Tumor immunotherapy resistance: Revealing the mechanism of PD-1 / PD-L1-mediated tumor immune escape

Tumor immunotherapy, an innovative anti-cancer therapy, has showcased encouraging outcomes across diverse tumor types. Among these, the PD-1/PD-L1 signaling pathway is a well-known immunological checkpoint, which is significant in the regulation of immune evasion by tumors. Nevertheless, a considerable number of patients develop resistance to anti-PD-1/PD-L1 immunotherapy, rendering it ineffective in the long run. This research focuses on exploring the factors of PD-1/PD-L1-mediated resistance in tumor immunotherapy. Initially, the PD-1/PD-L1 pathway is characterized by its role in facilitating tumor immune evasion, emphasizing its role in autoimmune homeostasis. Next, the primary mechanisms of resistance to PD-1/PD-L1-based immunotherapy are analyzed, including tumor antigen deletion, T cell dysfunction, increased immunosuppressive cells, and alterations in the expression of PD-L1 within tumor cells. The possible ramifications of altered metabolism, microbiota, and DNA methylation on resistance is also described. Finally, possible resolution strategies for dealing with anti-PD-1/PD-L1 immunotherapy resistance are discussed, placing particular emphasis on personalized therapeutic approaches and the exploration of more potent immunotherapy regimens.

Fatty acids metabolism affects the therapeutic effect of anti-PD-1/PD-L1 in tumor immune microenvironment in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is a highly invasive and metastatic subtype of kidney malignancy and is correlated with metabolic reprogramming for adaptation to the tumor microenvironment comprising infiltrated immune cells and immunomodulatory molecules. The role of immune cells in the tumor microenvironment (TME) and their association with abnormal fatty acids metabolism in ccRCC remains poorly understood.

METHOD

RNA-seq and clinical data of KIRC from The Cancer Genome Atlas (TCGA) and E-MTAB-1980 from the ArrayExpress dataset. The Nivolumab group and Everolimus group of the CheckMate 025 study, the Atezolizumab arm of IMmotion150 and the Atezolizumab plus Bevacizumab group of IMmotion151 cohort were obtained for subsequent analysis. After differential expression genes identification, the signature was constructed through univariate Cox proportional hazard regression and simultaneously the least absolute shrinkage and selection operator (Lasso) analysis and the predictive performance of our signature was assessed by using receiver operating characteristic (ROC), Kaplan-Meier (KM) survival analysis, nomogram, drug sensitivity analysis, immunotherapeutic effect analysis and enrichment analysis. Immunohistochemistry (IHC), qPCR and western blot were performed to measure related mRNA or protein expression. Biological features were evaluated by wound healing, cell migration and invasion assays and colony formation test and analyzed using coculture assay and flow cytometry.

RESULTS

Twenty fatty acids metabolism-related mRNA signatures were constructed in TCGA and possessed a strong predictive performance demonstrated through time-dependent ROC and KM survival analysis. Notably, the high-risk group exhibited an impaired response to anti-PD-1/PD-L1 (Programmed death-1 receptor/Programmed death-1 receptor-ligand) therapy compared to the low-risk group. The overall levels of the immune score were higher in the high-risk group. Additionally, drug sensitivity analysis observed that the model could effectively predict efficacy and sensitivity to chemotherapy. Enrichment analysis revealed that the IL6-JAK-STAT3 signaling pathway was a major pathway. IL4I1 could promote ccRCC cells' malignant features through JAK1/STAT3 signaling pathway and M2-like macrophage polarization.

CONCLUSION

The study elucidates that targeting fatty acids metabolism can affect the therapeutic effect of PD-1/PD-L1 in TME and related signal pathways. The model can effectively predict the response to several treatment options, underscoring its potential clinical utility.

Predictive biomarkers of anti-PD-1/PD-L1 therapy in NSCLC

Immunotherapy, especially anti-programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) treatment has significantly improved the survival of non-small cell lung cancer (NSCLC) patients. However, the overall response rate remains unsatisfactory. Many factors affect the outcome of anti-PD-1/PD-L1 treatment, such as PD-L1 expression level, tumor-infiltrating lymphocytes (TILs), tumor mutation burden (TMB), neoantigens, and driver gene mutations. Further exploration of biomarkers would be favorable for the best selection of patients and precisely predict the efficacy of anti-PD-1/PD-L1 treatment. In this review, we summarized the latest advances in this field, and discussed the potential applications of these laboratory findings in the clinic.