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Genomic Analysis Shown to Detect Early Pancreatic Cancer

Blood sample tubes


29 Sept. 2021. Analysis of genomic and protein indicators in blood samples is shown to detect pancreatic cancer in earlier stages, increasing chances of survival. Researchers from cancer analytics company Freenome in South San Francisco and University of Pittsburgh report their findings today at a virtual meeting of American Association of Cancer Research.

Pancreatic cancer is often difficult to diagnose in its early stages, due to few unique symptoms associated with the disease, and because the pancreas is hidden among other organs in the body. As a result, it is often diagnosed in later, more advanced stages of the disease, with generally a poor prognosis for survival. American Cancer Society estimates more than 60,000 people in the U.S. will be diagnosed with pancreatic cancer this year, leading to some 48,200 deaths.

Pancreatic cancer has an overall five-year survival rate of about 11 percent, with pancreatic ductal adenocarcinoma, or PDAC, the most common form of the disease. Detecting pancreatic cancer while in an early stage and still localized increases the five-year survival rate to 42 percent.

Freenome aims to improve the state of cancer diagnostics, making it possible to discover cancer earlier in the development of the disease, when individuals have more treatment and even prevention options. Part of the problem with current screening methods, says the company, is the application of simplified models to understand a dynamic, complex disease such as cancer. Moreover, physicians need to know more information about the particular disease than just its presence or absence in the patient.

A range of pancreatic cancer stages

The company’s technology combines genomics, computational biology, and artificial intelligence to analyze routine blood samples. Rather than focusing on a few genetic mutations suspected of causing a person’s cancer, Freenome says its process analyzes the full gamut of molecular clues in the blood, looking for evidence of immune-system or metabolic changes, as well as DNA from cells emitted by a tumor. These analytics, says the company, seek to identify unique molecular signatures that not only detect the presence of cancer, but also provide a detailed picture of the disorder for oncologists to prescribe a precise treatment earlier in the course of the disease.

The new retrospective study, led by Freenome computational biologist Teng-Kuei Hsu, evaluates the company’s analysis of blood samples from 75 individuals diagnosed with PDAC. The authors note the only FDA-cleared biomarker for pancreatic cancer testing is carbohydrate antigen 19-9, or CA19-9, used mainly to monitor progression, not detect the disease. The study compares the Freenome analysis combining methylation profiles of cell-free DNA in blood combined with CA19-9 test results, to CA19-9 analytics alone.

The 75 participants with PDAC represent a range of pancreatic cancer stages from growing but still localized (stage 2), to spreading to nearby tissues or lymph nodes (stage 3), to metastasizing or spreading to other parts of the body (stage 4). Overall, the Freenome analysis plus CA19-9 returned results with true-positive sensitivity in 93 percent of cases, ranging from 82 percent in stage 2 cases to 89 percent at stage 3, and 100 percent in stage 4.

The team found these sensitivity levels while holding true-negative specificity at 96 percent. Lowering specificity to 92 percent returned slightly higher sensitivity scores at stages 2 and 3, while also 100 percent at stage 4. Overall sensitivity for CA19-9 analysis alone was 88 and 87 percent for the same two respective specificity levels.

“An accurate blood-based test like this could be a powerful tool for early diagnosis and treatment, impacting so many patients,” says University of Pittsburgh medical school professor Randall Brand and a co-author of the study in a Freenome statement. “We are hoping to further validate the findings through additional studies, which are already underway.”

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