The efficacy of CAR-T cells for solid tumors is unsatisfactory. EpCAM is a biomarker of epithelial tumors, but the clinical feasibility of CAR-T therapy targeting EpCAM is lacking. Here, we report pre- and clinical investigations of EpCAM–CAR-T cells for solid tumors. We demonstrated that EpCAM–CAR-T cells costimulated by Dectin-1 exhibited robust antitumor activity without adverse effects in xenograft mouse models and EpCAM-humanized mice. Notably, in clinical trials for epithelial tumors (NCT02915445), 6 (50%) of the 12 enrolled patients experienced self-remitted grade 1/2 toxicities, 1 patient (8.3%) experienced reversible grade 3 leukopenia, and no higher-grade toxicity reported. Efficacy analysis determined two patients as partial response. Three patients showed >23 months of progression-free survival, among whom one patient experienced 2-year progress-free survival with detectable CAR-T cells 200 days after infusion. These data demonstrate the feasibility and tolerability of EpCAM–CAR-T therapy.

Background: Tumor-infiltrating lymphocytes (TILs) have demonstrated potential as prognostic biomarkers across various cancer types. However, their prognostic implications in non-small cell lung cancer (NSCLC) remain ambiguous.Methods: An exhaustive electronic search was executed across the Pubmed, EMBASE, Web of Science, and Cochrane Library databases to locate relevant studies published up until December 19, 2023. Studies were eligible if they assessed the association between TILs and overall survival (OS) and disease-free survival (DFS) in NSCLC patients. The OS and DFS were subsequently extracted for analysis. The prognostic significance of TILs was evaluated by calculating the Pooled Hazard Ratios (HRs) and their corresponding 95% Confidence Intervals (CIs).Results: The meta-analysis incorporated 60 studies, which collectively included 15829 NSCLC patients. The collective analysis indicated that NSCLC patients exhibiting TILs infiltration demonstrated a significantly improved OS(HR: 0.67; 95%CI: 0.55-0.81). Subgroup analyses, based on TIL subtypes (CD8+, CD3+ and CD4+), consistently revealed a favorable prognostic impact on OS. However, it was observed that FOXP3+ was correlated with a poor OS (HR: 1.35; 95% CI: 0.87-2.11).Conclusion: This comprehensive systematic review and meta-analysis substantiate the prognostic significance of TILs in patients diagnosed with NSCLC. Notably, elevated TILs infiltration correlates with a favorable prognosis, particularly among CD8+, CD3+ and CD4+ subtypes.Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023468089 PROSPERO, identifier CRD42023468089.

Cytokeratin fraction 21–1 (CYFRA 21–1) has been widely studied as an important biomarker in non-small cell lung cancer for both diagnosis and prognosis. Many studies have also assessed the clinical applications of CYFRA 21–1 in head and neck cancer, but the diagnostic and prognostic values of CYFRA 21–1 are not yet fully established. This pooled analysis aims at evaluating the diagnostic accuracy and prognostic applications of CYFRA 21–1 in patients with head and neck cancer. A systematic retrieval of literatures was conducted without time or language restrictions by searching PubMed, EMBASE, Web of Science, Cochrane library and China National Knowledge Infrastructure. Twenty studies were eligible for systematic review, of which 14 conformed for diagnostic analysis and 7 for prognostic analysis. The pooled sensitivity and specificity of CYFRA 21–1 analysis were 0.53 (95% CI: 0.39–0.67) and 0.97 (95% CI: 0.93–0.99), respectively. A high level of CYFRA 21–1 was significantly correlated with shorter overall survival (HR 1.33, 95% CI: 1.13–1.56) and disease-free survival (HR 1.48; 95%CI: 1.10–1.97). Current evidence indicates that the level of CYFRA 21–1 in the serum could be used as an indicator for monitoring tumor status and evaluating its curative effects.

Adverse effects and multidrug resistance remain significant obstacles in conventional cancer therapy. Nanomedicines, with their intrinsic properties such as nano-sized dimensions and tunable surface characteristics, have the potential to mitigate the side effects of traditional cancer treatments. While nanomaterials have been widely applied in cancer treatment, challenges such as low targeting efficiency and poor tumor penetration persist. Recent research has shown that anaerobic bacteria exhibit high selectivity for primary tumors and metastatic cancers, offering good safety and superior tumor penetration capabilities. This suggests that combining nanomaterials with bacteria could complement their respective limitations, opening vast potential applications in cancer therapy. The use of bacteria in combination with nanomaterials for anticancer treatments, including chemotherapy, radiotherapy, and photothermal/photodynamic therapy, has contributed to the rapid development of the field of bacterial oncology treatments. This review explores the mechanisms of bacterial tumor targeting and summarizes strategies for synthesizing bacterial-nanomaterial and their application in cancer therapy. The combination of bacterial-nanomaterial hybrids with modern therapeutic approaches represents a promising avenue for future cancer treatment research, with the potential to improve treatment outcomes for cancer patients.

We aimed to validate the accuracy and clinical value of a novel semisupervised learning framework for gross tumor volume (GTV) delineation in nasopharyngeal carcinoma. Two hundred fifty-eight patients with magnetic resonance imaging data sets were divided into training (n = 180), validation (n = 20), and testing (n = 58) cohorts. Ground truth contours of nasopharynx GTV (GTVnx) and node GTV (GTVnd) were manually delineated by 2 experienced radiation oncologists. Twenty percent (n = 36) labeled and 80% (n = 144) unlabeled images were used to train the model, producing model-generated contours for patients from the testing cohort. Nine experienced experts were invited to revise model-generated GTV in 20 randomly selected patients from the testing cohort. Six junior oncologists were asked to delineate GTV in 12 randomly selected patients from the testing cohort without and with the assistance of the model, and revision degrees were compared under these 2 modes. The Dice similarity coefficient (DSC) was used to quantify the accuracy of the model. The model-generated contours showed a high accuracy compared with ground truth contours, with an average DSC score of 0.83 and 0.80 for GTVnx and GTVnd, respectively. There was no significant difference in DSC score between T1-2 and T3-4 patients (0.81 vs 0.83; P = .223), or between N1-2 and N3 patients (0.80 vs 0.79; P = .807). The mean revision degree was lower than 10% in 19 (95%) patients for GTVnx and in 16 (80%) patients for GTVnd. With assistance of the model, the mean revision degree for GTVnx and GTVnd by junior oncologists was reduced from 25.63% to 7.75% and from 21.38% to 14.44%, respectively. Meanwhile, the delineating efficiency was improved by over 60%. The proposed semisupervised learning-based model showed a high accuracy for delineating GTV of nasopharyngeal carcinoma. It was clinically applicable and could assist junior oncologists to improve GTV contouring accuracy and save contouring time.