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Research Article
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Aims
The Hub genes highly related to the disease were found from the gene co-expression module, and the potential high expression genes were analyzed to predict the liver metastasis of colorectal cancer, so as to provide reference for subsequent targeted therapy.
Methods
In this study, we used the public data set of GEO database (GSE50760) to analyze the gene co-expression of liver metastasis of colon cancer, primary colon cancer and normal colon tissue (54 cases) and 50 cases of clinical cases. The functional annotations based on GO database are enriched, and the functional annotations of five gene modules are obtained through the enrichment of biological processes. Then the data mining is carried out to find the sub-networks with high adjacency in the gene co-expression network. At the same time, these sub-networks are annotated to find oncogenes related to liver metastasis of colorectal cancer.
Results
This experiment found that KRAS, APC, FBXW7, PIK3CA, TP53 were highly correlated with liver metastasis of colorectal cancer. Finally, two protein genes STAT1 and MAPK1 were found by MCODE, which may be highly correlated with liver metastasis of colorectal cancer. Two new genes with high expression proteins found in this experiment have potential cancer, which has not been reflected in previous studies.
Conclusion
According to clinical data, KRAS, APC, FBXW7, PIK3CA, TP53 are related to colorectal cancer liver metastasis, and the analysis of the data set shows that STAT1 and MAPK1 are not only related to colorectal cancer liver metastasis oncogene but also related to clinically obtained genes.
Keywords
Colorectal cancer liver metastasis, Potential biomarker, Weighted gene co-expression network analysis, Gene expression analysis
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Peer Review Timeline
CURRENT STATUS: Under Revision
Version 1
Posted 19 May, 2021
No community comments so far
Editorial decision: Minor revision
On 08 Jul, 2021
Reviews received
Received 31 May, 2021
Reviewers invited
Invitations sent on 17 May, 2021
Editor assigned
On 16 May, 2021
First submitted
On 10 May, 2021
Metrics
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PDF Downloads: ...
HTML Views: ...
Subject Areas
Gastroenterology & Hepatology
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A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
This preprint is under consideration at Journal of Gastrointestinal Cancer. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Revision
Version 1
Posted 19 May, 2021
No community comments so far
Editorial decision: Minor revision
On 08 Jul, 2021
Reviews received
Received 31 May, 2021
Reviewers invited
Invitations sent on 17 May, 2021
Editor assigned
On 16 May, 2021
First submitted
On 10 May, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Gastroenterology & Hepatology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Aims
The Hub genes highly related to the disease were found from the gene co-expression module, and the potential high expression genes were analyzed to predict the liver metastasis of colorectal cancer, so as to provide reference for subsequent targeted therapy.
Methods
In this study, we used the public data set of GEO database (GSE50760) to analyze the gene co-expression of liver metastasis of colon cancer, primary colon cancer and normal colon tissue (54 cases) and 50 cases of clinical cases. The functional annotations based on GO database are enriched, and the functional annotations of five gene modules are obtained through the enrichment of biological processes. Then the data mining is carried out to find the sub-networks with high adjacency in the gene co-expression network. At the same time, these sub-networks are annotated to find oncogenes related to liver metastasis of colorectal cancer.
Results
This experiment found that KRAS, APC, FBXW7, PIK3CA, TP53 were highly correlated with liver metastasis of colorectal cancer. Finally, two protein genes STAT1 and MAPK1 were found by MCODE, which may be highly correlated with liver metastasis of colorectal cancer. Two new genes with high expression proteins found in this experiment have potential cancer, which has not been reflected in previous studies.
Conclusion
According to clinical data, KRAS, APC, FBXW7, PIK3CA, TP53 are related to colorectal cancer liver metastasis, and the analysis of the data set shows that STAT1 and MAPK1 are not only related to colorectal cancer liver metastasis oncogene but also related to clinically obtained genes.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
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