NEW YORK – A group of researchers at Spain's University of Zaragoza have applied a novel heat-based method called "thermal liquid biopsy" to establish a risk score that they said could predict the presence of and monitor lung cancer in a patient's bloodstream.
The team envisions applying the minimally invasive technology and a predictive risk score to complement standard imaging techniques to screen for a variety of cancers in the clinical space.
While liquid biopsy techniques are starting to be used to diagnose and track a variety of cancers, researchers noted that the tool still needs improvement for continued clinical utility.Common challenges include handling and measuring a biological sample, collecting enough of a liquid sample for measuring a condition, and understanding cell population heterogeneity in solid tumors.
Differential scanning calorimetry (DSC) involves comparing the difference in heat flow between a liquid sample and a reference. Researchers then use TLB, a type of DSC thermogram analysis of a patient's serum sample, to monitor any potential distortion caused by a cancer tumor.
According to Olga Abian, a senior professor at Zaragoza, researchers at the university previously developed TLB in 2008 as an approach to diagnose melanoma patients. However, her team chose to focus on lung cancer as part of a collaboration with oncologists at the Hospital Clínico Universitario Lozano Blesa in Zaragoza.
In a pilot study published last month in Cancers, Abian's team sought to determine TLB's ability to discriminate between healthy controls and lung cancer patients. The researchers first began by recruiting a cohort of 114 lung cancer patients (ranging from Stage II to Stage IV) and a normal cohort of 85 patients without a history of lung cancer.
"It was previously reported that DSC could be applied to identify alterations caused by inflammatory diseases in cancer," Abain explained. "We have expertise in biological calorimetry, and we considered it was worth working toward the implementation of DSC of serum samples in clinical practice."
Abian's team collected about 10 ml of peripheral blood from each patient and control subject for TLB analysis. The group then measured the heat capacity of the samples using a high-sensitivity automated differential scanning microcalorimeter. In order to ensure reproducibility, the team periodically performed replicate experiments and control experiments with commercial human serum on the platform.
According to Abian, researchers can apply TLB to other body samples, including urine, cerebrospinal fluid, synovial fluid, as well as extracts from solid tissues. Once the serum fraction is isolated from the blood, the process roughly takes two to three hours to produce the probability score. In addition, Abian noted that researchers could apply the technology for cancer patient monitoring and surveillance during treatment.
In order to define an accurate risk score to distinguish between healthy controls and lung cancer patients, Abian's team considered four different predictive tools in three models. They eventually selected a model that constructed a probability score from 14 parameters obtained from individual thermograms, which could measure the relative importance of the parameters to classify diseased and healthy individuals.
"According to our prediction method based on the prediction score, a high score indicates no protein-related serum alterations and likely absence of lung cancer, while a low [score] indicates protein-related serum alterations and likely presence of lung cancer," Abian explained.
While the group did not find any significant relationship between the probability score and diagnosis, tumor stage, treatment, and clinical response, tumors determined to be squamous or small cell carcinoma demonstrated very small probability scores compared to adenocarcinoma or other non-small cell tumors.
By applying the third model, Abian noted that the probability score had a 90 percent clinical sensitivity and 92 percent clinical specificity when her team applied the tool to lung cancer. The study authors also noted that neither gender nor age had an effect on the probability score in the healthy and diseased cohorts.
While the type of tumor did not influence the distribution of the probability score, the study authors noted that the scores showed significantly different values for adenocarcinoma and other non-small cell tumors compared to squamous and small-cell tumors
Abian acknowledged that her team encountered several logistical issues during the study while attempting to develop a predictive TLB score for lung cancer. The group needed to figure out how to coordinate the different activities (such as sample extraction, the experimental tests, and statistical analysis) performed by doctors, nurses, technicians, researchers located across Spain.
"To solve that inconvenience and move toward a full implementation of TLB in clinical practices, we have established a dedicated laboratory for advanced diagnostics at the hospital," Abian explained. "All the activities can be carried out under the same roof following a straightforward and agile process."
In addition, Abian noted that one of the study's major limitations was gaining quick access to patients' medical records to classify their stages of cancer and determine how they were treated prior to the study.
Abian's team is now performing additional studies that involve applying TLB on other cancer types. The group is also investigating specific protein biomarkers or changes in protein composition that might affect the probability score. However, Abian noted that while specific biomarkers will add biochemical specificity to the detection process, they may reduce the wide applicability of thermal liquid biopsy.
Abian highlighted that her team's overarching goal is to implement thermal liquid biopsy in the clinical space in order to provide substantial benefits in combination with other current techniques.
"The technique is low-cost, low-risk, and minimally invasive, which will improve patient adherence and quality of life, while reducing mortality rate," Abian said. "We are working on different cancers, including melanoma, lung cancer, gastric cancer, pancreatic cancer, ovarian cancer, and colorectal cancer."
While Abian's group is focusing on cancer-related malignancies, she believes that researchers could potentially apply TLB in other application. The researchers eventually aim to apply the probability score on a cohort of patients suffering from a chronic non-neoplastic disease to explore and compare potential alterations in serum TLB profiles unrelated to cancer.
The study authors believe that future work using the probability score will need to include more patients with Stage I and II lung cancer to determine if the stage is correlated with the intensity of TLB serum proteome alterations and false negatives.
"At this moment, there is no clear connection between tumor stage and alteration of the serum proteome," the study authors said. "It might be possible that early tumor stages are highly metabolically active, resulting in a largely markedly altered serum protein, whereas late stages are less metabolically active, leading to lower levels of serum protein alterations.'
Abian envisions translating TLB to the clinical space through a potential startup based at the University of Zaragoza. The team is now collaborating with several oncologists at local hospitals and with cancer screening programs in Aragon, Spain in order to establish the technique in clinical practice.