Search

Ductal carcinoma in situ (DCIS) is characterized by inter-tumor heterogeneity that poses a therapeutic challenge due to its unpredictable recurrence and progression to invasive breast cancer (IBC). Recent publications have implicated the crucial role of the tumor microenvironment particularly stromal differences between DCIS patients who progress to IBC (progressors) and those that do not (non-progressors). However, spatial regulation of the collagen proteome has yet to be investigated in the context of disease progression in DCIS. In this study, we hypothesized that the collagen proteome was significantly altered between DCIS and IBC and that differentiating collagen peptide signatures could be related to clinical outcomes. Our initial studies investigated collagen peptide signatures in lumpectomies (n=13) annotated as DCIS, DCIS and invasive ductal carcinoma (IDC), or IDC only. We leveraged our previously published method for spatial imaging of collagen proteomics on tissue to report collagen types and collagen post-translational modifications including 40 other extracellular matrix (ECM) proteins involved in the regulation of collagen fibers. Over 1000 peaks were found to be linked to annotated pathologies or adjacent regions. Initial comparison of DCIS to IDC lesions demonstrated 63 differentially expressed peaks between these regions by unpaired, two-tailed t-test (p< 0.001). Image segmentation of the 315,541 pixels demonstrated 16 high-level hierarchical groups designating unique spatially localized ECM proteomic groups. Notably, these groups overlaid with histopathological features and pathological annotations. Next, we investigated collagen peptide signatures in a subset of DCIS samples from the Resource of Archival Breast Tissue (RAHBT) (n=37). Samples were histologically diverse within the tissue microarrays, with cribriform, micropapillary, papillary, solid, and comedo necrosis architectural patterns. In our preliminary analysis, we found two peptide peaks that could distinguish the solid subtype (n=22) from comedo necrosis (n=4) and one peak that could discriminate between the cribriform (n=8) and solid subtype (n=22) by area under the receiver operating curve (AUROC)≥0.75 and Wilson/Brown t-test (p< 0.05). Evaluated per clinical outcome, four ECM peptides showed significantly different peak intensities in progressors with IBC recurrence (n=7) compared to non-progressors (n=26) (AUROC≥0.75; Wilson/Brown t-test p< 0.05). One peptide had significantly different peak intensities between progressors with contralateral IBC recurrence and DCIS recurrence (n=5) and non-progressors (n=26) (AUROC≥0.75; Wilson/Brown t-test p< 0.05). Overall, the data suggest that unique collagen signatures in DCIS could be useful for understanding recurrence and progression to IBC. Further investigation of the spatial distribution of the collagen proteome within DCIS pathologies and relative to clinical outcome is warranted. Citation Format: Taylor S. Hulahan, Elizabeth N. Wallace, Siri H. Strand, Graham A. Colditz, E Shelley Hwang, Robert West, Laura Spruill, Jeffrey Marks, Richard R. Drake, Peggi M. Angel. Unique Collagen Peptide Signatures between Ductal Carcinoma in Situ and Invasive Breast Cancer by Mass Spectrometry Tissue Imaging [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-21-03.

PURPOSE To examine incremental values of estrogen receptor (ER) status, body mass index (BMI), menopausal status, and a previously reported multi-gene classifier over commonly used clinical factors (i.e. age, tumor grade, comedonecrosis, surgical margins, and treatment) in predicting risk of any ipsilateral recurrence (IR) event within five years after DCIS diagnosis. METHODS A derivation cohort consisted of participants in the Translational Breast Cancer Research Consortium (TBCRC) 038, a retrospective multicenter cohort study in women undergoing surgical resection for DCIS between 01/01/1998 and 02/29/2016 (n=216). The validation cohort, the Repository of Archival Human Breast Tissue (RAHBT) at Washington University School of Medicine, provided cases meeting the same eligibility criteria as TBCRC038 (n=97). Participants in both cohorts had RNA-seq data and either developed IR 1-5y after initial DCIS diagnosis or were free from subsequent breast events for at least five years. The previously reported 812-gene classifier had been developed from a subset of the TBCRC038 samples using a negative-binomial regression model to identify differentially expressed genes in the primary tumor associated with subsequent recurrence events. This classifier has been shown to be highly correlated with 5-year invasive, DCIS, and all breast cancer events, and validated in the RAHBT cohort. Cox proportional hazards regression was used to estimate hazard ratios (HRs) of IR in the TBCRC038 cohort (76 with IR). The clinical score was developed using clinical predictors (aforementioned clinical factors and ER) and their regression coefficients from the model with the maximum predictive accuracy (e.g. c-index) and the minimum number of predictors; the summary score integrated the clinical score and multi-gene classifier. Predictive performance of both clinical and summary scores was validated in the RAHBT cohort (20 with IR). RESULTS In the TBCRC cohort derivation set, we used a multivariable model based on clinical factors alone (clinical score) and found that ER status, but not BMI or menopausal status, was independently associated with a higher IR risk (HR=2.06, 95% CI 1.18-3.58). Adding the multi-gene classifier to the clinical factors-based model (summary score) in the TBCRC038 test set increased predictive accuracy (c-index 0.68 to 0.70), with the genomic classifier-adjusted HR of 14.96 (95% CI 8.64-25.91). The summary score had higher predictive performance for IR risk than clinical score alone (c-index 0.82 vs. 0.70). In the RAHBT validation samples, model performance was similarly improved using summary scores clinical factors-based model plus multigene classifier as compared to clinical scores along (c-index 0.74 vs. 0.58). CONCLUSION Combining clinical factors and a multigene classifier provided more accurate risk estimates of IR within five years after excision of DCIS than clinical factors alone. Figure 1. Observed and predicted recurrence-free survival in the first five years after initial DCIS diagnosis in the RAHBT validation cohort, by risk groups defined by clinical scores (left) and clinical score plus multigene classifier (right). Citation Format: Ying Liu, Siri H. Strand, Lorraine King, Bryan Harmon, Fergus J. Couch, Kristalyn Gallagher, Mark Kilgore, Shi Wei, Angela DeMichele, Tari King, Priscilla F. McAuliffe, Jeffrey Marks, Carlo Maley, Robert West, E Shelley Hwang, Graham A. Colditz. Using clinical characteristics and molecular markers to predict the risk of subsequent ipsilateral breast events after excision of DCIS [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-07-02.

Background. DCIS consists of a molecularly heterogeneous group of premalignant lesions, with variable risk of invasive progression. Understanding biomarkers for invasive progression could help individualize treatment recommendations based upon tumor biology. As part of the NCI Human Tumor Atlas Network (HTAN), we conducted comprehensive genomic analyses on two large DCIS case-control cohorts. Methods. We performed smart3-seq and low-pass whole genome sequencing on two independent, retrospective, longitudinally sampled DCIS case-control cohorts. TBCRC 038 was a multicenter cohort diagnosed with DCIS between 1998 and 2016 at one of the Translational Breast Cancer Research sites; the RAHBT (Resource of Archival Human Breast Tissue) cohort included women identified through the St. Louis Breast Tissue Repository, and the Women’s Health Repository diagnosed between 1997 and 2001. We studied the spectrum of molecular changes present and sought genomic predictors of subsequent ipsilateral breast events (iBEs: DCIS recurrence or invasive progression) in both DCIS epithelium and stroma in formalin fixed paraffin embedded tissue. We generated de novo tumor and stroma-centric subtypes for DCIS that represents fundamental transcriptomic organization. Copy number analysis was performed using low-pass DNA sequencing. Non-negative matrix factorization (NMF) was applied to the RNA expression of all coding genes to identify clusters. A negative-binomial regression model was used to identify differentially expressed genes. Results. We analyzed 677 DCIS samples from 481 patients with 7.1 years median follow-up. In TBCRC samples, we identified three clusters via NMF in TBCRC referred to as ER low, quiescent, and ER high. The ER-low cluster had significantly higher levels of ERBB2 and lower levels of ESR1 compared to quiescent and ER-high clusters. Quiescent cluster lesions were less proliferative and less metabolically active than ER high and ER low subtypes. These findings were replicated in the RAHBT cohort. Focusing on the stromal component of DCIS from laser capture microdissection in RAHBT samples, we identified four distinct DCIS-associated stromal clusters. A “normal-like” stromal cluster with ECM organization and PI3K-AKT signaling; a “collagen-rich” stromal cluster; a “desmoplastic” stromal cluster with high fibroblast and total myeloid abundance, mostly associated with macrophages and myeloid dendritic cells (mDC); and an “immune-dense” stromal cluster. Further, we compared differentially expressed genes in patients with or without subsequent iBEs within 5 years of diagnosis. Hypothesizing that the resulting 812 DE genes (DESeq2) represent multiple routes to subsequent iBEs, we leveraged NMF to identify paths to progression. In both TBCRC and RAHBT cohorts, poor outcome groups exhibited increased ER, MYC signaling, and oxidative phosphorylation, supporting that these pathways are important for DCIS recurrence and progression. Conclusion. Comprehensive genomic profiling in two independent DCIS cohorts with longitudinal outcomes shows distinct DCIS stromal expression patterns and immune cell composition. RNA expression profiles reveal underlying tumor biology that is associated with later iBEs in both cohorts. These studies provide new insight into DCIS biology and will guide the design of diagnostic strategies to prevent invasive progression. Citation Format: Siri H Strand, Belén Rivero-Gutiérrez, Kathleen E Houlahan, Jose A Seoane, Lorraine M King, Tyler Risom, Lunden Simpson, Sujay Vennam, Aziz Khan, Timothy Hardman, Bryan E Harmon, Fergus J Couch, Kristalyn Gallagher, Mark Kilgore, Shi Wei, Angela DeMichele, Tari King, Priscilla F McAuliffe, Julie Nangia, Joanna Lee, Jennifer Tseng, Anna Maria Storniolo, Alastair Thompson, Gaorav Gupta, Robyn Burns, Deborah J Veis, Katherine DeSchryver, Chunfang Zhu, Magdalena Matusiak, Jason Wang, Shirley X Zhu, Jen Tappenden, Daisy Yi Ding, Dadong Zhang, Jingqin Luo, Shu Jiang, Sushama Varma, Cody Straub, Sucheta Srivastava, Christina Curtis, Rob Tibshirani, Robert Michael Angelo, Allison Hall, Kouros Owzar, Kornelia Polyak, Carlo Maley, Jeffrey R Marks, Graham A Colditz, E Shelley Hwang, Robert B West. The Breast PreCancer Atlas DCIS genomic signatures define biology and correlate with clinical outcomes: An analysis of TBCRC 038 and RAHBT cohorts [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr GS4-07.

Ductal carcinoma in situ; Tumor microenvironment; Whole genome sequencing Carcinoma ductal in situ; Microambiente tumoral; Secuenciación del genoma completo Carcinoma ductal in situ; Microambient tumoral; Seqüenciació del genoma complet Ductal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We perform multiscale, integrated molecular profiling of DCIS with clinical outcomes by analyzing 774 DCIS samples from 542 patients with 7.3 years median follow-up from the Translational Breast Cancer Research Consortium 038 study and the Resource of Archival Breast Tissue cohorts. We identify 812 genes associated with ipsilateral recurrence within 5 years from treatment and develop a classifier that predicts DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions are identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome. This publication is part of the HTAN (Human Tumor Atlas Network) Consortium paper package. A list of HTAN members is available at humantumoratlas.org/htan-authors/. R01 CA185138-01 (E.S.H.); U2C CA-17-035 Pre-Cancer Atlas (PCA) Research Centers (E.S.H., R.B.W., C.M., K.P., G.A.C., K.O.); UO1 CA214183 (J.R.M.); DOD BC132057 (E.S.H., C.M.); BCRF 19-074 (E.S.H.); BCRF 19-028 (G.A.C.); PRECISION CRUK Grand Challenge (E.S.H.); R01CA193694 (R.B.W., G.A.C.), BCRF PPI-18-006 (R.B.W.). AEI RYC2019- 026576-I, "LaCaixa" Foundation LCF/PR/PR17/51120011 (J.A.S.). S.H.S. was supported by the Lundbeck Foundation (R288-2018-35) and the Danish Cancer Society (R229-A13616). K.E.H. was supported by a CIHR Banting Postdoctoral Fellowship. TBCRC 038 was conducted by the TBCRC, which receives major funding support from The Breast Cancer Research Foundation and Susan G. Komen. Some results in this paper are based upon data generated by the TCGA Research Network.

Available tools for prostate cancer (PC) prognosis are suboptimal but may be improved by better knowledge about genes driving tumor aggressiveness. Here, we identified FRMD6 (FERM domain-containing protein 6) as an aberrantly hypermethylated and significantly downregulated gene in PC. Low FRMD6 expression was associated with postoperative biochemical recurrence in two large PC patient cohorts. In overexpression and CRISPR/Cas9 knockout experiments in PC cell lines, FRMD6 inhibited viability, proliferation, cell cycle progression, colony formation, 3D spheroid growth, and tumor xenograft growth in mice. Transcriptomic, proteomic, and phospho-proteomic profiling revealed enrichment of Hippo/YAP and c-MYC signaling upon FRMD6 knockout. Connectivity Map analysis and drug repurposing experiments identified pyroxamide as a new potential therapy for FRMD6 deficient PC cells. Finally, we established orthotropic Frmd6 and Pten, or Pten only (control) knockout in the ROSA26 mouse prostate. After 12 weeks, Frmd6/Pten double knockouts presented high-grade prostatic intraepithelial neoplasia (HG-PIN) and hyperproliferation, while Pten single-knockouts developed only regular PIN lesions and displayed lower proliferation. In conclusion, FRMD6 was identified as a novel tumor suppressor gene and prognostic biomarker candidate in PC.

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.

Purpose: To examine incremental values of estrogen receptor (ER) status, body mass index (BMI), menopausal status, and a multi-gene classifier over commonly used clinical factors (i.e. age, tumor grade, comedonecrosis, surgical margins, and treatment) in predicting risk of ipsilateral recurrence (IR) within five years after DCIS diagnosis. Methods: A derivation cohort consisted of participants in the discovery cohort, a retrospective multicenter cohort study in women undergoing surgical resection for DCIS between 01/01/1998 and 02/29/2016. The validation cohort provided cases meeting the same eligibility criteria as the discovery cohort. This analysis includes 313 participants with RNA-seq data who either developed IR 1-5 years after initial DCIS diagnosis or were free from subsequent breast events at least five years. Cox proportional hazards regression was used to estimate hazard ratios (HRs) of IR in 216 TBCRC participants (76 with IR). We developed the clinical score using clinical predictors (aforementioned clinical factors and ER) and their regression coefficients from the model with the maximum predictive accuracy (e.g. c-index) and the minimum number of predictors, and the summary score integrating the clinical score and multi-gene classifier. Predictive performance of clinical and summary scores was validated in 97 RAHBT patients (20 with IR). Results: In the discovery cohort, ER negativity, but not BMI or menopausal status, was independently associated with a higher IR risk (HR=2.06, 95% CI 1.18-3.58), and adding ER to the clinical factors-based model increased predictive accuracy (c-index 0.68 to 0.70). The clinical score-adjusted HR was 14.96 (95% CI 8.64-25.91) for multi-gene classifier. Summary scores were better in predicting IR risk than clinical scores (c-index 0.82 vs. 0.70). Compared with their low-risk counterparts, the HR was 4.79 (95% CI 2.55-8.98) in the clinical score-defined high-risk group and 29.02 (95% CI 14.23-59.15) in the summary score-defined high-risk group. In the validation cohort, model performance was improved using summary scores as compared to clinical scores (c-index 0.74 vs. 0.58). Conclusion: Combination of clinical factors and multigene classifier provided more accurate risk estimates of IR within five years after excision of DCIS than clinical factors alone. Citation Format: Graham A. Colditz, Ying Liu, Siri H. Strand, Lorraine King, Jeff Marks, Carlo Maley, Robert B. West, E. Shelley Hwang. Using clinical characteristics and molecular markers to predict the risk of subsequent ipsilateral breast events after excision of DCIS [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr A012.

Identifying distinct biomarkers of DCIS and determining the invasive potential of DCIS are of great clinical importance. N-linked glycans present on the cell surface of DCIS lesions and surrounding stroma are potential biomarkers of disease and tissue, but remain largely unexplored. An N-glycan targeted imaging mass spectrometry (IMS) approach was initiated to identify N-glycans associated with DCIS and progression in clinical FFPE tissues. A cohort of pathologist annotated DCIS and IDC tissues with a range of disease severity as well as the RAHBT TMA DCIS cohort were evaluated. The RAHBT cohort contains primary DCIS lesions with known long-term outcomes and serves as a good sample set to identify early markers indicating progressive potential, while the DCIS and IDC large tissue biopsies provide information on distinct glycan profiles when DCIS has progressed to IDC. Initially, tissue samples containing DCIS alone or both DCIS and IDC were processed for N-glycan MALDI-IMS analysis, the goal being to establish a consensus panel of each analyte and determine distinct profiles of DCIS when alone vs. when IDC was present. For N-glycans, a peak list of 54 N-glycans was selected for evaluation of each DCIS only tissue, as well as the mixed DCIS/IDC tissues. By highest intensity, the major DCIS-associated glycans were in the high-mannose and paucimannose structure categories. Additionally, a series of tri- and tetra-antennary multi-fucosylated glycans were also detected specifically in the DCIS lesions. In tissues containing both IDC and DCIS lesions, the high mannose glycans were also detected in the IDC regions, and GlcNAc-bisected glycans were seen elevated in these as compared to DCIS-only tissues. For samples in the RAHBT TMA cohort (progressors N=43; non-progressors N=78), the bisected N-glycans seen elevated with IDC were also seen to be significantly increased in the RAHBT samples that would eventually progress to IDC. Additional analyses to evaluate N-glycan isomer distributions for fucosylated and sialylated glycan species are also ongoing. The cumulative N-glycan data will be assessed with the extensive spatial genomic, transcriptomic and immunohistological data already generated for the same samples in the RAHBT cohort. This novel combination of multi-enzymatic digests with histopathology annotations represents an extensive multi-dimensional profile of DCIS and a novel tissue biomarker discovery approach. Citation Format: Elizabeth N. Wallace, Grace Grimsley, Siri H. Strand, Robert Michael Angelo, Graham Colditz, E. Shelley Hwang, Robert West, Jeffrey R. Marks, Peggi M. Angel, Richard R. Drake. Characterizing N-glycan profiles of DCIS progression using tissue imaging MALDI mass spectrometry [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr PR010.

Ductal carcinoma in situ (DCIS) is characterized by inter-tumor heterogeneity that poses a therapeutic challenge due to its unpredictable recurrence and progression to invasive breast cancer (IBC). In recent publications, collagen stromal differences have been reported between patients that progressed to IBC (progressors) and those that did not (non-progressors). However, details on the role spatial regulation of the collagen proteome might play in this progression have yet to be studied. Here, we investigated the pathological distribution of collagen post-translational modifications in a cohort of patients classified as progressors with ipsilateral IBC recurrence compared to non-progressors. Previously published methods for collagen proteomics by targeted tissue mass spectrometry imaging were used. The method reports collagen types and post-translational modifications within the collagen triple-helical region as well as approximately 40 other extracellular matrix (ECM) proteins involved in the regulation of collagen fibers. Initial studies investigated collagen variation in lumpectomies (n=7) with DCIS, DCIS plus invasive ductal carcinoma (IDC) or IDC only. Over 590 peptides were found to be linked to annotated pathologies. A preliminary comparison of DCIS (n=2392 spectra) to IBC (n=4696 spectra) using area under the receiver operating curve (AUROC) ≥0.85 demonstrated that 47 peptides could individually discriminate between DCIS and IBC in this limited cohort. Image segmentation of the 405,652 pixels demonstrated 11 high-level hierarchical groups designating unique spatially localized ECM proteomic groups; these groups overlaid with histopathological features and pathological annotations. A total of 87 samples from the Resource of Archival Breast Tissue (RAHBT) matched with clinical characteristics were also investigated. Cores were histologically diverse within the tissue microarrays, with cribriform, micropapillary, papillary, solid, and comedo necrosis architectural patterns. Initial results suggest certain peptides may differentiate between non-progressors and progressors with ipsilateral IBC recurrence. Our current work focuses on correlating collagen signatures to mixed pathologies and the cellular content of cores. Further investigation of the collagen proteome is warranted. Overall, the data suggest unique collagen signatures in DCIS that could be useful for understanding recurrence and progression to IBC. Citation Format: Taylor S. Hulahan, Elizabeth N. Wallace, Siri H. Strand, Robert Michael Angelo, Graham Colditz, Eun-Sil Shelley Hwang, Robert West, Laura Spruill, Jeffrey R. Marks, Richard R. Drake, Peggi M. Angel. Discrete regulation of the collagen proteome among pathological features in DCIS and invasive breast cancer by mass spectrometry tissue imaging [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr B019.

miR-615-3p has previously been described as up-regulated in prostate cancer (PC) tissue samples compared with nonmalignant controls; however, its prognostic potential and functional role in PC remain largely unknown. In this study, we investigated the clinical and biological relevance of miR-615-3p in PC. The expression of miR-615-3p was measured in PC tissue specimens from 239 men who underwent radical prostatectomy (RP), and it was investigated if miR-615-3p could predict postoperative biochemical recurrence (BCR). These findings were subsequently validated in three independent RP cohorts (n = 222, n = 273, and n = 387) and functional overexpression studies conducted in PC cells (PC3M). High miR-615-3p expression was significantly associated with BCR in four independent PC patient cohorts (P < 0.05, log-rank test). In addition, high miR-615-3p expression was a significant predictor of PC-specific survival in univariate (hazard ratio, 3.75; P < 0.001) and multivariate (hazard ratio, 2.66; P = 0.008) analysis after adjustment for the Cancer of the Prostate Risk Assessment Post-Surgical (CAPRA-S) nomogram in a merged RP cohort (n = 734). Moreover, overexpression of miR-615-3p in PC cells (PC3M) significantly increased cell viability, proliferation, apoptosis, and migration. Together, our results suggest that miR-615-3p is a significant predictor of postoperative BCR and PC-specific survival and has oncogenic functions in PC cells.

SUMMARYDuctal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We have performed the first multiscale, integrated profiling of DCIS with clinical outcomes by analyzing 677 DCIS samples from 481 patients with 7.1 years median follow-up from the Translational Breast Cancer Research Consortium (TBCRC) 038 study and the Resource of Archival Breast Tissue (RAHBT) cohorts. We identified 812 genes associated with ipsilateral recurrence within 5 years from treatment and developed a classifier that was predictive of DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions were identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome.HIGHLIGHTS⍰ Development of a new classifier for DCIS recurrence or progression⍰ Outcome associated pathways identified across multiple data types and compartments⍰ Four stroma-specific signatures identified⍰ CNAs characterize DCIS subgroups associated with high risk invasive cancers

Ductal carcinomain situ(DCIS) is a pre-invasive lesion that is thought to be a precursor to invasive breast cancer (IBC). To understand how the tumor microenvironment (TME) changes with transition to IBC, we used Multiplexed Ion Beam Imaging by time of flight (MIBI-TOF) and a 37-plex antibody staining panel to analyze 140 clinically annotated surgical resections covering the full spectrum of breast cancer progression. We compared normal, DCIS, and IBC tissues using machine learning tools for multiplexed cell segmentation, pixel-based clustering, and object morphometrics. Transition from DCIS to IBC was found to occur along a trajectory marked by coordinated shifts in location and function of myoepithelium, fibroblasts, and infiltrating immune cells in the surrounding stroma. Taken together, this comprehensive study within the HTAN Breast PreCancer Atlas offers insight into the etiologies of DCIS, its transition to IBC, and emphasizes the importance of the TME stroma in promoting these processes.

Ductal carcinoma in situ (DCIS) is the most commonly diagnosed precursor of invasive breast cancer (IBC), with variable propensity for progression. We have performed the first multiscale, integrated profiling of DCIS with clinical outcomes to identify predictors of subsequent ipsilateral breast events. We analyzed 677 DCIS samples from 481 patients with 7.1 years median follow-up from two independent cohorts. We made observations on DNA, RNA, and protein expression, and generated a de novo clustering scheme for DCIS that represents the fundamental transcriptomic organization at this early stage of breast neoplasia. Distinct DCIS stromal expression patterns and immune cell compositions were identified. We also found RNA expression patterns that correlate with later events in both cohorts. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome.

Novel and minimally-invasive prostate cancer (PCa)-specific biomarkers are needed to improve diagnosis and risk stratification. Here, we investigated the biomarker potential in localized and de novo metastatic PCa (mPCa) of methylated circulating tumor DNA (ctDNA) in plasma. Using the Marmal-aid database and in-house datasets, we identified three top candidates specifically hypermethylated in PCa tissue: DOCK2, HAPLN3, and FBXO30 (specificity/sensitivity: 80%&ndash, 100%/75&ndash, 94%). These candidates were further analyzed in plasma samples from 36 healthy controls, 61 benign prostatic hyperplasia (BPH), 102 localized PCa, and 65 de novo mPCa patients using methylation-specific droplet digital PCR. Methylated ctDNA for DOCK2/HAPLN3/FBXO30 was generally not detected in healthy controls, BPH patients, nor in patients with localized PCa despite a positive signal in 98%&ndash, 100% of matched radical prostatectomy tissue samples. However, ctDNA methylation of DOCK2, HAPLN3, and/or FBXO30 was detected in 61.5% (40/65) of de novo mPCa patients and markedly increased in high- compared to low-volume mPCa (89.3% (25/28) vs. 32.1% (10/31), p &lt, 0.001). Moreover, detection of methylated ctDNA was associated with significantly shorter time to progression to metastatic castration resistant PCa, independent of tumor-volume. These results indicate that methylated ctDNA (DOCK2/HAPLN3/FBXO30) may be potentially useful for identification of hormone-na&iuml, ve mPCa patients who could benefit from intensified treatment.

SUMMARY Ductal carcinoma in situ (DCIS) is a pre-invasive lesion that is thought to be a precursor to invasive breast cancer (IBC). To understand the changes in the tumor microenvironment (TME) accompanying transition to IBC, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) and a 37-plex antibody staining panel to interrogate 79 clinically annotated surgical resections using machine learning tools for cell segmentation, pixel-based clustering, and object morphometrics. Comparison of normal breast with patient-matched DCIS and IBC revealed coordinated transitions between four TME states that were delineated based on the location and function of myoepithelium, fibroblasts, and immune cells. Surprisingly, myoepithelial disruption was more advanced in DCIS patients that did not develop IBC, suggesting this process could be protective against recurrence. Taken together, this HTAN Breast PreCancer Atlas study offers insight into drivers of IBC relapse and emphasizes the importance of the TME in regulating these processes., In brief A spatial imaging atlas of patient-matched ductal carcinoma in situ and invasive breast cancer depicts coordinated changes in the tumor microenviroment associated with invasive relapse, suggesting a potential protective role of myoepithelial disruption against invasive progression., Graphical Abstract

Background New molecular biomarkers for prostate cancer (PC) prognosis are urgently needed. Ratio-based models are attractive, as they require no additional normalization. Here, we train and independently validate a novel 4-miRNA prognostic ratio model for PC. Patients and methods By genome-wide miRNA expression profiling of PC tissue samples from 123 men who underwent radical prostatectomy (RP) (PCA123, training cohort), we identified six top candidate prognostic miRNAs and systematically tested their ability to predict postoperative biochemical recurrence (BCR). The best miRNA-based prognostic ratio model (MiCaP) was validated in two independent cohorts (PCA352 and PCA476) including >800 RP patients in total. Clinical end points were BCR and prostate cancer-specific survival (CSS). The prognostic potential of MiCaP was assessed by univariate and multivariate Cox-regression analyses and Kaplan–Meier analyses. Results We identified a 4-miRNA ratio model, MiCaP (miR-23a-3p×miR-10b-5p)/(miR-133a×miR-374b-5p), that predicted time to BCR independently of routine clinicopathologic variables in the training cohort (PCA123) and was successfully validated in two independent RP cohorts. In addition, MiCaP was a significant predictor of CSS in univariate analysis [HR 3.35 (95% CI 1.34−8.35), P=0.0096] and in multivariate analysis [HR 2.43 (95% CI 1.45–4.07), P=0.0210]. As proof-of-principle, we also analyzed MiCaP in plasma samples from 111 RP patients. A high MiCaP score in plasma was significantly associated with BCR (P=0.0036, Kaplan–Meier analysis). Limitations include low mortality rates (CSS: 5.4%). Conclusions We identified a novel 4-miRNA ratio model (MiCaP) with significant independent prognostic value in three RP cohorts, indicating promising potential to improve PC risk stratification.

INTRODUCTION AND OBJECTIVES:Discovery of biomarkers could refine treatment of and follow-up programs for men with prostate cancer (PCa). Validation of potential biomarkers for PCa aggressiveness is...

Prostate cancer (PCa) is a clinically heterogeneous disease and currently, accurate diagnostic and prognostic molecular biomarkers are lacking. This study aimed to identify novel DNA hypermethylation markers for PCa with future potential for blood-based testing. Accordingly, to search for genes specifically hypermethylated in PCa tissue samples and not in blood cells or other cancer tissue types, we performed a systematic analysis of genome-wide DNA methylation data (Infinium 450K array) available in the Marmal-aid database for 4072 malignant/normal tissue samples of various types. We identified eight top candidate markers (cg12799885, DOCK2, FBXO30, GRASP, HIF3A, MOB3B, PFKP, and TPM4) that were specifically hypermethylated in PCa tissue samples and hypomethylated in other benign and malignant tissue types, including in peripheral blood cells. Potential as diagnostic and prognostic biomarkers was further assessed by the quantitative methylation specific PCR (qMSP) analysis of 37 nonmalignant and 197 PCa tissue samples from an independent population. Here, all eight hypermethylated candidates showed high sensitivity (75&ndash, 94%) and specificity (84&ndash, 100%) for PCa. Furthermore, DOCK2, GRASP, HIF3A and PKFP hypermethylation was significantly associated with biochemical recurrence (BCR) after radical prostatectomy (RP, 197 patients), independent of the routine clinicopathological variables. DOCK2 is the most promising single candidate marker (hazard ratio (HR) (95% confidence interval (CI)): 1.96 (1.24&ndash, 3.10), adjusted p = 0.016, multivariate cox regression). Further validation studies are warranted and should investigate the potential value of these hypermethylation candidate markers for blood-based testing also.

This study aimed to validate whether 5-hydroxymethylcytosine (5hmC) level in combination with ERG expression is a predictive biomarker for biochemical failure (BF) in men undergoing radical prostatectomy (RP) for prostate cancer (PCa). The study included 592 PCa patients from two consecutive Danish RP cohorts. 5hmC level and ERG expression were analyzed using immunohistochemistry in RP specimens. 5hmC was scored as low or high and ERG was scored as negative or positive. Risk of BF was analyzed using stratified cumulative incidences and multiple cause-specific Cox regression using competing risk assessment. Median follow-up was 10 years (95% CI: 9.5&ndash, 10.2). In total, 246 patients (41.6%) had low and 346 patients (58.4%) had high 5hmC level. No significant association was found between 5hmC level or ERG expression and time to BF (p = 0.2 and p = 1.0, respectively). However, for men with ERG negative tumors, high 5hmC level was associated with increased risk of BF following RP (p = 0.01). In multiple cause-specific Cox regression analyses of ERG negative patients, high 5hmC expression was associated with time to BF (HR: 1.8, 95% CI: 1.2&ndash, 2.7, p = 0.003). In conclusion, high 5hmC level was correlated with time to BF in men with ERG negative PCa, which is in accordance with previous results.

Improved prognostic biomarkers are needed to guide personalized prostate cancer (PC) treatment decisions. Due to the prominent molecular heterogeneity of PC, multimarker panels may be more robust. Here, 25 selected top-candidate miRNA and methylation markers for PC were profiled by qPCR in malignant radical prostatectomy (RP) tissue specimens from 198 PC patients (Cohort 1, training). Using GLMnet, we trained a novel multimarker model (miMe) comprising nine miRNAs and three methylation markers that predicted postoperative biochemical recurrence (BCR) independently of the established clinicopathological CAPRA-S nomogram in Cox multivariate regression analysis in Cohort 1 (HR [95% CI]: 1.53 [1.26-1.84], p < 0.001). This result was successfully validated in two independent RP cohorts (Cohort 2, n = 159: HR [95% CI]: 1.35 [1.06-1.73], p = 0.015. TCGA, n = 350: HR [95% CI]: 1.34 [1.01-1.77], p = 0.04). Notably, in CAPRA-S low-risk patients, a high miMe score was associated with >6 times higher risk of BCR, suggesting that miMe may help identify PC patients at high risk of progression despite favorable clinicopathological factors postsurgery. Finally, miMe was a significant predictor of cancer-specific survival (p = 0.019, log-rank test) in a merged analysis of 357 RP patients. In conclusion, we trained, tested and validated a novel 12-marker panel (miMe) that showed significant independent prognostic value in three RP cohorts. In the future, combining miMe score with existing clinical nomograms may improve PC risk stratification and thus help guide treatment decisions.

// Siri H. Strand 1 , Michal Switnicki 1 , Mia Moller 1 , Christa Haldrup 1 , Tine M. Storebjerg 1,2,3 , Jakob Hedegaard 1 , Iver Nordentoft 1 , Soren Hoyer 2 , Michael Borre 3 , Jakob S. Pedersen 1 , Peter J. Wild 4 , Jong Y. Park 5 , Torben F. Orntoft 1 and Karina D. Sorensen 1 1 Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark 2 Institute of Pathology, Aarhus University Hospital, Aarhus, Denmark 3 Department of Urology, Aarhus University Hospital, Aarhus, Denmark 4 Institute of Surgical Pathology, University Hospital Zurich, Zurich, Switzerland 5 Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida, USA Correspondence to: Karina D. Sorensen, email: // Keywords : prostate cancer, DNA methylation, biomarker, diagnosis, prognosis Received : December 14, 2016 Accepted : December 18, 2016 Published : December 30, 2016 Abstract Purpose: The lack of biomarkers that can distinguish aggressive from indolent prostate cancer has caused substantial overtreatment of clinically insignificant disease. Here, by genome-wide DNA methylome profiling, we sought to identify new biomarkers to improve the accuracy of prostate cancer diagnosis and prognosis. Experimental design: Eight novel candidate markers, COL4A6, CYBA, TCAF1 ( FAM115A ) , HLF, LINC01341 ( LOC149134 ), LRRC4 , PROM1 , and RHCG , were selected from Illumina Infinium HumanMethylation450 BeadChip analysis of 21 tumor (T) and 21 non-malignant (NM) prostate specimens. Diagnostic potential was further investigated by methylation-specific qPCR analysis of 80 NM vs. 228 T tissue samples. Prognostic potential was assessed by Kaplan-Meier, uni- and multivariate Cox regression analysis in 203 Danish radical prostatectomy (RP) patients (cohort 1), and validated in an independent cohort of 286 RP patients from Switzerland and the U.S. (cohort 2). Results: Hypermethylation of the 8 candidates was highly cancer-specific (area under the curves: 0.79-1.00). Furthermore, high methylation of the 2-gene panel RHCG-TCAF1 was predictive of biochemical recurrence (BCR) in cohort 1, independent of the established clinicopathological parameters Gleason score, pathological tumor stage, and pre-operative PSA (HR (95% confidence interval (CI)): 2.09 (1.26 - 3.46); P = 0.004), and this was successfully validated in cohort 2 (HR (95% CI): 1.81 (1.05 - 3.12); P = 0.032). Conclusion: Methylation of the RHCG-TCAF1 panel adds significant independent prognostic value to established prognostic parameters for prostate cancer and thus may help to guide treatment decisions in the future. Further investigation in large independent cohorts is necessary before translation into clinical utility.

Prostate cancer (PCa) is a clinically heterogeneous disease and currently, accurate diagnostic and prognostic molecular biomarkers are lacking. This study aimed to identify novel DNA hypermethylation markers for PCa with future potential for blood-based testing. Accordingly, to search for genes specifically hypermethylated in PCa tissue samples and not in blood cells or other cancer tissue types, we performed a systematic analysis of genome-wide DNA methylation data (Infinium 450K array) available in the Marmal-aid database for 4072 malignant/normal tissue samples of various types. We identified eight top candidate markers (cg12799885, DOCK2, FBXO30, GRASP, HIF3A, MOB3B, PFKP, and TPM4) that were specifically hypermethylated in PCa tissue samples and hypomethylated in other benign and malignant tissue types, including in peripheral blood cells. Potential as diagnostic and prognostic biomarkers was further assessed by the quantitative methylation specific PCR (qMSP) analysis of 37 nonmalignant and 197 PCa tissue samples from an independent population. Here, all eight hypermethylated candidates showed high sensitivity (75–94%) and specificity (84–100%) for PCa. Furthermore, DOCK2, GRASP, HIF3A and PKFP hypermethylation was significantly associated with biochemical recurrence (BCR) after radical prostatectomy (RP; 197 patients), independent of the routine clinicopathological variables. DOCK2 is the most promising single candidate marker (hazard ratio (HR) (95% confidence interval (CI)): 1.96 (1.24–3.10), adjusted p = 0.016; multivariate cox regression). Further validation studies are warranted and should investigate the potential value of these hypermethylation candidate markers for blood-based testing also.

BACKGROUND: The current inability to predict whether a primary prostate cancer (PC) will progress to metastatic disease leads to overtreatment of indolent PCs as well as undertreatment of aggressive PCs. Here, we explored the transcriptional changes associated with metastatic progression of multifocal hormone-naive PC.METHODS: Using total RNA-sequencing, we analysed laser micro-dissected primary PC foci (n = 23), adjacent normal prostate tissue samples (n = 23) and lymph node metastases (n = 9) from ten hormone-naive PC patients. Genes important for PC progression were identified using differential gene expression and clustering analysis. From these, two multi-gene-based expression signatures (models) were developed, and their prognostic potential was evaluated using Cox-regression and Kaplan-Meier analyses in three independent radical prostatectomy (RP) cohorts (>650 patients).RESULTS: We identified several novel PC-associated transcripts deregulated during PC progression, and these transcripts were used to develop two novel gene-expression-based prognostic models. The models showed independent prognostic potential in three RP cohorts (n = 405, n = 107 and n = 91), using biochemical recurrence after RP as the primary clinical endpoint.CONCLUSIONS: We identified several transcripts deregulated during PC progression and developed two new prognostic models for PC risk stratification, each of which showed independent prognostic value beyond routine clinicopathological factors in three independent RP cohorts.

Current diagnostic and prognostic tools for prostate cancer (PC) are suboptimal, leading to overdiagnosis and overtreatment. Aberrant promoter hypermethylation of specific genes has been suggested as novel candidate biomarkers for PC that may improve diagnosis and prognosis. We here analyzed ST6GALNAC3 and ZNF660 promoter methylation in prostate tissues, and ST6GALNAC3, ZNF660, CCDC181, and HAPLN3 promoter methylation in liquid biopsies. First, using four independent patient sample sets, including a total of 110 nonmalignant (NM) and 705 PC tissue samples, analyzed by methylation-specific qPCR or methylation array, we found that hypermethylation of ST6GALNAC3 and ZNF660 was highly cancer-specific with areas under the curve (AUC) of receiver operating characteristic (ROC) curve analysis of 0.917-0.995 and 0.846-0.903, respectively. Furthermore, ZNF660 hypermethylation was significantly associated with biochemical recurrence in two radical prostatectomy (RP) cohorts of 158 and 392 patients and remained significant also in the subsets of patients with Gleason score ≤7 (univariate Cox regression and log-rank tests, P < 0.05), suggesting that ZNF660 methylation analysis can potentially help to stratify low-/intermediate-grade PCs into indolent vs. more aggressive subtypes. Notably, ZNF660 hypermethylation was also significantly associated with poor overall and PC-specific survival in the RP cohort (n = 158) with long clinical follow-up available. Moreover, as proof of principle, we successfully detected highly PC-specific hypermethylated circulating tumor DNA (ctDNA) for ST6GALNAC3, ZNF660, HAPLN3, and CCDC181 in liquid biopsies (serum) from 27 patients with PC vs. 10 patients with BPH, using droplet digital methylation-specific PCR analysis. Finally, we generated a three-gene (ST6GALNAC3/CCDC181/HAPLN3) ctDNA hypermethylation model, which detected PC with 100% specificity and 67% sensitivity. In conclusion, we here for the first time demonstrate diagnostic biomarker potential of ST6GALNAC3 and ZNF660 methylation, as well as prognostic biomarker potential of ZNF660. Furthermore, we show that hypermethylation of four genes can be detected in ctDNA in liquid biopsies (serum) from patients with PC.

Background Prognostic tools for prostate cancer (PC) are inadequate and new molecular biomarkers may improve risk stratification. The epigenetic mark 5-hydroxymethylcytosine (5hmC) has recently been proposed as a novel candidate prognostic biomarker in several malignancies including PC. 5hmC is an oxidized derivative of 5-methylcytosine (5mC) and can be further oxidized to 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC). The present study is the first to investigate the biomarker potential in PC for all four DNA methylation marks in parallel. Thus, we determined 5mC, 5hmC, 5fC, and 5caC levels in non-malignant (NM) and PC tissue samples from a large radical prostatectomy (RP) patient cohort (n = 546) by immunohistochemical (IHC) analysis of serial sections of a tissue microarray. Possible associations between methylation marks, routine clinicopathological parameters, ERG status, and biochemical recurrence (BCR) after RP were investigated. Results 5mC and 5hmC levels were significantly reduced in PC compared to NM prostate tissue samples (p ≤ 0.027) due to a global loss of both marks specifically in ERG− PCs. 5fC levels were significantly increased in ERG+ PCs (p = 0.004), whereas 5caC levels were elevated in both ERG− and ERG+ PCs compared with NM prostate tissue samples (p ≤ 0.019). Positive correlations were observed between 5mC, 5fC, and 5caC levels in both NM and PC tissues (p

Prostate cancer (PC) is the most commonly diagnosed neoplasm and the third most common cause of cancer-related death amongst men in the Western world. PC is a clinically highly heterogeneous disease, and distinction between aggressive and indolent disease is a major challenge for the management of PC. Currently, no biomarkers or prognostic tools are able to accurately predict tumor progression at the time of diagnosis. Thus, improved biomarkers for PC prognosis are urgently needed. This review focuses on the prognostic potential of DNA methylation biomarkers for PC. Epigenetic changes are hallmarks of PC and associated with malignant initiation as well as tumor progression. Moreover, DNA methylation is the most frequently studied epigenetic alteration in PC, and the prognostic potential of DNA methylation markers for PC has been demonstrated in multiple studies. The most promising methylation marker candidates identified so far include PITX2, C1orf114 (CCDC181) and the GABRE~miR-452~miR-224 locus, in addition to the three-gene signature AOX1/C1orf114/HAPLN3. Several other biomarker candidates have also been investigated, but with less stringent clinical validation and/or conflicting evidence regarding their possible prognostic value available at this time. Here, we review the current evidence for the prognostic potential of DNA methylation markers in PC.

Purpose: Available tools for prostate cancer diagnosis and prognosis are suboptimal and novel biomarkers are urgently needed. Here, we investigated the regulation and biomarker potential of the GABRE∼miR-452∼miR-224 genomic locus. Experimental Design: GABRE/miR-452/miR-224 transcriptional expression was quantified in 80 nonmalignant and 281 prostate cancer tissue samples. GABRE∼miR-452∼miR-224 promoter methylation was determined by methylation-specific qPCR (MethyLight) in 35 nonmalignant, 293 prostate cancer [radical prostatectomy (RP) cohort 1] and 198 prostate cancer tissue samples (RP cohort 2). Diagnostic/prognostic biomarker potential of GABRE∼miR-452∼miR-224 methylation was evaluated by ROC, Kaplan–Meier, uni- and multivariate Cox regression analyses. Functional roles of miR-224 and miR-452 were investigated in PC3 and DU145 cells by viability, migration, and invasion assays and gene-set enrichment analysis (GSEA) of posttransfection transcriptional profiling data. Results: GABRE∼miR-452∼miR-224 was significantly downregulated in prostate cancer compared with nonmalignant prostate tissue and had highly cancer-specific aberrant promoter hypermethylation (AUC = 0.98). Functional studies and GSEA suggested that miR-224 and miR-452 inhibit proliferation, migration, and invasion of PC3 and DU145 cells by direct/indirect regulation of pathways related to the cell cycle and cellular adhesion and motility. Finally, in uni- and multivariate analyses, high GABRE∼miR-452∼miR-224 promoter methylation was significantly associated with biochemical recurrence in RP cohort 1, which was successfully validated in RP cohort 2. Conclusion: The GABRE∼miR-452∼miR-224 locus is downregulated and hypermethylated in prostate cancer and is a new promising epigenetic candidate biomarker for prostate cancer diagnosis and prognosis. Tumor-suppressive functions of the intronic miR-224 and miR-452 were demonstrated in two prostate cancer cell lines, suggesting that epigenetic silencing of GABRE∼miR-452∼miR-224 may be selected for in prostate cancer. Clin Cancer Res; 20(8); 2169–81. ©2014 AACR.

Two independent regions within HNF1B are consistently identified in prostate and ovarian cancer genome-wide association studies (GWAS); their functional roles are unclear. We link prostate cancer (PC) risk SNPs rs11649743 and rs3760511 with elevated HNF1B gene expression and allele-specific epigenetic silencing, and outline a mechanism by which common risk variants could effect functional changes that increase disease risk: functional assays suggest that HNF1B is a pro-differentiation factor that suppresses epithelial-to-mesenchymal transition (EMT) in unmethylated, healthy tissues. This tumor-suppressor activity is lost when HNF1B is silenced by promoter methylation in the progression to PC. Epigenetic inactivation of HNF1B in ovarian cancer also associates with known risk SNPs, with a similar impact on EMT. This represents one of the first comprehensive studies into the pleiotropic role of a GWAS-associated transcription factor across distinct cancer types, and is the first to describe a conserved role for a multi-cancer genetic risk factor.

Prostate cancer (PC) diagnosis is based on histological evaluation of prostate needle biopsies, which have high false negative rates. Here, we investigated if cancer-associated epigenetic field effects in histologically normal prostate tissue may be used to increase sensitivity for PC. We focused on nine genes (AOX1, CCDC181 (C1orf114), GABRE, GAS6, HAPLN3, KLF8, MOB3B, SLC18A2, and GSTP1) known to be hypermethylated in PC. Using quantitative methylation-specific PCR, we analysed 66 malignant and 134 non-malignant tissue samples from 107 patients, who underwent ultrasound-guided prostate biopsy (67 patients had at least one cancer-positive biopsy, 40 had exclusively cancer-negative biopsies). Hypermethylation was detectable for all genes in malignant needle biopsy samples (AUC: 0.80 to 0.98), confirming previous findings in prostatectomy specimens. Furthermore, we identified a four-gene methylation signature (AOX1xGSTP1xHAPLN3xSLC18A2) that distinguished histologically non-malignant biopsies from patients with vs. without PC in other biopsies (AUC = 0.65; sensitivity = 30.8%; specificity = 100%). This signature was validated in an independent patient set (59 PC, 36 adjacent non-malignant, and 9 normal prostate tissue samples) analysed on Illumina 450 K methylation arrays (AUC = 0.70; sensitivity = 40.6%; specificity = 100%). Our results suggest that a novel four-gene signature may be used to increase sensitivity for PC diagnosis through detection of epigenetic field effects in histologically non-malignant prostate tissue samples.

Background:Novel biomarkers for prostate cancer (PC) are urgently needed. This study investigates the expression, epigenetic regulation, and prognostic potential of ANPEP in PC.Methods:Aminopeptidase N (APN; encoded by ANPEP) expression was analysed by immunohistochemistry using tissue microarrays representing 267 radical prostatectomy (RP) and 111 conservatively treated (CT) PC patients. Clinical end points were recurrence-free survival (RFS) and cancer-specific survival (CSS), respectively. The ANPEP promoter methylation levels were determined by bisulphite sequencing or MethyLight analysis in 278 nonmalignant and PC tissue samples, and in cell lines.Results:The APN expression was significantly downregulated in PC compared with nonmalignant prostate tissue samples. Aberrant promoter hypermethylation was frequently observed in PC tissue samples, and 5-aza-2'-deoxycytidine induced ANPEP expression in three hypermethylated prostate cell lines, suggesting epigenetic silencing. Negative APN immunoreactivity was significantly associated with short RFS and short CSS in the RP and CT cohort, respectively, independently of routine clinicopathological predictors. Combining APN with a known angiogenesis marker (vascular endothelial growth factor or microvessel density) improved risk prediction significantly in both cohorts.Conclusion:Our results suggest negative APN immunoreactivity as a new independent adverse prognostic factor for patients with clinically localised PC and, furthermore, that epigenetic mechanisms are involved in silencing of ANPEP in PC.British Journal of Cancer advance online publication, 15 January 2013; doi:10.1038/bjc.2012.549 www.bjcancer.com.

Background: Prostate cancer (PC) can be stratified into distinct molecular subtypes based on TMPRSS2-ERG gene fusion status, but its potential prognostic value remains controversial. Likewise, routine clinicopathological features cannot clearly distinguish aggressive from indolent tumors at the time of diagnosis, thus new prognostic biomarkers are urgently needed. The DNA methylation variant 5-hydroxymethylcytosine (5hmC, an oxidized derivative of 5-methylcytosine) has recently emerged as a new diagnostic and/or prognostic biomarker candidate for several human malignancies. However, this remains to be systematically investigated for PC. In this study, we determined 5hmC levels in 311 PC (stratified by ERG status) and 228 adjacent non-malignant (NM) prostate tissue specimens by immunohistochemical analysis of a tissue microarray, representing a large radical prostatectomy (RP) cohort with long clinical follow-up. We investigated possible correlations between 5hmC and routine clinicopathological variables and assessed the prognostic potential of 5hmC by Kaplan-Meier, uni- and multivariate Cox regression analyses in ERG+ (n = 178) vs. ERG- (n = 133) PCs using biochemical recurrence (BCR) as endpoint. Results: We observed a borderline significant (p = 0.06) reduction in 5hmC levels in PC compared to NM tissue samples, which was explained by a highly significant (p Conclusions: This is the first study to demonstrate a prognostic potential for 5hmC in PC. Our findings highlight the importance of ERG stratification in PC biomarker studies, and suggest that epigenetic mechanisms involving 5hmC are important for the development and/or progression of ERG- PC. Citation Format: Siri H. Strand, Soren Hoyer, Anne-Sofie Lynnerup, Christa Haldrup, Tine M. Storebjerg, Michael Borre, Torben F. Orntoft, Karina D. Sorensen. High levels of 5-hydroxymethylcytosine (5hmC) predict biochemical recurrence after prostatectomy in ERG negative prostate cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2774.

Prostate cancer (PC) is the most common malignancy, and the second most common cause of cancer related death amongst men in the Western world. The PC biomarkers currently available are unable to distinguish between aggressive and indolent PC, causing significant over-diagnosis and over-treatment. Here, by genomewide profiling of the DNA methylome, we aimed to identify new molecular markers that can improve the accuracy of diagnosis and prognosis of PC. In total, 21 PC, 9 normal (N), and 12 adjacent normal (AN) prostate tissue samples, as well as 15 prostate (cancer) cell lines, were run on the Illumina Infinium HumanMethylation450 BeadChip, which investigates Identification of differential methylation between N and AN samples could potentially aid correct diagnosis of patients with false negative biopsies. However, only 16 probes showed significant differential methylation in N vs. AN samples (p-value We applied a Δβ cutoff value of 0.2 and a p-value of 0.05 (adjusted), which revealed 26,286 significantly differentially methylated CpG sites between PC and controls (3076 hypomethylated and 23,210 hypermethylated in PC). Global analysis showed that PC samples were hypermethylated in CpG islands (CGIs), a trend which was even more pronounced in CGI shores and shelves. Although less common overall, hypomethylation was also more prominent in shores and shelves compared to CGIs. Applying a strict Δβ cutoff value of 0.6, only 69 significantly differentially methylated CpG sites remained. Of these, 55 sites were gene associated (41 different genes), all were hypermethylated in PC samples, and all but one were located in CGIs. Out of these 41 genes, we selected 5 candidates for validation. In-house and publicly available gene expression datasets showed that at least three of the genes were downregulated in PC, consistent with silencing caused by aberrant promoter methylation. Initial validation was carried out in PC cell lines by bisulphite sequencing, which confirmed the array results for all 5 genes. We are currently validating these findings by methylation-specific qPCR analysis of a large independent patient cohort with long clinical follow-up, in order to assess the diagnostic/prognostic biomarker potential of these 5 novel candidate methylation markers. These results will be presented at the conference. Citation Format: Siri H. Strand, Michal Switnicki, Philippe Lamy, Soeren Hoeyer, Michael Borre, Jakob S. Pedersen, Torben Oerntoft, Karina D. Soerensen. Genome-wide profiling of the prostate cancer methylome for biomarker discovery. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 659. doi:10.1158/1538-7445.AM2013-659

Prostate cancer (PC) is a common malignancy and a leading cause of cancer-associated mortality among males in Western countries. Novel diagnostic and prognostic biomarkers for PC are urgently needed to prevent overdiagnosis and overtreatment of nonaggressive tumors. In this study, we investigated the biomarker potential of ANPEP in PC. ANPEP encodes a membrane-bound zinc-dependent protease termed aminopeptidase N (APN), which belongs to a group of widely expressed ectopeptidases. Expression of APN protein was determined by immunohistochemical analysis of tissue microarrays, including PC specimens from 267 radical prostatectomy (RP) patients and 199 conservatively treated (CT) patients as well as several nonmalignant prostate and metastatic PC samples. Clinical endpoints were recurrence-free survival (RFS) and cancer-specific survival (CSS), respectively. ANPEP promoter methylation was analyzed in parallel by quantitative methylation-specific PCR (qMSP/MethyLight) in approximately 250 nonmalignant and PC tissue samples. We found that APN protein expression was significantly lower in localized PC and further reduced in metastatic PC, compared to nonmalignant prostate tissue samples. Aberrant ANPEP promoter hypermethylation was observed in approximately half of all PC samples investigated. Methylation levels correlated inversely with APN immunoreactivity, suggesting that ANPEP is epigenetically silenced in PC. By multivariate analysis, negative APN immunoreactivity was significantly associated with short RFS in the RP cohort (HR=0.24; p=0.002) and with short CSS in the CT cohort (HR=0.23; p=0.049), in both cases independently of routine predictors such as Gleason score, T stage and PSA. Combining APN with a known angiogenesis marker (vascular endothelial growth factor (VEGF) immunoreactivity or microvessel density (MVD)) in a simple two-marker model improved risk prediction significantly in both cohorts. ANPEP promoter methylation did not show significant prognostic value in the RP cohort (p=0.09) and was not investigated in the CT cohort. In conclusion, our results indicate that a simple immunohistochemical test for APN may add significant prognostic value to currently used routine predictors for PC outcome. Furthermore, our findings suggest that it may be favorable to use APN in combination with an established angiogenesis marker to improve risk stratification and separate patients with clinically localized PC into low, intermediate and high risk subgroups in order to guide treatment decisions. Finally, we have identified ANPEP as a new common target for promoter hypermethylation in PC, indicating that epigenetic mechanisms contribute to downregulation of ANPEP in PC cells. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3636. doi:1538-7445.AM2012-3636

Background Prostate cancer (PC) can be stratified into distinct molecular subtypes based on TMPRSS2-ERG gene fusion status, but its potential prognostic value remains controversial. Likewise, routine clinicopathological features cannot clearly distinguish aggressive from indolent tumors at the time of diagnosis; thus, new prognostic biomarkers are urgently needed. The DNA methylation variant 5-hydroxymethylcytosine (5hmC, an oxidized derivative of 5-methylcytosine) has recently emerged as a new diagnostic and/or prognostic biomarker candidate for several human malignancies. However, this remains to be systematically investigated for PC. In this study, we determined 5hmC levels in 311 PC (stratified by ERG status) and 228 adjacent non-malignant (NM) prostate tissue specimens by immunohistochemical analysis of a tissue microarray, representing a large radical prostatectomy (RP) cohort with long clinical follow-up. We investigated possible correlations between 5hmC and routine clinicopathological variables and assessed the prognostic potential of 5hmC by Kaplan-Meier and uni- and multivariate Cox regression analyses in ERG+ (n = 178) vs. ERG− (n = 133) PCs using biochemical recurrence (BCR) as endpoint. Results We observed a borderline significant (p = 0.06) reduction in 5hmC levels in PC compared to NM tissue samples, which was explained by a highly significant (p