For people with lymphoma, getting the right diagnosis can be a race against time.
Symptoms such as swollen lymph nodes, fever, weight loss and fatigue can be signs of this cancer, but they can also point to infections such as tuberculosis or other illnesses. Confirming a lymphoma diagnosis usually requires a surgical biopsy that is then reviewed by specialized doctors. That process can take weeks or months, depending on where a patient lives, delaying treatment and allowing the disease to progress.
Researchers at MUSC Hollings Cancer Center and international collaborators believe a simple blood test could shorten the road to a lymphoma diagnosis.
Published in HemaSphere , their study describes the Access to Diagnosis using Liquid Biopsy (ADLiB) platform, a new test that combines multiple genetic clues from a simple blood sample with machine learning to identify patients most likely to have lymphoma. Rather than replacing a biopsy, the test is designed to help clinicians to prioritize patients who need one most urgently.
"We're trying to address one of the biggest bottlenecks in lymphoma care, which is getting patients diagnosed quickly and accurately," said Hollings physician-scientist Katherine Antel, M.D., Ph.D. , lead author of the study. "Our goal is to identify the patients who are most at risk for lymphoma so they can move to a biopsy and treatment much sooner."
A diagnostic bottleneck
Lymphoma is challenging to diagnose. Its symptoms overlap with those of many other conditions, making accurate diagnosis difficult. Even after lymphoma is suspected, patients can face delays in getting the biopsy and specialized pathology needed to confirm the disease.
Although those barriers exist around the world, South Africa faces an additional challenge: Tuberculosis is common there, and its symptoms can closely mimic lymphoma.
Antel, who practiced and conducted research in South Africa before joining MUSC, has spent years studying the delays patients face in receiving a lymphoma diagnosis. That experience shaped the development of ADLiB and gave her a broader perspective on the challenges of diagnosing lymphoma.
"Lymphoma is a global problem," she explained. "When I came to South Carolina, I was surprised to see many of the same challenges here that I see in other parts of the world: late diagnosis and limited access to specialized pathology expertise."
One reason for diagnostic delays is that many patients undergo a fine-needle aspiration, a minimally invasive procedure that removes only a small sample of cells. While useful for many conditions, it often does not yield sufficient tissue to diagnose lymphoma accurately.
"To diagnose lymphoma, you really need tissue," Antel said. "A fine-needle aspiration can come back falsely negative. Patients are reassured, and then the diagnosis is missed until they become much sicker."
The consequences of that delay can be severe. Previous research has shown that patients with lymphoma can face significant delays between first seeking medical care and receiving a diagnosis, potentially postponing treatment for a disease that can progress quickly. Studies have also highlighted the serious consequences of delays in completing diagnostic testing, particularly for patients with aggressive forms of lymphoma.
Searching for cancer's genetic clues
ADLiB is not meant to replace a biopsy. Instead, it is designed to help clinicians to determine which patients should be fast-tracked for more rigorous testing.
The platform analyzes cell-free DNA – tiny fragments of DNA released into the bloodstream after cells die. Mixed within that are minute amounts of DNA shed by lymphoma cells.
"We're looking for a needle in a haystack," Antel said. "We're looking for a very small amount of tumor DNA within all the body's circulating DNA."
Most liquid biopsy tests focus on one type of genetic signal. ADLiB combines several signals, measuring:
- Tumor DNA levels.
- Lymphoma-associated mutations.
- Chromosome changes.
- Immune cell receptor patterns.
- Infectious pathogens that can mimic lymphoma, including tuberculosis.
A machine-learning algorithm weighs all those signals together to estimate a patient's likelihood of having lymphoma.
Putting the test to work
Before studying ADLiB in patients, the researchers first confirmed that it could accurately detect the genetic changes associated with lymphoma using laboratory samples and patient samples with known results. Those early tests showed that the approach was highly accurate, giving the researchers confidence to evaluate it in patients.
The researchers tested ADLiB in 124 adults in Cape Town, South Africa, who presented with enlarged lymph nodes, a common early sign of lymphoma. About three-quarters were ultimately diagnosed with lymphoma, while the remainder had tuberculosis, benign conditions or metastatic solid tumors. Approximately one-third of patients were living with HIV, a population at substantially increased risk of developing lymphoma.
Compared with patients whose enlarged lymph nodes had other causes, those with lymphoma consistently had higher levels of circulating tumor DNA and more cancer-associated genetic mutations.
This would prioritize patients who are at high risk of having lymphoma and need to be expedited for a tissue biopsy. It doesn't eliminate the need for a biopsy, but it can help us identify those patients much earlier.
Katherine Antel, M.D., Ph.D.
Researchers then used the machine-learning program to combine those genetic clues. The platform correctly identified patients with lymphoma 95% of the time and distinguished them from patients with noncancerous causes of enlarged lymph nodes with 92% accuracy.
Despite its success, the test is not intended to replace tissue biopsy at this stage. Instead, Antel sees it as a triage tool that flags patients who should move more quickly to a biopsy and other follow-up testing.
"This would prioritize patients who are at high risk of having lymphoma and need to be expedited for a tissue biopsy," she said. "It doesn't eliminate the need for a biopsy, but it can help us identify those patients much earlier."
In some cases, the blood test may also detect chromosome changes that help doctors to classify lymphoma and guide treatment decisions. It may be especially useful for patients whose enlarged lymph nodes are located deep in the chest or abdomen, where obtaining a tissue biopsy can be more difficult.
Improving access to diagnosis
Although ADLiB was developed with resource-limited settings in mind, Antel said many of the barriers it addresses, including delays in diagnosis and limited access to specialized expertise, also affect patients in high-income countries. Patients in rural communities, smaller hospitals and health systems without lymphoma specialists face the same delays. A blood test that can identify patients at the highest risk could speed referrals, reduce waiting time and connect patients with appropriate care sooner in those settings.
Future studies will focus on refining the algorithm, improving its ability to distinguish lymphoma subtypes and evaluating its performance in larger, more diverse populations.
For Antel, the research is about more than developing a new diagnostic test. It is about making timely cancer diagnosis more accessible, regardless of where patients live.
"Access to specialized pathology expertise isn't universal, and delays in diagnosis still happen," she said. "If we can identify the patients who need urgent evaluation and get them to the right care faster, we have a real opportunity to improve outcomes."
