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Immune checkpoint inhibitor (ICI) is a major change in the field of tumor treatment, but tumor patients using ICI will have a series of immune-mediated organ-specific side effects, which are called immune-related adverse reactions (immune related adverse reactions).
adverse event, irAE)
.
When immunotherapy cancer patients develop irAEs, they will face severe consequences of stopping treatment, permanent tissue damage to vital organs, and even death
.
For example, immune-related pneumonitis is the most common lethal irAE in anti-PD-1/PD-L1-treated tumor patients, accounting for 35% of deaths from anti-PD-1/PD-L1-related irAEs
.
Although the incidence of immune-related myocarditis is relatively low, its fatality rate is as high as 50%
.
Given the increasing use of ICI therapy in cancer patients, a comprehensive understanding of irAEs will help immunotherapy patients achieve the greatest clinical benefit
.
At present, there are still many fundamental problems to be solved in the field of irAE research, such as predicting the risk of irAE in a single patient, the correlation between irAEs and immune benefit
.
To delve deeper into these questions, both clinical and molecular information from patients need to be collected
.
Due to the diversity of molecular mechanisms targeted by ICIs, the heterogeneity of clinical manifestations, onset time and incidence among different irAEs and different patients is also very strong
.
On the other hand, irAEs affect almost every organ in the human body and require clinicians to have expertise in multiple specialties for effective diagnosis and management
.
More importantly, it is ethically difficult for clinicians to systematically collect patients' organs and tissues affected by irAEs
.
Therefore, the collection of samples and clinical information for irAE research currently faces great challenges, which restricts the development of irAE related research
.
In view of the above research difficulties, on January 17, 2022, Professor Han Leng of Texas A&M University and Associate Researcher Jing Ying of the Clinical Research Center of Shanghai Jiaotong University School of Medicine published a paper entitled Harnessing big data to characterize in the journal Nature Reviews Clinical Oncology The article on immune-related adverse events summarizes and expounds how to maximize the use of multi-dimensional big data for irAE research
.
The authors first summarize the three main sources of big data available for irAE research, and the advantages and disadvantages of different sources of big data
.
The three key irAE questions, namely irAE biomarkers, the relationship between irAEs and ICI efficacy, and the demographic and quantitative characteristics of irAE risk, are used as examples to elaborate how to apply big data to irAE research
.
The authors first conducted a detailed study and investigation on the data characteristics of various existing big data, and concluded three types of big data that can be applied to irAE research: integrated clinical research data, large-scale real-world data and multiple omics data
.
The integrated clinical research data is of high quality due to its detailed clinical research specifications, but most clinical research does not disclose patient-level data
.
Real-world data includes a large number of patients, but the completeness and quality of the data are relatively lower than that of clinical research data
.
Multi-omics data can deeply reveal the molecular mechanism of irAEs, but the existing multi-omics datasets often lack detailed clinical information of patients, especially irAE information
.
Therefore, rigorous bioinformatics analysis and integration of data from these three different sources will greatly facilitate the development of fast, flexible and reliable irAE research, and will ultimately accelerate the clinical and translational progress of these studies
.
For example, the integration of multi-omics sequencing data and pharmacovigilance database data through bioinformatics analysis methods can effectively identify irAE biomarkers; the use of integrated clinical research data and real-world data can be used to study the correlation of irAE and ICI efficacy; irAE risk associated with patient characteristics can be studied using data from real-world databases
.
Figure 1.
Application of multi-dimensional big data in irAE research Associate researcher Jing Ying ( and Dr.
Yang Jingwen from Professor Han Leng's research group are the co-first authors of this paper, Han Leng, Vanderbilt University Douglas B.
Johnson and Professor Javid J.
Moslehi of the University of California, San Francisco are the co-corresponding authors of this paper
.
Associate Researcher Jing Ying and Professor Han Leng have published a series of original researches in the field of immunotherapy in recent years, such as biomarkers of irAE in cancer immunotherapy (see BioArt report for details: Nat Comm | Han Leng/Zhuang Guanglei/Xue Xinxin Research Group Collaborated to identify biomarkers of immune-related adverse events in cancer immunotherapy), gender-related differences in irAEs in cancer immunotherapy (see BioArt report for details: Chen Xiang/Han Leng/Liu Hong/Jingying collaborated to reveal immune-related differences in cancer immunotherapy Gender-related differences in adverse reactions) and single-cell-level studies on the toxicity of CAR cell therapy (Cancer Cell | Han Leng/Jing Ying's research group collaborated to reveal the targeted non-tumor effect-related toxicity of chimeric antigen receptor cell therapy)
.
This article is a summary and outlook of the two researchers and their teams on big data research in the field of irAE
.
Professor Han Leng's research group (https://hanlab.
tamhsc.
edu/) has been committed to using biological big data to study the pathogenesis of complex diseases such as cancer
.
His research team has used large-scale data such as TCGA to deeply study the mechanism of cancer and drug response.
As the corresponding author, he has published many papers in journals such as Cancer Cell, Nature Metabolism, Nature Immunology, Nature Communications, JNCI, etc.
, and contributed to Nature Reviews Clinical Wrote reviews and review articles for journals such as Oncology, Nature Biotechnology, Nature Metabolism, Trends series,
etc.
The research group has trained several PIs
.
The research group has been recruiting postgraduates and postdoctoral fellows for a long time.
Interested students are welcome to join or send us a letter for consultation
.
Resume delivery (if you are interested, please send your resume and other materials to): https://jinshuju.
net/f/ZqXwZt or scan the QR code to send the resume original link: https:// 021-00597-8 Publisher: Eleven reprint notices [Non-original article] The copyright of this article belongs to the author of the article.
Individuals are welcome to forward and share, and reprint is prohibited without permission.
The author has all legal rights, and offenders must be held accountable
.
adverse event, irAE)
.
When immunotherapy cancer patients develop irAEs, they will face severe consequences of stopping treatment, permanent tissue damage to vital organs, and even death
.
For example, immune-related pneumonitis is the most common lethal irAE in anti-PD-1/PD-L1-treated tumor patients, accounting for 35% of deaths from anti-PD-1/PD-L1-related irAEs
.
Although the incidence of immune-related myocarditis is relatively low, its fatality rate is as high as 50%
.
Given the increasing use of ICI therapy in cancer patients, a comprehensive understanding of irAEs will help immunotherapy patients achieve the greatest clinical benefit
.
At present, there are still many fundamental problems to be solved in the field of irAE research, such as predicting the risk of irAE in a single patient, the correlation between irAEs and immune benefit
.
To delve deeper into these questions, both clinical and molecular information from patients need to be collected
.
Due to the diversity of molecular mechanisms targeted by ICIs, the heterogeneity of clinical manifestations, onset time and incidence among different irAEs and different patients is also very strong
.
On the other hand, irAEs affect almost every organ in the human body and require clinicians to have expertise in multiple specialties for effective diagnosis and management
.
More importantly, it is ethically difficult for clinicians to systematically collect patients' organs and tissues affected by irAEs
.
Therefore, the collection of samples and clinical information for irAE research currently faces great challenges, which restricts the development of irAE related research
.
In view of the above research difficulties, on January 17, 2022, Professor Han Leng of Texas A&M University and Associate Researcher Jing Ying of the Clinical Research Center of Shanghai Jiaotong University School of Medicine published a paper entitled Harnessing big data to characterize in the journal Nature Reviews Clinical Oncology The article on immune-related adverse events summarizes and expounds how to maximize the use of multi-dimensional big data for irAE research
.
The authors first summarize the three main sources of big data available for irAE research, and the advantages and disadvantages of different sources of big data
.
The three key irAE questions, namely irAE biomarkers, the relationship between irAEs and ICI efficacy, and the demographic and quantitative characteristics of irAE risk, are used as examples to elaborate how to apply big data to irAE research
.
The authors first conducted a detailed study and investigation on the data characteristics of various existing big data, and concluded three types of big data that can be applied to irAE research: integrated clinical research data, large-scale real-world data and multiple omics data
.
The integrated clinical research data is of high quality due to its detailed clinical research specifications, but most clinical research does not disclose patient-level data
.
Real-world data includes a large number of patients, but the completeness and quality of the data are relatively lower than that of clinical research data
.
Multi-omics data can deeply reveal the molecular mechanism of irAEs, but the existing multi-omics datasets often lack detailed clinical information of patients, especially irAE information
.
Therefore, rigorous bioinformatics analysis and integration of data from these three different sources will greatly facilitate the development of fast, flexible and reliable irAE research, and will ultimately accelerate the clinical and translational progress of these studies
.
For example, the integration of multi-omics sequencing data and pharmacovigilance database data through bioinformatics analysis methods can effectively identify irAE biomarkers; the use of integrated clinical research data and real-world data can be used to study the correlation of irAE and ICI efficacy; irAE risk associated with patient characteristics can be studied using data from real-world databases
.
Figure 1.
Application of multi-dimensional big data in irAE research Associate researcher Jing Ying ( and Dr.
Yang Jingwen from Professor Han Leng's research group are the co-first authors of this paper, Han Leng, Vanderbilt University Douglas B.
Johnson and Professor Javid J.
Moslehi of the University of California, San Francisco are the co-corresponding authors of this paper
.
Associate Researcher Jing Ying and Professor Han Leng have published a series of original researches in the field of immunotherapy in recent years, such as biomarkers of irAE in cancer immunotherapy (see BioArt report for details: Nat Comm | Han Leng/Zhuang Guanglei/Xue Xinxin Research Group Collaborated to identify biomarkers of immune-related adverse events in cancer immunotherapy), gender-related differences in irAEs in cancer immunotherapy (see BioArt report for details: Chen Xiang/Han Leng/Liu Hong/Jingying collaborated to reveal immune-related differences in cancer immunotherapy Gender-related differences in adverse reactions) and single-cell-level studies on the toxicity of CAR cell therapy (Cancer Cell | Han Leng/Jing Ying's research group collaborated to reveal the targeted non-tumor effect-related toxicity of chimeric antigen receptor cell therapy)
.
This article is a summary and outlook of the two researchers and their teams on big data research in the field of irAE
.
Professor Han Leng's research group (https://hanlab.
tamhsc.
edu/) has been committed to using biological big data to study the pathogenesis of complex diseases such as cancer
.
His research team has used large-scale data such as TCGA to deeply study the mechanism of cancer and drug response.
As the corresponding author, he has published many papers in journals such as Cancer Cell, Nature Metabolism, Nature Immunology, Nature Communications, JNCI, etc.
, and contributed to Nature Reviews Clinical Wrote reviews and review articles for journals such as Oncology, Nature Biotechnology, Nature Metabolism, Trends series,
etc.
The research group has trained several PIs
.
The research group has been recruiting postgraduates and postdoctoral fellows for a long time.
Interested students are welcome to join or send us a letter for consultation
.
Resume delivery (if you are interested, please send your resume and other materials to): https://jinshuju.
net/f/ZqXwZt or scan the QR code to send the resume original link: https:// 021-00597-8 Publisher: Eleven reprint notices [Non-original article] The copyright of this article belongs to the author of the article.
Individuals are welcome to forward and share, and reprint is prohibited without permission.
The author has all legal rights, and offenders must be held accountable
.
