Of all the types of breast cancer, triple negative breast cancer (TNBC) is the most aggressive and lacks specific therapies. TNBC also is more likely to metastasize, or travel through the blood stream to spread to other organs, which causes most of breast cancer-related deaths each year. Until now, tracking circulating tumor cells (CTC), a powerful indicator of cancer metastasis, has been challenging because there are very few markers that specifically identify these cells.
Looking to find a better way to follow metastasis progression, researchers at Baylor College of Medicine developed a procedure to enhance the detection of TNBC cells collected from a simple blood draw, sometimes called a 'liquid biopsy,' offering a minimally invasive way to monitor cancer in near real time. This new approach led to the identification of four new proteins on the surface of live CTCs that specifically identify these cells. Capturing live cells is important because it allows scientists to analyze the genetic material of single cells, helping them understand how cancer spreads and how it might be stopped.
The study appeared in Cancer Research Communications , a journal of the American Association for Cancer Research.
"We developed a new workflow to isolate and analyze live CTCs, focusing first on mouse models of metastatic TNBC and then testing our findings in patient samples," said first author Dr. Bree M. Lege, former graduate student in the laboratory of corresponding author Dr. Chonghui Cheng , professor of molecular and human genetics and molecular and cellular biology and in the Lester and Sue Smith Breast Center at Baylor. Cheng also is a member of Baylor's Dan L Duncan Comprehensive Cancer Center.
The team began by capturing live CTCs, which typically are very few, from blood of tumor‑bearing mice by separating the tumor cells from normal blood cells. Next, they isolated individual tumor cells and analyzed them using single‑cell RNA sequencing, which measures gene activity in each cell. This allowed the researchers to see which genes – and importantly, which cell‑surface proteins – were present in TNBC CTCs.
The analysis allowed them to identify four new markers, AHNAK2, CAVIN1, ODR4 and TRIML2, that were present on the surface of CTCs but not in normal blood cells.
"We are very pleased with our approach to identify CTCs in blood," Cheng said. "The new markers detected cells that standard methods missed. When the four new markers were combined, detection improved substantially. Importantly, the new markers on CTCs showed very little overlap with markers on normal blood cells, reducing the risk of false positives."
"We were excited with the results with blood from patients with metastatic TNBC," Cheng said. "In these patients, tumor cells were frequently undetectable using standard markers but became clearly visible when we applied the new marker combination."
This study addresses a major limitation in liquid biopsy technology for aggressive breast cancers. Being able to reliably detect TNBC CTCs could help doctors monitor disease progression and treatment response more accurately. Because these markers allow live CTC capture, researchers can study the genetic expression of tumor cells in unprecedented detail, helping uncover how metastasis occurs and why some tumors resist treatment.
"Another exciting finding is that the newly identified markers are also expressed in other cancer types, suggesting that this strategy could improve CTC detection across multiple cancers," Cheng said.
BCM has a provisional patent on the Enhanced Detection of Circulating Tumor Cells in Triple Negative Breast Cancer.
Other contributors to this work include Khushali J. Patel, Brendan Panici, Ping Gong, Michael T. Lewis and Matthew J. Ellis, all at Baylor College of Medicine.
This project was supported by grants from Department of Defense (HT94252310753), NIH (R01CA276432) and a CPRIT Cancer Research fellowship (RR160009). The work also was supported by the Patient-Derived Xenograft Core part of the Lester and Sue Smith Breast Center at Baylor College of Medicine with funding from a CPRIT Core Facility Award (RP220646) and P30 Cancer Center Support Grant (NCI-CA125123), and by the Cytometry and Cell Sorting Core at Baylor College of Medicine with funding from a CPRIT Core Facility Support Award (CPRIT-RP180672) and the NIH (P30 CA125123 and S10 RR024574).
