| 1. |
- Borg, Åke, et al.
(författare)
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Predicting the future of breast cancer.
- 2003
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Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1546-170X .- 1078-8956. ; 9:1, s. 16-18
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Gruvberger, Sofia, et al.
(författare)
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Estrogen receptor status in breast cancer is associated with remarkably distinct gene expression patterns
- 2001
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Ingår i: Cancer Research. - 1538-7445. ; 61:16, s. 5979-5984
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Tidskriftsartikel (refereegranskat)abstract
- To investigate the phenotype associated with estrogen receptor alpha (ER) expression in breast carcinoma, gene expression profiles of 58 node-negative breast carcinomas discordant for ER status were determined using DNA microarray technology. Using artificial neural networks as well as standard hierarchical clustering techniques, the tumors could be classified according to ER status, and a list of genes which discriminate tumors according to ER status was generated. The artificial neural networks could accurately predict ER status even when excluding top discriminator genes, including ER itself. By reference to the serial analysis of gene expression database, we found that only a small proportion of the 100 most important ER discriminator genes were also regulated by estradiol in MCF-7 cells. The results provide evidence that ER+ and ER- tumors display remarkably different gene-expression phenotypes not solely explained by differences in estrogen responsiveness.
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| 3. |
- Gruvberger, Sofia, et al.
(författare)
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Expression profiling to predict outcome in breast cancer: the influence of sample selection
- 2003
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 5:1, s. 23-26
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Tidskriftsartikel (refereegranskat)abstract
- Gene expression profiling of tumors using DNA microarrays is a promising method for predicting prognosis and treatment response in cancer patients. It was recently reported that expression profiles of sporadic breast cancers could be used to predict disease recurrence better than currently available clinical and histopathological prognostic factors. Having observed an overlap in those data between the genes that predict outcome and those that predict estrogen receptor- status, we examined their predictive power in an independent data set. We conclude that it may be important to define prognostic expression profiles separately for estrogen receptor--positive and estrogen receptor--negative tumors.
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| 4. |
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| 5. |
- Koul, Anjila, et al.
(författare)
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TP53 protein expression analysis by luminometric immunoassay in comparison with gene mutation status and prognostic factors in early stage endometrial cancer
- 2002
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Ingår i: International Journal of Gynecological Cancer. - : BMJ. - 1048-891X .- 1525-1438. ; 12:4, s. 362-371
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Tidskriftsartikel (refereegranskat)abstract
- Mutations in the TP53 tumor suppressor gene have been shown to significantly correlate with poor prognosis in endometrial cancer. In the present study we have evaluated a luminometric immunoassay (LIA) for quantitative estimation of TP53 protein expression in 65 cytosol preparations from endometrial cancer, previously analyzed for mutations in TP53 exons 4-10. LIA showed high (greater than or equal to 0.6 ng/mg protein) expression of TP53 protein in all eight tumors with missense mutation, but high protein levels were also detected in 15 tumors with normal TP53 sequence. All four tumors with nonsense or frameshift mutations had low or no TP53 protein expression. LIA was further evaluated in a retrospective study of 201 cytosol samples from endometrial cancer. TP53 overexpression (>= 0.6 ng/mg protein) was observed in 22% of the tumors and correlated with nonendometrioid histology types (P = 0.005), poorly differentiated tumors (P = 0.001), higher FIGO grade (P = 0.001), DNA nondiploidy (P = 0.002), and high S-phase fraction (P = 0.03). After a median follow-up time of 6.8 years (range 0.7-9.9 years), 22 (13%) progressions were observed in the 175 patients with early stage (I-II) disease. TP53 overexpression (P = 0.04), FIGO grade 3 vs. 1 + 2 (P = 0.01), higher age (P = 0.02), and DNA nondiploidy (P < 0.001) showed significant correlation to shorter progression-free survival in these patients. We conclude that TP53 protein analysis by LIA provides an incomplete correlation to mutation status and cannot substitute for mutation analysis in assessment of prognosis in endometrial carcinoma. In comparison to TP53 overexpression and higher FIGO grades, DNA nonploidy status seems to be a better prognostic indicator to define a subset of early stage endometrial cancer patients who may benefit by adjuvant chemotherapy/radiotherapy.
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