In recent years, the three‐dimensional (3D) culture system has emerged as a promising preclinical model for tumor research owing to its ability to replicate the tissue structure and molecular characteristics of solid tumors in vivo. This system offers several advantages, including high throughput, efficiency, and retention of tumor heterogeneity. Traditional Matrigel‐submerged organoid cultures primarily support the long‐term proliferation of epithelial cells. One solution for the exploration of the tumor microenvironment is a reconstitution approach involving the introduction of exogenous cell types, either in dual, triple or even multiple combinations. Another solution is a holistic approach including patient‐derived tumor fragments, air‐liquid interface, suspension 3D culture, and microfluidic tumor‐on‐chip models. Organoid co‐culture models have also gained popularity for studying the tumor microenvironment, evaluating tumor immunotherapy, identifying predictive biomarkers, screening for effective drugs, and modeling infections. By leveraging these 3D culture systems, it is hoped to advance the clinical application of therapeutic approaches and improve patient outcomes.

Senescence is believed to be a pivotal player in the onset and progression of tumors as well as cancer therapy. However, the guiding roles of senescence in clinical outcomes and therapy selection for patients with cancer remain obscure, largely due to the absence of a feasible senescence signature. Here, by integrative analysis of single cell and bulk transcriptome data from multiple datasets of gastric cancer patients, we uncovered senescence as a veiled tumor feature characterized by senescence gene signature enriched, unexpectedly, in the noncancerous cells, and further identified two distinct senescence-associated subtypes based on the unsupervised clustering. Patients with the senescence subtype had higher tumor mutation loads and better prognosis as compared with the aggressive subtype. By the machine learning, we constructed a scoring system termed as senescore based on six signature genes: ADH1B, IL1A, SERPINE1, SPARC, EZH2, and TNFAIP2. Higher senescore demonstrated robustly predictive capability for longer overall and recurrence-free survival in 2290 gastric cancer samples, which was independently validated by the multiplex staining analysis of gastric cancer samples on the tissue microarray. Remarkably, the senescore signature served as a reliable predictor of chemotherapeutic and immunotherapeutic efficacies, with high-senescore patients benefited from immunotherapy, while low-senescore patients were responsive to chemotherapy. Collectively, we report senescence as a heretofore unrecognized hallmark of gastric cancer that impacts patient outcomes and therapeutic efficacy.

Tumor-selective replication herpes simplex virus-based technology significantly improves clinical detection and prognostication of viable circulating tumor cells Tumor-selective replication herpes simplex virus-based technology significantly improves clinical detection and prognostication of viable circulating tumor cells

BACKGROUND: Early diagnosis and treatment are key to the long-term survival of lung cancer patients. Although CT has significantly contributed to the early diagnosis of lung cancer, there are still consequences of excessive or delayed treatment. By improving the sensitivity and specificity of circulating tumor cell (CTC) detection, a solution was proposed for differentiating benign from malignant pulmonary nodules. METHODS: In this study, we used telomerase reverse transcriptase–based (TERT-based) CTC detection (TBCD) to distinguish benign from malignant pulmonary nodules < 2 cm and compared this method with the pathological diagnosis as the gold standard. FlowSight and FISH were used to confirm the CTCs detected by TBCD. RESULTS: Our results suggest that CTCs based on TBCD can be used as independent biomarkers to distinguish benign from malignant nodules and are significantly superior to serum tumor markers. When the detection threshold was 1, the detection sensitivity and specificity of CTC diagnosis were 0.854 and 0.839, respectively. For pulmonary nodules ≤ 1 cm and 1–2 cm, the sensitivity and specificity of CTCs were both higher than 77%. Additionally, the diagnostic ability of CTC-assisted CT was compared by CT detection. The results show that CT combined with CTCs could significantly improve the differentiation ability of benign and malignant nodules in lung nodules < 2 cm and that the sensitivity and specificity could reach 0.899 and 0.839, respectively. CONCLUSION: TBCD can effectively diagnose pulmonary nodules and be used as an effective auxiliary diagnostic scheme for CT diagnosis. FUNDING: National Key Research and Development Project grant nos. 2019YFC1315700 and 2017YFC1308702, CAMS Initiative for Innovative Medicine grant no. 2017-I2M-1-005, and National Natural Science Foundation of China grant no. 81472013.