Musaddeque Ahmed

Genomic hallmarks of localized, non-indolent prostate cancer

Prostate tumours are highly variable in their response to therapies, but clinically available prognostic factors can explain only a fraction of this heterogeneity. Here we analysed 200 whole-genome sequences and 277 additional whole-exome sequences from localized, non-indolent prostate tumours with similar clinical risk profiles, and carried out RNA and methylation analyses in a subset. These tumours had a paucity of clinically actionable single nucleotide variants, unlike those seen in metastatic disease. Rather, a significant proportion of tumours harboured recurrent non-coding aberrations, large-scale genomic rearrangements, and alterations in which an inversion repressed transcription within its boundaries. Local hypermutation events were frequent, and correlated with specific genomic profiles. Numerous molecular aberrations were prognostic for disease recurrence, including several DNA methylation events, and a signature comprised of these aberrations outperformed well-described prognostic biomarkers. We suggest that intensified treatment of genomically aggressive localized prostate cancer may improve cure rates.

Modulation of long noncoding RNAs by risk SNPs underlying genetic predispositions to prostate cancer

Long noncoding RNAs (lncRNAs) represent an attractive class of candidates to mediate cancer risk. Through integrative analysis of the lncRNA transcriptome with genomic data and SNP data from prostate cancer genome-wide association studies (GWAS), we identified 45 candidate lncRNAs associated with risk to prostate cancer. We further evaluated the mechanism underlying the top hit, PCAT1, and found that a risk-associated variant at rs7463708 increases binding of ONECUT2, a novel androgen receptor (AR)-interacting transcription factor, at a distal enhancer that loops to the PCAT1 promoter, resulting in upregulation of PCAT1 upon prolonged androgen treatment. In addition, PCAT1 interacts with AR and LSD1 and is required for their recruitment to the enhancers of GNMT and DHCR24, two androgen late-response genes implicated in prostate cancer development and progression. PCAT1 promotes prostate cancer cell proliferation and tumor growth in vitro and in vivo. These findings suggest that modulating lncRNA expression is an important mechanism for risk-associated SNPs in promoting prostate transformation.

LSD1-Mediated Epigenetic Reprogramming Drives CENPE Expression and Prostate Cancer Progression

Androgen receptor (AR) signaling is a key driver of prostate cancer, and androgen-deprivation therapy (ADT) is a standard treatment for patients with advanced and metastatic disease. However, patients receiving ADT eventually develop incurable castration-resistant prostate cancer (CRPC). Here, we report that the chromatin modifier LSD1, an important regulator of AR transcriptional activity, undergoes epigenetic reprogramming in CRPC. LSD1 reprogramming in this setting activated a subset of cell-cycle genes, including CENPE, a centromere binding protein and mitotic kinesin. CENPE was regulated by the co-binding of LSD1 and AR to its promoter, which was associated with loss of RB1 in CRPC. Notably, genetic deletion or pharmacological inhibition of CENPE significantly decreases tumor growth. Our findings show how LSD1-mediated epigenetic reprogramming drives CRPC, and they offer a mechanistic rationale for its therapeutic targeting in this disease. Cancer Res; 77(20); 5479-90. ©2017 AACR.

Variant Set Enrichment: an R package to identify disease-associated functional genomic regions

BackgroundGenetic predispositions to diseases populate the noncoding regions of the human genome. Delineating their functional basis can inform on the mechanisms contributing to disease development. However, this remains a challenge due to the poor characterization of the noncoding genome. Here, we propose an R package that can pinpoint which genomic features are etiologically important based on the genetic predispositions.ResultsVariant Set Enrichment (VSE) is an R package to calculate the enrichment of a set of disease-associated variants across functionally annotated genomic regions, consequently highlighting the mechanisms important in the etiology of the disease studied.ConclusionsVSE is implemented as an R package and can easily be implemented in any system with R.

SgTiler: a fast method to design tiling sgRNAs for CRISPR/Cas9 mediated screening

Summary Screening of genomic regions of interest using CRISPR/Cas9 is getting increasingly popular. The system requires designing of single guide RNAs (sgRNAs) that can efficiently guide the Cas9 endonuclease to the targeted region with minimal off-target effects. Tiling sgRNAs is the most effective way to perturb regulatory regions, such as promoters and enhancers. sgTiler is the first tool that provides a fast method for designing tiling sgRNAs. Availability and Implementation sgTiler is a command line tool that requires only one command to execute. Its source code is freely available on the web at https://github.com/HansenHeLab/sgTiler. sgTiler is implemented in Python and supported on any platform with Python and Bowtie.

Abstract A033: Identity fraud: Lineage plasticity as a mechanism of antiandrogen resistance and target for therapy

Background: Potent targeting of the androgen receptor (AR) in castration-resistant prostate cancer has altered the archetypal course of the disease, fueling the emergence of aggressive and incurable neuroendocrine prostate cancer (NEPC). Recent evidence suggests that these tumors can arise from non-neuroendocrine cells in response to AR pathway inhibitors (ARPIs), such as enzalutamide (ENZ), an observation consistent with lineage plasticity. What regulates this plasticity that allows cells to shed their dependence on the AR and re-emerge as “AR-indifferent” NEPC? Sequencing studies have uncovered that the evolution toward a NEPC phenotype is aligned with dynamic epigenetic reprogramming, but the molecular basis underlying this phenomenon remains poorly understood. Methods: We developed an in vivo model of acquired ENZ resistance to (a) identify reprogramming factors that facilitate lineage plasticity, and (b) determine how to best capitalize on therapeutic strategies aimed at blocking or reversing lineage transformation. Cell lines derived from ENZ-resistant tumors were profiled by RNA-seq and ChIP-seq, and functionally assessed for stem cell-associated properties. Our findings were validated across NEPC cell lines (NCI-H660), genetically engineered mouse models (PBCre4:Ptenf/f:Rb1f/f), and patient tumors and organoids. CRISPR/Cas9-mediated genomic editing allowed us to assess the effect of knocking out reprogramming factors on therapy-induced neuroendocrine transdifferentiation. Results: AR-indifferent ENZ-resistant tumors were enriched for a Polycomb/EZH2 signature; in particular, we identified EZH2 to be phosphorylated at threonine-350 (pEZH2-T350) by CDK1 in NEPC cell lines, mouse models, and patient tumors. Accordingly, RB1 loss was sufficient to enhance pEZH2-T350, which was required for prostate cancer cells to convert to a metastable stem-like state and, in turn, acquire neuroendocrine features under the pressure of ARPIs both in vitro and in patient-derived xenografts. This therapy-induced NEPC transdifferentation was associated with a marked redistribution of EZH2 and H3K27me3, specifically to a core set of genes governing lineage identity. AR colocalized at the reprogrammed EZH2 binding sites, and was found to be part of the same complex with EZH2. Treating AR-indifferent/NEPC cell lines with clinically relevant EZH2 inhibitors reversed the lineage switch and mitigated ENZ resistance. Conclusions: This research establishes the centrality of epigenetic reprogramming in driving the insurgence of a neuroendocrine phenotype in response to ARPIs, and posits that drugging the epigenome via EZH2 inhibition may reverse or delay lineage transformation to extend the durability of clinically beneficial ARPIs. Citation Format: Alastair Davies, Chiara Bostock, Musaddeque Ahmed, Yen-Yi Lin, Fraser Johnson, Ka Mun Nip, Kirsi Ketola, Jennifer Bishop, Ladan Fazli, David Goodrich, Faraz Hach, Hansen He, Himisha Beltran, Amina Zoubeidi. Identity fraud: Lineage plasticity as a mechanism of antiandrogen resistance and target for therapy [abstract]. In: Proceedings of the AACR Special Conference: Prostate Cancer: Advances in Basic, Translational, and Clinical Research; 2017 Dec 2-5; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(16 Suppl):Abstract nr A033.

Onco-Multi-OMICS Approach: A New Frontier in Cancer Research

The acquisition of cancer hallmarks requires molecular alterations at multiple levels including genome, epigenome, transcriptome, proteome, and metabolome. In the past decade, numerous attempts have been made to untangle the molecular mechanisms of carcinogenesis involving single OMICS approaches such as scanning the genome for cancer-specific mutations and identifying altered epigenetic-landscapes within cancer cells or by exploring the differential expression of mRNA and protein through transcriptomics and proteomics techniques, respectively. While these single-level OMICS approaches have contributed towards the identification of cancer-specific mutations, epigenetic alterations, and molecular subtyping of tumors based on gene/protein-expression, they lack the resolving-power to establish the casual relationship between molecular signatures and the phenotypic manifestation of cancer hallmarks. In contrast, the multi-OMICS approaches involving the interrogation of the cancer cells/tissues in multiple dimensions have the potential to uncover the intricate molecular mechanism underlying different phenotypic manifestations of cancer hallmarks such as metastasis and angiogenesis. Moreover, multi-OMICS approaches can be used to dissect the cellular response to chemo- or immunotherapy as well as discover molecular candidates with diagnostic/prognostic value. In this review, we focused on the applications of different multi-OMICS approaches in the field of cancer research and discussed how these approaches are shaping the field of personalized oncomedicine. We have highlighted pioneering studies from “The Cancer Genome Atlas (TCGA)” consortium encompassing integrated OMICS analysis of over 11,000 tumors from 33 most prevalent forms of cancer. Accumulation of huge cancer-specific multi-OMICS data in repositories like TCGA provides a unique opportunity for the systems biology approach to tackle the complexity of cancer cells through the unification of experimental data and computational/mathematical models. In future, systems biology based approach is likely to predict the phenotypic changes of cancer cells upon chemo-/immunotherapy treatment. This review is sought to encourage investigators to bring these different approaches together for interrogating cancer at molecular, cellular, and systems levels.

Noncoding RNA for personalized prostate cancer treatment: utilizing the ‘dark matters’ of the genome

Prostate cancer is the most commonly diagnosed cancer in men in western countries, with significant health impact. Clinically, it is complicated with the lack of biomarkers and effective treatments for aggressive disease, particularly castration-resistant prostate cancer. Although we have gained much insight into the biology of prostate cancer through studying protein-coding genes, they represent only a small fraction of our genome. Therefore, it is essential for us to investigate noncoding RNAs, which comprise the majority of our transcriptome, in order to achieve a better understanding of prostate cancer and move toward personalized medicine. In this article, we will address recent advancements in our knowledge of noncoding RNAs, and discuss the clinical potentials and challenges of different types of noncoding RNAs in prostate cancer.

Crucial role of noncoding RNA in driving prostate cancer development and progression

Genomic regions without protein-coding potential give rise to a large number of long noncoding RNAs (lncRNAs), which represent close to three-times the number of protein-coding genes [1]. Studies over the past 10 years have shown that lncRNAs are implicated in a range of developmental processes and diseases [2,3]. More recently, lncRNAs have been found to be functional and clinically relevant in prostate cancer (PCa). Specifically, lncRNA PCA3 has been approved to aid PCa diagnosis by the US FDA [4], while lncRNA SChLAP1 has been shown to be an independent biomarker for metastatic PCa [5]. In general, the functional aspects of lncRNAs have been summarized as decoys, guides, scaffolds and enhancer RNAs [2,3]. Similar as well as unique mechanisms have been discovered in PCa. In castration-resistant prostate cancer, lncRNA HOTAIR has been found to interact with AR and block ubiquitination of AR by the E3 ubiquitin ligase, MDM2 [6]. lncRNA SChLAP1 drives PCa metastasis by binding to SWI/SNF chromatin-modifying complex and antagonizing SWI/SNF genome localization and target gene regulation [7]. lncRNA PCA3 was recently found to form a dsRNA complex with PRUNE2, a tumor suppressor gene, thereby promoting ADAR-mediated RNA editing [8]. Finally, lncRNA CTBP1AS directly suppresses CTBP1 transcription by guiding the PSF-HDAC-Sin3A complex to the CTBP1 promoter, which abolishes the androgen-mediated gene repression program [9]. Altogether, these studies have revealed the dynamic interplay between lncRNAs and cancer development, which has highlighted the importance of lncRNAs in the etiology of PCa. Transcriptome analyses have identified hundreds of novel lncRNA transcripts that are dysregulated in PCa. lncRNAs PCAT1 and SChLAP1 were first discovered in a cohort of 102 PCa tissues and cell lines by RNA sequencing, and reported to participate in PCa tumorigenesis and progression. SChLAP1 was recently shown to have significant prognostic value for metastatic progression of PCa [5]. In addition, another lncRNA named PCAT14 was identified as a novel PCaand lineage-specific lncRNA by analyzing The Cancer Genome Atlas PCa RNA-seq data, and was reported to be inversely related with disease aggressiveness [10]. However, dysregulation of lncRNAs expression does not necessarily speak for functional importance in PCa pathogenesis. Nevertheless, with rich genome, epigenome as well as transcriptome data of PCa available, it is now feasible to systematically evaluate the function of lncRNAs in PCa. Crucial role of noncoding RNA in driving prostate cancer development and progression

Abstract B07: Long noncoding RNAs underlying genetic predispositions to prostate cancer

Trait-associated SNPs identified through Genome-Wide Association Studies are enriched in regulatory regions. However, the functional link between these SNPs and their target genes remains elusive. Due to their involvement in fundamental biological processes, long noncoding RNAs (lncRNAs) represent an attractive class of molecules mediating cancer risk. Through integrative analysis of the lncRNA transcriptome with genomic and prostate cancer risk SNP data, we identified 60 candidate lncRNAs associated with risk to prostate cancer. The mechanism underlying the top hit, PCAT1, was evaluated further. The risk variant at rs7463708 decreases HOXB13 and increases AR binding at a distal enhancer that loops to PCAT1 promoter, resulting in upregulation of PCAT1 upon prolonged androgen treatment. In addition, PCAT1 interacts with AR and LSD1 and is required for their recruitment to the enhancers of GNMT and DHCR24, two androgen late response genes implicated in prostate cancer development and progression. These findings suggest that modulating lncRNA expression is an important mechanism for risk SNPs in promoting prostate transformation. Note: This abstract was not presented at the conference. Citation Format: Haiyang Guo, Musaddeque Ahmed, Junjie Tony Hua, Yi Liang, Housheng Hansen He. Long noncoding RNAs underlying genetic predispositions to prostate cancer. [abstract]. In: Proceedings of the AACR Special Conference on Noncoding RNAs and Cancer: Mechanisms to Medicines ; 2015 Dec 4-7; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2016;76(6 Suppl):Abstract nr B07.