A simple, fast, and effective blood test for a wide range of cancers is closer to becoming a new reality, according to a new study published in Nature Medicine. Researchers from Standford University have devised a new technique that could make the test happen in the near future.

Researchers from the Standford University School of Medicine have designed a highly sensitive way of finding DNA from cancer tumors within the bloodstream.

Although past research has shown that circulating tumor DNA is a promising biomarker for cancer, current methods for detecting it are not sensitive enough and do not cover a wide range of cancers.

The tests that are currently on the market may be altered to increase their sensitivity and detection rate, although the process is often drawn out and cumbersome. Because the process involves many steps to customize the tests for individuals, it is not used in clinics.

The new approach from the Stanford University researchers appears to change this. That is because the test is very specific and is to be used with a wide range of cancers.

During the course of the study, the new test found half of all patients with state 1 lung cancer. The new test also found all cases of stage 2 or higher lung cancer. Additionally, the new test depicted circulation DNA tumor in high correlation with tumor volume using CT and PET scans for estimates.

Tumors are often referred to as solid, or liquid, depending on the area they are growing within the body. Over 80 percent of all cancers result from solid tumors that grow as a group of cells in a specific organ, gland, or tissue.

The new sequence, referred to as CAPP-Seq, or cancer personalized profiling by deep sequencing, is highly sensitive and can detect a single molecule of tumor DNA out of 10,000 healthy DNA molecules within the blood.

Assistant professor of radiation oncology at Stanford University’s School of Medicine, Maximilian Diehn, said, “We set out to develop a method that overcomes two major hurdles in the circulating tumor DNA field. We are trying to develop a general method to detect and measure disease burden.”