Application of radiomics-based multiomics combinations in the tumor microenvironment and cancer prognosis

被引:32
|
作者
Kang, Wendi [1 ]
Qiu, Xiang [2 ]
Luo, Yingen [1 ]
Luo, Jianwei [3 ,4 ]
Liu, Yang [5 ]
Xi, Junqing [1 ]
Li, Xiao [1 ]
Yang, Zhengqiang [1 ]
机构
[1] Chinese Acad Med Sci & Peking Union Med Coll, Natl Canc Ctr, Dept Intervent Therapy, Natl Clin Res Ctr Canc,Canc Hosp, Panjiayuan Nanli 17, Beijing 100021, Peoples R China
[2] Fudan Univ, Obstet & Gynecol Hosp, Shanghai 200011, Peoples R China
[3] Cent South Univ, Hunan Canc Hosp, Dept Diagnost Radiol, 283 Tongzipo Rd, Changsha 410013, Hunan, Peoples R China
[4] Cent South Univ, Affiliated Canc Hosp, Xiangya Sch Med, 283 Tongzipo Rd, Changsha 410013, Hunan, Peoples R China
[5] Chinese Acad Med Sci & Peking Union Med Coll, Natl Clin Res Ctr Canc, Natl Canc Ctr, Dept Thorac Surg,Canc Hosp, Beijing, Peoples R China
基金
国家重点研发计划;
关键词
Multiomics combination; Radiomics; Biomarkers; Tumor microenvironment; Cancer prognosis; B-CELLS; RISK STRATIFICATION; LUNG-CANCER; SURVIVAL; IMMUNOTHERAPY; PREDICT; MODEL; MRI; SIGNATURE; FEATURES;
D O I
10.1186/s12967-023-04437-4
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
The advent of immunotherapy, a groundbreaking advancement in cancer treatment, has given rise to the prominence of the tumor microenvironment ( TME) as a critical area of research. The clinical implications of an improved understanding of the TME are significant and far-reaching. Radiomics has been increasingly utilized in the comprehensive assessment of the TME and cancer prognosis. Similarly, the advancement of pathomics, which is based on pathological images, can offer additional insights into the panoramic view and microscopic information of tumors. The combination of pathomics and radiomics has revolutionized the concept of a "digital biopsy". As genomics and transcriptomics continue to evolve, integrating radiomics with genomic and transcriptomic datasets can offer further insights into tumor and microenvironment heterogeneity and establish correlations with biological significance. Therefore, the synergistic analysis of digital image features (radiomics, pathomics) and genetic phenotypes (genomics) can comprehensively decode and characterize the heterogeneity of the TME as well as predict cancer prognosis. This review presents a comprehensive summary of the research on important radiomics biomarkers for predicting the TME, emphasizing the interplay between radiomics, genomics, transcriptomics, and pathomics, as well as the application of multiomics in decoding the TME and predicting cancer prognosis. Finally, we discuss the challenges and opportunities in multiomics research. In conclusion, this review highlights the crucial role of radiomics and multiomics associations in the assessment of the TME and cancer prognosis. The combined analysis of radiomics, pathomics, genomics, and transcriptomics is a promising research direction with substantial research significance and value for comprehensive TME evaluation and cancer prognosis assessment.
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收藏
页数:20
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