Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Prediction of metastasis from low-malignant breast cancer by gene expression profiling

Prediction of metastasis from low-malignant breast cancer by gene expression profiling

Abstract

Promising results for prediction of outcome in breast cancer has been obtained by genome wide gene expression profiling. Some studies have suggested that an extensive overtreatment of breast cancer patients might be reduced by risk assessment with gene expression profiling. A patient group hardly examined in these studies is the low-risk patients who are very difficult to differentiate with currently used methods. These patients do not receive adjuvant treatment according to the guidelines of the Danish Breast Cancer Cooperative Group (DBCG). In this study a group of tumors from low-risk patients was examined with gene expression profiling. An intermediate risk group of low-malignant T2 tumors that fulfilled all other low-risk criteria than tumor size was included to increase statistical power. A 32-gene classifier, HUMAC32, was identified and it accurately predicted metastases. The classifier was also validated in an independent group of high-risk tumors resulting in comparable performance of HUMAC32 and a 70-gene classifier developed for this group. Furthermore, the 70-gene signature was tested in the present low- and intermediate-risk samples. The results indicated better performance of HUMAC32 among the low-malignant cancers compared to the 70-gene classifier. This may indicate that although the metastatic potential of a tumor is on the whole determined by the same genes in tumors with different characteristics and risk, some expression patterns have higher predictive power in the low-risk group. Keywords: case-control design Overall design: In this study, a group of low-risk node-negative patients with long follow-up was studied with the aim to predict metastasis in this group by gene expression profiling using a 29K chip composed with 60-mer oligonucleotides. Thirteen patients who fulfilled the low-risk criteria, defined by DBCG, and who developed metastasis were matched with 13 patients who did not develop metastasis within 10 years (L samples). The DBCG low-risk criteria are essentially the same as the criteria defined at the eighth St. Gallen meeting in 2003: Node negative, T = 20 mm, grade = 1 if ductal carcinoma NOS (not otherwise specified), receptor positive, and age = 35. In addition a group of 17 intermediate-risk tumors (Node negative, T = 50 mm, grade = 1 if ductal carcinoma NOS, receptor positive, and age = 35) from patients who developed metastasis and 17 matched non-metastasizing tumors was included. This group did not fulfill the DBCG low-risk criteria because the tumor size was 20-50 mm, but satisfied all other criteria (R samples) Metastasis: A-samples Non-metastases: B-samples

Keywords

Transcriptomics

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Related to Research communities