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Ochs-Balcom HM, Preus L, Du Z, Elston RC, Teerlink CC, Jia G, Guo X, Cai Q, Long J, Ping J, Li B, Stram DO, Shu XO, Sanderson M, Gao G, Ahearn T, Lunetta KL, Zirpoli G, Troester MA, Ruiz-Narváez EA, Haddad SA, Figueroa J, John EM, Bernstein L, Hu JJ, Ziegler RG, Nyante S, Bandera EV, Ingles SA, Mancuso N, Press MF, Deming SL, Rodriguez-Gil JL, Yao S, Ogundiran TO, Ojengbede O, Bolla MK, Dennis J, Dunning AM, Easton DF, Michailidou K, Pharoah PDP, Sandler DP, Taylor JA, Wang Q, O’Brien KM, Weinberg CR, Kitahara CM, Blot W, Nathanson KL, Hennis A, Nemesure B, Ambs S, Sucheston-Campbell LE, Bensen JT, Chanock SJ, Olshan AF, Ambrosone CB, Olopade OI, the Ghana Breast Health Study Team, Conti DV, Palmer J, García-Closas M, Huo D, Zheng W, Haiman C. Novel breast cancer susceptibility loci under linkage peaks identified in African ancestry consortia. Hum Mol Genet 2024; 33:687-697. [PMID: 38263910 PMCID: PMC11000665 DOI: 10.1093/hmg/ddae002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 01/25/2024] Open
Abstract
BACKGROUND Expansion of genome-wide association studies across population groups is needed to improve our understanding of shared and unique genetic contributions to breast cancer. We performed association and replication studies guided by a priori linkage findings from African ancestry (AA) relative pairs. METHODS We performed fixed-effect inverse-variance weighted meta-analysis under three significant AA breast cancer linkage peaks (3q26-27, 12q22-23, and 16q21-22) in 9241 AA cases and 10 193 AA controls. We examined associations with overall breast cancer as well as estrogen receptor (ER)-positive and negative subtypes (193,132 SNPs). We replicated associations in the African-ancestry Breast Cancer Genetic Consortium (AABCG). RESULTS In AA women, we identified two associations on chr12q for overall breast cancer (rs1420647, OR = 1.15, p = 2.50×10-6; rs12322371, OR = 1.14, p = 3.15×10-6), and one for ER-negative breast cancer (rs77006600, OR = 1.67, p = 3.51×10-6). On chr3, we identified two associations with ER-negative disease (rs184090918, OR = 3.70, p = 1.23×10-5; rs76959804, OR = 3.57, p = 1.77×10-5) and on chr16q we identified an association with ER-negative disease (rs34147411, OR = 1.62, p = 8.82×10-6). In the replication study, the chr3 associations were significant and effect sizes were larger (rs184090918, OR: 6.66, 95% CI: 1.43, 31.01; rs76959804, OR: 5.24, 95% CI: 1.70, 16.16). CONCLUSION The two chr3 SNPs are upstream to open chromatin ENSR00000710716, a regulatory feature that is actively regulated in mammary tissues, providing evidence that variants in this chr3 region may have a regulatory role in our target organ. Our study provides support for breast cancer variant discovery using prioritization based on linkage evidence.
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Affiliation(s)
- Heather M Ochs-Balcom
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, 270 Farber Hall, Buffalo, NY 14214, United States
| | - Leah Preus
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, 270 Farber Hall, Buffalo, NY 14214, United States
| | - Zhaohui Du
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
- Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave, N. Seattle, WA 98109, United States
| | - Robert C Elston
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, United States
| | - Craig C Teerlink
- Department of Internal Medicine, University of Utah School of Medicine, 30 North Mario Capecchi Dr, 3rd Floor North, Salt Lake City, UT 84112, United States
| | - Guochong Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Jie Ping
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Bingshan Li
- Department of Molecular Physiology and Biophysics, Vanderbilt University, 707 Light Hall 2215 Garland Avenue, Nashville, TN 37232, United States
| | - Daniel O Stram
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Maureen Sanderson
- Department of Family and Community Medicine, Meharry Medical College, 1005 Dr. DB Todd Jr, Blvd. Nashville, TN 37208, United States
| | - Guimin Gao
- Department of Public Health Sciences, University of Chicago, 5841 S. Maryland Ave., Chicago, IL 60637, United States
| | - Thomas Ahearn
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University, 715 Albany St, Boston, MA 02118, United States
| | - Gary Zirpoli
- Slone Epidemiology Center, Boston University, L-7, 72 East Concord Street, Boston, MA 02118, United States
| | - Melissa A Troester
- Department of Epidemiology, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, 135 Dauer Drive, CB 7435, Chapel Hill, NC 27599, United States
| | - Edward A Ruiz-Narváez
- Department of Nutritional Sciences, University of Michigan School of Public Health, 1860 SPH I, 1415 Washington Heights, Ann Arbor, MI 48109, United States
| | - Stephen A Haddad
- Slone Epidemiology Center, Boston University, L-7, 72 East Concord Street, Boston, MA 02118, United States
| | - Jonine Figueroa
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
- Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, 9 Little France Road, Edinburgh, EH16 4UX, United Kingdom
- Cancer Research UK Edinburgh Centre, Crewe Rd S, Edinburgh, EH4 2XR, United Kingdom
| | - Esther M John
- Department of Epidemiology & Population Health, Stanford University School of Medicine, 3145 Porter Dr, Suite E223, MC 5393, Palo Alto, CA 94304, United States
- Department of Medicine (Oncology), Stanford University School of Medicine, 291 Campus Drive Li Ka Shing Building, Stanford, CA 94305, United States
| | - Leslie Bernstein
- Division of Biomarkers of Early Detection and Prevention Department of Population Sciences, Beckman Research Institute of the City of Hope, City of Hope Comprehensive Cancer Center, 1500 East Duarte Road, Duarte, CA 91010, United States
| | - Jennifer J Hu
- Sylvester Comprehensive Cancer Center and Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14th St, CRB 1511, Miami, FL 33136, United States
| | - Regina G Ziegler
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - Sarah Nyante
- Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, 130 Mason Farm Rd., Chapel Hill, NC 27599, United States
| | - Elisa V Bandera
- Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute of New Jersey, 120 Albany Street, Tower 2, 8th Floor, New Brunswick, NJ 08903, United States
| | - Sue A Ingles
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| | - Nicholas Mancuso
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| | - Michael F Press
- Department of Pathology, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1441 Eastlake Ave., Los Angeles, CA 90033, United States
| | - Sandra L Deming
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Jorge L Rodriguez-Gil
- Genomics, Development and Disease Section, Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, 31 Center Dr, Bethesda, MD 20894, United States
- Medical Scientist Training Program, School of Medicine and Public Health, University of Wisconsin-Madison, 750 Highland Ave., Madison, WI 53705, United States
| | - Song Yao
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, United States
| | - Temidayo O Ogundiran
- Department of Surgery, College of Medicine, University of Ibadan, Queen Elizabeth II Road, Ibadan, 200285, Nigeria
| | - Oladosu Ojengbede
- Center for Population and Reproductive Health, College of Medicine, University of Ibadan, UCH, Queen Elizabeth II Road, Ibadan, 200285, Nigeria
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, 2 Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, 2 Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Kyriaki Michailidou
- Biostatistics Unit, The Cyprus Institute of Neurology & Genetics, Iroon Avenue 6, 2371 Ayius Dometios, Nicosia, Cyprus
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, United States
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, United States
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, 2 Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Katie M O’Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, United States
| | - Clarice R Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, United States
| | - Cari M Kitahara
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - William Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
- International Epidemiology Institute, 1455 Research Boulevard, Rockville, MD 20850, United States
| | - Katherine L Nathanson
- Department of Medicine, Abramson Cancer Center, The Perelman School of Medicine at the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19140, United States
| | - Anselm Hennis
- Chronic Disease Research Centre and Faculty of Medical Sciences, University of the West Indies, Jemmotts Lane, Avalon, Bridgetown, Barbados
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Stony Brook University, 100 Nicolls Road, Stony Brook, NY 11794, United States
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, National Cancer Institute, 37 Convent Drive, Bethesda, MD 20892, United States
| | - Lara E Sucheston-Campbell
- College of Pharmacy, The Ohio State University, 217 Lloyd M. Parks Hall, 500 West 12th Ave., Columbus, OH 43210, United States
- College of Veterinary Medicine, The Ohio State University, 1900 Coffey Road, Columbus, OH 43210, United States
| | - Jeannette T Bensen
- Department of Epidemiology, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, 135 Dauer Drive, CB 7435, Chapel Hill, NC 27599, United States
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - Andrew F Olshan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 170 Rosenau Hall, CB #7400, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, United States
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, University of Chicago, 5841 S Maryland Avenue, Chicago, IL 60637, United States
| | | | - David V Conti
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| | - Julie Palmer
- Slone Epidemiology Center, Boston University, L-7, 72 East Concord Street, Boston, MA 02118, United States
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, 5841 S. Maryland Ave., Chicago, IL 60637, United States
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Christopher Haiman
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
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Rattsev I, Stearns V, Blackford AL, Hertz DL, Smith KL, Rae JM, Taylor CO. Incorporation of emergent symptoms and genetic covariates improves prediction of aromatase inhibitor therapy discontinuation. JAMIA Open 2024; 7:ooae006. [PMID: 38250582 PMCID: PMC10799747 DOI: 10.1093/jamiaopen/ooae006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Revised: 08/09/2023] [Accepted: 01/08/2024] [Indexed: 01/23/2024] Open
Abstract
Objectives Early discontinuation is common among breast cancer patients taking aromatase inhibitors (AIs). Although several predictors have been identified, it is unclear how to simultaneously consider multiple risk factors for an individual. We sought to develop a tool for prediction of AI discontinuation and to explore how predictive value of risk factors changes with time. Materials and Methods Survival machine learning was used to predict time-to-discontinuation of AIs in 181 women who enrolled in a prospective cohort. Models were evaluated via time-dependent area under the curve (AUC), c-index, and integrated Brier score. Feature importance was analysis was conducted via Shapley Additive Explanations (SHAP) and time-dependence of their predictive value was analyzed by time-dependent AUC. Personalized survival curves were constructed for risk communication. Results The best-performing model incorporated genetic risk factors and changes in patient-reported outcomes, achieving mean time-dependent AUC of 0.66, and AUC of 0.72 and 0.67 at 6- and 12-month cutoffs, respectively. The most significant features included variants in ESR1 and emergent symptoms. Predictive value of genetic risk factors was highest in the first year of treatment. Decrease in physical function was the strongest independent predictor at follow-up. Discussion and Conclusion Incorporation of genomic and 3-month follow-up data improved the ability of the models to identify the individuals at risk of AI discontinuation. Genetic risk factors were particularly important for predicting early discontinuers. This study provides insight into the complex nature of AI discontinuation and highlights the importance of incorporating genetic risk factors and emergent symptoms into prediction models.
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Affiliation(s)
- Ilia Rattsev
- Institute for Computational Medicine, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, 21218, United States
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, 21218, United States
| | - Vered Stearns
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, United States
| | - Amanda L Blackford
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, United States
| | - Daniel L Hertz
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, MI, 48109, United States
| | - Karen L Smith
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, United States
| | - James M Rae
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, 48109, United States
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI, 48109, United States
| | - Casey Overby Taylor
- Institute for Computational Medicine, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, 21218, United States
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, 21218, United States
- Department of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, United States
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Wolfson EA, Schonberg MA, Eliassen AH, Bertrand KA, Shvetsov YB, Rosner BA, Palmer JR, LaCroix AZ, Chlebowski RT, Nelson RA, Ngo LH. Validating a model for predicting breast cancer and nonbreast cancer death in women aged 55 years and older. J Natl Cancer Inst 2024; 116:81-96. [PMID: 37676833 PMCID: PMC10777669 DOI: 10.1093/jnci/djad188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/24/2023] [Accepted: 08/29/2023] [Indexed: 09/09/2023] Open
Abstract
BACKGROUND To support mammography screening decision making, we developed a competing-risk model to estimate 5-year breast cancer risk and 10-year nonbreast cancer death for women aged 55 years and older using Nurses' Health Study data and examined model performance in the Black Women's Health Study (BWHS). Here, we examine model performance in predicting 10-year outcomes in the BWHS, Women's Health Initiative-Extension Study (WHI-ES), and Multiethnic Cohort (MEC) and compare model performance to existing breast cancer prediction models. METHODS We used competing-risk regression and Royston and Altman methods for validating survival models to calculate our model's calibration and discrimination (C index) in BWHS (n = 17 380), WHI-ES (n = 106 894), and MEC (n = 49 668). The Nurses' Health Study development cohort (n = 48 102) regression coefficients were applied to the validation cohorts. We compared our model's performance with breast cancer risk assessment tool (Gail) and International Breast Cancer Intervention Study (IBIS) models by computing breast cancer risk estimates and C statistics. RESULTS When predicting 10-year breast cancer risk, our model's C index was 0.569 in BWHS, 0.572 in WHI-ES, and 0.576 in MEC. The Gail model's C statistic was 0.554 in BWHS, 0.564 in WHI-ES, and 0.551 in MEC; IBIS's C statistic was 0.547 in BWHS, 0.552 in WHI-ES, and 0.562 in MEC. The Gail model underpredicted breast cancer risk in WHI-ES; IBIS underpredicted breast cancer risk in WHI-ES and in MEC but overpredicted breast cancer risk in BWHS. Our model calibrated well. Our model's C index for predicting 10-year nonbreast cancer death was 0.760 in WHI-ES and 0.763 in MEC. CONCLUSIONS Our competing-risk model performs as well as existing breast cancer prediction models in diverse cohorts and predicts nonbreast cancer death. We are developing a website to disseminate our model.
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Affiliation(s)
- Emily A Wolfson
- Division of General Medicine and Primary Care, Department of Medicine, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Mara A Schonberg
- Division of General Medicine and Primary Care, Department of Medicine, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - A Heather Eliassen
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Harvard School of Public Health, Boston, MA, USA
| | - Kimberly A Bertrand
- Slone Epidemiology Center at Boston University and Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Yurii B Shvetsov
- University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Bernard A Rosner
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Harvard School of Public Health, Boston, MA, USA
| | - Julie R Palmer
- Slone Epidemiology Center at Boston University and Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Andrea Z LaCroix
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | | | - Rebecca A Nelson
- Department of Computational and Quantitative Medicine, City of Hope, Duarte, CA, USA
| | - Long H Ngo
- Division of General Medicine and Primary Care, Department of Medicine, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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4
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Brauer ER, Petersen L, Ganz PA. Survivorship care in breast cancer: understanding implementation barriers through the lens of the Theoretical Domains Framework. JNCI Cancer Spectr 2024; 8:pkad108. [PMID: 38128018 PMCID: PMC10868380 DOI: 10.1093/jncics/pkad108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 12/06/2023] [Accepted: 12/18/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND Breast cancer survivorship guidelines with specific recommendations on managing long-term effects are available, but uptake in clinical practice remains low. Using the lens of the Theoretical Domains Framework, we aimed to understand key factors in guideline-concordant management of long-term effects to inform future implementation efforts in clinical practice contexts. METHODS As part of a broader survey of oncologists, a theory-guided questionnaire was developed. Oncologists were asked to report level of agreement with Theoretical Domains Framework-based statements, current usage and perceived value of survivorship resources, and frequency of managing long-term effects in routine care. Data analyses included psychometric assessment of the questionnaire, descriptive summaries of theoretical domains and survivorship resources, and multivariable logistic regression models. RESULTS In total, 217 oncologists completed the Theoretical Domains Framework-based questionnaire; 54% of oncologists reported "always or almost always" evaluating physical effects at routine survivorship appointments, while 34% did so for psychosocial effects. In regression models, Environmental Context and Resources was the only theoretical domain found to be statistically significantly associated with "always or almost always" evaluating both physical (odds ratio = 0.29, 95% confidence interval = 0.09 to 0.80) and psychosocial (odds ratio = 0.09, 95% confidence interval = 0.02 to 0.35) effects. CONCLUSIONS Findings support application of the Theoretical Domains Framework in understanding oncologists' behaviors and perceived barriers in managing long-term effects in breast cancer survivors. In future implementation efforts, this theory-informed approach can be used to target relevant domains and strategies focused on embedding guideline recommendations in the clinical context through structured resources and environmental supports.
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Affiliation(s)
- Eden R Brauer
- School of Nursing, University of California Los Angeles, Los Angeles, CA, USA
- Center for Cancer Prevention and Control Research, Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, CA, USA
| | - Laura Petersen
- Center for Cancer Prevention and Control Research, Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, CA, USA
| | - Patricia A Ganz
- Center for Cancer Prevention and Control Research, Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, CA, USA
- Division of Hematology-Oncology, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Department of Health Policy and Management, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
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5
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McDowell SA, Milette S, Doré S, Yu MW, Sorin M, Wilson L, Desharnais L, Cristea A, Varol O, Atallah A, Swaby A, Breton V, Arabzadeh A, Petrecca S, Loucif H, Bhagrath A, De Meo M, Lach KD, Issac MS, Fiset B, Rayes RF, Mandl JN, Fritz JH, Fiset PO, Holt PR, Dannenberg AJ, Spicer JD, Walsh LA, Quail DF. Obesity alters monocyte developmental trajectories to enhance metastasis. J Exp Med 2023; 220:e20220509. [PMID: 37166450 PMCID: PMC10182775 DOI: 10.1084/jem.20220509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 02/27/2023] [Accepted: 04/19/2023] [Indexed: 05/12/2023] Open
Abstract
Obesity is characterized by chronic systemic inflammation and enhances cancer metastasis and mortality. Obesity promotes breast cancer metastasis to lung in a neutrophil-dependent manner; however, the upstream regulatory mechanisms of this process remain unknown. Here, we show that obesity-induced monocytes underlie neutrophil activation and breast cancer lung metastasis. Using mass cytometry, obesity favors the expansion of myeloid lineages while restricting lymphoid cells within the peripheral blood. RNA sequencing and flow cytometry revealed that obesity-associated monocytes resemble professional antigen-presenting cells due to a shift in their development and exhibit enhanced MHCII expression and CXCL2 production. Monocyte induction of the CXCL2-CXCR2 axis underlies neutrophil activation and release of neutrophil extracellular traps to promote metastasis, and enhancement of this signaling axis is observed in lung metastases from obese cancer patients. Our findings provide mechanistic insight into the relationship between obesity and cancer by broadening our understanding of the interactive role that myeloid cells play in this process.
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Affiliation(s)
- Sheri A.C. McDowell
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Physiology, McGill University, Montreal, Canada
| | - Simon Milette
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Medicine, Division of Experimental Medicine, McGill University, Montreal, Canada
| | - Samuel Doré
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Human Genetics, McGill University, Montreal, Canada
| | - Miranda W. Yu
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Physiology, McGill University, Montreal, Canada
| | - Mark Sorin
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Human Genetics, McGill University, Montreal, Canada
| | - Liam Wilson
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Physiology, McGill University, Montreal, Canada
| | - Lysanne Desharnais
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Human Genetics, McGill University, Montreal, Canada
| | - Alyssa Cristea
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Medicine, Division of Experimental Medicine, McGill University, Montreal, Canada
| | - Ozgun Varol
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Medicine, Division of Experimental Medicine, McGill University, Montreal, Canada
| | - Aline Atallah
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Medicine, Division of Experimental Medicine, McGill University, Montreal, Canada
| | - Anikka Swaby
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Medicine, Division of Experimental Medicine, McGill University, Montreal, Canada
| | - Valérie Breton
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
| | | | - Sarah Petrecca
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Medicine, Division of Experimental Medicine, McGill University, Montreal, Canada
| | - Hamza Loucif
- Department of Microbiology and Immunology, McGill University, Montreal, Canada
- McGill University Research Centre on Complex Traits, Montreal, Canada
| | - Aanya Bhagrath
- Department of Physiology, McGill University, Montreal, Canada
- McGill University Research Centre on Complex Traits, Montreal, Canada
| | - Meghan De Meo
- Department of Experimental Surgery, McGill University, Montreal, Canada
| | - Katherine D. Lach
- Department of Pathology, Faculty of Medicine, McGill University, Montreal, Canada
| | - Marianne S.M. Issac
- Department of Pathology, Faculty of Medicine, McGill University, Montreal, Canada
| | - Benoit Fiset
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
| | - Roni F. Rayes
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
| | - Judith N. Mandl
- Department of Physiology, McGill University, Montreal, Canada
- Department of Microbiology and Immunology, McGill University, Montreal, Canada
- McGill University Research Centre on Complex Traits, Montreal, Canada
| | - Jörg H. Fritz
- Department of Microbiology and Immunology, McGill University, Montreal, Canada
- McGill University Research Centre on Complex Traits, Montreal, Canada
| | - Pierre O. Fiset
- Department of Pathology, Faculty of Medicine, McGill University, Montreal, Canada
| | - Peter R. Holt
- Laboratory of Biochemical Genetics and Metabolism, Rockefeller University, New Nork, NY, USA
| | - Andrew J. Dannenberg
- Department of Medicine (retired), Weill Cornell Medical College, New York, NY, USA
| | - Jonathan D. Spicer
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Medicine, Division of Experimental Medicine, McGill University, Montreal, Canada
- Department of Surgery, McGill University Health Centre, Montreal, Canada
| | - Logan A. Walsh
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Human Genetics, McGill University, Montreal, Canada
| | - Daniela F. Quail
- Rosalind and Morris Goodman Cancer Institute, Montreal, Canada
- Department of Physiology, McGill University, Montreal, Canada
- Department of Medicine, Division of Experimental Medicine, McGill University, Montreal, Canada
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6
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Chavez-MacGregor M, Lei X, Malinowski C, Zhao H, Shih YC, Giordano SH. Medicaid expansion, chemotherapy delays, and racial disparities among women with early-stage breast cancer. J Natl Cancer Inst 2023; 115:644-651. [PMID: 36794921 PMCID: PMC10248833 DOI: 10.1093/jnci/djad033] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 12/19/2022] [Accepted: 02/13/2023] [Indexed: 02/17/2023] Open
Abstract
BACKGROUND Medicaid expansion under the Affordable Care Act extends eligibility for participating states and has been associated with improved outcomes by facilitating access to care. Delayed initiation of adjuvant chemotherapy is associated with worse outcomes among patients with early-stage breast cancer (BC). The impact of Medicaid expansion in narrowing delays by race and ethnicity has not been studied, to our knowledge. METHODS This was a population-based study using the National Cancer Database. Patients diagnosed with primary early-stage BC between 2007 and 2017 residing in states that underwent Medicaid expansion in January 2014 were included. Time to chemotherapy initiation and proportion of patients experiencing chemotherapy delays (>60 days) were evaluated using difference-in-difference and Cox proportional hazards models in preexpansion and postexpansion periods according to race and ethnicity. RESULTS A total 100 643 patients were included (63 313 preexpansion and 37 330 postexpansion). After Medicaid expansion, the proportion of patients experiencing chemotherapy initiation delay decreased from 23.4% to 19.4%. The absolute decrease was 3.2, 5.3, 6.4, and 4.8 percentage points (ppt) for Black, Hispanic, White, and Other patients. Compared with White patients, statistically significant adjusted difference-in-differences were observed for Black (-2.1 ppt, 95% confidence interval [CI] = -3.7% to -0.5%) and Hispanic patients (-3.2 ppt, 95% CI = -5.6% to -0.9%). Statistically significant reductions in time to chemotherapy between expansion periods were observed among White patients (adjusted hazard ratio = .11, 95% CI = 1.09 to 1.12) and those belonging to racialized groups (adjusted hazard ratio = 1.14, 95% CI = 1.11 to 1.17). CONCLUSIONS Among patients with early-stage BC, Medicaid expansion was associated with a reduction in racial disparities by decreasing the gap in the proportion of Black and Hispanic patients experiencing delays in adjuvant chemotherapy initiation.
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Affiliation(s)
- Mariana Chavez-MacGregor
- Department of Health Services Research, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Breast Cancer Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xiudong Lei
- Department of Health Services Research, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Catalina Malinowski
- Department of Health Services Research, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Hui Zhao
- Department of Health Services Research, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ya-Chen Shih
- Department of Health Services Research, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sharon H Giordano
- Department of Health Services Research, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Breast Cancer Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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7
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Gharzai LA, Jagsi R. Incorporating financial toxicity considerations into clinical trial design to facilitate patient-centered decision-making in oncology. Cancer 2023; 129:1143-1148. [PMID: 36775839 DOI: 10.1002/cncr.34677] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/14/2023]
Abstract
PLAIN LANGUAGE SUMMARY Financial toxicity is increasingly being recognized as an important and devastating consequence of cancer treatment that receives little attention when clinical trials are being designed. There is a significant need to obtain this important information in an era of increasingly expensive anticancer treatments. Patients who are informed of all implications of therapy-efficacy, side effects, cost, and broader financial impact-are able to select the best cancer treatment for themselves.
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Affiliation(s)
| | - Reshma Jagsi
- University of Michigan, Ann Arbor, Michigan, USA
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8
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Morgan E, O'Neill C, Bardot A, Walsh P, Soerjomataram I, Arnold M. The Challenges of Collecting Long-Term Outcomes in Cancer Patients on the Population-Level: The Case of Metastatic Breast Cancer. J Registry Manag 2023; 50:173-175. [PMID: 38504704 PMCID: PMC10945923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Affiliation(s)
- Eileen Morgan
- Cancer Surveillance Branch, International Agency for Research on Cancer, Lyon, France
| | | | - Aude Bardot
- Cancer Surveillance Branch, International Agency for Research on Cancer, Lyon, France
| | - Paul Walsh
- National Cancer Registry Ireland, Cork, Republic of Ireland
| | | | - Melina Arnold
- Cancer Surveillance Branch, International Agency for Research on Cancer, Lyon, France
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9
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Hou J, Liang S, Xu C, Wei Y, Wang Y, Tan Y, Sahni N, McGrail D, Bernatchez C, Davies M, Li Y, Chen R, Yi S, Chen Y, Yee C, Chen K, Peng W. Single-cell CRISPR immune screens reveal immunological roles of tumor intrinsic factors. NAR Cancer 2022; 4:zcac038. [PMID: 36518525 PMCID: PMC9732527 DOI: 10.1093/narcan/zcac038] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 10/15/2022] [Accepted: 11/16/2022] [Indexed: 12/14/2022] Open
Abstract
Genetic screens are widely exploited to develop novel therapeutic approaches for cancer treatment. With recent advances in single-cell technology, single-cell CRISPR screen (scCRISPR) platforms provide opportunities for target validation and mechanistic studies in a high-throughput manner. Here, we aim to establish scCRISPR platforms which are suitable for immune-related screens involving multiple cell types. We integrated two scCRISPR platforms, namely Perturb-seq and CROP-seq, with both in vitro and in vivo immune screens. By leveraging previously generated resources, we optimized experimental conditions and data analysis pipelines to achieve better consistency between results from high-throughput and individual validations. Furthermore, we evaluated the performance of scCRISPR immune screens in determining underlying mechanisms of tumor intrinsic immune regulation. Our results showed that scCRISPR platforms can simultaneously characterize gene expression profiles and perturbation effects present in individual cells in different immune screen conditions. Results from scCRISPR immune screens also predict transcriptional phenotype associated with clinical responses to cancer immunotherapy. More importantly, scCRISPR screen platforms reveal the interactive relationship between targeting tumor intrinsic factors and T cell-mediated antitumor immune response which cannot be easily assessed by bulk RNA-seq. Collectively, scCRISPR immune screens provide scalable and reliable platforms to elucidate molecular determinants of tumor immune resistance.
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Affiliation(s)
- Jiakai Hou
- Department of Biology and Biochemistry, University of Houston, Houston, TX, USA
| | - Shaoheng Liang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Chunyu Xu
- Department of Biology and Biochemistry, University of Houston, Houston, TX, USA
| | - Yanjun Wei
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yunfei Wang
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yukun Tan
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Nidhi Sahni
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Daniel J McGrail
- Center for Immunotherapy and Precision Immuno-Oncology, Cleveland Clinic, Cleveland, OH, USA
| | - Chantale Bernatchez
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Michael Davies
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yumei Li
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Rui Chen
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - S Stephen Yi
- Department of Oncology, Livestrong Cancer Institutes, and Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA
- Interdisciplinary Life Sciences Graduate Programs (ILSGP) and Oden Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin, Austin, TX, USA
| | - Yiwen Chen
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Cassian Yee
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ken Chen
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Weiyi Peng
- Department of Biology and Biochemistry, University of Houston, Houston, TX, USA
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10
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Gao G, Zhao F, Ahearn TU, Lunetta KL, Troester MA, Du Z, Ogundiran TO, Ojengbede O, Blot W, Nathanson KL, Domchek SM, Nemesure B, Hennis A, Ambs S, McClellan J, Nie M, Bertrand K, Zirpoli G, Yao S, Olshan AF, Bensen JT, Bandera EV, Nyante S, Conti DV, Press MF, Ingles SA, John EM, Bernstein L, Hu JJ, Deming-Halverson SL, Chanock SJ, Ziegler RG, Rodriguez-Gil JL, Sucheston-Campbell LE, Sandler DP, Taylor JA, Kitahara CM, O’Brien KM, Bolla MK, Dennis J, Dunning AM, Easton DF, Michailidou K, Pharoah PDP, Wang Q, Figueroa J, Biritwum R, Adjei E, Wiafe S, Ambrosone CB, Zheng W, Olopade OI, García-Closas M, Palmer JR, Haiman CA, Huo D. Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach. Hum Mol Genet 2022; 31:3133-3143. [PMID: 35554533 PMCID: PMC9476624 DOI: 10.1093/hmg/ddac102] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 03/29/2022] [Accepted: 04/26/2022] [Indexed: 11/13/2022] Open
Abstract
Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.
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Affiliation(s)
- Guimin Gao
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | - Fangyuan Zhao
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | - Thomas U Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Melissa A Troester
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zhaohui Du
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Temidayo O Ogundiran
- Department of Surgery, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oladosu Ojengbede
- Centre for Population & Reproductive Health, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - William Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Katherine L Nathanson
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Susan M Domchek
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY 11794, USA
| | - Anselm Hennis
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY 11794, USA
- University of the West Indies, Bridgetown, Bardados
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Julian McClellan
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | - Mark Nie
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | | | - Gary Zirpoli
- Slone Epidemiology Center, Boston University, Boston, MA 02215, USA
| | - Song Yao
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA
| | - Andrew F Olshan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jeannette T Bensen
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Elisa V Bandera
- Cancer Prevention and Control Program, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ 08903, USA
| | - Sarah Nyante
- Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - David V Conti
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Michael F Press
- Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Sue A Ingles
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Esther M John
- Departments of Epidemiology & Population Health and of Medicine (Oncology) and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Leslie Bernstein
- Biomarkers of Early Detection and Prevention, Department of Population Sciences, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA
| | - Jennifer J Hu
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Sandra L Deming-Halverson
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Regina G Ziegler
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Jorge L Rodriguez-Gil
- Genomics, Development and Disease Section, Genetic Disease Research Branch, National Human Genome Research Institute, Bethesda, MD 20894, USA
| | - Lara E Sucheston-Campbell
- Department of Veterinary Biosciences, College of Veterinary Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Cari M Kitahara
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Katie M O’Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Manjeet K Bolla
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Joe Dennis
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Alison M Dunning
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Douglas F Easton
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Kyriaki Michailidou
- Biostatistics Unit, The Cyprus Institute of Neurology & Genetics, Nicosia 2371, Cyprus
| | - Paul D P Pharoah
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Qin Wang
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Jonine Figueroa
- Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, Edinburgh EH16 5TJ, UK
- Cancer Research UK Edinburgh Centre, Edinburgh EH4 2XR, UK
| | | | | | - Seth Wiafe
- School of Public Health, Loma Linda University, Loma Linda, CA 92350, USA
| | | | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics & Global Health, The University of Chicago, Chicago, IL 60637, USA
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Julie R Palmer
- Slone Epidemiology Center, Boston University, Boston, MA 02215, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Dezheng Huo
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
- Center for Clinical Cancer Genetics & Global Health, The University of Chicago, Chicago, IL 60637, USA
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11
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Li Q, Jiang B, Guo J, Shao H, Del Priore IS, Chang Q, Kudo R, Li Z, Razavi P, Liu B, Boghossian AS, Rees MG, Ronan MM, Roth JA, Donovan KA, Palafox M, Reis-Filho JS, de Stanchina E, Fischer ES, Rosen N, Serra V, Koff A, Chodera JD, Gray NS, Chandarlapaty S. INK4 Tumor Suppressor Proteins Mediate Resistance to CDK4/6 Kinase Inhibitors. Cancer Discov 2022; 12:356-371. [PMID: 34544752 PMCID: PMC8831444 DOI: 10.1158/2159-8290.cd-20-1726] [Citation(s) in RCA: 62] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 07/13/2021] [Accepted: 09/15/2021] [Indexed: 01/22/2023]
Abstract
Cyclin-dependent kinases 4 and 6 (CDK4/6) represent a major therapeutic vulnerability for breast cancer. The kinases are clinically targeted via ATP competitive inhibitors (CDK4/6i); however, drug resistance commonly emerges over time. To understand CDK4/6i resistance, we surveyed over 1,300 breast cancers and identified several genetic alterations (e.g., FAT1, PTEN, or ARID1A loss) converging on upregulation of CDK6. Mechanistically, we demonstrate CDK6 causes resistance by inducing and binding CDK inhibitor INK4 proteins (e.g., p18INK4C). In vitro binding and kinase assays together with physical modeling reveal that the p18INK4C-cyclin D-CDK6 complex occludes CDK4/6i binding while only weakly suppressing ATP binding. Suppression of INK4 expression or its binding to CDK6 restores CDK4/6i sensitivity. To overcome this constraint, we developed bifunctional degraders conjugating palbociclib with E3 ligands. Two resulting lead compounds potently degraded CDK4/6, leading to substantial antitumor effects in vivo, demonstrating the promising therapeutic potential for retargeting CDK4/6 despite CDK4/6i resistance. SIGNIFICANCE: CDK4/6 kinase activation represents a common mechanism by which oncogenic signaling induces proliferation and is potentially targetable by ATP competitive inhibitors. We identify a CDK6-INK4 complex that is resilient to current-generation inhibitors and develop a new strategy for more effective inhibition of CDK4/6 kinases.This article is highlighted in the In This Issue feature, p. 275.
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Affiliation(s)
- Qing Li
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Baishan Jiang
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts
| | - Jiaye Guo
- Computational & Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Hong Shao
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Isabella S Del Priore
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Qing Chang
- Anti-Tumor Assessment, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Rei Kudo
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Zhiqiang Li
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Pedram Razavi
- Breast Medicine Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
- Weill Cornell Medical College, New York, New York
| | - Bo Liu
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | | | - Matthew G Rees
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Melissa M Ronan
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Jennifer A Roth
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Katherine A Donovan
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts
| | - Marta Palafox
- Vall d'Hebron Institute of Oncology, Barcelona, Spain
| | - Jorge S Reis-Filho
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Elisa de Stanchina
- Anti-Tumor Assessment, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Eric S Fischer
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts
| | - Neal Rosen
- Program in Molecular Pharmacology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Violeta Serra
- Vall d'Hebron Institute of Oncology, Barcelona, Spain
| | - Andrew Koff
- Program in Molecular Biology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - John D Chodera
- Computational & Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Nathanael S Gray
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts
| | - Sarat Chandarlapaty
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York.
- Breast Medicine Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
- Weill Cornell Medical College, New York, New York
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Press DJ, Shariff-Marco S, Lichtensztajn DY, Lauderdale D, Murphy AB, Inamdar PP, DeRouen MC, Hamilton AS, Yang J, Lin K, Hedeker D, Haiman CA, Cheng I, Gomez SL. Contributions of Social Factors to Disparities in Prostate Cancer Risk Profiles among Black Men and Non-Hispanic White Men with Prostate Cancer in California. Cancer Epidemiol Biomarkers Prev 2022; 31:404-412. [PMID: 34853020 PMCID: PMC8825684 DOI: 10.1158/1055-9965.epi-21-0697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 09/20/2021] [Accepted: 11/22/2021] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Black men are more likely than Non-Hispanic White (NHW) men to be diagnosed with high-risk prostate cancer. We examined the extent to which social factors were associated with differences in prostate cancer risk profiles between Black men and NHW men [using a modification to the original D'Amico risk groups based on prostate specific antigen (PSA), Gleason score (GS), and TNM stage (stage)], based on individual and combined clinicopathologic characteristics. METHODS We conducted a cross-sectional population-based study of 23,555 Black men and 146,889 NHW men diagnosed with prostate cancer in the California Cancer Registry from 2004 to 2017. We conducted multivariable logistic regression to examine the association of year of diagnosis, block group-level neighborhood socioeconomic status (nSES), marital status, and insurance type on differences in prostate cancer risk profiles between Black and NHW men. RESULTS High PSA (>20 ng/mL), GS, stage, individually and combined prostate cancer risk profiles were more common among Black men versus NHW men. In fully adjusted models, relative to NHW men, we observed a persistent 67% increased odds of high PSA among Black men. nSES was the factor most strongly associated with racial disparity in high PSA, accounting for 25% of the difference. Marital status was the factor that was second most associated with a racial disparity. CONCLUSIONS nSES was the factor most strongly associated with racial disparities in high PSA prostate cancer. IMPACT The influence of nSES on racial disparities in PSA, GS, stage, and prostate cancer risk profiles warrants further consideration.
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Affiliation(s)
- David J Press
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois.
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago Illinois
- The Center for Health Information Partnerships (CHiP), Institute of Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Salma Shariff-Marco
- Greater Bay Area Cancer Registry, Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
- Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
- Helen Diller Family Comprehensive Cancer Center, San Francisco, California
| | - Daphne Y Lichtensztajn
- Greater Bay Area Cancer Registry, Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
- Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Diane Lauderdale
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois
| | - Adam B Murphy
- Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Pushkar P Inamdar
- Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Mindy C DeRouen
- Greater Bay Area Cancer Registry, Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
- Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
- Helen Diller Family Comprehensive Cancer Center, San Francisco, California
| | - Ann S Hamilton
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California (USC), Los Angeles, California
| | - Juan Yang
- Greater Bay Area Cancer Registry, Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
- Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Katherine Lin
- Greater Bay Area Cancer Registry, Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
- Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
| | - Donald Hedeker
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California (USC), Los Angeles, California
| | - Iona Cheng
- Greater Bay Area Cancer Registry, Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
- Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
- Helen Diller Family Comprehensive Cancer Center, San Francisco, California
| | - Scarlett Lin Gomez
- Greater Bay Area Cancer Registry, Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
- Department of Epidemiology and Biostatistics, University of California, San Francisco, School of Medicine, San Francisco, California
- Helen Diller Family Comprehensive Cancer Center, San Francisco, California
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Palmer JR, Polley EC, Hu C, John EM, Haiman C, Hart SN, Gaudet M, Pal T, Anton-Culver H, Trentham-Dietz A, Bernstein L, Ambrosone CB, Bandera EV, Bertrand KA, Bethea TN, Gao C, Gnanaolivu RD, Huang H, Lee KY, LeMarchand L, Na J, Sandler DP, Shah PD, Yadav S, Yang W, Weitzel JN, Domchek SM, Goldgar DE, Nathanson KL, Kraft P, Yao S, Couch FJ. Contribution of Germline Predisposition Gene Mutations to Breast Cancer Risk in African American Women. J Natl Cancer Inst 2020; 112:1213-1221. [PMID: 32427313 PMCID: PMC7735769 DOI: 10.1093/jnci/djaa040] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 01/27/2020] [Accepted: 03/23/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND The risks of breast cancer in African American (AA) women associated with inherited mutations in breast cancer predisposition genes are not well defined. Thus, whether multigene germline hereditary cancer testing panels are applicable to this population is unknown. We assessed associations between mutations in panel-based genes and breast cancer risk in 5054 AA women with breast cancer and 4993 unaffected AA women drawn from 10 epidemiologic studies. METHODS Germline DNA samples were sequenced for mutations in 23 cancer predisposition genes using a QIAseq multiplex amplicon panel. Prevalence of mutations and odds ratios (ORs) for associations with breast cancer risk were estimated with adjustment for study design, age, and family history of breast cancer. RESULTS Pathogenic mutations were identified in 10.3% of women with estrogen receptor (ER)-negative breast cancer, 5.2% of women with ER-positive breast cancer, and 2.3% of unaffected women. Mutations in BRCA1, BRCA2, and PALB2 were associated with high risks of breast cancer (OR = 47.55, 95% confidence interval [CI] = 10.43 to >100; OR = 7.25, 95% CI = 4.07 to 14.12; OR = 8.54, 95% CI = 3.67 to 24.95, respectively). RAD51D mutations were associated with high risk of ER-negative disease (OR = 7.82, 95% CI = 1.61 to 57.42). Moderate risks were observed for CHEK2, ATM, ERCC3, and FANCC mutations with ER-positive cancer, and RECQL mutations with all breast cancer. CONCLUSIONS The study identifies genes that predispose to breast cancer in the AA population, demonstrates the validity of current breast cancer testing panels for use in AA women, and provides a basis for increased referral of AA patients for cancer genetic testing.
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Affiliation(s)
- Julie R Palmer
- Department of Medicine, Boston University School of Medicine, and Slone Epidemiology Center, Boston, MA 02118, USA
| | - Eric C Polley
- Departments of Health Sciences Research, Laboratory Medicine and Pathology, and Oncology, Mayo Clinic, Rochester, MN 55902, USA
| | - Chunling Hu
- Departments of Health Sciences Research, Laboratory Medicine and Pathology, and Oncology, Mayo Clinic, Rochester, MN 55902, USA
| | - Esther M John
- Department of Health Research & Policy, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Christopher Haiman
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Steven N Hart
- Departments of Health Sciences Research, Laboratory Medicine and Pathology, and Oncology, Mayo Clinic, Rochester, MN 55902, USA
| | - Mia Gaudet
- Epidemiology Research, American Cancer Society, Atlanta, GA 30303, USA
| | - Tuya Pal
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | | | - Amy Trentham-Dietz
- Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Leslie Bernstein
- Department of Population Sciences, City of Hope, Duarte, CA 91010, USA
| | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA
| | - Elisa V Bandera
- Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute of New, New Brunswick, NJ 08903, USA
| | - Kimberly A Bertrand
- Department of Medicine, Boston University School of Medicine, and Slone Epidemiology Center, Boston, MA 02118, USA
| | - Traci N Bethea
- Department of Medicine, Boston University School of Medicine, and Slone Epidemiology Center, Boston, MA 02118, USA
| | - Chi Gao
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Rohan D Gnanaolivu
- Departments of Health Sciences Research, Laboratory Medicine and Pathology, and Oncology, Mayo Clinic, Rochester, MN 55902, USA
| | - Hongyan Huang
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Kun Y Lee
- Departments of Health Sciences Research, Laboratory Medicine and Pathology, and Oncology, Mayo Clinic, Rochester, MN 55902, USA
| | - Loic LeMarchand
- Population Sciences in the Pacific Program (Cancer Epidemiology), University of Hawaii Cancer Center Honolulu, HI 96813, USA
| | - Jie Na
- Departments of Health Sciences Research, Laboratory Medicine and Pathology, and Oncology, Mayo Clinic, Rochester, MN 55902, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - Payal D Shah
- Abramson Cancer Center and Basser Center for BRCA, University of Pennsylvania, Philadelphia, PA 19104, USA; and 16Department of Dermatology, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Siddhartha Yadav
- Departments of Health Sciences Research, Laboratory Medicine and Pathology, and Oncology, Mayo Clinic, Rochester, MN 55902, USA
| | - William Yang
- Departments of Health Sciences Research, Laboratory Medicine and Pathology, and Oncology, Mayo Clinic, Rochester, MN 55902, USA
| | - Jeffrey N Weitzel
- Department of Population Sciences, City of Hope, Duarte, CA 91010, USA
| | - Susan M Domchek
- Abramson Cancer Center and Basser Center for BRCA, University of Pennsylvania, Philadelphia, PA 19104, USA; and 16Department of Dermatology, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - David E Goldgar
- Department of Medicine, Boston University School of Medicine, and Slone Epidemiology Center, Boston, MA 02118, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Katherine L Nathanson
- Abramson Cancer Center and Basser Center for BRCA, University of Pennsylvania, Philadelphia, PA 19104, USA; and 16Department of Dermatology, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Peter Kraft
- Departments of Health Sciences Research, Laboratory Medicine and Pathology, and Oncology, Mayo Clinic, Rochester, MN 55902, USA
| | - Song Yao
- Departments of Health Sciences Research, Laboratory Medicine and Pathology, and Oncology, Mayo Clinic, Rochester, MN 55902, USA
| | - Fergus J Couch
- Departments of Health Sciences Research, Laboratory Medicine and Pathology, and Oncology, Mayo Clinic, Rochester, MN 55902, USA
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Chitgupi U, Nyayapathi N, Kim J, Wang D, Sun B, Li C, Carter K, Huang WC, Kim C, Xia J, Lovell JF. Surfactant-Stripped Micelles for NIR-II Photoacoustic Imaging through 12 cm of Breast Tissue and Whole Human Breasts. Adv Mater 2019; 31:e1902279. [PMID: 31414515 PMCID: PMC6773519 DOI: 10.1002/adma.201902279] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 06/11/2019] [Indexed: 05/19/2023]
Abstract
Surfactant-stripped micelles are formed from a commercially available cyanine fluoroalkylphosphate (CyFaP) salt dye and used for high contrast photoacoustic imaging (PAI) in the second near-infrared window (NIR-II). The co-loading of Coenzyme Q10 into surfactant-stripped CyFaP (ss-CyFaP) micelles improves yield, storage stability, and results in a peak absorption wavelength in the NIR-II window close to the 1064 nm output of Nd-YAG lasers used for PAI. Aqueous ss-CyFaP dispersions exhibit intense NIR-II optical absorption, calculated to be greater than 500 at 1064 nm. ss-CyFaP is detected through 12 cm of chicken breast tissue with PAI. In preclinical animal models, ss-CyFaP is visualized in draining lymph nodes of rats through 3.1 cm of overlaid chicken breast tissue. Following intravenous administration, ss-CyFaP accumulates in neoplastic tissues of mice and rats bearing orthotopic mammary tumors without observation of acute toxic side effects. ss-CyFaP is imaged through whole compressed human breasts in three female volunteers at depths of 2.6-5.1 cm. Taken together, these data show that ss-CyFaP is an accessible contrast agent for deep tissue PAI in the NIR-II window.
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Affiliation(s)
- Upendra Chitgupi
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
| | - Nikhila Nyayapathi
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
| | - Jeesu Kim
- Departments of Creative IT Engineering, Mechanical Engineering and Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk, 37673, Republic of Korea
| | - Depeng Wang
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
| | - Boyang Sun
- Department of Chemical and Biological Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
| | - Changning Li
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
| | - Kevin Carter
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
| | - Wei-Chiao Huang
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
| | - Chulhong Kim
- Departments of Creative IT Engineering, Mechanical Engineering and Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk, 37673, Republic of Korea
| | - Jun Xia
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
| | - Jonathan F Lovell
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
- Department of Chemical and Biological Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA
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Abstract
Epithelial-mesenchymal transition (EMT) is a developmental process whereby stationary, adherent cells acquire the ability to migrate. EMT is critical for dramatic cellular movements during embryogenesis; however, tumor cells can reactivate EMT programs, which increases their aggressiveness. In addition to motility, EMT is associated with enhanced stem cell properties and drug resistance; thus it can drive metastasis, tumor recurrence, and therapy resistance in the context of cancer. However, the precise requirements for EMT in metastasis have not been fully delineated, with different tumor types relying on discrete EMT effectors. Most tumor cells do not undergo a full EMT, but rather adopt some qualities of mesenchymal cells and maintain some epithelial characteristics. Emerging evidence suggests that partial EMT can drive distinct migratory properties and enhance the epithelial-mesenchymal plasticity of cancer cells as well as cell fate plasticity. This review discusses the diverse regulatory mechanisms and functional consequences of EMT, with an emphasis on the importance of partial EMT.
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Affiliation(s)
- Nicole M Aiello
- Department of Molecular Biology, Princeton University, Princeton, NJ
| | - Yibin Kang
- Department of Molecular Biology, Princeton University, Princeton, NJ
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