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Item Enhanced CT-Based Radiomics to Predict Micropapillary Pattern Within Lung Invasive Adenocarcinoma(Frontiers Media, 2021-08-27) Xu, Yunyu; Ji, Wenbin; Hou, Liqiao; Lin, Shuangxiang; Shi, Yangyang; Zhou, Chao; Meng, Yinnan; Wang, Wei; Chen, Xiaofeng; Wang, Meihao; Yang, Haihua; Radiation Oncology, School of MedicineObjective: We aimed to investigate whether enhanced CT-based radiomics can predict micropapillary pattern (MPP) of lung invasive adenocarcinoma (IAC) in the pre-op phase and to develop an individual diagnostic predictive model for MPP in IAC. Methods: 170 patients who underwent complete resection for pathologically confirmed lung IAC were included in our study. Of these 121 were used as a training cohort and the other 49 as a test cohort. Clinical features and enhanced CT images were collected and assessed. Quantitative CT analysis was performed based on feature types including first order, shape, gray-level co-occurrence matrix-based, gray-level size zone matrix-based, gray-level run length matrix-based, gray-level dependence matrix-based, neighboring gray tone difference matrix-based features and transform types including Log, wavelet and local binary pattern. Receiver operating characteristic (ROC) and area under the curve (AUC) were used to value the ability to identify the lung IAC with MPP using these characteristics. Results: Using quantitative CT analysis, one thousand three hundred and seventeen radiomics features were deciphered from R (https://www.r-project.org/). Then these radiomic features were decreased to 14 features after dimension reduction using the least absolute shrinkage and selection operator (LASSO) method in R. After correlation analysis, 5 key features were obtained and used as signatures for predicting MPP within IAC. The individualized prediction model which included age, smoking, family tumor history and radiomics signature had better identification (AUC=0.739) in comparison with the model consisting only of radiomics features (AUC=0.722). DeLong test showed that the difference in AUC between the two models was statistically significant (P<0.01). Compared with the simple radiomics model, the more comprehensive individual prediction model has better prediction performance. Conclusion: The use of radiomics approach is of great value in the diagnosis of tumors by non-invasive means. The individualized prediction model in the study, when incorporated with age, smoking and radiomics signature, had effective predictive performance of lung IAC with MPP lesions. The combination of imaging features and clinical features can provide additional diagnostic value to identify the micropapillary pattern in IAC and can affect clinical diagnosis and treatment.Item Global Transcriptome Analysis of RNA Abundance Regulation by ADAR in Lung Adenocarcinoma(Elsevier, 2018-01) Sharpnack, Michael F.; Chen, Bin; Aran, Dvir; Kosti, Idit; Sharpnack, Douglas D.; Carbone, David P.; Mallick, Parag; Huang, Kun; Medicine, School of MedicineDespite tremendous advances in targeted therapies against lung adenocarcinoma, the majority of patients do not benefit from personalized treatments. A deeper understanding of potential therapeutic targets is crucial to increase the survival of patients. One promising target, ADAR, is amplified in 13% of lung adenocarcinomas and in-vitro studies have demonstrated the potential of its therapeutic inhibition to inhibit tumor growth. ADAR edits millions of adenosines to inosines within the transcriptome, and while previous studies of ADAR in cancer have solely focused on protein-coding edits, >99% of edits occur in non-protein coding regions. Here, we develop a pipeline to discover the regulatory potential of RNA editing sites across the entire transcriptome and apply it to lung adenocarcinoma tumors from The Cancer Genome Atlas. This method predicts that 1413 genes contain regulatory edits, predominantly in non-coding regions. Genes with the largest numbers of regulatory edits are enriched in both apoptotic and innate immune pathways, providing a link between these known functions of ADAR and its role in cancer. We further show that despite a positive association between ADAR RNA expression and apoptotic and immune pathways, ADAR copy number is negatively associated with apoptosis and several immune cell types' signatures.Item Immunogenomic classification of lung squamous cell carcinoma characterizes tumor immune microenvironment and predicts cancer therapy(Elsevier, 2023-03-28) Fu, Denggang; Zhang, Biyu; Zhang, Yinghua; Feng, Jueping; Jiang, Hua; Medicine, School of MedicineItem XPC protects against smoking- and carcinogen-induced lung adenocarcinoma(Oxford University Press, 2019-04-10) Zhou, Huaxin; Salib, Jacob; Sandusky, George E.; Sears, Catherine R.; Medicine, School of MedicineCigarette smoke (CS) contains hundreds of carcinogens and is a potent inducer of oxidative and bulky DNA damage, which when insufficiently repaired leads to activation of DNA damage response and possibly mutations. The DNA repair protein xeroderma pigmentosum group C (XPC) is primed to play an important role in CS-induced DNA damage because of its function in initiating repair of both bulky oxidative DNA damage. We hypothesized that loss of XPC function will increase susceptibility to developing CS- and carcinogen-induced lung cancer through impaired repair of oxidative DNA damage. Mice deficient in XPC (XPC-/-) exposed to chronic CS developed lung tumors whereas their wild-type littermates (XPC+/+) did not. XPC-/- mice treated with the CS-carcinogen urethane developed lung adenocarcinomas representing progressive stages of tumor development, with lung tumor number increased 17-fold compared with XPC+/+ mice. Mice heterozygous for XPC (XPC+/-) demonstrated a gene-dose effect, developing an intermediate number of lung tumors with urethane treatment. Treatment of XPC-/- mice with the carcinogen 3-methylcholanthrene followed by the proliferative agent butylated hydroxytoluene resulted in a 2-fold increase in lung adenocarcinoma development. Finally, tumor number decreased 7-fold in the lungs of XPC-/- mice by concurrent treatment with the antioxidant, N-acetylcysteine. Altogether, this supports a mechanism by which decreased XPC expression promotes lung adenocarcinoma development in response to CS-carcinogen exposure, due in part to impaired oxidative DNA damage repair.