Deep Sequence Analysis of Non-Small Cell Lung Cancer: Integrated Analysis of Gene Expression, Alternative Splicing, and Single Nucleotide Variations in Lung Adenocarcinomas with and without Oncogenic KRAS Mutations - PubMed (original) (raw)

doi: 10.3389/fonc.2012.00012. eCollection 2012.

David Rossell, Brian M Necela, Yan W Asmann, Asha Nair, Saurabh Baheti, Jennifer M Kachergus, Curtis S Younkin, Tiffany Baker, Jennifer M Carr, Xiaojia Tang, Michael P Walsh, High-Seng Chai, Zhifu Sun, Steven N Hart, Alexey A Leontovich, Asif Hossain, Jean-Pierre Kocher, Edith A Perez, David N Reisman, Alan P Fields, E Aubrey Thompson

Affiliations

Deep Sequence Analysis of Non-Small Cell Lung Cancer: Integrated Analysis of Gene Expression, Alternative Splicing, and Single Nucleotide Variations in Lung Adenocarcinomas with and without Oncogenic KRAS Mutations

Krishna R Kalari et al. Front Oncol. 2012.

Abstract

KRAS mutations are highly prevalent in non-small cell lung cancer (NSCLC), and tumors harboring these mutations tend to be aggressive and resistant to chemotherapy. We used next-generation sequencing technology to identify pathways that are specifically altered in lung tumors harboring a KRAS mutation. Paired-end RNA-sequencing of 15 primary lung adenocarcinoma tumors (8 harboring mutant KRAS and 7 with wild-type KRAS) were performed. Sequences were mapped to the human genome, and genomic features, including differentially expressed genes, alternate splicing isoforms and single nucleotide variants, were determined for tumors with and without KRAS mutation using a variety of computational methods. Network analysis was carried out on genes showing differential expression (374 genes), alternate splicing (259 genes), and SNV-related changes (65 genes) in NSCLC tumors harboring a KRAS mutation. Genes exhibiting two or more connections from the lung adenocarcinoma network were used to carry out integrated pathway analysis. The most significant signaling pathways identified through this analysis were the NFκB, ERK1/2, and AKT pathways. A 27 gene mutant KRAS-specific sub network was extracted based on gene-gene connections from the integrated network, and interrogated for druggable targets. Our results confirm previous evidence that mutant KRAS tumors exhibit activated NFκB, ERK1/2, and AKT pathways and may be preferentially sensitive to target therapeutics toward these pathways. In addition, our analysis indicates novel, previously unappreciated links between mutant KRAS and the TNFR and PPARγ signaling pathways, suggesting that targeted PPARγ antagonists and TNFR inhibitors may be useful therapeutic strategies for treatment of mutant KRAS lung tumors. Our study is the first to integrate genomic features from RNA-Seq data from NSCLC and to define a first draft genomic landscape model that is unique to tumors with oncogenic KRAS mutations.

Keywords: KRAS mutation; NSCLC; RNA-Seq; bioinformatics; data integration and computational methods; network analysis; transcriptome sequencing.

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Figures

Figure 1

Figure 1

Our data analysis approach. High-level representation of our approach to analyze RNA-Seq data in human lung adenocarcinomas with and without KRAS mutation.

Figure 2

Figure 2

High-level approach of CASPER – a splicing analysis R package. Flowchart of methods to quantify alternate splice forms from RNA-Seq data.

Figure 3

Figure 3

High-level approach to identify SNVs. Flowchart of methods to process RNA-Seq data to obtain SNVs using a variety of tools, databases, and next-generation sequencing normal sample datasets.

Figure 4

Figure 4

Results from differential gene expression analysis. (A) Top six significantly differentially expressed genes between KRAS-mutant genotype (GT) and KRAS-wild-type genotype (GG). (B) Hierarchical clustering of 374 genes that are differentially expressed with at least twofold-change and _p_-value <0.05.

Figure 5

Figure 5

Network analysis. (A–D) Top networks identified with IPA software for the 374 genes that are differentially expressed between KRAS-mutant and wild-type lung adenocarcinoma samples. The pink or red color nodes in networks indicate a gene that is up regulated in KRAS-mutant compared to the KRAS-wild-type, green color indicates the genes that are down regulated in KRAS-mutant samples compared to the KRAS-wild-type samples.

Figure 6

Figure 6

Output of CASPER from splicing analysis. (A) CASPER output for alternate splice forms in KRAS-mutant sample. The data indicates that NM_002628 transcript is highly abundant compared to NM_053024 transcript of PFN2 gene. (B) Observed reads for PFN2 gene. Black lines in upper section of the plot indicates long reads and gray lines indicate short reads typically spanning a single exon. The gray line on bottom half of plot indicates coverage at each position. (C) CASPER output for KRAS WT sample. NM_053024 transcript is predominantly expressed compared to other transcript. (D) Is similar to (B) but it corresponds to KRAS WT sample in (C).

Figure 7

Figure 7

Genomic view diagram. Chromosomal view of all the genes obtained from multi-feature analysis of lung adenocarcinomas with and without KRAS mutation. Chromosomes 1, 3, 6, and 11 consists of abundant gene clusters associated with KRAS mutation. Arrow in the diagram represents a gene obtained from genomic feature analysis. Arrows identify the loci of genes obtained from genomic feature analysis. Larger arrows are shown when the genes are far apart, but when the gene locations are adjacent they are represented as smaller arrows.

Figure 8

Figure 8

The qPCR validation and SNV validation results. (A) Validation of CASPER estimations of relative abundances for PFN2 gene in two mutant and wild-type samples using qPCR (B) Visualization of KRAS-mutant SNV using IGV Browser. Coverage file and bam files are shown in the top part of the IGV Browser output. The bottom part of the picture consists of Refseq gene with nucleotides. Nucleotide position of chr12: 133384864 is displayed in dotted columns of the figure, it shows that the reference allele at that particular position is (C) and alternate allele present at that position is (A), so the SNV at that position is (C/A) change. (C) Sanger sequencing data confirming the variation.

Figure 9

Figure 9

Lung adenocarcinoma interaction network. In the diagram white squares are linker genes. Dark pink are differentially expressed genes, light blue are splicing variants, purple are genes that are differentially expressed and alternately spliced. Green are genes corresponding to SNVs. Blue dotted lines means indirect connections, blue solid lines indicate direct evidence of connection between the genes.

Figure 10

Figure 10

Most significant canonical pathway from this study. Molecular mechanisms of cancer is the most significant known pathway obtained from multi-feature analysis of lung adenocarcinoma network. In the diagram green symbols represent linker genes and red or pink colors represent list of genes from lung adenocarcinoma network.

Figure 11

Figure 11

KRAS sub network. The network connections are obtained from our multi-feature gene list and Ingenuity knowledge base (IKB). Direct and indirect connections to KRAS gene are obtained from multi-feature list and only direct connections are obtained from IKB. The bar chart close to the gene indicates the log2 expression of the gene for each sample from RNA-sequencing data. Rx connection to a gene indicates FDA approved or clinical trial drugs.

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