Kovtun, Irina V.

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 Gleason score 7 (GS7) prostate cancer [tumors with both Gleason patterns 3 (GP3) and 4 (GP4)] portends a significantly more aggressive tumor than Gleason score 6 (GS6). It is, therefore, critical to understand the molecular relationship of adjacent GP3 and GP4 tumor cell populations and relate molecular abnormalities to disease progression. To decipher molecular relatedness, we used laser capture microdissection (LCM) and whole-genome amplification (WGA) to separately collect and amplify DNA from adjacent GP3 and GP4 cell populations from 14 cases of GS7 prostate cancer. We then carried out massively parallel mate-pair next generation sequencing (NGS) to examine the landscape of large chromosomal alterations. We identified four to 115 DNA breakpoints in GP3 and 17 to 480 in GP4. Our findings indicate that while GP3 and GP4 from the same tumor each possess unique breakpoints, they also share identical ones, indicating a common origin. Approximately 300 chromosomal breakpoints were localized to the regions affected in at least two tumors, whereas more than 3,000 were unique within the set of 14 tumors. TMPRSS2–ERG was the most recurrent rearrangement present in eight cases, in both GP3 and GP4. PTEN rearrangements were found in five of eight TMPRSS2–ERG fusion–positive cases in both GP3 and GP4. Hierarchical clustering analysis revealed that GP3 has greater breakpoint similarity to its partner GP4 compared with GP3 from different patients. We show evidence that LCM, WGA, and NGS of adjacent tumor regions provide an important tool in deciphering lineage relationships and discovering chromosomal alterations associated with tumor progression. Cancer Res; 73(11); 3275–84. ©2013 AACR.

Abstract Peripheral T-cell lymphomas (PTCLs) are aggressive malignancies of mature T lymphocytes with 5-year overall survival rates of only ∼ 35%. Improvement in outcomes has been stymied by poor understanding of the genetics and molecular pathogenesis of PTCL, with a resulting paucity of molecular targets for therapy. We developed bioinformatic tools to identify chromosomal rearrangements using genome-wide, next-generation sequencing analysis of mate-pair DNA libraries and applied these tools to 16 PTCL patient tissue samples and 6 PTCL cell lines. Thirteen recurrent abnormalities were identified, of which 5 involved p53-related genes (TP53, TP63, CDKN2A, WWOX, and ANKRD11). Among these abnormalities were novel TP63 rearrangements encoding fusion proteins homologous to ΔNp63, a dominant-negative p63 isoform that inhibits the p53 pathway. TP63 rearrangements were seen in 11 (5.8%) of 190 PTCLs and were associated with inferior overall survival; they also were detected in 2 (1.2%) of 164 diffuse large B-cell lymphomas. As TP53 mutations are rare in PTCL compared with other malignancies, our findings suggest that a constellation of alternate genetic abnormalities may contribute to disruption of p53-associated tumor suppressor function in PTCL.

Purpose In men who are at high-risk of prostate cancer, progression and death from cancer after radical retropubic prostatectomy (RRP), limited prognostic information is provided by established prognostic features. The objective of this study was to develop a model predictive of outcome in this group of patients. Methods Candidate genes were identified from microarray expression data from 102 laser capture microdissected prostate tissue samples. Candidates were overexpressed in tumor compared with normal prostate and more frequently in Gleason patterns 4 and 5 than in 3. A case control study of 157 high-risk patients, matched on Gleason score and stage with systemic progression or death of prostate cancer as the end point, was used to evaluate the expression of candidate genes and build a multivariate model. Tumor was collected from the highest Gleason score in paraffin-embedded blocks and the gene expression was quantified by real-time reverse transcription polymerase chain reaction. Validation of the final model was performed on a separate case-control study of 57 high-risk patients who underwent RRP. Results A model incorporating gene expression of topoisomerase-2a, cadherin-10, the fusion status based on ERG, ETV1, and ETV4 expression, and the aneuploidy status resulted in a 0.81 area under the curve (AUC) in receiver operating characteristic statistical analysis for the identification of men with systemic progression and death from high grade prostate cancer. The AUC was 0.79 in the independent validation study. Conclusion The model can identify men with high-risk prostate cancer who may benefit from more intensive postoperative follow-up and adjuvant therapies.

There has been a longstanding debate regarding the role of proteolysis in Huntington's disease. The toxic peptide theory posits that N-terminal cleavage fragments of mutant Huntington's disease protein [mutant huntingtin (mhtt)] enter the nucleus to cause transcriptional dysfunction. However, recent data suggest a second model in which proteolysis of full-length mhtt is inhibited. Importantly, the two competing theories differ with respect to subcellular distribution of mhtt at initiation of toxicity: nuclear if cleaved and cytoplasmic in the absence of cleavage. Using quantitative single-cell analysis and time-lapse imaging, we show here that transcriptional dysfunction is “downstream” of cytoplasmic dysfunction. Primary and reversible toxic events involve destabilization of microtubules mediated by full-length mhtt before cleavage. Restoration of microtubule structure by taxol inhibits nuclear entry and increases cell survival.