Gastrointestinal (GI) cancers are a leading cause of cancer morbidity and mortality worldwide. Despite advances in treatment, cancer relapse remains a significant challenge, necessitating novel therapeutic strategies. In this study, we engineered nanobody-based chimeric antigen receptor (CAR) natural killer (NK) cells targeting cadherin 17 (CDH17) for the treatment of GI tumors. In addition, to enhance the efficacy of CAR-NK cells, we also incorporated CV1, a CD47-SIRPα axis inhibitor, to evaluate the anti-tumor effect of this combination. We found that CDH17-CAR-NK cells effectively eliminated GI cancers cells in a CDH17-dependent manner. CDH17-CAR-NK cells also exhibit potent in vivo anti-tumor effects in cancer cell-derived xenograft and patient-derived xenograft mouse models. Additionally, the anti-tumor activity of CDH17-CAR-NK cells is synergistically enhanced by CD47-signal regulatory protein α (SIRPα) axis inhibitor CV1, likely through augmented macrophages activation and an increase in M1-phenotype macrophages in the tumor microenvironment. Collectively, our findings suggest that CDH17-targeting CAR-NK cells are a promising strategy for GI cancers. The combination of CDH17-CAR-NK cells with CV1 emerges as a potential combinatorial approach to overcome the limitations of CAR-NK therapy. Further investigations are warranted to speed up the clinical translation of these findings.

BACKGROUND:After arthroscopic knee surgery, deep vein thrombosis easily occurs. Currently, there were no specific clinical manifestations in deep vein thrombosis, so a fast, convenient and reliable risk assessment tool was needed to evaluate the clinical high-risk groups for prevention and intervention. The effectiveness of Caprini Risk Assessment Scale used in thrombosis risk assessment has been confirmed by a large number of researches, but the current domestic research is less.
OBJECTIVE:To verify the validity of Caprini risk assessment scale in evaluations of high deep venous thrombosis risk patients among knee arthroscopy patients, and to explore effective strategies for prevention of deep vein thrombosis in patients undergoing knee arthroscopic surgery.
METHODS: A case-control study design was used to colect 49 deep vein thrombosis patients admitted to the Department of Orthopedics, Renhe Hospital of Three Gorges University from January 2008 to June 2015 as case group, and randomly selected 98 patients admitted during the same period of non-deep vein thrombosis patients as control group. Caprini risk assessment scale was used to assess risk assessment and risk grading of deep venous thrombosis, and to explore the correlation between risk classification and risk of deep vein thrombosis.
RESULTS AND CONCLUSION: (1) Basic conditions comparison: application time of tourniquet, the proportion of smoking patients, and proportion of deep venous thrombosis and (or) the history of pulmonary thromboembolism were higher in the case group than in the control group (P < 0.05). (2) Caprini score was significantly higher in the case group than in the control group (P < 0.001). In the case group, the proportion of very high risk patients (53%) was highest, folowed by high risk (25%), totaly 78%. In the control group, the proportion of high risk patients (32%) was highest, folowed by low risk (29%). Significant differences in above risk degree analysis were identified between the two groups (P< 0.001). (3) Deep venous thrombosis and (or) the history of pulmonary thromboembolism was positively correlated with Caprini score in the case and control groups (P < 0.05). Caprini score was positively associated with application time of tourniquet in the case group (P< 0.05). (4) Logistic regression analysis of Caprini risk classification and the risk of deep vein thrombosis: with increased caprini risk classification, the risk of deep vein thrombosis increased significantly. The risk of deep venous thrombosis in patients with high risk and very high risk was 2.130 and 11.786 times of patients with low risk, respectively. (5) These results indicate that Caprini risk assessment model can effectively assess the risk of deep vein thrombosis among patients receiving knee arthroscopy.