The impact of preoperative immune checkpoint inhibitors on kidney and bladder cancer surgeries: a systematic review☆

The triple-drug combination DBDx enhances the antitumor efficacy of PD-1 antibody associated with Treg modulation

OBJECTIVE

This study investigated the antitumor efficacy of programmed cell death protein-1 (PD-1) antibody and DBDx, a triple-drug combination of dipyridamole, bestatin, and dexamethasone, and their related immunomodulation.

MATERIALS AND METHODS

Mouse melanoma B16, mouse Lewis lung carcinoma, and mouse breast carcinoma 4T1 were used for evaluating the in vivo therapeutic efficacy of DBDx, PD-1 antibody, and their combination. The peripheral blood and tumor tissues of 4T1 tumor-bearing mice were collected to analyze regulatory T cells and measured using flow cytometry.

RESULTS

The combination of PD-1 antibody and DBDx enhanced the therapeutic efficacy against B16 melanoma. The suppression of tumor growth by PD-1 antibody and DBDx was more significant than that by anti-PD-1 monotherapy. The tumor growth inhibition rates of PD-1 antibody, DBDx, and their combination were 54.0%, 72.4%, and 83.1%, respectively, suggesting a synergistic effect as determined by the coefficient of drug interaction. No significant changes were found in the body weights in all the above groups, indicating that the treated mice tolerated the applied drug doses. Similarly, enhanced therapeutic efficacy of the PD-1 antibody and DBDx combination was observed in murine Lewis lung carcinoma and 4T1 breast cancer models. In 4T1 breast cancer-bearing mice, the immunotherapy-related changes in lymphocytes in peripheral blood and tumor microenvironment were evaluated with flow cytometry. Compared with anti-PD-1 monotherapy, peripheral blood and tumor-infiltrating lymphocytes were found a lower ratio of regulatory T cell (Treg) subset cells and a higher ratio of CD8+/Treg cells.

CONCLUSIONS

The combination of PD-1 antibody and DBDx could achieve enhanced therapeutic antitumor efficacy than anti-PD-1 monotherapy, suggesting potential for using the triple-drug combination DBDx in cancer immunotherapy.

Identification of Immune-Related Genes Associated With Bladder Cancer Based on Immunological Characteristics and Their Correlation With the Prognosis

BACKGROUND

To identify the immune-related genes of bladder cancer (BLCA) based on immunological characteristics and explore their correlation with the prognosis.

METHODS

We downloaded the gene and clinical data of BLCA from the Cancer Genome Atlas (TCGA) as the training group, and obtained immune-related genes from the Immport database. We downloaded GSE31684 and GSE39281 from the Gene Expression Omnibus (GEO) as the external validation group. R (version 4.0.5) and Perl were used to analyze all data.

RESULT

Univariate Cox regression analysis and Lasso regression analysis revealed that 9 prognosis-related immunity genes (PIMGs) of differentially expressed immune genes (DEIGs) were significantly associated with the survival of BLCA patients (p < 0.01), of which 5 genes, including NPR2, PDGFRA, VIM, RBP1, RBP1 and TNC, increased the risk of the prognosis, while the rest, including CD3D, GNLY, LCK, and ZAP70, decreased the risk of the prognosis. Then, we used these genes to establish a prognostic model. We drew receiver operator characteristic (ROC) curves in the training group, and estimated the area under the curve (AUC) of 1-, 3- and 5-year survival for this model, which were 0.688, 0.719, and 0.706, respectively. The accuracy of the prognostic model was verified by the calibration chart. Combining clinical factors, we established a nomogram. The ROC curve in the external validation group showed that the nomogram had a good predictive ability for the survival rate, with a high accuracy, and the AUC values of 1-, 3-, and 5-year survival were 0.744, 0.770, and 0.782, respectively. The calibration chart indicated that the nomogram performed similarly with the ideal model.

CONCLUSION

We had identified nine genes, including PDGFRA, VIM, RBP1, RBP1, TNC, CD3D, GNLY, LCK, and ZAP70, which played important roles in the occurrence and development of BLCA. The prognostic model based on these genes had good accuracy in predicting the OS of patients and might be promising candidates of therapeutic targets. This study may provide a new insight for the diagnosis, treatment and prognosis of BLCA from the perspective of immunology. However, further experimental studies are necessary to reveal the underlying mechanisms by which these genes mediate the progression of BLCA.