All Publications

  • Chromatin insulation orchestrates matrix metalloproteinase gene cluster expression reprogramming in aggressive breast cancer tumors. Molecular cancer Llinàs-Arias, P., Ensenyat-Mendez, M., Íñiguez-Muñoz, S., Orozco, J. I., Valdez, B., Salomon, M. P., Matsuba, C., Solivellas-Pieras, M., Bedoya-López, A. F., Sesé, B., Mezger, A., Ormestad, M., Unzueta, F., Strand, S. H., Boiko, A. D., Hwang, E. S., Cortés, J., DiNome, M. L., Esteller, M., Lupien, M., Marzese, D. M. 2023; 22 (1): 190


    Triple-negative breast cancer (TNBC) is an aggressive subtype that exhibits a high incidence of distant metastases and lacks targeted therapeutic options. Here we explored how the epigenome contributes to matrix metalloprotease (MMP) dysregulation impacting tumor invasion, which is the first step of the metastatic process.We combined RNA expression and chromatin interaction data to identify insulator elements potentially associated with MMP gene expression and invasion. We employed CRISPR/Cas9 to disrupt the CCCTC-Binding Factor (CTCF) binding site on an insulator element downstream of the MMP8 gene (IE8) in two TNBC cellular models. We characterized these models by combining Hi-C, ATAC-seq, and RNA-seq with functional experiments to determine invasive ability. The potential of our findings to predict the progression of ductal carcinoma in situ (DCIS), was tested in data from clinical specimens.We explored the clinical relevance of an insulator element located within the Chr11q22.2 locus, downstream of the MMP8 gene (IE8). This regulatory element resulted in a topologically associating domain (TAD) boundary that isolated nine MMP genes into two anti-correlated expression clusters. This expression pattern was associated with worse relapse-free (HR = 1.57 [1.06 - 2.33]; p = 0.023) and overall (HR = 2.65 [1.31 - 5.37], p = 0.005) survival of TNBC patients. After CRISPR/Cas9-mediated disruption of IE8, cancer cells showed a switch in the MMP expression signature, specifically downregulating the pro-invasive MMP1 gene and upregulating the antitumorigenic MMP8 gene, resulting in reduced invasive ability and collagen degradation. We observed that the MMP expression pattern predicts DCIS that eventually progresses into invasive ductal carcinomas (AUC = 0.77, p < 0.01).Our study demonstrates how the activation of an IE near the MMP8 gene determines the regional transcriptional regulation of MMP genes with opposing functional activity, ultimately influencing the invasive properties of aggressive forms of breast cancer.

    View details for DOI 10.1186/s12943-023-01906-8

    View details for PubMedID 38017545

    View details for PubMedCentralID 6745820

  • From the lab to the clinic: Lessons learned from a translational working group. Lynch, T., Basila, D., Schnitt, S. J., Marks, J. R., Strand, S. H., Hyslop, T., Badve, S. S., Watson, M. A., Le-Petross, H. T., Grimm, L., West, R. B., Weiss, A., Rapperport, A., King, L., Factor, R. E., Ryser, M. D., Partridge, A. H., Hwang, E., Thompson, A., Collyar, D. E. LIPPINCOTT WILLIAMS & WILKINS. 2023
  • Characterizing N-glycan profiles of DCIS progression using tissue imaging MALDI mass spectrometry Wallace, E. N., Grimsley, G., Strand, S. H., Angelo, R., Colditz, G., Hwang, E., West, R., Marks, J. R., Angel, P. M., Drake, R. R. AMER ASSOC CANCER RESEARCH. 2022
  • Characterizing N-glycan profiles of DCIS progression using tissue imaging MALDI mass spectrometry. Wallace, E. N., Grimsley, G., Strand, S. H., Angelo, R., Colditz, G., Hwang, E., West, R., Marks, J. R., Angel, P. M., Drake, R. R. AMER ASSOC CANCER RESEARCH. 2022: 8-9
  • A SOX9-B7x axis safeguards dedifferentiated tumor cells from immunosurveillance to enable DCIS progression Wallace, E. N., Grimsley, G., Strand, S. H., Angelo, R., Colditz, G., Hwang, E., West, R., Marks, J. R., Angel, P. M., Drake, R. R. AMER ASSOC CANCER RESEARCH. 2022
  • Discrete regulation of the collagen proteome among pathological features in DCIS and invasive breast cancer by mass spectrometry tissue imaging Hulahan, T. S., Wallace, E. N., Strand, S. H., Angelo, R., Colditz, G., Hwang, E., West, R., Spruill, L., Marks, J. R., Drake, R. R., Angel, P. M. AMER ASSOC CANCER RESEARCH. 2022
  • Discrete regulation of the collagen proteome among pathological features in DCIS and invasive breast cancer by mass spectrometry tissue imaging Hulahan, T. S., Wallace, E. N., Strand, S. H., Angelo, R., Colditz, G., Hwang, E., West, R., Spruill, L., Marks, J. R., Drake, R. R., Angel, P. M. AMER ASSOC CANCER RESEARCH. 2022
  • Using clinical characteristics and molecular markers to predict the risk of subsequent ipsilateral breast events after excision of DCIS Colditz, G. A., Liu, Y., Strand, S. H., King, L., Marks, J., Maley, C., West, R. B., Hwang, E. AMER ASSOC CANCER RESEARCH. 2022
  • Using clinical characteristics and molecular markers to predict the risk of subsequent ipsilateral breast events after excision of DCIS Colditz, G. A., Liu, Y., Strand, S. H., King, L., Marks, J., Maley, C., West, R. B., Hwang, E. AMER ASSOC CANCER RESEARCH. 2022
  • Molecular classification and biomarkers of clinical outcome in breast ductal carcinoma in situ: Analysis of TBCRC 038 and RAHBT cohorts. Cancer cell Strand, S. H., Rivero-Gutierrez, B., Houlahan, K. E., Seoane, J. A., King, L. M., Risom, T., Simpson, L. A., Vennam, S., Khan, A., Cisneros, L., Hardman, T., Harmon, B., Couch, F., Gallagher, K., Kilgore, M., Wei, S., DeMichele, A., King, T., McAuliffe, P. F., Nangia, J., Lee, J., Tseng, J., Storniolo, A. M., Thompson, A. M., Gupta, G. P., Burns, R., Veis, D. J., DeSchryver, K., Zhu, C., Matusiak, M., Wang, J., Zhu, S. X., Tappenden, J., Ding, D. Y., Zhang, D., Luo, J., Jiang, S., Varma, S., Anderson, L., Straub, C., Srivastava, S., Curtis, C., Tibshirani, R., Angelo, R. M., Hall, A., Owzar, K., Polyak, K., Maley, C., Marks, J. R., Colditz, G. A., Hwang, E. S., West, R. B. 2022


    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.

    View details for DOI 10.1016/j.ccell.2022.10.021

    View details for PubMedID 36400020

  • MITI minimum information guidelines for highly multiplexed tissue images. Nature methods Schapiro, D., Yapp, C., Sokolov, A., Reynolds, S. M., Chen, Y., Sudar, D., Xie, Y., Muhlich, J., Arias-Camison, R., Arena, S., Taylor, A. J., Nikolov, M., Tyler, M., Lin, J., Burlingame, E. A., Human Tumor Atlas Network, Chang, Y. H., Farhi, S. L., Thorsson, V., Venkatamohan, N., Drewes, J. L., Pe'er, D., Gutman, D. A., Herrmann, M. D., Gehlenborg, N., Bankhead, P., Roland, J. T., Herndon, J. M., Snyder, M. P., Angelo, M., Nolan, G., Swedlow, J. R., Schultz, N., Merrick, D. T., Mazzili, S. A., Cerami, E., Rodig, S. J., Santagata, S., Sorger, P. K., Abravanel, D. L., Achilefu, S., Ademuyiwa, F. O., Adey, A. C., Aft, R., Ahn, K. J., Alikarami, F., Alon, S., Ashenberg, O., Baker, E., Baker, G. J., Bandyopadhyay, S., Bayguinov, P., Beane, J., Becker, W., Bernt, K., Betts, C. B., Bletz, J., Blosser, T., Boire, A., Boland, G. M., Boyden, E. S., Bucher, E., Bueno, R., Cai, Q., Cambuli, F., Campbell, J., Cao, S., Caravan, W., Chaligne, R., Chan, J. M., Chasnoff, S., Chatterjee, D., Chen, A. A., Chen, C., Chen, C., Chen, B., Chen, F., Chen, S., Chheda, M. G., Chin, K., Cho, H., Chun, J., Cisneros, L., Coffey, R. J., Cohen, O., Colditz, G. A., Cole, K. A., Collins, N., Cotter, D., Coussens, L. M., Coy, S., Creason, A. L., Cui, Y., Zhou, D. C., Curtis, C., Davies, S. R., Bruijn, I., Delorey, T. M., Demir, E., Denardo, D., Diep, D., Ding, L., DiPersio, J., Dubinett, S. M., Eberlein, T. J., Eddy, J. A., Esplin, E. D., Factor, R. E., Fatahalian, K., Feiler, H. S., Fernandez, J., Fields, A., Fields, R. C., Fitzpatrick, J. A., Ford, J. M., Franklin, J., Fulton, B., Gaglia, G., Galdieri, L., Ganesh, K., Gao, J., Gaudio, B. L., Getz, G., Gibbs, D. L., Gillanders, W. E., Goecks, J., Goodwin, D., Gray, J. W., Greenleaf, W., Grimm, L. J., Gu, Q., Guerriero, J. L., Guha, T., Guimaraes, A. R., Gutierrez, B., Hacohen, N., Hanson, C. R., Harris, C. R., Hawkins, W. G., Heiser, C. N., Hoffer, J., Hollmann, T. J., Hsieh, J. J., Huang, J., Hunger, S. P., Hwang, E., Iacobuzio-Donahue, C., Iglesia, M. D., Islam, M., Izar, B., Jacobson, C. A., Janes, S., Jayasinghe, R. G., Jeudi, T., Johnson, B. E., Johnson, B. E., Ju, T., Kadara, H., Karnoub, E., Karpova, A., Khan, A., Kibbe, W., Kim, A. H., King, L. M., Kozlowski, E., Krishnamoorthy, P., Krueger, R., Kundaje, A., Ladabaum, U., Laquindanum, R., Lau, C., Lau, K. S., LeBoeuf, N. R., Lee, H., Lenburg, M., Leshchiner, I., Levy, R., Li, Y., Lian, C. G., Liang, W., Lim, K., Lin, Y., Liu, D., Liu, Q., Liu, R., Lo, J., Lo, P., Longabaugh, W. J., Longacre, T., Luckett, K., Ma, C., Maher, C., Maier, A., Makowski, D., Maley, C., Maliga, Z., Manoj, P., Maris, J. M., Markham, N., Marks, J. R., Martinez, D., Mashl, J., Masilionis, I., Massague, J., Mazurowski, M. A., McKinley, E. T., McMichael, J., Meyerson, M., Mills, G. B., Mitri, Z. I., Moorman, A., Mudd, J., Murphy, G. F., Deen, N. N., Navin, N. E., Nawy, T., Ness, R. M., Nevins, S., Nirmal, A. J., Novikov, E., Oh, S. T., Oldridge, D. A., Owzar, K., Pant, S. M., Park, W., Patti, G. J., Paul, K., Pelletier, R., Persson, D., Petty, C., Pfister, H., Polyak, K., Puram, S. V., Qiu, Q., Villalonga, A. Q., Ramirez, M. A., Rashid, R., Reeb, A. N., Reid, M. E., Remsik, J., Riesterer, J. L., Risom, T., Ritch, C. C., Rolong, A., Rudin, C. M., Ryser, M. D., Sato, K., Sears, C. L., Semenov, Y. R., Shen, J., Shoghi, K. I., Shrubsole, M. J., Shyr, Y., Sibley, A. B., Simmons, A. J., Sinha, A., Sivagnanam, S., Song, S., Southar-Smith, A., Spira, A. E., Cyr, J. S., Stefankiewicz, S., Storrs, E. P., Stover, E. H., Strand, S. H., Straub, C., Street, C., Su, T., Surrey, L. F., Suver, C., Tan, K., Terekhanova, N. V., Ternes, L., Thadi, A., Thomas, G., Tibshirani, R., Umeda, S., Uzun, Y., Vallius, T., Van Allen, E. R., Vandekar, S., Vega, P. N., Veis, D. J., Vennam, S., Verma, A., Vigneau, S., Wagle, N., Wahl, R., Walle, T., Wang, L., Warchol, S., Washington, M. K., Watson, C., Weimer, A. K., Wendl, M. C., West, R. B., White, S., Windon, A. L., Wu, H., Wu, C., Wu, Y., Wyczalkowski, M. A., Xu, J., Yao, L., Yu, W., Zhang, K., Zhu, X. 2022; 19 (3): 262-267

    View details for DOI 10.1038/s41592-022-01415-4

    View details for PubMedID 35277708

  • Transition to invasive breast cancer is associated with progressive changes in the structure and composition of tumor stroma. Cell Risom, T., Glass, D. R., Averbukh, I., Liu, C. C., Baranski, A., Kagel, A., McCaffrey, E. F., Greenwald, N. F., Rivero-Gutiérrez, B., Strand, S. H., Varma, S., Kong, A., Keren, L., Srivastava, S., Zhu, C., Khair, Z., Veis, D. J., Deschryver, K., Vennam, S., Maley, C., Hwang, E. S., Marks, J. R., Bendall, S. C., Colditz, G. A., West, R. B., Angelo, M. 2022; 185 (2): 299-310.e18


    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.

    View details for DOI 10.1016/j.cell.2021.12.023

    View details for PubMedID 35063072

  • The human tumor atlas network (HTAN) breast pre cancer atlas: A multi-omic integrative analysis of ductal carcinoma in situ (DCIS) and correlation with clinical outcomes Hwang, S., Strand, S. H., Rivero, B., King, L., Risom, T., Harmon, B., Couch, F., Gallagher, K., Kilgore, M., Wei, S., DeMichele, A., King, T., McAuliffe, P., Nangia, J., Storniolo, A., Thompson, A., Gupta, G., Lee, J., Tseng, J., Burns, R., Zhu, C., Matusiak, M., Zhu, S. X., Wang, J., Seoane, J., Tappenden, J., Ding, D., Zhang, D., Luo, J., Vennam, S., Varma, S., Simpson, L., Cisneros, L., Hardman, T., Anderson, L., Straub, C., Srivastava, S., Veis, D. J., Curtis, C., Tibshirani, R., Angelo, R., Hall, A., Owzar, K., Polyak, K., Maley, C., Marks, J., Colditz, G., West, R. B. AMER ASSOC CANCER RESEARCH. 2021
  • Mapping the tumor and microenvironmental evolution underlying DCIS progression through multiplexed ion beam imaging. Risom, T., Rivero, B., Liu, C., Baranski, A., Strand, S., Greenwald, N., McCaffrey, E., Varma, S., Keren, L., Srivastava, S., Zhu, C., Vennam, S., Hwang, S., Colditz, G., Bendall, S., West, R., Angelo, M. AMER ASSOC CANCER RESEARCH. 2020
  • Validation of the four-miRNA biomarker panel MiCaP for prediction of long-term prostate cancer outcome SCIENTIFIC REPORTS Strand, S. H., Schmidt, L., Weiss, S., Borre, M., Kristensen, H., Rasmussen, A., Daugaard, T., Kristensen, G., Stroomberg, H., Roder, M., Brasso, K., Mouritzen, P., Sorensen, K. 2020; 10 (1): 10704


    Improved prostate cancer prognostic biomarkers are urgently needed. We previously identified the four-miRNA prognostic biomarker panel MiCaP ((miR-23a-3p × miR-10b-5p)/(miR-133a-3p × miR-374b-5p)) for prediction of biochemical recurrence (BCR) after radical prostatectomy (RP). Here, we identified an optimal numerical cut-off for MiCaP dichotomisation using a training cohort of 475 RP patients and tested this in an independent cohort of 281 RP patients (PCA281). Kaplan-Meier, uni- and multivariate Cox regression analyses were conducted for multiple endpoints: BCR, metastatic-(mPC) and castration-resistant prostate cancer (CRPC), prostate cancer-specific (PCSS) and overall survival (OS). Functional effects of the four MiCaP miRNAs were assessed by overexpression and inhibition experiments in prostate cancer cell lines. We found the numerical value 5.709 optimal for MiCaP dichotomisation. This was independently validated in PCA281, where a high MiCaP score significantly [and independent of the Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) score] predicted BCR, progression to mPC and CRPC, and PCSS, but not OS. Harrell's C-index increased upon addition of MiCaP to CAPRA-S for all endpoints. Inhibition of miR-23a-3p and miR-10b-5p, and overexpression of miR-133a-3p and miR-374b-5p significantly reduced cell survival. Our results may promote future implementation of a MiCaP-based test for improved prostate cancer risk stratification.

    View details for DOI 10.1038/s41598-020-67320-y

    View details for Web of Science ID 000546550700018

    View details for PubMedID 32612164

    View details for PubMedCentralID PMC7329825

  • Epigenetic Analysis of Circulating Tumor DNA in Localized and Metastatic Prostate Cancer: Evaluation of Clinical Biomarker Potential CELLS Bjerre, M., Norgaard, M., Larsen, O., Jensen, S., Strand, S. H., Ostergren, P., Fode, M., Fredsoe, J., Ulhoi, B., Mortensen, M., Jensen, J., Borre, M., Sorensen, K. D. 2020; 9 (6)


    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%-100%/75-94%). 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%-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 < 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-naïve mPCa patients who could benefit from intensified treatment.

    View details for DOI 10.3390/cells9061362

    View details for Web of Science ID 000554726500001

    View details for PubMedID 32486483

    View details for PubMedCentralID PMC7349912

  • The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution. Cell Rozenblatt-Rosen, O., Regev, A., Oberdoerffer, P., Nawy, T., Hupalowska, A., Rood, J. E., Ashenberg, O., Cerami, E., Coffey, R. J., Demir, E., Ding, L., Esplin, E. D., Ford, J. M., Goecks, J., Ghosh, S., Gray, J. W., Guinney, J., Hanlon, S. E., Hughes, S. K., Hwang, E. S., Iacobuzio-Donahue, C. A., Jane-Valbuena, J., Johnson, B. E., Lau, K. S., Lively, T., Mazzilli, S. A., Pe'er, D., Santagata, S., Shalek, A. K., Schapiro, D., Snyder, M. P., Sorger, P. K., Spira, A. E., Srivastava, S., Tan, K., West, R. B., Williams, E. H., Human Tumor Atlas Network, Aberle, D., Achilefu, S. I., Ademuyiwa, F. O., Adey, A. C., Aft, R. L., Agarwal, R., Aguilar, R. A., Alikarami, F., Allaj, V., Amos, C., Anders, R. A., Angelo, M. R., Anton, K., Ashenberg, O., Aster, J. C., Babur, O., Bahmani, A., Balsubramani, A., Barrett, D., Beane, J., Bender, D. E., Bernt, K., Berry, L., Betts, C. B., Bletz, J., Blise, K., Boire, A., Boland, G., Borowsky, A., Bosse, K., Bott, M., Boyden, E., Brooks, J., Bueno, R., Burlingame, E. A., Cai, Q., Campbell, J., Caravan, W., Cerami, E., Chaib, H., Chan, J. M., Chang, Y. H., Chatterjee, D., Chaudhary, O., Chen, A. A., Chen, B., Chen, C., Chen, C., Chen, F., Chen, Y., Chheda, M. G., Chin, K., Chiu, R., Chu, S., Chuaqui, R., Chun, J., Cisneros, L., Coffey, R. J., Colditz, G. A., Cole, K., Collins, N., Contrepois, K., Coussens, L. M., Creason, A. L., Crichton, D., Curtis, C., Davidsen, T., Davies, S. R., de Bruijn, I., Dellostritto, L., De Marzo, A., Demir, E., DeNardo, D. G., Diep, D., Ding, L., Diskin, S., Doan, X., Drewes, J., Dubinett, S., Dyer, M., Egger, J., Eng, J., Engelhardt, B., Erwin, G., Esplin, E. D., Esserman, L., Felmeister, A., Feiler, H. S., Fields, R. C., Fisher, S., Flaherty, K., Flournoy, J., Ford, J. M., Fortunato, A., Frangieh, A., Frye, J. L., Fulton, R. S., Galipeau, D., Gan, S., Gao, J., Gao, L., Gao, P., Gao, V. R., Geiger, T., George, A., Getz, G., Ghosh, S., Giannakis, M., Gibbs, D. L., Gillanders, W. E., Goecks, J., Goedegebuure, S. P., Gould, A., Gowers, K., Gray, J. W., Greenleaf, W., Gresham, J., Guerriero, J. L., Guha, T. K., Guimaraes, A. R., Guinney, J., Gutman, D., Hacohen, N., Hanlon, S., Hansen, C. R., Harismendy, O., Harris, K. A., Hata, A., Hayashi, A., Heiser, C., Helvie, K., Herndon, J. M., Hirst, G., Hodi, F., Hollmann, T., Horning, A., Hsieh, J. J., Hughes, S., Huh, W. J., Hunger, S., Hwang, S. E., Iacobuzio-Donahue, C. A., Ijaz, H., Izar, B., Jacobson, C. A., Janes, S., Jane-Valbuena, J., Jayasinghe, R. G., Jiang, L., Johnson, B. E., Johnson, B., Ju, T., Kadara, H., Kaestner, K., Kagan, J., Kalinke, L., Keith, R., Khan, A., Kibbe, W., Kim, A. H., Kim, E., Kim, J., Kolodzie, A., Kopytra, M., Kotler, E., Krueger, R., Krysan, K., Kundaje, A., Ladabaum, U., Lake, B. B., Lam, H., Laquindanum, R., Lau, K. S., Laughney, A. M., Lee, H., Lenburg, M., Leonard, C., Leshchiner, I., Levy, R., Li, J., Lian, C. G., Lim, K., Lin, J., Lin, Y., Liu, Q., Liu, R., Lively, T., Longabaugh, W. J., Longacre, T., Ma, C. X., Macedonia, M. C., Madison, T., Maher, C. A., Maitra, A., Makinen, N., Makowski, D., Maley, C., Maliga, Z., Mallo, D., Maris, J., Markham, N., Marks, J., Martinez, D., Mashl, R. J., Masilionais, I., Mason, J., Massague, J., Massion, P., Mattar, M., Mazurchuk, R., Mazutis, L., Mazzilli, S. A., McKinley, E. T., McMichael, J. F., Merrick, D., Meyerson, M., Miessner, J. R., Mills, G. B., Mills, M., Mondal, S. B., Mori, M., Mori, Y., Moses, E., Mosse, Y., Muhlich, J. L., Murphy, G. F., Navin, N. E., Nawy, T., Nederlof, M., Ness, R., Nevins, S., Nikolov, M., Nirmal, A. J., Nolan, G., Novikov, E., Oberdoerffer, P., O'Connell, B., Offin, M., Oh, S. T., Olson, A., Ooms, A., Ossandon, M., Owzar, K., Parmar, S., Patel, T., Patti, G. J., Pe'er, D., Pe'er, I., Peng, T., Persson, D., Petty, M., Pfister, H., Polyak, K., Pourfarhangi, K., Puram, S. V., Qiu, Q., Quintanal-Villalonga, A., Raj, A., Ramirez-Solano, M., Rashid, R., Reeb, A. N., Regev, A., Reid, M., Resnick, A., Reynolds, S. M., Riesterer, J. L., Rodig, S., Roland, J. T., Rosenfield, S., Rotem, A., Roy, S., Rozenblatt-Rosen, O., Rudin, C. M., Ryser, M. D., Santagata, S., Santi-Vicini, M., Sato, K., Schapiro, D., Schrag, D., Schultz, N., Sears, C. L., Sears, R. C., Sen, S., Sen, T., Shalek, A., Sheng, J., Sheng, Q., Shoghi, K. I., Shrubsole, M. J., Shyr, Y., Sibley, A. B., Siex, K., Simmons, A. J., Singer, D. S., Sivagnanam, S., Slyper, M., Snyder, M. P., Sokolov, A., Song, S., Sorger, P. K., Southard-Smith, A., Spira, A., Srivastava, S., Stein, J., Storm, P., Stover, E., Strand, S. H., Su, T., Sudar, D., Sullivan, R., Surrey, L., Suva, M., Tan, K., Terekhanova, N. V., Ternes, L., Thammavong, L., Thibault, G., Thomas, G. V., Thorsson, V., Todres, E., Tran, L., Tyler, M., Uzun, Y., Vachani, A., Van Allen, E., Vandekar, S., Veis, D. J., Vigneau, S., Vossough, A., Waanders, A., Wagle, N., Wang, L., Wendl, M. C., West, R., Williams, E. H., Wu, C., Wu, H., Wu, H., Wyczalkowski, M. A., Xie, Y., Yang, X., Yapp, C., Yu, W., Yuan, Y., Zhang, D., Zhang, K., Zhang, M., Zhang, N., Zhang, Y., Zhao, Y., Zhou, D. C., Zhou, Z., Zhu, H., Zhu, Q., Zhu, X., Zhu, Y., Zhuang, X. 2020; 181 (2): 236–49


    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.

    View details for DOI 10.1016/j.cell.2020.03.053

    View details for PubMedID 32302568

  • Elevated miR-615-3p Expression Predicts Adverse Clinical Outcome and Promotes Proliferation and Migration of Prostate Cancer Cells AMERICAN JOURNAL OF PATHOLOGY Laursen, E. B., Fredsoe, J., Schmidt, L., Strand, S. H., Kristensen, H., Rasmussen, A. I., Daugaard, T. F., Mouritzen, P., Hoyer, S., Kristensen, G., Stroomberg, H. V., Brasso, K., Roder, M., Borre, M., Sorensen, K. D. 2019; 189 (12): 2377–88


    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.

    View details for DOI 10.1016/j.ajpath.2019.08.007

    View details for Web of Science ID 000501397900003

    View details for PubMedID 31539518

  • A novel combined miRNA and methylation marker panel (miMe) for prediction of prostate cancer outcome after radical prostatectomy. International journal of cancer Strand, S. H., Bavafaye-Haghighi, E., Kristensen, H., Rasmussen, A. K., Hoyer, S., Borre, M., Mouritzen, P., Besenbacher, S., Orntoft, T. F., Sorensen, K. D. 2019


    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.

    View details for DOI 10.1002/ijc.32427

    View details for PubMedID 31125115

  • Aberrant DOCK2, GRASP, HIF3A and PKFP Hypermethylation has Potential as a Prognostic Biomarker for Prostate Cancer. International journal of molecular sciences Bjerre, M. T., Strand, S. H., Nørgaard, M., Kristensen, H., Rasmussen, A. K., Mortensen, M. M., Fredsøe, J., Mouritzen, P., Ulhøi, B., Ørntoft, T., Borre, M., Sørensen, K. D. 2019; 20 (5)


    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.

    View details for DOI 10.3390/ijms20051173

    View details for PubMedID 30866497

    View details for PubMedCentralID PMC6429171

  • 5hmC Level Predicts Biochemical Failure Following Radical Prostatectomy in Prostate Cancer Patients with ERG Negative Tumors. International journal of molecular sciences Kristensen, G., Strand, S. H., Røder, M. A., Berg, K. D., Toft, B. G., Høyer, S., Borre, M., Sørensen, K. D., Brasso, K. 2019; 20 (5)


    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: 9.5⁻10.2). 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: 1.2⁻2.7; 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.

    View details for DOI 10.3390/ijms20051025

    View details for PubMedID 30818754

    View details for PubMedCentralID PMC6429366

  • Exploring the transcriptome of hormone-naive multifocal prostate cancer and matched lymph node metastases. British journal of cancer Schmidt, L., Møller, M., Haldrup, C., Strand, S. H., Vang, S., Hedegaard, J., Høyer, S., Borre, M., Ørntoft, T., Sørensen, K. D. 2018; 119 (12): 1527-1537


    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.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).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.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.

    View details for DOI 10.1038/s41416-018-0321-5

    View details for PubMedID 30449885

    View details for PubMedCentralID PMC6288156

  • Training and validation of a novel 4-miRNA ratio model (MiCaP) for prediction of postoperative outcome in prostate cancer patients. Annals of oncology : official journal of the European Society for Medical Oncology Schmidt, L., Fredsøe, J., Kristensen, H., Strand, S. H., Rasmussen, A., Høyer, S., Borre, M., Mouritzen, P., Ørntoft, T., Sørensen, K. D. 2018; 29 (9): 2003-2009


    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.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.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%).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.

    View details for DOI 10.1093/annonc/mdy243

    View details for PubMedID 30010760

    View details for PubMedCentralID PMC6158759

  • Dysregulation and prognostic potential of 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxylcytosine (5caC) levels in prostate cancer. Clinical epigenetics Storebjerg, T. M., Strand, S. H., Høyer, S., Lynnerup, A. S., Borre, M., Ørntoft, T. F., Sørensen, K. D. 2018; 10 (1): 105


    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.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 < 0.001), while 5hmC levels were only weakly positively correlated to 5mC in the PC subset (p = 0.030). There were no significant associations between 5mC, 5fC, or ERG status and time to BCR in this RP cohort. In contrast, high 5hmC levels were associated with BCR in ERG- PCs (p = 0.043), while high 5caC levels were associated with favorable prognosis in ERG+ PCs (p = 0.011) and were borderline significantly associated with worse prognosis in ERG- PCs (p = 0.058). Moreover, a combined high-5hmC/high-5caC score was a significant adverse predictor of post-operative BCR beyond routine clinicopathological variables in ERG- PCs (hazard ratio 3.18 (1.54-6.56), p = 0.002, multivariate Cox regression).This is the first comprehensive study of 5mC, 5hmC, 5fC, and 5caC levels in PC and the first report of a significant prognostic potential for 5caC in PC.

    View details for DOI 10.1186/s13148-018-0540-x

    View details for PubMedID 30086793

    View details for PubMedCentralID PMC6081903

  • Biomarker potential of ST6GALNAC3 and ZNF660 promoter hypermethylation in prostate cancer tissue and liquid biopsies. Molecular oncology Haldrup, C., Pedersen, A. L., Øgaard, N., Strand, S. H., Høyer, S., Borre, M., Ørntoft, T. F., Sørensen, K. D. 2018; 12 (4): 545-560


    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.

    View details for DOI 10.1002/1878-0261.12183

    View details for PubMedID 29465788

    View details for PubMedCentralID PMC5891052

  • RHCG and TCAF1 promoter hypermethylation predicts biochemical recurrence in prostate cancer patients treated by radical prostatectomy. Oncotarget Strand, S. H., Switnicki, M., Moller, M., Haldrup, C., Storebjerg, T. M., Hedegaard, J., Nordentoft, I., Hoyer, S., Borre, M., Pedersen, J. S., Wild, P. J., Park, J. Y., Orntoft, T. F., Sorensen, K. D. 2017; 8 (4): 5774-5788


    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.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).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).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.

    View details for DOI 10.18632/oncotarget.14391

    View details for PubMedID 28052017

    View details for PubMedCentralID PMC5351588

  • Heterogeneous patterns of DNA methylation-based field effects in histologically normal prostate tissue from cancer patients. Scientific reports Møller, M., Strand, S. H., Mundbjerg, K., Liang, G., Gill, I., Haldrup, C., Borre, M., Høyer, S., Ørntoft, T. F., Sørensen, K. D. 2017; 7: 40636


    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.

    View details for DOI 10.1038/srep40636

    View details for PubMedID 28084441

    View details for PubMedCentralID PMC5233981

  • HNF1B variants associate with promoter methylation and regulate gene networks activated in prostate and ovarian cancer. Oncotarget Ross-Adams, H., Ball, S., Lawrenson, K., Halim, S., Russell, R., Wells, C., Strand, S. H., Ørntoft, T. F., Larson, M., Armasu, S., Massie, C. E., Asim, M., Mortensen, M. M., Borre, M., Woodfine, K., Warren, A. Y., Lamb, A. D., Kay, J., Whitaker, H., Ramos-Montoya, A., Murrell, A., Sørensen, K. D., Fridley, B. L., Goode, E. L., Gayther, S. A., Masters, J., Neal, D. E., Mills, I. G. 2016; 7 (46): 74734-74746


    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.

    View details for DOI 10.18632/oncotarget.12543

    View details for PubMedID 27732966

    View details for PubMedCentralID PMC5342698

  • High levels of 5-hydroxymethylcytosine (5hmC) is an adverse predictor of biochemical recurrence after prostatectomy in ERG-negative prostate cancer. Clinical epigenetics Strand, S. H., Hoyer, S., Lynnerup, A. S., Haldrup, C., Storebjerg, T. M., Borre, M., Orntoft, T. F., Sorensen, K. D. 2015; 7: 111


    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.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 < 0.001) loss of 5hmC in ERG- PCs. ERG status was not predictive of BCR in this cohort (p = 0.73), and no significant association was found between BCR and 5hmC levels in ERG+ PCs (p = 0.98). In contrast, high 5hmC immunoreactivity was a significant adverse predictor of BCR after RP in ERG- PCs, independent of Gleason score, pathological tumor stage, surgical margin status, and pre-operative prostate-specific antigen (PSA) level (hazard ratio (HR) (95 % confidence interval (CI)): 1.62 (1.15-2.28), p = 0.006).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.

    View details for DOI 10.1186/s13148-015-0146-5

    View details for PubMedID 26478752

    View details for PubMedCentralID PMC4608326

  • Prognostic DNA methylation markers for prostate cancer. International journal of molecular sciences Strand, S. H., Orntoft, T. F., Sorensen, K. D. 2014; 15 (9): 16544-76


    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.

    View details for DOI 10.3390/ijms150916544

    View details for PubMedID 25238417

    View details for PubMedCentralID PMC4200823

  • Hypermethylation of the GABRE~miR-452~miR-224 promoter in prostate cancer predicts biochemical recurrence after radical prostatectomy. Clinical cancer research : an official journal of the American Association for Cancer Research Kristensen, H., Haldrup, C., Strand, S., Mundbjerg, K., Mortensen, M. M., Thorsen, K., Ostenfeld, M. S., Wild, P. J., Arsov, C., Goering, W., Visakorpi, T., Egevad, L., Lindberg, J., Grönberg, H., Høyer, S., Borre, M., Ørntoft, T. F., Sørensen, K. D. 2014; 20 (8): 2169-81


    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.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.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.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.

    View details for DOI 10.1158/1078-0432.CCR-13-2642

    View details for PubMedID 24737792

  • Prognostic significance of aberrantly silenced ANPEP expression in prostate cancer. British journal of cancer Sørensen, K. D., Abildgaard, M. O., Haldrup, C., Ulhøi, B. P., Kristensen, H., Strand, S., Parker, C., Høyer, S., Borre, M., Ørntoft, T. F. 2013; 108 (2): 420-8


    Novel biomarkers for prostate cancer (PC) are urgently needed. This study investigates the expression, epigenetic regulation, and prognostic potential of ANPEP in PC.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.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.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.

    View details for DOI 10.1038/bjc.2012.549

    View details for PubMedID 23322201

    View details for PubMedCentralID PMC3566819