scholarly journals Statistical clustering of parametric maps from dynamic contrast enhanced MRI and an associated decision tree model for non-invasive tumour grading of T1b solid clear cell renal cell carcinoma

2017 ◽  
Vol 28 (1) ◽  
pp. 124-132 ◽  
Author(s):  
Yin Xi ◽  
Qing Yuan ◽  
Yue Zhang ◽  
Ananth J. Madhuranthakam ◽  
Michael Fulkerson ◽  
...  
2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 4580-4580
Author(s):  
Durga Udayakumar ◽  
Ze Zhang ◽  
Durgesh Dwivedi ◽  
Yin Xi ◽  
Tao Wang ◽  
...  

4580 Background: Mutation/inactivation of VHL in clear cell renal cell carcinoma (ccRCC) leads to upregulation of hypoxia inducible factors ( HIFs) and angiogenesis. However, ccRCC is characterized by high intra-tumor heterogeneity (ITH). Random small samples such as those in percutaneous biopsies are likely limited for characterization of molecular alterations in heterogeneous ccRCCs. We hypothesize that whole-tumor dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) is useful to noninvasively identify ITH in ccRCC. Methods: This IRB-approved, prospective, HIPAA-compliant study, included 62 ccRCCs. 3T DCE MRI was obtained prior to nephrectomy. Surgical specimens were sectioned to match MRI acquisition plane. 182 snap frozen samples (49 tumors) and adjacent uninvolved renal parenchyma (URP) were collected. RNA isolations, cDNA library preparation and mRNA sequencing were performed using standard protocols. RNA expression in 81 tumor samples were correlated (Spearman ranked) with % enhancement in a region of interest (ROI) drawn in the same location of the tumor on pre- and 3 different post-contrast DCE MRI phases. Gene function overrepresentation (OR) analyses were done on top positively and negatively correlated genes. False discovery rate (FDR) < 0.1 was considered statistically significant. Results: Principal component analysis of > 20,000 genes indicated distinct gene expression in tumors from URP. Unsupervised clustering showed enrichment of ccA samples (better prognosis) compared to ccB samples (worse prognosis). Importantly, ccA and ccB samples coexisted in 25% of tumors. DCE-MRI % enhancement correlated with expression of > 300 genes (p < 0.003, FDR < 0.1). OR analyses placed angiogenic pathway gene processes and the immune/inflammatory response processes within the top 5 positively- and negatively-correlated gene functions, respectively. HIF2 target genes correlated positively with % enhancement. Conclusions: DCE MRI detects specific molecular signatures and may help overcome the challenges of ITH in ccRCC. Further research is needed to explore the potential role of DCE MRI to assess response to antiangiogenic and immune-based therapies.


2014 ◽  
Vol 55 (2) ◽  
pp. 131-139
Author(s):  
Hans-Juergen Raatschen ◽  
Susanne Fischer ◽  
Benjamin Zsivcsec ◽  
Christian-Olaf Schoenfeld ◽  
Birgit Hotz ◽  
...  

2019 ◽  
Vol 201 (Supplement 4) ◽  
Author(s):  
Antonio Luigi Pastore* ◽  
Yazan Al salhi ◽  
Andrea Fuschi ◽  
Lorenzo Capone ◽  
Gennaro Velotti ◽  
...  

2018 ◽  
Vol 17 (8) ◽  
pp. 169-170
Author(s):  
A. Pastore ◽  
Y. Al salhi ◽  
A. Fuschi ◽  
G. Velotti ◽  
A. Martoccia ◽  
...  

SpringerPlus ◽  
2014 ◽  
Vol 3 (1) ◽  
Author(s):  
Kousei Ishigami ◽  
Leandro V. Leite ◽  
Marius G. Pakalniskis ◽  
Daniel K. Lee ◽  
Danniele G. Holanda ◽  
...  

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaoling Shang ◽  
Xingguo Song ◽  
Kangyu Wang ◽  
Miao Yu ◽  
Shanshan Ding ◽  
...  

Abstract Background Increasing evidence has demonstrated that snoRNAs play crucial roles in tumorigenesis of various cancer types. However, researches on snoRNAs in ccRCC were very little. This study mainly aimed to validate the differential expression and the potential diagnostic value of SNORD63 and SNORD96A in ccRCC. Methods SnoRNAs expression was downloaded from the SNORic and TCGA database including 516 patients with ccRCC and 71 control cases. SNORD63 and SNORD96A expression were further detected in 54 tumor and adjacent FFPE ccRCC tissues, 55 plasma and 75 urinary sediment of ccRCC patients. Then, differential expression and diagnostic value of SNORD63 and SNORD96A were further calculated. Results SNORD63 and SNORD96A expression were significantly increased in ccRCC tissues compared with normal tissues from the TCGA database (both, P < 0.0001). In addition, we found that SNORD63 and SNORD96A localized in plasma and US stably after treating with RNase A. Meanwhile, SNORD63 and SNORD96A in FFPE and US were elevated in ccRCC patients (all, P < 0.0001). However, plasma SNORD63 expression had no significance while SNORD96A significantly increased in plasma of ccRCC patients. Notably, the AUC of SNORD63 in US was 0.7055, by comparison the AUC of plasma SNORD63 was only 0.5161. However, the AUC of plasma SNORD96A was up to 0.8909, by comparison the AUC of SNORD96A in US was 0.6788. Interestingly, the AUC of plasma SNORD96A in early stage ccRCC was highly up to 0.9359. Conclusions Our findings revealed that SNORD63 in US and SNORD96A in plasma could act as the promising non-invasive diagnostic biomarkers for ccRCC patients.


2021 ◽  
Vol 11 ◽  
Author(s):  
Lei Yan ◽  
Guangjie Yang ◽  
Jingjing Cui ◽  
Wenjie Miao ◽  
Yangyang Wang ◽  
...  

PurposeTo develop and validate the radiomics nomogram that combines clinical factors and radiomics features to estimate overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC), and assess the incremental value of radiomics for OS estimation.Materials and MethodsOne hundred ninety-four ccRCC cases were included in the training cohort and 188 ccRCC patients from another hospital as the test cohort. Three-dimensional region-of-interest segmentation was manually segmented on multiphasic contrast-enhanced abdominal CT images. Radiomics score (Rad-score) was calculated from a formula generated via least absolute shrinkage and selection operator (LASSO) Cox regression, after which the association between the Rad-score and OS was explored. The radiomics nomogram (clinical factors + Rad-score) was developed to demonstrate the incremental value of the Rad-score to the clinical nomogram for individualized OS estimation, which was then evaluated in relation to calibration and discrimination.ResultsRad-score, calculated using a linear combination of the 11 screened features multiplied by their respective LASSO Cox coefficients, was significantly associated with OS. Calibration curves showed good agreement between the OS predicted by the nomograms and observed outcomes. The radiomics nomogram presented higher discrimination capability compared to clinical nomogram in the training (C-index: 0.884; 95% CI: 0.808–0.940 vs. 0.803; 95% CI: 0.705–0.899, P &lt; 0.05) and test cohorts (C-index: 0.859; 95% CI: 0.800–0.921 vs. 0.846; 95% CI: 0.777–0.915, P &lt; 0.05).ConclusionsThe radiomics nomogram may be used for predicting OS in patients with ccRCC, and radiomics is useful to assist quantitative and personalized treatment.


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