Circulating tumor DNA (ctDNA) has emerged as a pivotal biomarker in oncology, offering insights into tumor dynamics and treatment responses. Cohen et al. provide practical recommendations for the clinical utility of ctDNA, emphasizing its strengths and limitations in various treatment settings, particularly for solid tumors (ref: Cohen doi.org/10.1038/s41586-023-06225-y/). In a comprehensive analysis of whole-genome sequencing data from the Pan-Cancer Analysis of Whole Genomes (PCAWG) study, Bruhm et al. identified distinct mutation profiles in cell-free DNA, demonstrating a machine-learning model that achieved over 90% detection accuracy for early-stage lung cancer (ref: Bruhm doi.org/10.1038/s41588-023-01446-3/). The IMvigor010 trial by Powles et al. highlighted that ctDNA positivity correlates with overall survival (OS) outcomes in muscle-invasive urothelial carcinoma, showcasing that ctDNA clearance after treatment with atezolizumab is associated with improved OS (ref: Powles doi.org/10.1016/j.eururo.2023.06.007/). Furthermore, García-Pardo et al. demonstrated that ctDNA testing prior to tissue diagnosis can significantly reduce time to treatment in advanced non-small cell lung cancer (NSCLC) patients (ref: García-Pardo doi.org/10.1001/jamanetworkopen.2023.25332/). Brenne et al. reported that ctDNA markers could detect colorectal cancer up to two years before clinical diagnosis, suggesting a potential role in early screening programs (ref: Brenne doi.org/10.1038/s41416-023-02337-4/). Tsai et al. explored the emergence of RAS mutations during cetuximab treatment, finding a 9.3% detection rate of RAS mutations in patients initially classified as RAS wild-type (ref: Tsai doi.org/10.1038/s41416-023-02366-z/). Collectively, these studies underscore the transformative potential of ctDNA in cancer diagnosis, monitoring, and treatment decision-making.

Liquid biopsy technologies are revolutionizing cancer diagnostics and monitoring by enabling non-invasive sampling of biomarkers. Wang et al. introduced origamiFISH, a universal method for the single-molecule visualization of DNA origami nanostructures in biological samples, which could enhance the detection of cancer biomarkers (ref: Wang doi.org/10.1038/s41565-023-01449-5/). Genco et al. developed a portable bioelectronic sensing array for early diagnosis of pancreatic cancer precursors, achieving a sensitivity of up to 80% in a cohort of 47 patients (ref: Genco doi.org/10.1002/adma.202304102/). Ren et al. presented a multi-body biomarker entrapment system that improves the ultrasensitive identification of biomarkers in biofluids, addressing the limitations of traditional diagnostic methods (ref: Ren doi.org/10.1002/adma.202304119/). Additionally, Wang et al. reported on DNA-programmed stem cell niches that facilitate intercellular communication via extracellular vesicles, which could have implications for targeted therapies (ref: Wang doi.org/10.1002/adma.202302323/). The study by Pearsall et al. on lineage plasticity in small cell lung cancer (SCLC) highlights the role of circulating tumor cells in metastasis, emphasizing the need for innovative liquid biopsy approaches to monitor tumor evolution (ref: Pearsall doi.org/10.1016/j.jtho.2023.07.012/). These advancements illustrate the potential of liquid biopsy technologies to enhance early detection, treatment monitoring, and personalized medicine in oncology.

The landscape of cancer detection and monitoring is rapidly evolving, with innovative methodologies enhancing diagnostic accuracy. Pooler et al. examined the growth rates and histopathological outcomes of small colorectal polyps, revealing that 67.8% of patients undergoing immediate polypectomy had adenomas, with a significant correlation between polyp growth and advanced histology (ref: Pooler doi.org/10.1136/gutjnl-2022-326970/). Hunt et al. introduced a rapid cell-free expression platform for antibody discovery, streamlining the identification of potent antibodies against SARS-CoV-2, which could be adapted for cancer diagnostics (ref: Hunt doi.org/10.1038/s41467-023-38965-w/). Sikosek et al. reported on the early detection of lung cancer using small RNAs, achieving a median receiver-operating characteristic area under the curve of 0.86, highlighting the potential for stage-dependent diagnostic models (ref: Sikosek doi.org/10.1016/j.jtho.2023.07.005/). Abbas et al. explored mutational signature dynamics in esophageal adenocarcinoma, providing insights into the progression from pre-cancerous lesions to advanced disease, which could inform monitoring strategies (ref: Abbas doi.org/10.1038/s41467-023-39957-6/). Collectively, these studies underscore the importance of integrating novel detection methods and biomarkers to improve cancer diagnosis and monitoring.

The tumor microenvironment (TME) plays a critical role in cancer progression and treatment response, influencing immune dynamics and therapeutic outcomes. Kresovich et al. investigated changes in methylation-based aging in breast cancer survivors, revealing accelerated biological aging in those diagnosed with cancer, which may impact immune function and disease outcomes (ref: Kresovich doi.org/10.1093/jnci/). Wu et al. examined the intratumoral microbiota composition in esophageal squamous cell carcinoma (ESCC), finding that specific microbial signatures predicted responses to chemoimmunotherapy, suggesting a potential avenue for enhancing treatment efficacy (ref: Wu doi.org/10.1158/0008-5472.CAN-22-2593/). Mentis et al. highlighted that mutations traditionally associated with cancer may also occur in healthy tissues, prompting a reevaluation of their diagnostic significance and implications for immune response (ref: Mentis doi.org/10.1016/j.molmed.2023.06.004/). Peng et al. focused on the cellular dynamics within the TME of non-small cell lung cancer (NSCLC), revealing significant molecular and functional changes that could inform immunotherapeutic strategies (ref: Peng doi.org/10.1002/ctm2.1340/). These findings emphasize the intricate interplay between the TME and immune responses, underscoring the need for targeted approaches in cancer therapy.

Genomic and transcriptomic profiling are essential for understanding cancer biology and developing targeted therapies. Abbas et al. explored mutational signature dynamics in esophageal adenocarcinoma, analyzing 997 cases across various stages and providing insights into the mutagenic processes that drive tumorigenesis (ref: Abbas doi.org/10.1038/s41467-023-39957-6/). Sikosek et al. reported on the early detection of lung cancer using small RNAs, demonstrating a robust diagnostic model with stage-dependent performance, which could enhance early intervention strategies (ref: Sikosek doi.org/10.1016/j.jtho.2023.07.005/). Rochman et al. conducted a proteomic analysis of esophageal biopsies, identifying 402 differentially expressed proteins associated with eosinophilic esophagitis, which may have implications for understanding cancer-related inflammation (ref: Rochman doi.org/10.1172/jci.insight.172143/). Cheng et al. developed a nanomedicine-in-hydrogel approach targeting lymph nodes for systemic immunosuppression, highlighting the role of cell-free DNA in immune modulation (ref: Cheng doi.org/10.1002/advs.202302575/). These studies illustrate the critical role of genomic and transcriptomic profiling in elucidating cancer mechanisms and guiding therapeutic decisions.

Advancements in cancer treatment and therapeutics are increasingly focused on innovative strategies to enhance efficacy and safety. Spicer et al. reported on a Phase I trial of the IgE antibody MOv18, demonstrating its safety and anti-tumor activity in patients with advanced solid tumors expressing folate receptor-alpha, suggesting a promising new class of therapeutic antibodies (ref: Spicer doi.org/10.1038/s41467-023-39679-9/). Gvozdenovic et al. highlighted the role of hyposialylation in circulating tumor cell clusters, which contributes to therapy resistance and metastatic spread in breast cancer, emphasizing the need for targeted interventions to overcome such resistance (ref: Gvozdenovic doi.org/10.1158/0008-5472.CAN-23-1978/). Wu et al. investigated the impact of intratumoral microbiota on the response to chemoimmunotherapy in ESCC, revealing that specific microbial profiles can predict treatment efficacy, thus opening avenues for microbiome-based therapeutic strategies (ref: Wu doi.org/10.1158/0008-5472.CAN-22-2593/). Jo et al. focused on high-throughput profiling of extracellular vesicles for early ovarian cancer detection, highlighting the potential of liquid biopsy approaches in identifying early-stage disease (ref: Jo doi.org/10.1002/advs.202301930/). Collectively, these studies underscore the importance of innovative therapeutic strategies and the integration of biological insights to improve cancer treatment outcomes.

The identification of biomarkers is crucial for disease prediction and personalized treatment strategies in oncology. Huang et al. explored the role of cell-free mitochondrial DNA (cf-mtDNA) in sepsis-associated acute lung injury, revealing its potential as a therapeutic target for modulating inflammatory responses (ref: Huang doi.org/10.1002/advs.202301635/). Gvozdenovic et al. discussed the implications of hyposialylation in circulating tumor cell clusters, which enhances metastatic potential and therapy resistance, highlighting the need for biomarkers that can predict treatment outcomes (ref: Gvozdenovic doi.org/10.1158/0008-5472.CAN-23-1978/). Cheng et al. presented a novel nanomedicine approach targeting lymph nodes for systemic immunosuppression, emphasizing the role of cfDNA in immune modulation and its potential as a biomarker for treatment response (ref: Cheng doi.org/10.1002/advs.202302575/). Rochman et al. identified differentially expressed proteins in eosinophilic esophagitis, which may serve as biomarkers for understanding disease mechanisms and guiding therapeutic interventions (ref: Rochman doi.org/10.1172/jci.insight.172143/). These findings highlight the critical role of biomarkers in enhancing disease prediction and guiding personalized treatment approaches.

Emerging technologies are transforming cancer research by enabling novel approaches to diagnostics, treatment, and understanding tumor biology. Wang et al. introduced origamiFISH, a label-free method for single-molecule visualization of DNA origami nanostructures, which could enhance biomarker detection in cancer (ref: Wang doi.org/10.1038/s41565-023-01449-5/). Ren et al. developed a bionic biomarker entrapment system that improves the ultrasensitive identification of biomarkers in biofluids, addressing challenges in point-of-care applications (ref: Ren doi.org/10.1002/adma.202304119/). Wang et al. also reported on DNA-programmed stem cell niches that facilitate intercellular communication via extracellular vesicles, which could have implications for targeted therapies (ref: Wang doi.org/10.1002/adma.202302323/). Pearsall et al. investigated lineage plasticity in small cell lung cancer, revealing mechanisms that contribute to metastasis and therapy resistance, underscoring the need for innovative approaches to monitor tumor evolution (ref: Pearsall doi.org/10.1016/j.jtho.2023.07.012/). These advancements illustrate the potential of emerging technologies to enhance our understanding of cancer and improve diagnostic and therapeutic strategies.