New 3D Fluorescence Imaging Technique Maps PD-L1 in Lung Cancer to Gauge Immunotherapy Response

Lung cancer remains one of the deadliest malignancies worldwide, and immune checkpoint inhibitors that block the PD-1/PD-L1 pathway have transformed its treatment. Yet deciding which patients will actually benefit from these therapies still depends largely on a single number: the PD-L1 score obtained from a small biopsy sample analyzed by immunohistochemistry. That number carries a fundamental flaw. Tumors are not uniform blobs; PD-L1 expression can vary dramatically from one region of a tumor to another and from the primary tumor to its draining lymph nodes, and it can shift over time as treatment alters the tumor microenvironment. A needle sample taken from one spot at one moment may therefore misrepresent the biology that matters. An exploratory study published in BMC Medicine by Kongxu Dai, Jiaxuan Wen, Haozhuo Guo and colleagues from Peking University People’s Hospital and the Institute of Automation of the Chinese Academy of Sciences now presents a three-dimensional imaging approach designed to quantify PD-L1 across entire tumors and lymph nodes, offering a richer picture of the target that immunotherapies aim to hit.

The technology at the heart of the study is called NIR-II fluorescence molecular tomography integrated with X-ray computed tomography, or NIR-II FMT-XCT. Fluorescence molecular tomography is an optical imaging technique in which a fluorescent probe is delivered into the body and light emitted from the probe is collected at the tissue surface. Mathematical reconstruction algorithms then solve an inverse problem to localize and quantify the fluorescence source deep inside the tissue. The key innovation here is the use of the second near-infrared window, spanning roughly 1,000 to 1,700 nanometers, where biological tissues scatter and absorb far less light than in the conventional first near-infrared window. Lower scattering means photons can travel farther and more predictably through tissue, which translates into better penetration depth and higher contrast. In head-to-head comparisons reported in the paper, three-dimensional NIR-II FMT achieved a signal-to-background ratio 1.73 plus or minus 0.27 times higher than three-dimensional NIR-I FMT, a substantial gain in imaging contrast that matters enormously when the target is a faintly expressed protein buried inside dense tumor tissue.

To make PD-L1 visible, the team engineered a targeted probe called aPD-L1-ICG, which links an anti-PD-L1 antibody to indocyanine green, a clinically approved fluorescent dye already used in humans for angiography and other applications. Once injected, the antibody portion seeks out and binds PD-L1 molecules on tumor cells and immune cells, carrying the fluorescent tag to sites of expression. The XCT component of the hybrid system supplies anatomical context: it images the structural skeleton of the chest and nodes, allowing the optical signal to be mapped onto defined three-dimensional regions of interest. The reconstruction pipeline incorporated a standardized imaging space-based elastic net method with an alternating direction method of multipliers solver, designed to stabilize the notoriously ill-posed fluorescence reconstruction problem and produce quantitative, reproducible measurements rather than vague blobs of brightness.

The researchers validated the platform across a demanding spectrum of models and specimens. They began with lung cancer cell lines, then moved to patient-derived xenografts, in which fragments of human lung tumors are grown in immunocompromised mice, preserving much of the heterogeneity of the original cancer. They then applied the technique to resected human lung tumors and lymph nodes obtained from patients. Throughout this progression, the reconstructed three-dimensional fluorescence signals tracked with PD-L1 immunohistochemistry, the current clinical gold standard, but with an important added dimension: the imaging revealed spatial variation of PD-L1 within tumors and within lymph nodes, information that a slide-based method simply cannot capture because it samples only a thin plane of the specimen.

The most clinically consequential part of the study involved 28 patients with lung cancer who had received neoadjuvant chemoimmunotherapy, meaning chemotherapy plus immune checkpoint blockade given before surgery to shrink the tumor and prime the immune system. After treatment, when surgical specimens were resected, the team performed ex vivo NIR-II FMT measurements on the tumors and compared the resulting signal-to-background ratios with two benchmarks: the radiographic response seen on CT scans before surgery, and the pathological response measured in the resected tissue as the proportion of residual viable tumor cells. The results were striking. Tumor NIR-II FMT signal-to-background ratio correlated with CT-based tumor shrinkage with a correlation coefficient of 0.6076 and a P value below 0.001, indicating a moderately strong and highly statistically significant association between the molecular signal and the anatomical response to therapy.

Even more provocative was the comparison with conventional PD-L1 immunohistochemistry. The ex vivo NIR-II FMT signal-to-background ratio was inversely associated with the residual viable tumor proportion, with a Pearson correlation coefficient of minus 0.5332 and a P value of 0.0035, meaning patients whose tumors showed stronger PD-L1-targeted fluorescence after treatment tended to have less surviving tumor tissue. By contrast, tumor-cell PD-L1 expression measured by standard immunohistochemistry showed no significant association with residual viable tumor, with a coefficient of minus 0.1119 and a P value of 0.571. In other words, the three-dimensional whole-tissue fluorescence measurement captured information about therapeutic response that the conventional two-dimensional biomarker assessment missed, presumably because it integrates expression across the entire specimen rather than averaging over selected microscopic fields.

The biological rationale for this advantage is worth unpacking. PD-L1 is not a static property of tumor cells alone; it is dynamically induced by inflammatory signaling, particularly interferon gamma released by activated T cells. When checkpoint blockade works, T cells flood into the tumor, and the resulting immune activity can actually drive PD-L1 expression upward on surviving tumor and immune cells. A high post-treatment PD-L1 signal measured across the whole tumor volume may therefore reflect an engaged, drug-perturbed immune microenvironment rather than simply more target protein, and the correlation with tumor shrinkage and low residual disease is consistent with that interpretation. Immunohistochemistry, by contrast, examines a limited tissue plane and reports tumor proportion scores that may be discordant with deeper regions of the same tumor, especially after treatment has reshaped the tissue architecture.

The authors are careful, appropriately so, about what the study does and does not prove. All patient findings are retrospective and exploratory, based on post-treatment specimens measured after surgical resection. The associations support further prospective investigation but do not establish pretreatment predictive utility, meaning the technique has not yet been shown to identify which untreated patients will respond, nor do they establish clinical net benefit, meaning no evidence yet exists that using this imaging to guide decisions improves outcomes. Building that evidence will require prospective studies in which the fluorescence signal is measured before or early during therapy and used, ideally in a controlled trial design, to inform or stratify treatment. The regulatory and logistical path is also nontrivial: although indocyanine green is clinically established, the antibody-dye conjugate would need to be produced under good manufacturing practice conditions, validated for safety, biodistribution and specificity, and cleared through the appropriate regulatory frameworks before any routine clinical use.

Nevertheless, the technical achievement is considerable. By combining the deep-tissue advantages of second near-infrared fluorescence with the anatomical precision of X-ray CT and a robust reconstruction algorithm, the team has demonstrated a platform that turns a qualitative biomarker slide into a quantitative, three-dimensional molecular map. The intraclass correlation analyses and comparisons across preclinical models, xenografts and human resections described in the study suggest the measurements are reproducible enough to support larger trials. For a field in which roughly half of PD-L1-positive patients do not respond to checkpoint inhibitors and some PD-L1-negative patients respond unexpectedly, any tool that reads the tumor more completely has obvious appeal. If prospective validation confirms the promise of this exploratory work, surgeons and oncologists may one day assess not a single biopsy of a tumor but the whole tumor and its draining lymph nodes in three dimensions, bringing immunotherapy selection closer to the true, messy biology of the disease it is meant to conquer.

Subject of Research: Three-dimensional NIR-II fluorescence molecular tomography with X-ray CT for quantitative PD-L1 imaging in lung cancer and tumor-draining lymph nodes to assess immunotherapy efficacy

Article Title: 3D NIR-II FMT-XCT imaging for quantitative analysis of PD-L1 expression in lung cancer and tumor-draining lymph nodes facilitating immunotherapy efficacy assessment: an exploratory study

Article References: 3D NIR-II FMT-XCT imaging for quantitative analysis of PD-L1 expression in lung cancer and tumor-draining lymph nodes facilitating immunotherapy efficacy assessment: an exploratory study. (n.d.). https://doi.org/10.1186/s12916-026-05200-4

Image Credits: AI Generated

DOI: 10.1186/s12916-026-05200-4

Keywords: PD-L1, lung cancer, immunotherapy, fluorescence molecular tomography, NIR-II imaging, X-ray computed tomography, molecular imaging, immune checkpoint inhibitors, tumor-draining lymph nodes, neoadjuvant chemoimmunotherapy, biomarkers, precision medicine