Emerging Roles of Circulating Tumor DNA for Increased Precision and Personalization in Radiation Oncology

Emergence of Circulating Tumor DNA as a Precision Biomarker in Lung Cancer Radiation Oncology and Beyond

Circulating tumor DNA (ctDNA) is emerging as a transformative biomarker in the management of non-small cell lung cancer (NSCLC). This review focuses on its role in detecting minimal residual disease (MRD), predicting treatment response, and guiding therapeutic decision-making in radiation oncology and immunotherapy. Key studies demonstrate ctDNA's prognostic value, particularly in identifying relapse risk and refining patient stratification for curative-intent and consolidative treatments. Future research is essential to standardize ctDNA assays, optimize integration into clinical workflows, and expand its clinical utility. This biomarker holds substantial promise by enabling non-invasive, real-time monitoring and improving outcomes for patients with NSCLC and beyond.

Impact of Immune Checkpoint Inhibitors and Local Radical Treatment on Survival Outcomes in Synchronous Oligometastatic NSCLC

Introduction

The impact of an immune checkpoint inhibitor (ICI)-based systemic treatment strategy with or without local radical treatment (LRT) on outcomes for patients with NSCLC and synchronous oligometastatic disease (sOMD) is unknown.

Methods

Multicenter retrospective study including adequately staged patients, with sOMD NSCLC (maximum five metastases in three organs [European Organization for Research and Treatment of Cancer definition]) between January 1, 2015 and December 31, 2022, treated with a first-line ICI-based versus chemotherapy-only regimen. Primary end points were progression-free survival and overall survival (OS) for an ICI-based versus chemotherapy-only strategy. Subgroup analyses were performed for patients who were deemed candidates for LRT in the multidisciplinary meeting and those proceeding to LRT.

Results

A total of 416 patients were included, treated with chemotherapy-ICI (n = 138) or chemotherapy-only (n = 278), 319 out of 416 were deemed candidates by multidisciplinary meetings for LRT, whereas 192 (60%) proceeded to LRT. The median OS was significantly longer in the chemotherapy-ICI compared with the chemotherapy-only group (33.6 versus 15.9 mo, hazard ratio [HR] = 0.5, 95% confidence interval [CI]: 0.4-0.7, p < 0.001), in the subgroups who were candidate for LRT (36.1 versus 17.2 mo, HR = 0.5, 95% CI: 0.4-0.7, p < 0.001) and those proceeding to LRT (not reached versus 23.1 mo, HR = 0.4, 95% CI: 0.2-0.7, p < 0.001). In multivariate analysis, an ICI-based strategy was associated with improved survival in the total group (HR = 0.6, 95% CI: 0.4-0.9, p < 0.001), in those with intention of LRT (HR = 0.6, 95% CI: 0.4-0.9, p = 0.02) and those who proceeded to LRT (HR = 0.3, 95% CI: 0.1-0.6, p = 0.002).

Conclusions

An ICI-based systemic treatment strategy (±LRT) is associated with improved survival compared with chemotherapy-only (±LRT) for patients with sOMD NSCLC. Prospective randomized trial data are necessary to identify patients most likely to benefit from adding LRT.

The Promise of Radiotherapy in High-Risk Non-Muscle Invasive Bladder Cancer

Global shortages, toxicities, and high levels of incomplete treatment with Bacillus Calmette Guerin (BCG) for non-muscle invasive bladder cancer has resulted in increasing interest in alternative treatments. Radiotherapy is not the standard of care for non-muscle invasive bladder cancer (NMIBC), despite being routinely used in muscle invasive bladder cancer. Modern techniques and advances in technology mean that radiotherapy can be delivered with increased precision in reducing normal tissue damage. Developing novel biomarker approaches, together with combination approaches with radiosensitisers and other systemic treatments, means that radiotherapy could offer greater benefits than current treatments with BCG or surgery. This review summarises the current landscape and future potential of radiotherapy for high-risk NMIBC.

Prognostic and Predictive Biomarkers of Oligometastatic NSCLC: New Insights and Clinical Applications

This review discusses the current data on predictive and prognostic biomarkers in oligometastatic NSCLC and discusses whether biomarkers identified in other stages and widespread metastatic disease can be extrapolated to the oligometastatic disease (OMD) setting. Research is underway to explore the prognostic and predictive value of biological attributes of tumor tissue, circulating cells, the tumor microenvironment, and imaging findings as biomarkers of oligometastatic NSCLC. Biomarkers that help define true OMD and predict outcomes are needed for patient selection for oligometastatic treatment, and to avoid futile treatments in patients that will not benefit from locoregional treatment. Nevertheless, these biomarkers are still in the early stages of development and lack prospective validation in clinical trials. Furthermore, the absence of a clear definition of OMD contributes to a heterogeneous study population in which different types of OMD are mixed and treatment strategies are different. Multiple tissue-based, circulating, and imaging features are promising regarding their prognostic and predictive role in NSCLC, but data is still limited and might be biased owing to the inclusion of heterogeneous patient populations. Larger homogeneous and prospective series are needed to assess the prognostic and predictive role of these biomarkers. As obtaining tissue can be difficult and is invasive, the most promising tools for further evaluation are liquid biopsies and imaging-based biomarkers as these can also be used for longitudinal follow-up.

Sensitive MRD Detection from Lymphatic Fluid after Surgery in HPV-Associated Oropharyngeal Cancer

PURPOSE

Our goal was to demonstrate that lymphatic drainage fluid (lymph) has improved sensitivity in quantifying postoperative minimal residual disease (MRD) in locally advanced human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) compared with plasma, and leverage this novel biofluid for patient risk stratification.

EXPERIMENTAL DESIGN

We prospectively collected lymph samples from neck drains of 106 patients with HPV (+) OPSCC, along with 67 matched plasma samples, 24 hours after surgery. PCR and next-generation sequencing were used to quantify cancer-associated cell-free HPV (cf-HPV) and tumor-informed variants in lymph and plasma. Next, lymph cf-HPV and variants were compared with TNM stage, extranodal extension (ENE), and composite definitions of high-risk pathology. We then created a machine learning model, informed by lymph MRD and clinicopathologic features, to compare with progression-free survival (PFS).

RESULTS

Postoperative lymph was enriched with cf-HPV compared with plasma (P < 0.0001) and correlated with pN2 stage (P = 0.003), ENE (P < 0.0001), and trial-defined pathologic risk criteria (mean AUC = 0.78). In addition, the lymph mutation number and variant allele frequency were higher in pN2 ENE (+) necks than in pN1 ENE (+) (P = 0.03, P = 0.02) or pN0-N1 ENE (-) (P = 0.04, P = 0.03, respectively). The lymph MRD-informed risk model demonstrated inferior PFS in high-risk patients (AUC = 0.96, P < 0.0001).

CONCLUSIONS

Variant and cf-HPV quantification, performed in 24-hour postoperative lymph samples, reflects single- and multifeature high-risk pathologic criteria. Incorporating lymphatic MRD and clinicopathologic feature analysis can stratify PFS early after surgery in patients with HPV (+) head and neck cancer. See related commentary by Shannon and Iyer, p. 1223.

Research progress of CTC, ctDNA, and EVs in cancer liquid biopsy

Circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and extracellular vehicles (EVs) have received significant attention in recent times as emerging biomarkers and subjects of transformational studies. The three main branches of liquid biopsy have evolved from the three primary tumor liquid biopsy detection targets-CTC, ctDNA, and EVs-each with distinct benefits. CTCs are derived from circulating cancer cells from the original tumor or metastases and may display global features of the tumor. ctDNA has been extensively analyzed and has been used to aid in the diagnosis, treatment, and prognosis of neoplastic diseases. EVs contain tumor-derived material such as DNA, RNA, proteins, lipids, sugar structures, and metabolites. The three provide different detection contents but have strong complementarity to a certain extent. Even though they have already been employed in several clinical trials, the clinical utility of three biomarkers is still being studied, with promising initial findings. This review thoroughly overviews established and emerging technologies for the isolation, characterization, and content detection of CTC, ctDNA, and EVs. Also discussed were the most recent developments in the study of potential liquid biopsy biomarkers for cancer diagnosis, therapeutic monitoring, and prognosis prediction. These included CTC, ctDNA, and EVs. Finally, the potential and challenges of employing liquid biopsy based on CTC, ctDNA, and EVs for precision medicine were evaluated.

Mathematical modeling of radiotherapy: impact of model selection on estimating minimum radiation dose for tumor control

Introduction

Radiation therapy (RT) is one of the most common anticancer therapies. Yet, current radiation oncology practice does not adapt RT dose for individual patients, despite wide interpatient variability in radiosensitivity and accompanying treatment response. We have previously shown that mechanistic mathematical modeling of tumor volume dynamics can simulate volumetric response to RT for individual patients and estimation personalized RT dose for optimal tumor volume reduction. However, understanding the implications of the choice of the underlying RT response model is critical when calculating personalized RT dose.

Methods

In this study, we evaluate the mathematical implications and biological effects of 2 models of RT response on dose personalization: (1) cytotoxicity to cancer cells that lead to direct tumor volume reduction (DVR) and (2) radiation responses to the tumor microenvironment that lead to tumor carrying capacity reduction (CCR) and subsequent tumor shrinkage. Tumor growth was simulated as logistic growth with pre-treatment dynamics being described in the proliferation saturation index (PSI). The effect of RT was simulated according to each respective model for a standard schedule of fractionated RT with 2 Gy weekday fractions. Parameter sweeps were evaluated for the intrinsic tumor growth rate and the radiosensitivity parameter for both models to observe the qualitative impact of each model parameter. We then calculated the minimum RT dose required for locoregional tumor control (LRC) across all combinations of the full range of radiosensitvity and proliferation saturation values.

Results

Both models estimate that patients with higher radiosensitivity will require a lower RT dose to achieve LRC. However, the two models make opposite estimates on the impact of PSI on the minimum RT dose for LRC: the DVR model estimates that tumors with higher PSI values will require a higher RT dose to achieve LRC, while the CCR model estimates that higher PSI values will require a lower RT dose to achieve LRC.

Discussion

Ultimately, these results show the importance of understanding which model best describes tumor growth and treatment response in a particular setting, before using any such model to make estimates for personalized treatment recommendations.

Radiomics in colorectal cancer

Colorectal cancer (CRC) is a global health challenge with high morbidity and mortality. Radiomics, an emerging field, utilizes quantitative imaging features extracted from medical images for CRC diagnosis, staging, treatment response assessment, and prognostication. This review highlights the potential of radiomics for personalized CRC management. Radiomics enables noninvasive tumor characterization, aiding in early detection and accurate diagnosis, and it can be used to predict tumor stage, lymph node involvement, and prognosis. Furthermore, radiomics guides personalized therapies by assessing the treatment response and identifying patients who could benefit. Challenges include standardizing imaging protocols and analysis techniques. Robust validation frameworks and user‐friendly software are needed for the integration of radiomics into clinical practice. Despite challenges, radiomics offers valuable insights into tumor biology, treatment response, and prognosis in CRC. Overcoming technical and clinical hurdles will unlock its full potential in CRC management.