Over the past decade, substantial developments have been made in the detection of circulating tumor DNA (ctDNA)—cell‐free DNA (cfDNA) fragments released into the circulation from tumor cells and displaying the genetic alterations of those cells. As such, ctDNA detected in liquid biopsies serves as a powerful tool for cancer patient stratification, therapy guidance, detection of resistance, and relapse monitoring. In this Review, we describe lung cancer diagnosis and monitoring strategies using ctDNA detection technologies and compile recent evidence regarding lung cancer‐related mutation detection in liquid biopsy. We focus not only on epidermal growth factor receptor (EGFR) alterations, but also on significant co‐mutations that shed more light on novel ctDNA‐based liquid biopsy applications. Finally, we discuss future perspectives of early‐cancer detection and clonal hematopoiesis filtering strategies, with possible inclusion of microbiome‐driven liquid biopsy.

Although many studies highlight the implication of circular RNAs (circRNAs) in carcinogenesis and tumor progression, their potential as cancer biomarkers has not yet been fully explored in the clinic due to the limitations of current quantification methods. Here, we report the use of the nCounter platform as a valid technology for the analysis of circRNA expression patterns in non‐small cell lung cancer (NSCLC) specimens. Under this context, our custom‐made circRNA panel was able to detect circRNA expression both in NSCLC cells and formalin‐fixed paraffin‐embedded (FFPE) tissues. CircFUT8 was overexpressed in NSCLC, contrasting with circEPB41L2, circBNC2, and circSOX13 downregulation even at the early stages of the disease. Machine learning (ML) approaches from different paradigms allowed discrimination of NSCLC from nontumor controls (NTCs) with an 8‐circRNA signature. An additional 4‐circRNA signature was able to classify early‐stage NSCLC samples from NTC, reaching a maximum area under the ROC curve (AUC) of 0.981. Our results not only present two circRNA signatures with diagnosis potential but also introduce nCounter processing following ML as a feasible protocol for the study and development of circRNA signatures for NSCLC.

Background: The analysis of liquid biopsies brings new opportunities in the precision oncology field. Under this context, extracellular vesicle circular RNAs (EV-circRNAs) have gained interest as biomarkers for lung cancer (LC) detection. However, standardized and robust protocols need to be developed to boost their potential in the clinical setting. Although nCounter has been used for the analysis of other liquid biopsy substrates and biomarkers, it has never been employed for EV-circRNA analysis of LC patients. Methods: EVs were isolated from early-stage LC patients (n = 36) and controls (n = 30). Different volumes of plasma, together with different number of pre-amplification cycles, were tested to reach the best nCounter outcome. Differential expression analysis of circRNAs was performed, along with the testing of different machine learning (ML) methods for the development of a prognostic signature for LC. Results: A combination of 500 μL of plasma input with 10 cycles of pre-amplification was selected for the rest of the study. Eight circRNAs were found upregulated in LC. Further ML analysis selected a 10-circRNA signature able to discriminate LC from controls with AUC ROC of 0.86. Conclusions: This study validates the use of the nCounter platform for multiplexed EV-circRNA expression studies in LC patient samples, allowing the development of prognostic signatures.

Human tonsils from the nasopharyngeal mucosa mount frontline antibody responses, including IgD secretion by IgD+IgM– plasma cells (IgD-PCs). The developmental origins and functional significance of these IgD responses remain poorly understood. Here, we show that most IgD-PCs clonally emerge from a heterogeneous population of IgD class-switched IgD+IgM– memory (IgD-ME) B cells that reside within the epithelial, subepithelial, and interfollicular areas of the nasopharyngeal mucosa and share transcriptional and phenotypic properties with atypical B cells. These IgD-ME B cells arise from a mutation-intensive pathway that involves integrated innate and adaptive signals and engenders reactivities to respiratory commensal bacteria, common environmental antigens, and allergens. Such reactivities weaken in germline IgD revertants. Thus, the secreted IgD response heavily relies on nasopharyngeal mucosal IgD-ME B cells via a germinal center–imprinted mutational program that presumably enhances mucosal homeostasis and environmental tolerance.

In this issue, Luff et al. (https://doi.org/10.1084/jem.20251308) show that cell-intrinsic signals from TACI drive marginal zone B cell development from T2 B cells through a mechanism involving activation of the PI3K–AKT pathway and inhibition of the FOXO1-KLF2 axis.

The human nasopharyngeal mucosa includes organized lymphoepithelial structures continually engaged in frontline immune responses to aerodigestive antigens. Advancing our understanding of these responses might lead to the development of new strategies for the prevention and treatment of common immune disorders such as allergies. Here we identified a hitherto elusive tonsillar subset of atypical IgD class-switched IgD ⁺ IgM ^- memory (IgD-ME) B cells that were clonally related to IgD ⁺ IgM ⁻ germinal center (IgD-GC) B cells and IgD-secreting IgD ⁺ IgM ⁻ plasma cells (IgD-PCs) but not anergic IgD ⁺ IgM ⁻ B cells. Consistent with their pre-plasmacellular properties, IgD-ME B cells served as preferential precursors of IgD-PCs over IgD-GC B cells. IgD antibodies from IgD ⁺ IgM ⁻ cells acquired reactivity to multiple oral, airborne and commensal antigens through a mutation-dependent pathway involving both innate and adaptive signals. Thus, IgD-ME B cells may form a ready-to-use pre-plasmacellular reservoir for steady-state IgD responses likely aimed at enhancing nasopharyngeal homeostasis. One Sentence Summary: Tonsillar atypical memory B cells form a ready-to-use pre-plasmacellular repertoire for IgD responses to common aerodigestive antigens.