All cancers harbor molecular alterations in their genomes. The transcriptional consequences of these somatic mutations have not yet been comprehensively explored in lung cancer. Here we present the first large scale RNA sequencing study of lung adenocarcinoma, demonstrating its power to identify somatic point mutations as well as transcriptional variants such as gene fusions, alternative splicing events, and expression outliers. Our results reveal the genetic basis of 200 lung adenocarcinomas in Koreans including deep characterization of 87 surgical specimens by transcriptome sequencing. We identified driver somatic mutations in cancer genes including EGFR, KRAS, NRAS, BRAF, PIK3CA, MET, and CTNNB1. Candidates for novel driver mutations were also identified in genes newly implicated in lung adenocarcinoma such as LMTK2, ARID1A, NOTCH2, and SMARCA4. We found 45 fusion genes, eight of which were chimeric tyrosine kinases involving ALK, RET, ROS1, FGFR2, AXL, and PDGFRA. Among 17 recurrent alternative splicing events, we identified exon 14 skipping in the protooncogene MET as highly likely to be a cancer driver. The number of somatic mutations and expression outliers varied markedly between individual cancers and was strongly correlated with smoking history of patients. We identified genomic blocks within which gene expression levels were consistently increased or decreased that could be explained by copy number alterations in samples. We also found an association between lymph node metastasis and somatic mutations in TP53. These findings broaden our understanding of lung adenocarcinoma and may also lead to new diagnostic and therapeutic approaches.

The identification of the molecular events that drive cancer transformation is essential to the development of targeted agents that improve the clinical outcome of lung cancer. Many studies have reported genomic driver mutations in non-small-cell lung cancers (NSCLCs) over the past decade; however, the molecular pathogenesis of >40% of NSCLCs is still unknown. To identify new molecular targets in NSCLCs, we performed the combined analysis of massively parallel whole-genome and transcriptome sequencing for cancer and paired normal tissue of a 33-yr-old lung adenocarcinoma patient, who is a neversmoker and has no familial cancer history. The cancer showed no known driver mutation in EGFR or KRAS and no EML4-ALK fusion. Here we report a novel fusion gene between KIF5B and the RET proto-oncogene caused by a pericentric inversion of 10p11.22-q11.21. This fusion gene overexpresses chimeric RET receptor tyrosine kinase, which could spontaneously induce cellular transformation. We identified the KIF5B-RET fusion in two more cases out of 20 primary lung adenocarcinomas in the replication study. Our data demonstrate that a subset of NSCLCs could be caused by a fusion of KIF5B and RET, and suggest the chimeric oncogene as a promising molecular target for the personalized diagnosis and treatment of lung cancer.

Massively parallel sequencing technologies have identified a broad spectrum of human genome diversity. Here we deep sequenced and correlated 18 genomes and 17 transcriptomes of unrelated Korean individuals. This has allowed us to construct a genome-wide map of common and rare variants and also identify variants formed during DNA-RNA transcription. We identified 9.56 million genomic variants, 23.2% of which appear to be previously unidentified. From transcriptome sequencing, we discovered 4,414 transcripts not previously annotated. Finally, we revealed 1,809 sites of transcriptional base modification, where the transcriptional landscape is different from the corresponding genomic sequences, and 580 sites of allele-specific expression. Our findings suggest that a considerable number of unexplored genomic variants still remain to be identified in the human genome, and that the integrated analysis of genome and transcriptome sequencing is powerful for understanding the diversity and functional aspects of human genomic variants.

Direct imaging of nanoparticle solutions by liquid phase transmission electron microscopy has enabled unique in situ studies of nanoparticle motion and growth. In the present work, we report on real-time formation of two-dimensional nanoparticle arrays in the very low diffusive limit, where nanoparticles are mainly driven by capillary forces and solvent fluctuations. We find that superlattice formation appears to be segregated into multiple regimes. Initially, the solvent front drags the nanoparticles, condensing them into an amorphous agglomerate. Subsequently, the nanoparticle crystallization into an array is driven by local fluctuations. Following the crystallization event, superlattice growth can also occur via the addition of individual nanoparticles drawn from outlying regions by different solvent fronts. The dragging mechanism is consistent with simulations based on a coarse-grained lattice gas model at the same limit.