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However, the precise molecular mechanisms underlying the crosstalk between KDMs and HDACs in chromatin remodeling and regulation of gene transcription are still elusive. In this study, we showed that treatment of human breast cancer cells with inhibitors targeting the zinc cofactor dependent class I\u002FII HDAC, but not NAD+ dependent class III HDAC, led to significant increase of H3K4me2 which is a specific substrate of histone lysine-specific demethylase 1 (LSD1) and a key chromatin mark promoting transcriptional activation. We also demonstrated that inhibition of LSD1 activity by a pharmacological inhibitor, pargyline, or siRNA resulted in increased acetylation of H3K9 (AcH3K9). However, siRNA knockdown of LSD2, a homolog of LSD1, failed to alter the level of AcH3K9, suggesting that LSD2 activity may not be functionally connected with HDAC activity. Combined treatment with LSD1 and HDAC inhibitors resulted in enhanced levels of H3K4me2 and AcH3K9, and exhibited synergistic growth inhibition of breast cancer cells. Finally, microarray screening identified a unique subset of genes whose expression was significantly changed by combination treatment with inhibitors of LSD1 and HDAC. Our study suggests that LSD1 intimately interacts with histone deacetylases in human breast cancer cells. Inhibition of histone demethylation and deacetylation exhibits cooperation and synergy in regulating gene expression and growth inhibition, and may represent a promising and novel approach for epigenetic therapy of breast cancer.",{"EN":249,"VI":250},"Inhibitors of histone demethylation and histone deacetylation cooperate in regulating gene expression and inhibiting growth in human breast cancer cells","Các chất ức chế khử methyl histone và khử acetyl histone phối hợp điều hòa biểu hiện gene và ức chế sinh trưởng ở tế bào ung thư vú người",{"VOID":252},"Stearns V, Zhou Q, Davidson NE (2007) Epigenetic regulation as a new target for breast cancer therapy. Cancer Invest 25(8):659–665\nMarks PA, Richon VM, Miller T, Kelly WK (2004) Histone deacetylase inhibitors. Adv Cancer Res 91:137–168\nFicner R (2009) Novel structural insights into class I and II histone deacetylases. Curr Top Med Chem 9(3):235–240\nKeen JC, Yan L, Mack KM, Pettit C, Smith D, Sharma D, Davidson NE (2003) A novel histone deacetylase inhibitor, scriptaid, enhances expression of functional estrogen receptor alpha (ER) in ER negative human breast cancer cells in combination with 5-aza 2′-deoxycytidine. Breast Cancer Res Treat 81(3):177–186\nZhou Q, Atadja P, Davidson NE (2007) Histone deacetylase inhibitor LBH589 reactivates silenced estrogen receptor alpha (ER) gene expression without loss of DNA hypermethylation. Cancer Biol Ther 6(1):64–69\nYang X, Ferguson AT, Nass SJ, Phillips DL, Butash KA, Wang SM, Herman JG, Davidson NE (2000) Transcriptional activation of estrogen receptor alpha in human breast cancer cells by histone deacetylase inhibition. Cancer Res 60(24):6890–6894\nSharma D, Saxena NK, Davidson NE, Vertino PM (2006) Restoration of tamoxifen sensitivity in estrogen receptor-negative breast cancer cells: tamoxifen-bound reactivated ER recruits distinctive corepressor complexes. Cancer Res 66(12):6370–6378\nShi Y, Lan F, Matson C, Mulligan P, Whetstine JR, Cole PA, Casero RA, Shi Y (2004) Histone demethylation mediated by the nuclear amine oxidase homolog LSD1. Cell 119(7):941–953\nLee MG, Wynder C, Cooch N, Shiekhattar R (2005) An essential role for CoREST in nucleosomal histone 3 lysine 4 demethylation. Nature 437(7057):432–435\nKahl P, Gullotti L, Heukamp LC, Wolf S, Friedrichs N, Vorreuther R, Solleder G, Bastian PJ, Ellinger J, Metzger E et al (2006) Androgen receptor coactivators lysine-specific histone demethylase 1 and four and a half LIM domain protein 2 predict risk of prostate cancer recurrence. Cancer Res 66(23):11341–11347\nScoumanne A, Chen X (2007) The lysine-specific demethylase 1 is required for cell proliferation in both p53-dependent and -independent manners. J Biol Chem 282(21):15471–15475\nBradley C, van der Meer R, Roodi N, Yan H, Chandrasekharan MB, Sun ZW, Mernaugh RL, Parl FF (2007) Carcinogen-induced histone alteration in normal human mammary epithelial cells. Carcinogenesis 28(10):2184–2192\nHuang Y, Greene E, Murray Stewart T, Goodwin AC, Baylin SB, Woster PM, Casero RA Jr (2007) Inhibition of lysine-specific demethylase 1 by polyamine analogues results in reexpression of aberrantly silenced genes. Proc Natl Acad Sci USA 104(19):8023–8028\nHuang Y, Stewart TM, Wu Y, Baylin SB, Marton LJ, Perkins B, Jones RJ, Woster PM, Casero RA Jr (2009) Novel oligoamine analogues inhibit lysine-specific demethylase 1 and induce reexpression of epigenetically silenced genes. Clin Cancer Res 15(23):7217–7228\nHuang Y, Marton LJ, Woster PM, Casero RA (2009) Polyamine analogues targeting epigenetic gene regulation. Essays Biochem 46:95–110\nKarytinos A, Forneris F, Profumo A, Ciossani G, Battaglioli E, Binda C, Mattevi A (2009) A novel mammalian flavin-dependent histone demethylase. J Biol Chem 284(26):17775–17782\nCiccone DN, Su H, Hevi S, Gay F, Lei H, Bajko J, Xu G, Li E, Chen T (2009) KDM1B is a histone H3K4 demethylase required to establish maternal genomic imprints. Nature 461(7262):415–418\nYang Z, Jiang J, Stewart DM, Qi S, Yamane K, Li J, Zhang Y, Wong J (2010) AOF1 is a histone H3K4 demethylase possessing demethylase activity-independent repression function. Cell Res 20(3):276–287\nHuang Y, Hager ER, Phillips DL, Dunn VR, Hacker A, Frydman B, Kink JA, Valasinas AL, Reddy VK, Marton LJ et al (2003) A novel polyamine analog inhibits growth and induces apoptosis in human breast cancer cells. Clin Cancer Res 9(7):2769–2777\nHuang Y, Keen JC, Hager E, Smith R, Hacker A, Frydman B, Valasinas AL, Reddy VK, Marton LJ, Casero RA Jr et al (2004) Regulation of polyamine analogue cytotoxicity by c-Jun in human MDA-MB-435 cancer cells. Mol Cancer Res 2(2):81–88\nChou TC, Talalay P (1984) Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors. Adv Enzyme Regul 22:27–55\nHahm HA, Dunn VR, Butash KA, Deveraux WL, Woster PM, Casero RA Jr, Davidson NE (2001) Combination of standard cytotoxic agents with polyamine analogues in the treatment of breast cancer cell lines. Clin Cancer Res 7(2):391–399\nTusher VG, Tibshirani R, Chu G (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA 98(9):5116–5121\nBlander G, Guarente L (2004) The Sir2 family of protein deacetylases. Annu Rev Biochem 73:417–435\nShi YJ, Matson C, Lan F, Iwase S, Baba T, Shi Y (2005) Regulation of LSD1 histone demethylase activity by its associated factors. Mol Cell 19(6):857–864\nLan F, Collins RE, De Cegli R, Alpatov R, Horton JR, Shi X, Gozani O, Cheng X, Shi Y (2007) Recognition of unmethylated histone H3 lysine 4 links BHC80 to LSD1-mediated gene repression. Nature 448(7154):718–722\nCameron EE, Bachman KE, Myohanen S, Herman JG, Baylin SB (1999) Synergy of demethylation and histone deacetylase inhibition in the re-expression of genes silenced in cancer. Nat Genet 21(1):103–107\nGore SD, Baylin S, Sugar E, Carraway H, Miller CB, Carducci M, Grever M, Galm O, Dauses T, Karp JE et al (2006) Combined DNA methyltransferase and histone deacetylase inhibition in the treatment of myeloid neoplasms. Cancer Res 66(12):6361–6369\nAlexopoulou AN, Leao M, Caballero OL, Da Silva L, Reid L, Lakhani SR, Simpson AJ, Marshall JF, Neville AM, Jat PS (2010) Dissecting the transcriptional networks underlying breast cancer: NR4A1 reduces the migration of normal and breast cancer cell lines. Breast Cancer Res 12(4):R51\nWu Q, Dawson MI, Zheng Y, Hobbs PD, Agadir A, Jong L, Li Y, Liu R, Lin B, Zhang XK (1997) Inhibition of trans-retinoic acid-resistant human breast cancer cell growth by retinoid X receptor-selective retinoids. Mol Cell Biol 17(11):6598–6608\nNovak P, Jensen T, Oshiro MM, Watts GS, Kim CJ, Futscher BW (2008) Agglomerative epigenetic aberrations are a common event in human breast cancer. Cancer Res 68(20):8616–8625\nLiang G, Bansal G, Xie Z, Druey KM (2009) RGS16 inhibits breast cancer cell growth by mitigating phosphatidylinositol 3-kinase signaling. J Biol Chem 284(32):21719–21727\nRao R, Nalluri S, Kolhe R, Yang Y, Fiskus W, Chen J, Ha K, Buckley KM, Balusu R, Coothankandaswamy V et al (2010) Treatment with panobinostat induces glucose-regulated protein 78 acetylation and endoplasmic reticulum stress in breast cancer cells. Mol Cancer Ther 9(4):942–952\nHo TF, Ma CJ, Lu CH, Tsai YT, Wei YH, Chang JS, Lai JK, Cheuh PJ, Yeh CT, Tang PC et al (2007) Undecylprodigiosin selectively induces apoptosis in human breast carcinoma cells independent of p53. 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Patients with UBC (n=3163) and those who developed second cancer in the contralateral breast (CBC) after the initial breast cancer (n=67 or 2.1% of UBC) were analysed. Compared to UBC patients, those who developed CBC were younger at the time of diagnosis of initial breast cancer and had higher frequency of breast cancer among the family members. The relative survival rate takes into account competing causes of death and was estimated as the ratio of observed survival rate to the expected survival rate. The cumulative relative survival from UBC at 5 and 10 years were 51% and 41%, respectively, and the corresponding rates for CBC were 47 and 30% the survival difference seen between UBC and CBC patients was not statistically significant. The survival rates among younger, middle-aged and older women were significantly different from each other in UBC but not in CBC patients. Both UBC and CBC with early stage disease had a better survival compared to late stage disease. Survival advantage was also seen among both UBC and CBC patients with family history of breast cancer compared to those without. The multivariate analysis by the life table proportional hazards model showed that the age at diagnosis is an independent prognostic factor for breast cancer. The study results should be interpreted in the light of small sample size of second cancers.",{"EN":426},"Survival from contralateral breast cancer",{"VOID":428},"[\"17197786049539235248\"]",{"VOID":430},"Biennial report of the National Cancer Registry Programme: A project of the Indian Council of Medical Research, New Delhi, India, 1992\nSankaranarayanan R, Swaminathan R, Black RJ, on behalf of the study group on cancer survival in Developing countries: Global variations in cancer survival. Cancer 78: 2461–2464, 1996\nNandakumar A, Anantha N, Venugopal TC, Sankaranarayanan R, Thimmasetty K, Dhar M: Survival in breast cancer: a population-based study in Bangalore, India. Int J Cancer 60: 593–596, 1995\nGajalakshmi CK, Shanta V, Swaminathan R, Sankaranarayanan R, Black RJ: A population based survival study on female breast cancer in Madras, India. Br J Cancer 75: 771–775, 1997\nGajalakshmi CK, Shanta V, Hakama M: Risk factors for contralateral breast cancer in Chennai (Madras), India, Int J Epidemiol 27: 743–750, 1998\nGajalakshmi CK, Shanta V: Methodology for long term follow-up of cancer cases in a developing environment, Ind J Cancer 32: 160–168, 1995\nHermanek P, Sobin LH (eds): TNM Classification of Malignant Tumours. International Union Against Cancer, New York, 1987\nManual of the International Classification of Diseases for Oncology. 1st edition. World Health Organisation, Geneva, 1976\nRegistrar General of India: SRS Based Abridged Life Tables 1976–1980. Sample Registration Bulletin. Vol 18, No 1. Oflice of the Registrar General, New Delhi, 1984\nRegistrar General of India: SRS Based Abridged Life Tables 1985–1989. Occasional paper No 4 of 1990. Office of the Registrar General, New Delhi, 1990\nHakulinen T, Abeywickrama KH: A computer program package for relative survival analysis. Computer Prog Biomed 19: 197–207, 1985\nHakulinen T, Tenkanen L: Regression analysis of relative survival rates. Appl Stat 36: 309–317, 1987\nFrancis B, Green M, Payne C (eds): The GLIM system. Release 4 Manual. Generalised Linear Interactive Modelling, Oxford, 1993\nKurtz JM, Amalric R, Brandone H, Ayme Y, Spitalier JM: Contralateral breast cancer and other second malignancies in patients treated by breast-conserving therapy with radiation. Int J Radiat Oncol Biol Phys 15(2): 277–284, 1988\nBrenner H, Engelsmann B, Stegmaier C, Ziegler H: Clinical epidemiology of bilateral breast cancer. Cancer 72: 3629–3635, 1993\nBerrino F, Sant M, Verdecchia A, Capocaccia R, Hakulinen T, Esteve J (eds): The Eurocare Study - Survival of cancer patients in Europe. IARC Scientific Publication No 132. International Agency for Research on Cancer, Lyon, France, 1995\nYancik R, Ries LG, Yates JW: Breast cancer in aging women. A population-based study of contrasts in stage, surgery and survival. Cancer 63: 976–981, 1989\nFinney GG Jr, Finney GG, Montague ACW, Stonesifer GL, Brown CC: Bilateral breast cancer: clinical and pathological review. Ann Surg 175: 635–646, 1972\nSlack N, Bross KDJ, Nemoto T, Fisher B: Experiences with bilateral primary carcinoma of the breast. Surg Gynecol Obstet 136: 433–440, 1973\nKhafagy MM, Schottenfeld D, Robbins GF: Prognosis of the second breast cancer: the role of previous exposure to the first primary. Cancer 35: 596–599, 1975\nSchell SR, Montague ED, Spanos WJ Jr, Tapley ND, Fletcher GH, Oswald MJ: Bilateral breast cancer in patients with initial stage I and II disease. Cancer 50(6): 1191–1194, 1982\nBurns PE, Dabbs K, May C, Lees AW, Birkett LR, Jenkins HJ, Hanson J: Bilateral breast cancer in northern Alberta risk factors and survival patterns. Can Med Assoc J 130: 881–886, 1984\nFisher ER, Fischer B, Sass R, Wickerham L and Collaborating NSABP investigators: Pathologic findings from the National Surgical Adjuvant Breast Project (Protocol No 4): XI Bilateral breast cancer. Cancer 54: 3002–3011, 1984\nBerte E, Buzdar AU, Smith TL, Hortobagyi GN: Bilateral primary breast cancer in patients treated with adjuvant therapy. Am J Clin Oncol 11(2): 114–118, 1988\nHolmberg L, Adami H-O, Ekbom A, Bergstrom R, Sandstrom A, Lindgren A: Prognosis in bilateral breast cancer. Effects of time interval between first and second primary tumours. Br J Cancer 58: 191–194, 1988\nGulay H, Hameloglu E, Bulut O, Goksel HA: Bilateral breast carcinoma: 28 years experience. World J Surg 14(4): 529–533, 1990\nde-la-Rochefordiere A, Mouret-Fourme E, Asselain B, Scholl SM, Campana F, Broet P, Fourquet A: Metachronous contralateral breast cancer as first event of relapse. Int J Radiat Oncol Biol Phys 36: 615–621, 1996\nFisher ER: Prognostic and therapeutic significance of pathological features of breast cancer. Monogr Natl Cancer Inst 1: 29–34, 1986\nCarter CL, Allen C, Henson DE: Relation of tumour size, lymphnode status and survival in 24,740 breast cancer cases. Cancer 63: 181–187, 1989\nCrowe JP Jr, Gordon NH, Shenk RR, Zollinger RM Jr, Brumberg DJ, Shuck JM: Primary tumour size. Relevance to breast cancer survival. Arch Surg 127: 910–915, 1992\nLipponen P, Aaltomaa S, Eskelinen M, Kosma VM, Marin S, Syrjänen K: The changing importance of prognostic factors in breast cancer during long-term follow-up. Int J Cancer 51: 698–702, 1992\nNab HW, Kluck HM, Rutgers EJ, Coebergh JW, Hop WC: Long term prognosis of breast for a protective effect of lactation on risk of breast cancer in young women: results from a case-control study. Am J Epidemiol 124: 353–358, 1995\nEngin K: Prognostic factors in bilateral breast cancer. Neoplasma 41: 353–357, 1994\nNemoto T, Vana J, Bedwani RN, Baker HW, McGregor FH, Murphy GP: Management and survival of female breast cancer: results of national survey by the American College of Surgeons. Cancer 45: 2917–2924, 1980\nAaltomaa S, Lipponen P, Eskelinen M: Demographic prognostic factors in breast cancer. Acta Oncol 31: 635–640, 1992\nAlbain KS, Allred DC, Clark GM: Breast cancer outcome and predictors of outcome: are there age differentials? Monogr Natl Cancer Inst 16: 35–42, 1994\nAdami H-O, Malker B, Holmberg L, Persson I, Stone B: The relation between survival and age at diagnosis in breast cancer. N Engl J Med 315: 559–563, 1986\nHost H, Lund E: Age as a prognostic factor in breast cancer. Cancer 57: 2217–2221, 1986\nAlexieva-Figusch J, van Putten WLJ, Blankenstein MA, Blonk-Van Der Wijst J, Klijn JG: The prognostic value and relationships of patient characteristics, estrogen and progestin receptors, and site of relapse in primary breast cancer. Cancer 61: 758–768, 1988\nAlbain KS, Green S, LeBlanc M, Rivkin S, O'sullivan J, Osborne CK: Proportional hazards and recursive partitioning and amalgamation analyses of the Southwest Oncology Group node-positive adjuvant CMFVP breast cancer data base: a pilot study. Breast Cancer Res Treat 22: 273–284, 1992\nBelembaogo E, Feillel V, Chollet P, Cure H, Verrelle P, Kwiatkowski F, Achard JL, Le Bouedec G, Chassagne J, Bignon YJ, de Latour M, Lafaye C, Dauplat J: Neoadjuvant chemotherapy in 126 operable breast cancers. Eur J Cancer 28(A): 896–900, 1992\nClark GM: The biology of breast cancer in older women. J Gerontol 47: 19–23, 1992\nChaudary MA, Millis RR, Bulbrook RD, Hayward JL: Family history and bilateral primary breast cancer. Breast Cancer Res Treat 5(2): 201–205, 1985\nGogas J, Markopoulos C, Skandalakis P, Gogas H: Bilateral breast cancer. Am Surg 59(11): 733–735, 1993\nFukutomi T, Kobayashi Y, Nanasawa T, Yamamoto H, Tsuda H: A clinicopathological analysis of breast cancer in patients with a family history. Surg Today 23: 849–854, 1993\nAnderson DE, Badzioch MD: Survival in familial breast cancer patients. Cancer 58: 360–365, 1986\nToikkanen SP, Kujari HP, Joensuu H: Factors predicting late mortality from breast cancer. Eur J Cancer 27: 586–591, 1991\nSwanson GM, Lin C-S: Survival patterns among younger women with breast cancer: effects of age, race, stage and treatment, Natl Cancer Inst Monogr 16: 69–77, 1994",{"VOID":432},"10.1023\u002FA:1006361608241","2024-05-10T04:00:20.454+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1023\u002FA:1006361608241",[436,451,466],{"id":437,"sortIndex":21,"researcher":20,"roles":438,"affiliations":439,"properties":448,"displayName":450,"givenName":20,"familyName":20},"e3bd310f-c973-47ea-9731-4252e5bda278",[266],[440],{"id":441,"sortIndex":21,"affiliation":442,"properties":20},"de686d67-689a-4194-974f-137836f15f5f",{"id":441,"createTime":20,"updateTime":20,"relativeEntities":443,"slug":20,"properties":444,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":447,"statistic":20},[],{"title":445},{"VI":446},"Division of Epidemiology and Cancer Registry, Cancer Institute (WIA), Chennai, India",[],{"title":449},{"VI":450},"C.K. 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intake is one of the few modifiable risk factors for breast cancer. Current alcohol intake has been associated with mammographic density, a strong intermediate marker of breast cancer risk, though few studies have examined the effect of both current and average lifetime alcohol intake. We interviewed 262 participants from a New York birth cohort (born 1959–1963) and obtained mammograms from 163 (71.5% of participants with a mammogram). We collected information on alcohol intake by beverage type separately for each decade of life. We used multivariable linear models to assess the associations between current and average lifetime alcohol intake and mammographic density using a quantitative measure of density from digitized images. Overall, current alcohol intake was more strongly associated with mammographic density than average lifetime alcohol intake; compared with nondrinkers, those with current intake of seven or more servings per week had on average 12.3% (95% CI: 4.3, 20.4) higher density, adjusted for average lifetime alcohol intake, age, and body mass index. We observed a consistent inverse association for red wine intake and mammographic density, suggesting that the positive association between mammographic density and overall alcohol intake was driven by other types of alcoholic beverages. Our findings support an association between current alcohol intake and increased mammographic density independent of the effect of average lifetime alcohol intake. If replicated, our study suggests that reducing current alcohol consumption, particularly beer and white wine intake, may be a means of reducing mammographic density regardless of intake earlier in life.",{"EN":551},"Alcohol intake over the life course and mammographic density",{"VOID":553},"[\"646611399419027947\"]",{"VOID":555},"World Cancer Research Fund\u002FAmerican Institute for Cancer Research (2007) Food, Nutrition, Physical Activity, and the Prevention of Cancer: a Global Perspective. AICR, Washington DC\nSingletary KW, Gapstur SM (2001) Alcohol and breast cancer: review of epidemiologic and experimental evidence and potential mechanisms. JAMA 286(17):2143–2151. doi:10.1001\u002Fjama.286.17.2143\nHamajima N et al (2002) Alcohol, tobacco and breast cancer-collaborative reanalysis of individual data from 53 epidemiological studies, including 58, 515 women with breast cancer and 95, 067 women without the disease. Br J Cancer 87(11):1234–1245. doi:10.1038\u002Fsj.bjc.6600596\nHiatt RA (1990) Alcohol consumption and breast cancer. Med Oncol Tumor Pharmacother 7(2–3):143–151\nTerry MB et al (2006) Lifetime alcohol intake and breast cancer risk. Ann Epidemiol 16(3):230–240. doi:10.1016\u002Fj.annepidem.2005.06.048\nLongnecker MP et al (1995) Risk of breast cancer in relation to lifetime alcohol consumption. J Natl Cancer Inst 87(12):923–929. doi:10.1093\u002Fjnci\u002F87.12.923\nMartin LJ, Boyd NF (2008) Mammographic density. Potential mechanisms of breast cancer risk associated with mammographic density: hypotheses based on epidemiological evidence. Breast Cancer Res 10(1):201. doi:10.1186\u002Fbcr1831\nByng JW et al (1994) The quantitative analysis of mammographic densities. Phys Med Biol 39(10):1629–1638. doi:10.1088\u002F0031-9155\u002F39\u002F10\u002F008\nBoyd NF et al (1998) Mammographic densities and breast cancer risk. Cancer Epidemiol Biomarkers Prev 7(12):1133–1144\nMcCormack VA, s Silva I (2006) Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev 15(6):1159–1169. doi:10.1158\u002F1055-9965.EPI-06-0034\nBoyd NF et al (2005) Mammographic breast density as an intermediate phenotype for breast cancer. Lancet Oncol 6(10):798–808. doi:10.1016\u002FS1470-2045(05)70390-9\nBoyd NF et al (1995) Plasma lipids, lipoproteins, and mammographic densities. Cancer Epidemiol Biomarkers Prev 4(7):727–733\nMasala G et al (2006) Dietary and lifestyle determinants of mammographic breast density. A longitudinal study in a Mediterranean population. Int J Cancer 118(7):1782–1789. doi:10.1002\u002Fijc.21558\nVachon CM et al (2000) Association of mammographically defined percent breast density with epidemiologic risk factors for breast cancer (United States). Cancer Causes Control 11(7):653–662. doi:10.1023\u002FA:1008926607428\nHerrinton LJ et al (1993) Do alcohol intake and mammographic densities interact in regard to the risk of breast cancer? Cancer 71(10):3029–3035. doi:10.1002\u002F1097-0142(19930515)71:10\u003C3029::AID-CNCR2820711024>3.0.CO;2-K\nMaskarinec G et al (2006) Alcohol consumption and mammographic density in a multiethnic population. Int J Cancer 118(10):2579–2583. doi:10.1002\u002Fijc.21705\nVachon CM et al (2000) Association of diet and mammographic breast density in the Minnesota breast cancer family cohort. Cancer Epidemiol Biomarkers Prev 9(2):151–160\nVachon CM et al (2005) Alcohol intake in adolescence and mammographic density. Int J Cancer 117(5):837–841. doi:10.1002\u002Fijc.21227\nGapstur SM et al (2003) Associations of breast cancer risk factors with breast density in Hispanic women. Cancer Epidemiol Biomarkers Prev 12(10):1074–1080\nMaskarinec G et al (2007) Ethnic and geographic differences in mammographic density and their association with breast cancer incidence. Breast Cancer Res Treat 104(1):47–56. doi:10.1007\u002Fs10549-006-9387-5\nSala E et al (1999) High-risk mammographic parenchymal patterns and anthropometric measures: a case-control study. Br J Cancer 81(7):1257–1261. doi:10.1038\u002Fsj.bjc.6690838\nBrisson J et al (1989) Diet, mammographic features of breast tissue, and breast cancer risk. Am J Epidemiol 130(1):14–24\nBroman SH (1984) The collaborative perinatal project: an overview. In: Mednick SA, Harway M, Finello KM (eds) Hanbook of longitudinal research. Praeger, New York, pp 166–179\nTerry MB, Wei Y, Esserman D (2007) Maternal, birth, and early life influences on adult body size in women. Am J Epidemiol 166(1):5–13. doi:10.1093\u002Faje\u002Fkwm094\nHarvey EB et al (1987) Alcohol consumption and breast cancer. J Natl Cancer Inst 78(4):657–661\nByng JW et al (1996) Symmetry of projection in the quantitative analysis of mammographic images. Eur J Cancer Prev 5(5):319–327. doi:10.1097\u002F00008469-199610000-00003\nJang M et al (1997) Cancer chemopreventive activity of resveratrol, a natural product derived from grapes. Science 275(5297):218–220. doi:10.1126\u002Fscience.275.5297.218\nLongnecker MP (1995) Alcohol consumption and risk of cancer in humans: an overview. Alcohol 12(2):87–96. doi:10.1016\u002F0741-8329(94)00088-3\nBlot WJ (1992) Alcohol and cancer. Cancer Res 52(7 (Suppl)):2119s–2123s\nYu H, Berkel J (1999) Do insulin-like growth factors mediate the effect of alcohol on breast cancer risk? Med Hypotheses 52(6):491–496. doi:10.1054\u002Fmehy.1998.0828\nByrne C et al (2000) Plasma insulin-like growth factor (IGF) I, IGF-binding protein 3 and Mammographic density. Cancer Res 60:3744–3748\nBaglietto L et al (2005) Does dietary folate intake modify effect of alcohol consumption on breast cancer risk? Prospective cohort study. BMJ 331(7520):807. doi:10.1136\u002Fbmj.38551.446470.06\nNegri E, La Vecchia C, Franceschi S (2000) Re: dietary folate consumption and breast cancer risk. J Natl Cancer Inst 92(15):1270–1271. doi:10.1093\u002Fjnci\u002F92.15.1270-a\nRohan TE et al (2000) Dietary folate consumption and breast cancer risk. J Natl Cancer Inst 92(3):266–269. doi:10.1093\u002Fjnci\u002F92.3.266\nTerry MB et al (2006) ADH3 genotype, alcohol intake and breast cancer risk. Carcinogenesis 27(4):840–847. doi:10.1093\u002Fcarcin\u002Fbgi285\nNational Center for Health Statistics Health, United States (2007) With Chartbook on Trends in the Health of Americans. Hyattsville, MD\nUS Department of Health and Human Services and US Department of Agriculture (2005) Dietary guidelines for Americans, 6th edn. US Government Printing Office, Washington DC\nKerlikowske K et al (2007) Longitudinal measurement of clinical mammographic breast density to improve estimation of breast cancer risk. J Natl Cancer Inst 99(5):386–395. doi:10.1093\u002Fjnci\u002Fdjk066\nCuzick J et al (2004) Tamoxifen and breast density in women at increased risk of breast cancer. J Natl Cancer Inst 96(8):621–628\nRutter CM et al (2001) Changes in breast density associated with initiation, discontinuation, and continuing use of hormone replacement therapy. JAMA 285:171–176. doi:10.1001\u002Fjama.285.2.171",{"VOID":557},"10.1007\u002Fs10549-008-0302-0","2024-05-12T05:32:39.001+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10549-008-0302-0",[561,576,589,604],{"id":562,"sortIndex":21,"researcher":20,"roles":563,"affiliations":564,"properties":573,"displayName":575,"givenName":20,"familyName":20},"f766feb5-af48-4c4e-9e04-6f363df610b9",[266],[565],{"id":566,"sortIndex":21,"affiliation":567,"properties":20},"ca9eaba7-e305-4be3-8765-a92cb77a456e",{"id":566,"createTime":20,"updateTime":20,"relativeEntities":568,"slug":20,"properties":569,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":572,"statistic":20},[],{"title":570},{"VI":571},"Department of Epidemiology, Columbia University Mailman School of Public Health, New York, USA",[],{"title":574},{"VI":575},"Julie D. 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sis-from-16-studies-involving-23-445-subjects",{"abstract":687,"title":689,"gsPaper":691,"doi":693},{"EN":688},"Epidemiological studies on the association between SULT1A1 codon 213 polymorphism and breast cancer risk are inconclusive. In order to derive a more precise estimation of the association, a meta-analysis was conducted in this article. Sixteen studies including 9,881 cases and 13,564 controls were collected for SULT1A1 codon 213 polymorphism by searching the databases of Medline, PubMed, Embase, and ISI Web of Knowledge. The strength of association between SULT1A1 codon 213 polymorphism and breast cancer susceptibility was assessed by calculating crude ORs with 95% CIs. When all the 21 studies were pooled into the meta-analysis, there was no evidence for significant association between SULT1A1 codon 213 polymorphism and breast cancer susceptibility (for Arg\u002FArg versus Arg\u002FHis: OR = 0.999, 95% CI = 0.941–1.061; for Arg\u002FArg versus His\u002FHis: OR = 1.121, 95% CI = 1.013–1.242; for dominant model: OR = 1.128, 95% CI = 1.01–1.26; for recessive model: OR = 1.151, 95% CI = 0.950–1.394). In the subgroup analysis by the source of controls, significant increased risk was found for hospital-based studies (for Arg\u002FArg versus Arg\u002FHis: OR = 1.173, 95% CI = 1.000–1.376; for Arg\u002FArg versus His\u002FHis: OR = 1.600, 95% CI = 1.134–2.256; for dominant model: OR = 1.269, 95% CI = 1.134–2.256; for recessive model: OR = 1.664, 95% CI = 1.070–2.588). In summary, the meta-analysis suggests that SULT1A1 codon 213 polymorphism may be associated with the hospital-based studies. However, large number of samples and representative hospital-based studies with homogeneous breast cancer patients and well-matched controls are warranted to confirm this finding.",{"EN":690},"The association of SULT1A1 codon 213 polymorphism and breast cancer susceptibility: meta-analysis from 16 studies involving 23,445 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J Cancer Res Clin Oncol 132:466–472","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs00432-006-0093-9",{"doi":918},"10.1007\u002Fs00432-006-0093-9",{"id":920,"text":921,"url":922,"identifiers":923},"6b1053a6-0df7-42d5-8269-5b4c6bb0d1eb","Boccia S, Persiani R, La Torre G, Rausei S, Arzani D, Gianfagna F, Romano-Spica V, D’Ugo D, Ricciardi G (2005) Sulfotransferase 1A1 polymorphism and gastric cancer risk: a pilot case-control study. Cancer Lett 229:235–243","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0304383505006208",{"doi":924},"10.1016\u002Fj.canlet.2005.06.035",{"id":878,"text":926,"url":880,"identifiers":927},"Syamala VS, Syamala V, Sheeja VR, Kuttan R, Balakrishnan R, Ankathil R (2010) Possible risk modification by polymorphisms of estrogen metabolizing genes in familial breast cancer susceptibility in an Indian population. Cancer Invest 28:304–311",{"doi":882},{"id":878,"text":929,"url":880,"identifiers":930},"Chang-Claude J, Beckmann L, Corson C, Hein R, Kropp S, Parthimos M, Dünnebier T, Hamann U, Brors B, Eils R, Zapatka M, Brauch H, Justenhoven C, Flesch-Janys D, Braendle W, Brüning T, Pesch B, Spickenheuer A, Krankenhaus J, Ko YD, Baisch C, Dahmen N, Brauch H, Chang-Claude J, Corson C, Dünnebier T, Hein R, Justenhoven C, Parthimos M, Zapatka M (2010) Genetic polymorphisms in phase I and phase II enzymes and breast cancer risk associated with menopausal hormone therapy in postmenopausal women. Breast Cancer Res Treat 119:463–474",{"doi":882},{"id":878,"text":932,"url":880,"identifiers":933},"Gulyaeva LF, Mikhailova ON, PustyInyak VO, Kim IV 4th, Gerasimov AV, Krasilnikov SE, Filipenko ML, Pechkovsky EV (2008) Comparative analysis of SNP in estrogen-metabolizing enzymes for ovarian, endometrial, and breast cancers in Novosibirsk, Russia. 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Anticancer Res 25:2515–2517",{"doi":882},{"id":878,"text":944,"url":880,"identifiers":945},"Le Marchand L, Donlon T, Kolonel LN, Henderson BE, Wilkens LR (2005) Estrogen metabolism-related genes and breast cancer risk: the multiethnic cohort study. Cancer Epidemiol Biomarkers Prev 14:1998–2003",{"doi":882},{"id":947,"text":948,"url":949,"identifiers":950},"b6a23373-7712-47b8-b59a-ccf5dd96f8f5","Lilla C, Risch A, Kropp S, Chang-Claude J (2005) SULT1A1 genotype, active and passive smoking, and breast cancer risk by age 50 years in a German case-control study. Breast Cancer Res 7:R229–R237","https:\u002F\u002Fbreast-cancer-research.biomedcentral.com\u002Farticles\u002F10.1186\u002Fbcr976",{"doi":951},"10.1186\u002Fbcr976",{"id":878,"text":953,"url":880,"identifiers":954},"Yang G, Gao YT, Cai QY, Shu XO, Cheng JR, Zheng W (2005) Modifying effects of sulfotransferase 1A1 gene polymorphism on the association of breast cancer risk with body mass index or endogenous steroid hormones. 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Breast Cancer Res Treat 87:19–22",{"doi":882},{"id":878,"text":965,"url":880,"identifiers":966},"Tang D, Rundle A, Mooney L, Cho S, Schnabel F, Estabrook A, Kelly A, Levine R, Hibshoosh H, Perera F (2003) Sulfotransferase 1A1 (SULT1A1) polymorphism, PAH-DNA adduct levels in breast tissue and breast cancer risk in a case-control study. Breast Cancer Res Treat 78:217–222",{"doi":882},{"id":878,"text":968,"url":880,"identifiers":969},"Zheng W, Xie D, Cerhan JR, Sellers TA, Wen W, Folsom AR (2001) Sulfotransferase 1A1 polymorphism, endogenous estrogen exposure, well-done meat intake, and breast cancer risk. Cancer Epidemiol Biomarkers Prev 10:89–94",{"doi":882},{"id":878,"text":971,"url":880,"identifiers":972},"Seth P, Lunetta KL, Bell DW, Gray H, Nasser SM, Rhei E, Kaelin CM, Iglehart DJ, Marks JR, Garber JE, Haber DA, Polyak K (2000) Phenol sulfotransferases: hormonal regulation, polymorphism, and age of onset of breast cancer. Cancer Res 60:6859–6863",{"doi":882},{"id":878,"text":974,"url":880,"identifiers":975},"Mantel N, Haenszel W (1959) Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst 22:719–748",{"doi":882},{"id":977,"text":978,"url":979,"identifiers":980},"8d9ae324-e3b2-455c-a179-c2548013ff36","DerSimonian R, Laird N (1986) Meta-analysis in clinical trials. Control Clin Trials 7:177–188","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002F0197245686900462",{"doi":981},"10.1016\u002F0197-2456(86)90046-2",{"id":20,"text":983,"url":20,"identifiers":984},"Tobias A (1999) Assessing the influence of a single study in the meta-analysis estimate. Stata Tech Bull 8:15–17",{},{"id":986,"text":987,"url":988,"identifiers":989},"e4034cdc-bdf7-4ec4-8a58-c5f24b110791","Egger M, Davey Smith G, Schneider M, Minder C (1997) Bias in meta-analysis detected by a simple, graphical test. 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Breast Cancer Res Treat. doi:10.1007\u002Fs10549-009-0731-4","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10549-009-0731-4",{"doi":996},"10.1007\u002Fs10549-009-0731-4",{"id":998,"createTime":999,"updateTime":1000,"relativeEntities":1001,"slug":1002,"properties":1003,"entityType":255,"verifyStatus":256,"verifyTime":1012,"verifyNote":258,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1013,"fullTextUrl":20,"authors":1014,"publicationType":359,"publisherRelationship":1030,"citationCount":1082,"citationInfo":1083,"publishDate":1086,"publishYear":1084,"citationAnalyzeStatus":19,"lastCitationAnalyze":1000,"indexDatabases":1087,"openAccess":20,"references":1088,"isForceReanalyzing":415},"37e608df-416d-4816-8021-d540d97b0682","2024-02-07T17:58:11.447+00:00","2026-07-27T09:45:54.973+00:00",[],"Adrenal-androgens-and-human-breast-cancer-A-new-appraisal",{"abstract":1004,"title":1006,"gsPaper":1008,"doi":1010},{"EN":1005},"A clearer picture of the role of adrenal androgens in the etiology of breast cancer is beginning to emerge. Women who develop breast cancer in premenopausal years tend to have subnormal serum levels of adrenal androgens, while subjects who develop the disease in postmenopausal years have supranormal levels of these hormones. Androgens, by acting via the androgen receptor, oppose estrogen-stimulated cell growth in premenopausal years. In postmenopausal women, elevated adrenal androgen levels stimulate cell growth by the action of the unique adrenal androgen 5-androstene-3β,17β-diol, also termed hermaphrodiol, via its combination with the estrogen receptor in a hormone milieu lacking, or having low concentrations of, the classical estrogen 17β-estradiol.",{"EN":1007},"Adrenal androgens and human breast cancer: A new appraisal",{"VOID":1009},"[\"1867888377848180260\"]",{"VOID":1011},"10.1023\u002FA:1006050720900","2024-04-29T00:31:09.168+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1023\u002FA:1006050720900",[1015],{"id":1016,"sortIndex":21,"researcher":20,"roles":1017,"affiliations":1018,"properties":1027,"displayName":1029,"givenName":20,"familyName":20},"65ba2773-bba0-41e0-8ee1-8a240ad69f0d",[266],[1019],{"id":1020,"sortIndex":21,"affiliation":1021,"properties":20},"22a58d25-fbda-4e6c-9e45-742a36f49870",{"id":1020,"createTime":20,"updateTime":20,"relativeEntities":1022,"slug":20,"properties":1023,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1026,"statistic":20},[],{"title":1024},{"VI":1025},"School of Biochemistry and Molecular Genetics, University of New South Wales, Sydney, Australia",[],{"title":1028},{"VI":1029},"John B. Adams",{"url":1013,"publisher":1031,"properties":1077},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1032,"slug":10,"properties":1033,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":1037,"manageAffiliations":1046,"indexDatabases":1057,"url":20,"thumbnailPath":20,"statistic":1072,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":1034,"title":1035,"eissn":1036},{"VOID":13},{"EN":15},{"VOID":17},[1038,1042],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":1039,"label":1040,"description":1041,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},{"id":30,"createTime":20,"updateTime":20,"relativeEntities":1043,"label":1044,"description":1045,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":33},{},[1047,1052],{"id":37,"createTime":20,"updateTime":20,"relativeEntities":1048,"slug":20,"properties":1049,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1051,"statistic":20},[],{"title":1050},{"EN":41},[43],{"id":45,"createTime":20,"updateTime":20,"relativeEntities":1053,"slug":20,"properties":1054,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1056,"statistic":20},[],{"title":1055},{"EN":49},[],[1058,1065],{"id":53,"indexDatabase":1059,"url":64,"indexYears":65,"academicFieldIds":1064,"indexDatabaseRanking":69},{"id":55,"createTime":20,"updateTime":20,"relativeEntities":1060,"label":1061,"description":1062,"key":61,"publicationTags":1063,"standard":20},[],{"EN":58,"VI":58},{"EN":58,"VI":60},[63],[67,68],{"id":71,"indexDatabase":1066,"url":84,"indexYears":20,"academicFieldIds":1071,"indexDatabaseRanking":20},{"id":73,"createTime":20,"updateTime":20,"relativeEntities":1067,"label":1068,"description":1069,"key":80,"publicationTags":1070,"standard":20},[],{"EN":76,"VI":76},{"EN":78,"VI":79},[82,83],[86],{"impactFactor":21,"impactFactorByYear":1073,"i10Index":100,"i10IndexLast5Year":101,"totalPublication":102,"totalPublicationByYear":1074,"totalCitation":146,"totalCitationByYear":1075,"totalCitationPerPublication":191,"totalCitationPerPublicationByYear":1076,"hindexLast5Year":123,"hindex":123},{"2012":89,"2013":90,"2014":91,"2015":92,"2016":93,"2017":90,"2018":94,"2019":95,"2020":96,"2021":97,"2022":98,"2023":99},{"1981":104,"1982":105,"1983":106,"1984":107,"1985":108,"1986":109,"1987":110,"1988":111,"1989":112,"1990":113,"1991":114,"1992":115,"1993":116,"1994":117,"1995":118,"1996":119,"1997":120,"1998":121,"1999":122,"2000":123,"2001":124,"2002":125,"2003":126,"2004":127,"2005":128,"2006":129,"2007":130,"2008":131,"2009":132,"2010":133,"2011":134,"2012":135,"2013":136,"2014":137,"2015":138,"2016":132,"2017":139,"2018":140,"2019":141,"2020":142,"2021":143,"2022":144,"2023":145,"2024":111},{"1981":148,"1982":124,"1983":149,"1984":150,"1985":151,"1986":152,"1987":153,"1988":154,"1989":155,"1990":156,"1991":157,"1992":158,"1993":159,"1994":160,"1995":161,"1996":162,"1997":163,"1998":164,"1999":165,"2000":166,"2001":167,"2002":168,"2003":169,"2004":170,"2005":171,"2006":172,"2007":173,"2008":174,"2009":175,"2010":176,"2011":177,"2012":178,"2013":179,"2014":180,"2015":181,"2016":182,"2017":183,"2018":184,"2019":185,"2020":186,"2021":187,"2022":188,"2023":189,"2024":190},{"1981":193,"1982":194,"1983":195,"1984":196,"1985":197,"1986":198,"1987":199,"1988":200,"1989":201,"1990":202,"1991":203,"1992":204,"1993":205,"1994":206,"1995":207,"1996":208,"1997":209,"1998":210,"1999":211,"2000":212,"2001":213,"2002":214,"2003":215,"2004":194,"2005":216,"2006":217,"2007":218,"2008":219,"2009":211,"2010":220,"2011":221,"2012":222,"2013":223,"2014":224,"2015":225,"2016":226,"2017":227,"2018":228,"2019":229,"2020":230,"2021":231,"2022":232,"2023":233,"2024":234},{"pages":1078,"volume":1080},{"VOID":1079},"183-188",{"VOID":1081},"51",59,{"total":1082,"publishYear":1084,"statisticByYear":1085},1998,{},"1998-09-01",[82,69],[1089,1092,1095,1098,1101,1104,1107,1110,1113,1116,1119,1125,1128,1131,1134,1137,1143,1146,1149,1155,1161,1167,1170],{"id":20,"text":1090,"url":20,"identifiers":1091},"Beaulieu EE, Corpechot C, Dray F, Emilozzi R, Lebean M, Mauvais-Jarvis P, Robel P: An adrenal-secreted ‘androgen’: dehydroepiandrosterone sulfate, its metabolism and a tentative generalisation on the metabolism of other steroid conjugates in man. Recent Prog Hormone Res 21: 411–500, 1965",{},{"id":20,"text":1093,"url":20,"identifiers":1094},"Allen BJ, Hayward JL, Merivale WMH: The exeretion of 17-kestosteroids in the urine of patients with carcinoma of the breast. Lancet 1: 496–497, 1957",{},{"id":20,"text":1096,"url":20,"identifiers":1097},"Zumoff B: Hormone profiles and the epidemiology of breast cancer. In: Stoll BA (ed) Endocrine Relationships in Breast Cancer. Heinman, London, 1982, pp 3–47",{},{"id":878,"text":1099,"url":880,"identifiers":1100},"Adams JB: Control of secretion and the function of C12-Δ5-steroids of the human adrenal gland. Mol Cell Endierinol 41: 1–17, 1985",{"doi":882},{"id":878,"text":1102,"url":880,"identifiers":1103},"Bulbrook RD, Hayward JL, Wang DY, Thomas BS, Clark GMG, Allen DS, Moore JW: Identification of women at high risk of breast cancer. Breast Cancer Res Treat 7(Suppl): 5–10, 1986",{"doi":882},{"id":20,"text":1105,"url":20,"identifiers":1106},"Bulbrook RD, Thomas BS: Hormones are ambiguous factors for breast cancer. Acta Oncologica 28: 841–847, 1989",{},{"id":20,"text":1108,"url":20,"identifiers":1109},"Zumoff B, Levin J, Rosenfeld RS, Markham M, Strain GW, Fukushima DK: Abnormal 24-hr mean plasma concentration of dehydroepiandrosterone and dehydroepiandrosterone sulfate in women with primary operable breast cancer. Cancer Res 41: 3360–3363, 1981",{},{"id":878,"text":1111,"url":880,"identifiers":1112},"Gordon GB, Bush TL, Helzlsouer KJ, Miller SR, Comstock GW: Relationship of serum levels of dehydroepiandrosterone and dehydroepiandrosterone sulfate to the risk of developing postmenopausal breast cancer. Cancer Res 50: 3859–3862, 1990",{"doi":882},{"id":878,"text":1114,"url":880,"identifiers":1115},"Helzlsouer KJ, Gordon GB, Alberg AJ, Bush TL, Comstock GW: Relationship of prediagnostic serum levels of dehydroplandrosterone and dehydroeplandrosterone sulfate to the risk of developing premenopausal breast cancer. Cancer Res 52: 1–4, 1992",{"doi":882},{"id":20,"text":1117,"url":20,"identifiers":1118},"Dorgan JF, Stanczyk F, Longcope C, Stephenson HE, Chang L, Miller R, Franz C, Falk RT, Kahle L: Relationship of serum DHEA, DHEAS and 5-androstene-3β,17β-diol to risk of breast cancer in postmenopausal women. Cancer Epidemiol Biomarkers Prevention 6: 177–181, 1997",{},{"id":1120,"text":1121,"url":1122,"identifiers":1123},"b46ba8f2-3409-46ac-a08e-917ea7fd9124","Bonney R, Scanlon MJ, Jones DL, Beranek PA, Reed MJ, James VHT: The interrelationship between plasma 5-ene adrenal androgens in normal women. J Steriod Biochem 20: 1353–1355, 1984","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002F0022473184901687",{"doi":1124},"10.1016\u002F0022-4731(84)90168-7",{"id":20,"text":1126,"url":20,"identifiers":1127},"Huggins C, Jensen EV, Cleveland AS: Chemical structure of steroids in relation to promotion of growth of the vagina and uterus of the hypophysectomized rat. J Exp Med 100: 225–240, 1954",{},{"id":878,"text":1129,"url":880,"identifiers":1130},"Adams J, Garcia M, Rochefort H: Estrogenic effects of physiological concentrations of 5-androstene-3β,17β-diol and its metabolism in MCF7 human breast cancer cells. Cancer Res 41: 4720–4726, 1981",{"doi":882},{"id":20,"text":1132,"url":20,"identifiers":1133},"Seymour-Munn K, Adams J: Estrogenic effects of 5-androstone-3β,17β-diol and its possible implication in the etiology of breast cancer. Endocrinology 112: 486–491, 1983",{},{"id":878,"text":1135,"url":880,"identifiers":1136},"Poulin R, Labrie F: Stimulation of cell proliferation and estrogenic response by adrenal C19-Δ5-steroids in the ZR-75-1 human breast cancer cell line. Cancer Res 46: 4933–4937, 1986",{"doi":882},{"id":1138,"text":1139,"url":1140,"identifiers":1141},"24f366d0-74f9-4203-812c-f03e470fb954","Spinola PG, Marchetti B, Labrie F: Adrenal steroids stimulate growth and progesterone receptor levels in rat uterus and DMBA-induced mammary tumors. Breast Cancer Res Treat 81: 241–248, 1986","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002FBF01807337",{"doi":1142},"10.1007\u002FBF01807337",{"id":20,"text":1144,"url":20,"identifiers":1145},"Adams JB, Martyn P, Lee F-T, Phillips NS, Smith DL: Metabolism of 17β-estradiol and the adrenal-derived estrogen 5-androstene-3β,17β-diol (Hermaphrodiol) in human mammary cell lines. Ann NY Acad Sci 595: 93–105, 1990",{},{"id":878,"text":1147,"url":880,"identifiers":1148},"Rochefort H, Garcia M: Androgen on the estrogen receptor 1. Binding and in vivo nuclear translocation. Steroids 28: 549–560, 1976",{"doi":882},{"id":1150,"text":1151,"url":1152,"identifiers":1153},"259311e3-6170-4275-b6ee-968c2f73f428","Rochefort H, Garcia M: The estrogenic and antiestrogenic activities of androgens in female target tissues. Pharm Ther 23: 193–216, 1984","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002F016372588390013X",{"doi":1154},"10.1016\u002F0163-7258(83)90013-x",{"id":1156,"text":1157,"url":1158,"identifiers":1159},"2d460404-9bf0-403c-b268-b768d36e6389","Poulin R, Baker D, Labrie F: Androgens inhibit basal and estrogen-induced cell proliferation in the ZR-75-1 human breast cancer cell line. Breast Cancer Res Treat 12: 213–225, 1988","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002FBF01805942",{"doi":1160},"10.1007\u002FBF01805942",{"id":1162,"text":1163,"url":1164,"identifiers":1165},"dd57b330-a3c4-47a6-94de-2bc1b3edf2db","Hackenberg R, Schulz K-D: Androgen receptor mediated growth control of breast cancer and endometrial cancer modulated by antiandrogen-and androgen-like steroids. J Steroid Biochem Mol Biol 56: 113–117, 1996","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002F0960076095002286",{"doi":1166},"10.1016\u002F0960-0760(95)00228-6",{"id":878,"text":1168,"url":880,"identifiers":1169},"Bocuzzi G, Brignardello E, Di Monaco M, Gatto V, Leonardi L, Pizzini A, Gallo M: 5-En-androstene-3β,17β-diol inhibits the growth of MCF-7 breast cancer cells when oestrogen receptors are blocked by oestradiol. Br J Cancer 70: 1035–1039, 1994",{"doi":882},{"id":878,"text":1171,"url":880,"identifiers":1172},"Hayward JL, Greenwood FC, Glober G, Stemmerman G, Bulbrook RD, Wang DY, Kamaoka S: Endocrine status in normal British, Japanese and Hawaiian-Japanese women. Eur J Cancer 14: 1221–1228, 1978",{"doi":882},{"id":1174,"createTime":1175,"updateTime":1176,"relativeEntities":1177,"slug":1178,"properties":1179,"entityType":255,"verifyStatus":256,"verifyTime":1192,"verifyNote":258,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1193,"fullTextUrl":20,"authors":1194,"publicationType":359,"publisherRelationship":1321,"citationCount":676,"citationInfo":1368,"publishDate":1370,"publishYear":673,"citationAnalyzeStatus":1371,"lastCitationAnalyze":1176,"indexDatabases":1372,"openAccess":20,"references":20,"isForceReanalyzing":415},"0c134e2b-5508-49dd-80bd-4dbfcde07ae9","2024-04-06T04:13:06.815+00:00","2026-07-27T09:38:45.754+00:00",[],"Learning-to-predict-relapse-in-invasive-ductal-carcinomas-based-on-the-subcellular-localization-of-junctional-proteins",{"abstract":1180,"title":1182,"gsPaper":1184,"keywords":1186,"references":1188,"doi":1190},{"EN":1181},"The complexity of breast cancer biology makes it challenging to analyze large datasets of clinicopathologic and molecular attributes, toward identifying the key prognostic features and producing systems capable of predicting which patients are likely to relapse. We applied machine-learning techniques to analyze a set of well-characterized primary breast cancers, which specified the abundance and localization of various junctional proteins. We hypothesized that disruption of junctional complexes would lead to the cytoplasmic\u002Fnuclear redistribution of the protein components and their potential interactions with growth-regulating molecules, which would promote relapse, and that machine-learning techniques could use the subcellular locations of these proteins, together with standard clinicopathological data, to produce an efficient prognostic classifier. We used immunohistochemistry to assess the expression and subcellular distribution of six junctional proteins, in addition to a panel of eight standard clinical features and concentrations of four “growth-regulating” proteins, to produce a database involving 36 features, over 66 primary invasive ductal breast carcinomas. A machine-learning system was applied to this clinicopathologic dataset to produce a decision-tree classifier that could predict whether a novel breast cancer patient would relapse. We show that this decision-tree classifier, which incorporates a combination of only four features (nuclear α- and β-catenin levels, the total level of PTEN and the number of involved axillary lymph nodes), is able to correctly classify patient outcomes essentially 80% of the time. Further, this classifier is significantly better than classifiers based on any subgroup of these 36 features. This study demonstrates that autonomous machine-learning techniques are able to generate simple and efficient decision-tree prognostic classifiers from a wide variety of clinical, pathologic and biomarker data, and unlike other analytic methods, suggest testable biologic relationships among explicitly identified key variables. The decision-tree classifier resulting from these analytic methods is sufficiently simple and should be widely applicable to a spectrum of clinical cancer settings. Further, the subcellular distribution of junctional proteins, which influences growth regulatory pathways involved in locoregional and metastatic relapse of breast cancer, helped to identify which patients would relapse while their total concentration did not. This emphasizes the need to evaluate the subcellular distribution of junctional proteins in assessing their contribution to tumor progression.",{"EN":1183},"Learning to predict relapse in invasive ductal carcinomas based on the subcellular localization of junctional proteins",{"VOID":1185},"[\"3556749807582918653\"]",{"EN":1187},"",{"VOID":1189},"Sorlie T, Tibshirani R, Parker J et al (2003) Repeated observation of breast tumor subtypes in independent gene expression data sets. 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Curr Opin Cell Biol 19:508–514\nChetty R, Serra S (2008) Nuclear E-cadherin immunoexpression: from biology to potential applications in diagnostic pathology. Adv Anat Pathol 15:234–240\nPerez-Moreno M, Fuchs E (2006) Catenins: keeping cells from getting their signals crossed. Dev Cell 11:601–612\nCowin P, Rowlands TM, Hatsell SJ (2005) Cadherins and catenins in breast cancer. Curr Opin Cell Biol 17:499–508\nBalda MS, Matter K (2000) The tight junction protein ZO-1 and an interacting transcription factor regulate ErbB-2 expression. EMBO J 19:2024–2033\nLi L, Chapman K, Hu X, Wong A, Pasdar M (2007) Modulation of the oncogenic potential of beta-catenin by the subcellular distribution of plakoglobin. Mol Carcinog 46:824–838\nRavdin PM, Siminoff LA, Davis GJ et al (2001) Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol 19:980–991\nHelguero LA, Lindberg K, Gardmo C, Schwend T, Gustafsson JA, Haldosén LA (2008) Different roles of estrogen receptors alpha and beta in the regulation of E-cadherin protein levels in a mouse mammary epithelial cell line. Cancer Res 68:8695–8704\nHarris SL, Levine AJ (2005) The p53 pathway: positive and negative feedback loops. Oncogene 24:2899–2908\nLam L, Hu X, Aktary Z, Andrews DW, Pasdar M (2008) Tamoxifen and ICI 182,780 increase Bcl-2 levels and inhibit growth of breast carcinoma cells by modulating PI3K\u002FAKT, ERK and IGF-1R pathways independent of ERα. Breast Cancer Res Treat. doi:10.1007\u002Fs10549-008-0231-y\nKotelevets L, van Hengel J, Bruyneel E, Mareel M, van Roy F, Chastre E (2005) Implication of the MAGI-1b\u002FPTEN signalosome in stabilization of adherens junctions and suppression of invasiveness. FASEB J 19:115–117\nElston CW, Ellis IO (1991) Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 19:403–410\nWitten IH, Frank E (2005) Data mining: practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco\nBishop CM (2006) Pattern recognition and machine learning. Springer, Berlin\nQuinlan JR (2003) “C4.5: programs for machine learning”. Morgan Kaufmann, San Francisco\nNelson WJ (2008) Regulation of cell–cell adhesion by the cadherin-catenin complex. Biochem Soc Trans 36:149–155\nLindman HR (1974) Analysis of variance in complex experimental designs. W. H. Freeman and Co, San Francisco\nMarchionni L, Wilson RF, Wolff AC et al (2008) Systematic review: gene expression profiling assays in early-stage breast cancer. Ann Intern Med 148:358–369\nOzawa M, Baribault H, Kemler R (1989) The cytoplasmic domain of the cell adhesion molecule uvomorulin associates with three independent proteins structurally related in different species. EMBO J 8:1711–1717\nBenjamin JM, Nelson WJ (2008) Bench to bedside and back again: molecular mechanisms of alpha-catenin function and roles in tumorigenesis. Semin Cancer Biol 18:53–64\nHuang H, He X (2008) Wnt\u002Fbeta-catenin signaling: new (and old) players and new insights. Curr Opin Cell Biol 20:119–125\nLindvall C, Bu W, Williams BO, Li Y (2007) Wnt signaling, stem cells, and the cellular origin of breast cancer. Stem Cell Rev 3:157–168\nDrees F, Pokutta S, Yamada S, Nelson WJ, Weis WI (2005) Alpha-catenin is a molecular switch that binds E-cadherin-beta-catenin and regulates actin-filament assembly. Cell 123:903–915\nYamada S, Pokutta S, Drees F, Weis WI, Nelson WJ (2005) Deconstructing the cadherin-catenin-actin complex. Cell 123:889–901\nGottardi CJ, Gumbiner BM (2004) Distinct molecular forms of beta-catenin are targeted to adhesive or transcriptional complexes. J Cell Biol 33:9–49\nKobielak A, Fuchs E (2006) Links between alpha-catenin, NF-kappaB, and squamous cell carcinoma in skin. Proc Natl Acad Sci USA 103:2322–2327\nShtutman M, Chausovsky A, Prager-Khoutorsky M et al (2008) Signaling function of alpha-catenin in microtubule regulation. Cell Cycle 7:2377–2383\nKnobbe CB, Lapin V, Suzuki A, Mak TW (2008) The roles of PTEN in development, physiology and tumorigenesis in mouse models: a tissue-by-tissue survey. Oncogene 27:5398–5415\nDiao L, Chen YG (2008) PTEN, a general negative regulator of cyclin D expression. Cell Res 17:291–292\nMareel M, Leroy A (2003) Clinical, cellular, and molecular aspects of cancer invasion. Physiol Rev 83:337–376\nCampeau PM, Foulkes WD, Tischkowitz MD (2008) Hereditary breast cancer: new genetic developments, new therapeutic avenues. Hum Genet 124:31–42\nDobrosotskaya IY, James GL (2000) MAGI-1 interacts with beta-catenin and is associated with cell–cell adhesion structures. Biochem Biophys Res Commun 270:903–909\nTsutsui S, Inoue H, Yasuda K et al (2005) Reduced expression of PTEN protein and its prognostic implications in invasive ductal carcinoma of the breast. Oncology 68:398–404",{"VOID":1191},"10.1007\u002Fs10549-009-0557-0","2024-05-13T05:55:02.686+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10549-009-0557-0",[1195,1210,1225,1238,1251,1264,1279,1294,1307],{"id":1196,"sortIndex":21,"researcher":20,"roles":1197,"affiliations":1198,"properties":1207,"displayName":1209,"givenName":20,"familyName":20},"3cc850c4-94cf-4145-8f21-e7b1f9ae1fda",[266],[1199],{"id":1200,"sortIndex":21,"affiliation":1201,"properties":20},"1644c792-fbfb-4006-8071-c5ecba7832a5",{"id":1200,"createTime":20,"updateTime":20,"relativeEntities":1202,"slug":20,"properties":1203,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1206,"statistic":20},[],{"title":1204},{"VI":1205},"Department of Computing Science, University of Alberta, Edmonton, Canada",[],{"title":1208},{"VI":1209},"Nasimeh 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importance of matrix metalloproteinases and their inhibitors in tumor progression is well documented. We wanted to investigate if single nucleotide polymorphisms (SNPs) in the promoter regions of these genes are associated with susceptibility to or progression of breast cancer. In this, so far largest case–control study, we genotyped eight SNPs in the MMP1, MMP2, MMP3, MMP9, MMP13, RECK and TIMP3 genes in a well-characterized breast cancer series of 959 cases and 952 controls from Sweden. Even though we did not correct for multiple comparisons, only a few associations were noted. We observed a moderately increased risk for the TT homozygotes of the MMP9−1562 C\u002FT SNP (OR 1.88, 95% CI 0.97–3.63) and for the C allele carriers of the TIMP3−1296 T\u002FC SNP (OR 1.25, 95% CI 1.05–1.50). In the survival analysis, only the TC heterozygotes of the RECK−420 T\u002FC SNP showed a better survival compared to the TT homozygotes (P = 0.02 in all cases and P = 0.03 in lymph node negative cases). None of the other SNPs conferred an increased breast cancer risk, nor did they correlate with survival. A combination of the −585 TT homozygosity in the RECK gene and the −1296 TT homozygosity in the TIMP3 gene correlated with estrogen and progesterone receptor status (OR 1.81, 95% CI 1.03–3.21 and OR 2.10, 95% CI 1.18–3.86, respectively), and a combination of the −1306 TT homozygosity in the MMP2 gene and the −1562 CC homozygosity in the MMP9 gene with progesterone receptor status (OR 2.34, 95% CI 1.08–5.08). Although our study suggests some correlations between the studied SNPs and the progression of breast cancer, the rarity of the risk genotypes limits their usefulness in the clinic.",{"EN":1383},"Promoter polymorphisms in matrix metalloproteinases and their inhibitors: few associations with breast cancer susceptibility and progression",{"VOID":1385},"[\"659434390427529628\"]",{"VOID":1387},"Kim JB, Stein R, O’Hare MJ (2005) Tumour–stromal interactions in breast cancer: the role of stroma in tumourigenesis. Tumour Biol 26:173–185\nCrawford HC, Matrisian LM (1994) Tumor and stromal expression of matrix metalloproteinases and their role in tumor progression. Invasion Metastasis 14:234–245\nLambert E, Dasse E, Haye B, Petitfrere E (2004) TIMPs as multifacial proteins. Crit Rev Oncol Hematol 49:187–198\nNoda M, Oh J, Takahashi R, Kondo S, Kitayama H, Takahashi C (2003) RECK: a novel suppressor of malignancy linking oncogenic signaling to extracellular matrix remodeling. Cancer Metastasis Rev 22:167–175\nRhee JS, Coussens LM (2002) RECKing MMP function: implications for cancer development. Trends Cell Biol 12:209–211\nEgeblad M, Werb Z (2002) New functions for the matrix metalloproteinases in cancer progression. Nat Rev Cancer 2:161–174\nSpan PN, Sweep CG, Manders P, Beex LV, Leppert D, Lindberg RL (2003) Matrix metalloproteinase inhibitor reversion-inducing cysteine-rich protein with Kazal motifs: a prognostic marker for good clinical outcome in human breast carcinoma. Cancer 97:2710–2715\nBiondi ML, Turri O, Leviti S, Seminati R, Cecchini F, Bernini M, Ghilardi G, Guagnellini E (2000) (2000) MMP1 and MMP3 polymorphisms in promoter regions and cancer. Clin Chem 46:2023–2024\nGhilardi G, Biondi ML, Caputo M, Leviti S, DeMonti M, Guagnellini E, Scorza R (2002) A single nucleotide polymorphism in the matrix metalloproteinase-3 promoter enhances breast cancer susceptibility. Clin Cancer Res 8:3820–3823\nGrieu F, Li WQ, Iacopetta B (2004) Genetic polymorphisms in the MMP-2 and MMP-9 genes and breast cancer phenotype. Breast Cancer Res Treat 88:197–204\nKrippl P, Langsenlehner U, Renner W, Yazdani-Biuki B, Koppel H, Leithner A, Wascher TC, Paulweber B, Samonigg H (2004) The 5A\u002F6A polymorphism of the matrix metalloproteinase 3 gene promoter and breast cancer. Clin Cancer Res 10:3518–3520\nPrzybylowska K, Zielinska J, Zadrozny M, Krawczyk T, Kulig A, Wozniak P, Rykala J, Kolacinska A, Morawiec Z, Drzewoski J, Blasiak J (2004) An association between the matrix metalloproteinase 1 promoter gene polymorphism and lymphnode metastasis in breast cancer. J Exp Clin Cancer Res 23:121–125\nPrzybylowska K, Kluczna A, Zadrozny M, Krawczyk T, Kulig A, Rykala J, Kolacinska A, Morawiec Z, Drzewoski J, Blasiak J (2006) Polymorphisms of the promoter regions of matrix metalloproteinases genes MMP-1 and MMP-9 in breast cancer. Breast Cancer Res Treat 95:65–72\nKaaks R, Lundin E, Rinaldi S, Manjer J, Biessy C, Soderberg S, Lenner P, Janzon L, Riboli E, Berglund G, Hallmans G (2002) Prospective study of IGF-I, IGF-binding proteins, and breast cancer risk, in northern and southern Sweden. Cancer Causes Control 13:307–316\nPrice SJ, Greaves DR, Watkins H (2001) Identification of novel, functional genetic variants in the human matrix metalloproteinase-2 gene: role of Sp1 in allele-specific transcriptional regulation. J Biol Chem 276:7549–7558\nRutter JL, Mitchell TI, Buttice G, Meyers J, Gusella JF, Ozelius LJ, Brinckerhoff CE (1998) A single nucleotide polymorphism in the matrix metalloproteinase-1 promoter creates an Ets binding site and augments transcription. Cancer Res 58:5321–5325\nSun Y, Cheung JM, Martel-Pelletier J, Pelletier JP, Wenger L, Altman RD, Howell DS, Cheung HS (2000) Wild type and mutant p53 differentially regulate the gene expression of human collagenase-3 (hMMP-13). J Biol Chem 275:11327–11332\nYe S, Eriksson P, Hamsten A, Kurkinen M, Humphries SE, Henney AM (1996) Progression of coronary atherosclerosis is associated with a common genetic variant of the human stromelysin-1 promoter which results in reduced gene expression. J Biol Chem 271:13055–13060\nZhang B, Ye S, Herrmann SM, Eriksson P, de Maat M, Evans A, Arveiler D, Luc G, Cambien F, Hamsten A, Watkins H, Henney AM (1999) Functional polymorphism in the regulatory region of gelatinase B gene in relation to severity of coronary atherosclerosis. Circulation 99:1788–1794\nLei H, Zaloudik J, Vorechovsky I (2002) Lack of association of the −1171 (5A) allele of the MMP3 promoter with breast cancer. Clin Chem 48:798–799\nZhou Y, Yu C, Miao X, Tan W, Liang G, Xiong P, Sun T, Lin D (2004) Substantial reduction in risk of breast cancer associated with genetic polymorphisms in the promoters of the matrix metalloproteinase-2 and tissue inhibitor of metalloproteinase-2 genes. Carcinogenesis 25:399–404\nHosking L, Lumsden S, Lewis K, Yeo A, McCarthy L, Bansal A, Riley J, Purvis I, Xu CF (2004) Detection of genotyping errors by Hardy-Weinberg equilibrium testing. Eur J Hum Genet 12:395–399\nLeal SM (2005) Detection of genotyping errors and pseudo-SNPs via deviations from Hardy-Weinberg equilibrium. Genet Epidemiol 29:204–214\nWigginton JE, Cutler DJ, Abecasis GR (2005) A note on exact tests of Hardy-Weinberg equilibrium. Am J Hum Genet 76:887–893\nJin Q, Hemminki K, Enquist K, Lenner P, Grzybowska E, Klaes R, Henriksson R, Chen B, Pamula J, Pekala W, Zientek H, Rogozinska-Szczepka J, Utracka-Hutka B, Hallmans G, Forsti A (2005) Vascular endothelial growth factor polymorphisms in relation to breast cancer development and prognosis. Clin Cancer Res 11:3647–3653\nFörsti A, Jin Q, Altieri A, Johansson R, Wagner K, Enquist K, Grzybowska E, Pamula J, Pekala W, Hallmans G, Lenner P, Hemminki K (2006) Polymorphisms in the KDR and POSTN genes: association with breast cancer susceptibility and prognosis. 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receptor-positive tissue powders and cytosols, prepared from calf uterus and human breast tumor tissue, are used to assess the validity of routine dextran-coated charcoal estrogen receptor assays. Since 1978 lyophilized reference preparations have been analyzed twice yearly by 18 laboratories in the Netherlands. During 8 consecutive trials 20 different lyophilized samples were studied. The inter-laboratory variability of estrogen receptor results decreased with time. Most laboratories found receptor values around the median value of all groups together, though some participants consistently reported estrogen receptor values that were higher or lower than the median. The variability of estrogen receptor results between labs seemed to be associated with cytosol dilution, determination of non-specific binding, concentration and volume of dextrancoated charcoal, and the use of single dose assays or Scatchard analysis. The agreement on the presence or absence of estrogen receptors was more than 98% for lyophilized reference samples with high receptor content. For samples with low receptor content 85% agreement was observed, while 12% of the assays performed on receptor-negative material were reported to be estrogen receptor-positive. The use of the same protein determination (Coomassie Brilliant Blue) and human serum albumin standard has decreased the interlaboratory variation coefficient of the protein results to 7.5%.",{"EN":1591},"Quality control of estrogen receptor assays in the Netherlands",{"VOID":1593},"[\"9440351715163538616\"]",{"VOID":1595},"10.1007\u002FBF01806699","2024-05-01T12:50:23.652+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002FBF01806699",[1599,1614],{"id":1600,"sortIndex":21,"researcher":20,"roles":1601,"affiliations":1602,"properties":1611,"displayName":1613,"givenName":20,"familyName":20},"23f2cdef-71d8-43c5-9bd5-50fe2f2f3079",[266],[1603],{"id":1604,"sortIndex":21,"affiliation":1605,"properties":20},"fd08d1ef-350c-4110-9511-27278eb3ea8e",{"id":1604,"createTime":20,"updateTime":20,"relativeEntities":1606,"slug":20,"properties":1607,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1610,"statistic":20},[],{"title":1608},{"VI":1609},"Department of Experimental and Chemical Endocrinology, St. Radboud Hospital, Nijmegen, The Netherlands",[],{"title":1612},{"VI":1613},"Ton Koenders",{"id":1615,"sortIndex":278,"researcher":20,"roles":1616,"affiliations":1617,"properties":1624,"displayName":1626,"givenName":20,"familyName":20},"e57a7d98-2f88-4254-86b5-a9e431aeb2c7",[266],[1618],{"id":1604,"sortIndex":21,"affiliation":1619,"properties":20},{"id":1604,"createTime":20,"updateTime":20,"relativeEntities":1620,"slug":20,"properties":1621,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1623,"statistic":20},[],{"title":1622},{"VI":1609},[],{"title":1625},{"VI":1626},"Theo J. 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Raven Press, New York, 1975",{},{"id":878,"text":1690,"url":880,"identifiers":1691},"DeSombre ER, Jensen EV: Estrophilin assays in breast cancer: Quantitative features and application to the mastectomy specimen. Cancer 46:2783–2788, 1980",{"doi":882},{"id":878,"text":1693,"url":880,"identifiers":1694},"Paridaens R, Sylvester RJ, Ferrazzi E, Legros N, Leclercq G, Heuson JC: Clinical significance of the quantitative assessment of estrogen receptors in advanced breast cancer. Cancer 46:2889–2895, 1980",{"doi":882},{"id":878,"text":1696,"url":880,"identifiers":1697},"Lippmann ME, Allegra JC: Quantitative estrogen receptor analysis: The response to endocrine and cytotoxic chemotherapy in human breast cancer and the disease-free interval. Cancer 46:2829–2834, 1980",{"doi":882},{"id":878,"text":1699,"url":880,"identifiers":1700},"King RJB, Barnes DM, Hawkins RA, Leake RE, Maynard PV, Roberts MM: Measurement of oestradiol receptors by five institutions on common tissue samples. Brit J Cancer 38:428–430, 1978",{"doi":882},{"id":878,"text":1702,"url":880,"identifiers":1703},"Koenders AJ, Geurts-Moespot J, Kho KH, Benraad Th J: Estradiol and progesterone receptor activities in stored lyophilized target tissue. J Steroid Biochem 9:947–950, 1978",{"doi":882},{"id":878,"text":1705,"url":880,"identifiers":1706},"Benraad Th, Koenders A: Estradiol receptor activity in lyophilized calf uterus and human breast tumor tissue. Cancer 46:2762–2764, 1980",{"doi":882},{"id":20,"text":1708,"url":20,"identifiers":1709},"Koenders A, Benraad Th J: Preparation of lyophilized reference samples for quality control of steroid receptor measurements. Ligand Review 3(4):32–39, 1981",{},{"id":20,"text":1711,"url":20,"identifiers":1712},"Koenders A, Hendriks T, Benraad Th: Steroid receptors in lyophilized tissues and cytosols of calf uterus and human breast tumor.In GA Sarfaty, AR Nash, and DD Keightly (eds). Estrogen Receptor Assays in Breast Cancer. Laboratory discrepancies and quality assurance. Masson Publishing USA, 1981, pp 126–138",{},{"id":20,"text":1714,"url":20,"identifiers":1715},"Koenders A, Geurts-Moespot J, Hendriks T, Benraad Th: The Netherlands interlaboratory quality control program of steroid receptor assays in breast cancer.In GA Sarfaty, AR Nash, and DD Keightly (eds). Estrogen Receptor Assays in Breast Cancer. Laboratory discrepancies and quality assurance. Masson Publishing USA, 1981, pp 69–82",{},{"id":1717,"text":1718,"url":1719,"identifiers":1720},"f0047d80-5ec6-4780-b7d1-2c86faa715aa","Bradford MM: A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein dye-binding. Anal Biochem 72:248–254, 1976","https:\u002F\u002Flinkinghub.elsevier.com\u002Fretrieve\u002Fpii\u002F0003269776905273",{"doi":1721},"10.1016\u002F0003-2697(76)90527-3",{"id":878,"text":1723,"url":880,"identifiers":1724},"Nash AR, Sarfaty GA: Laboratory variability in estrogen receptor (ER) assays — the Australian experience.In GA Sarfaty, AR Nash, and DD Keightly (eds). Estrogen Receptor Assays in Breast Cancer. Laboratory discrepancies and quality assurance. Masson Publishing USA, 1981, pp 57–68",{"doi":882},{"id":878,"text":1726,"url":880,"identifiers":1727},"King RJB: Quality control of estradiol receptor analysis: The United Kingdom experience. Cancer 46:2822–2824, 1980",{"doi":882},{"id":878,"text":1729,"url":880,"identifiers":1730},"Fumero S, Piffanelli A: Results of the Italian interlaboratory quality control program for estradiol receptor assay. Tumori 67:301–306, 1981",{"doi":882},{"id":878,"text":1732,"url":880,"identifiers":1733},"Zava DT, Guelpa C: A quality control study to assess the interlaboratory variability of routine estrogen and progesterone receptor assays. Eur J Cancer Clin Oncol 18:713–721, 1982",{"doi":882},{"id":878,"text":1735,"url":880,"identifiers":1736},"Wittliff JL: Steroid receptor interaction in human breast cancer. Cancer 46:2953–2960, 1980",{"doi":882},{"id":20,"text":1738,"url":20,"identifiers":1739},"Cohen JL, Raam S, Gelman R, Wittliff JL: A blinded study of inter- and intra-laboratory variations in the performance of estrogen receptor (ER) assay.In GA Sarfaty, AR Nash, and DD Keightly (eds). Estrogen Receptor Assays in Breast Cancer. Laboratory discrepancies and quality assurance. Masson Publishing USA, 1981, pp 43–56.",{},{"id":878,"text":1741,"url":880,"identifiers":1742},"Bojar H, Staib W, Beck K, Pilaski J: Investigation on the thermostability of steroid hormone receptors in lyophilized calf uterine tissue powder. Cancer 46:2770–2774, 1980",{"doi":882},{"id":20,"text":1744,"url":20,"identifiers":1745},"EORTC Breast Cancer Cooperative Group: Revision of the standards for the assessment of hormone receptors in human breast cancer. Eur J Cancer 16:1513–1515, 1980",{},{"id":878,"text":1747,"url":880,"identifiers":1748},"Godolphin W, Jacobson H: Quality control of estrogen receptor assays. J Immunoassay 1(3):363–364, 1980",{"doi":882},{"id":20,"text":1750,"url":20,"identifiers":1751},"Wittliff JL, Brown AM, Fisher B: Establishment of uniformity in steroid receptor determinations for protocol B-09 of the national surgical adjuvant breast project.In GA Sarfaty, AR Nash, and DD Keightly (eds). Estrogen Receptor Assays in Breast Cancer. Laboratory discrepancies and quality assurance. Masson Publishing USA, 1981, pp 27–39",{},{"id":878,"text":1753,"url":880,"identifiers":1754},"Raam S, Gelman R, Cohen J: Estrogen receptor assay: interlaboratory and intralaboratory variations in the measurement of receptors using dextran-coated charcoal technique. A study sponsored by ECOG. Eur J Cancer 17:643–649, 1981",{"doi":882},{"id":20,"text":1756,"url":20,"identifiers":1757},"Koenders A, Thorpe SM, on behalf of the EORTC Receptor Group: Standardization of steroid receptor assays in human breast Cancer. II. Samples with low receptor content. Eur J Cancer, submitted for publication",{},{"id":1759,"createTime":1760,"updateTime":1761,"relativeEntities":1762,"slug":1763,"properties":1764,"entityType":255,"verifyStatus":256,"verifyTime":1776,"verifyNote":258,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1777,"fullTextUrl":20,"authors":1778,"publicationType":359,"publisherRelationship":1839,"citationCount":1886,"citationInfo":1887,"publishDate":1890,"publishYear":1888,"citationAnalyzeStatus":1371,"lastCitationAnalyze":1761,"indexDatabases":1891,"openAccess":20,"references":20,"isForceReanalyzing":415},"e89fdd42-3599-4f11-809a-939b150f88bc","2024-04-09T02:37:35.132+00:00","2026-07-24T17:33:21.130+00:00",[],"Predictive-value-of-lymphoscintigraphy-in-patients-with-breast-cancer-related-lymphedema-undergoing-complex-decongestive-therapy",{"abstract":1765,"title":1767,"gsPaper":1769,"keywords":1771,"references":1772,"doi":1774},{"EN":1766},"We evaluated the prognostic value of lymphoscintigraphy after complex decongestive therapy (CDT) in breast cancer-related secondary lymphedema. Prior to CDT, 80 patients with breast cancer-related lymphedema underwent a 99mTc tin-colloid lymphoscintigram. We investigated the uptake patterns of axillary lymph nodes (LNs), main lymphatic vessels, collateral lymphatic vessels, and dermal back flow in the lymphoscintigraphy of the upper extremities. We also compared the above findings with other clinical variables between patients who respond well to CDT (responders) and those who do not (poor responders). We used Pearson’s χ2 test and Fisher’s exact test to compare the lymphoscintigram findings with the studied variables. There were 50 poor responders and 30 responders 1 year after CDT. There were significant differences between the two groups with regard to compliance (P \u003C 0.05) and visualization of axillary LNs (P \u003C 0.05). In combined results, the odds ratio was 21.33 (2.37–192.03) in the compliance and visible axillary LNs group compared to the poor compliance and invisible axillary LNs group. Lymphoscintigraphy of the upper extremities can be a useful tool to predict the prognosis of CDT in breast cancer-related lymphedema patients.",{"EN":1768},"Predictive value of lymphoscintigraphy in patients with breast cancer-related lymphedema undergoing complex decongestive therapy",{"VOID":1770},"[\"18287337968911231849\"]",{"EN":1187},{"VOID":1773},"Shimony A, Tidhar D (2008) Lymphedema: a comprehensive review. Ann Plast Surg 60(2):228. https:\u002F\u002Fdoi.org\u002F10.1097\u002FSAP.0b013e318165f1f5\nSchook CC, Mulliken JB, Fishman SJ, Grant FD, Zurakowski D, Greene AK (2011) Primary lymphedema: clinical features and management in 138 pediatric patients. Plast Reconstr Surg 127(6):2419–2431. https:\u002F\u002Fdoi.org\u002F10.1097\u002FPRS.0b013e318213a218\nAhmed RL, Prizment A, Lazovich D, Schmitz KH, Folsom AR (2008) Lymphedema and quality of life in breast cancer survivors: the Iowa Women’s Health Study. J Clin Oncol 26(35):5689–5696. https:\u002F\u002Fdoi.org\u002F10.1200\u002FJCO.2008.16.4731\nSmoot B, Wong J, Cooper B, Wanek L, Topp K, Byl N, Dodd M (2010) Upper extremity impairments in women with or without lymphedema following breast cancer treatment. J Cancer Surviv 4(2):167–178. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11764-010-0118-x\nTaghian NR, Miller CL, Jammallo LS, O’Toole J, Skolny MN (2014) Lymphedema following breast cancer treatment and impact on quality of life: a review. Crit Rev Oncol Hematol 92(3):227–234. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.critrevonc.2014.06.004\nOzaslan C, Kuru B (2004) Lymphedema after treatment of breast cancer. Am J Surg 187(1):69–72\nMerchant SJ, Chen SL (2015) Prevention and management of lymphedema after breast cancer treatment. Breast J 21(3):276–284. https:\u002F\u002Fdoi.org\u002F10.1111\u002Ftbj.12391\nLee JH, Shin BW, Jeong HJ, Kim GC, Kim DK, Sim YJ (2013) Ultrasonographic evaluation of therapeutic effects of complex decongestive therapy in breast cancer-related lymphedema. Ann Rehabil Med 37(5):683–689. https:\u002F\u002Fdoi.org\u002F10.5535\u002Farm.2013.37.5.683\nYoo J, Choi JY, Hwang JH, Kim DI, Kim YW, Choe YS, Lee KH, Kim BT (2014) Prognostic value of lymphoscintigraphy in patients with gynecological cancer-related lymphedema. J Surg Oncol 109(8):760–763. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fjso.23588\nWilliams WH, Witte CL, Witte MH, McNeill GC (2000) Radionuclide lymphangioscintigraphy in the evaluation of peripheral lymphedema. Clin Nucl Med 25(6):451–464\nSzuba A, Shin WS, Strauss HW, Rockson S (2003) The third circulation: radionuclide lymphoscintigraphy in the evaluation of lymphedema. J Nucl Med 44(1):43–57\nSzuba A, Strauss W, Sirsikar SP, Rockson SG (2002) Quantitative radionuclide lymphoscintigraphy predicts outcome of manual lymphatic therapy in breast cancer-related lymphedema of the upper extremity. Nucl Med Commun 23(12):1171–1175. https:\u002F\u002Fdoi.org\u002F10.1097\u002F01.mnm.0000046208.83338.da\nAdriaenssens N, Buyl R, Lievens P, Fontaine C, Lamote J (2013) Comparative study between mobile infrared optoelectronic volumetry with a Perometer and two commonly used methods for the evaluation of arm volume in patients with breast cancer related lymphedema of the arm. Lymphology 46(3):132–143\nNoh S, Hwang JH, Yoon TH, Chang HJ, Chu IH, Kim JH (2015) Limb differences in the therapeutic effects of complex decongestive therapy on edema, quality of life, and satisfaction in lymphedema patients. Ann Rehabil Med 39(3):347–359. https:\u002F\u002Fdoi.org\u002F10.5535\u002Farm.2015.39.3.347\nYoo JN, Cheong YS, Min YS, Lee SW, Park HY, Jung TD (2015) Validity of quantitative lymphoscintigraphy as a lymphedema assessment tool for patients with breast cancer. Ann Rehabil Med 39(6):931–940. https:\u002F\u002Fdoi.org\u002F10.5535\u002Farm.2015.39.6.931\nKim YB, Hwang JH, Kim TW, Chang HJ, Lee SG (2012) Would complex decongestive therapy reveal long term effect and lymphoscintigraphy predict the outcome of lower-limb lymphedema related to gynecologic cancer treatment? Gynecol Oncol 127(3):638–642. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ygyno.2012.09.015\nExecutive C (2016) The diagnosis and treatment of peripheral lymphedema: 2016 consensus document of the International Society of Lymphology. Lymphology 49(4):170–184\nPecking AP, Alberini JL, Wartski M, Edeline V, Cluzan RV (2008) Relationship between lymphoscintigraphy and clinical findings in lower limb lymphedema (LO): toward a comprehensive staging. Lymphology 41(1):1–10\nStanton AW, Modi S, Mellor RH, Levick JR, Mortimer PS (2009) Recent advances in breast cancer-related lymphedema of the arm: lymphatic pump failure and predisposing factors. Lymphat Res Biol 7(1):29–45. https:\u002F\u002Fdoi.org\u002F10.1089\u002Flrb.2008.1026\nWitte CL, Witte MH (1999) Diagnostic and interventional imaging of lymphatic disorders. Int Angiol 18(1):25–30\nNawaz K, Hamad MM, Sadek S, Awdeh M, Eklof B, Abdel-Dayem HM (1986) Dynamic lymph flow imaging in lymphedema. Normal and abnormal patterns. Clin Nucl Med 11(9):653–658\nEge GN (1983) Lymphoscintigraphy with Tc-99m labeled dextran. J Nucl Med 24(4):370–371\nSvensson W, Glass DM, Bradley D, Peters AM (1999) Measurement of lymphatic function with technetium-99m-labelled polyclonal immunoglobulin. Eur J Nucl Med 26(5):504–510",{"VOID":1775},"10.1007\u002Fs10549-018-5041-2","2024-05-08T18:44:57.693+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10549-018-5041-2",[1779,1794,1809,1824],{"id":1780,"sortIndex":21,"researcher":20,"roles":1781,"affiliations":1782,"properties":1791,"displayName":1793,"givenName":20,"familyName":20},"cf8bb600-f8f7-4adc-b74f-9e1826f25c33",[266],[1783],{"id":1784,"sortIndex":21,"affiliation":1785,"properties":20},"8a3fc85f-e254-41c9-86a7-f85e9885dd49",{"id":1784,"createTime":20,"updateTime":20,"relativeEntities":1786,"slug":20,"properties":1787,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1790,"statistic":20},[],{"title":1788},{"VI":1789},"Department of Nuclear Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea",[],{"title":1792},{"VI":1793},"Young Hwan Kim",{"id":1795,"sortIndex":278,"researcher":20,"roles":1796,"affiliations":1797,"properties":1806,"displayName":1808,"givenName":20,"familyName":20},"92ed89ae-2d95-471b-ad0d-c4443ed20753",[266],[1798],{"id":1799,"sortIndex":21,"affiliation":1800,"properties":20},"ab202f5c-1c0d-436d-82d5-128e6ca2667f",{"id":1799,"createTime":20,"updateTime":20,"relativeEntities":1801,"slug":20,"properties":1802,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1805,"statistic":20},[],{"title":1803},{"VI":1804},"Department of Physical & Rehabilitation Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea",[],{"title":1807},{"VI":1808},"Ji Hye Hwang",{"id":1810,"sortIndex":304,"researcher":20,"roles":1811,"affiliations":1812,"properties":1821,"displayName":1823,"givenName":20,"familyName":20},"e24a4a1e-d8d9-45b6-8551-65df5d0badc3",[266],[1813],{"id":1814,"sortIndex":21,"affiliation":1815,"properties":20},"64c73f57-14f3-4c68-abf7-cad7691d6a98",{"id":1814,"createTime":20,"updateTime":20,"relativeEntities":1816,"slug":20,"properties":1817,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1820,"statistic":20},[],{"title":1818},{"VI":1819},"Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea",[],{"title":1822},{"VI":1823},"Ji Hoon 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use the National Cancer Database to assess treatment patterns in very young women with ductal carcinoma in situ (DCIS) given their propensity for higher risk features and increased risk of recurrence. We used the NCDB to identify female patients who underwent surgery for a first cancer diagnosis of DCIS within three different age groups: ≤30, 31–50, and >50. Demographic information, tumor characteristics, and initial treatment patterns were characterized and compared. Univariable and multivariable logistic regression of individuals with hormone-receptor-positive disease who underwent breast-conserving surgery (BCS) was conducted to assess for group differences in adjuvant endocrine therapy utilization. Survival analysis was conducted via Kaplan-Meier method and Cox regression. We identified 236,832 patients meeting inclusion criteria. Individuals in the youngest group were more likely to be a minority, had better Charlson-Deyo scores, lived further from their treatment facility, and were less often insured. This group also had more unfavorable tumor features and were more likely to undergo bilateral mastectomy. In subgroup analysis of patients with hormone-receptor-positive disease who underwent BCS, the youngest group was significantly less likely to have received endocrine therapy. There was also a trend toward worse overall survival in the youngest group. We report differences in demographics, tumor characteristics, and treatment of very young women with DCIS. Given the known reduction in recurrence with use of adjuvant endocrine therapy, there may be room for increasing therapy rates or otherwise altering guidelines for treatment of young women with hormone-receptor-positive DCIS who undergo BCS.",{"EN":1902},"Ductal carcinoma in situ in patients younger than 30 years: differences in adjuvant endocrine therapy and outcomes",{"VOID":1904},"[\"12489489362503358569\"]",{"VOID":1906},"Narod SA, Iqbal J, Giannakeas V et al (2015) Breast cancer mortality after a diagnosis of ductal carcinoma in situ. JAMA Oncol 1:888–896. https:\u002F\u002Fdoi.org\u002F10.1001\u002Fjamaoncol.2015.2510\nJones CE, Richman J, Jackson BE et al (2018) Treatment patterns for ductal carcinoma in situ with close or positive mastectomy margins. J Surg Res 231:36–42. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jss.2018.05.007\nSagara Y, Freedman RA, Wong SM et al (2017) Trends in adjuvant therapies after breast-conserving surgery for hormone receptor-positive ductal carcinoma in situ: findings from the National Cancer Database, 2004–2013. Breast Cancer Res Treat 166:583–592. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10549-017-4436-9\nVan Bockstal MR, Agahozo MC, Koppert LB, van Deurzen CHM (2020) A retrospective alternative for active surveillance trials for ductal carcinoma in situ of the breast. Int J Cancer 146:1189–1197. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fijc.32362\nNguyen TT, Hoskin TL, Day CN et al (2017) Factors influencing use of hormone therapy for ductal carcinoma in situ: a National Cancer Database Study. Ann Surg Oncol 24:2989–2998. https:\u002F\u002Fdoi.org\u002F10.1245\u002Fs10434-017-5930-3\nNassar H, Sharafaldeen B, Visvanathan K, Visscher D (2009) Ductal carcinoma in situ in African American versus Caucasian American women: analysis of clinicopathologic features and outcome. Cancer 115:3181–3188. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fcncr.24376\nWard EP, Unkart JT, Bryant A et al (2017) Influence of distance to hospital and insurance status on the rates of contralateral prophylactic mastectomy, a National Cancer Data Base study. Ann Surg Oncol 24:3038–3047. https:\u002F\u002Fdoi.org\u002F10.1245\u002Fs10434-017-5985-1\nCronin PA, Olcese C, Patil S et al (2016) Impact of age on risk of recurrence of ductal carcinoma in situ: outcomes of 2996 women treated with breast-conserving surgery over 30 years. Ann Surg Oncol 23:2816–2824. https:\u002F\u002Fdoi.org\u002F10.1245\u002Fs10434-016-5249-5\nVicini FA, Kestin LL, Goldstein NS et al (2000) Impact of young age on outcome in patients with ductal carcinoma-in-situ treated with breast-conserving therapy. J Clin Oncol Off J Am Soc Clin Oncol 18:296–306. https:\u002F\u002Fdoi.org\u002F10.1200\u002FJCO.2000.18.2.296\nAlvarado R, Lari SA, Roses RE et al (2012) Biology, treatment, and outcome in very young and older women with DCIS. Ann Surg Oncol 19. https:\u002F\u002Fdoi.org\u002F10.1245\u002Fs10434-012-2413-4\nXiong Q, Valero V, Kau V et al (2001) Female patients with breast carcinoma age 30 years and younger have a poor prognosis. Cancer 92:2523–2528. https:\u002F\u002Fdoi.org\u002F10.1002\u002F1097-0142(20011115)92:10\u003C2523::AID-CNCR1603>3.0.CO;2-6\nFrancis PA (2011) Optimal adjuvant therapy for very young breast cancer patients. Breast 20:297–302. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.breast.2011.05.002\nPark HL, Chang J, Lal G et al (2018) Trends in treatment patterns and clinical outcomes in young women diagnosed with ductal carcinoma in situ. Clin Breast Cancer 18:e179–e185. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.clbc.2017.08.001\nLlarena NC, Estevez SL, Tucker SL, Jeruss JS (2015) Impact of fertility concerns on Tamoxifen initiation and persistence. J Natl Cancer Inst 107. https:\u002F\u002Fdoi.org\u002F10.1093\u002Fjnci\u002Fdjv202\nVoci A, Bandera B, Ho E et al (2018) Variations in cancer care for adolescents and young adults (AYAs) with ductal carcinoma in situ. Breast J 24:555–560. https:\u002F\u002Fdoi.org\u002F10.1111\u002Ftbj.12999\nBoffa DJ, Rosen JE, Mallin K et al (2017) Using the national cancer database for outcomes research: a review. JAMA Oncol 3:1722–1728. https:\u002F\u002Fdoi.org\u002F10.1001\u002Fjamaoncol.2016.6905\nParsons BM, Landercasper J, Smith AL et al (2016) 21-gene recurrence score decreases receipt of chemotherapy in ER+ early-stage breast cancer: an analysis of the NCDB 2010–2013. Breast Cancer Res Treat 159:315–326. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10549-016-3926-5\nAllred DC, Anderson SJ, Paik S et al (2012) Adjuvant tamoxifen reduces subsequent breast cancer in women with estrogen receptor-positive ductal carcinoma in situ: a study based on NSABP protocol B-24. J Clin Oncol Off J Am Soc Clin Oncol 30:1268–1273. https:\u002F\u002Fdoi.org\u002F10.1200\u002FJCO.2010.34.0141\nKauffmann RM, Goldstein L, Marcinkowski E et al (2016) Predictors of Antiestrogen recommendation in women with Estrogen receptor-positive ductal carcinoma in situ. J Natl Compr Cancer Netw 14:1081–1090. https:\u002F\u002Fdoi.org\u002F10.6004\u002Fjnccn.2016.0118\nGnerlich JL, Deshpande AD, Jeffe DB et al (2009) Elevated breast cancer mortality in young women (\u003C40 years) compared with older women is attributed to poorer survival in early stage disease. J Am Coll Surg 208:341–347. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jamcollsurg.2008.12.001\nFredholm H, Eaker S, Frisell J et al (2009) Breast cancer in young women: poor survival despite intensive treatment. PLoS One 4. https:\u002F\u002Fdoi.org\u002F10.1371\u002Fjournal.pone.0007695\nVirnig BA, Torchia MT, Jarosek SL et al (2011) Use of endocrine therapy following diagnosis of ductal carcinoma in situ or early invasive breast cancer: data points # 14, Data points publication series. Agency for Healthcare Research and Quality (US), Rockville\nDeCensi A, Puntoni M, Guerrieri-Gonzaga A et al (2019) Randomized placebo controlled trial of low-dose Tamoxifen to prevent local and contralateral recurrence in breast intraepithelial Neoplasia. J Clin Oncol 37:1629–1637. https:\u002F\u002Fdoi.org\u002F10.1200\u002FJCO.18.01779",{"VOID":1908},"10.1007\u002Fs10549-020-06014-5","2024-06-23T01:08:55.066+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10549-020-06014-5",[1912,1927,1940,1955],{"id":1913,"sortIndex":21,"researcher":20,"roles":1914,"affiliations":1915,"properties":1924,"displayName":1926,"givenName":20,"familyName":20},"e21f8fbd-bc5c-4532-a206-68abfb1ca046",[266],[1916],{"id":1917,"sortIndex":21,"affiliation":1918,"properties":20},"4b9b0ed6-759f-40c2-b827-0029ff909588",{"id":1917,"createTime":20,"updateTime":20,"relativeEntities":1919,"slug":20,"properties":1920,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1923,"statistic":20},[],{"title":1921},{"VI":1922},"Department of Surgery, University of California, San Diego, La Jolla, USA",[],{"title":1925},{"VI":1926},"Sasha R. 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