Pelvic lymph node metastasis (PLNM) is an independent prognostic parameter and determines the treatment strategies of cervical cancer. Increasing evidence indicates that long non-coding RNAs (lncRNAs) play a crucial role in the process of tumor biological functions. This study aimed to mine lymph node metastasis-associated lncRNAs and investigate their potential pathophysiological mechanism in cervical cancer lymph node metastasis. We applied the lncRNA-mining approach to identify lncRNA transcripts represented on Affymetrix human genome U133 plus 2.0 microarrays from Gene Expression Omnibus (GEO) and then by validation in clinical specimens. The biological role and molecular mechanism of these lncRNAs were predicted by bioinformatic analysis. Subsequently, a receiver operating characteristic (ROC) curve and survival curve were conducted to evaluate the diagnostic and prognostic value of candidate lncRNAs. In total, 234 differentially expressed lncRNAs were identified to significantly associate with pelvic lymph node metastasis in early-stage cervical cancer. Our qRT-PCR results were consistent with the mining analysis (P<0.05). The functional enrichment analysis suggested that these lncRNAs may be involved in the biological process of lymph node metastasis. The ROC curves demonstrated satisfactory discrimination power of MIR100HG and AC024560.2 with areas under the curve of 0.801 and 0.837, respectively. Survival curve also indicated that patients with high MIR100HG expression had a tendency of poor prognosis. This is the first study to successfully mine the lncRNA expression patterns in PLNM of early-stage cervical cancer. MIR100HG and AC024560.2 may be a potential biomarkers of PLNM and these lncRNAs may provide broader perspective for combating cervical cancer metastasis.