A Comprehensive Pipeline for Long Non-Coding RNA Discovery and Characterization in Cancer

Long non-coding RNAs (lncRNAs) represent a significant yet underexplored component of the human genome, with emerging evidence linking them to various biological processes and diseases. Despite over 205,000 lncRNAs documented in existing databases, a substantial number remain unidentified, highlighting the complexity of the human genome. LncRNAs engage in intricate regulatory mechanisms that influence gene expression, chromatin dynamics, and cellular metabolism, particularly in the context of cancer. While substantial progress has been made in cataloging lncRNAs and elucidating their functions, the unknown and uncharacterized information is more than the known. A functional framework to effectively profile lncRNAs from the plethora of RNA-seq datasets of cancer remains inadequate, particularly regarding best practices to discover novel and known lncRNAs. Therefore, a comprehensive approach is needed to address these gaps and to harness the biological and pathological potential of lncRNAs in cancers. Here, we present a comprehensive framework that incorporates proven and reliable tools for rigorous quality control, adapter trimming, alignment, post-processing, differential analysis, interaction prediction, and visualization of lncRNAs from RNA-seq data. We employed this framework to examine the dysregulation of lncRNAs derived from human breast tumors. This dataset includes 29 pairs of luminal A subtype tumors and matched normal breast tissues from the same patients. The framework identified 4390 lncRNAs that were dysregulated with log2 fold change (log2fc) thresholds of ≤-1 and ≥+1, with a padj of ≤0.05. The log2FoldChange ranged from -7.75 to 5.76, indicating significant variability in differential expression. LncRNA interaction analysis revealed one of the significantly upregulated lncRNAs ENSG00000256513 (log2fc 5.47 with padj of 3.76E-15) showing base-pairing contact with ENST00000582008 (LINC00667/lncOCMRL1). We propose that the upregulated lncRNA ENSG00000265613 may enhance malignancy by stabilizing the RNA target ENSG00000582008, particularly given its established role in oncogenesis. This interaction appears crucial for regulating stability, translation, or splicing, potentially influencing oncogenic and tumor-suppressive processes. This lncRNA data analysis framework effectively facilitated the identification of critical lncRNA dysregulations and potential oncogenic contacts, revealing the role of ENSG00000265613 in enhancing malignancy through its association with ENSG00000582008 in luminal A breast cancer.