Each of the cells in breast cancer tumors have different genomes and, depending on the tumor cell, they can grow in different rhythms, according to new research led by Nicholas Navin, Ph.D., an assistant professor in the Department of Genetics at The University of Texas M.D. Anderson Cancer Center in Houston. As part of the study, the scientists developed a new sequencing approach, revealing that the different subtypes of breast cancer displayed varied tumor diversity.
The research developed by Navin is an important contribution to the understanding of genomic diversity within tumors. The findings of the study, which were published in this week’s issue of the journal Nature, may have significant implications for the diagnosis and treatment of breast cancer, and may be useful in the development of chemotherapy for breast cancer patients, as well as for clinical applications such as predicting tumor invasion, metastasis, and survival rates.
The new sequencing approach designed by the team, Nuc-Seq, revealed that different subtypes of breast cancer displayed varied tumor diversity. Although other large-group sequencing studies of breast tumors had already identified many prevalent mutations, this was the first time that a study was able to also explore the tumor cells’ diversity.
“We found that two distinct ‘molecular clocks’ were operating at different stages of tumor growth,” said Navin. “Tumor cells from triple-negative breast cancer had an increased mutation rate, while tumor cells from estrogen receptor positive (ER+) breast cancer did not.” According to the study, approximately 75 percent of breast cancer diagnoses are ER+ and grow based on estrogen levels, which calls for hormone-related treatment for the disease. Triple-negative breast cancers, on the other hand, represent 15 to 25 percent of breast cancer diagnoses and typically do not respond well to hormone therapy or standard chemotherapy.
Nuc-Sec was developed as a single-cell genome sequencing method and used to examine how cell mutations occur in both types of breast cancer. The researchers were able to profile thousands of cells, combining the technology with single-cell molecule sequencing. “A common problem in the field of single cell genomics is the inability to validate mutations that are detected in individual cells,” explained postdoctoral fellow Yong Wang, Ph.D., and first author on the study. “To address this problem we combined single-cell sequencing with targeted single-molecule deep sequencing. This approach not only validates mutations, but also measures the precise mutation frequencies of thousands of cells.”
The research team also addressed the problem of resistant mutations that pre-exist in rare tumor cells, as well as their spontaneous emergence in response to therapy. “While this question has been studied for decades in bacteria, it remains poorly understood in most human cancers,” said Navin. “Our data suggests that a large number of diverse mutations are likely to be pre-existing in the tumor prior to chemotherapy. Therefore, we expect that measuring genomic diversity will have prognostic value in identifying which patient will develop resistance to chemotherapy.”
In addition to Navin, other researchers on the project included Yong Wang, Ph.D., Funda Merica-Bernstam, M.D., Han Liang, Ph.D., Asha Multani, Ph.D., Paul Scheet, Ph.D., and Ken Chen, Ph.D.
The research was funded by the National Institutes of Health, in collaboration with the National Cancer Institute, the Nadia’s Gift Foundation Damon Runyon-Rachleff Innovator, the T.C. Hsu and Alice-Reynolds Kleberg Foundation, the Center for Genetics & Genomics, the Susan G. Komen for the Cure, the Dell Foundation, and the Cancer Prevention Research Institute of Texas.