Associating Protein Interactions with Disease Comorbidity to Prioritize Colorectal Cancer Genes

2018 ◽  
pp. 91-95
Author(s):  
Sayedeh Razieh Abdollahi Demneh ◽  
Sama Goliaei ◽  
Zahra Razaghi Moghadam
Keyword(s):  
Colorectal Cancer ◽  
Protein Interactions ◽  
Cancer Genes

scholarly journals Machine learning identifies two autophagy-related genes as markers of recurrence in colorectal cancer

2020 ◽  
Vol 48 (10) ◽  
pp. 030006052095880
Author(s):  
Jianping Wu ◽  
Sulai Liu ◽  
Xiaoming Chen ◽  
Hongfei Xu ◽  
Yaoping Tang
Keyword(s):  
Colorectal Cancer ◽  
Machine Learning ◽  
Protein Interactions ◽  
Early Stage ◽  
Predictive Ability ◽  
Improve Patient Care ◽  
Active Role ◽  
Risk Groups ◽  
Recurrence Risk ◽  
Machine Learning Algorithms

Objective Colorectal cancer (CRC) is the most common cancer worldwide. Patient outcomes following recurrence of CRC are very poor. Therefore, identifying the risk of CRC recurrence at an early stage would improve patient care. Accumulating evidence shows that autophagy plays an active role in tumorigenesis, recurrence, and metastasis. Methods We used machine learning algorithms and two regression models, univariable Cox proportion and least absolute shrinkage and selection operator (LASSO), to identify 26 autophagy-related genes (ARGs) related to CRC recurrence. Results By functional annotation, these ARGs were shown to be enriched in necroptosis and apoptosis pathways. Protein–protein interactions identified SQSTM1, CASP8, HSP80AB1, FADD, and MAPK9 as core genes in CRC autophagy. Of 26 ARGs, BAX and PARP1 were regarded as having the most significant predictive ability of CRC recurrence, with prediction accuracy of 71.1%. Conclusion These results shed light on prediction of CRC recurrence by ARGs. Stratification of patients into recurrence risk groups by testing ARGs would be a valuable tool for early detection of CRC recurrence.

A framework for identifying colorectal cancer genes in detected protein complexes

2019 ◽  
Vol 22 (3) ◽  
pp. 265
Author(s):  
Xiwei Tang ◽  
Mingcai Zheng ◽  
Bihai Zhao ◽  
Guosheng Huang
Keyword(s):  
Colorectal Cancer ◽  
Protein Complexes ◽  
Cancer Genes

scholarly journals Comparative proteomics—network analysis of proteins responsible for ursolic acid–induced cytotoxicity in colorectal cancer cells

Tumor Biology ◽  
2017 ◽  
Vol 39 (3) ◽  
pp. 101042831769501 ◽  
Author(s):  
Qiaoyan Cai ◽  
Jing Lin ◽  
Ling Zhang ◽  
Jiumao Lin ◽  
Lili Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Cells ◽  
Ursolic Acid ◽  
Protein Interactions ◽  
Direct Interaction ◽  
Interaction Network ◽  
Two Dimensional Gel Electrophoresis ◽  
Cellular Targets ◽  
Protein Protein Interaction ◽  
Colorectal Cancer Cells

Ursolic acid is a key active compound present in many medicinal herbs that have been widely used in traditional Chinese medicine for the clinical treatment of various cancers. However, the precise mechanisms of its antitumor activity have been poorly understood. To identify the cellular targets of ursolic acid, two-dimensional gel electrophoresis combined with mass spectrometry was performed in this study, which identified 15 proteins with significantly altered levels in protein expression. This demonstrated that ursolic acid–induced cytotoxicity in colorectal cancer cells involves dysregulation in protein folding, signal transduction, cell proliferation, cell cycle, and apoptosis. Corresponding protein regulation was also confirmed by Western blotting. Furthermore, the study of functional association between these 15 proteins revealed that 10 were closely related in a protein–protein interaction network, whereby the proteins either had a direct interaction with each other or were associated via only one intermediary protein. In this instance, the ATP5B/CALR/HSP90B1/HSPB1/HSPD1-signaling network was revealed as the predominant target which was associated with the majority of the observed protein–protein interactions. As a result, the identified targets may be useful in explaining the anticancer mechanisms of ursolic acid and as potential targets for colorectal cancer therapy.

Analysis of genomic DNA copy number alterations in chromosome arm 18q demonstrates distinct molecular categories of colorectal carcinoma

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 10005-10005
Author(s):  
H. Ji ◽  
M. Zhang ◽  
K. Farnam ◽  
K. Salari ◽  
R. Davis ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Colorectal Carcinoma ◽  
Genomic Instability ◽  
Genetic Markers ◽  
New Technologies ◽  
Stage Ii ◽  
Cancer Genes ◽  
Genomic Deletions ◽  
Chromosome Arm ◽  
Dna Copy Number Alterations

10005 Background: Genomic instability is a major feature of neoplastic development in colorectal carcinoma and other cancers. Specific genomic instability events such as genomic deletions have potential utility as biologically relevant prognostic biomarkers. Loss of heterozygosity (LOH) on chromosome arm 18q is an indicator of colorectal carcinoma behavior and potentially, prognosis. For stage II and III colorectal cancer, a number of retrospective studies have shown strong correlations between deletions in 18q and reduced survival. However, other studies have failed to identify this correlation. This discrepancy is likely the result of different sets of genetic markers and their widely disparate locations along chromosome arm 18q, often separated by megabases. New technologies are needed to overcome these issues. Methods: Using a novel genomic technology called molecular inversion probes (MIPs), we analyzed genomic deletions at exon-level resolution in primary colorectal carcinoma. Unlike microsatellite genetic markers, MIPs are not dependent on having informative alleles to discern a LOH event. This enables querying microsatellite genetic markers used in any clinical study. We designed a set of probes to interrogate several hundred individual exons of over two hundred cancer genes with an overall distribution covering all chromosome arms. Also represented were a series of over 100 probes along chromosome arm 18q representing genetic markers used in clinical studies. An analysis was carried out on primary tumor samples from patients with stage II and III disease. Results: We discovered several distinct categories of colorectal carcinomas based upon their profile of 18q genomic deletions and other allelic imbalances. Colorectal carcinoma extent of invasion showed an association with cluster designation which suggests that the multiple genomic instability events influence the invasive behavior of colorectal carcinoma. Conclusions: Colorectal cancer has distinct patterns of 18q genomic deletions, representing a potential molecular classifier. This finding has potential clinical ramifications given the application of 18q LOH events as an indicator for adjuvant treatment in stage II colorectal carcinoma. No significant financial relationships to disclose.

Stratification of patients with colorectal cancer of UICC stage II using prognostic mutations signatures obtained by deep amplicon sequencing of cancer genes.

2013 ◽  
Vol 31 (4_suppl) ◽  
pp. 377-377
Author(s):  
Andre Rosenthal ◽  
Karsten Ridwelski ◽  
Frank Marusch ◽  
Matthias Pross ◽  
Rene Mantke ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Adjuvant Therapy ◽  
Deep Sequencing ◽  
Predictive Value ◽  
Amplicon Sequencing ◽  
Stage Ii ◽  
Rna Expression ◽  
Uicc Stage ◽  
Cancer Genes ◽  
Primary Tumors

377 Background: Assignment of patients (pts) with UICC-stage II colorectal cancer (CRC) to adjuvant therapy remains controversial. The clinical utility of histo-pathological parameters (pT4, L+, V+) as well as tumor RNA expression signatures like Oncotype Dx Colon Cancer Assay, ColoPrint, or Predictor C is low given their positive predictive value (PPV) of 0.13, 0.22, 0.19, and 0.33, respectively, when adjusted to an incidence of 10% for occurrence of metastatic disease (mets) within 3 years after diagnosis. Methods: We applied deep amplicon sequencing of 48 well-known cancer genes to DNA samples of primary tumors from 173 pts with UICC-stage II CRC using the Illumina MiSeq technology. Patients were selected from a prospective, multicenter clinical diagnostic study named MSKK. More than 6,500 patients with CRC have been recruited into this study conducted by 39 hospitals in Germany. 79 of the 173 pts had progression of disease events within 3 years after R0 resection including 40 pts with mets, 12 pts with local recurrences, and 27 pts with secondary malignancies. 94 pts remained progression-free. Results: Deep sequencing revealed a total of 2,221 sequence variations (SV) including missense, stop, InDel, noncoding, nonsense SV. 401 SV were in COSMIC, 750 SV in normal tissue. The remaining 1471 SV served as basis for development of SV-signatures (SVS) for prediction of progression events in a classical double-nested bootstrap approach in order to generate second order unbiased estimates of performance of SVS, namely sensitivity(S+), specificity (S-), PPV, and negative predictive value (NPV). The best SVS for prediction of metastases contained SV in less than 15 genes and has a S+ of 0.41, S- of 0.93, PPV of 0.40, and NPV of 0.93 (incidence of metastasis: 10%). The best SVS for prediction any progression event has a S+ of 0.33, S- of 0.93, PPV of 0.54, and NPV of 0.84 (incidence for any progression = 20.5%). Conclusions: This deep sequencing based prognostic tissue test with a PPV of 40% and a NPV of 93% represents a milestone over prognostic tests based on RNA expression. The increased PPV leads to more patients being treated correctly with adjuvant therapy.

scholarly journals A genomic strategy for the functional validation of colorectal cancer genes identifies potential therapeutic targets

2010 ◽  
Vol 128 (5) ◽  
pp. 1069-1079 ◽  
Author(s):  
Marian Grade ◽  
Amanda B. Hummon ◽  
Jordi Camps ◽  
Georg Emons ◽  
Melanie Spitzner ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Therapeutic Targets ◽  
Cancer Genes ◽  
Functional Validation

Multidimensional Integration Analysis of Autophagy-related Modules in Colorectal Cancer

2019 ◽  
Vol 16 (4) ◽  
pp. 340-346
Author(s):  
Yang Zhang ◽  
Zheng Zhang ◽  
Dong Wang ◽  
Jianzhen Xu ◽  
Yanhui Li ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Protein Interactions ◽  
Colon Adenocarcinoma ◽  
Undifferentiated Carcinoma ◽  
Protein Protein Interactions ◽  
Integration Strategy ◽  
Novel Approach ◽  
Multidimensional Integration ◽  
Regulation Network ◽  
Integration Analysis

Colorectal cancer (CRC) is a common malignant tumor of the digestive tract occurring in the colon, which mainly divided into adenocarcinoma, mucinous adenocarcinoma, and undifferentiated carcinoma. However, autophagy is related to the occurrence and development of various kinds of human diseases such as cancer. There is little research on the relationship between CRC and autophagy. Hence, we performed multidimensional integration analysis to systematically explore potential relationship between autophagy and CRC. Based on gene expression datasets of colon adenocarcinoma (COAD) and protein-protein interactions (PPIs), we first identified 12 autophagy-related modules in COAD using WGCNA. Then, 9 module pairs which with significantly crosstalk were deciphered, a total of 6 functional modules. Autophagy-related genes in these modules were closely related with CRC, emphasizing that the important role of autophagy-related genes in CRC, including PPP2CA and EIF4E, etc. In addition to, by integrating transcription factor (TF)-target and RNA-associated interactions, a regulation network was constructed, in which 42 TFs (including SMAD3 and TP53, etc.) and 20 miRNAs (including miR-20 and miR-30a, etc.) were identified as pivot regulators. Pivot TFs were mainly involved in cell cycle, cell proliferation and pathways in cancer. And pivot miRNAs were demonstrated associated with CRC. It suggests that these pivot regulators might be have an effect on the development of CRC by regulating autophagy. In a word, our results suggested that multidimensional integration strategy provides a novel approach to discover potential relationships between autophagy and CRC, and further improves our understanding of autophagy and tumor in human.

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