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01-12-2021 | Metastasis | Research article

A genomic-clinicopathologic Nomogram for the preoperative prediction of lymph node metastasis in gastric cancer

Authors: Xin Zhong, Feichao Xuan, Yun Qian, Junhai Pan, Suihan Wang, Wenchao Chen, Tianyu Lin, Hepan Zhu, Xianfa Wang, Guanyu Wang

Published in: BMC Cancer | Issue 1/2021

Abstract

Background

Preoperative evaluation of lymph node (LN) state is of pivotal significance for informing therapeutic decisions in gastric cancer (GC) patients. However, there are no non-invasive methods that can be used to preoperatively identify such status. We aimed at developing a genomic biosignature based model to predict the possibility of LN metastasis in GC patients.

Methods

We used the RNA profile retrieving strategy and performed RNA expression profiling in a large GC cohort (GSE62254, n = 300) from Gene Expression Ominus (GEO). In the exploratory stage, 300 GC patients from GSE62254 were involved and the differentially expressed RNAs (DERs) for LN-status were determined using the R software. GC samples in GSE62254 were randomly allocated into a learning set (n = 210) and a verification set (n = 90). By using the Least absolute shrinkage and selection operator (LASSO) regression approach, a set of 23-RNA signatures were established and the signature based nomogram was subsequently built for distinguishing LN condition. The diagnostic efficiency, as well as the clinical performance of this model were assessed using the decision curve analysis (DCA). Metascape was used for bioinformatic analysis of the DERs.

Results

Based on the genomic signature, we established a nomogram that robustly distinguished LN status in the learning (AUC = 0.916, 95% CI 0.833–0.999) and verification sets (AUC = 0.775, 95% CI 0.647–0.903). DCA demonstrated the clinical value of this nomogram. Functional enrichment analysis of the DERs was performed using bioinformatics methods which revealed that these DERs were involved in several lymphangiogenesis-correlated cascades.

Conclusions

In this study, we present a genomic signature based nomogram that integrates the 23-RNA biosignature based scores and Lauren classification. This model can be utilized to estimate the probability of LN metastasis with good performance in GC. The functional analysis of the DERs reveals the prospective biogenesis of LN metastasis in GC.

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Title: A genomic-clinicopathologic Nomogram for the preoperative prediction of lymph node metastasis in gastric cancer
Authors: Xin Zhong
Feichao Xuan
Yun Qian
Junhai Pan
Suihan Wang
Wenchao Chen
Tianyu Lin
Hepan Zhu
Xianfa Wang
Guanyu Wang
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Metastasis
Gastric Cancer
Gastric Cancer
Published in: BMC Cancer / Issue 1/2021
Electronic ISSN: 1471-2407
DOI: https://doi.org/10.1186/s12885-021-08203-x

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