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 proto-oncogene 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 upper respiratory tract is compromised in the early period of COVID-19, but SARS-CoV-2 tropism at the cellular level is not fully defined. Unlike recent single-cell RNA-Seq analyses indicating uniformly low mRNA expression of SARS-CoV-2 entry–related host molecules in all nasal epithelial cells, we show that the protein levels are relatively high and that their localizations are restricted to the apical side of multiciliated epithelial cells. In addition, we provide evidence in patients with COVID-19 that SARS-CoV-2 is massively detected and replicated within the multiciliated cells. We observed these findings during the early stage of COVID-19, when infected ciliated cells were rapidly replaced by differentiating precursor cells. Moreover, our analyses revealed that SARS-CoV-2 cellular tropism was restricted to the nasal ciliated versus oral squamous epithelium. These results imply that targeting ciliated cells of the nasal epithelium during the early stage of COVID-19 could be an ideal strategy to prevent SARS-CoV-2 propagation.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the cause of a present pandemic, infects human lung alveolar type 2 (hAT2) cells. Characterizing pathogenesis is crucial for developing vaccines and therapeutics. However, the lack of models mirroring the cellular physiology and pathology of hAT2 cells limits the study. Here, we develop a feeder-free, long-term, three-dimensional (3D) culture technique for hAT2 cells derived from primary human lung tissue and investigate infection response to SARS-CoV-2. By imaging-based analysis and single-cell transcriptome profiling, we reveal rapid viral replication and the increased expression of interferon-associated genes and proinflammatory genes in infected hAT2 cells, indicating a robust endogenous innate immune response. Further tracing of viral mutations acquired during transmission identifies full infection of individual cells effectively from a single viral entry. Our study provides deep insights into the pathogenesis of SARS-CoV-2 and the application of defined 3D hAT2 cultures as models for respiratory diseases.

Exposing rare but highly malignant tumor cells that migrate from the primary tumor mass into adjacent tissue(s) or circulate in the bloodstream is critical for early detection and effective intervention(s). Here, we report on an aptamer-based strategy directed against epidermal growth factor receptor (EGFR), the most common oncogene in glioblastoma (GBM), to detect these deadly tumor cells. GBMs are characterized by diffuse infiltration into normal brain regions, and the inability to detect GBM cells renders the disease surgically incurable with a median survival of just 14.2 months. To test the sensitivity and specificity of our platform, anti-EGFR RNA aptamers were immobilized on chemically modified glass surfaces. Cells tested included primary human GBM cells expressing high levels of the wild-type EGFR, as well as genetically engineered murine glioma cells overexpressing the most common EGFR mutant (EGFRvIII lacking exons 2–7) in Ink4a/Arf-deficient astrocytes. We found that surfaces functionalized with anti-EGFR aptamers could capture both the human and murine GBM cells with high sensitivity and specificity. Our findings show how novel aptamer substrates could be used to determine whether surgical resection margins are free of tumor cells, or more widely for detecting tumor cells circulating in peripheral blood to improve early detection and/or monitoring residual disease after treatment. Cancer Res; 70(22); 9371–80. ©2010 AACR.

A deep learning model for preoperative chest CT predicted disease-free survival in patients with lung adenocarcinoma. Background Deep learning models have the potential for lung cancer prognostication, but model output as an independent prognostic factor must be validated with clinical risk factors. Purpose To dev...