Clinical and Molecular Characteristics of NF1-Mutant Lung Cancer.

PURPOSE: NF1 is a tumor suppressor that negatively regulates Ras signaling. NF1 mutations occur in lung cancer, but their clinical significance is unknown. We evaluated clinical and molecular characteristics of NF1 mutant lung cancers with comparison to tumors with KRAS mutations. EXPERIMENTAL DESIGN: Between July 2013 and October 2014, 591 non-small cell lung cancer (NSCLC) tumors underwent targeted next-generation sequencing in a 275 gene panel that evaluates gene mutations and genomic rearrangements. NF1 and KRAS cohorts were identified, with subsequent clinical and genomic analysis. RESULTS: Among 591 patients, 60 had NF1 mutations (10%) and 141 (24%) had KRAS mutations. 15 NF1 mutations (25%) occurred with other oncogenic mutations [BRAF (2); ERBB2 (2); KRAS (9); HRAS (1); NRAS (1)]. There were 72 unique NF1 variants. NF1 tumor pathology was diverse, including both adenocarcinoma (36, 60%) and squamous cell carcinoma (10, 17%). In contrast, KRAS mutations occurred predominantly in adenocarcinoma (136, 96%). Both mutations were common in former/current smokers. Among NF1 tumors without concurrent oncogenic alterations, TP53 mutations/2-copy deletions occurred more often (33, 65%) than with KRAS mutation (46, 35%; P < 0.001). No difference between cohorts was seen with other tumor suppressors. CONCLUSIONS: NF1 mutations define a unique population of NSCLC. NF1 and KRAS mutations present in similar patient populations, but NF1 mutations occur more often with other oncogenic alterations and TP53 mutations. Therapeutic strategies targeting KRAS activation, including inhibitors of MAP kinase signaling, may warrant investigation in NF1 mutant tumors. Tumor-suppressor inactivation patterns may help further define novel treatment strategies. Clin Cancer Res; 22(13); 3148-56. ©2016 AACR.

OncDRS: An integrative clinical and genomic data platform for enabling translational research and precision medicine.

We live in the genomic era of medicine, where a patient's genomic/molecular data is becoming increasingly important for disease diagnosis, identification of targeted therapy, and risk assessment for adverse reactions. However, decoding the genomic test results and integrating it with clinical data for retrospective studies and cohort identification for prospective clinical trials is still a challenging task. In order to overcome these barriers, we developed an overarching enterprise informatics framework for translational research and personalized medicine called Synergistic Patient and Research Knowledge Systems (SPARKS) and a suite of tools called Oncology Data Retrieval Systems (OncDRS). OncDRS enables seamless data integration, secure and self-navigated query and extraction of clinical and genomic data from heterogeneous sources. Within a year of release, the system has facilitated more than 1500 research queries and has delivered data for more than 50 research studies.

Ab initio RNA folding by discrete molecular dynamics: from structure prediction to folding mechanisms.

RNA molecules with novel functions have revived interest in the accurate prediction of RNA three-dimensional (3D) structure and folding dynamics. However, existing methods are inefficient in automated 3D structure prediction. Here, we report a robust computational approach for rapid folding of RNA molecules. We develop a simplified RNA model for discrete molecular dynamics (DMD) simulations, incorporating base-pairing and base-stacking interactions. We demonstrate correct folding of 150 structurally diverse RNA sequences. The majority of DMD-predicted 3D structures have <4 A deviations from experimental structures. The secondary structures corresponding to the predicted 3D structures consist of 94% native base-pair interactions. Folding thermodynamics and kinetics of tRNA(Phe), pseudoknots, and mRNA fragments in DMD simulations are in agreement with previous experimental findings. Folding of RNA molecules features transient, non-native conformations, suggesting non-hierarchical RNA folding. Our method allows rapid conformational sampling of RNA folding, with computational time increasing linearly with RNA length. We envision this approach as a promising tool for RNA structural and functional analyses.

Fast complementation of split fluorescent protein triggered by DNA hybridization.

Fluorescent proteins have proven to be excellent reporters and biochemical sensors with a wide range of applications. In a split form, they are not fluorescent, but their fluorescence can be restored by supplementary protein-protein or protein-nucleic acid interactions that reassemble the split polypeptides. However, in prior studies, it took hours to restore the fluorescence of a split fluorescent protein because the formation of the protein chromophore slowly occurred de novo concurrently with reassembly. Here we provide evidence that a fluorogenic chromophore can self-catalytically form within an isolated N-terminal fragment of the enhanced green fluorescent protein (EGFP). We show that restoration of the split protein fluorescence can be driven by nucleic acid complementary interactions. In our assay, fluorescence development is fast (within a few minutes) when complementary oligonucleotide-linked fragments of the split EGFP are combined. The ability of our EGFP system to respond quickly to DNA hybridization should be useful for detecting the kinetics of many other types of pairwise interactions both in vitro and in living cells.