Abstracts: AACR Special Conference: Translation of the Cancer Genome; February 7-9, 2015; San Francisco, CA

Conference Information
Name: Abstracts: AACR Special Conference: Translation of the Cancer Genome; February 7-9, 2015; San Francisco, CA

Latest articles from this conference

Elinne Coral Becket, Christopher Duymich, Yin-Wei Chang, Kurinji Pandiyan, Peter Nichols, Peter Jones, Inderbir Gill,
Cancer Genomics and Epigenomics, Volume 75; https://doi.org/10.1158/1538-7445.transcagen-a1-05

Abstract:
Background: While many studies have uncovered genetic mutations that drive tumorigenesis, far fewer have described epigenetic changes, such as nucleosome positioning and DNA methylation, which lead to the development of cancer. Therefore, accurately mapping these changes between normal and tumor tissue will provide novel information to identify genes that undergo epigenetic changes that drive tumorigenesis (“epigenetic driver genes”). In this study, we used an assay developed in our laboratory to investigate the epigenetic changes between clear cell renal cell carcinoma (ccRCC, the most common subtype of renal carcinoma) tumors and normal tissue to uncover genes that contribute to ccRCC tumorigenesis. Methods: Current methods to investigate epigenomic changes in clinical samples are expensive and require abundant biological sample material for analysis. We have developed a novel assay (“AcceSssIble”) to simultaneously determine DNA methylation and chromatin accessibility in clinical samples. It is rapid and cost-effective, only requiring 20 mg of tissue, the Infinium HumanMethylation450 BeadChip platform, and the CpG methyltransferase M.SssI. We used this method to measure the changes in DNA methylation and chromatin accessibility in 9 matched pairs of ccRCC tumors and adjacent normal tissue from different patients, and intersected this data with RNA-seq data of 72 matched ccRCC samples and DNA methylation data of 160 matched ccRCC samples from The Cancer Genome Atlas (TCGA). Genes that were revealed to have the most changes in chromatin structure and expression were then targeted by siRNA knockdown for functional validation in ccRCC. Results: From the AcceSssIble assay on 9 pairs of ccRCC patient tumor/normal samples, we uncovered 438 genes whose promoters change in chromatin accessibility in at least 2 ccRCC samples, both dependent and independent of DNA methylation changes, and have an accompanying change in gene expression in TCGA RNA-seq data. The results produce a striking figure in which chromatin accessibility changes are inversely correlated with DNA methylation but directly correlated with gene expression changes. Interestingly, loss of (DNA methylation change-dependent) accessibility preferentially occurred within CpG islands, while gain of (DNA methylation change-dependent) accessibility was strongly biased towards non-CpG islands. Meanwhile, chromatin accessibility changes independent of DNA methylation changes do not show preference in CpG content. Furthermore, pathway analyses reveal involvement of HIF1α signaling, cAMP-mediated signaling, and G-protein Coupled Receptor Signaling in the development of ccRCC. Lastly, we performed siRNA knockdown experiments on several top genes most changing in expression and accessibility, which revealed two genes, encoding type IV collagen and an RNA-binding protein, whose knockdown resulted in a significant increase in proliferation in normal kidney epithelial cells. Conclusions: Our study revealed a vast number of chromatin accessibility and accompanying gene expression changes that occur in gene promoters in the development of ccRCC, both dependent and independent of DNA methylation changes. Each individual tumor has a unique profile of epigenetic alterations. Moreover, almost none of the genes that were found to undergo epigenetic and resulting gene expression changes overlap with TCGA's findings of commonly mutated genes in ccRCC. Overall, these studies represent novel approaches that can help identify new therapeutic target genes and treatment strategies for ccRCC, including personalized approaches. Citation Format: Elinne Coral Becket, Christopher Duymich, Yin-Wei Chang, Kurinji Pandiyan, Peter Nichols, Peter Jones, Inderbir Gill, Gangning Liang. Elucidation of epigenetic driver genes in clear cell renal cell carcinoma using a newly developed assay, AcceSssIble. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-05.
Patient Stratification: Biomarker/Genomic Approaches, Volume 75; https://doi.org/10.1158/1538-7445.transcagen-a1-54

Abstract:
This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR03) of the Conference Proceedings. Citation Format: Noemi Andor, Trevor A. Graham, Claudia Petritsch, Hanlee P. Ji*, Carlo C. Maley*. Pan-cancer analysis of the etiology and consequences of intratumor heterogeneity. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-54.
Min Y. Cho, Diego Acosta-Alvear, , Thomas Wild, Chuna Ram Choudhary, ,
Genomics, Proteomics, and Target Discovery, Volume 75; https://doi.org/10.1158/1538-7445.transcagen-a2-12

Abstract:
Targeted therapies for cancer are often hindered by the variable genetic makeup within and between tumors. This hurdle makes the identification of therapeutic targets challenging. Genetic susceptibilities found within networks encoded in the genome of a cancer cell can provide such therapeutic opportunities. Essential cellular networks overseeing homeostasis are often rewired in tumors, providing a landscape where synthetic lethal pairs may exist. A prominent example is the susceptibility of multiple myeloma (MM) cells to proteasome inhibitors. Because of their highly secretory nature, the proteasomes of MM cells can be burdened in a load-versus-capacity tug-of-war. This renders MM cells sensitive to proteasome inhibitors. Unfortunately, single agent therapies against the proteasome do not provide a cure, as tumor cells often acquire resistance. Because of this, we sought to understand how MM cancer cells respond and adapt to proteasome inhibition. Utilizing ultra-complex shRNA libraries, we screened several MM cell lines exposed to the proteasome inhibitor bortezomib. In these screens, we identified several genes that either sensitize or protect MM cells towards bortezomib intoxication. Unexpectedly we found that, contrary to knockdown of genes encoding subunits of the 20S core particle of the proteasome, knockdown of genes encoding subunits of the 19S regulatory particle of the proteasome lead to bortezomib desensitization. To understand the nature of this phenotype, we queried proteome changes in bortezomib treated cells where we ablated a single 19S subunit. By performing ubiquitin-remnant profiling and total proteome SILAC experiments, we identified several proteins involved in autophagy and NF-κB signaling as potential mediators of the protective phenotype. We are currently investigating the roles of components of these pathways in tailoring the response towards bortezomib. We surmise that some of these will be amenable for pharmacological targeting in developing novel combination therapies. Citation Format: Min Y. Cho, Diego Acosta-Alvear, Martin Kampmann, Thomas Wild, Chuna Ram Choudhary, Jonathan S. Weissman, Peter Walter. Opposing roles of the 19S regulatory and 20S core proteasomal subunits in controlling sensitivity to proteasome inhibitors. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-12.
Tasnim Chagtai, Christina Zill, Linda Dainese, Jenny Wegert, Mariana Maschietto, Gordan Vujanic, , Ivo Leuschner, Peter Ambros, Maureen O'sullivan, et al.
Patient Stratification: Biomarker/Genomic Approaches, Volume 75; https://doi.org/10.1158/1538-7445.transcagen-a1-67

Abstract:
Background and Purpose: Treatment of Wilms tumor (WT) patients under International Society of Paediatric Oncology (SIOP) protocols is currently stratified by staging and histopathology at nephrectomy after neoadjuvant chemotherapy. However, most relapses occur in cases without specific histopathological risk factors, and there is a clinical need for better prognostic biomarkers. Combined loss of heterozygosity (LOH) of 1p and 16q has recently been introduced in the US as an adverse prognostic indicator, while previous work in our and other laboratories suggests that 1q gain may have a similar association with poor outcome. To examine the clinical significance of 1q gain and assess its potential as a WT biomarker, we developed a simple, effective assay that measures its genomic copy number together with that of several other loci of interest, and applied it to a large tumor series. Methods: 686 frozen tumor samples from the SIOP WT 2001 trial (from a total of 7 countries) were assayed using a rapid multiplex ligation-dependent probe amplification (MLPA) assay that was developed and optimized in association with MRC-Holland b.v. to assess the copy number status of 1p, 1q, 16q, WT1, WTX, TP53, MYCN and FBXW7. Analyses were conducted in 3 laboratories, with exchange of a blinded quality assurance sample set. Results: 1q gain was present in 28% (190/686) of the cases. The 5- year Event Free Survival (EFS) rate was 72.6% (95% Confidence Interval (CI), 66.3%-85%) for those with 1q gain and 86.4% (95% CI, 83.4%-89.6%) for those who lacked 1q gain (p=<0.0001). The Overall Survival (OS) rate for 1q gain cases was 86.9% (95% CI, 82.1%-92.1%) compared to 93.8% (95% CI, 91.7%-92.1%) for cases without the aberration (p=0.01). Both the EFS and OS analysis showed a statistically significant poorer outcome for cases with 1q gain, but there was no association with disease stage. 1q gain was associated with a significantly increased risk of disease recurrence (HR = 2.18, p<0.0001). In this analysis the proportions of samples with 1p and 16q loss were respectively 8% and 16%. Both were marginally significant for EFS but in the OS analysis 1p lost its significance. MYCN gain, 4q (FBXW7) loss and 17p (TP53) loss were also associated with adverse outcome. Conclusion: Gain of 1q is a potential adverse biomarker for WT. Its association with high risk histological features after pre-operative chemotherapy and independent impact on survival require assessment in a larger number of patients before consideration for clinical use. Citation Format: Tasnim Chagtai, Christina Zill, Linda Dainese, Jenny Wegert, Mariana Maschietto, Gordan Vujanic, Neil Sebire, Ivo Leuschner, Peter Ambros, Maureen O'Sullivan, Christophe Bergeron, David Gisselsson, Marcel Kool, Marry van den Heuvel-Eibrink, Norbert Graf, Harm van Tinteren, Aurore Coulomb, Manfred Gessler, Richard Williams, Kathy Pritchard-Jones. Prognostic significance of copy number aberrations in Wilms tumor. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-67.
, , Michael R. Freeman
Patient Stratification: Biomarker/Genomic Approaches, Volume 75; https://doi.org/10.1158/1538-7445.transcagen-a1-49

Abstract:
Background: Gene expression profiling has been used to define subclasses of cancers and in the assembly of potential prognostic signatures. Molecular categories are commonly defined by supervised or unsupervised cluster analysis of mRNA levels. However, despite efforts to profile prostate cancer using transcriptome data, the genetic alterations and biological processes that contribute to clinical progression have made disease subtype categorization difficult. In addition, most studies are limited in statistical power, and therefore do not accurately reflect the heterogeneity of the disease in the general population. The goal of this study was to generate molecular profiles of prostate cancer using an unprecedentedly large transcriptome dataset. Methods: We compiled a very large compendium of 50 human prostate cancer transcriptome datasets containing over 4,000 human prostate cancer specimens, which we named the “Prostate Cancer Transcriptome Atlas” (PCTA). From this resource, 38 datasets, containing over 2,000 specimens, were combined into a single, normalized and batch-corrected dataset using the median-centering method. Molecular categories were sought using 29 published gene expression signature profiles, including castration-resistance (CRPC), oncogene activation, AR activation, AR variants, EZH2, FOXA1, TMPRSS2–ERG fusion, stemness, PTEN inactivation, polycomb complex (PRC2) repression, cell proliferation, epithelial-mesenchymal transition, and proneural and neuroendocrine differentiation. Signature profiles were computed by the weighted Z-score method. Results: Unsupervised clustering identified subsets of tumors manifesting consistent molecular features across many specimens, including a category showing strong AR signatures coupled in concert with significantly repressed PRC2 signatures. These features were mostly seen in high Gleason score (>7) or metastatic prostate cancer. Another major group was an “inverse” signature, showing activated PRC2 and repressed AR signatures. This stratification was independently validated using two datasets: (1) from 545 formalin-fixed paraffin-embedded (FFPE) tissue samples from primary prostate cancer from the Mayo Clinic (PLoS One 2013; 8(6):e66855) and 281 prostate cancers from a watchful-waiting cohort recruited in Sweden (BMC Med Genomics 2010;3:8). This analysis also allowed us to observe other, distinct variant classes, including activation of AR-variants and EZH2, high enrichment of stemness, and proneural and neuroendocrine differentiation. Conclusion: These results show that analyzing gene signatures using an integrated collection of transcriptome profiles from multiple platforms, and thereby significantly increasing sample size, allows the assignment of provisional disease categories that are either difficult to observe or not detected even in large profiling studies. Citation Format: Sungyong You, Jayoung Kim, Michael R. Freeman. Prostate cancer classification using a transcriptome atlas. []. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1): nr A1-49.
Jun Wang, Gang Feng, Nadereh Jafari, Ali Shidfar, David Ivanicic, Megan E. Sullivan, Seema A. Khan
Genomics, Proteomics, and Target Discovery, Volume 75; https://doi.org/10.1158/1538-7445.transcagen-a2-03

Abstract:
Background: Breast cancer prevention is currently in a challenge due to the inability to identify high-risk women accurately only based on family history and pathologic evaluation of benign biopsy. Somatic molecular changes in clinically normal breasts have potential value for to improve the assessment of truly high-risk women. The identification of risk biomarkers in benign biopsy material will directly benefit the millions of women who undergo benign breast biopsy annually, adding precision to the risk implied by the histologic features of the benign biopsy. Therefore, we are pursuing robust biomarkers for breast cancer risk by sequencing pre-cancer benign biopsies, which may lead to discovery of genomic variation responsible for initiation and early progression of breast cancer. Methods: We are assembling a case-control set of benign breast biopsy matched by age, race, and duration of follow-up. The cases were the benign biopsies from women who subsequently developed breast cancer after at least one year, and the controls were the benign biopsy samples obtained from women who remain cancer free. 10-micron sections from formalin-fixed, paraffin-embedded tissue blocks are used for laser capture microdissection of selected epithelial areas and extraction of DNA. As a pilot experiment, we examined hotspot mutation in 4 cases and 4 control samples, using Ion AmpliSeq cancer hotspot panel consisting of 50 oncogenes/tumor suppressor and detecting 2855 hotspot mutation from COSMIC (Catalogue Of Somatic Mutations In Cancer). The average amplicon length was 154 (111-187) with average depth coverage of 1400x. SNP detection sensitivity was 98% for 5% variant frequency. Results: Among the 2855 hotspot mutation in 50 oncogenes/tumor suppressor detected, 153 mutation in 27 genes were identified in cases, and 62 mutations in 18 genes were found in controls. The most frequent mutanted gene was TP53 (71 mutation in cases, 24 mutation in controls). In 6 genes (CTNNB1, CDKN2A, ATM, KRAS, STK11 and SMARCB1), hotspot mutation was identified in at least two cases, but no hotspot mutation was identified in controls. Among the 4 cases, one cases had 95 hotspot mutation, much higher than the other 3 cases (5, 16, 37 mutation, respectively) and 4 controls (8, 11, 14, 29 mutation, respectively). This case progressed to triple negative (ER-, PR-, HER2-) breast cancer, a very aggressive subtype of cancer with poor prognosis. Conclusion: The pilot study of deep sequencing of breast benign biopsy suggested that the overall hotspot mutation frequency was higher in cases which progressed to malignant cancer compared to controls which did not progress to malignant cancer. Several genes were identified to be specifically associated with the progression. Citation Format: Jun Wang, Gang Feng, Nadereh Jafari, Ali Shidfar, David Ivanicic, Megan E. Sullivan, Seema A. Khan. Hotspot mutation in breast benign biopsy associated with subsequent progression to malignant breast cancer. []. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1): nr A2-03.
Michael L. Nickerson, Kate M. Im, Sevilay Turan, Guangwu Guo, Lee E. Moore, Dan Theodorescu,
Cancer Genomics and Epigenomics, Volume 75; https://doi.org/10.1158/1538-7445.transcagen-a1-01

Abstract:
Next generation sequencing (NGS) of urologic tumor genomes has led to the detection of frequently altered cancer genes. We have characterized bladder (BCa), prostate (PCa), and kidney (RCC) tumor genomes using exome, whole genome, and transcriptome NGS; copy number and SNP arrays, and bisulfite sequencing for methylation to detect genomic alterations associated with disease. We recently examined BCa tumors from 54 U.S. patients and compared these to 99 Chinese patients to identify novel alterations of cancer genes encoding proteins associated with DNA and chromatin, including telomerase (TERT), stromal antigen 2 (STAG2), and BRCA1-associated protein-1 (BAP1). We are the first to show the TERT promoter is altered in BCa by both somatic and germline nucleotide changes in 37/54 (69%) and 30/54 (56%) tumors, respectively; and that TERT somatic alterations do not correlate with other cancer gene mutations examined by exome NGS. Most TERT germline variants were novel (19/20), and three variants were confirmed as both somatic and germline in distinct tumors, including the most frequent variant, c. – 245 T>C (rs2853669). We show somatic promoter alterations are associated with increased TERT expression but, paradoxically, with significantly shorter telomeres in tumors as compared to matched normal tissue. STAG2 was altered by somatic deleterious sequence changes, genomic deletions, and promoter CpG hypermethylation. Mutations are associated with reduced patient survival and tumor cell aneuploidy based on an increased number of chromosomal arm copy number changes. Somatic BAP1 mutations are primarily deleterious sequence changes that occurred preferentially in U.S. Caucasian as compared to Chinese BCa patients. BAP1 mutations are associated with papillary histologic features in a subset of tumors and with mutations in the histone lysine–specific demethylase 6A (KDM6A/UTX) gene. BAP1 mutations contribute to a significant number of tumors with somatic and rare germline variants in BRCA pathway genes, including BRCA1, BRCA2, PALB2, and ATM. We experimentally examined the function of KDM6A since it is the most frequently altered chromatin modifying gene in 24% of tumors. KDM6A loss in human BCa cells enhanced in vitro proliferation, in vivo tumor growth, and cell migration, confirming KDM6A loss drives the BCa phenotype. A comparison of BCa and other urologic tumor genomes allows us to identify several emergent common characteristics. Significant numbers of tumors are altered by rare, disease-associated germline cancer gene variants that likely have substantive effects on cancer risk and which likely influence the subsequent accrual of somatic alterations. These likely contribute to the missing heritability that is observed by cancer epidemiology studies. Many cancer genes are altered by characteristic frequencies of nonsynonymous sequence changes, promoter variants, copy number variation, and hypermethylation, that are routinely observed for a given gene-tissue-patient ethnicity combination. Approximately 4-5 tumor suppressors are altered for each oncogene, and interactions between altered cancer genes affect the resulting biological functions. In BCa, we show KDM6A loss increases cell proliferation which likely results in shorter telomeres even though TERT expression is increased. We identified altered cancer genes such as STAG2 that are associated with discrete clinical aspects of the disease phenotype, namely aneuploidy and reduced patient survival indicating a lethal subtype of disease. Cancer genes on the X chromosome such as STAG2 and KDM6A have a single copy in men and likely contribute to the gender bias observed in cancer. Finally, cancer gene alterations can identify patients likely to respond to a currently approved therapy. BAP1 and BRCA pathway alterations define BCa, PCa, and RCC tumors with a common DNA repair deficiency that might be exploited by targeted therapies such as poly (ADP ribose) polymerase inhibitors.
, David Tamborero, Michael P. Schroeder, , Jordi Deu-Pons, Christian Perez-Llamas, , Abel Gonzalez-Perez,
Clinical Applications of Cancer Genomics, Volume 75; https://doi.org/10.1158/1538-7445.transcagen-a1-45

Abstract:
The development of targeted therapies against altered driver proteins holds the promise of selectively and efficiently eliminating cancer cells. However, high intertumor heterogeneity is a major obstacle to develop and apply therapeutic targeted agents to treat most cancer patients. Here, we present the first large-scale therapeutic landscape of cancer as it stands today in a 6.792 sample cohort covering 28 tumor types. To pursue this goal, we developed a three-step in silico drug prescription strategy. 1) To discover actionable driver events, we first comprehensively identified mutational cancer driver genes by detecting complementary signals of positive selection in the pattern of their mutations across the tumor cohorts. We also identified actionable copy number alteration (CNA) and fusion cancer driver genes. Second, we detected which of these driver genes would have an oncogenic role in the tumor and which ones would lose their function. With these two steps we generated the Drivers Database. 2) Next, we systematically gathered all information available on therapeutic agents; FDA approved and in clinical or pre-clinical stages. We considered three different types of targeting strategies for the cancer driver genes: direct targeting, indirect targeting and gene therapies in clinical trials. Moreover, we designed a set of rules for assigning therapeutic agents to specific genomic alterations beard for the driver genes. By doing this last step, we generated the Drivers Actionability Database. 3) Finally, by combining data of Drivers Database, Drivers Actionability Database and sample data, we developed in silico drug prescription, a novel approach to determine which of the drugs could benefit each of the tumor individuals. In all, in the Driver Database we identified 460 mutational cancer driver genes acting in one or more of the tumor types along with 39 driver genes acting via CNAs or fusions. Fifty of these cancer driver genes are targeted by FDA approved agents, 63 by molecules currently in clinical trials and 74 are bound by pre-clinical ligands. We also identified 81 therapeutically unexploited targetable cancer genes. Lastly, by applying in silico drug prescription we found that only 6.7% of the patients could be treated following clinical guidelines, and were concentrated in only 6 tumor types. Moreover, considering repurposing strategies the fraction of patients that could benefit from FDA approved drugs would increase up to 40%, increasing remarkably the fraction of targetable patients in some tumor types like glioblastoma and thyroid cancer, and up to 72% if considering targeted therapies in clinical trials. In summary, the in silico drug prescription based on Drivers and Drivers Actionability Databases was tested on one of the largest cohorts of tumor samples currently collected for research. The main result highlights the current scope of targeted anti-cancer therapies and its prospects for growth in view of the drugs that are currently in clinical trials or at pre-clinical stages. Additionally, another important output of this work is a ranked list of novel target opportunities for anticancer drug development. Continuous update of drug-target interactions information, and the application of the strategy to larger cohorts, will improve the in silico prescription rules contained within the two databases, thus enhancing its usefulness within personalized cancer medicine. Citation Format: Carlota Rubio-Perez, David Tamborero, Michael P. Schroeder, Albert A. Antolín, Jordi Deu-Pons, Christian Perez-Llamas, Jordi Mestres, Abel Gonzalez-Perez, Nuria Lopez-Bigas. In silico prescription of anticancer drugs to cohorts of 28 tumor types reveals novel targeting opportunities. []. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1): nr A1-45.
Zhaoyu Li
Cancer Genomics and Epigenomics, Volume 75; https://doi.org/10.1158/1538-7445.transcagen-a1-08

Abstract:
Estrogen, the female dominant hormone, has been found to play critical roles in cancers for over 100 years. In 1896, estrogen was found to promote the tumor growth of breast cancer; and in 1937, estrogen was found to prevent the tumor growth of liver cancer. After the estrogen receptor alpha (ERα) was identified in 1958, ERα-mediated estrogen signaling was found to promote or prevent the growth of breast cancer cells or liver cancer cells, respectively. Recent studies showed that ERα-mediated estrogen signaling in promoting the growth of breast cancer cells was dependent of forkhead box protein A1 (FOXA1). Our recent study showed that ERα-mediated estrogen signaling in preventing the growth of liver cancer cells also depended on FOXA factors (FOXA1 and FOXA2). Thus, FOXA-dependent ERα-mediated estrogen signaling plays opposite roles in the growth of breast cancer and liver cancer cells. Here, we applied genomic approaches to identify 184 FOXA/ER dual target genes that showed opposite expression in response to estrogen-mediated stimulation or suppression of cell growth in breast or liver cancer cells. Gene ontology analysis showed that the majority of these FOXA/ER dual target genes were involved in the processes of cell proliferation and growth, cell death, tissue development, and cancer. Manipulations of the expression of these target genes were able to reverse the growth of breast and liver cancer cells. Thus, these 184 FOXA/ER dual target genes provide us a novel set of potential biomarkers and therapeutic targets for both breast cancer and liver cancer. Note: This was not presented at the conference. Citation Format: Zhaoyu Li. Comparative genomics study of FOXA/ER dual regulation in breast cancer and liver cancer. []. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1): nr A1-08.
, Anne Jedlicka, Oluwasina Folawiyo, , Blanca L. Valle, Fahcina Lawson, Angelo Vergura, Gabriela Pérez, Marisa Renehan, Carolina Guerrero-Díaz, et al.
Patient Stratification: Biomarker/Genomic Approaches, Volume 75; https://doi.org/10.1158/1538-7445.transcagen-a1-50

Abstract:
Human Papilloma Virus (HPV) testing is increasingly used for cervical cancer screening in conjunction with cervical cytology. Although privacy, cultural, and infrastructure issues challenge the effective implementation of HPV testing for cervical cancer screening worldwide, several countries have already implemented HPV testing in their screening protocols. There are currently no tests that can reliably identify the patients with abnormal cytology and positive oncogenic HPV results (HPV+) that need to be referred for colposcopy. A useful triage test from cytology to colposcopy must discriminate the patients with a Cervical Intraepithelial Neoplasia (CIN) lesion that are more likely to progress to cervical cancer (CIN2+), from those that are less likely to progress. We set out to identify a panel of methylated HPV and human genes that can discriminate between CIN2+ and normal/CIN1 patients, first in cytology samples and then in urine samples. The Reverse Line Blot Assay identified high-risk HPV types in study participants from a Discovery cohort (n=96): 31 women with normal cervical cytology and 65 women with dysplasia (LSIL, n=43) and (HSIL, n=22). We developed custom sequence capture pools of baits to pull down genomic (Roche SeqCap EZ) and bisulfite converted high-risk HPV DNA (Agilent SureSelect) from urine, before library prep for NGS in a Roche 454 and MiSeq instruments, respectively. We also optimzed a qPCR assay to identify high risk HPV types, and quantitative Methylation Specific PCR (qMSP) assays to examine methylated HPV and human genes, in Pap smear DNA and TrDNA samples from women with normal Pap and women with CIN1, CIN2 and CIN3 lesions (n=80). The human genes selected for the qMSP assays, ZNF516, FKBP6, and INTS1, were identified in a previously published genome-wide analysis of the cevical cancer methylome using Nimblegen 385K CpG plus Promoters oligonucleotide tiling arrays. Presence of high-risk HPV in cervical epithelium correctly classified 37% of HSIL when compared with LSIL patients, with 61% sensitivity and 22% specificity. Promoter methylation of INTS1 correctly classified 67% (31% sensitivity, 92% specificity), promoter methylation of ZNF516 correctly classified 54% (11% sensitivity, 84% specificity), promoter methylation of FKBP6 correctly classified 59% (19% sensitivity, 88% specificity), and methylation of the HPVL1 gene correctly classified 61% (22% sensitivity, 90% specificity) of HSIL patients when compared with LSIL patients. A molecular panel comprised of HPV16-L1 methylation and promoter methylation of INTS1, ZNF516 and FKBP6 correctly classified 70% of HSIL patients with an Area Under the Curve of 0.66, 44% sensitivity, 88% specificity and 72% Positive Predictive value. While HPV16-L1 methylation discriminated patients with normal cytology from women with cervical dysplasia with close to 100% sensitivity and specificity, the high-risk HPV TrDNA qPCR assay had a pre-capture and post-capture sensitivity of 79% with 50% specificity. The detection of circulating HPV DNA in urine is a cost-effective and non-invasive alternative for cervical cancer screening. We have shown that a panel of genomic and epigenomic alterations in human and high risk HPV DNA can discriminate normal from cervical dysplasia in cervical epithelium DNA and TrDNA isolated from patients seen in a high risk cervical cancer screening setting. Citation Format: Rafael Guerrero-Preston, Anne Jedlicka, Oluwasina Folawiyo, Francesca Pirini, Blanca L. Valle, Fahcina Lawson, Angelo Vergura, Gabriela Perez, Marisa Renehan, Carolina Guerrero-Díaz, Liliana Florea, Teresa Díaz-Montes, Josefina Romaguera, David Sidransky. Genomic and epigenomic alterations in human and high-risk HPV DNA can discriminate normal from cervical dysplasia patients in urine. []. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1): nr A1-50.
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