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A qualitative transcriptional signature for determining the grade of colorectal adenocarcinoma

Cancer Gene Therapy volume 27, pages 680–690 (2020)Cite this article

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A Correction to this article was published on 05 December 2019

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Abstract

Histological grading (HG) is an important prognostic factor of colorectal adenocarcinoma (CRAC): the high-grade CRAC patients have poorer prognosis after tumor resection. Especially, the high-grade stage II CRAC patients are recommended to receive adjuvant chemotherapy. Due to the subjective nature of HG assessment, it is difficult to achieve consistency among pathologists, which brings patients uncertain grading outcomes and inappropriate treatments. We developed a qualitative transcriptional signature based on the within-sample relative expression orderings (REOs) of gene pairs to discriminate high-grade and low-grade CRAC. Using the stage II–III CRAC samples, we detected gene pairs with stable REOs in the high-grade samples and reversal stable REOs in the low-grade samples, and retained the gene pairs whose specific REO patterns were significantly associated with the disease-free survival of patients by univariate Cox regression model. Then, we used a forward-backward searching procedure to extract gene pairs with the highest concordance index as the final grading signature. Finally, 9 gene pairs (9-GPS) were developed to divide CRAC patients into high-grade and low-grade groups. With the signature, there were more differential expression characteristics between reclassified high-grade and low-grade groups. Significant difference of prognosis between the classified two group patients could be seen in four independent datasets. Additionally, genomic analyses showed that the classified high-grade groups were characterized by hypermutation while classified low-grade groups were characterized by frequent copy number alternations. In conclusion, the 9-GPS can provide an objective and robust grading assessment for CRAC patients, which could assist clinical treatment decision.

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  • 05 December 2019

    In the original version of this Article, the affiliation details for Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China were not assigned to all of the authors. This has now been corrected in both the PDF and HTML versions of the Article.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China [grant numbers: 61601151, 61701143, 61673143, 81872396 and 81572935], the Natural Science Foundation of Heilongjiang Province [grant number: C2016037] and the Joint Scientific and Technology Innovation Fund of Fujian Province [grant number: 2016Y9044].

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  1. These authors contributed equally: Hailong Zheng, Kai Song

Authors and Affiliations

  1. Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China

    Hailong Zheng, Kai Song, Yelin Fu, Tianyi You, Jing Yang, Wenbing Guo, Kai Wang, Liangliang Jin, Yunyan Gu, Lishuang Qi, Wenyuan Zhao & Zheng Guo

  2. Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China

    Zheng Guo

  3. Key Laboratory of Medical Bioinformatics, Fujian Province, Fuzhou, China

    Zheng Guo

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Zheng, H., Song, K., Fu, Y. et al. A qualitative transcriptional signature for determining the grade of colorectal adenocarcinoma. Cancer Gene Ther 27, 680–690 (2020). https://doi.org/10.1038/s41417-019-0139-1

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