Abstract
Accumulating evidence has shown that lymph node metastasis (LNM) is not only an important prognostic factor but also an indicator of the need for postoperative chemoradiotherapy. Therefore, identifying risk factors or molecular markers related to LNM is critical for predicting the prognosis and guiding individualized treatment of patients with cervical cancer. In this study, we used the machine learning-based feature selection approach to identify eight optimal biomarkers from the list of 250 differentially expressed protein-coding genes and long non-coding RNAs (lncRNAs) in the TCGA cohort. Then a coding-non-coding signature (named CNC8SIG) was developed using the elastic-net logistic regression approach based on the expression levels of eight optimal biomarkers, which is useful in discriminating patients with LNM from those without LNM in the discovery cohort. The predictive performance of the CNC8SIG was further validated in two independent patient cohorts. Moreover, the CNC8SIG was significantly associated with patient’s survival in different patient cohorts. In silico functional analysis suggested that the CNC8SIG-associated mRNAs are enriched in known cancer-related biological pathways such as the Wnt signaling pathway, the Ras signaling pathway, Rap1 signaling pathway, and PI3K-Akt signaling pathway.
Highlights
Cervical cancer is the second leading cause of cancer death in women aged 20 to 39 years
One hundred ninety-three cervical cancer patients with lymph node metastasis information were divided into the training cohort (n = 129; 89 patients without LNM and 40 patients with LNM) and testing cohort (n = 64; 44 patients with LNM and 20 patients without LNM) according to a 2:1 ratio
To identify key mRNAs and long non-coding RNAs (lncRNAs) associated with lymph node metastasis, we first compared the mRNA and lncRNA expression profiles obtained from 40 patients that were metastatic to lymph nodes (N+) to 89 patients that were not (N−) in the training cohort
Summary
Cervical cancer is the second leading cause of cancer death in women aged 20 to 39 years. Lymph node metastasis (LNM) status has been reported to be one of the most important prognostic factors and is significantly related to the clinic-pathologic characters (Du et al, 2018). Radical hysterectomy followed by pelvic lymphadenectomy is the standard surgical management for patients with early-stage cervical cancer, pelvic lymphadenectomy may be unnecessary for most patients with early-stage cervical cancer with low risk of LNM. LNM status is an indicator of the need for postoperative radiotherapy. Identifying risk factors or molecular markers related to LNM is critical for predicting the prognosis and guiding individualized radiotherapy of patients with cervical cancer
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