Share this content in WeChat
Application progress of radiogenomics in the prediction of liver metastasis gene mutations in colorectal cancer
MA Jiaqi  XIAO Lingqing  LI Xiaofu 

Cite this article as: Ma JQ, Xiao LQ, Li XF. Application progress of radiogenomics in the prediction of liver metastasis gene mutations in colorectal cancer[J]. Chin J Magn Reson Imaging, 2022, 13(9): 160-162, 170. DOI:10.12015/issn.1674-8034.2022.09.038.

[Abstract] Colorectal cancer (CRC) is the one of the common gastroenteritis tumors, liver is the most common metastatic site of advanced CRC, colorectal liver metastasis (CRLM) is the main adverse factor that effects the long-term prognosis of patients. It is shown that CRLM is usually associated with the gene mutation status intimately. Traditional imaging methods still have some limitations in the prediction, diagnosis, treatment and prognosis of CRLM gene mutation. In recent years, radiogenomics has shown great potential and broad application prospects in predicting gene mutation status of CRLM, guiding treatment decision making, improving long-term prognosis and overall survival rate, and predicting treatment sensitivity.
[Keywords] colorectal cancer;liver metastasis;radiomics;radiogenomics;gene mutation;colorectal liver metastasis

MA Jiaqi1   XIAO Lingqing2   LI Xiaofu1*  

1 Department of Magnetic Resonance Imaging Diagnostic, the 2nd Affiliated Hospital of Harbin Medical University, Harbin 150086, China

2 Medical Imaging Center, Beitun General Hospital, 10th Division, Xinjiang Production and Construction Corps, Beitun 836099, China

*Li XF, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS Finance Science and Technology Project of Xinjiang Production and Construction Corps (No. 2021AB029).
Received  2022-04-20
Accepted  2022-07-29
DOI: 10.12015/issn.1674-8034.2022.09.038
Cite this article as: Ma JQ, Xiao LQ, Li XF. Application progress of radiogenomics in the prediction of liver metastasis gene mutations in colorectal cancer[J]. Chin J Magn Reson Imaging, 2022, 13(9): 160-162, 170. DOI:10.12015/issn.1674-8034.2022.09.038.

Lambin P, Rios-Velazquez E, Leijenaar R, et al. Radiomics: Extracting more information from medical images using advanced feature analysis[J]. Eur J Cancer, 2012, 48(4): 441-446. DOI: 10.1016/j.ejca.2011.11.036.
Kumar V, Gu YH, Basu S, et al. Radiomics: the process and the challenges[J]. Magn Reson Imaging, 2012, 30(9): 1234-1248. DOI: 10.1016/j.mri.2012.06.010.
Aerts HJWL, Velazquez ER, Leijenaar RTH, et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach[J/OL]. Nat Commun, 2014 [2022-04-20]. DOI: 10.1038/ncomms5006.
Gillies RJ, Kinahan PE, Hricak H. Radiomics: images are more than pictures, they are data[J]. Radiology, 2016, 278(2): 563-577. DOI: 10.1148/radiol.2015151169.
Mayerhoefer ME, Materka A, Langs G, et al. Introduction to radiomics[J]. J Nucl Med, 2020, 61(4): 488-495. DOI: 10.2967/jnumed.118.222893.
Abdollahi H, Mofid B, Shiri I, et al. Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer[J]. Radiol Med, 2019, 124(6): 555-567. DOI: 10.1007/s11547-018-0966-4.
Fusco R, Granata V, Petrillo A. Introduction to special issue of radiology and imaging of cancer[J/OL]. Cancers (Basel), 2020 [2022-04-20]. DOI: 10.3390/cancers12092665.
Granata V, Fusco R, Avallone A, et al. Radiomics-derived data by contrast enhanced magnetic resonance in ras mutations detection in colorectal liver metastases[J/OL]. Cancers (Basel), 2021 [2022-04-20]. DOI: 10.3390/cancers13030453.
Kassahun WT. Unresolved issues and controversies surrounding the management of colorectal cancer liver metastasis[J/OL]. World J Surg Oncol, 2015 [2022-04-20]. DOI: 10.1186/s12957-014-0420-6.
Shi YL, Wei W, Chen L, et al. Progress in the study of prognostic factors of hepatectomy in the treatment of colorectal cancer liver metastasis[J]. Chin J Pract Surg, 2020, 40(12): 1448-1452. DOI: 10.19538/j.cjps.issn1005-2208.2020.12.27.
Bruera G, Cannita K, Di Giacomo D, et al. Prognostic value of kras genotype in metastatic colorectal cancer (mcrc) patients treated with intensive triplet chemotherapy plus bevacizumab (fir-b/fox) according to extension of metastatic disease[J/OL]. BMC Med, 2012 [2022-04-20]. DOI: 10.1186/1741-7015-10-135.
Jones JC, Renfro LA, Al-Shamsi HO, et al.Non-V600 BRAF mutations define a clinically distinct molecular subtype of metastatic colorectal cancer[J]. J Clin Oncol, 2017, 35(23): 2624-2630. DOI: 10.1200/JCO.2016.71.4394.
Fanelli GN, Dal Pozzo CA, Depetris I, et al. The heterogeneous clinical and pathological landscapes of metastatic Braf-mutated colorectal cancer[J/OL]. Cancer Cell Int, 2020 [2022-04-20]. DOI: 10.1186/s12935-020-1117-2.
He P, Zou Y, Qiu J, et al. Pretreatment 18F-FDG PET/CT imaging predicts the KRAS/NRAS/BRAF gene mutational status in colorectal cancer[J/OL]. J Oncol, 2021 [2022-04-20]. DOI: 10.1155/2021/6687291.
Oliveira C, Velho S, Moutinho C, et al. KRAS and BRAF oncogenic mutations in MSS colorectal carcinoma progression[J]. Oncogene, 2007, 26(1): 158-163. DOI: 10.1038/sj.onc.1209758.
Guo XF, Yang WQ, Yang Q, et al. Feasibility of MRI radiomics for predicting KRAS mutation in rectal cancer[J]. Curr Med Sci, 2020, 40(6): 1156-1160. DOI: 10.1007/s11596-020-2298-6.
Shi RC, Chen WX, Yang BW, et al. Prediction of KRAS, NRAS and BRAF status in colorectal cancer patients with liver metastasis using a deep artificial neural network based on radiomics and semantic features[J]. Am J Cancer Res, 2020, 10(12): 4513-4526.
Park JE, Kim HS, Park SY, et al. Prediction of core signaling pathway by using diffusion-and perfusion-based MRI radiomics and next-generation sequencing in isocitrate dehydrogenase wild-type glioblastoma[J]. Radiology, 2020, 294(2): 388-397. DOI: 10.1148/radiol.2019190913.
Wang XH, Long LH, Cui Y, et al. MRI-based radiomics model for preoperative prediction of 5-year survival in patients with hepatocellular carcinoma[J]. Br J Cancer, 2020, 122(7): 978-985. DOI: 10.1038/s41416-019-0706-0.
Kawada K, Nakamoto Y, Kawada M, et al. Relationship between 18F-fluorodeoxyglucose accumulation and KRAS/BRAF mutations in colorectal cancer[J]. Clin Cancer Res, 2012, 18(6): 1696-1703. DOI: 10.1158/1078-0432.CCR-11-1909.
Granata V, Fusco R, Risi C, et al. Diffusion-weighted mri and diffusion kurtosis imaging to detect ras mutation in colorectal liver metastasis[J/OL]. Cancers, 2020 [2022-04-20]. DOI: 10.3390/cancers12092420.
Gültekin MA, Türk HM, Beşiroğlu M, et al. Relationship between kras mutation and diffusion weighted imaging in colorectal liver metastases; preliminary study[J/OL]. Eur J Radiol, 2020 [2022-04-20]. DOI: 10.1016/j.ejrad.2020.108895.
Mao WJ, Zhou J, Zhang H, et al. Relationship between KRAS mutations and dual time point 18F-FDG PET/CT imaging in colorectal liver metastases[J]. Abdom Radiol (NY), 2019, 44(6): 2059-2066. DOI: 10.1007/s00261-018-1740-8.
Chen SW, Lin CY, Ho CM, et al. Genetic alterations in colorectal cancer have different patterns on 18F-FDG PET/CT[J]. Clin Nucl Med, 2015, 40(8): 621-626. DOI: 10.1097/RLU.0000000000000830.
Chen SW, Shen WC, Chen WT, et al. Metabolic imaging phenotype using radiomics of [18F] FDG PET/CT associated with genetic alterations of colorectal cancer[J]. Mol Imaging Biol, 2019, 21(1): 183-190. DOI: 10.1007/s11307-018-1225-8.
Oh JE, Kim MJ, Lee J, et al. Magnetic resonance-based texture analysis differentiating KRAS mutation status in rectal cancer[J]. Cancer Res Treat, 2020, 52(1): 51-59. DOI: 10.4143/crt.2019.050.
Shin YR, Kim KA, Im S, et al. Prediction of KRAS mutation in rectal cancer using MRI[J]. Anticancer Res, 2016, 36(9): 4799-4804. DOI: 10.21873/anticanres.11039.
Xu Y, Xu Q, Ma Y, et al. Characterizing mri features of rectal cancers with different kras status[J/OL]. BMC Cancer, 2019 [2022-04-20]. DOI: 10.1186/s12885-019-6341-6.
Lubner MG, Stabo N, Lubner SJ, et al. CT textural analysis of hepatic metastatic colorectal cancer: pre-treatment tumor heterogeneity correlates with pathology and clinical outcomes[J]. Abdom Imaging, 2015, 40(7): 2331-2337. DOI: 10.1007/s00261-015-0438-4.
Modest DP, Ricard I, Heinemann V, et al. Outcome according to KRAS-, NRAS- and BRAF-mutation as well as KRAS mutation variants: pooled analysis of five randomized trials in metastatic colorectal cancer by the AIO colorectal cancer study group[J]. Ann Oncol, 2016, 27(9): 1746-1753. DOI: 10.1093/annonc/mdw261.
Souglakos J, Philips J, Wang R, et al. Prognostic and predictive value of common mutations for treatment response and survival in patients with metastatic colorectal cancer[J]. Br J Cancer, 2009, 101(3): 465-472. DOI: 10.1038/sj.bjc.6605164.
Deng YH, Wang L, Tan SY, et al. KRAS as a predictor of poor prognosis and benefit from postoperative FOLFOX chemotherapy in patients with stage Ⅱ and Ⅲ colorectal cancer[J]. Mol Oncol, 2015, 9(7): 1341-1347. DOI: 10.1016/j.molonc.2015.03.006.
Taieb J, Shi Q, Pederson L, et al. Prognosis of microsatellite instability and/or mismatch repair deficiency stage Ⅲ colon cancer patients after disease recurrence following adjuvant treatment: results of an ACCENT pooled analysis of seven studies[J]. Ann Oncol, 2019, 30(9): 1466-1471. DOI: 10.1093/annonc/mdz208.
Margonis GA, Buettner S, Andreatos N, et al. Association of braf mutations with survival and recurrence in surgically treated patients with metastatic colorectal liver cancer[J/OL]. JAMA Surg, 2018 [2022-04-20]. DOI: 10.1001/jamasurg.2018.0996.
Huang XM, Cheng ZX, Huang YQ, et al. CT-based radiomics signature to discriminate high-grade from low-grade colorectal adenocarcinoma[J]. Acad Radiol, 2018, 25(10): 1285-1297. DOI: 10.1016/j.acra.2018.01.020.
Badic B, Hatt M, Durand S, et al. Radiogenomics-based cancer prognosis in colorectal cancer[J/OL]. Sci Rep, 2019 [2022-04-20]. DOI: 10.1038/s41598-019-46286-6.
Starmans MPA, Buisman FE, Renckens M, et al. Distinguishing pure histopathological growth patterns of colorectal liver metastases on CT using deep learning and radiomics: a pilot study[J]. Clin Exp Metastasis, 2021, 38(5): 483-494. DOI: 10.1007/s10585-021-10119-6.
Tharmaseelan H, Hertel A, Tollens F, et al. Identification of ct imaging phenotypes of colorectal liver metastases from radiomics signatures-towards assessment of interlesional tumor heterogeneity[J/OL]. Cancers (Basel), 2022 [2022-04-20]. DOI: 10.3390/cancers14071646.
Asaoka Y, Ijichi H, Koike K. PD-1 blockade in tumors with mismatch-repair deficiency[J/OL]. N Engl J Med, 2015 [2022-04-20]. DOI: 10.1056/nejmc1510353.
Chen G. Current situation and progress of immunotherapy for colorectal cancer[J]. J Precis Med, 2019, 34(1): 1-5. DOI: 10.13362/j.jpmed.201901001.
Dercle L, Lu L, Schwartz LH, et al. Radiomics response signature for identification of metastatic colorectal cancer sensitive to therapies targeting EGFR pathway[J]. J Natl Cancer Inst, 2020, 112(9): 902-912. DOI: 10.1093/jnci/djaa017.
Rizzo S, Bronte G, Fanale D, et al. Prognostic vs predictive molecular biomarkers in colorectal cancer: is KRAS and BRAF wild type status required for anti-EGFR therapy?[J]. Cancer Treat Rev, 2010, 36(Suppl 3): S56-S61. DOI: 10.1016/S0305-7372(10)70021-9.
van Brummelen EMJ, de Boer A, Beijnen JH, et al. BRAF mutations as predictive biomarker for response to anti-EGFR monoclonal antibodies[J]. Oncologist, 2017, 22(7): 864-872. DOI: 10.1634/theoncologist.2017-0031.
Salem ME, Weinberg BA, Xiu J, et al. Comparative molecular analyses of left-sided colon, right-sided colon, and rectal cancers[J]. Oncotarget, 2017, 8(49): 86356-86368. DOI: 10.18632/oncotarget.21169.
Giannini V, Rosati S, Defeudis A, et al. Radiomics predicts response of individual HER2-amplified colorectal cancer liver metastases in patients treated with HER2-targeted therapy[J]. Int J Cancer, 2020, 147(11): 3215-3223. DOI: 10.1002/ijc.33271.
Tsilimigras DI, Ntanasis-Stathopoulos I, Bagante F, et al. Clinical significance and prognostic relevance of KRAS, BRAF, PI3K and TP53 genetic mutation analysis for resectable and unresectable colorectal liver metastases: a systematic review of the current evidence[J]. Surg Oncol, 2018, 27(2): 280-288. DOI: 10.1016/j.suronc.2018.05.012.

PREV Research progress of functional magnetic resonance imaging in evaluating biological behavior of hepatocellular carcinoma
NEXT Progress of MRI in predicting of the tumor response after neoadjuvant chemoradiotherapy for rectal cancer

Tel & Fax: +8610-67113815    E-mail: