A multidisciplinary team at the University of California, Los Angeles has now received a major boost in its effort to resolve this diagnostic dilemma. The group, led by Dr. Steven Dubinett, dean of the David Geffen School of Medicine at UCLA, Associate Vice Chancellor for Research, and an investigator at the UCLA Health Jonsson Comprehensive Cancer Center, has been awarded the inaugural Early Detection Award from the LUNGevity Foundation and the Rising Tide Foundation for Clinical Cancer Research. The $1 million award will fund a three-year study aimed at developing a noninvasive approach to determine whether indeterminate pulmonary nodules are cancerous, potentially transforming how clinicians manage one of the most common and consequential findings in modern chest imaging.

The scale of the problem is difficult to overstate. Lung cancer remains the leading cause of cancer-related death in the United States, claiming more lives each year than colon, breast, and prostate cancers combined. The paradox that has long frustrated oncologists is that lung cancer caught early is often curable, yet the very screening technologies designed to catch it early, most notably low-dose CT scanning, generate enormous numbers of ambiguous findings. A nodule of a few millimeters may be nothing at all, or it may be the first visible sign of a malignancy that will spread within months. Current clinical guidelines rely on nodule size, growth rate, and risk models built from population data, but these tools leave a wide gray zone in which neither aggressive intervention nor simple watchful waiting is clearly correct.

The UCLA team’s strategy is to attack that gray zone from two directions simultaneously. The three-year study will combine advanced computational analysis of CT images, a field known as radiomics, with a blood-based test that examines cell-free DNA methylation. Radiomics uses algorithms to extract quantitative patterns from medical images, features such as texture, shape, and density characteristics that are invisible to the human eye but may correlate with underlying tumor biology. DNA methylation analysis, meanwhile, looks for chemical modifications to fragments of DNA shed into the bloodstream, patterns that can differ between cancer-derived DNA and DNA released by healthy tissue. By integrating these two complementary streams of data, the investigators hope to generate a risk assessment that is more precise than either imaging or molecular testing could achieve alone.

This convergence of disciplines is no accident. The research team brings together experts in cancer biology, pulmonary medicine, computational imaging, artificial intelligence, and molecular diagnostics. Alongside Dr. Dubinett, the project includes Dr. Ramin Salehi-Rad, Dr. Xianghong J. Zhou, Dr. William Hsu, and Dr. Linh M. Tran, each contributing a distinct layer of expertise that spans the biological, technological, and clinical dimensions of the problem. The design reflects a growing conviction in cancer research that the hardest problems in early detection, those sitting at the intersection of imaging physics, genomics, and clinical decision-making, are best solved not by isolated laboratories but by teams whose members can translate findings across disciplinary boundaries in real time.

The clinical validation plan is ambitious in scope. The team will test its combined approach in 500 patients receiving care at UCLA Health and Veterans Affairs medical centers, populations that include both community patients and veterans, a group with elevated lung cancer risk. The central question is whether fusing imaging-derived features with blood-based molecular biomarkers can meaningfully improve risk stratification compared with existing methods. Success would mean that clinicians could more accurately identify which patients require prompt evaluation and treatment, while sparing others from biopsies or surgeries that carry real risks of complications, anxiety, and cost. In a health system where millions of nodules are detected annually, even a modest improvement in diagnostic accuracy could prevent tens of thousands of unnecessary invasive procedures each year.

The implications extend beyond the individual patient encounter. Unnecessary biopsies and surgeries represent a substantial burden on the health care system, both financially and in terms of clinical resources. A bronchoscopy or needle biopsy of the lung carries risks including bleeding, collapsed lung, and infection, and surgical resection of a nodule that proves benign exposes patients to the morbidity of major thoracic surgery for no benefit. Conversely, the cost of a false reassurance, a cancer dismissed as benign that later presents at an advanced stage, is measured in lives. A validated noninvasive test that pushes diagnostic confidence in either direction would allow clinicians to allocate invasive resources where they matter most and to monitor low-risk nodules with greater confidence and less patient anxiety.

The award itself marks a notable milestone for the two supporting organizations. The Early Detection Award is the inaugural grant of its kind jointly offered by the LUNGevity Foundation, the largest nonprofit dedicated to lung cancer research and patient support, and the Rising Tide Foundation for Clinical Cancer Research, which funds translational projects designed to move scientific discoveries toward clinical application. By directing the award toward pulmonary nodule assessment, the funders have targeted what many in the field consider the single most consequential bottleneck in lung cancer early detection: the moment after a scan reveals a spot and before anyone knows what it means.

For Dr. Dubinett, the project represents the culmination of years of work at the frontier of lung cancer biology and early detection research. In a statement accompanying the announcement, he emphasized the collaborative character of the effort. “This award recognizes the power of team science and the value of bringing together experts from multiple disciplines to tackle a critical problem in lung cancer detection,” he said. “By integrating advances in imaging science, artificial intelligence, and molecular diagnostics, we hope to improve assessment of pulmonary nodules and help ensure that patients receive the right care at the right time.” The statement captures the underlying philosophy of the project: that no single technology, however sophisticated, will resolve the nodule dilemma on its own, but that a carefully engineered synthesis of imaging and molecular data might.

If the three-year study succeeds, the consequences could ripple well beyond UCLA. A validated imaging-plus-blood test for nodule assessment would fit naturally into existing lung cancer screening programs, which already perform annual low-dose CT scans on millions of high-risk individuals, and could be deployed at the moment of the very first suspicious finding. It could also inform the design of future early-detection tools for other cancers, where similar combinations of radiomic image analysis and liquid biopsy biomarkers are under active investigation. For the 1.5 million Americans who each year face the anxious limbo of an indeterminate lung nodule, the UCLA team’s work offers the prospect of something deceptively simple yet profoundly valuable: a faster, safer, and more accurate answer to the question every one of them asks, is it cancer?

Subject of Research: Noninvasive detection of cancerous indeterminate pulmonary nodules using CT radiomics and blood-based cell-free DNA methylation analysis

Article Title: UCLA research team awarded $1 million to develop new approach for detecting lung cancer

Article References: UCLA research team awarded $1 million to develop new approach for detecting lung cancer. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: lung cancer, early detection, pulmonary nodules, radiomics, cell-free DNA methylation, artificial intelligence, liquid biopsy, CT imaging, UCLA, LUNGevity Foundation, clinical validation, cancer diagnostics