The grant awarded by the US National Cancer Institute to Arul Chinnaiyan, a professor at the University of Michigan, will provide long-term support to increase understanding of these markers to leverage targeted treatments for cancer.
Chinnaiyan has received an ‘Outstanding Investigator Award’ from the National Cancer Institute, which provides USD 6.5 million in funding over seven years, the University of Michigan said in a statement.
“The field of precision oncology continues to evolve with the overarching goal of providing cancer patients with enhanced diagnostic and prognostic capabilities and better treatments,” said Chinnaiyan, a professor of Pathology at the University of Michigan Medical School.
“This grant will help us identify new biomarkers and understand their biological roles in cancer progression,” Chinnaiyan said in a statement.
The award — roughly three times a traditional individual investigator award — is part of a grant programme called R35 developed by the National Cancer Institute.
It is designed to fund projects of unusual potential in cancer research over an extended period of seven years.
The goal is to provide established investigators long-term support that gives them the flexibility to focus on exceptional and ambitious cancer research programmes.
The award is designed to support the very best researchers who have a track record of innovation and success, the statement said.
In 2010, Chinnaiyan launched the Michigan Oncology Sequencing Program at the Rogel Cancer Center.
Mi-ONCOSEQ is a research protocol for sequencing the DNA and RNA of metastatic cancers and normal tissue to identify alterations that could help drive treatment.
Chinnaiyan’s lab has also analysed the global landscape of a portion of the genome that has not been previously well-explored — long non-coding RNAs.
This vast portion of the human genome has been considered the dark matter because so little is known about it.
Emerging new evidence suggests that lncRNAs may play a role in cancer and that understanding them better could lead to new potential targets for improving cancer diagnosis, prognosis or treatment.