Mechanisms of Cancer Resistance to Immunotherapy

Abstract

Over the last decade, based on the extensive development of preclinical animal studies and clinical trials, the efficacy, and mechanisms of immunotherapy have been fully explored. Significant and lasting clinical responses with immunotherapy provide a new breakthrough treatment for a variety of refractory cancer histologies, which gradually change the treatment pattern of tumors. However, although immune checkpoint inhibitor drugs are promising for achieving longer-term efficacy, their benefits in the overall population are still very low, such as low frequency of response in some common tumor types such as breast and prostate, and heterogeneity in the degree of response among different tumor lesions in the same patient, making immunotherapy with many limitations and challenges. Most patients do not respond to immunotherapy or inevitably develop resistance to treatment after a period of treatment, manifesting with primary resistance or acquired resistance who initially respond to treatment. The mechanisms of tumor immune resistance are very complex and involve multiple aspects such as genes, metabolism, inflammation, and abnormal neovascularization. Currently, many mechanisms of immunotherapy resistance have been characterized, and more continue to be uncovered. These efforts can improve the quality of medical care for cancer diagnosis and treatment, which improve the quality of life of patients, and finally lead to accurate individualized treatment. This review discusses mechanisms of cancer immunotherapy resistance including tumor-intrinsic factors and tumor-extrinsic factors.

Value of the Lung Immune Prognostic Index in Patients with Non-Small Cell Lung Cancer Initiating First-Line Atezolizumab Combination Therapy: Subgroup Analysis of the IMPOWER150 Trial

“…Standard first line treatment of advanced non-small cell lung cancer (NSCLC) is quickly evolving to be immune checkpoint inhibitors (ICIs) in combination with conventional chemotherapies [ 1 ]. With the arrival of ICIs, a multitude of potential factors that may assist in explaining heterogeneity in survival outcomes with immunotherapies have emerged [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ]. However, for many of these factors, there is minimal information on performance with first-line, ICI combination approaches.…”

ISPRF: A Machine Learning Model to Predict the Immune Subtype of Kidney Cancer Samples by Four Genes

“…Immunotherapies such as PD-1/PD-L1 antibodies are thought as promising tumor intervention methods since immunotherapies prolonged the overall survival time of ccRCC patients in different clinical trials [32]. However, the response rate of cancer patients to immunotherapy is still limited and unsatisfactory [33]. Since the tumor heterogeneity exists among cancer samples, identifying the potential immune subtypes with different immunotherapy drug responses might contribute to the individualized immunotherapy treatment.…”

Multicellular 3D Models to Study Tumour-Stroma Interactions

“…These observations have opened the way to immune oncology, a ground-breaking pharmacological approach for the cure of tumours, based on the enhancement of tumour immunity through the block of inhibitory pathways and inhibitory cells in the TME via immune checkpoint inhibitors. Due to the increasing clinical use and resistance to immunotherapies [ 89 ], it is crucial that relevant components of the immune system start being incorporated into 3D co-culture models to better predict clinical outcomes.…”