Abstract
BackgroundDeep sequencing techniques provide a remarkable opportunity for comprehensive understanding of tumorigenesis at the molecular level. As omics studies become popular, integrative approaches need to be developed to move from a simple cataloguing of mutations and changes in gene expression to dissecting the molecular nature of carcinogenesis at the systemic level and understanding the complex networks that lead to cancer development.ResultsHere, we describe a high-throughput, multi-dimensional sequencing study of primary lung adenocarcinoma tumors and adjacent normal tissues of six Korean female never-smoker patients. Our data encompass results from exome-seq, RNA-seq, small RNA-seq, and MeDIP-seq. We identified and validated novel genetic aberrations, including 47 somatic mutations and 19 fusion transcripts. One of the fusions involves the c-RET gene, which was recently reported to form fusion genes that may function as drivers of carcinogenesis in lung cancer patients. We also characterized gene expression profiles, which we integrated with genomic aberrations and gene regulations into functional networks. The most prominent gene network module that emerged indicates that disturbances in G2/M transition and mitotic progression are causally linked to tumorigenesis in these patients. Also, results from the analysis strongly suggest that several novel microRNA-target interactions represent key regulatory elements of the gene network.ConclusionsOur study not only provides an overview of the alterations occurring in lung adenocarcinoma at multiple levels from genome to transcriptome and epigenome, but also offers a model for integrative genomics analysis and proposes potential target pathways for the control of lung adenocarcinoma.
Highlights
Recent advances in DNA sequencing technology have revolutionized genomics and biomedical research, especially in the field of cancer research [1]
Multi-omic Data Description To understand the genomic, transcriptomic and epigenomic changes in non-small cell lung cancer (NSCLC), we performed high-throughput sequencing experiments for exome, transcriptome, and methylome on matched normal and tumor samples of 6 female non-smoker patients
The genomic landscape of all NSCLC samples analyzed is visualized as a Circos plot of somatic mutations, transcriptome expression, copy number variations (CNVs), and structural variations_ENREF_6 (Figure 1; see Table S2 in File S8 for summary statistics of the exome data and Figure S2 in File S8 for Circos plots for individual patients) [9]
Summary
Multi-omic Data Description To understand the genomic, transcriptomic and epigenomic changes in NSCLC, we performed high-throughput sequencing experiments for exome, transcriptome, and methylome on matched normal and tumor samples of 6 female non-smoker patients (see Figure S1 in File S8; data summary, experimental procedures are provided in the File S8; detailed sample/patient descriptions are provided in Table S1 in File S8 and File S1). Expanding the search scope beyond DEmiRs to identify other microRNAs of potential functional importance, we found 13 additional microRNAs with at least a two-fold change in expression between normal and tumor samples involved in 53 validated inverse correlations with DEGs. We did not use the predicted targets in this case, in order to avoid the inclusion of false positives. RECK, which is known to be strongly downregulated in multiple tumors and in cell lines transformed by oncogenes [32], is a predicted and inverse correlated target of several microRNAs (miR-96, miR-182, and miR-135b) within our network (Figure 4, Figure S6 in File S8). It is a validated target of miR-30a*, miR30b* and 30C-2*, all of which are downregulated in tumors consistent with upregulation of MYBL2
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