Sendurai Mani, Associate Director of Translational Oncology at the Legorreta Cancer Center, is presenting a series exploring some of the most influential scientific papers that have shaped the field of cancer research on LinkedIn:
I recently shared an AI-generated (Claude) list of the top 200 papers that have shaped cancer research on LinkedIn. Today, I share more about Paper 10.
Paper 10: Gene expression profiling predicts clinical outcome of breast cancer
Could the genes active inside a breast tumor help predict whether that cancer is likely to recur?
In 2002, Laura van ’t Veer and colleagues published a landmark Nature study using gene-expression profiling to investigate clinical outcomes in breast cancer.
The researchers studied tumors from 117 young patients and developed a 70-gene expression signature capable of distinguishing tumors associated with different risks of distant metastasis.
This represented an important shift.
Traditional prognosis relied heavily on features such as tumor size, grade, lymph-node involvement, and receptor status.
Gene-expression profiling offered another layer of information:
- Tumor tissue
- gene-expression pattern
- molecular signature
- recurrence-risk information
The work helped establish the principle that the collective behavior of multiple genes could provide clinically relevant information that may not be apparent from anatomy alone.
The 70-gene signature later became the basis for MammaPrint, with subsequent studies evaluating and validating its clinical utility in broader patient populations.
The paper also marked an important transition in cancer genomics: From describing molecular differences to asking whether those differences could help guide clinical decisions.
Importantly, this initial study developed a prognostic signature; later prospective research was needed to establish how genomic risk information could be incorporated into treatment decisions.
The enduring lesson: Precision oncology is not only about finding a drug target. Molecular information can also help estimate how a cancer may behave.
Title: Gene expression profiling predicts clinical outcome of breast cancer
Authors: Laura van ‘t Veer, Hongyue Dai, Marc van de Vijver, Yudong He, Augustinus Hart, Mao Mao, Hans Peterse, Karin van der Kooy, Matthew Marton, Anke Witteveen, George Schreiber, Ron Kerkhoven, Chris Roberts, Peter Linsley, René Bernards, Stephen Friend
Read the Full Article.
You can also read: 200 Most Influential Cancer Papers Suggested by Sendurai Mani: How a Human Oncogene Is Activated
