A High-Dimensional, Deep-Sequencing Study of Lung Adenocarcinoma in Female Never-Smokers

<div><h3>Background</h3><p>Deep 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.</p> <h3>Results</h3><p>Here, 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 <em>c-RET</em> 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.</p> <h3>Conclusions</h3><p>Our 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.</p> </div

Circos plot of somatic mutations, copy number variations, transcriptome expression, and structural variations.

<p>From inside to out, structural variations (purple and orange), copy number variations (gain in dark red, loss in dark blue, mRNA expression (up in gold, down in olive), differentially expressed microRNAs (up in red, down in green), DNA methylation with sky-blue background (up in dark orange, down in chartreuse), somatic mutations with a gene symbols, and chromosomal cytobands.</p

Differential expression of microRNAs.

<p>Fold change versus expression level is shown in the MA-plot of DEmiRs and anti-correlated microRNAs. MicroRNAs from the same genomic locus are shown with the same color and symbol (e.g., 96, 182, 183). MicroRNAs inversely correlated with DEGs are indicated with a black circle. Fold changes in log₂ (tumor/normal) and expression magnitude in ½log₂ (tumor × normal) are the average values over six patients. Inset figures show subsets of microRNA-centric relationships with targets potentially involved in carcinogenesis. Relevant microRNAs are indicated by background orange and blue ovals within the plot. Only the validated targets are shown for simplicity. Changes in expression levels are indicated via node color.</p

<i>MARK4-ERCC2</i> fusion transcript.

<p>(a) Allignment of sequence reads of fusion transcripts. The extent of the assembled fusion transcript appears at the top and reads are shows below it. The vertical line indicates the fusion point. The sequence to the left matches the 3′ end of exon 7 of <i>MARK4</i>, and the sequence to the right matches the 5′ end of exon 18 of <i>ERCC2</i>. (b) cDNA samples taken from tumor (T) and adjacent normal (N) tissue of patient 3 were used to confirm the presence of the <i>MARK4-ERCC2</i> fusion transcript by RT-PCR only in the tumor sample. ACTB was used as the internal control. (c) Schematic diagram of the predicted fusion protein along with domains having a defined function. The fusion protein is predicted to contain a part of the <i>MARK4</i> kinase domain and most of the C-terminal helicase domain of <i>ERCC2</i>. (d) Array-CGH profiles are shown for the <i>MARK4-ERCC2</i> intrachromosomal fusion. Note that the copy number variation is seen only in the tumor tissue but in not normal tissue. Vertical lines represent fusion points.</p

NSCLC pathway modeling for female never-smokers.

<p>The pathway information was obtained from an Ingenuity Pathway Analysis (IPA) using the 66 network module genes as an input list. The resulting genes were grouped into five functional categories as suggested by IPA. Validated and predicted microRNA-target relations are shown in solid and dotted lines, respectively. Changes in expression levels are indicated via node color (red for up-regulation and blue for down-regulation). For <i>c-RET</i> and <i>PTK2</i>, the+symbol was used to indicate that they are involved in gene fusion event.</p