A Six-microRNA Signature Nomogram for Preoperative Prediction of Tumor Deposits in Colorectal Cancer

Shihan Xiao; Jianping Guo; Wuming Zhang; Xianqin Hu; Ran Wang; Zhikang Chen; Chen Lai

doi:10.2147/IJGM.S346790

A Six-microRNA Signature Nomogram for Preoperative Prediction of Tumor Deposits in Colorectal Cancer

Int J Gen Med. 2022 Jan 18:15:675-687. doi: 10.2147/IJGM.S346790. eCollection 2022.

Authors

Shihan Xiao^{1

2}, Jianping Guo^{3

4}, Wuming Zhang^{1

2}, Xianqin Hu^{1

2}, Ran Wang^{1

2}, Zhikang Chen^#^{1

2

5}, Chen Lai^#^{1

2

5}

Affiliations

¹ Department of General Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.
² International Joint Research Center of Minimally Invasive Endoscopic Technology Equipment & Standardization, Xiangya Hospital, Central South University, Changsha, Hunan Province, People's Republic of China.
³ Department of Gastrointestinal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China.
⁴ Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China.
⁵ Hunan Key Laboratory of Precise Diagnosis and Treatment of Gastrointestinal Tumor, Xiangya Hospital Central South University, Changsha, Hunan Province, People's Republic of China.

^# Contributed equally.

Abstract

Purpose: Tumor deposits (TDs) are acknowledged negative prognostic factors in colorectal cancer (CRC), and their pathogenesis remains a puzzle. This study aimed to construct and validate a nomogram available for preoperative TDs prediction in CRC patients.

Patients and methods: Patients from the Surveillance, Epidemiology, and End Results (SEER) and the cancer genome atlas (TCGA) databases were randomly divided into training and validation sets according to the sample size ratio of 7:3. Univariate logistic regression was performed for identifying differentially expressed microRNAs between TDs and non-TDs. Nomograms for TDs prediction were developed from the multivariate logistic regression model with least absolute shrinkage and selection operator and were validated internally in terms of accuracy, calibration, and clinical utility. Based on the target genes, pathways tightly associated with TDs were selected using enrichment analysis.

Results: Six clinicopathologic factors and expressions of six microRNAs (miR-614, miR-1197, miR-4770, miR-3136, miR-3173, and miR-4636) differed significantly between TDs and non-TDs CRC patients from the SEER and TCGA training sets. We compared potential prediction discrimination between two nomograms: a clinicopathologic nomogram and a six-microRNA signature nomogram. The six-microRNA signature nomogram revealed better accuracy than the clinicopathologic one for TDs prediction (AUC values of 0.96 and 0.93 in the validation cohort). The calibration plots and decision curve analysis demonstrated that the six-microRNA signature nomogram had better validity and a greater prognostic benefit versus the clinicopathologic one for TDs prediction. Calcium signaling pathways were closely associated with roles of the six microRNAs in TDs of CRC patients.

Conclusion: The six-microRNA signature nomogram can be used as an efficient tool for preoperative TDs prediction in CRC patients.

Keywords: colorectal cancer; microRNA; nomogram; prediction; tumor deposits.

Grants and funding

This study was funded by the National Natural Science Foundation of China (grant 81974386) and the Research and Development program in Key Areas of Hunan Province (grant 2019SK2143).