With the change in the disease spectrum, tumors have become a significant threat to people’s health. Although targeted drugs and combination therapies have been successful in many tumors, patient prognosis has not significantly improved. Over the past decades, immunotherapy has shed light on treating solid tumors, yet only about 20% of patients have sustained responses. Meanwhile, the heavy economic burden and serious immune-related adverse events (irAEs) urgently require us to accurately identify immunotherapy-sensitive patients to receive immunotherapy as early as possible. The emergence of transcriptomics, genomics, epigenetics, and proteomics has largely enlightened in predicting immunotherapy efficacy. Some biomarkers such as PD-L1, TMB, dMMR, and MSI have been applied to clinical practice. However, given the numerous steps involved in tumor immunity, the predictive ability of the above indicators is difficult to meet the requirements of precision medicine. It is crucial to develop new strategies for improving immunotherapy outcomes and prognosis.
Searching for and developing novel biomarkers that can accurately predict immunotherapy efficacy, and guide decision-making and clinical management is an urgent problem in the current field of immunotherapy. Recent advances in the comprehensive analysis and integrated application of multi-omics technologies such as transcriptomics, genomics, epigenomics, proteomics, and even single-cell omics have shown the potential to guide treatment and improve prognosis. Given the complicated procedures of anti-tumor immunity and immunotherapy, problems in any step, such as neoantigen generation, presentation, and recognition, as well as T cell infiltration and killing, may lead to immune escape in tumors. In recent years, biomarkers for the above steps have emerged, including TMB, HLA-I molecules, and various indicators for evaluating the tumor microenvironment. However, although they have shown certain predictive performance at different levels, the overall capability is unsatisfactory, and rarely applied in clinical practice. Considering this current situation and the urgent need for ideal biomarkers, this research topic aims to provide a platform for sharing new strategies developed through multi-omics that can improve immunotherapy efficacy and patient prognosis.
This topic aims to introduce recent findings focusing on multi-omics studies and to illustrate the fundamental understanding of the tumor microenvironment, anti-tumor immunity, immunotherapy, and immune escape mechanisms. Meanwhile, we look forward to these studies providing new insights into the early identification of immunotherapy-sensitive patients, improvement of immunotherapy efficacy, and even the development of new strategies for immune combination therapy. Submissions may focus on, but are not limited to, the following:
· Discover novel targets, develop drugs and cancer vaccines
· Integrated analyses the impact of multi-omics characteristics on tumor microenvironment, immunotherapy, and prognosis
· Development and validation of biomarkers to predict prognosis and immunotherapy efficacy
· Development and validation of multi-omics molecular subtypes serving precision medicine
· The role of multi-omics data in the early identification of immunotherapy-sensitive populations
· Combined with bioinformatics and artificial intelligence to mine new strategies and biomarkers for pan-cancer immunotherapy
· Case reports and clinical trials on new strategies for tumor immune combination therapy
With the change in the disease spectrum, tumors have become a significant threat to people’s health. Although targeted drugs and combination therapies have been successful in many tumors, patient prognosis has not significantly improved. Over the past decades, immunotherapy has shed light on treating solid tumors, yet only about 20% of patients have sustained responses. Meanwhile, the heavy economic burden and serious immune-related adverse events (irAEs) urgently require us to accurately identify immunotherapy-sensitive patients to receive immunotherapy as early as possible. The emergence of transcriptomics, genomics, epigenetics, and proteomics has largely enlightened in predicting immunotherapy efficacy. Some biomarkers such as PD-L1, TMB, dMMR, and MSI have been applied to clinical practice. However, given the numerous steps involved in tumor immunity, the predictive ability of the above indicators is difficult to meet the requirements of precision medicine. It is crucial to develop new strategies for improving immunotherapy outcomes and prognosis.
Searching for and developing novel biomarkers that can accurately predict immunotherapy efficacy, and guide decision-making and clinical management is an urgent problem in the current field of immunotherapy. Recent advances in the comprehensive analysis and integrated application of multi-omics technologies such as transcriptomics, genomics, epigenomics, proteomics, and even single-cell omics have shown the potential to guide treatment and improve prognosis. Given the complicated procedures of anti-tumor immunity and immunotherapy, problems in any step, such as neoantigen generation, presentation, and recognition, as well as T cell infiltration and killing, may lead to immune escape in tumors. In recent years, biomarkers for the above steps have emerged, including TMB, HLA-I molecules, and various indicators for evaluating the tumor microenvironment. However, although they have shown certain predictive performance at different levels, the overall capability is unsatisfactory, and rarely applied in clinical practice. Considering this current situation and the urgent need for ideal biomarkers, this research topic aims to provide a platform for sharing new strategies developed through multi-omics that can improve immunotherapy efficacy and patient prognosis.
This topic aims to introduce recent findings focusing on multi-omics studies and to illustrate the fundamental understanding of the tumor microenvironment, anti-tumor immunity, immunotherapy, and immune escape mechanisms. Meanwhile, we look forward to these studies providing new insights into the early identification of immunotherapy-sensitive patients, improvement of immunotherapy efficacy, and even the development of new strategies for immune combination therapy. Submissions may focus on, but are not limited to, the following:
· Discover novel targets, develop drugs and cancer vaccines
· Integrated analyses the impact of multi-omics characteristics on tumor microenvironment, immunotherapy, and prognosis
· Development and validation of biomarkers to predict prognosis and immunotherapy efficacy
· Development and validation of multi-omics molecular subtypes serving precision medicine
· The role of multi-omics data in the early identification of immunotherapy-sensitive populations
· Combined with bioinformatics and artificial intelligence to mine new strategies and biomarkers for pan-cancer immunotherapy
· Case reports and clinical trials on new strategies for tumor immune combination therapy