Early detection plays a critical role in mitigating mortality rates linked to gastric cancer. However, current clinical screening methods exhibit suboptimal efficacy. Methylation alterations identified from cell‐free DNA (cfDNA) present a promising biomarker for early cancer detection. Our study focused on identifying gastric cancer‐specific markers from cfDNA methylation to facilitate early detection. We enrolled 150 gastric cancer patients and 100 healthy controls in this study, and undertook genome‐wide methylation profiling of cfDNA using cell‐free methylated DNA immunoprecipitation and high‐throughput sequencing. We identified 21 differentially methylated regions (DMRs) between the gastric tumor and nontumor groups using multiple algorithms. Subsequently, using the 21 DMRs, we developed a gastric cancer detection model by random forest algorithm in the discovery set, and validated the model in an independent set. The model was able to accurately discriminate gastric cancer with a sensitivity and specificity of 93.90% and 95.15% in the discovery set, respectively, and 88.38% and 94.23% in the validation set, respectively. These results underscore the efficacy and accuracy of cfDNA‐derived methylation markers in distinguishing early stage gastric cancer. This study highlighted the significance of cfDNA methylation alterations in early gastric cancer detection.

Over the past decades, low‐dose computed tomography (LD‐CT) screening has been widely used for the early detection of lung cancer. Increasing numbers of indeterminate pulmonary nodules are now being discovered. However, it remains challenging to distinguish malignant from benign pulmonary nodules, especially those considered to be small or ground‐glass (GGN) nodules. Liquid biopsies have been successfully applied in the diagnosis of advanced lung cancer, and the potential value for early detection of lung cancer has made great progress. Recent studies have demonstrated the value of various blood‐based tumor biomarkers in determining the nature of pulmonary nodules, including cell‐free DNA (cfDNA), microRNAs (miRNAs), circulating tumor cells (CTCs) and tumor‐associated autoantibodies (AAbs). In this review, we summarize the latest progress of liquid biopsies, and their potential applications and challenges in the diagnosis of malignant pulmonary nodules.

Background: Tumor mutational burden (TMB) is one of the most significant predictive biomarkers of immunotherapy efficacy in non-small cell lung cancer (NSCLC). Radiomics allows high-throughput extraction and analysis of advanced and quantitative medical imaging features. This study develops and validates a radiomic model for predicting TMB level and the response to immunotherapy based on CT features in NSCLC. Method: Pre-operative chest CT images of 127 patients with NSCLC were retrospectively studied. The 3D-Slicer software was used to outline the region of interest and extract features from the CT images. Radiomics prediction model was constructed by LASSO and multiple logistic regression in a training dataset. The model was validated by receiver operating characteristic (ROC) curves and calibration curves using external datasets. Decision curve analysis was used to assess the value of the model for clinical application. Results: A total of 1037 radiomic features were extracted from the CT images of NSCLC patients from TCGA. LASSO regression selected three radiomics features (Flatness, Autocorrelation and Minimum), which were associated with TMB level in NSCLC. A TMB prediction model consisting of 3 radiomic features was constructed by multiple logistic regression. The area under the curve (AUC) value in the TCGA training dataset was 0.816 (95% CI: 0.7109–0.9203) for predicting TMB level in NSCLC. The AUC value in external validation dataset I was 0.775 (95% CI: 0.5528–0.9972) for predicting TMB level in NSCLC, and the AUC value in external validation dataset II was 0.762 (95% CI: 0.5669–0.9569) for predicting the efficacy of immunotherapy in NSCLC. Conclusion: The model based on CT radiomic features helps to achieve cost effective improvement in TMB classification and precise immunotherapy treatment of NSCLC patients.

Cell‐free methylated DNA immunoprecipitation and high‐throughput sequencing (cfMeDIP‐seq) is a new bisulfite‐free technique, which can detect the whole‐genome methylation of blood cell‐free DNA (cfDNA). Using this technique, we identified differentially methylated regions (DMR) of cfDNA between lung tumors and normal controls. Based on the top 300 DMR, we built a random forest prediction model, which was able to distinguish malignant lung tumors from normal controls with high sensitivity and specificity of 91.0% and 93.3% (AUROC curve of 0.963). In summary, we reported a non–invasive prediction model that had good ability to distinguish malignant pulmonary nodules.

Small cell lung cancer (SCLC) is a malignant neuroendocrine tumor with very high mortality. Effective new therapy for advanced SCLC patients is urgently needed. By screening a FDA-approved drug library, we identified a cardiac glycoside (CG), namely digoxin (an inhibitor of cellular Na⁺/K⁺ ATPase pump), which was highly effective in inhibiting SCLC cell growth. Intriguing findings showed that NaCl supplement markedly enhanced the anti-tumor activities of digoxin in both in vitro and in vivo models of SCLC. Subsequent analysis revealed that this novel combination of digoxin/NaCl caused an up-regulation of intracellular Na⁺ and Ca²⁺ levels with an induction of higher resting membrane potential of SCLC cells. We also found that this combination lead to morphological shrinking of SCLC cells, together with high levels of cytochrome C release. Lastly, our data revealed that NaCl supplement was able to induce the expression of ATP1A1 (a Na⁺/K⁺ ATPase subunit), in which contributes directly to the increased sensitivity of SCLC cells to digoxin. Thus, this is the first demonstration that NaCl is a potent supplement necessitating superior anti-cancer effects of digoxin for SCLC. Further, our study suggests that digoxin treatment could need to be combined with NaCl supplement in future clinical trial of SCLC, particularly where low Na⁺ is often present in SCLC patients.