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BMC Cancer
Published in: BMC Cancer 1/2017

Open Access 01-12-2017 | Research article

A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer

Authors: Bangrong Cao, Liping Luo, Lin Feng, Shiqi Ma, Tingqing Chen, Yuan Ren, Xiao Zha, Shujun Cheng, Kaitai Zhang, Changmin Chen

Published in: BMC Cancer | Issue 1/2017

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Abstract

Background

The clinical benefit of adjuvant chemotherapy for stage II colorectal cancer (CRC) is controversial. This study aimed to explore novel gene signature to predict outcome benefit of postoperative 5-Fu-based therapy in stage II CRC.

Methods

Gene-expression profiles of stage II CRCs from two datasets with 5-Fu-based adjuvant chemotherapy (training dataset, n = 212; validation dataset, n = 85) were analyzed to identify the indicator. A systemic approach by integrating gene-expression and protein-protein interaction (PPI) network was implemented to develop the predictive signature. Kaplan-Meier curves and Cox proportional hazards model were used to determine the survival benefit of adjuvant chemotherapy. Experiments with shRNA knock-down were carried out to confirm the signature identified in this study.

Results

In the training dataset, we identified 44 PPI sub-modules, by which we separate patients into two clusters (1 and 2) having different chemotherapeutic benefit. A predictor of 11 PPI sub-modules (11-PPI-Mod) was established to discriminate the two sub-groups, with an overall accuracy of 90.1%. This signature was independently validated in an external validation dataset. Kaplan-Meier curves showed an improved outcome for patients who received adjuvant chemotherapy in Cluster 1 sub-group, but even worse survival for those in Cluster 2 sub-group. Similar results were found in both the training and the validation dataset. Multivariate Cox regression revealed an interaction effect between 11-PPI-Mod signature and adjuvant therapy treatment in the training dataset (RFS, p = 0.007; OS, p = 0.006) and the validation dataset (RFS, p = 0.002). From the signature, we found that PTGES gene was up-regulated in CRC cells which were more resistant to 5-Fu. Knock-down of PTGES indicated a growth inhibition and up-regulation of apoptotic markers induced by 5-Fu in CRC cells.

Conclusions

Only a small proportion of stage II CRC patients could benefit from adjuvant therapy. The 11-PPI-Mod as a potential predictor could be helpful to distinguish this sub-group with favorable outcome.
Appendix
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Literature
1.
Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ, He J. Cancer statistics in China, 2015. CA Cancer J Clin. 2016;66(2):115–32.CrossRefPubMed
2.
Wang Y, Jatkoe T, Zhang Y, Mutch MG, Talantov D, Jiang J, McLeod HL, Atkins D. Gene expression profiles and molecular markers to predict recurrence of Dukes’ B colon cancer. J Clin Oncol. 2004;22(9):1564–71.CrossRefPubMed
3.
Andre T, Boni C, Mounedji-Boudiaf L, Navarro M, Tabernero J, Hickish T, Topham C, Zaninelli M, Clingan P, Bridgewater J, et al. Oxaliplatin, fluorouracil, and leucovorin as adjuvant treatment for colon cancer. N Engl J Med. 2004;350(23):2343–51.CrossRefPubMed
4.
Moertel CG, Fleming TR, Macdonald JS, Haller DG, Laurie JA, Goodman PJ, Ungerleider JS, Emerson WA, Tormey DC, Glick JH, et al. Levamisole and fluorouracil for adjuvant therapy of resected colon carcinoma. N Engl J Med. 1990;322(6):352–8.CrossRefPubMed
5.
6.
Graziano F, Cascinu S. Prognostic molecular markers for planning adjuvant chemotherapy trials in Dukes’ B colorectal cancer patients: how much evidence is enough? Ann Oncol. 2003;14(7):1026–38.CrossRefPubMed
7.
Kelley RK, Venook AP. Prognostic and predictive markers in stage II colon cancer: is there a role for gene expression profiling? Clin Colorectal Cancer. 2011;10(2):73–80.CrossRefPubMedPubMedCentral
8.
Ribic CM, Sargent DJ, Moore MJ, Thibodeau SN, French AJ, Goldberg RM, Hamilton SR, Laurent-Puig P, Gryfe R, Shepherd LE, et al. Tumor microsatellite-instability status as a predictor of benefit from fluorouracil-based adjuvant chemotherapy for colon cancer. N Engl J Med. 2003;349(3):247–57.CrossRefPubMedPubMedCentral
9.
Sargent DJ, Marsoni S, Monges G, Thibodeau SN, Labianca R, Hamilton SR, French AJ, Kabat B, Foster NR, Torri V, et al. Defective mismatch repair as a predictive marker for lack of efficacy of fluorouracil-based adjuvant therapy in colon cancer. J Clin Oncol. 2010;28(20):3219–26.CrossRefPubMedPubMedCentral
10.
Gray R, Barnwell J, McConkey C, Hills RK, Williams NS, Kerr DJ. Adjuvant chemotherapy versus observation in patients with colorectal cancer: a randomised study. Lancet. 2007;370(9604):2020–9.CrossRefPubMed
11.
Hutchins G, Southward K, Handley K, Magill L, Beaumont C, Stahlschmidt J, Richman S, Chambers P, Seymour M, Kerr D, et al. Value of mismatch repair, KRAS, and BRAF mutations in predicting recurrence and benefits from chemotherapy in colorectal cancer. J Clin Oncol. 2011;29(10):1261–70.CrossRefPubMed
12.
Bandres E, Malumbres R, Cubedo E, Honorato B, Zarate R, Labarga A, Gabisu U, Sola JJ, Garcia-Foncillas J. A gene signature of 8 genes could identify the risk of recurrence and progression in Dukes’ B colon cancer patients. Oncol Rep. 2007;17(5):1089–94.PubMed
13.
Barrier A, Boelle PY, Roser F, Gregg J, Tse C, Brault D, Lacaine F, Houry S, Huguier M, Franc B, et al. Stage II colon cancer prognosis prediction by tumor gene expression profiling. J Clin Oncol. 2006;24(29):4685–91.CrossRefPubMed
14.
Eschrich S, Yang I, Bloom G, Kwong KY, Boulware D, Cantor A, Coppola D, Kruhoffer M, Aaltonen L, Orntoft TF, et al. Molecular staging for survival prediction of colorectal cancer patients. J Clin Oncol. 2005;23(15):3526–35.CrossRefPubMed
15.
Marisa L, de Reynies A, Duval A, Selves J, Gaub MP, Vescovo L, Etienne-Grimaldi MC, Schiappa R, Guenot D, Ayadi M, et al. Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value. PLoS Med. 2013;10(5):e1001453.CrossRefPubMedPubMedCentral
16.
Chen J, Sam L, Huang Y, Lee Y, Li J, Liu Y, Xing HR, Lussier YA. Protein interaction network underpins concordant prognosis among heterogeneous breast cancer signatures. J Biomed Inform. 2010;43(3):385–96.CrossRefPubMedPubMedCentral
17.
18.
Xin J, Ren X, Chen L, Wang Y. Identifying network biomarkers based on protein-protein interactions and expression data. BMC Med Genet. 2015;8(Suppl 2):S11.
19.
Zeng T, Sun SY, Wang Y, Zhu H, Chen L. Network biomarkers reveal dysfunctional gene regulations during disease progression. FEBS J. 2013;280(22):5682–95.CrossRefPubMed
20.
Peri S, Navarro JD, Kristiansen TZ, Amanchy R, Surendranath V, Muthusamy B, Gandhi TK, Chandrika KN, Deshpande N, Suresh S, et al. Human protein reference database as a discovery resource for proteomics. Nucleic Acids Res. 2004;32(Database issue):D497–501.CrossRefPubMedPubMedCentral
21.
Jorissen RN, Gibbs P, Christie M, Prakash S, Lipton L, Desai J, Kerr D, Aaltonen LA, Arango D, Kruhoffer M, et al. Metastasis-associated gene expression changes predict poor outcomes in patients with dukes stage B and C colorectal cancer. Clin Cancer Res. 2009;15(24):7642–51.CrossRefPubMedPubMedCentral
22.
Keshava Prasad TS, Goel R, Kandasamy K, Keerthikumar S, Kumar S, Mathivanan S, Telikicherla D, Raju R, Shafreen B, Venugopal A, et al. Human protein reference database--2009 update. Nucleic Acids Res. 2009;37(Database issue):D767–72.CrossRefPubMed
23.
24.
Langfelder P, Zhang B, Horvath S. Defining clusters from a hierarchical cluster tree: the dynamic tree cut package for R. Bioinformatics. 2008;24(5):719–20.CrossRefPubMed
25.
26.
Hochberg YBaY: Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc 1995, 57:289-300.
27.
28.
Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez JC, Muller M. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12:77.CrossRefPubMedPubMedCentral
29.
Huang da W, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009;37(1):1–13.CrossRefPubMed
30.
Huang da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57.CrossRefPubMed
31.
Ma SQ, Cao BR, Zhang H, Luo LP, Ren Y, Hu T, Chen CM. The lack of Raf-1 kinase feedback regulation enhances antiapoptosis in cancer cells. Oncogene. 2017;36(14):2014–22.CrossRefPubMed
32.
Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) method. Methods. 2001;25(4):402–8.CrossRefPubMed
33.
Sinicrope FA, Foster NR, Yoon HH, Smyrk TC, Kim GP, Allegra CJ, Yothers G, Nikcevich DA, Sargent DJ. Association of obesity with DNA mismatch repair status and clinical outcome in patients with stage II or III colon carcinoma participating in NCCTG and NSABP adjuvant chemotherapy trials. J Clin Oncol. 2012;30(4):406–12.CrossRefPubMed
34.
Fluge O, Gravdal K, Carlsen E, Vonen B, Kjellevold K, Refsum S, Lilleng R, Eide TJ, Halvorsen TB, Tveit KM, et al. Expression of EZH2 and Ki-67 in colorectal cancer and associations with treatment response and prognosis. Br J Cancer. 2009;101(8):1282–9.CrossRefPubMedPubMedCentral
35.
Myklebust MP, Li Z, Tran TH, Rui H, Knudsen ES, Elsaleh H, Fluge O, Vonen B, Myrvold HE, Leh S, et al. Expression of cyclin D1a and D1b as predictive factors for treatment response in colorectal cancer. Br J Cancer. 2012;107(10):1684–91.CrossRefPubMedPubMedCentral
36.
Ma Y, Ren Y, Han EQ, Li H, Chen D, Jacobs JJ, Gitelis S, O'Keefe RJ, Konttinen YT, Yin G, et al. Inhibition of the Wnt-beta-catenin and Notch signaling pathways sensitizes osteosarcoma cells to chemotherapy. Biochem Biophys Res Commun. 2013;431(2):274–9.CrossRefPubMedPubMedCentral
37.
Wei Y, Shen N, Wang Z, Yang G, Yi B, Yang N, Qiu Y, Lu J. Sorafenib sensitizes hepatocellular carcinoma cell to cisplatin via suppression of Wnt/beta-catenin signaling. Mol Cell Biochem. 2013;381(1–2):139–44.CrossRefPubMed
38.
Lien WH, Polak L, Lin M, Lay K, Zheng D, Fuchs E. In vivo transcriptional governance of hair follicle stem cells by canonical Wnt regulators. Nat Cell Biol. 2014;16(2):179–90.CrossRefPubMedPubMedCentral
39.
Hsu HC, Liu YS, Tseng KC, Hsu CL, Liang Y, Yang TS, Chen JS, Tang RP, Chen SJ, Chen HC. Overexpression of Lgr5 correlates with resistance to 5-FU-based chemotherapy in colorectal cancer. Int J Color Dis. 2013;28(11):1535–46.CrossRef
40.
Shikina A, Shinto E, Hashiguchi Y, Ueno H, Naito Y, Okamoto K, Kubo T, Fukazawa S, Yamamoto J, Hase K. Differential clinical benefits of 5-fluorouracil-based adjuvant chemotherapy for patients with stage III colorectal cancer according to CD133 expression status. Jpn J Clin Oncol. 2014;44(1):42–8.CrossRefPubMed
41.
Wang MT, Honn KV, Nie D. Cyclooxygenases, prostanoids, and tumor progression. Cancer Metastasis Rev. 2007;26(3–4):525–34.CrossRefPubMed
42.
Sinicrope FA, Gill S. Role of cyclooxygenase-2 in colorectal cancer. Cancer Metastasis Rev. 2004;23(1–2):63–75.CrossRefPubMed
43.
Kim SH, Hashimoto Y, Cho SN, Roszik J, Milton DR, Dal F, Kim SF, Menter DG, Yang P, Ekmekcioglu S, et al. Microsomal PGE2 synthase-1 regulates melanoma cell survival and associates with melanoma disease progression. Pigment Cell Melanoma Res. 2016;29(3):297–308.CrossRefPubMedPubMedCentral
44.
45.
Mattila S, Tuominen H, Koivukangas J, Stenback F. The terminal prostaglandin synthases mPGES-1, mPGES-2, and cPGES are all overexpressed in human gliomas. Neuropathology. 2009;29(2):156–65.CrossRefPubMed
46.
Seo T, Tatsuguchi A, Shinji S, Yonezawa M, Mitsui K, Tanaka S, Fujimori S, Gudis K, Fukuda Y, Sakamoto C. Microsomal prostaglandin E synthase protein levels correlate with prognosis in colorectal cancer patients. Virchows Arch. 2009;454(6):667–76.CrossRefPubMed
47.
Lee JJ, Natsuizaka M, Ohashi S, Wong GS, Takaoka M, Michaylira CZ, Budo D, Tobias JW, Kanai M, Shirakawa Y, et al. Hypoxia activates the cyclooxygenase-2-prostaglandin E synthase axis. Carcinogenesis. 2010;31(3):427–34.CrossRefPubMed
48.
Doktorova H, Hrabeta J, Khalil MA, Eckschlager T. Hypoxia-induced chemoresistance in cancer cells: the role of not only HIF-1. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2015;159(2):166–77.PubMed
49.
Wen YA, Stevens PD, Gasser ML, Andrei R, Gao T. Downregulation of PHLPP expression contributes to hypoxia-induced resistance to chemotherapy in colon cancer cells. Mol Cell Biol. 2013;33(22):4594–605.CrossRefPubMedPubMedCentral
50.
Metadata
Title
A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer
Authors
Bangrong Cao
Liping Luo
Lin Feng
Shiqi Ma
Tingqing Chen
Yuan Ren
Xiao Zha
Shujun Cheng
Kaitai Zhang
Changmin Chen
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2017
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-017-3821-4

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