Radiogenomics-based Cancer Prognosis in Colorectal Cancer

Overview

Journal Sci Rep

Specialty Science

Date 2019 Jul 7

PMID 31278324

Citations 23

Authors

Bogdan Badic

Mathieu Hatt

Stephanie Durand

Catherine Le Jossic-Corcos

Brigitte Simon

Dimitris Visvikis

Laurent Corcos

Affiliations

Soon will be listed here.

Abstract

Radiogenomics aims at investigating the relationship between imaging radiomic features and gene expression alterations. This study addressed the potential prognostic complementary value of contrast enhanced computed tomography (CE-CT) radiomic features and gene expression data in primary colorectal cancers (CRC). Sixty-four patients underwent CT scans and radiomic features were extracted from the delineated tumor volume. Gene expression analysis of a small set of genes, previously identified as relevant for CRC, was conducted on surgical samples from the same tumors. The relationships between radiomic and gene expression data was assessed using the Kruskal-Wallis test. Multiple testing was not performed, as this was a pilot study. Cox regression was used to identify variables related to overall survival (OS) and progression free survival (PFS). ABCC2 gene expression was correlated with N (p = 0.016) and M stages (p = 0.022). Expression changes of ABCC2, CD166, CDKNV1 and INHBB genes exhibited significant correlations with some radiomic features. OS was associated with Ratio 3D Surface/volume (p = 0.022) and ALDH1A1 expression (p = 0.042), whereas clinical stage (p = 0.004), ABCC2 expression (p = 0.035), and Entropy (p = 0.0031), were prognostic factors for PFS. Combining CE-CT radiomics with gene expression analysis and histopathological examination of primary CRC could provide higher prognostic stratification power, leading to improved patient management.

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References

Tixier F, Hatt M, Rest C, le Pogam A, Corcos L, Visvikis D . Reproducibility of tumor uptake heterogeneity characterization through textural feature analysis in 18F-FDG PET. J Nucl Med. 2012; 53(5):693-700. PMC: 3779464. DOI: 10.2967/jnumed.111.099127. View

Incoronato M, Aiello M, Infante T, Cavaliere C, Grimaldi A, Mirabelli P . Radiogenomic Analysis of Oncological Data: A Technical Survey. Int J Mol Sci. 2017; 18(4). PMC: 5412389. DOI: 10.3390/ijms18040805. View

Candeil L, Gourdier I, Peyron D, Vezzio N, Copois V, Bibeau F . ABCG2 overexpression in colon cancer cells resistant to SN38 and in irinotecan-treated metastases. Int J Cancer. 2004; 109(6):848-54. DOI: 10.1002/ijc.20032. View

Huang Y, Liang C, He L, Tian J, Liang C, Chen X . Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer. J Clin Oncol. 2016; 34(18):2157-64. DOI: 10.1200/JCO.2015.65.9128. View

Ng F, Kozarski R, Ganeshan B, Goh V . Assessment of tumor heterogeneity by CT texture analysis: can the largest cross-sectional area be used as an alternative to whole tumor analysis?. Eur J Radiol. 2012; 82(2):342-8. DOI: 10.1016/j.ejrad.2012.10.023. View

Kahlert C, Gaitzsch E, Steinert G, Mogler C, Herpel E, Hoffmeister M . Expression analysis of aldehyde dehydrogenase 1A1 (ALDH1A1) in colon and rectal cancer in association with prognosis and response to chemotherapy. Ann Surg Oncol. 2012; 19(13):4193-201. DOI: 10.1245/s10434-012-2518-9. View

Liang C, Huang Y, He L, Chen X, Ma Z, Dong D . The development and validation of a CT-based radiomics signature for the preoperative discrimination of stage I-II and stage III-IV colorectal cancer. Oncotarget. 2016; 7(21):31401-12. PMC: 5058766. DOI: 10.18632/oncotarget.8919. View

Leijenaar R, Nalbantov G, Carvalho S, van Elmpt W, Troost E, Boellaard R . The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis. Sci Rep. 2015; 5:11075. PMC: 4525145. DOI: 10.1038/srep11075. View

Aerts H, Velazquez E, Leijenaar R, Parmar C, Grossmann P, Carvalho S . Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014; 5:4006. PMC: 4059926. DOI: 10.1038/ncomms5006. View

10.

Badic B, Desseroit M, Hatt M, Visvikis D . Potential Complementary Value of Noncontrast and Contrast Enhanced CT Radiomics in Colorectal Cancers. Acad Radiol. 2018; 26(4):469-479. DOI: 10.1016/j.acra.2018.06.004. View

11.

Leng Z, Tao K, Xia Q, Tan J, Yue Z, Chen J . Krüppel-like factor 4 acts as an oncogene in colon cancer stem cell-enriched spheroid cells. PLoS One. 2013; 8(2):e56082. PMC: 3572033. DOI: 10.1371/journal.pone.0056082. View

12.

Desseroit M, Visvikis D, Tixier F, Majdoub M, Perdrisot R, Guillevin R . Development of a nomogram combining clinical staging with (18)F-FDG PET/CT image features in non-small-cell lung cancer stage I-III. Eur J Nucl Med Mol Imaging. 2016; 43(8):1477-85. PMC: 5409954. DOI: 10.1007/s00259-016-3325-5. View

13.

Chen J, Xia Q, Jiang B, Chang W, Yuan W, Ma Z . Prognostic Value of Cancer Stem Cell Marker ALDH1 Expression in Colorectal Cancer: A Systematic Review and Meta-Analysis. PLoS One. 2015; 10(12):e0145164. PMC: 4686173. DOI: 10.1371/journal.pone.0145164. View

14.

Wang X, Xia B, Liang Y, Peng L, Wang Z, Zhuo J . Membranous ABCG2 expression in colorectal cancer independently correlates with shortened patient survival. Cancer Biomark. 2013; 13(2):81-8. DOI: 10.3233/CBM-130344. View

15.

Theile D, Grebhardt S, Haefeli W, Weiss J . Involvement of drug transporters in the synergistic action of FOLFOX combination chemotherapy. Biochem Pharmacol. 2009; 78(11):1366-73. DOI: 10.1016/j.bcp.2009.07.006. View

16.

Ganeshan B, Skogen K, Pressney I, Coutroubis D, Miles K . Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: preliminary evidence of an association with tumour metabolism, stage, and survival. Clin Radiol. 2011; 67(2):157-64. DOI: 10.1016/j.crad.2011.08.012. View

17.

Balagurunathan Y, Gu Y, Wang H, Kumar V, Grove O, Hawkins S . Reproducibility and Prognosis of Quantitative Features Extracted from CT Images. Transl Oncol. 2014; 7(1):72-87. PMC: 3998690. DOI: 10.1593/tlo.13844. View

18.

Andersen V, Vogel L, Kopp T, Saebo M, Nonboe A, Hamfjord J . High ABCC2 and low ABCG2 gene expression are early events in the colorectal adenoma-carcinoma sequence. PLoS One. 2015; 10(3):e0119255. PMC: 4368545. DOI: 10.1371/journal.pone.0119255. View

19.

Huang X, Cheng Z, Huang Y, Liang C, He L, Ma Z . CT-based Radiomics Signature to Discriminate High-grade From Low-grade Colorectal Adenocarcinoma. Acad Radiol. 2018; 25(10):1285-1297. DOI: 10.1016/j.acra.2018.01.020. View

20.

Hatt M, Tixier F, Pierce L, Kinahan P, Rest C, Visvikis D . Characterization of PET/CT images using texture analysis: the past, the present… any future?. Eur J Nucl Med Mol Imaging. 2016; 44(1):151-165. PMC: 5283691. DOI: 10.1007/s00259-016-3427-0. View