Biomarkers, Resistance Mechanisms, and Potential Targets for Immunotherapy

Dear Colleagues,

In this era of precision medicine and exciting advances, drug resistance remains an important obstacle to cancer treatment. The development of targeted therapy based on increasingly revealed pathogenic mechanisms of cancer has made contributions to overcoming drug resistance. In addition, immunotherapy, represented by immune checkpoint inhibitors (ICIs) and CAR-T therapy, has led to better therapeutic outcomes.

The discovery of ICIs has now been universally acknowledged as a significant breakthrough in cancer therapy after the targeted treatment of checkpoint molecules: anti-programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) and anti-cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) on several cancer types achieved satisfying results. However, there are still quite a lot of patients suffering from severe side effects and ineffective treatment outcomes. Although some candidate biomarkers, including PD-L1, tumor mutation burden (TMB), interferon-gamma (IFN-g), and microsatellite instability (MSI), could facilitate the clinical selection of patients for ICI treatment, these approaches are hampered by moderate accuracy and limited scope of application. To this end, identifying new immunotherapy biomarkers, mining resistance mechanisms, and exploring potential targets for enhancing immunotherapy efficacy are urgent, as this could facilitate the selection of potential immunotherapy beneficiaries.

This Research Topic aims to deepen our understanding of immunotherapy's potential mechanisms and biomarkers.

Potential topics include but are not limited to the following:

1. New technologies or methods employed to discover biomarkers for cancer immunotherapy.
2. Integrated genomic analysis identifies clinically relevant subtypes of patients sensitive to cancer immunotherapy.
3. Novel molecular mechanisms involved in the response or sensibility of cancer immunotherapy.
4. Immune neoantigen of tumor involved in the immune response during cancer immunotherapy.
5. Bioinformatics research with validation to identify novel biomarkers and models based on cancer immunotherapy patients.
6. Pathogenic mechanisms of cancer in drug resistance.
7. Novel targeted therapy of cancer based on newly defined molecular mechanisms.
8. Biomarkers for cancer development.
9. Machine learning-based predictive and prognostic model

Dr. Hao Zhang
Dr. Nan Zhang
Guest Editors

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• cancer
• drug resistance
• immunotherapy
• biomarker
• pathogenic mechanism
• targeted therapy
• bioinformatics