changes.

Project description:The current standard front-line therapy for patients with diffuse large-B cell lymphoma (DLBCL)-rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP)-is found to be ineffective in up to one-third of them. Thus, their early identification is an important step towards testing alternative treatment options. In this retrospective study, we assessed the ability of 18F-FDG PET/CT imaging features (radiomic + PET conventional parameters) plus clinical data, alone or in combination with genomic parameters to predict complete response to first-line treatment. Imaging features were extracted from images prior treatment. Lesions were segmented as a whole to reflect tumor burden. Multivariate logistic regression predictive models for response to first-line treatment trained with clinical and imaging features, or with clinical, imaging, and genomic features were developed. For imaging feature selection, a manual selection approach or a linear discriminant analysis (LDA) for dimensionality reduction were applied. Confusion matrices and performance metrics were obtained to assess model performance. Thirty-three patients (median [range] age, 58 [49-69] years) were included, of whom 23 (69.69%) achieved long-term complete response. Overall, the inclusion of genomic features improved prediction ability. The best performance metrics were obtained with the combined model including genomic data and built applying the LDA method (AUC of 0.904, and 90% of balanced accuracy). The amplification of BCL6 was found to significantly contribute to explain response to first-line treatment in both manual and LDA models. Among imaging features, radiomic features reflecting lesion distribution heterogeneity (GLSZM_GrayLevelVariance, Sphericity and GLCM_Correlation) were predictors of response in manual models. Interestingly, when the dimensionality reduction was applied, the whole set of imaging features-mostly composed of radiomic features-significantly contributed to explain response to front-line therapy. A nomogram predictive for response to first-line treatment was constructed. In summary, a combination of imaging features, clinical variables and genomic data was able to successfully predict complete response to first-line treatment in DLBCL patients, with the amplification of BCL6 as the genetic marker retaining the highest predictive value. Additionally, a panel of imaging features may provide important information when predicting treatment response, with lesion dissemination-related radiomic features deserving especial attention.

Dataset Information

Genetic features associated with ¹⁸F-FDG uptake in intrahepatic cholangiocarcinoma.

Purpose

Methods

Results

Conclusion

Publications

Genetic features associated with <sup>18</sup>F-FDG uptake in intrahepatic cholangiocarcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Genetic features associated with 18F-FDG uptake in intrahepatic cholangiocarcinoma.

Purpose

Methods

Results

Conclusion

Publications

Genetic features associated with <sup>18</sup>F-FDG uptake in intrahepatic cholangiocarcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Genetic features associated with ¹⁸F-FDG uptake in intrahepatic cholangiocarcinoma.