Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer

Weizmann Institute of Science

PubMed
Indexed incrossrefpubmed

Abstract

Predicting at the time of discovery the prognosis and metastatic potential of cancer is a major challenge in current clinical research. Numerous recent studies searched for gene expression signatures that outperform traditionally used clinical parameters in outcome prediction. Finding such a signature will free many patients of the suffering and toxicity associated with adjuvant chemotherapy given to them under current protocols, even though they do not need such treatment. A reliable set of predictive genes also will contribute to a better understanding of the biological mechanism of metastasis. Several groups have published lists of predictive genes and reported good predictive performance based on them.…

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Authors

3

Topics & keywords

Keywords
  • Robustness (evolution)
  • Breast cancer
  • Computational biology
  • Gene signature
  • Predictive value
  • Bioinformatics
  • Computer science
  • Gene expression profiling
UN Sustainable Development Goals
  • Good health and well-being
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