Share：
Share this content in WeChat
X
[Chinese][PDF]601
• Review •
Evaluation mechanism and research progress of radiogenomics in urinary tumors
MIAO Guoliang  ZHANG Yunfeng  YANG Jin  YANG Zhijun  ZHOU Fenghai 

Cite this article as: MIAO G L, ZHANG Y F, YANG J, et al. Evaluation mechanism and research progress of radiogenomics in urinary tumors[J]. Chin J Magn Reson Imaging, 2024, 15(10): 211-216. DOI:10.12015/issn.1674-8034.2024.10.036.


[Abstract] Radiogenomics is a newly emerging interdisciplinary field that has developed rapidly in the past decade and has shown great potential. By linking quantitative imaging features of tumor phenotypes with genomic features, it provides a new method for non-invasive disease diagnosis. Its application prospects are particularly significant in the treatment of genitourinary tumors, as the incidence of genitourinary tumors is increasing. Given its biodiversity and the need for careful long-term monitoring, research in imaging genomics is particularly urgent. Radiogenomics demonstrates deep research prospects and application value in the diagnosis, prognosis assessment, treatment response monitoring, and new target discovery of genitourinary tumors. We hope that this research can provide clinical doctors with powerful scientific evidence and practical reference information in the diagnosis and treatment evaluation of genitourinary tumors.
[Keywords] radiogenomics；urinary tumors；magnetic resonance imaging；prognostic evaluation

MIAO Guoliang1   ZHANG Yunfeng2   YANG Jin1   YANG Zhijun2   ZHOU Fenghai1, 3*  

1 First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou 730000, China

2 The First Clinical Medical College of Lanzhou University, Lanzhou 73000, China

3 Department of Urology, Gansu Provincial People's Hospital, Lanzhou 730000, China

Corresponding author: ZHOU F H, E-mail: zhoufengh@163.com

Conflicts of interest   None.

Received  2024-04-23
Accepted  2024-10-10
DOI: 10.12015/issn.1674-8034.2024.10.036
Cite this article as: MIAO G L, ZHANG Y F, YANG J, et al. Evaluation mechanism and research progress of radiogenomics in urinary tumors[J]. Chin J Magn Reson Imaging, 2024, 15(10): 211-216. DOI:10.12015/issn.1674-8034.2024.10.036.

[1]
SIEGEL R L, MILLER K D, WAGLE N S, et al. Cancer statistics, 2023[J]. CA Cancer J Clin, 2023, 73(1): 17-48. DOI: 10.3322/caac.21763.
[2]
LIU Z Q, DUAN T, ZHANG Y Y, et al. Radiogenomics: a key component of precision cancer medicine[J]. Br J Cancer, 2023, 129(5): 741-753. DOI: 10.1038/s41416-023-02317-8.
[3]
AGAZZI G M, RAVANELLI M, ROCA E, et al. CT texture analysis for prediction of EGFR mutational status and ALK rearrangement in patients with non-small cell lung cancer[J]. Radiol Med, 2021, 126(6): 786-794. DOI: 10.1007/s11547-020-01323-7.
[4]
KHALEEL S, KATIMS A, CUMARASAMY S, et al. Radiogenomics in clear cell renal cell carcinoma: a review of the current status and future directions[J/OL]. Cancers, 2022, 14(9): 2085 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/35565216/. DOI: 10.3390/cancers14092085.
[5]
SIEGEL R L, GIAQUINTO A N, JEMAL A. Cancer statistics, 2024 [J]. CA Cancer J Clin, 2024, 74(1): 12-49. DOI: 10.3322/caac.21820.
[6]
MENG L B, COLLIER K A, WANG P, et al. Emerging immunotherapy approaches for advanced clear cell renal cell carcinoma[J/OL]. Cells, 2023, 13(1): 34 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/35079777/. DOI: 10.3390/cells13010034.
[7]
BAHADORAM S, DAVOODI M, HASSANZADEH S, et al. Renal cell carcinoma: an overview of the epidemiology, diagnosis, and treatment[J/OL]. G Ital Nefrol, 2022, 39(3): 2022-vol3 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/35819037/.
[8]
GRECO F, D'ANDREA V, BEOMONTE ZOBEL B, et al. Radiogenomics and texture analysis to detect von hippel-lindau (VHL) mutation in clear cell renal cell carcinoma[J]. Curr Issues Mol Biol, 2024, 46(4): 3236-3250. DOI: 10.3390/cimb46040203.
[9]
LI Z C, ZHAI G T, ZHANG J H, et al. Differentiation of clear cell and non-clear cell renal cell carcinomas by all-relevant radiomics features from multiphase CT: a VHL mutation perspective[J]. Eur Radiol, 2019, 29(8): 3996-4007. DOI: 10.1007/s00330-018-5872-6.
[10]
KIM B J, KIM J H, KIM H S, et al. Prognostic and predictive value of VHL gene alteration in renal cell carcinoma: a meta-analysis and review[J]. Oncotarget, 2017, 8(8): 13979-13985. DOI: 10.18632/oncotarget.14704.
[11]
WU X H, ZHU J M, LIN B H, et al. Semantic computed tomography features for predicting BRCA1-associated protein 1 and/or tumor protein p53 gene mutation status in clear cell renal cell carcinoma[J]. Int J Radiat Oncol Biol Phys, 2023, 116(3): 666-675. DOI: 10.1016/j.ijrobp.2022.12.023.
[12]
KOCAK B, DURMAZ E S, KAYA O K, et al. Machine learning-based unenhanced CT texture analysis for predicting BAP1 mutation status of clear cell renal cell carcinomas[J]. Acta Radiol, 2020, 61(6): 856-864. DOI: 10.1177/0284185119881742.
[13]
RUGGIERI F, JONAS K, FERRACIN M, et al. MicroRNAs as regulators of tumor metabolism[J/OL]. Endocr Relat Cancer, 2023, 30(8): e220267 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/37224081/. DOI: 10.1530/ERC-22-0267.
[14]
MARIGLIANO C, BADIA S, BELLINI D, et al. Radiogenomics in clear cell renal cell carcinoma: correlations between advanced CT imaging (texture analysis) and microRNAs expression[J/OL]. Technol Cancer Res Treat, 2019, 18: 1533033819878458 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/31564221/. DOI: 10.1177/1533033819878458.
[15]
CEN D Z, XU L, ZHANG S W, et al. Renal cell carcinoma: predicting RUNX3 methylation level and its consequences on survival with CT features[J]. Eur Radiol, 2019, 29(10): 5415-5422. DOI: 10.1007/s00330-019-06049-3.
[16]
GAO J H, YE F D, HAN F, et al. A novel radiogenomics biomarker based on hypoxic-gene subset: accurate survival and prognostic prediction of renal clear cell carcinoma[J/OL]. Front Oncol, 2021, 11: 739815 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/31564221/. DOI: 10.3389/fonc.2021.739815.
[17]
SHI R, GAO S S, ZHANG J, et al. Collagen prolyl 4-hydroxylases modify tumor progression[J]. Acta Biochim Biophys Sin, 2021, 53(7): 805-814. DOI: 10.1093/abbs/gmab065.
[18]
GRECO F, PANUNZIO A, TAFURI A, et al. CT-based radiogenomics of P4HA3 expression in clear cell renal cell carcinoma[J]. Acad Radiol, 2024, 31(3): 902-908. DOI: 10.1016/j.acra.2023.07.003.
[19]
HE H F, XIE Y Z, SONG F L, et al. Radiogenomic analysis based on lipid metabolism-related subset for non-invasive prediction for prognosis of renal clear cell carcinoma[J/OL]. Eur J Radiol, 2024, 175: 111433 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/38554673/. DOI: 10.1016/j.ejrad.2024.111433.
[20]
GAO J J, YANG D D, XU H N, et al. ADAM metallopeptidase domain 12 overexpression correlates with prognosis and immune cell infiltration in clear cell renal cell carcinoma[J]. Bioengineered, 2022, 13(2): 2412-2429. DOI: 10.1080/21655979.2021.2010313.
[21]
GRECO F, PANUNZIO A, BERNETTI C, et al. Exploring the ADAM12 expression in clear cell renal cell carcinoma: a radiogenomic analysis on CT imaging[J]. Acad Radiol, 2024, 31(9): 3672-3677. DOI: 10.1016/j.acra.2024.02.032.
[22]
RICHTERS A, ABEN K K H, KIEMENEY L A L M. The global burden of urinary bladder cancer: an update[J]. World J Urol, 2020, 38(8): 1895-1904. DOI: 10.1007/s00345-019-02984-4.
[23]
AHMADZADEH M, JOHNSON L A, HEEMSKERK B, et al. Tumor antigen-specific CD8 T cells infiltrating the tumor express high levels of PD-1 and are functionally impaired[J]. Blood, 2009, 114(8): 1537-1544. DOI: 10.1182/blood-2008-12-195792.
[24]
ZHENG Z T, GUO Y D, HUANG X S, et al. CD8A as a prognostic and immunotherapy predictive biomarker can be evaluated by MRI radiomics features in bladder cancer[J/OL]. Cancers, 2022, 14(19): 4866 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/36230788/. DOI: 10.3390/cancers14194866.
[25]
LIU Q, GREGORY R I. RNAmod: an integrated system for the annotation of mRNA modifications[J]. Nucleic Acids Res, 2019, 47(W1): W548-W555. DOI: 10.1093/nar/gkz479.
[26]
BERTERO A, BROWN S, MADRIGAL P, et al. The SMAD2/3 interactome reveals that TGFβ controls m6A mRNA methylation in pluripotency[J]. Nature, 2018, 555(7695): 256-259. DOI: 10.1038/nature25784.
[27]
HAN J, WANG J Z, YANG X, et al. METTL3 promote tumor proliferation of bladder cancer by accelerating pri-miR221/222 maturation in m6A-dependent manner[J/OL]. Mol Cancer, 2019, 18(1): 110 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/31228940/. DOI: 10.1186/s12943-019-1036-9.
[28]
ZHANG C Z, HUANG S Z, ZHUANG H K, et al. YTHDF2 promotes the liver cancer stem cell phenotype and cancer metastasis by regulating OCT4 expression via m6A RNA methylation[J]. Oncogene, 2020, 39(23): 4507-4518. DOI: 10.1038/s41388-020-1303-7.
[29]
LIU P H, FAN B Y, OTHMANE B, et al. m6A-induced lncDBET promotes the malignant progression of bladder cancer through FABP5-mediated lipid metabolism[J]. Theranostics, 2022, 12(14): 6291-6307. DOI: 10.7150/thno.71456.
[30]
YE F D, HU Y, GAO J H, et al. Radiogenomics map reveals the landscape of m6A methylation modification pattern in bladder cancer[J/OL]. Front Immunol, 2021, 12: 722642 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/34733275/. DOI: 10.3389/fimmu.2021.722642.
[31]
MARCH-VILLALBA J A, RAMOS-SOLER D, SORIANO-SARRIÓ P, et al. Immunohistochemical expression of Ki-67, Cyclin D1, p16INK4a, and Survivin as a predictive tool for recurrence and progression-free survival in papillary urothelial bladder cancer pTa/pT1 G2 (WHO 1973)[J]. Urol Oncol, 2019, 37(2): 158-165. DOI: 10.1016/j.urolonc.2018.10.005.
[32]
ZHENG Z T, GU Z R, XU F J, et al. Magnetic resonance imaging-based radiomics signature for preoperative prediction of Ki67 expression in bladder cancer[J/OL]. Cancer Imaging, 2021, 21(1): 65 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/34863282/. DOI: 10.1186/s40644-021-00433-3.
[33]
LIN P, WEN D Y, CHEN L, et al. A radiogenomics signature for predicting the clinical outcome of bladder urothelial carcinoma[J]. Eur Radiol, 2020, 30(1): 547-557. DOI: 10.1007/s00330-019-06371-w.
[34]
WITJES J A, BRUINS H M, CATHOMAS R, et al. European association of urology guidelines on muscle-invasive and metastatic bladder cancer: summary of the 2020 guidelines[J]. Eur Urol, 2021, 79(1): 82-104. DOI: 10.1016/j.eururo.2020.03.055.
[35]
QURESHI T A, CHEN X Y, XIE Y B, et al. MRI/RNA-seq-based radiogenomics and artificial intelligence for more accurate staging of muscle-invasive bladder cancer[J/OL]. Int J Mol Sci, 2023, 25(1): 88 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/38203254/. DOI: 10.3390/ijms25010088.
[36]
XU C T, CAO J C, ZHOU T J. Radiogenomics uncovers an interplay between angiogenesis and clinical outcomes in bladder cancer[J]. Environ Toxicol, 2024, 39(3): 1374-1387. DOI: 10.1002/tox.24038.
[37]
LAWRENCE E M, WARREN A Y, PRIEST A N, et al. Evaluating prostate cancer using fractional tissue composition of radical prostatectomy specimens and pre-operative diffusional kurtosis magnetic resonance imaging[J/OL]. PLoS One, 2016, 11(7): e0159652 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/27467064/. DOI: 10.1371/journal.pone.0159652.
[38]
CHEN C Y, CHEN J Y, HE L N, et al. PTEN: tumor suppressor and metabolic regulator[J/OL]. Front Endocrinol, 2018, 9: 338 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/30038596/. DOI: 10.3389/fendo.2018.00338.
[39]
MCCANN S M, JIANG Y L, FAN X B, et al. Quantitative multiparametric MRI features and PTEN expression of peripheral zone prostate cancer: A pilot study[J]. AJR Am J Roentgenol, 2016, 206(3): 559-565. DOI: 10.2214/AJR.15.14967.
[40]
SWITLYK M D, SALBERG U B, GEIER O M, et al. PTEN expression in prostate cancer: relationship with clinicopathologic features and multiparametric MRI findings[J]. AJR Am J Roentgenol, 2019, 212(6): 1206-1214. DOI: 10.2214/AJR.18.20743.
[41]
JAMSHIDI N, MARGOLIS D J, RAMAN S, et al. Multiregional radiogenomic assessment of prostate microenvironments with multiparametric MR imaging and DNA whole-exome sequencing of prostate glands with adenocarcinoma[J]. Radiology, 2017, 284(1): 109-119. DOI: 10.1148/radiol.2017162827.
[42]
HECTORS S J, CHERNY M, YADAV K K, et al. Radiomics features measured with multiparametric magnetic resonance imaging predict prostate cancer aggressiveness[J]. J Urol, 2019, 202(3): 498-505. DOI: 10.1097/JU.0000000000000272.
[43]
WIBMER A G, ROBERTSON N L, HRICAK H, et al. Extracapsular extension on MRI indicates a more aggressive cell cycle progression genotype of prostate cancer[J]. Abdom Radiol, 2019, 44(8): 2864-2873. DOI: 10.1007/s00261-019-02023-1.
[44]
MILOSEVIC M, WARDE P, MÉNARD C, et al. Tumor hypoxia predicts biochemical failure following radiotherapy for clinically localized prostate cancer[J]. Clin Cancer Res, 2012, 18(7): 2108-2114. DOI: 10.1158/1078-0432.CCR-11-2711.
[45]
HOSKIN P J, CARNELL D M, TAYLOR N J, et al. Hypoxia in prostate cancer: correlation of BOLD-MRI with pimonidazole immunohistochemistry-initial observations[J]. Int J Radiat Oncol Biol Phys, 2007, 68(4): 1065-1071. DOI: 10.1016/j.ijrobp.2007.01.018.
[46]
SUN Y, WILLIAMS S, BYRNE D, et al. Association analysis between quantitative MRI features and hypoxia-related genetic profiles in prostate cancer: a pilot study[J/OL]. Br J Radiol, 2019, 92(1104): 20190373 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/31356111/. DOI: 10.1259/bjr.20190373.
[47]
KESCH C, RADTKE J P, WINTSCHE A, et al. Correlation between genomic index lesions and mpMRI and 68Ga-PSMA-PET/CT imaging features in primary prostate cancer[J/OL]. Sci Rep, 2018, 8(1): 16708 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/30420756/. DOI: 10.1038/s41598-018-35058-3.
[48]
FISCHER S, TAHOUN M, KLAAN B, et al. A radiogenomic approach for decoding molecular mechanisms underlying tumor progression in prostate cancer[J/OL]. Cancers, 2019, 11(9): 1293 [2024-07-10].https://pubmed.ncbi.nlm.nih.gov/31480766/. DOI: 10.3390/cancers11091293.
[49]
FERNANDES C D, SCHAAP A, KANT J, et al. Radiogenomics analysis linking multiparametric MRI and transcriptomics in prostate cancer[J/OL]. Cancers, 2023, 15(12): 3074 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/37370685/. DOI: 10.3390/cancers15123074.
[50]
KU A T, SHANKAVARAM U, TROSTEL S Y, et al. Radiogenomic profiling of prostate tumors prior to external beam radiotherapy converges on a transcriptomic signature of TGF-β activity driving tumor recurrence[J/OL]. medRxiv, 2023: 2023.05.01.23288883 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/37205576/. DOI: 10.1101/2023.05.01.23288883.
[51]
SKINGEN V E, HOMPLAND T, FJELDBO C S, et al. Prostate cancer radiogenomics reveals proliferative gene expression programs associated with distinct MRI-based hypoxia levels[J/OL]. Radiother Oncol, 2023, 188: 109875 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/37640161/. DOI: 10.1016/j.radonc.2023.109875.
[52]
WANG S Y, XU G X, CHAO F, et al. HNRNPC promotes proliferation, metastasis and predicts prognosis in prostate cancer[J]. Cancer Manag Res, 2021, 13: 7263-7276. DOI: 10.2147/CMAR.S330713.
[53]
FU Q H, LUO L, HONG R X, et al. Radiogenomic analysis of ultrasound phenotypic features coupled to proteomes predicts metastatic risk in primary prostate cancer[J/OL]. BMC Cancer, 2024, 24(1): 290 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/38438956/. DOI: 10.1186/s12885-024-12028-9.

PREV MRI-Based Artificial Intelligence in Lymph Node Metastasis of Rectal Cancer
NEXT Advances in ultrahigh-field MRI with 7.0 T and above in the musculoskeletal system
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn