Gene expression correlates of clinical prostate cancer behavior.

@article{Singh2002GeneEC,
  title={Gene expression correlates of clinical prostate cancer behavior.},
  author={Dinesh Singh and Phillip G. Febbo and Kenneth Ross and Donald G. Jackson and Judith B. Manola and Christine M Ladd and Pablo Tamayo and Andrew A Renshaw and Anthony V. D'Amico and Jerome P. Richie and Eric S. Lander and Massimo F. Loda and Philip W. Kantoff and Todd R. Golub and William R Sellers},
  journal={Cancer cell},
  year={2002},
  volume={1 2},
  pages={203-9}
}
Prostate tumors are among the most heterogeneous of cancers, both histologically and clinically. Microarray expression analysis was used to determine whether global biological differences underlie common pathological features of prostate cancer and to identify genes that might anticipate the clinical behavior of this disease. While no expression correlates of age, serum prostate specific antigen (PSA), and measures of local invasion were found, a set of genes was identified that strongly… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 28 references

Delinea - tested , after exclusion of one sample , genes were ranked using the S 2 N tion of prognostic biomarkers in prostate cancer

K. Kurachi, K. J. Pienta, M. A. Rubin, A. M. Chinnaiyan
Nature • 2001

Gene expression ( 2002 ) . Prediction of central nervous system embryonal tumour outcome profiling predicts clinical outcome of breast cancer

J. B. Welsh, L. M. Sapinoso, +10 authors G. M. Hampton
Nature • 2001
View 2 Excerpts

Identification of differentially expressed genes in organ - and permutation testing for dichotomous variables confined

A. Chetcuti, S. Margan, +4 authors Q. Dong
PROSTATE • 2001

Molecular abnormalities in prostateA and B prostatic cancer

H. J. Jewett
Urol . Clin . North Am . Prostate Cancer : Principles & Practice • 2001

T specific biochemical recurrence-free survival following radical prostatectomy

O RREP
2001

Cancer statiscontinuous variable ) . Pearson coefficients were also used to measure the tics , 2000

P. C. Walsh
CA Cancer J . Clin . • 2000

Molecular of the prostate

L. A. Akslen
Nature • 2000

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