Literature DB >> 8123871

DNA ploidy, S-phase, and steroid receptors in more than 127,000 breast cancer patients.

C R Wenger1, S Beardslee, M A Owens, G Pounds, T Oldaker, P Vendely, M R Pandian, D Harrington, G M Clark, W L McGuire.   

Abstract

Several potential prognostic factors are available today for patients with breast cancer, and many more are being identified and studied. To evaluate the clinical utility of these factors, it will be necessary to measure them on a large number of patients, and then follow these patients so that multivariate survival analyses can be performed. The Oncology Research Network was established in 1986 by the University of Texas Health Science Center at San Antonio and Nichols Institute Reference Laboratories in order to evaluate the clinical utility of new prognostic factors for patients with primary breast cancer. The first generation of prognostic factors included steroid receptors, along with DNA ploidy and S-phase fraction determined by flow cytometry. Currently, laboratory results have been obtained from more than 127,000 patients, and follow-up information is available on a subset of more than 25,000 of these patients. S-phase fraction was related to the ploidy status of the tumor. An increased incidence of aneuploidy and higher S-phase fractions were found in estrogen and progesterone receptor negative tumors, tumors from patients with positive axillary lymph nodes, tumors greater than 2 cm in diameter, and patients younger than 35 years of age. Preliminary survival analyses suggest that S-phase fraction and DNA ploidy, in combination with other prognostic factors, are powerful predictors of early disease relapse. The Oncology Research Network provides an important resource for examining the clinical significance of new laboratory assays and for expediting improvements in existing laboratory techniques.

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Year:  1993        PMID: 8123871     DOI: 10.1007/bf00666351

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  31 in total

1.  Comparison of extent of disease and morphometric and DNA flow cytometric prognostic factors in invasive ductal breast cancer.

Authors:  A M Uyterlinde; N W Schipper; J P Baak
Journal:  J Clin Pathol       Date:  1987-12       Impact factor: 3.411

2.  Is DNA ploidy an independent prognostic indicator in infiltrative node-negative breast adenocarcinoma?

Authors:  S Keyhani-Rofagha; R V O'Toole; W B Farrar; B Sickle-Santanello; J DeCenzo; D Young
Journal:  Cancer       Date:  1990-04-01       Impact factor: 6.860

3.  The use of flow cytometry for the prognosis of stage II adjuvant treated breast cancer patients.

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Journal:  Cancer       Date:  1990-10-15       Impact factor: 6.860

4.  Multiparametric deoxyribonucleic acid and cell cycle analysis of breast carcinomas by flow cytometry. Clinicopathologic correlations.

Authors:  D W Visscher; R J Zarbo; G Jacobsen; A Kambouris; G Talpos; W Sakr; J D Crissman
Journal:  Lab Invest       Date:  1990-03       Impact factor: 5.662

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Authors:  S B Ewers; E Långström; B Baldetorp; D Killander
Journal:  Cytometry       Date:  1984-07

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Journal:  Cancer Res       Date:  1987-09-01       Impact factor: 12.701

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Authors:  S A Fuqua; S D Fitzgerald; G C Chamness; A K Tandon; D P McDonnell; Z Nawaz; B W O'Malley; W L McGuire
Journal:  Cancer Res       Date:  1991-01-01       Impact factor: 12.701

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Journal:  N Engl J Med       Date:  1990-04-12       Impact factor: 91.245

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Journal:  Cancer       Date:  1989-08-01       Impact factor: 6.860

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Journal:  Br J Cancer       Date:  1986-01       Impact factor: 7.640

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  25 in total

1.  Prognostic and Predictive Factors for Breast Cancer.

Authors: 
Journal:  Breast Cancer       Date:  1995-10-31       Impact factor: 4.239

2.  Reverse transcription-polymerase chain reaction (RT-PCR) assays of estrogen and progesterone receptors in breast cancer.

Authors:  S Chevillard; A Müller; C Levalois; C Lainé-Bidron; P Vielh; H Magdelénat
Journal:  Breast Cancer Res Treat       Date:  1996       Impact factor: 4.872

Review 3.  Prognostic factors in node-negative breast cancer: a review of studies with sample size more than 200 and follow-up more than 5 years.

Authors:  Attiqa N Mirza; Nadeem Q Mirza; Georges Vlastos; S Eva Singletary
Journal:  Ann Surg       Date:  2002-01       Impact factor: 12.969

4.  Rat strain-specific actions of 17beta-estradiol in the mammary gland: correlation between estrogen-induced lobuloalveolar hyperplasia and susceptibility to estrogen-induced mammary cancers.

Authors:  D M Harvell; T E Strecker; M Tochacek; B Xie; K L Pennington; R D McComb; S K Roy; J D Shull
Journal:  Proc Natl Acad Sci U S A       Date:  2000-03-14       Impact factor: 11.205

Review 5.  Breast cancer in African American women: epidemiology and tumor biology.

Authors:  B J Trock
Journal:  Breast Cancer Res Treat       Date:  1996       Impact factor: 4.872

6.  DNA ploidy analyses in 218 consecutive Pakistani breast cancer patients: does it add anything?

Authors:  E Khan; Z Mapara; S Khan; N Arshad; T Siddiqui; S Pervez
Journal:  Pathol Oncol Res       Date:  2001       Impact factor: 3.201

7.  Immunohistochemical study of androgen receptors in breast carcinoma. Evidence of their frequent expression in lobular carcinoma.

Authors:  Cristina Riva; Emanuele Dainese; Giacomo Caprara; Paolo Cossu Rocca; Giovanni Massarelli; Tibor Tot; Carlo Capella; Vincenzo Eusebi
Journal:  Virchows Arch       Date:  2005-10-19       Impact factor: 4.064

8.  Improved detection of DNA aneuploidy in primary breast cancer using quantitative DNA image analysis in combination with fluorescent in situ hybridization technique.

Authors:  B Verdoodt; P Castelain; C Bourgain; M Kirsch-Volders
Journal:  Histochem J       Date:  1995-01

9.  Estrogen receptor beta protein in human breast cancer: correlation with clinical tumor parameters.

Authors:  Suzanne A W Fuqua; Rachel Schiff; Irma Parra; John T Moore; Syed K Mohsin; C Kent Osborne; Gary M Clark; D Craig Allred
Journal:  Cancer Res       Date:  2003-05-15       Impact factor: 12.701

10.  Making the most of your prognostic factors: presenting a more accurate survival model for breast cancer patients.

Authors:  K L Knorr; S G Hilsenbeck; C R Wenger; G Pounds; T Oldaker; P Vendely; M R Pandian; D Harrington; G M Clark
Journal:  Breast Cancer Res Treat       Date:  1992       Impact factor: 4.872

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