Vasmatzis, George

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.

Abstract Tumor-associated hypoxia facilitates malignant progression, metastasis and poor prognosis in prostate cancer (CaP); however, effects of oxygen tension (pO2) in CaP are just beginning to be investigated. To establish mechanisms whereby hypoxia enhances malignant properties and survival of CaP and to identify pO2-regulated tumor-associated macromolecules, we propagated CaP cell lines LnCaP, VCaP and DU145 in hypoxia (pO2=2 kPa) and compared them with normoxically grown cells (pO2=20 kPa); hypoxic cells proliferated faster and secreted more vascular endothelial growth factor (p<0.05). Transcriptome studies revealed different gene expression in cells grown in hypoxia relative to those in normoxia. Interestingly, in hypoxic cells transcripts associated with cancer and urologic disease were overexpressed in comparison to normoxic cells (p<0.001) suggesting an association of low pO2 and aggressive features of CaP. Further, we analyzed the transcriptome in primary CaP cells isolated by laser-capture microdissection (LCM) and whole CaP tissue. We compared the data to those from CaP cells cultured at pO2=20 kPa or pO2=2 kPa. Notably, hypoxia increased transcript levels for pyruvate dehydrogenase kinase isozyme 1, nuclear prelamin A recognition factor, glucose phosphate isomerase, and glyceraldehyde-3-phosphate dehydrogenase in all three cell lines (p<0.05) to levels comparable to those found in primary bulk tissue and LCM isolated cells (p<0.005). This finding suggests that gene expression in hypoxically cultured cells is more akin to that in tumor cells in situ than are cells grown normoxically. By 2D-gel electrophoresis, we found that change in pO2 affected the proteome mostly quantitatively (i.e., by change in spot intensity). Our results suggest that hypoxia affects transcriptome and proteome in CaP cells. In addition, we screened 20 patient sera and 20 healthy control sera for spontaneous antibodies cross-reactive with VCaP cells and found that the sera reacted with numerous proteins, some previously reported to elicit an immune response in CaP patients (e.g., nucleoporin 62 and transitional endoplasmic reticulum ATPase). By this method we detected numerous novel autoantigens (under validation). Currently we are clarifying the pO2 effects on the relationship of transcriptome, proteome and tumor-associated antigens in CaP cells. Support: DOD PC094680 (CRG), Minnesota Partnership for Biotechnology and Medical Genomics, Mayo Clinic Prostate SPORE 5P50CA091956 (FK); Mrs. Adelyn L. Luther, Singer Island, Florida and Mayo Clinic Cancer Center (SV-P). 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 LB-308. doi:10.1158/1538-7445.AM2011-LB-308

Abstract Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr LB-186.

Abstract The objective of this study was to assess the relationship of the tumor protein levels of TOP2A and MIB-1 and ERG status with cancer-specific outcomes in men with high-risk prostate cancer treated by radical prostatectomy (RP). A 150-pair case-control study was designed from RP patients who developed systemic progression (SP) within 6 years of RP (cases) and men who were free of disease at least 8 years after RP (controls). The cases and controls were matched on conventional prognostic clinical parameters. TOP2A and MIB-1 levels were assessed by immunohistochemical methods, and ERG status was assessed by quantitative reverse transcription-PCR. The prognostic abilities of TOP2A and MIB-1 were significantly better in ERG(−) patients, and TOP2A was superior to MIB-1. In receiver operating characteristic analysis, the TOP2A and MIB-1 scores exhibited AUCs of 0.81 and 0.78 for ERG(−) patients, versus 0.67 and 0.68 for ERG(+) patients, respectively. Clinical parameters attained an AUC of 0.65 in ERG(−) patients and 0.54 in ERG(+) patients. When both markers were incorporated into a model for ERG(−) patients, the AUC increased to 0.83, with TOP2A showing a stronger association with SP than MIB-1. The time to SP was significantly associated with TOP2A; higher 5-year SP rates were observed in patients with higher TOP2A protein levels. In addition, although patient numbers are small, the response to adjuvant androgen deprivation therapy is associated with ERG status, showing more significant treatment effect in ERG(+) patients. Cancer Res; 70(22); 8994–9002. ©2010 AACR.

Abstract The genetics of peripheral T-cell lymphomas are poorly understood. The most well-characterized abnormalities are translocations involving ALK, occurring in approximately half of anaplastic large cell lymphomas (ALCLs). To gain insight into the genetics of ALCLs lacking ALK translocations, we combined mate-pair DNA library construction, massively parallel (“Next Generation”) sequencing, and a novel bioinformatic algorithm. We identified a balanced translocation disrupting the DUSP22 phosphatase gene on 6p25.3 and adjoining the FRA7H fragile site on 7q32.3 in a systemic ALK-negative ALCL. Using fluorescence in situ hybridization, we demonstrated that the t(6;7)(p25.3;q32.3) was recurrent in ALK-negative ALCLs. Furthermore, t(6;7)(p25.3;q32.3) was associated with down-regulation of DUSP22 and up-regulation of MIR29 microRNAs on 7q32.3. These findings represent the first recurrent translocation reported in ALK-negative ALCL and highlight the utility of massively parallel genomic sequencing to discover novel translocations in lymphoma and other cancers.

Abstract ETS variant 1 (ETV1), also known as ETS-related protein 81, is overexpressed in prostate tumors, but whether and how this transcription factor affects tumorigenesis has remained elusive. Here, we show that ETV1 is primarily overexpressed in the most aggressive human prostate tumors. Transgenic ETV1 mice developed prostatic intraepithelial neoplasia as well as hyperplasia/neoplasia in seminal vesicles. Moreover, ETV1 cooperated with the androgen receptor (AR) to bind to the prostate-specific antigen enhancer and stimulate gene transcription. Consistent with its ability to physically interact with AR, ETV1 rendered an ETV1 binding site–driven reporter androgen inducible, and, on the other hand, ETV1 superinduced transcription from an AR binding site on androgen stimulation. In conclusion, our study substantiates that ETV1 overexpression is an underlying cause in the development of prostate and possibly also seminal vesicle cancer. Its interaction with and activation of AR provides a molecular mechanism on how ETV1 exerts its deleterious function. Thus, inhibiting ETV1 or blocking its interaction with AR may represent novel strategies in prostate cancer therapy. [Cancer Res 2009;69(20):8102–10]

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.

Abstract Purpose: This paper describes a process for the identification of genes that can report on the aggressiveness of prostate tumors and thereby add to the information provided by current pathologic analysis. Materials and Methods: Expression profiling data from over 100 laser capture microdissection derived samples from nonneoplastic epithelium; Gleason patterns 3, 4, and 5 and node metastasis prostate cancer were used to identify genes at abnormally high levels in only some tumors. These variably overexpressed genes were stratified by their association with aggressive phenotypes and were subsequently filtered to exclude genes with redundant expression patterns. Selected genes were validated in a case-control study in which cases (systemic progression within 5 years) and controls (no systemic progression at 7 years of follow-up) were matched for all clinical and pathologic criteria from time of prostatectomy (n = 175). Both cases and controls, therefore, could have nodal invasion or seminal vesicle involvement at the time of initial treatment. Results: A number of candidate variably overexpressed genes selected for their association with aggressive prostate cancer phenotype were evaluated in the case control study. The most prominent candidates were SSTR1 and genes related to proliferation, including TOP2A. Conclusions: The process described here identified genes that add information not available from current clinical measures and can improve the prognosis of prostate cancer.

AbstractWe describe a method to identify candidate cancer biomarkers by analyzing numeric approximations of tissue specificity of human genes. These approximations were calculated by analyzing predicted tissue expression distributions of genes derived from mapping expressed sequence tags (ESTs) to the human genome sequence using a binary indexing algorithm. Tissue-specificity values facilitated high-throughput analysis of the human genes and enabled the identification of genes highly specific to different tissues. Tissue expression distributions for several genes were compared to estimates obtained from other public gene expression datasets and experimentally validated using quantitative RT-PCR on RNA isolated from several human tissues. Our results demonstrate that most human genes (∼98%) are expressed in many tissues (low specificity), and only a small number of genes possess very specific tissue expression profiles. These genes comprise a rich dataset from which novel therapeutic targets and novel diagnostic serum biomarkers may be selected.Contact: vasm@mayo.eduSupplementary information: Supplementary data are available at Bioinformatics online.