Identification of proteins associated with treatment response of neoadjuvant chemoradiotherapy in rectal mucinous adenocarcinoma by co-expression network analysis based on proteomic analysis

2022 ◽  
pp. 104472
Author(s):  
Yanwu Sun ◽  
Yu Lin ◽  
Yu Deng ◽  
Xuejing Wu ◽  
Jingming Zhong ◽  
...  
Keyword(s):  
Network Analysis ◽  
Treatment Response ◽  
Mucinous Adenocarcinoma ◽  
Proteomic Analysis ◽  
Neoadjuvant Chemoradiotherapy

scholarly journals Predicting Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Mucinous Adenocarcinoma Using an MRI-Based Radiomics Nomogram

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhihui Li ◽  
Shuai Li ◽  
Shuqin Zang ◽  
Xiaolu Ma ◽  
Fangying Chen ◽  
...  
Keyword(s):  
Treatment Response ◽  
Mucinous Adenocarcinoma ◽  
Tumor Regression ◽  
Neoadjuvant Chemoradiotherapy ◽  
Roc Curves ◽  
Quantitative Mri ◽  
Tumor Regression Grade ◽  
Patient Variables ◽  
Validation Set ◽  
Radiomics Signature

ObjectiveTo build and validate an MRI-based radiomics nomogram to predict the therapeutic response to neoadjuvant chemoradiotherapy (nCRT) in rectal mucinous adenocarcinoma (RMAC).MethodsTotally, 92 individuals with pathologically confirmed RMAC administered surgical resection upon nCRT in two different centers were assessed retrospectively (training set, n = 52, validation set, n = 40). Rectal MRI was performed pre-nCRT. Radiomics parameters were obtained from high-resolution T2-weighted images and selected to construct a radiomics signature. Then, radiomics nomogram construction integrated patient variables and the radiomics signature. The resulting radiomics nomogram was utilized to assess the tumor regression grade (TRG). Diagnostic performance was determined by generating receiver operating characteristic (ROC) curves and decision curve analysis (DCA).ResultsSix optimal features related to TRG were obtained to construct a radiomics signature. The nomogram combining the radiomics signature with age and mucin deposit outperformed the radiomics signature alone in the training (AUC, 0.950 vs 0.843, p < 0.05) and validation (AUC, 0.868 vs 0.719, p < 0.05) cohorts. DCA demonstrated a clinical utility for the radiomics nomogram model.ConclusionsThe established quantitative MRI-based radiomics nomogram is effective in predicting treatment response to neoadjuvant therapy in patients with RMAC.

scholarly journals Network Analysis of a Membrane-Enriched Brain Proteome across Stages of Alzheimer’s Disease

Proteomes ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 30 ◽  
Author(s):  
Lenora Higginbotham ◽  
Eric Dammer ◽  
Duc Duong ◽  
Erica Modeste ◽  
Thomas Montine ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Network Analysis ◽  
Proteomic Analysis ◽  
Expression Patterns ◽  
Label Free ◽  
Post Mortem Brain ◽  
Brain Proteome ◽  
Associated Proteins ◽  
Membrane Bound

Previous systems-based proteomic approaches have characterized alterations in protein co-expression networks of unfractionated asymptomatic (AsymAD) and symptomatic Alzheimer’s disease (AD) brains. However, it remains unclear how sample fractionation and sub-proteomic analysis influences the organization of these protein networks and their relationship to clinicopathological traits of disease. In this proof-of-concept study, we performed a systems-based sub-proteomic analysis of membrane-enriched post-mortem brain samples from pathology-free control, AsymAD, and AD brains (n = 6 per group). Label-free mass spectrometry based on peptide ion intensity was used to quantify the 18 membrane-enriched fractions. Differential expression and weighted protein co-expression network analysis (WPCNA) were then used to identify and characterize modules of co-expressed proteins most significantly altered between the groups. We identified a total of 27 modules of co-expressed membrane-associated proteins. In contrast to the unfractionated proteome, these networks did not map strongly to cell-type specific markers. Instead, these modules were principally organized by their associations with a wide variety of membrane-bound compartments and organelles. Of these, the mitochondrion was associated with the greatest number of modules, followed by modules linked to the cell surface compartment. In addition, we resolved networks with strong associations to the endoplasmic reticulum, Golgi apparatus, and other membrane-bound organelles. A total of 14 of the 27 modules demonstrated significant correlations with clinical and pathological AD phenotypes. These results revealed that the proteins within individual compartments feature a heterogeneous array of AD-associated expression patterns, particularly during the preclinical stages of disease. In conclusion, this systems-based analysis of the membrane-associated AsymAD brain proteome yielded a unique network organization highly linked to cellular compartmentalization. Further study of this membrane-associated proteome may reveal novel insight into the complex pathways governing the earliest stages of disease.

Integrated in silico and experimental methods revealed that Arctigenin inhibited angiogenesis and HCT116 cell migration and invasion through regulating the H1F4A and Wnt/β-catenin pathway

2015 ◽  
Vol 11 (11) ◽  
pp. 2878-2884 ◽  
Author(s):  
Shouyue Zhang ◽  
Jie Li ◽  
Sicheng Song ◽  
Jing Li ◽  
Rongsheng Tong ◽  
...  
Keyword(s):  
Cell Migration ◽  
Network Analysis ◽  
Proteomic Analysis ◽  
In Silico ◽  
Hct116 Cell ◽  
Experimental Methods ◽  
Migration And Invasion ◽  
Cell Migration And Invasion ◽  
Signalling Network ◽  
Novel Target

The proteomic analysis integrated signalling network analysis suggested that the Wnt/β-catenin signalling pathway was a novel target of Arctigenin.

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