Yang, Ping

Abstract Lung cancer accounts for about 27% of the cancer related deaths in the USA annually. Pathologically, it is a very complex disease broadly classified into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). NSCLCs are further classified into squamous cell carcinoma, large cell carcinoma and adenocarcinoma. Achaete-scute homolog 1 (ASCL1), an important transcription factor essential in the development of neuroendocrine cells (NE) in lungs is shown to be specifically expressed in lung NE cancers and 10-20% of adenocarcinomas (AD) with NE differentiation (NED), thus suggesting a role in the pathogenesis of these tumors. Our previous study showed that ASCL1 is a regulator of the RET oncogene in AD with NED. RET is a receptor tyrosine kinase with two isoforms in humans: RET9 (short) and RET51 (long). We performed survival analysis to study implications of RET isoforms in ASCL1+ tumors and found that elevated expression of the long RET mRNA was associated with poor survival. Subsequent in vitro experiments demonstrated that treatment with EGF robustly induced phosphorylation of RET in HCC1833 and H1755 cell lines which have high endogenous levels of ASCL1 and RET but not in VMRC-LCD cell line which has high level of ASCL1 but low level of RET. EGF induced phosphorylation of RET was diminished by gefitinib and by EGFR siRNA. Immunoprecipitation results indicated direct binding between EGFR and RET in presence of EGF. Furthermore, a high throughput drug screening found 8 EGFR inhibitors that were 10 - 250 fold more cytotoxic in ASCL1+ compared with ASCL1- AD cells. These results implicate EGFR as a key regulator of RET activation in ASCL1+ AD and suggest that EGFR inhibitors may be therapeutic for this population of patients. Citation Format: Kaustubh N. Bhinge, Yang Lin, Hamed Rahi, Marie Christine Aubry, Aaron Mansfield, Irina Kovtun, Stephen Murphy, Ping Yang, Dennis Wigle, Joanne (Eunhee) Yi, Aqsa Nasir, Simone Terra, Julian Molina, George Vasmatzis, Farhad Kosari. EGFR-mediated activation of RET in ASCL1+ lung adenocarcinoma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1129.

Abstract ASCL1 is an important regulatory transcription factor in pulmonary neuroendocrine cell development, but its value as a biomarker of neuroendocrine differentiation in lung adenocarcinoma (AD) and as a potential prognostic biomarker remains unclear. We examined ASCL1expression in lung cancer samples of varied histologic subtype, clinical outcome, and smoking status and compared to expression of traditional neuroendocrine markers. ASCL1 mRNA expression was found almost exclusively in smokers with AD, in contrast to non-smokers. ASCL1 protein expression by immunohistochemistry (IHC) correlated best with synaptophysin compared to chromogranin and CD56/NCAM. Analysis of a compendium of 367 microarray-based gene expression profiles in stage I lung adenocarcinomas identified significantly higher expression levels of the RET oncogene in ASCL1 positive tumors (ASCL1+) compared to ASCL1- tumors (q-value < 10 - 9). High levels of RET expression in ASCL1+ but not in ASCL1- tumors was associated with significantly shorter overall survival in stage 1 (p = 0.007) and in all AD (p = 0.037). RET protein expression by IHC had an association with overall survival in the context of ASCL1 expression. In silico gene set analysis and in vitro experiments by ASCL1 shRNA in AD cells with high endogenous expression of ASCL1 and RET implicated ASCL1 as a potential upstream regulator of the RET oncogene. Also, silencing ASCL1 in AD cells markedly reduced cell growth and motility. These results suggest that ASCL1 and RET expression define a clinically relevant subgroup of approximately 10% of AD characterized by neuroendocrine differentiation. Citation Format: Farhad Kosari, Cristiane M. Ida, Marie Christine Aubry, Lin Yang, Irina V. Kovtun, Janet L. Schaefer Klein, Sandra C. Tomaszek, Stephen J. Murphy, Ping Yang, Dennis Wigle, George Vasmatzis. ASCL1 and RET expression define a clinically relevant subgroup of lung adenocarcinoma characterized by neuroendocrine differentiation. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5251. doi:10.1158/1538-7445.AM2014-5251

Abstract Lung adenocarcinoma is the most common type of primary lung cancer. Previous studies have shown that gene expression signatures may predict clinical outcome. In this study, we used a systems biology approach, weighted gene co-expression network analysis (WGCNA), to identify survival related networks and gene signatures. We first analyzed whole genome gene expression profiles in 82 lung adenocarcinoma tumor tissues from never smokers (smoked <100 cigarettes lifetime) and found a significant correlation of an expression module with tumor grade of differentiation (r=0.38, p=4×10−4) and overall survival (OS, p =0.027, HR, 1.71; 95% CI, 1.06-2.74) after adjusting for potential confounders (age and tumor grade). When this module signature was incorporated and compared to the conventional model consisting of clinical variables only, the survival prediction accuracy was increased from 0.70 to 0.75. Gene Ontology (GO) enrichment analysis indicated this module was significantly enriched in biological process GO term “cell cycle” (p = 2.1×10−53). To explore the effect of this network module at germline level, we performed the WGCNA on normal lung tissues derived from 78 of the 82 patients and observed significant association of an expression module with OS (adjusted p=3×10−4, HR=1.98; 95% CI, 1.36-2.87). Interestingly, this module was also significantly enriched in cell cycle-related genes (p=4.1×10−41). To further validate this result, we analyzed an independent microarray gene expression dataset including 442 lung adenocarcinoma patients from NCI Director's Challenge Consortium. We found the same association: the cell cycle-enriched module was correlated with tumor grade of cell differentiation (r=0.55, p-value=5×10−37) and OS (adjusted p=7.4×10−3; HR, 1.20; 95% CI, 1.05-1.37). We further identified 30 genes in the OS-related module that overlapped between the discovery and validation data sets. Furthermore, all these 30 genes were found to be up-regulated in adenocarcinoma compared to adjacent normal lung tissues in the discovery data set. Of the 30 genes, three key genes, UBE2C, TPX2 and MELK, were identified with highest connectivity in cell cycle-enriched module; their expression levels were significantly associated with OS in both discovery and validation sets. UBE2C and TPX2 have been reported as gene signatures for human lung cancer prognosis in vitro lung carcinogenesis system; MELK was identified as a key regulator of the proliferation of malignant brain tumors and malignant grade in human astrocytomas, and was also associated with breast cancer prognosis. Our results suggest that genes involved in cell-cycle are likely related with tumor aggressiveness and therefore can predict survival in lung adenocarcinoma. Further studies are needed to validate the key genes that could improve survival prediction and provide potential new targets to intervene progression of lung adenocarcinoma. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5060. doi:10.1158/1538-7445.AM2011-5060

Abstract DNA microarray has been widely used in cancer research to better predict clinical outcomes and potentially improve patient management. The new approach provides accurate tumor classification and outcome predictions, such as tumor stage, metastatic status, and patient survival, and offers some hope for individualized medicine. However, growing evidence suggests that gene-based prediction is not stable and little is known about the prediction power of gene expression profiles compared with well-known clinical and pathologic predictors. This review summarized up-to-date publications in microarray-based lung cancer clinical outcome prediction and conducted secondary analyses for those with sufficient sample sizes and associated clinical information. Among the most commonly used analytic approaches, unsupervised clustering mainly recaptures tumor histology and provides variable degrees of prediction for tumor stage, lymph node status, or survival. Overall, most studies lack an independent validation. Supervised learning and testing generally offer a better prediction. Noted is that when conventional predictors of age, gender, stage, cell type, and tumor grade are considered collectively, the predictive advantage of the gene expression profiles diminishes. We conclude that outcome prediction from gene expression signatures selected by current analytic approaches can be mostly explained by well-known conventional predictors, particularly histologic subtype and grade of differentiation. A strategy for establishing independent or more accurate signatures is commented. (Cancer Epidemiol Biomarkers Prev 2006;15(11):2063–8)

Purpose: We conducted this study because the duration of excess lung cancer risk among former smokers has been inconsistently reported, doubt has been raised regarding the population impact of smoking cessation, and differential risk reduction by histologic cell type after smoking cessation needs to be confirmed. Methods: The Iowa Women’s Health Study is a prospective cohort study of 41,836 Iowa women aged 55 to 69 years. In 1986, mailed questionnaires were used to collect detailed smoking history. Age-adjusted lung cancer incidence through 1999 was analyzed according to years of smoking abstinence. Relative risks were estimated using Cox regression analysis. Results: There were 37,078 women in the analytic cohort. Compared with the never smokers, former smokers had an elevated lung cancer risk (relative risk, 6.6; 95% confidence interval, 5.0 to 8.7) up to 30 years after smoking cessation for all former smokers. However, a beneficial effect of smoking cessation was observed among recent and distant former smokers. The risk of adenocarcinoma remained elevated up to 30 years for both former heavier and former lighter smokers. Conclusion: The risk for lung cancer is increased for both current and former smokers compared with never smokers and declines for former smokers with increasing duration of abstinence. The decline in excess lung cancer risk among former smokers is prolonged compared with other studies, especially for adenocarcinoma and for heavy smokers, suggesting that more emphasis should be placed on smoking prevention and lung cancer chemoprevention.