J Cancer 2020; 11(23):6861-6873. doi:10.7150/jca.49262 This issue Cite

Research Paper

Pathologic evolution-related Gene Analysis based on both single-cell and bulk transcriptomics in Colorectal Cancer

Jiali Li1, Zihang Zeng1, Jiarui Chen1, Xingyu Liu1, Xueping Jiang1, Wenjie Sun1, Yuan Luo1, Jiangbo Ren2, Yan Gong2,3✉, Conghua Xie1,4,5✉

1. Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China.
2. Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.
3. Human Genetics Resource Preservation Center of Hubei Province, Zhongnan Hospital of Wuhan University, Wuhan, China.
4. Hubei Key Laboratory of Tumor Biological Behaviors, Zhongnan Hospital of Wuhan University, Wuhan, China.
5. Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, China.

Citation:
Li J, Zeng Z, Chen J, Liu X, Jiang X, Sun W, Luo Y, Ren J, Gong Y, Xie C. Pathologic evolution-related Gene Analysis based on both single-cell and bulk transcriptomics in Colorectal Cancer. J Cancer 2020; 11(23):6861-6873. doi:10.7150/jca.49262. https://www.jcancer.org/v11p6861.htm
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Abstract

Purpose: The patients diagnosed with colorectal cancer (CRC) are likely to undergo differential outcomes in clinical survival owing to different pathologic stages. However, signatures in association with pathologic evolution and CRC prognosis are not clearly defined. This study aimed to identify pathologic evolution-related genes in CRC based on both single-cell and bulk transcriptomics.

Patients and methods: The CRC single-cell transcriptomic dataset (GSE81861, n=590) with clinical information and tumor microenvironmental tissues was collected to identify the pathologic evolution-related genes. The colonic adenocarcinoma and rectum adenocarcinoma transcriptomics from The Cancer Genome Atlas were obtained as the training dataset (n=363) and 5 other CRC transcriptomics cohorts from Gene Expression Omnibus (n=1031) were acquired as validation data. Graph-based clustering analysis algorithm was applied to identify pathologic evolution-related cell populations. Pseudotime analysis was performed to construct the trajectory plot of pathologic evolution and to define hub genes in the evolution process. Cell-type identification by estimating relative subsets of RNA transcripts was then executed to build a novel cell infiltration classifier. The prediction efficacy of this classifier was validated in bulk transcriptomic datasets.

Results: Epithelial and T cells were elucidated to be related to the pathologic stages in CRC tissues. Pseudotime analysis and survival analysis indicated that HOXC5, HOXC8 and BMP5 were the marker genes in pathologic evolution process. Our cell infiltration classifier exhibited excellent forecast efficacy in predicting pathologic stages and prognosis of CRC patients.

Conclusion: We identified pathologic evolution-related genes in single-cell transcriptomic and proposed a novel specific cell infiltration classifier to forecast the prognosis of CRC patients based on pathologic stage-related hub genes HOXC6, HOXC8 and BMP5.

Keywords: single-cell sequencing, colorectal cancer, pathologic stage, prognosis, TCGA, GEO


Citation styles

APA
Li, J., Zeng, Z., Chen, J., Liu, X., Jiang, X., Sun, W., Luo, Y., Ren, J., Gong, Y., Xie, C. (2020). Pathologic evolution-related Gene Analysis based on both single-cell and bulk transcriptomics in Colorectal Cancer. Journal of Cancer, 11(23), 6861-6873. https://doi.org/10.7150/jca.49262.

ACS
Li, J.; Zeng, Z.; Chen, J.; Liu, X.; Jiang, X.; Sun, W.; Luo, Y.; Ren, J.; Gong, Y.; Xie, C. Pathologic evolution-related Gene Analysis based on both single-cell and bulk transcriptomics in Colorectal Cancer. J. Cancer 2020, 11 (23), 6861-6873. DOI: 10.7150/jca.49262.

NLM
Li J, Zeng Z, Chen J, Liu X, Jiang X, Sun W, Luo Y, Ren J, Gong Y, Xie C. Pathologic evolution-related Gene Analysis based on both single-cell and bulk transcriptomics in Colorectal Cancer. J Cancer 2020; 11(23):6861-6873. doi:10.7150/jca.49262. https://www.jcancer.org/v11p6861.htm

CSE
Li J, Zeng Z, Chen J, Liu X, Jiang X, Sun W, Luo Y, Ren J, Gong Y, Xie C. 2020. Pathologic evolution-related Gene Analysis based on both single-cell and bulk transcriptomics in Colorectal Cancer. J Cancer. 11(23):6861-6873.

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