Development of a novel prognostic score for breast cancer patients using mRNA expression of CHAC1
Abstract
Aim: To develop a prognostic score for primary breast cancer patients integrating conventional predictors and the novel biomarker CHAC1 to aid adjuvant chemotherapy decisions. Patients & methods: A prognostic score for overall survival was developed using: conventional predictors from a dataset of 1777 patients and the weight of CHAC1 mRNA expression from an independent dataset of 106 patients using multivariate Cox regression. Results: The new score includes: CHAC1 mRNA expression, age, tumor size, HER2 neu status, lymph node status and degree of malignancy. Using a cut-off value of 11 score points, 10-year survival was 82% in low-risk (n = 34) and 43% in high-risk patients (n = 72). The addition of CHAC1 resulted in 16% reclassification. Conclusion: Including CHAC1 in prognostic prediction may aid (and change) personalized treatment selection.
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References
1.
Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat. Med. 15(4), 361–387 (1996).
2.
Rogowski W, Payne K, Schnell-Inderst P et al. Concepts of ‘personalization’ in personalized medicine: implications for economic evaluation. Pharmacoeconomics 33(1), 49–59 (2015).
3.
Febbo PG, Ladanyi M, Aldape KD et al. NCCN Task Force report: evaluating the clinical utility of tumor markers in oncology. J. Natl Comp. Canc. Netw. 9(Suppl. 5), S1–S32 (2011).
4.
National Institute for Health and Clinical Excellence. Technology Assessment Report commissioned by the NIHR HTA Programme on behalf of the National Institute for Health and Clinical Excellence – Protocol. Gene expression profiling tests and expanded immunohistochemistry tests to guide selection of chemotherapy regimes in breast cancer management. Final Protocol (2011). www.nice.org.uk/guidance/dg10/documents/gep-and-ihc-tests-for-breast-cancer-assessment-final-protocol2.
5.
Goebel G, Berger R, Strasak AM et al. Elevated mRNA expression of CHAC1 splicing variants is associated with poor outcome for breast and ovarian cancer patients. Br. J. Cancer 106(1), 189–198 (2012).
6.
Scriven P, Brown NJ, Pockley AG, Wyld L. The unfolded protein response and cancer: a brighter future unfolding? J. Mol. Med. (Berl.) 85(4), 331–341 (2007).
7.
Gargalovic PS, Imura M, Zhang B et al. Identification of inflammatory gene modules based on variations of human endothelial cell responses to oxidized lipids. Proc. Natl Acad. Sci. USA 103(34), 12741–12746 (2006).
8.
Mungrue IN, Pagnon J, Kohannim O, Gargalovic PS, Lusis AJ. CHAC1/MGC4504 is a novel proapoptotic component of the unfolded protein response, downstream of the ATF4-ATF3-CHOP cascade. J. Immunol. 182(1), 466–476 (2009).
9.
Fernandez PM, Tabbara SO, Jacobs LK et al. Overexpression of the glucose-regulated stress gene GRP78 in malignant but not benign human breast lesions. Breast Cancer Res. Treat. 59(1), 15–26 (2000).
10.
Scriven P, Coulson S, Haines R, Balasubramanian S, Cross S, Wyld L. Activation and clinical significance of the unfolded protein response in breast cancer. Brit. J. Cancer 101(10), 1692–1698 (2009).
11.
Magne L, Blanc E, Legrand B et al. ATF4 and the integrated stress response are induced by ethanol and cytochrome P450 2E1 in human hepatocytes. J. Hepatol. 54(4), 729–737 (2011).
12.
Galluzzi L, De Santi M, Crinelli R et al. Induction of endoplasmic reticulum stress response by the indole-3-carbinol cyclic tetrameric derivative ctet in human breast cancer cell lines. PLoS ONE 7(8), e43249 (2012).
13.
Joo NE, Ritchie K, Kamarajan P, Miao D, Kapila YL. Nisin, an apoptogenic bacteriocin and food preservative, attenuates HNSCC tumorigenesis via CHAC1. Cancer Med. 1(3), 295–305 (2012).
14.
Tattoli I, Sorbara MT, Vuckovic D et al. Amino acid starvation induced by invasive bacterial pathogens triggers an innate host defense program. Cell Host Microbe 11(6), 563–575 (2012).
15.
Kemmner W, Kessel P, Sanchez-Ruderisch H et al. Loss of UDP-N-acetylglucosamine 2-epimerase/N-acetylmannosamine kinase (GNE) induces apoptotic processes in pancreatic carcinoma cells. FASEB J. 26(2), 938–946 (2012).
16.
Yasuda M, Tanaka Y, Ryu M, Tsuda S, Nakazawa T. RNA sequence reveals mouse retinal transcriptome changes early after axonal injury. PLoS ONE 9(3), e93258 (2014).
17.
Dixon SJ, Patel DN, Welsch M et al. Pharmacological inhibition of cystine-glutamate exchange induces endoplasmic reticulum stress and ferroptosis. eLlife 3, e02523 (2014).
18.
Joo JH, Ueda E, Bortner CD, Yang XP, Liao G, Jetten AM. Farnesol activates the intrinsic pathway of apoptosis and the ATF4-ATF3-CHOP cascade of ER stress in human T lymphoblastic leukemia Molt4 cells. Biochem. Pharmacol. 97(3), 256–268 (2015).
19.
Kimura K, Huang RC. Tetra-O-methyl nordihydroguaiaretic acid broadly suppresses cancer metabolism and synergistically induces strong anticancer activity in combination with etoposide, rapamycin and UCN-01. PLoS ONE 11(2), e0148685 (2016).
20.
Selvik L-KM, Fjeldbo CS, Flatberg A et al. The duration of gastrin treatment affects global gene expression and molecular responses involved in ER stress and anti-apoptosis. BMC Genomics 14(1), 429 (2013).
21.
Bieche I, Onody P, Laurendeau I et al. Real-time reverse transcription-PCR assay for future management of ERBB2-based clinical applications. Clin. Chem. 45(8 Pt 1), 1148–1156 (1999).
22.
Hosmer DW, Lemeshow S. Applied Logistic Regression. Wiley, NY, USA (2000).
23.
Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code Biol. Med. 3, 17 (2008).
24.
Camp RL, Dolled-Filhart M, Rimm DL. X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization. Clin. Cancer Res. 10(21), 7252–7259 (2004).
25.
Paulden M, Franek J, Pham B, Bedard PL, Trudeau M, Krahn M. Cost-effectiveness of the 21-gene assay for guiding adjuvant chemotherapy decisions in early breast cancer. Value Health 16, 729–739 (2013).
26.
Tsoi DT, Inoue M, Kelly CM, Verma S, Pritchard KI. Cost-effectiveness analysis of recurrence score-guided treatment using a 21-gene assay in early breast cancer. Oncologist 15(5), 457–465 (2010).
27.
Lyman GH, Cosler LE, Kuderer NM, Hornberger J. Impact of a 21-gene RT-PCR assay on treatment decisions in early-stage breast cancer: an economic analysis based on prognostic and predictive validation studies. Cancer 109(6), 1011–1018 (2007).
28.
Hornberger J, Cosler LE, Lyman GH. Economic analysis of targeting chemotherapy using a 21-gene RT-PCR assay in lymph-node-negative, estrogen-receptor-positive, early-stage breast cancer. Am. J. Manag. Care 11(5), 313–324 (2005).
29.
Adjuvant! Online, Inc. Decision making tools for health care professionals. www.adjuvantonline.com/index.jsp.
30.
Haybittle JL, Blamey RW, Elston CW et al. A prognostic index in primary breast cancer. Br. J. Cancer 45(3), 361–366 (1982).
31.
Todd JH, Dowle C, Williams MR et al. Confirmation of a prognostic index in primary breast cancer. Br. J. Cancer 56(4), 489–492 (1987).
32.
Fisher ER, Anderson S, Tan-Chiu E, Fisher B, Eaton L, Wolmark N. Fifteen-year prognostic discriminants for invasive breast carcinoma: National Surgical Adjuvant Breast and Bowel Project Protocol-06. Cancer 91(Suppl. 8), 1679–1687 (2001).
33.
Soerjomataram I, Louwman MW, Ribot JG, Roukema JA, Coebergh JW. An overview of prognostic factors for long-term survivors of breast cancer. Breast Cancer Res. Treat. 107(3), 309–330 (2008).
34.
Paredes-Aracil E, Palazon-Bru A, Folgado-de la Rosa DM, Ots-Gutierrez JR, Compan-Rosique AF, Gil-Guillen VF. A scoring system to predict breast cancer mortality at 5 and 10 years. Sci. Rep. 7(1), 415 (2017).
35.
McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM. Reporting recommendations for tumor marker prognostic studies (REMARK). J. Natl Cancer Inst. 97(16), 1180–1184 (2005).
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Published online: 19 September 2017
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Development of a novel prognostic score for breast cancer patients using mRNA expression of CHAC1
. (2017) Journal of Comparative Effectiveness Research. DOI: 10.2217/cer-2017-0015
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