A novel identified pyroptosis-related prognostic signature of colorectal cancer
Colorectal cancer (CRC), one of the most common malignancies worldwide, leads to abundant cancer-related mortalities annually. Pyroptosis, a new kind of programmed cell death, plays a critical role in immune response and tumor progression. Our study aimed to identify a prognostic signature for CRC b...
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| Format: | Article |
| Language: | English |
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AIMS Press
2021-10-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2021433?viewType=HTML |
| _version_ | 1818742084400578560 |
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| author | Chen Zheng Zhaobang Tan |
| author_facet | Chen Zheng Zhaobang Tan |
| author_sort | Chen Zheng |
| collection | DOAJ |
| description | Colorectal cancer (CRC), one of the most common malignancies worldwide, leads to abundant cancer-related mortalities annually. Pyroptosis, a new kind of programmed cell death, plays a critical role in immune response and tumor progression. Our study aimed to identify a prognostic signature for CRC based on pyroptosis-related genes (PRGs). The difference in PRGs between CRC tissues and normal tissues deposited in the TCGA database was calculated by "limma" R package. The tumor microenvironment (TME) of CRC cases was accessed by the ESTIMATE algorithm. The prognostic PRGs were identified using Cox regression analysis. A least absolute shrinkage and selector operation (LASSO) algorithm was used to calculate the risk scores and construct a clinical predictive model of CRC. Gene Set Enrichment Analysis (GSEA) was performed for understanding the function annotation of the signature in the tumor microenvironment. We found that most PRGs were significantly dysregulated in CRC. Through the LASSO method, three key PRGs were selected to calculate the risk scores and construct the prognostic model for CRC. The risk score was an independent indicator of patient's prognosis. In addition, we classified the CRC patients into two clusters based on risk scores and discovered that CRC patients in cluster 2 underwent worse overall survival and owned higher expression levels of immune checkpoint genes in tumor tissues. In conclusion, our study identified a PRG-related prognostic signature for CRC, according to which we classified the CRC patients into two clusters with distinct prognosis and immunotherapy potential. |
| first_indexed | 2024-12-18T02:06:54Z |
| format | Article |
| id | doaj.art-75368c0f40d447efb1b1e0785d500245 |
| institution | Directory Open Access Journal |
| issn | 1551-0018 |
| language | English |
| last_indexed | 2024-12-18T02:06:54Z |
| publishDate | 2021-10-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj.art-75368c0f40d447efb1b1e0785d5002452022-12-21T21:24:34ZengAIMS PressMathematical Biosciences and Engineering1551-00182021-10-011868783879610.3934/mbe.2021433A novel identified pyroptosis-related prognostic signature of colorectal cancerChen Zheng0Zhaobang Tan11. First Department of General Surgery, Xi'an Central Hospital, Xi'an, Shaanxi Province, China2. Department of digestive surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, ChinaColorectal cancer (CRC), one of the most common malignancies worldwide, leads to abundant cancer-related mortalities annually. Pyroptosis, a new kind of programmed cell death, plays a critical role in immune response and tumor progression. Our study aimed to identify a prognostic signature for CRC based on pyroptosis-related genes (PRGs). The difference in PRGs between CRC tissues and normal tissues deposited in the TCGA database was calculated by "limma" R package. The tumor microenvironment (TME) of CRC cases was accessed by the ESTIMATE algorithm. The prognostic PRGs were identified using Cox regression analysis. A least absolute shrinkage and selector operation (LASSO) algorithm was used to calculate the risk scores and construct a clinical predictive model of CRC. Gene Set Enrichment Analysis (GSEA) was performed for understanding the function annotation of the signature in the tumor microenvironment. We found that most PRGs were significantly dysregulated in CRC. Through the LASSO method, three key PRGs were selected to calculate the risk scores and construct the prognostic model for CRC. The risk score was an independent indicator of patient's prognosis. In addition, we classified the CRC patients into two clusters based on risk scores and discovered that CRC patients in cluster 2 underwent worse overall survival and owned higher expression levels of immune checkpoint genes in tumor tissues. In conclusion, our study identified a PRG-related prognostic signature for CRC, according to which we classified the CRC patients into two clusters with distinct prognosis and immunotherapy potential.https://www.aimspress.com/article/doi/10.3934/mbe.2021433?viewType=HTMLcolorectal cancerpyroptosisprognosistcgaimmune infiltration |
| spellingShingle | Chen Zheng Zhaobang Tan A novel identified pyroptosis-related prognostic signature of colorectal cancer Mathematical Biosciences and Engineering colorectal cancer pyroptosis prognosis tcga immune infiltration |
| title | A novel identified pyroptosis-related prognostic signature of colorectal cancer |
| title_full | A novel identified pyroptosis-related prognostic signature of colorectal cancer |
| title_fullStr | A novel identified pyroptosis-related prognostic signature of colorectal cancer |
| title_full_unstemmed | A novel identified pyroptosis-related prognostic signature of colorectal cancer |
| title_short | A novel identified pyroptosis-related prognostic signature of colorectal cancer |
| title_sort | novel identified pyroptosis related prognostic signature of colorectal cancer |
| topic | colorectal cancer pyroptosis prognosis tcga immune infiltration |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2021433?viewType=HTML |
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