By counting the number of cancer-fighting immune cells inside tumors, scientists say they may have found a way to predict survival from ovarian cancer.
The researchers developed an experimental method to count these cells, called tumor-infiltrating T lymphocytes (TILs), in women with early stage and advanced ovarian cancer.
"We have developed a standardizable method that should one day be available in the clinic to better inform physicians on the best course of cancer therapy, therefore improving treatment and patient survival," said lead researcher Jason Bielas, at the Fred Hutchinson Cancer Research Center, in Seattle.
The test may have broader implications beyond ovarian cancer and be useful with other types of cancer, the study authors suggested.
In their current work with ovarian cancer patients, the researchers "demonstrated that this method can be used to diagnose T-cells quickly and effectively from a blood sample," said Bielas, an associate member in human biology and public health sciences.
The report was published online Dec. 4 in Science Translational Medicine.
The researchers developed the test to count TILs, identify their frequency and develop a system to determine their ability to clone themselves. This is a way of measuring the tumor's population of immune T-cells.
The test works by collecting genetic information of proteins only found in these cells.
"T-cell clones have unique DNA sequences that are [comparable] to product barcodes on items at the grocery store. Our technology is comparable to a barcode scanner," Bielas said.
The technique, called QuanTILfy, was tested on tumor samples from 30 women with ovarian cancer whose survival ranged from one month to about 10 years.
Bielas and colleagues looked at the number of TILs in the tumors, comparing those numbers to the women's survival.
The researchers found that higher TIL levels were linked with better survival. For example, the percent of TILs was about three times higher in women who survived more than five years than in those who survived less than two years.
"We are hoping to investigate whether this is a general phenomena of all cancers," Bielas said. "There is good evidence now that the same associations can be made for melanoma and colorectal cancer."
This new technology potentially could be used to predict treatment response, cancer recurrence and disease-free survival earlier and more effectively than current methods, Bielas noted.
It could therefore be used to guide personalized medicine. For example, it could be used to determine which immune and chemotherapy drugs are best to treat a particular patient, Bielas suggested.
"Thus, TIL can be used to guide the selection of drugs for cancer therapy, thereby improving patient outcome. The implementation of this assay in the clinic should improve cancer diagnostics and ultimately save lives," he said.
Because the test is still experimental, Bielas could not estimate what the test might cost if it were eventually approved and used widely in patients.
Right now the test isn't ready for general use, according to Dr. Franck Pages, a professor of immunology at the Hospital European Georges Pompidou in Paris, and author of an accompanying journal editorial.
"The new technology does not obviously fulfill the requirements for an easy routine clinical use to quantify T-cell infiltration in a tumor," Pages said, "but the technology could help in immunotherapy trials to determine the immunological response induced in the tumor."
Another expert agreed that more work must be done before the test can be used clinically.
"It's been known for some time that there is a correlation between the level of natural killer cells -- T-cells -- and the prognosis of patients," said William Chambers, interim national vice president for extramural research at the American Cancer Society.
"There is going to be a need for other people to verify the findings from this study," Chambers said. "There is also a need to figure out how this would fit in the context of any sort of clinical approach."