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Vachon, Celine M.

0000-0002-1962-9322

Mayo Clinic

Mayo Clinic

Citations 275

A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci
Rand, Kristin A. , Song, Chi , Déan, Eric, Serie, Daniel, Curtin, Karen , Sheng, Xin , Huff, Carol Ann , Bernal‐Mizrachi, Leon , Tomasson, Michael H. , Pawlish, Karen , Peters, Edward , Stram, Alex , Edlund, Christopher K., Conti, David V. , Zimmerman, Todd M., Hwang, Amie E. , Huntsman, Scott , Graff, John, Kong, Yinfei , Pregja, Silvana, Berndt, Sonja I. , Blot, William J. , Carpten, John D. , Chu, Lisa W., Diver, W. Ryan , Stevens, Victoria L. , Lieber, Michael R. , Goodman, Phyllis J. , Hennis, Anselm , Hsing, Ann W. , Mehta, Jayesh, Klein, Eric A. , Leske, Cristina, Murphy, Adam B. , Nemesure, Barbara , Strom, Sara S., Vij, Ravi , Rybicki, Benjamin A. , Stanford, Janet L. , Signorello, Lisa B., Witte, John S. , Bhatti, Parveen , Hu, Jennifer J. , Nyante, Sarah J. , Birmann, Brenda M. , Atanackovic, Djordje , Glenn, Martha, Jones, Brandt, Tricot, Guido , Kumar, Shaji , Wolf, Jeffrey L. , Halverson, Sandra L. , Rothman, Nathaniel , Brooks‐Wilson, Angela , Kolonel, Laurence N. , Severson, Richard K., Janakiraman, Nalini, Terebelo, Howard R. , Brown, Elizabeth E. , Roos, Anneclaire J. De , Mohrbacher, Ann , Spinelli, John J. , Munshi, Nikhil C. , Levy, Joan, Zonder, Jeffrey A. , Orlowski, Robert Z. , Camp, Nicola J. , Vachon, Celine M. , Ziv, Elad , Hazelett, Dennis J. , Haiman, Christopher A. , Serie, Daniel J, Hu, Donglei , Ailawadhi, Sikander , Singhal, Seema , Bock, Cathryn Hufford , Berg, David Van Den , Nooka, Ajay K. , Casey, Graham , Kittles, Rick A. , Kolb, Suzanne , Neslund-Dudas, Christine M , Ambrosone, Christine B. , John, Esther M. , Bernstein, Leslie , Zheng, Wei , Olshan, Andrew F. , Ziegler, Regina G. , Bandera, Elisa V. , Ingles, Sue A. , Press, Michael F. , Cannon‐Albright, Lisa , Martin, Thomas G. , Rothman, Nathaniel , Rajkumar, S. Vincent , Chanock, Stephen Jacob , Slager, Susan L. , Colditz, Graham A. , Giles, Graham G. , Chiu, Brian C.‐H. , Anderson, Kenneth C. , Orlowski, Robert Z. , Lonial, Sagar , Vachon, Celine M. , Stram, Daniel O. , Cozen, Wendy , Hazelett, Dennis J , Brooks-Wilson, Angela R , Klein, Eric A , De Roos, Anneclaire J , Nyante, Sarah , Bhatti, Parveen , Birmann, Brenda M , Ziv, Elad , Conti, David V

Cancer Epidemiology, Biomarkers & Prevention | September 2, 2016 | Volume: 25 | Issue: 12 | Pages: 1609-1618

10.1158/1055-9965.epi-15-1193 Get It

Abstract Background: Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma. Methods: We performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. Results: We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P < 0.05) associated with multiple myeloma risk in persons of African ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry–European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4. Correlated variants in 7p15.3 clustered around an enhancer at the 3′ end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10−7) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7. Conclusions: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. Impact: A subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609–18. ©2016 AACR.
Abstract LB-364: Natural history of age-related lobular involution and impact on breast cancer risk
Visscher, Daniel W., Frank, Ryan D. , Vachon, Celine M. , Denison, Lori A., Hartmann, Lynn C. , Frost, Marlene H., Radisky, Derek C. , Vierkant, Robert A. , Winham, Stacey J. , Stallings‐Mann, Melody , Hoskin, Tanya L. , Nassar, Aziza , Vachon, Celine M. , Degnim, Amy C.

Cancer Research | July 26, 2016 | Volume: 76 | Issue: 14_Supplement | Pages: LB-364-LB-364

10.1158/1538-7445.am2016-lb-364 Get It

Abstract Background: Age-related lobular involution (LI) is a physiological process in which the terminal duct lobular units of the breast regress as a woman ages. Analyses of breast biopsies from women with benign breast disease (BBD) have found that extent of LI is negatively associated with subsequent breast cancer development. Here we assess the natural course of LI within individual women, and the impact of progressive LI on breast cancer risk. Methods: The Mayo Clinic BBD cohort consists of 13,455 women with BBD from 1967-2001. The BBD cohort includes 1115 women who had multiple benign biopsies, 106 of whom had developed breast cancer. Within this multiple biopsy cohort, the progression of the LI process was examined by age at initial biopsy and time between biopsies. The relationship between LI progression and breast cancer risk was assessed using standardized incidence ratios (SIRs) and by Cox proportional hazards analysis. Results: Women who had multiple biopsies were younger age and had a slightly higher family history of breast cancer as compared with the overall BBD cohort. Extent of LI at subsequent biopsy was greater with increasing time between biopsies and for women age 55+ at initial biopsy. Among women with multiple biopsies, there was a significant association of higher breast cancer risk among those with involution stasis (lack of progression, HR 1.63) as compared with those with involution progression, p = 0.036. Conclusions: The multiple biopsy BBD cohort allows for a longitudinal study of the natural progression of LI. The majority of women in the multiple biopsy cohort showed progression of LI status between benign biopsies, and extent of progression was highest for women who were in the perimenopausal age range at initial biopsy. Progression of LI status between initial and subsequent biopsy was associated with decreased breast cancer risk. Citation Format: Derek Radisky, Daniel W. Visscher, Ryan Frank, Robert A. Vierkant, Stacey J. Winham, Melody L. Stallings-Mann, Tanya L. Hoskin, Aziza Nassar, Celine M. Vachon, Lori A. Denison, Lynn C. Hartmann, Marlene H. Frost, Amy C. Degnim. Natural history of age-related lobular involution and impact on breast cancer risk. [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 LB-364.
Abstract 3453: Medical history, lifestyle, and family history exposures and chronic lymphocytic leukemia outcome
Beiggi, Sara, Foran, James M. , Megan, O’Byrne, Vachon, Celine M. , Call, Timothy G. , Vachon, Celine M. , Kay, Neil E. , Shanafelt, Tait D. , Cerhan, James R. , Slager, Susan L.

Cancer Research | July 26, 2016 | Volume: 76 | Issue: 14_Supplement | Pages: 3453-3453

10.1158/1538-7445.am2016-3453 Get It

Abstract Background: Associations of medical history, lifestyle, and family history of hematological disorders with risk of chronic lymphocytic leukemia (CLL) have been previously established (1), but these exposures have not been well-studied as contributing factors to CLL prognosis. Here we investigate the association of these exposures with time to first treatment (TTFT) in 730 CLL patients. Methods: Newly diagnosed CLL patients seen at the Mayo Clinic between 2002 and 2012 were enrolled. CLL was defined according to the 1996 NCI-Working Group criteria (2). Risk factor data (including body mass index, smoking, alcohol use, sun exposure, having lived on a farm, any allergy, asthma, eczema, blood transfusion, diabetes, rheumatoid arthritis, and family history of hematological malignancy) were collected from self-administered questionnaires. Clinical and prognostic characteristics for CLL were extracted from medical records. Analyses were performed using Cox regression with first treatment as the event. Hazard ratios (HR) and 95% confidence intervals were estimated. We used Bonferroni correction for multiple testing with statistical significance at 0.004. Results: The median age at CLL diagnosis was 63 years (range 36 - 89); 65% were male, and 95% had a Rai stage< III. The median follow up time was 6.3 years, and 40% received treatment. In unadjusted analyses, patients with any history of allergies had significantly longer TTFT (HR = 0.66, 95% CI: 0.51-0.85, P = 0.001). We also observed borderline significance with history of asthma (HR = 0.53, 95% CI: 0.34-0.85, P = 0.008). These associations held after adjusting for important prognostic factors including age, sex, Rai stage, and IGVH mutational status. The other risk factors had non-significant associations (P>0.1). Conclusions: We observed an improved CLL prognosis in patients with a history of any allergies or asthma. These results were independent of other prognostic markers and suggest that an overactive IgE level from environmental exposures may provide insight into the progression of CLL. Literature Cited 1. Slager SL, Benavente Y, Blair A, Vermeulen R, Cerhan JR, Costantini AS, et al. Medical history, lifestyle, family history, and occupational risk factors for chronic lymphocytic leukemia/small lymphocytic lymphoma: the InterLymph Non-Hodgkin Lymphoma Subtypes Project. J Natl Cancer Inst Monogr. 2014 Aug;2014(48):41-51. 2. Cheson BD, Bennett JM, Grever M, Kay N, Keating MJ, O’Brien S, et al. National Cancer Institute-sponsored Working Group guidelines for chronic lymphocytic leukemia: revised guidelines for diagnosis and treatment. Blood. 1996 Jun 15;87(12):4990-7. Citation Format: Sara Beiggi, James M. Foran, O’Byrne Megan, Celine M. Vachon, Timothy G. Call, Neil E. Kay, Tait D. Shanafelt, James R. Cerhan, Susan L. Slager. Medical history, lifestyle, and family history exposures and chronic lymphocytic leukemia outcome. [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 3453.
Abstract 3424: Longitudinal changes in volumetric breast density with adjuvant endocrine therapy among women with breast cancer
Vachon, Celine M. , Jensen, Matthew R. , Brandt, Kathleen R. , Mahmoudzadeh, Amir Pasha , Whaley, Dana H. , Wu, Fang , Heine, John , Engmann, Natalie J. , Vachon, Celine M. , Scott, Christopher G. , Malkov, Serghei , Hruska, Carrie B. , Wu, Fang F., Winham, Stacey J. , Miglioretti, Diana L. , Norman, Aaron D. , Shepherd, John , Pankratz, V. Shane , Kerlikowske, Karla

Cancer Research | July 26, 2016 | Volume: 76 | Issue: 14_Supplement | Pages: 3424-3424

10.1158/1538-7445.am2016-3424 Get It

Abstract Breast density represents the stromal and epithelial tissue in the breast and is a strong risk factor for breast cancer. Reductions in breast density attributable to tamoxifen (TAM) and aromatase inhibitors (AI) may be associated with reduced risk of first primary and subsequent breast cancer. Studies assessing breast density changes have principally used two-dimensional measures. We assess changes in breast density following initiation of TAM and AI using two automated volumetric density measures that have shown strong associations to breast cancer risk. Breast cancer cases with a full field digital mammogram (FFDM) prior to diagnosis (index mammogram) and after initiation of TAM (n = 379) or AI (n = 425) were identified from the Mayo Clinic Mammography Practice and the San Francisco Mammography Registry. Volumetric percent density (VPD) and dense volume (DV) were measured on 4-view FFDM using VolparaTM (Matakina Technology) and QuantraTM (Hologic) automated software. We used linear regression to assess the effect of treatment on mean annualized change in VPD and DV (change from index to last mammogram divided by time interval) for each software type, adjusting for age, body mass index (BMI) and density at index mammogram. The median time between index mammogram and cancer diagnosis was 0.6 months (IQR: 0.2, 2.2) and median time between index and last mammogram was 3 years (IQR: 2.0, 3.9). Women on TAM were younger, had lower BMI and higher baseline VPD and DV relative to women on AI (Table). An annual decrease in VPD and DV was observed with both TAM and AI. Both Volpara and Quantra estimated a similar magnitude of change in VPD in women on TAM and AI, and a greater change in DV with TAM. Our findings suggest that both Volpara and Quantra can assess volumetric changes in breast density among women on hormone therapy. If declines in volumetric density correlate with a reduction in breast cancer risk, these automated measures could be used in clinical practice to assess response to therapy. Annualized changes in volumetric breast density estimated by linear regression.Tamoxifen (n = 379)Aromatase Inhibitors (n = 425)Baseline Median (IQR)Annualized Change (95% CI)*Baseline Median (IQR)Annualized Change (95% CI)*Age at Diagnosis50.0 (45.0, 60.0)–63.0 (58.0, 71.0)–Body Mass Index (BMI)23.6 (21.5, 26.8)–25.7 (22.7, 29.9)–Time Interval¥3.0 (2.1, 3.9)–3.0 (2.1, 3.9)–VolparaPercent Density (VPD,%)11.6 (6.8, 18.8)-0.17 (-0.27, -0.10)7.2 (5.0, 11.0)-0.19 (-0.29, -0.12)Dense Volume (DV, cm3)64.7 (45.4, 90.9)-0.90 (-1.45, -0.48)51.9 (38.9, 69.9)-0.52 (-0.93, -0.23)QuantraPercent Density (VPD,%)14.5 (9.2, 20.2)-0.42 (-0.59, -0.28)9.9 (7.1, 14.5)-0.38 (-0.54, -0.25)Dense Volume (DV, cm3)94.0 (58.0, 144.0)-2.20 (-3.52, -1.19)80.0 (49.0, 128.0)-0.95 (-1.85, -0.35)IQR = Interquartile range ¥ Median number of years between index mammogram and last mammogram post-initiation of therapy. *Annualized change estimated as change from index to last mammogram divided by time interval and adjusted for study site, age at diagnosis, BMI and density at index mammogram. Citation Format: Natalie J. Engmann, Celine M. Vachon, Christopher G. Scott, Matthew R. Jensen, Lin Ma, Kathleen R. Brandt, Amir P. Mahmoudzadeh, Serghei Malkov, Dana H. Whaley, Carrie B. Hruska, Fang F. Wu, Stacey J. Winham, Diana L. Miglioretti, Aaron D. Norman, John J. Heine, John Shepherd, V Shane Pankratz, Karla Kerlikowske. Longitudinal changes in volumetric breast density with adjuvant endocrine therapy among women with breast 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 3424.
Abstract 2593: Association of mammographic density measures and breast cancer ‘intrinsic’ molecular subtypes
Visscher, Daniel W., Shepherd, John, Chen, Yunn‐Yi , Beck, Andrew H. , Vachon, Celine M. , Norman, Aaron D. , Tamimi, Rulla M. , Scott, Christopher G. , Bertrand, Kimberly A. , Jensen, Matthew R. , Couch, Fergus J. , Fan, Bo, Pankratz, V. Shane , Kerlikowske, Karla , Vachon, Celine M.

Cancer Research | July 26, 2016 | Volume: 76 | Issue: 14_Supplement | Pages: 2593-2593

10.1158/1538-7445.am2016-2593 Get It

Abstract Percent mammographic density (PMD) is a risk factor for estrogen receptor (ER)-positive and ER-negative invasive breast cancer (BC). Gene expression profiling has identified molecular signatures that classify invasive BC into distinct subtypes that vary in their clinical behavior, response to treatment and likely, etiology. Immunohistochemical (IHC) staining of tumor sections using antibody panels can be used to classify these ‘intrinsic’ molecular subtypes. We evaluated whether density measures [PMD, absolute dense area (DA) and non-dense area (NDA)], are associated equally with all ‘intrinsic’ molecular subtypes. Pooled analysis of six cohort or case-control studies included 3492 women with invasive BC and 10,148 without, who underwent screening mammography a median 4 years prior to diagnosis (for cases). PMD, DA, and NDA were assessed from digitized film-screen mammograms using a computer-assisted thresholding technique, and categorized as 0-10%, 11-25%, 26-50% and 51%+ (PMD) or into quartiles (DA and NDA). Receptor status was abstracted from pathology records and supplemented by IHC staining. We classified tumors as Luminal A (ER+ and/or PR+ and HER2- and grade 1 or 2), Luminal B (ER+ and/or PR+ and HER2+ or Luminal A and grade 3), HER2 expressing (HER2+/ER-/PR-) and triple negative (TN) (ER-/PR-/HER2-). For TN, we also differentiated basal-like tumors (positive for EGFR and/or CK 5/6) from unclassified (negative on both markers). We used polytomous logistic regression to calculate the odds ratio (OR) of each ‘intrinsic’ subtype of BC by categories of PMD, DA or NDA, adjusting for age, body mass index and study. We tested for statistical heterogeneity of associations by subtype. Of 3492 invasive BC cases, 2217 (63%) were classified as Luminal A, 747 (21%) as Luminal B, 159 (5%) as HER2 expressing, and 369 (11%) as TN. Of TN, 203 were evaluated for CK 5/6 and EGFR, with 167 (82%) classified as basal-like and 36 (18%) unclassified. PMD was associated with BC risk across all subtypes. For Luminal A, compared to women with 11-25% PMD (reference), women with 0-10% had a reduced risk of BC (OR = 0.63 [95% confidence interval: 0.55, 0.74]) while women with 26-50% had an OR = 1.5 [1.3, 1.7] and women with 51%+ had the highest risk, OR = 2.3 [2.0, 2.7]. Similar BC associations were seen across PMD categories when comparing the five subtypes (P-heterogeneity = 0.63). Similar trends were seen for DA and BC across the five subtypes (P-het = 0.25). NDA was inversely associated with BC across subtypes, and there was suggestion of a stronger inverse trend among HER2-expressing BC compared to other subtypes (P-het = 0.09). Our results suggest mammographic density measures are associated with all ‘intrinsic’ molecular subtypes. However, NDA may be more strongly inversely associated with HER2-expressing than other subtypes. Understanding the importance of density measures for BC subtypes has significance for subtype-specific risk models. Citation Format: Aaron D. Norman, Rulla M. Tamimi, Christopher G. Scott, Kimberly A. Bertrand, Matthew R. Jensen, Daniel W. Visscher, Fergus J. Couch, John Shepherd, Bo Fan, Yunn-Yi Chen, Lin Ma, Andrew Beck, Vernon S. Pankratz, Karla Kerlikowske, Celine M. Vachon. Association of mammographic density measures and breast cancer ‘intrinsic’ molecular subtypes. [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 2593.
Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types
Kar, Siddhartha , Beesley, Jonathan, Olama, Ali Amin Al , Michailidou, Kyriaki , Lawrenson, Kate , Lindström, Sara, Ramus, Susan J. , Thompson, Deborah J. , Investigators, ABCTB, Kibel, Adam S. , Dansonka‐Mieszkowska, Agnieszka , Michael, Agnieszka , Dieffenbach, Aida Karina, Whittemore, Alice S. , Monteiro, Álvaro N.A. , Peixoto, Ana , González‐Neira, Anna , Wu, Anna H. , Lindblom, Annika , Swerdlow, Anthony J. , Cancer), AOCS Study Group & Australian Cancer Study (Ovarian, BioResource, APCB, Ekici, Arif B. , Burwinkel, Barbara , Nordestgaard, Børge G. , Blomqvist, Carl , Phelan, Catherine, McLean, Catriona , Pearce, Celeste Leigh, Vachon, Celine M. , Stegmaier, Christa, Maier, Christiane, Høgdall, Claus , Kang, Daehee , Tessier, Daniel C., Schaid, Daniel J. , Neal, David E. , Eccles, Diana , Flesch‐Janys, Dieter, Wokozorczyk, Dominika, Levine, Douglas A. , Yannoukakos, Drakoulis , Sawyer, Elinor J. , Goode, Ellen L. , Хуснутдинова, Э. К. , Høgdall, Estrid , Song, Fengju, Bruinsma, Fiona, Heitz, Florian , Hamdy, Freddie C. , Olsson, Håkan , Wildiers, Hans , Ulmer, Hans-Ulrich, Pandha, Hardev , Darabi, Hatef, Salvesen, Helga B., Grönberg, Henrik , Brenner, Hermann , Brauch, Hiltrud , Song, Honglin , Lim, Hui-Yi, McNeish, Iain A. , Campbell, Ian , Vergote, Ignace , Lubiński, Jan , Stanford, Janet L. , Benı́tez, Javier , Chang‐Claude, Jenny , Donovan, Jenny , Schildkraut, Joellen M. , Schleutker, Johanna , Hopper, John L. , Kupryjańczyk, Jolanta , Figueroa, Jonine D. , Clements, Judith A. , Knight, Julia A. , Peto, Julian , Cunningham, Julie M. , Pow‐Sang, Julio M. , Batra, Jyotsna , Lu, Karen H., Herkommer, Kathleen , Investigators, kConFab, Matsuo, Keitaro , Muir, Kenneth , Offitt, Kenneth, Chen, Kexin , Moysich, Kirsten B., Aittomäki, Kristiina, Odunsi, Kunle , Kiemeney, Lambertus A. , Massuger, Leon F.A.G. , Hooning, Maartje J. , Pike, Malcolm C., Bolla, Manjeet K. , Luedeke, Manuel, Teixeira, Manuel R. , Goodman, Marc T. , Schmidt, Marjanka K. , Riggan, Marjorie J. , Rossing, Mary Anne, Beckmann, Matthias W. , Moisse, Matthieu , Southey, Melissa C. , Jones, Michael E. , Hildebrandt, Michelle A.T., Hou, Ming‐Feng , Schoemaker, Minouk J. , García‐Closas, Montserrat , Bogdanova, Natalia , Investigators, NBCS, Le, Nhu D. , Orr, Nick , Wentzensen, Nicolas , Pashayan, Nora , Peterlongo, Paolo , Guénel, Pascal , Brennan, Paul , Paulo, Paula , Webb, Penelope M. , Broberg, Per, Fasching, Peter A. , Devilee, Peter , Wang, Qin, Kaneva, Radka , Kopperud, Reidun Kristin, Schmutzler, Rita K., Stephenson, Robert A., MacInnis, Robert J. , Hoover, Robert N. , Winqvist, Robert , Ness, Roberta B., Travis, Ruth C. , Benlloch, Sara, Olson, Sara H. , McDonnell, Shannon K. , Tworoger, Shelley S. , Maia, Sofia , Berndt, Sonja I., Lee, Soo Chin , Teo, Soo‐Hwang , Thibodeau, Stephen N. , Bojesen, Stig E. , Gapstur, Susan M. , Tammela, Teuvo L.J. , Network, the GENICA, Dörk, Thilo , Brüning, Thomas , Wahlfors, Tiina , Edwards, Todd L., Menon, Usha , Hamann, Ute , Mitev, Vanio , Kosma, Veli‐Matti , Setiawan, Veronica Wendy , Kristensen, Vessela, Vogel, Walther , Zheng, Wei , Sieh, Weiva , Blot, William J. , Kluźniak, Wojciech , Gao, Yu‐Tang , Schumacher, Fredrick R. , Freedman, Matthew L., Dunning, Alison M. , Simard, Jacques , Haiman, Christopher A. , Sellers, Thomas A. , Hunter, David J. , Henderson, Brian E., Kraft, Peter , Gayther, Simon A. , Easton, Douglas F. , Chenevix‐Trench, Georgia , Eeles, Rosalind A. , Lambrechts, Diether , Lu, Karen H. , Durocher, Francine , Zheng, Wei , Thorne, Heather , Lambrechts, Diether , Chen, Kexin , Vachon, Celine, Tyrer, Jonathan P. , Kote‐Jarai, Zsofia , Investigators, ABCTB, Gentry‐Maharaj, Aleksandra , Wolk, Alicja , Kierzek, Andrzej , Cox, Angela , Rudolph, Anja , Cancer), AOCS Study Group & Australian Cancer Study (Ovarian, BioResource, APCB, Ziogas, Argyrios , Karlan, Beth Y. , Vachon, Celine M. , Cybulski, Cezary , Slavov, Chavdar , Ambrosone, Christine B. , Teerlink, Craig C. , Stram, Daniel O. , Cramer, Daniel W. , Edwards, Digna R. Velez , Bandera, Elisa V. , Poole, Elizabeth M. , Song, Fengju , Modugno, Francesmary , Wiklund, Fredrik E. , Giles, Graham G. , Risch, Harvey A. , Nevanlinna, Heli , Anton‐Culver, Hoda , Gronwald, Jacek , Doherty, Jennifer A. , Permuth, Jennifer B. , Dennis, Joe , Park, Jong Y. , Czene, Kamila , Khaw, Kay‐Tee , Investigators, kConFab, Moysich, Kirsten B., FitzGerald, Liesel M. , Cook, Linda S. , Cannon‐Albright, Lisa , Hooning, Maartje J. , Aly, Markus , Sanderson, Maureen , Lush, Michael J. , Hildebrandt, Michelle A.T. , Rahman, Nazneen , Investigators, NBCS, Wang, Qin, Cai, Qiuyin , Li, Qiyuan , Bützow, Ralf C. , Milne, Roger L. , Berndt, Sonja I. , Kjær, Susanne K. , Pejovic, Tanja B. , Network, the GENICA, Key, Tim , Kristensen, Vessela N. , Arndt, Volker , Shu, Xiao‐Ou , Berchuck, Andrew , Spurdle, Amanda B. , Chanock, Stephen Jacob , Couch, Fergus J. , Hall, Per N , Pharoah, Paul D.P. , Dörk, Thilo , Lambrechts, Diether , Kiemeney, Lambertus A , McNeish, Iain A , Peterlongo, Paolo , Ramus, Susan J , Teixeira, Manuel R , Teo, Soo H , Tworoger, Shelley S , Webb, Penelope M , Eccles, Diana , Menon, Usha , Lawrenson, Kate , Monteiro, Alvaro N , Swerdlow, Anthony J , Moysich, Kirsten , Campbell, Ian G , Eeles, Rosalind A , Southey, Melissa C , Donovan, Jenny L , Muir, Kenneth , Schleutker, Johanna , Travis, Ruth C , Pashayan, Nora , Michael, Agnieszka , Maclnnis, Robert , Matsuo, Keitaro , Dunning, Alison M , Heitz, Florian , Jones, Michael E , Kupryjanczyk, Jolanta , Lambrechts, Diether , Sieh, Weiva , Brenner, Hermann , Guénel, Pascal , García-Closas, Montserrat , Schmidt, Marjanka K , Ekici, Arif B , Moisse, Matthieu , Michailidou, Kyriaki , Bogdanova, Natalia V , Kraft, Peter , Benitez, Javier , Simard, Jacques , Chenevix-Trench, Georgia , Zheng, Wei , Figueroa, Jonine D , Høgdall, Estrid , Høgdall, Claus K , Kar, Siddhartha , Batra, Jyotsna , Clements, Judith , Setiawan, Veronica W , Yannoukakos, Drakoulis , Devilee, Peter , Lubinski, Jan , Bojesen, Stig E , Schoemaker, Minouk J , Goodman, Marc T , Wildiers, Hans , Mclean, Catriona , Brauch, Hiltrud , Lindblom, Annika , Sawyer, Elinor J , Orr, Nick , McDonnell, Shannon K , Kang, Daehee

Cancer Discovery | July 18, 2016 | Volume: 6 | Issue: 9 | Pages: 1052-1067

10.1158/2159-8290.cd-15-1227 Get It

Abstract Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10−8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type–specific expression quantitative trait locus and enhancer–gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10−5 in the three-cancer meta-analysis. Significance: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052–67. ©2016 AACR. This article is highlighted in the In This Issue feature, p. 932
Mammographic density is the main correlate of tumors detected on ultrasound but not on mammography
Häberle, Lothar , Fasching, Peter A. , Brehm, Barbara, Heusinger, Katharina, Jud, Sebastian M. , Loehberg, Christian R. , Hack, Carolin C. , Preuß, Caroline, Lux, Michael P. , Hartmann, Arndt , Vachon, Celine M. , Meier-Meitinger, M., Beckmann, Matthias W. , Schulz‐Wendtland, Rüdiger, Vachon, Celine M. , Uder, Michael , Lux, Michael P

International Journal of Cancer | July 8, 2016 | Volume: 139 | Issue: 9 | Pages: 1967-1974

10.1002/ijc.30261 Get It

Although mammography screening programs do not include ultrasound examinations, some diagnostic units do provide women with both mammography and ultrasonography. This article is concerned with estimating the risk of a breast cancer patient diagnosed in a hospital‐based mammography unit having a tumor that is visible on ultrasound but not on mammography. A total of 1,399 women with invasive breast cancer from a hospital‐based diagnostic mammography unit were included in this retrospective study. For inclusion, mammograms from the time of the primary diagnosis had to be available for computer‐assisted assessment of percentage mammographic density (PMD), as well as Breast Imaging Reporting and Data System (BIRADS) assessment of mammography. In addition, ultrasound findings were available for the complete cohort as part of routine diagnostic procedures, regardless of any patient or imaging characteristics. Logistic regression analyses were conducted to identify predictors of mammography failure, defined as BIRADS assessment 1 or 2. The probability that the visibility of a tumor might be masked at diagnosis was estimated using a regression model with the identified predictors. Tumors were only visible on ultrasound in 107 cases (7.6%). PMD was the strongest predictor for mammography failure, but age, body mass index and previous breast surgery also influenced the risk, independently of the PMD. Risk probabilities ranged from 1% for a defined low‐risk group up to 40% for a high‐risk group. These findings might help identify women who should be offered ultrasound examinations in addition to mammography.
Extent of atypical hyperplasia stratifies breast cancer risk in 2 independent cohorts of women
Dupont, William D. , Vierkant, Robert A. , Frank, Ryan D. , Frost, Marlene H., Winham, Stacey J. , Smith, Jeffrey R. , Page, David L., Vachon, Celine M. , Ghosh, Karthik, Denison, Lori A., Carter, Jodi M. , Hartmann, Lynn C. , Visscher, Daniel W., Radisky, Derek C. , Hoskin, Tanya L. , Degnim, Amy C. , Sanders, Melinda E. , Vachon, Celine M. , Hieken, Tina J. , Winham, Stacey J , Vierkant, Robert A , Carter, Jodi

Cancer | June 29, 2016 | Volume: 122 | Issue: 19 | Pages: 2971-2978

10.1002/cncr.30153 Get It

BACKGROUNDWomen with atypical hyperplasia (AH) on breast biopsy have a substantially increased risk of breast cancer (BC). Here the BC risk for the extent and subtype of AH is reported for 2 separate cohorts.METHODSAll samples containing AH were included from 2 cohorts of women with benign breast disease (Mayo Clinic and Nashville). Histology review quantified the number of foci of atypical ductal hyperplasia (ADH) and atypical lobular hyperplasia (ALH). The BC risk was stratified for the number of AH foci within AH subtypes.RESULTSThe study included 708 Mayo AH subjects and 466 Nashville AH subjects. In the Mayo cohort, an increasing number of foci of AH was associated with a significant increase in the risk of BC both for ADH (relative risks of 2.61, 5.21, and 6.36 for 1, 2, and ≥3 foci, respectively; P for linear trend = .006) and for ALH (relative risks of 2.56, 3.50, and 6.79 for 1, 2, and ≥3 foci, respectively; P for linear trend = .001). In the Nashville cohort, the relative risks of BC for ADH were 2.70, 5.17, and 15.06 for 1, 2, and ≥3 foci, respectively (P for linear trend < .001); for ALH, the relative risks also increased but not significantly (2.61, 3.48, and 4.02, respectively; P = .148). When the Mayo and Nashville samples were combined, the risk increased significantly for 1, 2, and ≥3 foci: the relative risks were 2.65, 5.19, and 8.94, respectively, for ADH (P < .001) and 2.58, 3.49, and 4.97, respectively, for ALH (P = .001).CONCLUSIONSIn 2 independent cohort studies of benign breast disease, the extent of atypia stratified the long‐term BC risk for ADH and ALH. Cancer 2016;122:2971‐2978. © 2016 American Cancer Society.
Breast cancer risk by the extent and type of atypical hyperplasia
Visscher, Daniel W., Frost, Marlene H., Vierkant, Robert A. , Frank, Ryan D. , Winham, Stacey J. , Vachon, Celine M. , Dupont, William D. , Hartmann, Lynn C. , Radisky, Derek C. , Degnim, Amy C. , Vachon, Celine M. , Winham, Stacey J , Vierkant, Robert A

Cancer | June 28, 2016 | Volume: 122 | Issue: 19 | Pages: 3087-3088

10.1002/cncr.30151 Get It

Abstract IA22: Mammographic density: A risk factor for all breast cancers or only specific subtypes?
Vachon, Celine M. , Chen, Yunn‐Yi , Jensen, Matthew R. , Visscher, Daniel W., Shepherd, John, Fan, Bo , Wu, Fangfang , Beck, Andrew H. , Cummings, Steve, Vachon, Celine M. , Tamimi, Rulla M. , Scott, Christopher G. , Bertrand, Kimberly A. , Norman, Aaron D. , Couch, Fergus J. , Wu, Fang-Fang, Pankratz, V. Shane , Kerlikowske, Karla

Cancer Epidemiology, Biomarkers & Prevention | May 20, 2016 | Volume: 25 | Issue: 3_Supplement | Pages: IA22-IA22

10.1158/1538-7755.disp15-ia22 Get It

Abstract Gene expression profiling has identified molecular subtypes that classify invasive breast cancers into distinct categories that vary in their clinical behavior and response to treatment. These subtypes highlight the many possible biologically and clinically distinct types of breast cancer. Immunohistochemical (IHC) staining of tumor sections using antibody panels has been used as a surrogate for the molecular subtypes identified through gene expression profiling, resulting in a set of intrinsic molecular subtypes. Given the heterogeneity within breast cancer, one might expect that different risk factors influence specific subtypes of breast cancer through various etiologic pathways. We evaluated whether percent mammographic density (MD), the proportion of fibroglandular or white tissue on a mammogram and one of the strongest and most consistent risk factors for breast cancer, is associated equally with all intrinsic molecular subtypes. Data were pooled from six cohort or case-control studies including 3389 women with invasive breast cancer and 9860 without, who underwent screening mammography. Percent MD was assessed from digitized film-screen mammograms (for cases, at a median 4 years prior to diagnosis) using a computer-assisted threshold technique, and categorized as 0-10%, 11-25%, 26-50% and 51%+. Receptor status was abstracted from clinical pathology records and supplemented by IHC staining of tumor sections or microarrays. With estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (HER2) information, we classified tumors into the intrinsic molecular subtypes: Luminal A ( ER+ and/or PR+ and HER2- and grade 1 or 2), Luminal B (ER+ and/or PR+ and HER2+ or Luminal A and grade 3), HER2 expressing (HER2+/ER-/PR-) and triple negative (ER-/PR-/HER2-). For cancers found to be triple negative (TN), we also stained for epidermal growth factor receptor (EGFR) and cytokeratins (CK) 5/6 to differentiate basal-like tumors (positive for EGFR and/or CK 5/6) from the unclassifieds (negative on both EGFR and CK 5/6). We used polytomous logistic regression to calculate the odds (OR) of each of the intrinsic subtypes of breast cancer by categories of percent MD, adjusting for age, BMI and study. Contrasts were constructed and tested within the polytomous model framework to investigate differences in the strength of association of percent MD across subtypes. On average, cases were slightly older (56.4 years [SD=11.3]) than controls (55.8 [10.9]). Of the 3389 invasive breast cancer cases, 2146 (63%) were classified as Luminal A, 709 (21%) as Luminal B, 169 (5%) as HER-2 expressing, and 365(11%) as triple negative (TN). Of the TN tumors, 203 had tumor tissue available and were evaluated for CK 5/6 and EGFR, with 167 (82%) classified as basal-like and 36 (18%) as unclassified. Percent (%) MD was associated with breast cancer risk across all intrinsic subtypes. For Luminal A, compared to women with 11-25% MD (reference), women with 0-10% MD had a reduced risk of breast cancer (OR=0.64 [95% confidence interval (CI): 0.55, 0.74]) while women with 26-50% MD had an OR=1.5 (1.3,1.7) and women with 51%+ MD had the highest risk, OR=2.4 (2.0, 2.8). Similar associations were seen for Luminal B, HER2 expressing, and TN across percent MD categories. The small differences among the percent MD-breast cancer associations observed for the different subtypes were not statistically significant, either when comparing the four (Luminal A, Luminal B, HER-2 expressing and TN; p=0.61) or five categories of subtypes (Luminal A, Luminal B, HER-2 expressing, basal-like, unclassified; p=0.66). Our results suggest percent MD is a risk factor for all intrinsic molecular subtypes. Additional study is needed to examine whether these results hold for younger and older aged women. Understanding the importance of mammographic density measures for subtypes of breast cancer has significance for development of subtype-specific risk models. Citation Format: Celine Vachon, Rulla Tamimi, Yunn-Yi Chen, Christopher Scott, Kimberly Bertrand, Matthew Jensen, Daniel Visscher, Aaron Norman, Fergus Couch, John Shepherd, Bo Fan, Fang-Fang Wu, Lin Ma, Andrew Beck, Steve Cummings, V. Shane Pankratz, Karla Kerlikowske. Mammographic density: A risk factor for all breast cancers or only specific subtypes? [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr IA22.