Dimple Chakravarty

Integrative annotation of variants from 1092 humans: application to cancer genomics.

Introduction Plummeting sequencing costs have led to a great increase in the number of personal genomes. Interpreting the large number of variants in them, particularly in noncoding regions, is a current challenge. This is especially the case for somatic variants in cancer genomes, a large proportion of which are noncoding. Prioritization of candidate noncoding cancer drivers based on patterns of selection. (Step 1) Filter somatic variants to exclude 1000 Genomes polymorphisms; (2) retain variants in noncoding annotations; (3) retain those in “sensitive” regions; (4) prioritize those disrupting a transcription-factor binding motif and (5) residing near the center of a biological network; (6) prioritize ones in annotation blocks mutated in multiple cancer samples. Methods We investigated patterns of selection in DNA elements from the ENCODE project using the full spectrum of variants from 1092 individuals in the 1000 Genomes Project (Phase 1), including single-nucleotide variants (SNVs), short insertions and deletions (indels), and structural variants (SVs). Although we analyzed broad functional annotations, such as all transcription-factor binding sites, we focused more on highly specific categories such as distal binding sites of factor ZNF274. The greater statistical power of the Phase 1 data set compared with earlier ones allowed us to differentiate the selective constraints on these categories. We also used connectivity information between elements from protein-protein-interaction and regulatory networks. We integrated all the information on selection to develop a workflow (FunSeq) to prioritize personal-genome variants on the basis of their deleterious impact. As a proof of principle, we experimentally validated and characterized a few candidate variants. Results We identified a specific subgroup of noncoding categories with almost as much selective constraint as coding genes: “ultrasensitive” regions. We also uncovered a number of clear patterns of selection. Elements more consistently active across tissues and both maternal and paternal alleles (in terms of allele-specific activity) are under stronger selection. Variants disruptive because of mechanistic effects on transcription-factor binding (i.e. “motif-breakers”) are selected against. Higher network connectivity (i.e. for hubs) is associated with higher constraint. Additionally, many hub promoters and regulatory elements show evidence of recent positive selection. Overall, indels and SVs follow the same pattern as SNVs; however, there are notable exceptions. For instance, enhancers are enriched for SVs formed by nonallelic homologous recombination. We integrated these patterns of selection into the FunSeq prioritization workflow and applied it to cancer variants, because they present a strong contrast to inherited polymorphisms. In particular, application to ~90 cancer genomes (breast, prostate and medulloblastoma) reveals nearly a hundred candidate noncoding drivers. Discussion Our approach can be readily used to prioritize variants in cancer and is immediately applicable in a precision-medicine context. It can be further improved by incorporation of larger-scale population sequencing, better annotations, and expression data from large cohorts. Identifying Important Identifiers Each of us has millions of sequence variations in our genomes. Signatures of purifying or negative selection should help identify which of those variations is functionally important. Khurana et al. (1235587) used sequence polymorphisms from 1092 humans across 14 populations to identify patterns of selection, especially in noncoding regulatory regions. Noncoding regions under very strong negative selection included binding sites of some chromatin and general transcription factors (TFs) and core motifs of some important TF families. Positive selection in TF binding sites tended to occur in network hub promoters. Many recurrent somatic cancer variants occurred in noncoding regulatory regions and thus might indicate mutations that drive cancer. Regions under strong selection in the human genome identify noncoding regulatory elements with possible roles in disease. Interpreting variants, especially noncoding ones, in the increasing number of personal genomes is challenging. We used patterns of polymorphisms in functionally annotated regions in 1092 humans to identify deleterious variants; then we experimentally validated candidates. We analyzed both coding and noncoding regions, with the former corroborating the latter. We found regions particularly sensitive to mutations (“ultrasensitive”) and variants that are disruptive because of mechanistic effects on transcription-factor binding (that is, “motif-breakers”). We also found variants in regions with higher network centrality tend to be deleterious. Insertions and deletions followed a similar pattern to single-nucleotide variants, with some notable exceptions (e.g., certain deletions and enhancers). On the basis of these patterns, we developed a computational tool (FunSeq), whose application to ~90 cancer genomes reveals nearly a hundred candidate noncoding drivers.

The oestrogen receptor alpha-regulated lncRNA NEAT1 is a critical modulator of prostate cancer

The androgen receptor (AR) plays a central role in establishing an oncogenic cascade that drives prostate cancer progression. Some prostate cancers escape androgen dependence and are often associated with an aggressive phenotype. The oestrogen receptor alpha (ERα) is expressed in prostate cancers, independent of AR status. However, the role of ERα remains elusive. Using a combination of chromatin immunoprecipitation (ChIP) and RNA-sequencing data, we identified an ERα-specific non-coding transcriptome signature. Among putatively ERα-regulated intergenic long non-coding RNAs (lncRNAs), we identified nuclear enriched abundant transcript 1 (NEAT1) as the most significantly overexpressed lncRNA in prostate cancer. Analysis of two large clinical cohorts also revealed that NEAT1 expression is associated with prostate cancer progression. Prostate cancer cells expressing high levels of NEAT1 were recalcitrant to androgen or AR antagonists. Finally, we provide evidence that NEAT1 drives oncogenic growth by altering the epigenetic landscape of target gene promoters to favour transcription.

Role of non-coding sequence variants in cancer

Patients with cancer carry somatic sequence variants in their tumour in addition to the germline variants in their inherited genome. Although variants in protein-coding regions have received the most attention, numerous studies have noted the importance of non-coding variants in cancer. Moreover, the overwhelming majority of variants, both somatic and germline, occur in non-coding portions of the genome. We review the current understanding of non-coding variants in cancer, including the great diversity of the mutation types — from single nucleotide variants to large genomic rearrangements — and the wide range of mechanisms by which they affect gene expression to promote tumorigenesis, such as disrupting transcription factor-binding sites or functions of non-coding RNAs. We highlight specific case studies of somatic and germline variants, and discuss how non-coding variants can be interpreted on a large-scale through computational and experimental methods.

Whole-Exome Sequencing of Metastatic Cancer and Biomarkers of Treatment Response

IMPORTANCE Understanding molecular mechanisms of response and resistance to anticancer therapies requires prospective patient follow-up and clinical and functional validation of both common and low-frequency mutations. We describe a whole-exome sequencing (WES) precision medicine trial focused on patients with advanced cancer. OBJECTIVE To understand how WES data affect therapeutic decision making in patients with advanced cancer and to identify novel biomarkers of response. DESIGN, SETTING, AND PATIENTS Patients with metastatic and treatment-resistant cancer were prospectively enrolled at a single academic center for paired metastatic tumor and normal tissue WES during a 19-month period (February 2013 through September 2014). A comprehensive computational pipeline was used to detect point mutations, indels, and copy number alterations. Mutations were categorized as category 1, 2, or 3 on the basis of actionability; clinical reports were generated and discussed in precision tumor board. Patients were observed for 7 to 25 months for correlation of molecular information with clinical response. MAIN OUTCOMES AND MEASURES Feasibility, use of WES for decision making, and identification of novel biomarkers. RESULTS A total of 154 tumor-normal pairs from 97 patients with a range of metastatic cancers were sequenced, with a mean coverage of 95X and 16 somatic alterations detected per patient. In total, 16 mutations were category 1 (targeted therapy available), 98 were category 2 (biologically relevant), and 1474 were category 3 (unknown significance). Overall, WES provided informative results in 91 cases (94%), including alterations for which there is an approved drug, there are therapies in clinical or preclinical development, or they are considered drivers and potentially actionable (category 1-2); however, treatment was guided in only 5 patients (5%) on the basis of these recommendations because of access to clinical trials and/or off-label use of drugs. Among unexpected findings, a patient with prostate cancer with exceptional response to treatment was identified who harbored a somatic hemizygous deletion of the DNA repair gene FANCA and putative partial loss of function of the second allele through germline missense variant. Follow-up experiments established that loss of FANCA function was associated with platinum hypersensitivity both in vitro and in patient-derived xenografts, thus providing biologic rationale and functional evidence for his extreme clinical response. CONCLUSIONS AND RELEVANCE The majority of advanced, treatment-resistant tumors across tumor types harbor biologically informative alterations. The establishment of a clinical trial for WES of metastatic tumors with prospective follow-up of patients can help identify candidate predictive biomarkers of response.

PELP1 is a reader of histone H3 methylation that facilitates oestrogen receptor‐α target gene activation by regulating lysine demethylase 1 specificity

Histone methylation has a key role in oestrogen receptor (ERα)‐mediated transactivation of genes. Proline glutamic acid and leucine‐rich protein 1 (PELP1) is a new proto‐oncogene that functions as an ERα co‐regulator. In this study, we identified histone lysine demethylase, KDM1, as a new PELP1‐interacting protein. These proteins, PELP1 and KDM1, were both recruited to ERα target genes, and PELP1 depletion affected the dimethyl histone modifications at ERα target genes. Dimethyl‐modified histones H3K4 and H3K9 are recognized by PELP1, and PELP1 alters the substrate specificity of KDM1 from H3K4 to H3K9. Effective demethylation of dimethyl H3K9 by KDM1 requires a KDM1–ERα–PELP1 functional complex. These results suggest that PELP1 is a reader of H3 methylation marks and has a crucial role in modulating the histone code at the ERα target genes.

Extranuclear Functions of ER Impact Invasive Migration and Metastasis by Breast Cancer Cells

The molecular basis of breast cancer progression to metastasis and the role of estrogen receptor (ER) signaling in this process remain poorly understood. Emerging evidence suggests that ER participates in extranuclear signaling in addition to genomic functions. Recent studies identified proline-, glutamic acid-, and leucine-rich protein-1 (PELP1) as one of the components of ER signalosome in the cytoplasm. PELP1 expression is deregulated in metastatic breast tumors. We examined the mechanism and significance of ER-PELP1-mediated extranuclear signals in the cytoskeletal remodeling and metastasis. Using estrogen dendrimer conjugate (EDC) that uniquely activate ER extranuclear signaling and by using model cells that stably express PELP1 short hairpin RNA (shRNA), we show that PELP1 is required for optimal activation of ER extranuclear actions. Using a yeast two-hybrid screen, we identified integrin-linked kinase 1 (ILK1) as a novel PELP1-binding protein. Activation of extranuclear signaling by EDC uniquely enhanced E2-mediated ruffles and filopodia-like structures. Using dominant-negative and dominant-active reagents, we found that estrogen-mediated extranuclear signaling promotes cytoskeleton reorganization through the ER-Src-PELP1-phosphoinositide 3-kinase-ILK1 pathway. Using in vitro Boyden chamber assays and in vivo xenograft assays, we found that ER extranuclear actions contribute to cell migration. Collectively, our results suggest that ER extranuclear actions play a role in cell motility/metastasis, establishing for the first time that endogenous PELP1 serves as a critical component of ER extranuclear actions leading to cell motility/invasion and that the ER-Src-PELP1-ILK1 pathway represents a novel therapeutic target for preventing the emergence of ER-positive metastasis.

Significance of ER–Src axis in hormonal therapy resistance

The estrogen receptor (ER) is implicated in the progression of breast cancer. Despite positive effects of hormonal therapy, initial or acquired resistance to endocrine therapies frequently occurs. Recent studies suggested ERα-coregulator PELP1 and growth factor receptor ErbB2/HER2 play an essential role in hormonal therapy responsiveness. Src axis couples ERα with HER2 and PELP1, thus representing a new pathway for targeted therapy resistance. To establish the significance of ER–Src axis in PELP1 and HER2 mediated therapy resistance, we have generated model cells that stably express Src-shRNA under conditions of PELP1, HER2 deregulation. Depletion of Src using shRNA substantially reduced E2 mediated activation of Src and MAPK activation in resistant model cells. Pharmacological inhibition of Src using dasatinib, an orally available inhibitor substantially inhibited the growth of therapy resistant MCF7–PELP1, MCF7–HER2, and MCF7–Tam model cells in proliferation assays. In post-menopausal xenograft based studies, treatment with dasatinib significantly inhibited the growth of therapy resistant cells. IHC analysis revealed that the tumors were ERα positive, and dasatinib treated tumors exhibited alterations in Src and MAPK signaling pathways. Combinatorial therapy of tamoxifen with dasatinib showed better therapeutic effect compared to single agent therapy on the growth of therapy resistant PELP1 driven tumors. The results from our study showed that ER–Src axis play an important role in promoting hormonal resistance by proto-oncogenes such as HER2, PELP1, and blocking this axis prevents the development of hormonal independence in vivo. Since PELP1, HER2, and Src kinase are commonly deregulated in breast cancers, combination therapies using both endocrine agents and dasatinib may have better therapeutic effect by delaying the development of hormonal resistance.

Identification of functionally active, low frequency copy number variants at 15q21.3 and 12q21.31 associated with prostate cancer risk

Copy number variants (CNVs) are a recently recognized class of human germ line polymorphisms and are associated with a variety of human diseases, including cancer. Because of the strong genetic influence on prostate cancer, we sought to identify functionally active CNVs associated with susceptibility of this cancer type. We queried low-frequency biallelic CNVs from 1,903 men of Caucasian origin enrolled in the Tyrol Prostate Specific Antigen Screening Cohort and discovered two CNVs strongly associated with prostate cancer risk. The first risk locus (P = 7.7 × 10−4, odds ratio = 2.78) maps to 15q21.3 and overlaps a noncoding enhancer element that contains multiple activator protein 1 (AP-1) transcription factor binding sites. Chromosome conformation capture (Hi-C) data suggested direct cis-interactions with distant genes. The second risk locus (P = 2.6 × 10−3, odds ratio = 4.8) maps to the α-1,3-mannosyl-glycoprotein 4-β-N-acetylglucosaminyltransferase C (MGAT4C) gene on 12q21.31. In vitro cell-line assays found this gene to significantly modulate cell proliferation and migration in both benign and cancer prostate cells. Furthermore, MGAT4C was significantly overexpressed in metastatic versus localized prostate cancer. These two risk associations were replicated in an independent PSA-screened cohort of 800 men (15q21.3, combined P = 0.006; 12q21.31, combined P = 0.026). These findings establish noncoding and coding germ line CNVs as significant risk factors for prostate cancer susceptibility and implicate their role in disease development and progression.

Significance of PELP1 in ER-Negative Breast Cancer Metastasis

Breast cancer metastasis is a major clinical problem. The molecular basis of breast cancer progression to metastasis remains poorly understood. PELP1 is an estrogen receptor (ER) coregulator that has been implicated as a proto-oncogene whose expression is deregulated in metastatic breast tumors and whose expression is retained in ER-negative tumors. We examined the mechanism and significance of PELP1-mediated signaling in ER-negative breast cancer progression using two ER-negative model cells (MDA-MB-231 and 4T1 cells) that stably express PELP1-shRNA. These model cells had reduced PELP1 expression (75% of endogenous levels) and exhibited less propensity to proliferate in growth assays in vitro. PELP1 downregulation substantially affected migration of ER-negative cells in Boyden chamber and invasion assays. Using mechanistic studies, we found that PELP1 modulated expression of several genes involved in the epithelial mesenchymal transition (EMT), including MMPs, SNAIL, TWIST, and ZEB. In addition, PELP1 knockdown reduced the in vivo metastatic potential of ER-negative breast cancer cells and significantly reduced lung metastatic nodules in a xenograft assay. These results implicate PELP1 as having a role in ER-negative breast cancer metastasis, reveal novel mechanism of coregulator regulation of metastasis via promoting cell motility/EMT by modulating expression of genes, and suggest PELP1 may be a potential therapeutic target for metastatic ER-negative breast cancer. Mol Cancer Res; 10(1); 25–33. ©2011 AACR.

Therapeutic Targeting of PELP1 Prevents Ovarian Cancer Growth and Metastasis

Purpose: Ovarian cancer remains a major threat to womens health, partly due to difficulty in early diagnosis and development of metastases. A critical need exists to identify novel targets that curb the progression and metastasis of ovarian cancer. In this study, we examined whether the nuclear receptor coregulator PELP1 (proline-, glutamic acid-, leucine-rich protein-1) contributes to progression and metastatic potential of ovarian cancer cells and determined whether blocking of the PELP1 signaling axis had a therapeutic effect. Experimental Design: Ovarian cancer cells stably expressing PELP1-shRNA (short hairpin RNA) were established. Fluorescent microscopy, Boyden chamber, invasion assays, wound healing, and zymography assays were performed to examine the role of PELP1 in metastasis. Expression analysis of the model cells was conducted using tumor metastasis microarray to identify PELP1 Target genes. Therapeutic potential of PELP1-siRNA in vivo was determined using a nanoliposomal formulation of PELP1-siRNA-DOPC (1,2-dioleoyl-sn-glycero-3-phosphatidylcholine) administered systemically in a xenograft model. Results: PELP1 knockdown caused cytoskeletal defects and significantly affected the migratory potential of ovarian cancer cells. Microarray analysis revealed that PELP1 affected the expression of selective genes involved in metastasis including Myc, MTA1, MMP2, and MMP9. Zymography analysis confirmed that PELP1 knockdown caused a decrease in the activation of matrix metalloproteases (MMP) 2 and MMP9. Compared with control siRNA-DOPC–treated mice, animals injected with PELP1-siRNA-DOPC had 54% fewer metastatic tumor nodules, exhibited a 51% reduction in tumor growth and an 84% reduction in ascites volume. Conclusion: The results suggest that PELP1 signaling axis is a potential druggable target and liposomal PELP1-siRNA-DOPC could be used as a novel drug to prevent or treat ovarian metastasis. Clin Cancer Res; 17(8); 2250–9. ©2011 AACR.